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Author SHA1 Message Date
greatmengqi 228a2a66e3 fix(actor): harden lifecycle, supervision, Redis mailbox, and add comprehensive tests
- Fix spawn() zombie cell: clean up registry on start() failure
- Fix shutdown(): cancel + await tasks that exceed graceful timeout
- Fix _shutdown(): await mailbox.close() to release backend resources
- Fix escalate directive: stop failing child before propagating to grandparent
- Fix RedisMailbox.put(): wrap Redis errors in try/except, return False on failure
- Fix retry.py: replace assert with proper raise for last_exc
- Add put_batch() to Mailbox abstraction for single-roundtrip bulk enqueue
- Add RedisMailbox.put_batch() with atomic Lua script for bounded queues
- Add MailboxFullError exception type for semantic backpressure handling
- Add redis>=7.4.0 dependency with public PyPI sources in uv.lock

Tests added (31 total, up from 27):
- test_middleware_on_restart_hook: verifies middleware.on_restart() on supervision restart
- test_ask_propagates_actor_exception: ask() re-raises original exception type
- test_ask_propagates_exception_while_supervised: exception propagates; root actor survives
- test_ask_timeout_late_reply_no_exception: late reply after timeout is silent no-op
- test_actor_backpressure.py: MailboxFullError + dead letter on full mailbox
- test_actor_retry.py: ask_with_retry with exponential backoff
- test_mailbox_redis.py: RedisMailbox put/get/batch/close
- bench_actor_redis.py: RedisMailbox throughput benchmarks
2026-03-31 10:09:05 +08:00
greatmengqi 3e17417122 feat: asyncio-native Actor framework with supervision, middleware, and pluggable mailbox
Lightweight actor library built on asyncio primitives (~800 lines):

- Actor base class with lifecycle hooks (on_started/on_stopped/on_restart)
- ActorRef with tell (fire-and-forget) and ask (request-response)
- Supervision: OneForOne/AllForOne strategies with restart limits
- Middleware pipeline for cross-cutting concerns
- Pluggable Mailbox interface (MemoryMailbox default, RedisMailbox optional)
- ReplyRegistry + ReplyChannel: ask() works across any mailbox backend
- System-level thread pool for blocking I/O (run_in_executor)
- Dead letter handling, poison message quarantine, parallel shutdown
- 22 tests + benchmark suite
2026-03-30 23:50:54 +08:00
678 changed files with 11913 additions and 71115 deletions
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---
name: smoke-test
description: End-to-end smoke test skill for DeerFlow. Guides through: 1) Pulling latest code, 2) Docker OR Local installation and deployment (user preference, default to Local if Docker network issues), 3) Service availability verification, 4) Health check, 5) Final test report. Use when the user says "run smoke test", "smoke test deployment", "verify installation", "test service availability", "end-to-end test", or similar.
---
# DeerFlow Smoke Test Skill
This skill guides the Agent through DeerFlow's full end-to-end smoke test workflow, including code updates, deployment (supporting both Docker and local installation modes), service availability verification, and health checks.
## Deployment Mode Selection
This skill supports two deployment modes:
- **Local installation mode** (recommended, especially when network issues occur) - Run all services directly on the local machine
- **Docker mode** - Run all services inside Docker containers
**Selection strategy**:
- If the user explicitly asks for Docker mode, use Docker
- If network issues occur (such as slow image pulls), automatically switch to local mode
- Default to local mode whenever possible
## Structure
```
smoke-test/
├── SKILL.md ← You are here - core workflow and logic
├── scripts/
│ ├── check_docker.sh ← Check the Docker environment
│ ├── check_local_env.sh ← Check local environment dependencies
│ ├── frontend_check.sh ← Frontend page smoke check
│ ├── pull_code.sh ← Pull the latest code
│ ├── deploy_docker.sh ← Docker deployment
│ ├── deploy_local.sh ← Local deployment
│ └── health_check.sh ← Service health check
├── references/
│ ├── SOP.md ← Standard operating procedure
│ └── troubleshooting.md ← Troubleshooting guide
└── templates/
├── report.local.template.md ← Local mode smoke test report template
└── report.docker.template.md ← Docker mode smoke test report template
```
## Standard Operating Procedure (SOP)
### Phase 1: Code Update Check
1. **Confirm current directory** - Verify that the current working directory is the DeerFlow project root
2. **Check Git status** - See whether there are uncommitted changes
3. **Pull the latest code** - Use `git pull origin main` to get the latest updates
4. **Confirm code update** - Verify that the latest code was pulled successfully
### Phase 2: Deployment Mode Selection and Environment Check
**Choose deployment mode**:
- Ask for user preference, or choose automatically based on network conditions
- Default to local installation mode
**Local mode environment check**:
1. **Check Node.js version** - Requires 22+
2. **Check pnpm** - Package manager
3. **Check uv** - Python package manager
4. **Check nginx** - Reverse proxy
5. **Check required ports** - Confirm that ports 2026, 3000, 8001, and 2024 are not occupied
**Docker mode environment check** (if Docker is selected):
1. **Check whether Docker is installed** - Run `docker --version`
2. **Check Docker daemon status** - Run `docker info`
3. **Check Docker Compose availability** - Run `docker compose version`
4. **Check required ports** - Confirm that port 2026 is not occupied
### Phase 3: Configuration Preparation
1. **Check whether config.yaml exists**
- If it does not exist, run `make config` to generate it
- If it already exists, check whether it needs an upgrade with `make config-upgrade`
2. **Check the .env file**
- Verify that required environment variables are configured
- Especially model API keys such as `OPENAI_API_KEY`
### Phase 4: Deployment Execution
**Local mode deployment**:
1. **Check dependencies** - Run `make check`
2. **Install dependencies** - Run `make install`
3. **(Optional) Pre-pull the sandbox image** - If needed, run `make setup-sandbox`
4. **Start services** - Run `make dev-daemon` (background mode, recommended) or `make dev` (foreground mode)
5. **Wait for startup** - Give all services enough time to start completely (90-120 seconds recommended)
**Docker mode deployment** (if Docker is selected):
1. **Initialize Docker environment** - Run `make docker-init`
2. **Start Docker services** - Run `make docker-start`
3. **Wait for startup** - Give all containers enough time to start completely (60 seconds recommended)
### Phase 5: Service Health Check
**Local mode health check**:
1. **Check process status** - Confirm that LangGraph, Gateway, Frontend, and Nginx processes are all running
2. **Check frontend service** - Visit `http://localhost:2026` and verify that the page loads
3. **Check API Gateway** - Verify the `http://localhost:2026/health` endpoint
4. **Check LangGraph service** - Verify the availability of relevant endpoints
5. **Frontend route smoke check** - Run `bash .agent/skills/smoke-test/scripts/frontend_check.sh` to verify key routes under `/workspace`
**Docker mode health check** (when using Docker):
1. **Check container status** - Run `docker ps` and confirm that all containers are running
2. **Check frontend service** - Visit `http://localhost:2026` and verify that the page loads
3. **Check API Gateway** - Verify the `http://localhost:2026/health` endpoint
4. **Check LangGraph service** - Verify the availability of relevant endpoints
5. **Frontend route smoke check** - Run `bash .agent/skills/smoke-test/scripts/frontend_check.sh` to verify key routes under `/workspace`
### Optional Functional Verification
1. **List available models** - Verify that model configuration loads correctly
2. **List available skills** - Verify that the skill directory is mounted correctly
3. **Simple chat test** - Send a simple message to verify the end-to-end flow
### Phase 6: Generate Test Report
1. **Collect all test results** - Summarize execution status for each phase
2. **Record encountered issues** - If anything fails, record the error details
3. **Generate the final report** - Use the template that matches the selected deployment mode to create the complete test report, including overall conclusion, detailed key test cases, and explicit frontend page / route results
4. **Provide follow-up recommendations** - Offer suggestions based on the test results
## Execution Rules
- **Follow the sequence** - Execute strictly in the order described above
- **Idempotency** - Every step should be safe to repeat
- **Error handling** - If a step fails, stop and report the issue, then provide troubleshooting suggestions
- **Detailed logging** - Record the execution result and status of each step
- **User confirmation** - Ask for confirmation before potentially risky operations such as overwriting config
- **Mode preference** - Prefer local mode to avoid network-related issues
- **Template requirement** - The final report must use the matching template under `templates/`; do not output a free-form summary instead of the template-based report
- **Report clarity** - The execution summary must include the overall pass/fail conclusion plus per-case result explanations, and frontend smoke check results must be listed explicitly in the report
- **Optional phase handling** - If functional verification is not executed, do not present it as a separate skipped phase in the final report
## Known Acceptable Warnings
The following warnings can appear during smoke testing and do not block a successful result:
- Feishu/Lark SSL errors in Gateway logs (certificate verification failure) can be ignored if that channel is not enabled
- Warnings in LangGraph logs about missing methods in the custom checkpointer, such as `adelete_for_runs` or `aprune`, do not affect the core functionality
## Key Tools
Use the following tools during execution:
1. **bash** - Run shell commands
2. **present_file** - Show generated reports and important files
3. **task_tool** - Organize complex steps with subtasks when needed
## Success Criteria
Smoke test pass criteria (local mode):
- [x] Latest code is pulled successfully
- [x] Local environment check passes (Node.js 22+, pnpm, uv, nginx)
- [x] Configuration files are set up correctly
- [x] `make check` passes
- [x] `make install` completes successfully
- [x] `make dev` starts successfully
- [x] All service processes run normally
- [x] Frontend page is accessible
- [x] Frontend route smoke check passes (`/workspace` key routes)
- [x] API Gateway health check passes
- [x] Test report is generated completely
Smoke test pass criteria (Docker mode):
- [x] Latest code is pulled successfully
- [x] Docker environment check passes
- [x] Configuration files are set up correctly
- [x] `make docker-init` completes successfully
- [x] `make docker-start` completes successfully
- [x] All Docker containers run normally
- [x] Frontend page is accessible
- [x] Frontend route smoke check passes (`/workspace` key routes)
- [x] API Gateway health check passes
- [x] Test report is generated completely
## Read Reference Files
Before starting execution, read the following reference files:
1. `references/SOP.md` - Detailed step-by-step operating instructions
2. `references/troubleshooting.md` - Common issues and solutions
3. `templates/report.local.template.md` - Local mode test report template
4. `templates/report.docker.template.md` - Docker mode test report template
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# DeerFlow Smoke Test Standard Operating Procedure (SOP)
This document describes the detailed operating steps for each phase of the DeerFlow smoke test.
## Phase 1: Code Update Check
### 1.1 Confirm Current Directory
**Objective**: Verify that the current working directory is the DeerFlow project root.
**Steps**:
1. Run `pwd` to view the current working directory
2. Check whether the directory contains the following files/directories:
- `Makefile`
- `backend/`
- `frontend/`
- `config.example.yaml`
**Success Criteria**: The current directory contains all of the files/directories listed above.
---
### 1.2 Check Git Status
**Objective**: Check whether there are uncommitted changes.
**Steps**:
1. Run `git status`
2. Check whether the output includes "Changes not staged for commit" or "Untracked files"
**Notes**:
- If there are uncommitted changes, recommend that the user commit or stash them first to avoid conflicts while pulling
- If the user confirms that they want to continue, this step can be skipped
---
### 1.3 Pull the Latest Code
**Objective**: Fetch the latest code updates.
**Steps**:
1. Run `git fetch origin main`
2. Run `git pull origin main`
**Success Criteria**:
- The commands succeed without errors
- The output shows "Already up to date" or indicates that new commits were pulled successfully
---
### 1.4 Confirm Code Update
**Objective**: Verify that the latest code was pulled successfully.
**Steps**:
1. Run `git log -1 --oneline` to view the latest commit
2. Record the commit hash and message
---
## Phase 2: Deployment Mode Selection and Environment Check
### 2.1 Choose Deployment Mode
**Objective**: Decide whether to use local mode or Docker mode.
**Decision Flow**:
1. Prefer local mode first to avoid network-related issues
2. If the user explicitly requests Docker, use Docker
3. If Docker network issues occur, switch to local mode automatically
---
### 2.2 Local Mode Environment Check
**Objective**: Verify that local development environment dependencies are satisfied.
#### 2.2.1 Check Node.js Version
**Steps**:
1. If nvm is used, run `nvm use 22` to switch to Node 22+
2. Run `node --version`
**Success Criteria**: Version >= 22.x
**Failure Handling**:
- If the version is too low, ask the user to install/switch Node.js with nvm:
```bash
nvm install 22
nvm use 22
```
- Or install it from the official website: https://nodejs.org/
---
#### 2.2.2 Check pnpm
**Steps**:
1. Run `pnpm --version`
**Success Criteria**: The command returns pnpm version information.
**Failure Handling**:
- If pnpm is not installed, ask the user to install it with `npm install -g pnpm`
---
#### 2.2.3 Check uv
**Steps**:
1. Run `uv --version`
**Success Criteria**: The command returns uv version information.
**Failure Handling**:
- If uv is not installed, ask the user to install uv
---
#### 2.2.4 Check nginx
**Steps**:
1. Run `nginx -v`
**Success Criteria**: The command returns nginx version information.
**Failure Handling**:
- macOS: install with Homebrew using `brew install nginx`
- Linux: install using the system package manager
---
#### 2.2.5 Check Required Ports
**Steps**:
1. Run the following commands to check ports:
```bash
lsof -i :2026 # Main port
lsof -i :3000 # Frontend
lsof -i :8001 # Gateway
lsof -i :2024 # LangGraph
```
**Success Criteria**: All ports are free, or they are occupied only by DeerFlow-related processes.
**Failure Handling**:
- If a port is occupied, ask the user to stop the related process
---
### 2.3 Docker Mode Environment Check (If Docker Is Selected)
#### 2.3.1 Check Whether Docker Is Installed
**Steps**:
1. Run `docker --version`
**Success Criteria**: The command returns Docker version information, such as "Docker version 24.x.x".
---
#### 2.3.2 Check Docker Daemon Status
**Steps**:
1. Run `docker info`
**Success Criteria**: The command runs successfully and shows Docker system information.
**Failure Handling**:
- If it fails, ask the user to start Docker Desktop or the Docker service
---
#### 2.3.3 Check Docker Compose Availability
**Steps**:
1. Run `docker compose version`
**Success Criteria**: The command returns Docker Compose version information.
---
#### 2.3.4 Check Required Ports
**Steps**:
1. Run `lsof -i :2026` (macOS/Linux) or `netstat -ano | findstr :2026` (Windows)
**Success Criteria**: Port 2026 is free, or it is occupied only by a DeerFlow-related process.
**Failure Handling**:
- If the port is occupied by another process, ask the user to stop that process or change the configuration
---
## Phase 3: Configuration Preparation
### 3.1 Check config.yaml
**Steps**:
1. Check whether `config.yaml` exists
2. If it does not exist, run `make config`
3. If it already exists, consider running `make config-upgrade` to merge new fields
**Validation**:
- Check whether at least one model is configured in config.yaml
- Check whether the model configuration references the correct environment variables
---
### 3.2 Check the .env File
**Steps**:
1. Check whether the `.env` file exists
2. If it does not exist, copy it from `.env.example`
3. Check whether the following environment variables are configured:
- `OPENAI_API_KEY` (or other model API keys)
- Other required settings
---
## Phase 4: Deployment Execution
### 4.1 Local Mode Deployment
#### 4.1.1 Check Dependencies
**Steps**:
1. Run `make check`
**Description**: This command validates all required tools (Node.js 22+, pnpm, uv, nginx).
---
#### 4.1.2 Install Dependencies
**Steps**:
1. Run `make install`
**Description**: This command installs both backend and frontend dependencies.
**Notes**:
- This step may take some time
- If network issues cause failures, try using a closer or mirrored package registry
---
#### 4.1.3 (Optional) Pre-pull the Sandbox Image
**Steps**:
1. If Docker / Container sandbox is used, run `make setup-sandbox`
**Description**: This step is optional and not needed for local sandbox mode.
---
#### 4.1.4 Start Services
**Steps**:
1. Run `make dev-daemon` (background mode)
**Description**: This command starts all services (LangGraph, Gateway, Frontend, Nginx).
**Notes**:
- `make dev` runs in the foreground and stops with Ctrl+C
- `make dev-daemon` runs in the background
- Use `make stop` to stop services
---
#### 4.1.5 Wait for Services to Start
**Steps**:
1. Wait 90-120 seconds for all services to start completely
2. You can monitor startup progress by checking these log files:
- `logs/langgraph.log`
- `logs/gateway.log`
- `logs/frontend.log`
- `logs/nginx.log`
---
### 4.2 Docker Mode Deployment (If Docker Is Selected)
#### 4.2.1 Initialize the Docker Environment
**Steps**:
1. Run `make docker-init`
**Description**: This command pulls the sandbox image if needed.
---
#### 4.2.2 Start Docker Services
**Steps**:
1. Run `make docker-start`
**Description**: This command builds and starts all required Docker containers.
---
#### 4.2.3 Wait for Services to Start
**Steps**:
1. Wait 60-90 seconds for all services to start completely
2. You can run `make docker-logs` to monitor startup progress
---
## Phase 5: Service Health Check
### 5.1 Local Mode Health Check
#### 5.1.1 Check Process Status
**Steps**:
1. Run the following command to check processes:
```bash
ps aux | grep -E "(langgraph|uvicorn|next|nginx)" | grep -v grep
```
**Success Criteria**: Confirm that the following processes are running:
- LangGraph (`langgraph dev`)
- Gateway (`uvicorn app.gateway.app:app`)
- Frontend (`next dev` or `next start`)
- Nginx (`nginx`)
---
#### 5.1.2 Check Frontend Service
**Steps**:
1. Use curl or a browser to visit `http://localhost:2026`
2. Verify that the page loads normally
**Example curl command**:
```bash
curl -I http://localhost:2026
```
**Success Criteria**: Returns an HTTP 200 status code.
---
#### 5.1.3 Check API Gateway
**Steps**:
1. Visit `http://localhost:2026/health`
**Example curl command**:
```bash
curl http://localhost:2026/health
```
**Success Criteria**: Returns health status JSON.
---
#### 5.1.4 Check LangGraph Service
**Steps**:
1. Visit relevant LangGraph endpoints to verify availability
---
### 5.2 Docker Mode Health Check (When Using Docker)
#### 5.2.1 Check Container Status
**Steps**:
1. Run `docker ps`
2. Confirm that the following containers are running:
- `deer-flow-nginx`
- `deer-flow-frontend`
- `deer-flow-gateway`
- `deer-flow-langgraph` (if not in gateway mode)
---
#### 5.2.2 Check Frontend Service
**Steps**:
1. Use curl or a browser to visit `http://localhost:2026`
2. Verify that the page loads normally
**Example curl command**:
```bash
curl -I http://localhost:2026
```
**Success Criteria**: Returns an HTTP 200 status code.
---
#### 5.2.3 Check API Gateway
**Steps**:
1. Visit `http://localhost:2026/health`
**Example curl command**:
```bash
curl http://localhost:2026/health
```
**Success Criteria**: Returns health status JSON.
---
#### 5.2.4 Check LangGraph Service
**Steps**:
1. Visit relevant LangGraph endpoints to verify availability
---
## Optional Functional Verification
### 6.1 List Available Models
**Steps**: Verify the model list through the API or UI.
---
### 6.2 List Available Skills
**Steps**: Verify the skill list through the API or UI.
---
### 6.3 Simple Chat Test
**Steps**: Send a simple message to test the complete workflow.
---
## Phase 6: Generate the Test Report
### 6.1 Collect Test Results
Summarize the execution status of each phase and record successful and failed items.
### 6.2 Record Issues
If anything fails, record detailed error information.
### 6.3 Generate the Report
Use the template to create a complete test report.
### 6.4 Provide Recommendations
Provide follow-up recommendations based on the test results.
@@ -1,612 +0,0 @@
# Troubleshooting Guide
This document lists common issues encountered during DeerFlow smoke testing and how to resolve them.
## Code Update Issues
### Issue: `git pull` Fails with a Merge Conflict Warning
**Symptoms**:
```
error: Your local changes to the following files would be overwritten by merge
```
**Solutions**:
1. Option A: Commit local changes first
```bash
git add .
git commit -m "Save local changes"
git pull origin main
```
2. Option B: Stash local changes
```bash
git stash
git pull origin main
git stash pop # Restore changes later if needed
```
3. Option C: Discard local changes (use with caution)
```bash
git reset --hard HEAD
git pull origin main
```
---
## Local Mode Environment Issues
### Issue: Node.js Version Is Too Old
**Symptoms**:
```
Node.js version is too old. Requires 22+, got x.x.x
```
**Solutions**:
1. Install or upgrade Node.js with nvm:
```bash
nvm install 22
nvm use 22
```
2. Or download and install it from the official website: https://nodejs.org/
3. Verify the version:
```bash
node --version
```
---
### Issue: pnpm Is Not Installed
**Symptoms**:
```
command not found: pnpm
```
**Solutions**:
1. Install pnpm with npm:
```bash
npm install -g pnpm
```
2. Or use the official installation script:
```bash
curl -fsSL https://get.pnpm.io/install.sh | sh -
```
3. Verify the installation:
```bash
pnpm --version
```
---
### Issue: uv Is Not Installed
**Symptoms**:
```
command not found: uv
```
**Solutions**:
1. Use the official installation script:
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
2. macOS users can also install it with Homebrew:
```bash
brew install uv
```
3. Verify the installation:
```bash
uv --version
```
---
### Issue: nginx Is Not Installed
**Symptoms**:
```
command not found: nginx
```
**Solutions**:
1. macOS (Homebrew):
```bash
brew install nginx
```
2. Ubuntu/Debian:
```bash
sudo apt update
sudo apt install nginx
```
3. CentOS/RHEL:
```bash
sudo yum install nginx
```
4. Verify the installation:
```bash
nginx -v
```
---
### Issue: Port Is Already in Use
**Symptoms**:
```
Error: listen EADDRINUSE: address already in use :::2026
```
**Solutions**:
1. Find the process using the port:
```bash
lsof -i :2026 # macOS/Linux
netstat -ano | findstr :2026 # Windows
```
2. Stop that process:
```bash
kill -9 <PID> # macOS/Linux
taskkill /PID <PID> /F # Windows
```
3. Or stop DeerFlow services first:
```bash
make stop
```
---
## Local Mode Dependency Installation Issues
### Issue: `make install` Fails Due to Network Timeout
**Symptoms**:
Network timeouts or connection failures occur during dependency installation.
**Solutions**:
1. Configure pnpm to use a mirror registry:
```bash
pnpm config set registry https://registry.npmmirror.com
```
2. Configure uv to use a mirror registry:
```bash
uv pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
```
3. Retry the installation:
```bash
make install
```
---
### Issue: Python Dependency Installation Fails
**Symptoms**:
Errors occur during `uv sync`.
**Solutions**:
1. Clean the uv cache:
```bash
cd backend
uv cache clean
```
2. Resync dependencies:
```bash
cd backend
uv sync
```
3. View detailed error logs:
```bash
cd backend
uv sync --verbose
```
---
### Issue: Frontend Dependency Installation Fails
**Symptoms**:
Errors occur during `pnpm install`.
**Solutions**:
1. Clean the pnpm cache:
```bash
cd frontend
pnpm store prune
```
2. Remove node_modules and the lock file:
```bash
cd frontend
rm -rf node_modules pnpm-lock.yaml
```
3. Reinstall:
```bash
cd frontend
pnpm install
```
---
## Local Mode Service Startup Issues
### Issue: Services Exit Immediately After Startup
**Symptoms**:
Processes exit quickly after running `make dev-daemon`.
**Solutions**:
1. Check log files:
```bash
tail -f logs/langgraph.log
tail -f logs/gateway.log
tail -f logs/frontend.log
tail -f logs/nginx.log
```
2. Check whether config.yaml is configured correctly
3. Check environment variables in the .env file
4. Confirm that required ports are not occupied
5. Stop all services and restart:
```bash
make stop
make dev-daemon
```
---
### Issue: Nginx Fails to Start Because Temp Directories Do Not Exist
**Symptoms**:
```
nginx: [emerg] mkdir() "/opt/homebrew/var/run/nginx/client_body_temp" failed (2: No such file or directory)
```
**Solutions**:
Add local temp directory configuration to `docker/nginx/nginx.local.conf` so nginx uses the repository's temp directory.
Add the following at the beginning of the `http` block:
```nginx
client_body_temp_path temp/client_body_temp;
proxy_temp_path temp/proxy_temp;
fastcgi_temp_path temp/fastcgi_temp;
uwsgi_temp_path temp/uwsgi_temp;
scgi_temp_path temp/scgi_temp;
```
Note: The `temp/` directory under the repository root is created automatically by `make dev` or `make dev-daemon`.
---
### Issue: Nginx Fails to Start (General)
**Symptoms**:
The nginx process fails to start or reports an error.
**Solutions**:
1. Check the nginx configuration:
```bash
nginx -t -c docker/nginx/nginx.local.conf -p .
```
2. Check nginx logs:
```bash
tail -f logs/nginx.log
```
3. Ensure no other nginx process is running:
```bash
ps aux | grep nginx
```
4. If needed, stop existing nginx processes:
```bash
pkill -9 nginx
```
---
### Issue: Frontend Compilation Fails
**Symptoms**:
Compilation errors appear in `frontend.log`.
**Solutions**:
1. Check frontend logs:
```bash
tail -f logs/frontend.log
```
2. Check whether Node.js version is 22+
3. Reinstall frontend dependencies:
```bash
cd frontend
rm -rf node_modules .next
pnpm install
```
4. Restart services:
```bash
make stop
make dev-daemon
```
---
### Issue: Gateway Fails to Start
**Symptoms**:
Errors appear in `gateway.log`.
**Solutions**:
1. Check gateway logs:
```bash
tail -f logs/gateway.log
```
2. Check whether config.yaml exists and has valid formatting
3. Check whether Python dependencies are complete:
```bash
cd backend
uv sync
```
4. Confirm that the LangGraph service is running normally (if not in gateway mode)
---
### Issue: LangGraph Fails to Start
**Symptoms**:
Errors appear in `langgraph.log`.
**Solutions**:
1. Check LangGraph logs:
```bash
tail -f logs/langgraph.log
```
2. Check config.yaml
3. Check whether Python dependencies are complete
4. Confirm that port 2024 is not occupied
---
## Docker-Related Issues
### Issue: Docker Commands Cannot Run
**Symptoms**:
```
Cannot connect to the Docker daemon
```
**Solutions**:
1. Confirm that Docker Desktop is running
2. macOS: check whether the Docker icon appears in the top menu bar
3. Linux: run `sudo systemctl start docker`
4. Run `docker info` again to verify
---
### Issue: `make docker-init` Fails to Pull the Image
**Symptoms**:
```
Error pulling image: connection refused
```
**Solutions**:
1. Check network connectivity
2. Configure a Docker image mirror if needed
3. Check whether a proxy is required
4. Switch to local installation mode if necessary (recommended)
---
## Configuration File Issues
### Issue: config.yaml Is Missing or Invalid
**Symptoms**:
```
Error: could not read config.yaml
```
**Solutions**:
1. Regenerate the configuration file:
```bash
make config
```
2. Check YAML syntax:
- Make sure indentation is correct (use 2 spaces)
- Make sure there are no tab characters
- Check that there is a space after each colon
3. Use a YAML validation tool to check the format
---
### Issue: Model API Key Is Not Configured
**Symptoms**:
After services start, API requests fail with authentication errors.
**Solutions**:
1. Edit the .env file and add the API key:
```bash
OPENAI_API_KEY=your-actual-api-key-here
```
2. Restart services (local mode):
```bash
make stop
make dev-daemon
```
3. Restart services (Docker mode):
```bash
make docker-stop
make docker-start
```
4. Confirm that the model configuration in config.yaml references the environment variable correctly
---
## Service Health Check Issues
### Issue: Frontend Page Is Not Accessible
**Symptoms**:
The browser shows a connection failure when visiting http://localhost:2026.
**Solutions** (local mode):
1. Confirm that the nginx process is running:
```bash
ps aux | grep nginx
```
2. Check nginx logs:
```bash
tail -f logs/nginx.log
```
3. Check firewall settings
**Solutions** (Docker mode):
1. Confirm that the nginx container is running:
```bash
docker ps | grep nginx
```
2. Check nginx logs:
```bash
cd docker && docker compose -p deer-flow-dev -f docker-compose-dev.yaml logs nginx
```
3. Check firewall settings
---
### Issue: API Gateway Health Check Fails
**Symptoms**:
Accessing `/health` returns an error or times out.
**Solutions** (local mode):
1. Check gateway logs:
```bash
tail -f logs/gateway.log
```
2. Confirm that config.yaml exists and has valid formatting
3. Check whether Python dependencies are complete
4. Confirm that the LangGraph service is running normally
**Solutions** (Docker mode):
1. Check gateway container logs:
```bash
make docker-logs-gateway
```
2. Confirm that config.yaml is mounted correctly
3. Check whether Python dependencies are complete
4. Confirm that the LangGraph service is running normally
---
## Common Diagnostic Commands
### Local Mode Diagnostics
#### View All Service Processes
```bash
ps aux | grep -E "(langgraph|uvicorn|next|nginx)" | grep -v grep
```
#### View Service Logs
```bash
# View all logs
tail -f logs/*.log
# View specific service logs
tail -f logs/langgraph.log
tail -f logs/gateway.log
tail -f logs/frontend.log
tail -f logs/nginx.log
```
#### Stop All Services
```bash
make stop
```
#### Fully Reset the Local Environment
```bash
make stop
make clean
make config
make install
make dev-daemon
```
---
### Docker Mode Diagnostics
#### View All Container Status
```bash
docker ps -a
```
#### View Container Resource Usage
```bash
docker stats
```
#### Enter a Container for Debugging
```bash
docker exec -it deer-flow-gateway sh
```
#### Clean Up All DeerFlow-Related Containers and Images
```bash
make docker-stop
cd docker && docker compose -p deer-flow-dev -f docker-compose-dev.yaml down -v
```
#### Fully Reset the Docker Environment
```bash
make docker-stop
make clean
make config
make docker-init
make docker-start
```
---
## Get More Help
If the solutions above do not resolve the issue:
1. Check the GitHub issues for the project: https://github.com/bytedance/deer-flow/issues
2. Review the project documentation: README.md and the `backend/docs/` directory
3. Open a new issue and include detailed error logs
@@ -1,80 +0,0 @@
#!/usr/bin/env bash
set -e
echo "=========================================="
echo " Checking Docker Environment"
echo "=========================================="
echo ""
# Check whether Docker is installed
if command -v docker >/dev/null 2>&1; then
echo "✓ Docker is installed"
docker --version
else
echo "✗ Docker is not installed"
exit 1
fi
echo ""
# Check the Docker daemon
if docker info >/dev/null 2>&1; then
echo "✓ Docker daemon is running normally"
else
echo "✗ Docker daemon is not running"
echo " Please start Docker Desktop or the Docker service"
exit 1
fi
echo ""
# Check Docker Compose
if docker compose version >/dev/null 2>&1; then
echo "✓ Docker Compose is available"
docker compose version
else
echo "✗ Docker Compose is not available"
exit 1
fi
echo ""
# Check port 2026
if ! command -v lsof >/dev/null 2>&1; then
echo "✗ lsof is required to check whether port 2026 is available"
exit 1
fi
port_2026_usage="$(lsof -nP -iTCP:2026 -sTCP:LISTEN 2>/dev/null || true)"
if [ -n "$port_2026_usage" ]; then
echo "⚠ Port 2026 is already in use"
echo " Occupying process:"
echo "$port_2026_usage"
deerflow_process_found=0
while IFS= read -r pid; do
if [ -z "$pid" ]; then
continue
fi
process_command="$(ps -p "$pid" -o command= 2>/dev/null || true)"
case "$process_command" in
*[Dd]eer[Ff]low*|*[Dd]eerflow*|*[Nn]ginx*deerflow*|*deerflow/*[Nn]ginx*)
deerflow_process_found=1
;;
esac
done <<EOF
$(printf '%s\n' "$port_2026_usage" | awk 'NR > 1 {print $2}')
EOF
if [ "$deerflow_process_found" -eq 1 ]; then
echo "✓ Port 2026 is occupied by DeerFlow"
else
echo "✗ Port 2026 must be free before starting DeerFlow"
exit 1
fi
else
echo "✓ Port 2026 is available"
fi
echo ""
echo "=========================================="
echo " Docker Environment Check Complete"
echo "=========================================="
@@ -1,93 +0,0 @@
#!/usr/bin/env bash
set -e
echo "=========================================="
echo " Checking Local Development Environment"
echo "=========================================="
echo ""
all_passed=true
# Check Node.js
echo "1. Checking Node.js..."
if command -v node >/dev/null 2>&1; then
NODE_VERSION=$(node --version | sed 's/v//')
NODE_MAJOR=$(echo "$NODE_VERSION" | cut -d. -f1)
if [ "$NODE_MAJOR" -ge 22 ]; then
echo "✓ Node.js is installed (version: $NODE_VERSION)"
else
echo "✗ Node.js version is too old (current: $NODE_VERSION, required: 22+)"
all_passed=false
fi
else
echo "✗ Node.js is not installed"
all_passed=false
fi
echo ""
# Check pnpm
echo "2. Checking pnpm..."
if command -v pnpm >/dev/null 2>&1; then
echo "✓ pnpm is installed (version: $(pnpm --version))"
else
echo "✗ pnpm is not installed"
echo " Install command: npm install -g pnpm"
all_passed=false
fi
echo ""
# Check uv
echo "3. Checking uv..."
if command -v uv >/dev/null 2>&1; then
echo "✓ uv is installed (version: $(uv --version))"
else
echo "✗ uv is not installed"
all_passed=false
fi
echo ""
# Check nginx
echo "4. Checking nginx..."
if command -v nginx >/dev/null 2>&1; then
echo "✓ nginx is installed (version: $(nginx -v 2>&1))"
else
echo "✗ nginx is not installed"
echo " macOS: brew install nginx"
echo " Linux: install it with the system package manager"
all_passed=false
fi
echo ""
# Check ports
echo "5. Checking ports..."
if ! command -v lsof >/dev/null 2>&1; then
echo "✗ lsof is not installed, so port availability cannot be verified"
echo " Install lsof and rerun this check"
all_passed=false
else
for port in 2026 3000 8001 2024; do
if lsof -i :$port >/dev/null 2>&1; then
echo "⚠ Port $port is already in use:"
lsof -i :$port | head -2
all_passed=false
else
echo "✓ Port $port is available"
fi
done
fi
echo ""
# Summary
echo "=========================================="
echo " Environment Check Summary"
echo "=========================================="
echo ""
if [ "$all_passed" = true ]; then
echo "✅ All environment checks passed!"
echo ""
echo "Next step: run make install to install dependencies"
exit 0
else
echo "❌ Some checks failed. Please fix the issues above first"
exit 1
fi
@@ -1,65 +0,0 @@
#!/usr/bin/env bash
set -e
echo "=========================================="
echo " Docker Deployment"
echo "=========================================="
echo ""
# Check config.yaml
if [ ! -f "config.yaml" ]; then
echo "config.yaml does not exist. Generating it..."
make config
echo ""
echo "⚠ Please edit config.yaml to configure your models and API keys"
echo " Then run this script again"
exit 1
else
echo "✓ config.yaml exists"
fi
echo ""
# Check the .env file
if [ ! -f ".env" ]; then
echo ".env does not exist. Copying it from the example..."
if [ -f ".env.example" ]; then
cp .env.example .env
echo "✓ Created the .env file"
else
echo "⚠ .env.example does not exist. Please create the .env file manually"
fi
else
echo "✓ .env file exists"
fi
echo ""
# Check the frontend .env file
if [ ! -f "frontend/.env" ]; then
echo "frontend/.env does not exist. Copying it from the example..."
if [ -f "frontend/.env.example" ]; then
cp frontend/.env.example frontend/.env
echo "✓ Created the frontend/.env file"
else
echo "⚠ frontend/.env.example does not exist. Please create frontend/.env manually"
fi
else
echo "✓ frontend/.env file exists"
fi
echo ""
# Initialize the Docker environment
echo "Initializing the Docker environment..."
make docker-init
echo ""
# Start Docker services
echo "Starting Docker services..."
make docker-start
echo ""
echo "=========================================="
echo " Deployment Complete"
echo "=========================================="
echo ""
echo "🌐 Access URL: http://localhost:2026"
echo "📋 View logs: make docker-logs"
echo "🛑 Stop services: make docker-stop"
@@ -1,63 +0,0 @@
#!/usr/bin/env bash
set -e
echo "=========================================="
echo " Local Mode Deployment"
echo "=========================================="
echo ""
# Check config.yaml
if [ ! -f "config.yaml" ]; then
echo "config.yaml does not exist. Generating it..."
make config
echo ""
echo "⚠ Please edit config.yaml to configure your models and API keys"
echo " Then run this script again"
exit 1
else
echo "✓ config.yaml exists"
fi
echo ""
# Check the .env file
if [ ! -f ".env" ]; then
echo ".env does not exist. Copying it from the example..."
if [ -f ".env.example" ]; then
cp .env.example .env
echo "✓ Created the .env file"
else
echo "⚠ .env.example does not exist. Please create the .env file manually"
fi
else
echo "✓ .env file exists"
fi
echo ""
# Check dependencies
echo "Checking dependencies..."
make check
echo ""
# Install dependencies
echo "Installing dependencies..."
make install
echo ""
# Start services
echo "Starting services (background mode)..."
make dev-daemon
echo ""
echo "=========================================="
echo " Deployment Complete"
echo "=========================================="
echo ""
echo "🌐 Access URL: http://localhost:2026"
echo "📋 View logs:"
echo " - logs/langgraph.log"
echo " - logs/gateway.log"
echo " - logs/frontend.log"
echo " - logs/nginx.log"
echo "🛑 Stop services: make stop"
echo ""
echo "Please wait 90-120 seconds for all services to start completely, then run the health check"
@@ -1,70 +0,0 @@
#!/usr/bin/env bash
set +e
echo "=========================================="
echo " Frontend Page Smoke Check"
echo "=========================================="
echo ""
BASE_URL="${BASE_URL:-http://localhost:2026}"
DOC_PATH="${DOC_PATH:-/en/docs}"
all_passed=true
check_status() {
local name="$1"
local url="$2"
local expected_re="$3"
local status
status="$(curl -s -o /dev/null -w "%{http_code}" -L "$url")"
if echo "$status" | grep -Eq "$expected_re"; then
echo "$name ($url) -> $status"
else
echo "$name ($url) -> $status (expected: $expected_re)"
all_passed=false
fi
}
check_final_url() {
local name="$1"
local url="$2"
local expected_path_re="$3"
local effective
effective="$(curl -s -o /dev/null -w "%{url_effective}" -L "$url")"
if echo "$effective" | grep -Eq "$expected_path_re"; then
echo "$name redirect target -> $effective"
else
echo "$name redirect target -> $effective (expected path: $expected_path_re)"
all_passed=false
fi
}
echo "1. Checking entry pages..."
check_status "Landing page" "${BASE_URL}/" "200"
check_status "Workspace redirect" "${BASE_URL}/workspace" "200|301|302|307|308"
check_final_url "Workspace redirect" "${BASE_URL}/workspace" "/workspace/chats/"
echo ""
echo "2. Checking key workspace routes..."
check_status "New chat page" "${BASE_URL}/workspace/chats/new" "200"
check_status "Chats list page" "${BASE_URL}/workspace/chats" "200"
check_status "Agents gallery page" "${BASE_URL}/workspace/agents" "200"
echo ""
echo "3. Checking docs route (optional)..."
check_status "Docs page" "${BASE_URL}${DOC_PATH}" "200|404"
echo ""
echo "=========================================="
echo " Frontend Smoke Check Summary"
echo "=========================================="
echo ""
if [ "$all_passed" = true ]; then
echo "✅ Frontend smoke checks passed!"
exit 0
else
echo "❌ Frontend smoke checks failed"
exit 1
fi
@@ -1,125 +0,0 @@
#!/usr/bin/env bash
set +e
echo "=========================================="
echo " Service Health Check"
echo "=========================================="
echo ""
all_passed=true
mode="${SMOKE_TEST_MODE:-auto}"
summary_hint="make logs"
print_step() {
echo "$1"
}
check_http_status() {
local name="$1"
local url="$2"
local expected_re="$3"
local status
status="$(curl -s -o /dev/null -w "%{http_code}" "$url" 2>/dev/null)"
if echo "$status" | grep -Eq "$expected_re"; then
echo "$name is accessible ($url -> $status)"
else
echo "$name is not accessible ($url -> ${status:-000})"
all_passed=false
fi
}
check_listen_port() {
local name="$1"
local port="$2"
if lsof -nP -iTCP:"$port" -sTCP:LISTEN >/dev/null 2>&1; then
echo "$name is listening on port $port"
else
echo "$name is not listening on port $port"
all_passed=false
fi
}
docker_available() {
command -v docker >/dev/null 2>&1 && docker info >/dev/null 2>&1
}
detect_mode() {
case "$mode" in
local|docker)
echo "$mode"
return
;;
esac
if docker_available && docker ps --format "{{.Names}}" | grep -q "deer-flow"; then
echo "docker"
else
echo "local"
fi
}
mode="$(detect_mode)"
echo "Deployment mode: $mode"
echo ""
if [ "$mode" = "docker" ]; then
summary_hint="make docker-logs"
print_step "1. Checking container status..."
if docker ps --format "{{.Names}}" | grep -q "deer-flow"; then
echo "✓ Containers are running:"
docker ps --format " - {{.Names}} ({{.Status}})"
else
echo "✗ No DeerFlow-related containers are running"
all_passed=false
fi
else
summary_hint="logs/{langgraph,gateway,frontend,nginx}.log"
print_step "1. Checking local service ports..."
check_listen_port "Nginx" 2026
check_listen_port "Frontend" 3000
check_listen_port "Gateway" 8001
check_listen_port "LangGraph" 2024
fi
echo ""
echo "2. Waiting for services to fully start (30 seconds)..."
sleep 30
echo ""
echo "3. Checking frontend service..."
check_http_status "Frontend service" "http://localhost:2026" "200|301|302|307|308"
echo ""
echo "4. Checking API Gateway..."
health_response=$(curl -s http://localhost:2026/health 2>/dev/null)
if [ $? -eq 0 ] && [ -n "$health_response" ]; then
echo "✓ API Gateway health check passed"
echo " Response: $health_response"
else
echo "✗ API Gateway health check failed"
all_passed=false
fi
echo ""
echo "5. Checking LangGraph service..."
check_http_status "LangGraph service" "http://localhost:2024/" "200|301|302|307|308|404"
echo ""
echo "=========================================="
echo " Health Check Summary"
echo "=========================================="
echo ""
if [ "$all_passed" = true ]; then
echo "✅ All checks passed!"
echo ""
echo "🌐 Application URL: http://localhost:2026"
exit 0
else
echo "❌ Some checks failed"
echo ""
echo "Please review: $summary_hint"
exit 1
fi
@@ -1,49 +0,0 @@
#!/usr/bin/env bash
set -e
echo "=========================================="
echo " Pulling the Latest Code"
echo "=========================================="
echo ""
# Check whether the current directory is a Git repository
if [ ! -d ".git" ]; then
echo "✗ The current directory is not a Git repository"
exit 1
fi
# Check Git status
echo "Checking Git status..."
if git status --porcelain | grep -q .; then
echo "⚠ Uncommitted changes detected:"
git status --short
echo ""
echo "Please commit or stash your changes before continuing"
echo "Options:"
echo " 1. git add . && git commit -m 'Save changes'"
echo " 2. git stash (stash changes and restore them later)"
echo " 3. git reset --hard HEAD (discard local changes - use with caution)"
exit 1
else
echo "✓ Working tree is clean"
fi
echo ""
# Fetch remote updates
echo "Fetching remote updates..."
git fetch origin main
echo ""
# Pull the latest code
echo "Pulling the latest code..."
git pull origin main
echo ""
# Show the latest commit
echo "Latest commit:"
git log -1 --oneline
echo ""
echo "=========================================="
echo " Code Update Complete"
echo "=========================================="
@@ -1,180 +0,0 @@
# DeerFlow Smoke Test Report
**Test Date**: {{test_date}}
**Test Environment**: {{test_environment}}
**Deployment Mode**: Docker
**Test Version**: {{git_commit}}
---
## Execution Summary
| Metric | Status |
|------|------|
| Total Test Phases | 6 |
| Passed Phases | {{passed_stages}} |
| Failed Phases | {{failed_stages}} |
| Overall Conclusion | **{{overall_status}}** |
### Key Test Cases
| Case | Result | Details |
|------|--------|---------|
| Code update check | {{case_code_update}} | {{case_code_update_details}} |
| Environment check | {{case_env_check}} | {{case_env_check_details}} |
| Configuration preparation | {{case_config_prep}} | {{case_config_prep_details}} |
| Deployment | {{case_deploy}} | {{case_deploy_details}} |
| Health check | {{case_health_check}} | {{case_health_check_details}} |
| Frontend routes | {{case_frontend_routes_overall}} | {{case_frontend_routes_details}} |
---
## Detailed Test Results
### Phase 1: Code Update Check
- [x] Confirm current directory - {{status_dir_check}}
- [x] Check Git status - {{status_git_status}}
- [x] Pull latest code - {{status_git_pull}}
- [x] Confirm code update - {{status_git_verify}}
**Phase Status**: {{stage1_status}}
---
### Phase 2: Docker Environment Check
- [x] Docker version - {{status_docker_version}}
- [x] Docker daemon - {{status_docker_daemon}}
- [x] Docker Compose - {{status_docker_compose}}
- [x] Port check - {{status_port_check}}
**Phase Status**: {{stage2_status}}
---
### Phase 3: Configuration Preparation
- [x] config.yaml - {{status_config_yaml}}
- [x] .env file - {{status_env_file}}
- [x] Model configuration - {{status_model_config}}
**Phase Status**: {{stage3_status}}
---
### Phase 4: Docker Deployment
- [x] docker-init - {{status_docker_init}}
- [x] docker-start - {{status_docker_start}}
- [x] Service startup wait - {{status_wait_startup}}
**Phase Status**: {{stage4_status}}
---
### Phase 5: Service Health Check
- [x] Container status - {{status_containers}}
- [x] Frontend service - {{status_frontend}}
- [x] API Gateway - {{status_api_gateway}}
- [x] LangGraph service - {{status_langgraph}}
**Phase Status**: {{stage5_status}}
---
### Frontend Routes Smoke Results
| Route | Status | Details |
|-------|--------|---------|
| Landing `/` | {{landing_status}} | {{landing_details}} |
| Workspace redirect `/workspace` | {{workspace_redirect_status}} | target {{workspace_redirect_target}} |
| New chat `/workspace/chats/new` | {{new_chat_status}} | {{new_chat_details}} |
| Chats list `/workspace/chats` | {{chats_list_status}} | {{chats_list_details}} |
| Agents gallery `/workspace/agents` | {{agents_gallery_status}} | {{agents_gallery_details}} |
| Docs `{{docs_path}}` | {{docs_status}} | {{docs_details}} |
**Summary**: {{frontend_routes_summary}}
---
### Phase 6: Test Report Generation
- [x] Result summary - {{status_summary}}
- [x] Issue log - {{status_issues}}
- [x] Report generation - {{status_report}}
**Phase Status**: {{stage6_status}}
---
## Issue Log
### Issue 1
**Description**: {{issue1_description}}
**Severity**: {{issue1_severity}}
**Solution**: {{issue1_solution}}
---
## Environment Information
### Docker Version
```text
{{docker_version_output}}
```
### Git Information
```text
Repository: {{git_repo}}
Branch: {{git_branch}}
Commit: {{git_commit}}
Commit Message: {{git_commit_message}}
```
### Configuration Summary
- config.yaml exists: {{config_exists}}
- .env file exists: {{env_exists}}
- Number of configured models: {{model_count}}
---
## Container Status
| Container Name | Status | Uptime |
|----------|------|----------|
| deer-flow-nginx | {{nginx_status}} | {{nginx_uptime}} |
| deer-flow-frontend | {{frontend_status}} | {{frontend_uptime}} |
| deer-flow-gateway | {{gateway_status}} | {{gateway_uptime}} |
| deer-flow-langgraph | {{langgraph_status}} | {{langgraph_uptime}} |
---
## Recommendations and Next Steps
### If the Test Passes
1. [ ] Visit http://localhost:2026 to start using DeerFlow
2. [ ] Configure your preferred model if it is not configured yet
3. [ ] Explore available skills
4. [ ] Refer to the documentation to learn more features
### If the Test Fails
1. [ ] Review references/troubleshooting.md for common solutions
2. [ ] Check Docker logs: `make docker-logs`
3. [ ] Verify configuration file format and content
4. [ ] If needed, fully reset the environment: `make clean && make config && make docker-init && make docker-start`
---
## Appendix
### Full Logs
{{full_logs}}
### Tester
{{tester_name}}
---
*Report generated at: {{report_time}}*
@@ -1,185 +0,0 @@
# DeerFlow Smoke Test Report
**Test Date**: {{test_date}}
**Test Environment**: {{test_environment}}
**Deployment Mode**: Local
**Test Version**: {{git_commit}}
---
## Execution Summary
| Metric | Status |
|------|------|
| Total Test Phases | 6 |
| Passed Phases | {{passed_stages}} |
| Failed Phases | {{failed_stages}} |
| Overall Conclusion | **{{overall_status}}** |
### Key Test Cases
| Case | Result | Details |
|------|--------|---------|
| Code update check | {{case_code_update}} | {{case_code_update_details}} |
| Environment check | {{case_env_check}} | {{case_env_check_details}} |
| Configuration preparation | {{case_config_prep}} | {{case_config_prep_details}} |
| Deployment | {{case_deploy}} | {{case_deploy_details}} |
| Health check | {{case_health_check}} | {{case_health_check_details}} |
| Frontend routes | {{case_frontend_routes_overall}} | {{case_frontend_routes_details}} |
---
## Detailed Test Results
### Phase 1: Code Update Check
- [x] Confirm current directory - {{status_dir_check}}
- [x] Check Git status - {{status_git_status}}
- [x] Pull latest code - {{status_git_pull}}
- [x] Confirm code update - {{status_git_verify}}
**Phase Status**: {{stage1_status}}
---
### Phase 2: Local Environment Check
- [x] Node.js version - {{status_node_version}}
- [x] pnpm - {{status_pnpm}}
- [x] uv - {{status_uv}}
- [x] nginx - {{status_nginx}}
- [x] Port check - {{status_port_check}}
**Phase Status**: {{stage2_status}}
---
### Phase 3: Configuration Preparation
- [x] config.yaml - {{status_config_yaml}}
- [x] .env file - {{status_env_file}}
- [x] Model configuration - {{status_model_config}}
**Phase Status**: {{stage3_status}}
---
### Phase 4: Local Deployment
- [x] make check - {{status_make_check}}
- [x] make install - {{status_make_install}}
- [x] make dev-daemon / make dev - {{status_local_start}}
- [x] Service startup wait - {{status_wait_startup}}
**Phase Status**: {{stage4_status}}
---
### Phase 5: Service Health Check
- [x] Process status - {{status_processes}}
- [x] Frontend service - {{status_frontend}}
- [x] API Gateway - {{status_api_gateway}}
- [x] LangGraph service - {{status_langgraph}}
**Phase Status**: {{stage5_status}}
---
### Frontend Routes Smoke Results
| Route | Status | Details |
|-------|--------|---------|
| Landing `/` | {{landing_status}} | {{landing_details}} |
| Workspace redirect `/workspace` | {{workspace_redirect_status}} | target {{workspace_redirect_target}} |
| New chat `/workspace/chats/new` | {{new_chat_status}} | {{new_chat_details}} |
| Chats list `/workspace/chats` | {{chats_list_status}} | {{chats_list_details}} |
| Agents gallery `/workspace/agents` | {{agents_gallery_status}} | {{agents_gallery_details}} |
| Docs `{{docs_path}}` | {{docs_status}} | {{docs_details}} |
**Summary**: {{frontend_routes_summary}}
---
### Phase 6: Test Report Generation
- [x] Result summary - {{status_summary}}
- [x] Issue log - {{status_issues}}
- [x] Report generation - {{status_report}}
**Phase Status**: {{stage6_status}}
---
## Issue Log
### Issue 1
**Description**: {{issue1_description}}
**Severity**: {{issue1_severity}}
**Solution**: {{issue1_solution}}
---
## Environment Information
### Local Dependency Versions
```text
Node.js: {{node_version_output}}
pnpm: {{pnpm_version_output}}
uv: {{uv_version_output}}
nginx: {{nginx_version_output}}
```
### Git Information
```text
Repository: {{git_repo}}
Branch: {{git_branch}}
Commit: {{git_commit}}
Commit Message: {{git_commit_message}}
```
### Configuration Summary
- config.yaml exists: {{config_exists}}
- .env file exists: {{env_exists}}
- Number of configured models: {{model_count}}
---
## Local Service Status
| Service | Status | Endpoint |
|---------|--------|----------|
| Nginx | {{nginx_status}} | {{nginx_endpoint}} |
| Frontend | {{frontend_status}} | {{frontend_endpoint}} |
| Gateway | {{gateway_status}} | {{gateway_endpoint}} |
| LangGraph | {{langgraph_status}} | {{langgraph_endpoint}} |
---
## Recommendations and Next Steps
### If the Test Passes
1. [ ] Visit http://localhost:2026 to start using DeerFlow
2. [ ] Configure your preferred model if it is not configured yet
3. [ ] Explore available skills
4. [ ] Refer to the documentation to learn more features
### If the Test Fails
1. [ ] Review references/troubleshooting.md for common solutions
2. [ ] Check local logs: `logs/{langgraph,gateway,frontend,nginx}.log`
3. [ ] Verify configuration file format and content
4. [ ] If needed, fully reset the environment: `make stop && make clean && make install && make dev-daemon`
---
## Appendix
### Full Logs
{{full_logs}}
### Tester
{{tester_name}}
---
*Report generated at: {{report_time}}*
-7
View File
@@ -17,7 +17,6 @@ INFOQUEST_API_KEY=your-infoquest-api-key
# DEEPSEEK_API_KEY=your-deepseek-api-key
# NOVITA_API_KEY=your-novita-api-key # OpenAI-compatible, see https://novita.ai
# MINIMAX_API_KEY=your-minimax-api-key # OpenAI-compatible, see https://platform.minimax.io
# VLLM_API_KEY=your-vllm-api-key # OpenAI-compatible
# FEISHU_APP_ID=your-feishu-app-id
# FEISHU_APP_SECRET=your-feishu-app-secret
@@ -33,9 +32,3 @@ INFOQUEST_API_KEY=your-infoquest-api-key
# GitHub API Token
# GITHUB_TOKEN=your-github-token
# Database (only needed when config.yaml has database.backend: postgres)
# DATABASE_URL=postgresql://deerflow:password@localhost:5432/deerflow
#
# WECOM_BOT_ID=your-wecom-bot-id
# WECOM_BOT_SECRET=your-wecom-bot-secret
+2 -3
View File
@@ -2,6 +2,8 @@
docker/.cache/
# oh-my-claudecode state
.omc/
# Collaborator plugin state
.collaborator/
# OS generated files
.DS_Store
*.local
@@ -54,6 +56,3 @@ web/
# Deployment artifacts
backend/Dockerfile.langgraph
config.yaml.bak
.playwright-mcp
.gstack/
.worktrees
-128
View File
@@ -1,128 +0,0 @@
# Contributor Covenant Code of Conduct
## Our Pledge
We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level of experience, education, socio-economic status,
nationality, personal appearance, race, religion, or sexual identity
and orientation.
We pledge to act and interact in ways that contribute to an open, welcoming,
diverse, inclusive, and healthy community.
## Our Standards
Examples of behavior that contributes to a positive environment for our
community include:
* Demonstrating empathy and kindness toward other people
* Being respectful of differing opinions, viewpoints, and experiences
* Giving and gracefully accepting constructive feedback
* Accepting responsibility and apologizing to those affected by our mistakes,
and learning from the experience
* Focusing on what is best not just for us as individuals, but for the
overall community
Examples of unacceptable behavior include:
* The use of sexualized language or imagery, and sexual attention or
advances of any kind
* Trolling, insulting or derogatory comments, and personal or political attacks
* Public or private harassment
* Publishing others' private information, such as a physical or email
address, without their explicit permission
* Other conduct which could reasonably be considered inappropriate in a
professional setting
## Enforcement Responsibilities
Community leaders are responsible for clarifying and enforcing our standards of
acceptable behavior and will take appropriate and fair corrective action in
response to any behavior that they deem inappropriate, threatening, offensive,
or harmful.
Community leaders have the right and responsibility to remove, edit, or reject
comments, commits, code, wiki edits, issues, and other contributions that are
not aligned to this Code of Conduct, and will communicate reasons for moderation
decisions when appropriate.
## Scope
This Code of Conduct applies within all community spaces, and also applies when
an individual is officially representing the community in public spaces.
Examples of representing our community include using an official e-mail address,
posting via an official social media account, or acting as an appointed
representative at an online or offline event.
## Enforcement
Instances of abusive, harassing, or otherwise unacceptable behavior may be
reported to the community leaders responsible for enforcement at
willem.jiang@gmail.com.
All complaints will be reviewed and investigated promptly and fairly.
All community leaders are obligated to respect the privacy and security of the
reporter of any incident.
## Enforcement Guidelines
Community leaders will follow these Community Impact Guidelines in determining
the consequences for any action they deem in violation of this Code of Conduct:
### 1. Correction
**Community Impact**: Use of inappropriate language or other behavior deemed
unprofessional or unwelcome in the community.
**Consequence**: A private, written warning from community leaders, providing
clarity around the nature of the violation and an explanation of why the
behavior was inappropriate. A public apology may be requested.
### 2. Warning
**Community Impact**: A violation through a single incident or series
of actions.
**Consequence**: A warning with consequences for continued behavior. No
interaction with the people involved, including unsolicited interaction with
those enforcing the Code of Conduct, for a specified period of time. This
includes avoiding interactions in community spaces as well as external channels
like social media. Violating these terms may lead to a temporary or
permanent ban.
### 3. Temporary Ban
**Community Impact**: A serious violation of community standards, including
sustained inappropriate behavior.
**Consequence**: A temporary ban from any sort of interaction or public
communication with the community for a specified period of time. No public or
private interaction with the people involved, including unsolicited interaction
with those enforcing the Code of Conduct, is allowed during this period.
Violating these terms may lead to a permanent ban.
### 4. Permanent Ban
**Community Impact**: Demonstrating a pattern of violation of community
standards, including sustained inappropriate behavior, harassment of an
individual, or aggression toward or disparagement of classes of individuals.
**Consequence**: A permanent ban from any sort of public interaction within
the community.
## Attribution
This Code of Conduct is adapted from the [Contributor Covenant][homepage],
version 2.0, available at
https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
Community Impact Guidelines were inspired by [Mozilla's code of conduct
enforcement ladder](https://github.com/mozilla/diversity).
[homepage]: https://www.contributor-covenant.org
For answers to common questions about this code of conduct, see the FAQ at
https://www.contributor-covenant.org/faq. Translations are available at
https://www.contributor-covenant.org/translations.
+1 -13
View File
@@ -77,18 +77,6 @@ export UV_INDEX_URL=https://pypi.org/simple
export NPM_REGISTRY=https://registry.npmjs.org
```
#### Recommended host resources
Use these as practical starting points for development and review environments:
| Scenario | Starting point | Recommended | Notes |
|---------|-----------|------------|-------|
| `make dev` on one machine | 4 vCPU, 8 GB RAM | 8 vCPU, 16 GB RAM | Best when DeerFlow uses hosted model APIs. |
| `make docker-start` review environment | 4 vCPU, 8 GB RAM | 8 vCPU, 16 GB RAM | Docker image builds and sandbox containers need extra headroom. |
| Shared Linux test server | 8 vCPU, 16 GB RAM | 16 vCPU, 32 GB RAM | Prefer this for heavier multi-agent runs or multiple reviewers. |
`2 vCPU / 4 GB` environments often fail to start reliably or become unresponsive under normal DeerFlow workloads.
#### Linux: Docker daemon permission denied
If `make docker-init`, `make docker-start`, or `make docker-stop` fails on Linux with an error like below, your current user likely does not have permission to access the Docker daemon socket:
@@ -322,7 +310,7 @@ Every pull request runs the backend regression workflow at [.github/workflows/ba
- [Configuration Guide](backend/docs/CONFIGURATION.md) - Setup and configuration
- [Architecture Overview](backend/CLAUDE.md) - Technical architecture
- [MCP Setup Guide](backend/docs/MCP_SERVER.md) - Model Context Protocol configuration
- [MCP Setup Guide](MCP_SETUP.md) - Model Context Protocol configuration
## Need Help?
+36 -74
View File
@@ -1,67 +1,45 @@
# DeerFlow - Unified Development Environment
.PHONY: help config config-upgrade check install setup doctor dev dev-pro dev-daemon dev-daemon-pro start start-pro start-daemon start-daemon-pro stop up up-pro down clean docker-init docker-start docker-start-pro docker-stop docker-logs docker-logs-frontend docker-logs-gateway
.PHONY: help config config-upgrade check install dev dev-daemon start stop up down clean docker-init docker-start docker-stop docker-logs docker-logs-frontend docker-logs-gateway
PYTHON ?= python
BASH ?= bash
BACKEND_UV_RUN = cd backend && uv run
# Detect OS for Windows compatibility
ifeq ($(OS),Windows_NT)
SHELL := cmd.exe
PYTHON ?= python
# Run repo shell scripts through Git Bash when Make is launched from cmd.exe / PowerShell.
RUN_WITH_GIT_BASH = call scripts\run-with-git-bash.cmd
else
PYTHON ?= python3
RUN_WITH_GIT_BASH =
endif
help:
@echo "DeerFlow Development Commands:"
@echo " make setup - Interactive setup wizard (recommended for new users)"
@echo " make doctor - Check configuration and system requirements"
@echo " make config - Generate local config files (aborts if config already exists)"
@echo " make config-upgrade - Merge new fields from config.example.yaml into config.yaml"
@echo " make check - Check if all required tools are installed"
@echo " make install - Install all dependencies (frontend + backend)"
@echo " make setup-sandbox - Pre-pull sandbox container image (recommended)"
@echo " make dev - Start all services in development mode (with hot-reloading)"
@echo " make dev-pro - Start in dev + Gateway mode (experimental, no LangGraph server)"
@echo " make dev-daemon - Start dev services in background (daemon mode)"
@echo " make dev-daemon-pro - Start dev daemon + Gateway mode (experimental)"
@echo " make dev-daemon - Start all services in background (daemon mode)"
@echo " make start - Start all services in production mode (optimized, no hot-reloading)"
@echo " make start-pro - Start in prod + Gateway mode (experimental)"
@echo " make start-daemon - Start prod services in background (daemon mode)"
@echo " make start-daemon-pro - Start prod daemon + Gateway mode (experimental)"
@echo " make stop - Stop all running services"
@echo " make clean - Clean up processes and temporary files"
@echo ""
@echo "Docker Production Commands:"
@echo " make up - Build and start production Docker services (localhost:2026)"
@echo " make up-pro - Build and start production Docker in Gateway mode (experimental)"
@echo " make down - Stop and remove production Docker containers"
@echo ""
@echo "Docker Development Commands:"
@echo " make docker-init - Pull the sandbox image"
@echo " make docker-start - Start Docker services (mode-aware from config.yaml, localhost:2026)"
@echo " make docker-start-pro - Start Docker in Gateway mode (experimental, no LangGraph container)"
@echo " make docker-stop - Stop Docker development services"
@echo " make docker-logs - View Docker development logs"
@echo " make docker-logs-frontend - View Docker frontend logs"
@echo " make docker-logs-gateway - View Docker gateway logs"
## Setup & Diagnosis
setup:
@$(BACKEND_UV_RUN) python ../scripts/setup_wizard.py
doctor:
@$(BACKEND_UV_RUN) python ../scripts/doctor.py
config:
@$(PYTHON) ./scripts/configure.py
config-upgrade:
@$(RUN_WITH_GIT_BASH) ./scripts/config-upgrade.sh
@./scripts/config-upgrade.sh
# Check required tools
check:
@@ -118,47 +96,39 @@ setup-sandbox:
# Start all services in development mode (with hot-reloading)
dev:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev
# Start all services in dev + Gateway mode (experimental: agent runtime embedded in Gateway)
dev-pro:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --gateway
ifeq ($(OS),Windows_NT)
@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --dev
else
@./scripts/serve.sh --dev
endif
# Start all services in production mode (with optimizations)
start:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod
# Start all services in prod + Gateway mode (experimental)
start-pro:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --gateway
ifeq ($(OS),Windows_NT)
@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --prod
else
@./scripts/serve.sh --prod
endif
# Start all services in daemon mode (background)
dev-daemon:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --daemon
# Start daemon + Gateway mode (experimental)
dev-daemon-pro:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --gateway --daemon
# Start prod services in daemon mode (background)
start-daemon:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --daemon
# Start prod daemon + Gateway mode (experimental)
start-daemon-pro:
@$(PYTHON) ./scripts/check.py
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --gateway --daemon
@./scripts/start-daemon.sh
# Stop all services
stop:
@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --stop
@echo "Stopping all services..."
@-pkill -f "langgraph dev" 2>/dev/null || true
@-pkill -f "uvicorn app.gateway.app:app" 2>/dev/null || true
@-pkill -f "next dev" 2>/dev/null || true
@-pkill -f "next start" 2>/dev/null || true
@-pkill -f "next-server" 2>/dev/null || true
@-pkill -f "next-server" 2>/dev/null || true
@-nginx -c $(PWD)/docker/nginx/nginx.local.conf -p $(PWD) -s quit 2>/dev/null || true
@sleep 1
@-pkill -9 nginx 2>/dev/null || true
@echo "Cleaning up sandbox containers..."
@-./scripts/cleanup-containers.sh deer-flow-sandbox 2>/dev/null || true
@echo "✓ All services stopped"
# Clean up
clean: stop
@@ -174,29 +144,25 @@ clean: stop
# Initialize Docker containers and install dependencies
docker-init:
@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh init
@./scripts/docker.sh init
# Start Docker development environment
docker-start:
@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh start
# Start Docker in Gateway mode (experimental)
docker-start-pro:
@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh start --gateway
@./scripts/docker.sh start
# Stop Docker development environment
docker-stop:
@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh stop
@./scripts/docker.sh stop
# View Docker development logs
docker-logs:
@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh logs
@./scripts/docker.sh logs
# View Docker development logs
docker-logs-frontend:
@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh logs --frontend
@./scripts/docker.sh logs --frontend
docker-logs-gateway:
@$(RUN_WITH_GIT_BASH) ./scripts/docker.sh logs --gateway
@./scripts/docker.sh logs --gateway
# ==========================================
# Production Docker Commands
@@ -204,12 +170,8 @@ docker-logs-gateway:
# Build and start production services
up:
@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh
# Build and start production services in Gateway mode
up-pro:
@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh --gateway
@./scripts/deploy.sh
# Stop and remove production containers
down:
@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh down
@./scripts/deploy.sh down
+45 -177
View File
@@ -46,14 +46,12 @@ DeerFlow has newly integrated the intelligent search and crawling toolset indepe
- [🦌 DeerFlow - 2.0](#-deerflow---20)
- [Official Website](#official-website)
- [Coding Plan from ByteDance Volcengine](#coding-plan-from-bytedance-volcengine)
- [InfoQuest](#infoquest)
- [Table of Contents](#table-of-contents)
- [One-Line Agent Setup](#one-line-agent-setup)
- [Quick Start](#quick-start)
- [Configuration](#configuration)
- [Running the Application](#running-the-application)
- [Deployment Sizing](#deployment-sizing)
- [Option 1: Docker (Recommended)](#option-1-docker-recommended)
- [Option 2: Local Development](#option-2-local-development)
- [Advanced](#advanced)
@@ -61,8 +59,6 @@ DeerFlow has newly integrated the intelligent search and crawling toolset indepe
- [MCP Server](#mcp-server)
- [IM Channels](#im-channels)
- [LangSmith Tracing](#langsmith-tracing)
- [Langfuse Tracing](#langfuse-tracing)
- [Using Both Providers](#using-both-providers)
- [From Deep Research to Super Agent Harness](#from-deep-research-to-super-agent-harness)
- [Core Features](#core-features)
- [Skills \& Tools](#skills--tools)
@@ -75,8 +71,6 @@ DeerFlow has newly integrated the intelligent search and crawling toolset indepe
- [Embedded Python Client](#embedded-python-client)
- [Documentation](#documentation)
- [⚠️ Security Notice](#-security-notice)
- [Improper Deployment May Introduce Security Risks](#improper-deployment-may-introduce-security-risks)
- [Security Recommendations](#security-recommendations)
- [Contributing](#contributing)
- [License](#license)
- [Acknowledgments](#acknowledgments)
@@ -104,38 +98,35 @@ That prompt is intended for coding agents. It tells the agent to clone the repo
cd deer-flow
```
2. **Run the setup wizard**
2. **Generate local configuration files**
From the project root directory (`deer-flow/`), run:
```bash
make setup
make config
```
This launches an interactive wizard that guides you through choosing an LLM provider, optional web search, and execution/safety preferences such as sandbox mode, bash access, and file-write tools. It generates a minimal `config.yaml` and writes your keys to `.env`. Takes about 2 minutes.
This command creates local configuration files based on the provided example templates.
The wizard also lets you configure an optional web search provider, or skip it for now.
3. **Configure your preferred model(s)**
Run `make doctor` at any time to verify your setup and get actionable fix hints.
> **Advanced / manual configuration**: If you prefer to edit `config.yaml` directly, run `make config` instead to copy the full template. See `config.example.yaml` for the complete reference including CLI-backed providers (Codex CLI, Claude Code OAuth), OpenRouter, Responses API, and more.
<details>
<summary>Manual model configuration examples</summary>
Edit `config.yaml` and define at least one model:
```yaml
models:
- name: gpt-4o
display_name: GPT-4o
use: langchain_openai:ChatOpenAI
model: gpt-4o
api_key: $OPENAI_API_KEY
- name: gpt-4 # Internal identifier
display_name: GPT-4 # Human-readable name
use: langchain_openai:ChatOpenAI # LangChain class path
model: gpt-4 # Model identifier for API
api_key: $OPENAI_API_KEY # API key (recommended: use env var)
max_tokens: 4096 # Maximum tokens per request
temperature: 0.7 # Sampling temperature
- name: openrouter-gemini-2.5-flash
display_name: Gemini 2.5 Flash (OpenRouter)
use: langchain_openai:ChatOpenAI
model: google/gemini-2.5-flash-preview
api_key: $OPENROUTER_API_KEY
api_key: $OPENAI_API_KEY # OpenRouter still uses the OpenAI-compatible field name here
base_url: https://openrouter.ai/api/v1
- name: gpt-5-responses
@@ -145,26 +136,12 @@ That prompt is intended for coding agents. It tells the agent to clone the repo
api_key: $OPENAI_API_KEY
use_responses_api: true
output_version: responses/v1
- name: qwen3-32b-vllm
display_name: Qwen3 32B (vLLM)
use: deerflow.models.vllm_provider:VllmChatModel
model: Qwen/Qwen3-32B
api_key: $VLLM_API_KEY
base_url: http://localhost:8000/v1
supports_thinking: true
when_thinking_enabled:
extra_body:
chat_template_kwargs:
enable_thinking: true
```
OpenRouter and similar OpenAI-compatible gateways should be configured with `langchain_openai:ChatOpenAI` plus `base_url`. If you prefer a provider-specific environment variable name, point `api_key` at that variable explicitly (for example `api_key: $OPENROUTER_API_KEY`).
To route OpenAI models through `/v1/responses`, keep using `langchain_openai:ChatOpenAI` and set `use_responses_api: true` with `output_version: responses/v1`.
For vLLM 0.19.0, use `deerflow.models.vllm_provider:VllmChatModel`. For Qwen-style reasoning models, DeerFlow toggles reasoning with `extra_body.chat_template_kwargs.enable_thinking` and preserves vLLM's non-standard `reasoning` field across multi-turn tool-call conversations. Legacy `thinking` configs are normalized automatically for backward compatibility. Reasoning models may also require the server to be started with `--reasoning-parser ...`. If your local vLLM deployment accepts any non-empty API key, you can still set `VLLM_API_KEY` to a placeholder value.
CLI-backed provider examples:
```yaml
@@ -185,39 +162,50 @@ That prompt is intended for coding agents. It tells the agent to clone the repo
```
- Codex CLI reads `~/.codex/auth.json`
- Claude Code accepts `CLAUDE_CODE_OAUTH_TOKEN`, `ANTHROPIC_AUTH_TOKEN`, `CLAUDE_CODE_CREDENTIALS_PATH`, or `~/.claude/.credentials.json`
- ACP agent entries are separate from model providers — if you configure `acp_agents.codex`, point it at a Codex ACP adapter such as `npx -y @zed-industries/codex-acp`
- On macOS, export Claude Code auth explicitly if needed:
- The Codex Responses endpoint currently rejects `max_tokens` and `max_output_tokens`, so `CodexChatModel` does not expose a request-level token cap
- Claude Code accepts `CLAUDE_CODE_OAUTH_TOKEN`, `ANTHROPIC_AUTH_TOKEN`, `CLAUDE_CODE_OAUTH_TOKEN_FILE_DESCRIPTOR`, `CLAUDE_CODE_CREDENTIALS_PATH`, or plaintext `~/.claude/.credentials.json`
- ACP agent entries are separate from model providers. If you configure `acp_agents.codex`, point it at a Codex ACP adapter such as `npx -y @zed-industries/codex-acp`; the standard `codex` CLI binary is not ACP-compatible by itself
- On macOS, DeerFlow does not probe Keychain automatically. Export Claude Code auth explicitly if needed:
```bash
eval "$(python3 scripts/export_claude_code_oauth.py --print-export)"
```
4. **Set API keys for your configured model(s)**
Choose one of the following methods:
- Option A: Edit the `.env` file in the project root (Recommended)
API keys can also be set manually in `.env` (recommended) or exported in your shell:
```bash
OPENAI_API_KEY=your-openai-api-key
TAVILY_API_KEY=your-tavily-api-key
OPENAI_API_KEY=your-openai-api-key
# OpenRouter also uses OPENAI_API_KEY when your config uses langchain_openai:ChatOpenAI + base_url.
# Add other provider keys as needed
INFOQUEST_API_KEY=your-infoquest-api-key
```
</details>
- Option B: Export environment variables in your shell
```bash
export OPENAI_API_KEY=your-openai-api-key
```
For CLI-backed providers:
- Codex CLI: `~/.codex/auth.json`
- Claude Code OAuth: explicit env/file handoff or `~/.claude/.credentials.json`
- Option C: Edit `config.yaml` directly (Not recommended for production)
```yaml
models:
- name: gpt-4
api_key: your-actual-api-key-here # Replace placeholder
```
### Running the Application
#### Deployment Sizing
Use the table below as a practical starting point when choosing how to run DeerFlow:
| Deployment target | Starting point | Recommended | Notes |
|---------|-----------|------------|-------|
| Local evaluation / `make dev` | 4 vCPU, 8 GB RAM, 20 GB free SSD | 8 vCPU, 16 GB RAM | Good for one developer or one light session with hosted model APIs. `2 vCPU / 4 GB` is usually not enough. |
| Docker development / `make docker-start` | 4 vCPU, 8 GB RAM, 25 GB free SSD | 8 vCPU, 16 GB RAM | Image builds, bind mounts, and sandbox containers need more headroom than pure local dev. |
| Long-running server / `make up` | 8 vCPU, 16 GB RAM, 40 GB free SSD | 16 vCPU, 32 GB RAM | Preferred for shared use, multi-agent runs, report generation, or heavier sandbox workloads. |
- These numbers cover DeerFlow itself. If you also host a local LLM, size that service separately.
- Linux plus Docker is the recommended deployment target for a persistent server. macOS and Windows are best treated as development or evaluation environments.
- If CPU or memory usage stays pinned, reduce concurrent runs first, then move to the next sizing tier.
#### Option 1: Docker (Recommended)
**Development** (hot-reload, source mounts):
@@ -254,8 +242,7 @@ See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed Docker development guide.
If you prefer running services locally:
Prerequisite: complete the "Configuration" steps above first (`make setup`). `make dev` requires a valid `config.yaml` in the project root (can be overridden via `DEER_FLOW_CONFIG_PATH`). Run `make doctor` to verify your setup before starting.
On Windows, run the local development flow from Git Bash. Native `cmd.exe` and PowerShell shells are not supported for the bash-based service scripts, and WSL is not guaranteed because some scripts rely on Git for Windows utilities such as `cygpath`.
Prerequisite: complete the "Configuration" steps above first (`make config` and model API keys). `make dev` requires a valid configuration file (defaults to `config.yaml` in the project root; can be overridden via `DEER_FLOW_CONFIG_PATH`).
1. **Check prerequisites**:
```bash
@@ -287,60 +274,6 @@ On Windows, run the local development flow from Git Bash. Native `cmd.exe` and P
6. **Access**: http://localhost:2026
#### Startup Modes
DeerFlow supports multiple startup modes across two dimensions:
- **Dev / Prod** — dev enables hot-reload; prod uses pre-built frontend
- **Standard / Gateway** — standard uses a separate LangGraph server (4 processes); Gateway mode (experimental) embeds the agent runtime in the Gateway API (3 processes)
| | **Local Foreground** | **Local Daemon** | **Docker Dev** | **Docker Prod** |
|---|---|---|---|---|
| **Dev** | `./scripts/serve.sh --dev`<br/>`make dev` | `./scripts/serve.sh --dev --daemon`<br/>`make dev-daemon` | `./scripts/docker.sh start`<br/>`make docker-start` | — |
| **Dev + Gateway** | `./scripts/serve.sh --dev --gateway`<br/>`make dev-pro` | `./scripts/serve.sh --dev --gateway --daemon`<br/>`make dev-daemon-pro` | `./scripts/docker.sh start --gateway`<br/>`make docker-start-pro` | — |
| **Prod** | `./scripts/serve.sh --prod`<br/>`make start` | `./scripts/serve.sh --prod --daemon`<br/>`make start-daemon` | — | `./scripts/deploy.sh`<br/>`make up` |
| **Prod + Gateway** | `./scripts/serve.sh --prod --gateway`<br/>`make start-pro` | `./scripts/serve.sh --prod --gateway --daemon`<br/>`make start-daemon-pro` | — | `./scripts/deploy.sh --gateway`<br/>`make up-pro` |
| Action | Local | Docker Dev | Docker Prod |
|---|---|---|---|
| **Stop** | `./scripts/serve.sh --stop`<br/>`make stop` | `./scripts/docker.sh stop`<br/>`make docker-stop` | `./scripts/deploy.sh down`<br/>`make down` |
| **Restart** | `./scripts/serve.sh --restart [flags]` | `./scripts/docker.sh restart` | — |
> **Gateway mode** eliminates the LangGraph server process — the Gateway API handles agent execution directly via async tasks, managing its own concurrency.
#### Why Gateway Mode?
In standard mode, DeerFlow runs a dedicated [LangGraph Platform](https://langchain-ai.github.io/langgraph/) server alongside the Gateway API. This architecture works well but has trade-offs:
| | Standard Mode | Gateway Mode |
|---|---|---|
| **Architecture** | Gateway (REST API) + LangGraph (agent runtime) | Gateway embeds agent runtime |
| **Concurrency** | `--n-jobs-per-worker` per worker (requires license) | `--workers` × async tasks (no per-worker cap) |
| **Containers / Processes** | 4 (frontend, gateway, langgraph, nginx) | 3 (frontend, gateway, nginx) |
| **Resource usage** | Higher (two Python runtimes) | Lower (single Python runtime) |
| **LangGraph Platform license** | Required for production images | Not required |
| **Cold start** | Slower (two services to initialize) | Faster |
Both modes are functionally equivalent — the same agents, tools, and skills work in either mode.
#### Docker Production Deployment
`deploy.sh` supports building and starting separately. Images are mode-agnostic — runtime mode is selected at start time:
```bash
# One-step (build + start)
deploy.sh # standard mode (default)
deploy.sh --gateway # gateway mode
# Two-step (build once, start with any mode)
deploy.sh build # build all images
deploy.sh start # start in standard mode
deploy.sh start --gateway # start in gateway mode
# Stop
deploy.sh down
```
### Advanced
#### Sandbox Mode
@@ -368,8 +301,6 @@ DeerFlow supports receiving tasks from messaging apps. Channels auto-start when
| Telegram | Bot API (long-polling) | Easy |
| Slack | Socket Mode | Moderate |
| Feishu / Lark | WebSocket | Moderate |
| WeChat | Tencent iLink (long-polling) | Moderate |
| WeCom | WebSocket | Moderate |
**Configuration in `config.yaml`:**
@@ -397,11 +328,6 @@ channels:
# domain: https://open.feishu.cn # China (default)
# domain: https://open.larksuite.com # International
wecom:
enabled: true
bot_id: $WECOM_BOT_ID
bot_secret: $WECOM_BOT_SECRET
slack:
enabled: true
bot_token: $SLACK_BOT_TOKEN # xoxb-...
@@ -413,19 +339,6 @@ channels:
bot_token: $TELEGRAM_BOT_TOKEN
allowed_users: [] # empty = allow all
wechat:
enabled: false
bot_token: $WECHAT_BOT_TOKEN
ilink_bot_id: $WECHAT_ILINK_BOT_ID
qrcode_login_enabled: true # optional: allow first-time QR bootstrap when bot_token is absent
allowed_users: [] # empty = allow all
polling_timeout: 35
state_dir: ./.deer-flow/wechat/state
max_inbound_image_bytes: 20971520
max_outbound_image_bytes: 20971520
max_inbound_file_bytes: 52428800
max_outbound_file_bytes: 52428800
# Optional: per-channel / per-user session settings
session:
assistant_id: mobile-agent # custom agent names are also supported here
@@ -458,14 +371,6 @@ SLACK_APP_TOKEN=xapp-...
# Feishu / Lark
FEISHU_APP_ID=cli_xxxx
FEISHU_APP_SECRET=your_app_secret
# WeChat iLink
WECHAT_BOT_TOKEN=your_ilink_bot_token
WECHAT_ILINK_BOT_ID=your_ilink_bot_id
# WeCom
WECOM_BOT_ID=your_bot_id
WECOM_BOT_SECRET=your_bot_secret
```
**Telegram Setup**
@@ -488,22 +393,6 @@ WECOM_BOT_SECRET=your_bot_secret
3. Under **Events**, subscribe to `im.message.receive_v1` and select **Long Connection** mode.
4. Copy the App ID and App Secret. Set `FEISHU_APP_ID` and `FEISHU_APP_SECRET` in `.env` and enable the channel in `config.yaml`.
**WeChat Setup**
1. Enable the `wechat` channel in `config.yaml`.
2. Either set `WECHAT_BOT_TOKEN` in `.env`, or set `qrcode_login_enabled: true` for first-time QR bootstrap.
3. When `bot_token` is absent and QR bootstrap is enabled, watch backend logs for the QR content returned by iLink and complete the binding flow.
4. After the QR flow succeeds, DeerFlow persists the acquired token under `state_dir` for later restarts.
5. For Docker Compose deployments, keep `state_dir` on a persistent volume so the `get_updates_buf` cursor and saved auth state survive restarts.
**WeCom Setup**
1. Create a bot on the WeCom AI Bot platform and obtain the `bot_id` and `bot_secret`.
2. Enable `channels.wecom` in `config.yaml` and fill in `bot_id` / `bot_secret`.
3. Set `WECOM_BOT_ID` and `WECOM_BOT_SECRET` in `.env`.
4. Make sure backend dependencies include `wecom-aibot-python-sdk`. The channel uses a WebSocket long connection and does not require a public callback URL.
5. The current integration supports inbound text, image, and file messages. Final images/files generated by the agent are also sent back to the WeCom conversation.
When DeerFlow runs in Docker Compose, IM channels execute inside the `gateway` container. In that case, do not point `channels.langgraph_url` or `channels.gateway_url` at `localhost`; use container service names such as `http://langgraph:2024` and `http://gateway:8001`, or set `DEER_FLOW_CHANNELS_LANGGRAPH_URL` and `DEER_FLOW_CHANNELS_GATEWAY_URL`.
**Commands**
@@ -533,27 +422,6 @@ LANGSMITH_API_KEY=lsv2_pt_xxxxxxxxxxxxxxxx
LANGSMITH_PROJECT=xxx
```
#### Langfuse Tracing
DeerFlow also supports [Langfuse](https://langfuse.com) observability for LangChain-compatible runs.
Add the following to your `.env` file:
```bash
LANGFUSE_TRACING=true
LANGFUSE_PUBLIC_KEY=pk-lf-xxxxxxxxxxxxxxxx
LANGFUSE_SECRET_KEY=sk-lf-xxxxxxxxxxxxxxxx
LANGFUSE_BASE_URL=https://cloud.langfuse.com
```
If you are using a self-hosted Langfuse instance, set `LANGFUSE_BASE_URL` to your deployment URL.
#### Using Both Providers
If both LangSmith and Langfuse are enabled, DeerFlow attaches both tracing callbacks and reports the same model activity to both systems.
If a provider is explicitly enabled but missing required credentials, or if its callback fails to initialize, DeerFlow fails fast when tracing is initialized during model creation and the error message names the provider that caused the failure.
For Docker deployments, tracing is disabled by default. Set `LANGSMITH_TRACING=true` and `LANGSMITH_API_KEY` in your `.env` to enable it.
## From Deep Research to Super Agent Harness
-34
View File
@@ -40,7 +40,6 @@ https://github.com/user-attachments/assets/a8bcadc4-e040-4cf2-8fda-dd768b999c18
- [快速开始](#快速开始)
- [配置](#配置)
- [运行应用](#运行应用)
- [部署建议与资源规划](#部署建议与资源规划)
- [方式一:Docker(推荐)](#方式一docker推荐)
- [方式二:本地开发](#方式二本地开发)
- [进阶配置](#进阶配置)
@@ -151,20 +150,6 @@ https://github.com/user-attachments/assets/a8bcadc4-e040-4cf2-8fda-dd768b999c18
### 运行应用
#### 部署建议与资源规划
可以先按下面的资源档位来选择 DeerFlow 的运行方式:
| 部署场景 | 起步配置 | 推荐配置 | 说明 |
|---------|-----------|------------|-------|
| 本地体验 / `make dev` | 4 vCPU、8 GB 内存、20 GB SSD 可用空间 | 8 vCPU、16 GB 内存 | 适合单个开发者或单个轻量会话,且模型走外部 API。`2 核 / 4 GB` 通常跑不稳。 |
| Docker 开发 / `make docker-start` | 4 vCPU、8 GB 内存、25 GB SSD 可用空间 | 8 vCPU、16 GB 内存 | 镜像构建、源码挂载和 sandbox 容器都会比纯本地模式更吃资源。 |
| 长期运行服务 / `make up` | 8 vCPU、16 GB 内存、40 GB SSD 可用空间 | 16 vCPU、32 GB 内存 | 更适合共享环境、多 agent 任务、报告生成或更重的 sandbox 负载。 |
- 上面的配置只覆盖 DeerFlow 本身;如果你还要本机部署本地大模型,请单独为模型服务预留资源。
- 持续运行的服务更推荐使用 Linux + Docker。macOS 和 Windows 更适合作为开发机或体验环境。
- 如果 CPU 或内存长期打满,先降低并发会话或重任务数量,再考虑升级到更高一档配置。
#### 方式一:Docker(推荐)
**开发模式**(支持热更新,挂载源码):
@@ -195,7 +180,6 @@ make down # 停止并移除容器
如果你更希望直接在本地启动各个服务:
前提:先完成上面的“配置”步骤(`make config` 和模型 API key 配置)。`make dev` 需要有效配置文件,默认读取项目根目录下的 `config.yaml`,也可以通过 `DEER_FLOW_CONFIG_PATH` 覆盖。
在 Windows 上,请使用 Git Bash 运行本地开发流程。基于 bash 的服务脚本不支持直接在原生 `cmd.exe` 或 PowerShell 中执行,且 WSL 也不保证可用,因为部分脚本依赖 Git for Windows 的 `cygpath` 等工具。
1. **检查依赖环境**
```bash
@@ -247,7 +231,6 @@ DeerFlow 支持从即时通讯应用接收任务。只要配置完成,对应
| Telegram | Bot APIlong-polling | 简单 |
| Slack | Socket Mode | 中等 |
| Feishu / Lark | WebSocket | 中等 |
| 企业微信智能机器人 | WebSocket | 中等 |
**`config.yaml` 中的配置示例:**
@@ -275,11 +258,6 @@ channels:
# domain: https://open.feishu.cn # 国内版(默认)
# domain: https://open.larksuite.com # 国际版
wecom:
enabled: true
bot_id: $WECOM_BOT_ID
bot_secret: $WECOM_BOT_SECRET
slack:
enabled: true
bot_token: $SLACK_BOT_TOKEN # xoxb-...
@@ -323,10 +301,6 @@ SLACK_APP_TOKEN=xapp-...
# Feishu / Lark
FEISHU_APP_ID=cli_xxxx
FEISHU_APP_SECRET=your_app_secret
# 企业微信智能机器人
WECOM_BOT_ID=your_bot_id
WECOM_BOT_SECRET=your_bot_secret
```
**Telegram 配置**
@@ -349,14 +323,6 @@ WECOM_BOT_SECRET=your_bot_secret
3. 在 **事件订阅** 中订阅 `im.message.receive_v1`,连接方式选择 **长连接**。
4. 复制 App ID 和 App Secret,在 `.env` 中设置 `FEISHU_APP_ID` 和 `FEISHU_APP_SECRET`,并在 `config.yaml` 中启用该渠道。
**企业微信智能机器人配置**
1. 在企业微信智能机器人平台创建机器人,获取 `bot_id` 和 `bot_secret`。
2. 在 `config.yaml` 中启用 `channels.wecom`,并填入 `bot_id` / `bot_secret`。
3. 在 `.env` 中设置 `WECOM_BOT_ID` 和 `WECOM_BOT_SECRET`。
4. 安装后端依赖时确保包含 `wecom-aibot-python-sdk`,渠道会通过 WebSocket 长连接接收消息,无需公网回调地址。
5. 当前支持文本、图片和文件入站消息;agent 生成的最终图片/文件也会回传到企业微信会话中。
**命令**
渠道连接完成后,你可以直接在聊天窗口里和 DeerFlow 交互:
+15 -60
View File
@@ -13,10 +13,6 @@ DeerFlow is a LangGraph-based AI super agent system with a full-stack architectu
- **Nginx** (port 2026): Unified reverse proxy entry point
- **Provisioner** (port 8002, optional in Docker dev): Started only when sandbox is configured for provisioner/Kubernetes mode
**Runtime Modes**:
- **Standard mode** (`make dev`): LangGraph Server handles agent execution as a separate process. 4 processes total.
- **Gateway mode** (`make dev-pro`, experimental): Agent runtime embedded in Gateway via `RunManager` + `run_agent()` + `StreamBridge` (`packages/harness/deerflow/runtime/`). Service manages its own concurrency via async tasks. 3 processes total, no LangGraph Server.
**Project Structure**:
```
deer-flow/
@@ -84,8 +80,6 @@ When making code changes, you MUST update the relevant documentation:
make check # Check system requirements
make install # Install all dependencies (frontend + backend)
make dev # Start all services (LangGraph + Gateway + Frontend + Nginx), with config.yaml preflight
make dev-pro # Gateway mode (experimental): skip LangGraph, agent runtime embedded in Gateway
make start-pro # Production + Gateway mode (experimental)
make stop # Stop all services
```
@@ -158,7 +152,7 @@ from deerflow.config import get_app_config
Middlewares execute in strict order in `packages/harness/deerflow/agents/lead_agent/agent.py`:
1. **ThreadDataMiddleware** - Creates per-thread directories under the user's isolation scope (`backend/.deer-flow/users/{user_id}/threads/{thread_id}/user-data/{workspace,uploads,outputs}`); resolves `user_id` via `get_effective_user_id()` (falls back to `"default"` in no-auth mode); Web UI thread deletion now follows LangGraph thread removal with Gateway cleanup of the local thread directory
1. **ThreadDataMiddleware** - Creates per-thread directories (`backend/.deer-flow/threads/{thread_id}/user-data/{workspace,uploads,outputs}`); Web UI thread deletion now follows LangGraph thread removal with Gateway cleanup of the local `.deer-flow/threads/{thread_id}` directory
2. **UploadsMiddleware** - Tracks and injects newly uploaded files into conversation
3. **SandboxMiddleware** - Acquires sandbox, stores `sandbox_id` in state
4. **DanglingToolCallMiddleware** - Injects placeholder ToolMessages for AIMessage tool_calls that lack responses (e.g., due to user interruption)
@@ -216,9 +210,6 @@ FastAPI application on port 8001 with health check at `GET /health`.
| **Threads** (`/api/threads/{id}`) | `DELETE /` - remove DeerFlow-managed local thread data after LangGraph thread deletion; unexpected failures are logged server-side and return a generic 500 detail |
| **Artifacts** (`/api/threads/{id}/artifacts`) | `GET /{path}` - serve artifacts; active content types (`text/html`, `application/xhtml+xml`, `image/svg+xml`) are always forced as download attachments to reduce XSS risk; `?download=true` still forces download for other file types |
| **Suggestions** (`/api/threads/{id}/suggestions`) | `POST /` - generate follow-up questions; rich list/block model content is normalized before JSON parsing |
| **Thread Runs** (`/api/threads/{id}/runs`) | `POST /` - create background run; `POST /stream` - create + SSE stream; `POST /wait` - create + block; `GET /` - list runs; `GET /{rid}` - run details; `POST /{rid}/cancel` - cancel; `GET /{rid}/join` - join SSE; `GET /{rid}/messages` - paginated messages `{data, has_more}`; `GET /{rid}/events` - full event stream; `GET /../messages` - thread messages with feedback; `GET /../token-usage` - aggregate tokens |
| **Feedback** (`/api/threads/{id}/runs/{rid}/feedback`) | `PUT /` - upsert feedback; `DELETE /` - delete user feedback; `POST /` - create feedback; `GET /` - list feedback; `GET /stats` - aggregate stats; `DELETE /{fid}` - delete specific |
| **Runs** (`/api/runs`) | `POST /stream` - stateless run + SSE; `POST /wait` - stateless run + block; `GET /{rid}/messages` - paginated messages by run_id `{data, has_more}` (cursor: `after_seq`/`before_seq`); `GET /{rid}/feedback` - list feedback by run_id |
Proxied through nginx: `/api/langgraph/*` → LangGraph, all other `/api/*` → Gateway.
@@ -232,7 +223,7 @@ Proxied through nginx: `/api/langgraph/*` → LangGraph, all other `/api/*` →
**Virtual Path System**:
- Agent sees: `/mnt/user-data/{workspace,uploads,outputs}`, `/mnt/skills`
- Physical: `backend/.deer-flow/users/{user_id}/threads/{thread_id}/user-data/...`, `deer-flow/skills/`
- Physical: `backend/.deer-flow/threads/{thread_id}/user-data/...`, `deer-flow/skills/`
- Translation: `replace_virtual_path()` / `replace_virtual_paths_in_command()`
- Detection: `is_local_sandbox()` checks `sandbox_id == "local"`
@@ -241,7 +232,7 @@ Proxied through nginx: `/api/langgraph/*` → LangGraph, all other `/api/*` →
- `ls` - Directory listing (tree format, max 2 levels)
- `read_file` - Read file contents with optional line range
- `write_file` - Write/append to files, creates directories
- `str_replace` - Substring replacement (single or all occurrences); same-path serialization is scoped to `(sandbox.id, path)` so isolated sandboxes do not contend on identical virtual paths inside one process
- `str_replace` - Substring replacement (single or all occurrences)
### Subagent System (`packages/harness/deerflow/subagents/`)
@@ -272,7 +263,7 @@ Proxied through nginx: `/api/langgraph/*` → LangGraph, all other `/api/*` →
- `invoke_acp_agent` - Invokes external ACP-compatible agents from `config.yaml`
- ACP launchers must be real ACP adapters. The standard `codex` CLI is not ACP-compatible by itself; configure a wrapper such as `npx -y @zed-industries/codex-acp` or an installed `codex-acp` binary
- Missing ACP executables now return an actionable error message instead of a raw `[Errno 2]`
- Each ACP agent uses a per-thread workspace at `{base_dir}/users/{user_id}/threads/{thread_id}/acp-workspace/`. The workspace is accessible to the lead agent via the virtual path `/mnt/acp-workspace/` (read-only). In docker sandbox mode, the directory is volume-mounted into the container at `/mnt/acp-workspace` (read-only); in local sandbox mode, path translation is handled by `tools.py`
- Each ACP agent uses a per-thread workspace at `{base_dir}/threads/{thread_id}/acp-workspace/`. The workspace is accessible to the lead agent via the virtual path `/mnt/acp-workspace/` (read-only). In docker sandbox mode, the directory is volume-mounted into the container at `/mnt/acp-workspace` (read-only); in local sandbox mode, path translation is handled by `tools.py`
- `image_search/` - Image search via DuckDuckGo
### MCP System (`packages/harness/deerflow/mcp/`)
@@ -296,17 +287,10 @@ Proxied through nginx: `/api/langgraph/*` → LangGraph, all other `/api/*` →
- `create_chat_model(name, thinking_enabled)` instantiates LLM from config via reflection
- Supports `thinking_enabled` flag with per-model `when_thinking_enabled` overrides
- Supports vLLM-style thinking toggles via `when_thinking_enabled.extra_body.chat_template_kwargs.enable_thinking` for Qwen reasoning models, while normalizing legacy `thinking` configs for backward compatibility
- Supports `supports_vision` flag for image understanding models
- Config values starting with `$` resolved as environment variables
- Missing provider modules surface actionable install hints from reflection resolvers (for example `uv add langchain-google-genai`)
### vLLM Provider (`packages/harness/deerflow/models/vllm_provider.py`)
- `VllmChatModel` subclasses `langchain_openai:ChatOpenAI` for vLLM 0.19.0 OpenAI-compatible endpoints
- Preserves vLLM's non-standard assistant `reasoning` field on full responses, streaming deltas, and follow-up tool-call turns
- Designed for configs that enable thinking through `extra_body.chat_template_kwargs.enable_thinking` on vLLM 0.19.0 Qwen reasoning models, while accepting the older `thinking` alias
### IM Channels System (`app/channels/`)
Bridges external messaging platforms (Feishu, Slack, Telegram) to the DeerFlow agent via the LangGraph Server.
@@ -341,27 +325,18 @@ Bridges external messaging platforms (Feishu, Slack, Telegram) to the DeerFlow a
**Components**:
- `updater.py` - LLM-based memory updates with fact extraction, whitespace-normalized fact deduplication (trims leading/trailing whitespace before comparing), and atomic file I/O
- `queue.py` - Debounced update queue (per-thread deduplication, configurable wait time); captures `user_id` at enqueue time so it survives the `threading.Timer` boundary
- `queue.py` - Debounced update queue (per-thread deduplication, configurable wait time)
- `prompt.py` - Prompt templates for memory updates
- `storage.py` - File-based storage with per-user isolation; cache keyed by `(user_id, agent_name)` tuple
**Per-User Isolation**:
- Memory is stored per-user at `{base_dir}/users/{user_id}/memory.json`
- Per-agent per-user memory at `{base_dir}/users/{user_id}/agents/{agent_name}/memory.json`
- `user_id` is resolved via `get_effective_user_id()` from `deerflow.runtime.user_context`
- In no-auth mode, `user_id` defaults to `"default"` (constant `DEFAULT_USER_ID`)
- Absolute `storage_path` in config opts out of per-user isolation
- **Migration**: Run `PYTHONPATH=. python scripts/migrate_user_isolation.py` to move legacy `memory.json` and `threads/` into per-user layout; supports `--dry-run`
**Data Structure** (stored in `{base_dir}/users/{user_id}/memory.json`):
**Data Structure** (stored in `backend/.deer-flow/memory.json`):
- **User Context**: `workContext`, `personalContext`, `topOfMind` (1-3 sentence summaries)
- **History**: `recentMonths`, `earlierContext`, `longTermBackground`
- **Facts**: Discrete facts with `id`, `content`, `category` (preference/knowledge/context/behavior/goal), `confidence` (0-1), `createdAt`, `source`
**Workflow**:
1. `MemoryMiddleware` filters messages (user inputs + final AI responses), captures `user_id` via `get_effective_user_id()`, and queues conversation with the captured `user_id`
1. `MemoryMiddleware` filters messages (user inputs + final AI responses) and queues conversation
2. Queue debounces (30s default), batches updates, deduplicates per-thread
3. Background thread invokes LLM to extract context updates and facts, using the stored `user_id` (not the contextvar, which is unavailable on timer threads)
3. Background thread invokes LLM to extract context updates and facts
4. Applies updates atomically (temp file + rename) with cache invalidation, skipping duplicate fact content before append
5. Next interaction injects top 15 facts + context into `<memory>` tags in system prompt
@@ -369,7 +344,7 @@ Focused regression coverage for the updater lives in `backend/tests/test_memory_
**Configuration** (`config.yaml``memory`):
- `enabled` / `injection_enabled` - Master switches
- `storage_path` - Path to memory.json (absolute path opts out of per-user isolation)
- `storage_path` - Path to memory.json
- `debounce_seconds` - Wait time before processing (default: 30)
- `model_name` - LLM for updates (null = default model)
- `max_facts` / `fact_confidence_threshold` - Fact storage limits (100 / 0.7)
@@ -384,7 +359,6 @@ Focused regression coverage for the updater lives in `backend/tests/test_memory_
**`config.yaml`** key sections:
- `models[]` - LLM configs with `use` class path, `supports_thinking`, `supports_vision`, provider-specific fields
- vLLM reasoning models should use `deerflow.models.vllm_provider:VllmChatModel`; for Qwen-style parsers prefer `when_thinking_enabled.extra_body.chat_template_kwargs.enable_thinking`, and DeerFlow will also normalize the older `thinking` alias
- `tools[]` - Tool configs with `use` variable path and `group`
- `tool_groups[]` - Logical groupings for tools
- `sandbox.use` - Sandbox provider class path
@@ -407,16 +381,14 @@ Both can be modified at runtime via Gateway API endpoints or `DeerFlowClient` me
**Architecture**: Imports the same `deerflow` modules that LangGraph Server and Gateway API use. Shares the same config files and data directories. No FastAPI dependency.
**Agent Conversation** (replaces LangGraph Server):
- `chat(message, thread_id)` — synchronous, accumulates streaming deltas per message-id and returns the final AI text
- `stream(message, thread_id)`subscribes to LangGraph `stream_mode=["values", "messages", "custom"]` and yields `StreamEvent`:
- `"values"` — full state snapshot (title, messages, artifacts); AI text already delivered via `messages` mode is **not** re-synthesized here to avoid duplicate deliveries
- `"messages-tuple"` — per-chunk update: for AI text this is a **delta** (concat per `id` to rebuild the full message); tool calls and tool results are emitted once each
- `"custom"` — forwarded from `StreamWriter`
- `"end"` — stream finished (carries cumulative `usage` counted once per message id)
- `chat(message, thread_id)` — synchronous, returns final text
- `stream(message, thread_id)`yields `StreamEvent` aligned with LangGraph SSE protocol:
- `"values"` — full state snapshot (title, messages, artifacts)
- `"messages-tuple"` — per-message update (AI text, tool calls, tool results)
- `"end"` — stream finished
- Agent created lazily via `create_agent()` + `_build_middlewares()`, same as `make_lead_agent`
- Supports `checkpointer` parameter for state persistence across turns
- `reset_agent()` forces agent recreation (e.g. after memory or skill changes)
- See [docs/STREAMING.md](docs/STREAMING.md) for the full design: why Gateway and DeerFlowClient are parallel paths, LangGraph's `stream_mode` semantics, the per-id dedup invariants, and regression testing strategy
**Gateway Equivalent Methods** (replaces Gateway API):
@@ -464,25 +436,8 @@ make dev
This starts all services and makes the application available at `http://localhost:2026`.
**All startup modes:**
| | **Local Foreground** | **Local Daemon** | **Docker Dev** | **Docker Prod** |
|---|---|---|---|---|
| **Dev** | `./scripts/serve.sh --dev`<br/>`make dev` | `./scripts/serve.sh --dev --daemon`<br/>`make dev-daemon` | `./scripts/docker.sh start`<br/>`make docker-start` | — |
| **Dev + Gateway** | `./scripts/serve.sh --dev --gateway`<br/>`make dev-pro` | `./scripts/serve.sh --dev --gateway --daemon`<br/>`make dev-daemon-pro` | `./scripts/docker.sh start --gateway`<br/>`make docker-start-pro` | — |
| **Prod** | `./scripts/serve.sh --prod`<br/>`make start` | `./scripts/serve.sh --prod --daemon`<br/>`make start-daemon` | — | `./scripts/deploy.sh`<br/>`make up` |
| **Prod + Gateway** | `./scripts/serve.sh --prod --gateway`<br/>`make start-pro` | `./scripts/serve.sh --prod --gateway --daemon`<br/>`make start-daemon-pro` | — | `./scripts/deploy.sh --gateway`<br/>`make up-pro` |
| Action | Local | Docker Dev | Docker Prod |
|---|---|---|---|
| **Stop** | `./scripts/serve.sh --stop`<br/>`make stop` | `./scripts/docker.sh stop`<br/>`make docker-stop` | `./scripts/deploy.sh down`<br/>`make down` |
| **Restart** | `./scripts/serve.sh --restart [flags]` | `./scripts/docker.sh restart` | — |
Gateway mode embeds the agent runtime in Gateway, no LangGraph server.
**Nginx routing**:
- Standard mode: `/api/langgraph/*` → LangGraph Server (2024)
- Gateway mode: `/api/langgraph/*` → Gateway embedded runtime (8001) (via envsubst)
- `/api/langgraph/*` → LangGraph Server (2024)
- `/api/*` (other) → Gateway API (8001)
- `/` (non-API) → Frontend (3000)
+9 -48
View File
@@ -1,21 +1,14 @@
# Backend Dockerfile — multi-stage build
# Stage 1 (builder): compiles native Python extensions with build-essential
# Stage 2 (dev): retains toolchain for dev containers (uv sync at startup)
# Stage 3 (runtime): clean image without compiler toolchain for production
# Backend Development Dockerfile
# UV source image (override for restricted networks that cannot reach ghcr.io)
ARG UV_IMAGE=ghcr.io/astral-sh/uv:0.7.20
FROM ${UV_IMAGE} AS uv-source
# ── Stage 1: Builder ──────────────────────────────────────────────────────────
FROM python:3.12-slim-bookworm AS builder
FROM python:3.12-slim-bookworm
ARG NODE_MAJOR=22
ARG APT_MIRROR
ARG UV_INDEX_URL
# Optional extras to install (e.g. "postgres" for PostgreSQL support)
# Usage: docker build --build-arg UV_EXTRAS=postgres ...
ARG UV_EXTRAS
# Optionally override apt mirror for restricted networks (e.g. APT_MIRROR=mirrors.aliyun.com)
RUN if [ -n "${APT_MIRROR}" ]; then \
@@ -23,7 +16,7 @@ RUN if [ -n "${APT_MIRROR}" ]; then \
sed -i "s|deb.debian.org|${APT_MIRROR}|g" /etc/apt/sources.list 2>/dev/null || true; \
fi
# Install build tools + Node.js (build-essential needed for native Python extensions)
# Install system dependencies + Node.js (provides npx for MCP servers)
RUN apt-get update && apt-get install -y \
curl \
build-essential \
@@ -36,56 +29,24 @@ RUN apt-get update && apt-get install -y \
&& apt-get install -y nodejs \
&& rm -rf /var/lib/apt/lists/*
# Install Docker CLI (for DooD: allows starting sandbox containers via host Docker socket)
COPY --from=docker:cli /usr/local/bin/docker /usr/local/bin/docker
# Install uv (source image overridable via UV_IMAGE build arg)
COPY --from=uv-source /uv /uvx /usr/local/bin/
# Set working directory
WORKDIR /app
# Copy backend source code
# Copy frontend source code
COPY backend ./backend
# Install dependencies with cache mount
# When UV_EXTRAS is set (e.g. "postgres"), installs optional dependencies.
RUN --mount=type=cache,target=/root/.cache/uv \
sh -c "cd backend && UV_INDEX_URL=${UV_INDEX_URL:-https://pypi.org/simple} uv sync ${UV_EXTRAS:+--extra $UV_EXTRAS}"
# ── Stage 2: Dev ──────────────────────────────────────────────────────────────
# Retains compiler toolchain from builder so startup-time `uv sync` can build
# source distributions in development containers.
FROM builder AS dev
# Install Docker CLI (for DooD: allows starting sandbox containers via host Docker socket)
COPY --from=docker:cli /usr/local/bin/docker /usr/local/bin/docker
EXPOSE 8001 2024
CMD ["sh", "-c", "cd backend && PYTHONPATH=. uv run uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001"]
# ── Stage 3: Runtime ──────────────────────────────────────────────────────────
# Clean image without build-essential — reduces size (~200 MB) and attack surface.
FROM python:3.12-slim-bookworm
# Copy Node.js runtime from builder (provides npx for MCP servers)
COPY --from=builder /usr/bin/node /usr/bin/node
COPY --from=builder /usr/lib/node_modules /usr/lib/node_modules
RUN ln -s ../lib/node_modules/npm/bin/npm-cli.js /usr/bin/npm \
&& ln -s ../lib/node_modules/npm/bin/npx-cli.js /usr/bin/npx
# Install Docker CLI (for DooD: allows starting sandbox containers via host Docker socket)
COPY --from=docker:cli /usr/local/bin/docker /usr/local/bin/docker
# Install uv (source image overridable via UV_IMAGE build arg)
COPY --from=uv-source /uv /uvx /usr/local/bin/
# Set working directory
WORKDIR /app
# Copy backend with pre-built virtualenv from builder
COPY --from=builder /app/backend ./backend
sh -c "cd backend && UV_INDEX_URL=${UV_INDEX_URL:-https://pypi.org/simple} uv sync"
# Expose ports (gateway: 8001, langgraph: 2024)
EXPOSE 8001 2024
# Default command (can be overridden in docker-compose)
CMD ["sh", "-c", "cd backend && PYTHONPATH=. uv run --no-sync uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001"]
CMD ["sh", "-c", "cd backend && PYTHONPATH=. uv run uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001"]
+2 -2
View File
@@ -2,13 +2,13 @@ install:
uv sync
dev:
uv run langgraph dev --no-browser --no-reload --n-jobs-per-worker 10
uv run langgraph dev --no-browser --allow-blocking --no-reload
gateway:
PYTHONPATH=. uv run uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001
test:
PYTHONPATH=. uv run pytest tests/unittest -v
PYTHONPATH=. uv run pytest tests/ -v
lint:
uvx ruff check .
+1 -23
View File
@@ -78,7 +78,6 @@ Per-thread isolated execution with virtual path translation:
- **Virtual paths**: `/mnt/user-data/{workspace,uploads,outputs}` → thread-specific physical directories
- **Skills path**: `/mnt/skills``deer-flow/skills/` directory
- **Skills loading**: Recursively discovers nested `SKILL.md` files under `skills/{public,custom}` and preserves nested container paths
- **File-write safety**: `str_replace` serializes read-modify-write per `(sandbox.id, path)` so isolated sandboxes keep concurrency even when virtual paths match
- **Tools**: `bash`, `ls`, `read_file`, `write_file`, `str_replace` (`bash` is disabled by default when using `LocalSandboxProvider`; use `AioSandboxProvider` for isolated shell access)
### Subagent System
@@ -331,28 +330,7 @@ LANGSMITH_PROJECT=xxx
**Legacy variables:** The `LANGCHAIN_TRACING_V2`, `LANGCHAIN_API_KEY`, `LANGCHAIN_PROJECT`, and `LANGCHAIN_ENDPOINT` variables are also supported for backward compatibility. `LANGSMITH_*` variables take precedence when both are set.
### Langfuse Tracing
DeerFlow also supports [Langfuse](https://langfuse.com) observability for LangChain-compatible runs.
Add the following to your `.env` file:
```bash
LANGFUSE_TRACING=true
LANGFUSE_PUBLIC_KEY=pk-lf-xxxxxxxxxxxxxxxx
LANGFUSE_SECRET_KEY=sk-lf-xxxxxxxxxxxxxxxx
LANGFUSE_BASE_URL=https://cloud.langfuse.com
```
If you are using a self-hosted Langfuse deployment, set `LANGFUSE_BASE_URL` to your Langfuse host.
### Dual Provider Behavior
If both LangSmith and Langfuse are enabled, DeerFlow initializes and attaches both callbacks so the same run data is reported to both systems.
If a provider is explicitly enabled but required credentials are missing, or the provider callback cannot be initialized, DeerFlow raises an error when tracing is initialized during model creation instead of silently disabling tracing.
**Docker:** In `docker-compose.yaml`, tracing is disabled by default (`LANGSMITH_TRACING=false`). Set `LANGSMITH_TRACING=true` and/or `LANGFUSE_TRACING=true` in your `.env`, together with the required credentials, to enable tracing in containerized deployments.
**Docker:** In `docker-compose.yaml`, tracing is disabled by default (`LANGSMITH_TRACING=false`). Set `LANGSMITH_TRACING=true` and provide `LANGSMITH_API_KEY` in your `.env` to enable it in containerized deployments.
---
-18
View File
@@ -106,21 +106,3 @@ class Channel(ABC):
logger.warning("[%s] file upload skipped for %s", self.name, attachment.filename)
except Exception:
logger.exception("[%s] failed to upload file %s", self.name, attachment.filename)
async def receive_file(self, msg: InboundMessage, thread_id: str) -> InboundMessage:
"""
Optionally process and materialize inbound file attachments for this channel.
By default, this method does nothing and simply returns the original message.
Subclasses (e.g. FeishuChannel) may override this to download files (images, documents, etc)
referenced in msg.files, save them to the sandbox, and update msg.text to include
the sandbox file paths for downstream model consumption.
Args:
msg: The inbound message, possibly containing file metadata in msg.files.
thread_id: The resolved DeerFlow thread ID for sandbox path context.
Returns:
The (possibly modified) InboundMessage, with text and/or files updated as needed.
"""
return msg
-20
View File
@@ -1,20 +0,0 @@
"""Shared command definitions used by all channel implementations.
Keeping the authoritative command set in one place ensures that channel
parsers (e.g. Feishu) and the ChannelManager dispatcher stay in sync
automatically — adding or removing a command here is the single edit
required.
"""
from __future__ import annotations
KNOWN_CHANNEL_COMMANDS: frozenset[str] = frozenset(
{
"/bootstrap",
"/new",
"/status",
"/models",
"/memory",
"/help",
}
)
+6 -183
View File
@@ -5,27 +5,15 @@ from __future__ import annotations
import asyncio
import json
import logging
import re
import threading
from typing import Any, Literal
from typing import Any
from app.plugins.auth.security.actor_context import bind_user_actor_context
from app.channels.base import Channel
from app.channels.commands import KNOWN_CHANNEL_COMMANDS
from app.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
from deerflow.config.paths import VIRTUAL_PATH_PREFIX, get_paths
from deerflow.runtime.actor_context import get_effective_user_id
from deerflow.sandbox.sandbox_provider import get_sandbox_provider
from app.channels.message_bus import InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
logger = logging.getLogger(__name__)
def _is_feishu_command(text: str) -> bool:
if not text.startswith("/"):
return False
return text.split(maxsplit=1)[0].lower() in KNOWN_CHANNEL_COMMANDS
class FeishuChannel(Channel):
"""Feishu/Lark IM channel using the ``lark-oapi`` WebSocket client.
@@ -61,8 +49,6 @@ class FeishuChannel(Channel):
self._CreateFileRequestBody = None
self._CreateImageRequest = None
self._CreateImageRequestBody = None
self._GetMessageResourceRequest = None
self._thread_lock = threading.Lock()
async def start(self) -> None:
if self._running:
@@ -80,7 +66,6 @@ class FeishuChannel(Channel):
CreateMessageRequest,
CreateMessageRequestBody,
Emoji,
GetMessageResourceRequest,
PatchMessageRequest,
PatchMessageRequestBody,
ReplyMessageRequest,
@@ -104,7 +89,6 @@ class FeishuChannel(Channel):
self._CreateFileRequestBody = CreateFileRequestBody
self._CreateImageRequest = CreateImageRequest
self._CreateImageRequestBody = CreateImageRequestBody
self._GetMessageResourceRequest = GetMessageResourceRequest
app_id = self.config.get("app_id", "")
app_secret = self.config.get("app_secret", "")
@@ -215,9 +199,7 @@ class FeishuChannel(Channel):
await asyncio.sleep(delay)
logger.error("[Feishu] send failed after %d attempts: %s", _max_retries, last_exc)
if last_exc is None:
raise RuntimeError("Feishu send failed without an exception from any attempt")
raise last_exc
raise last_exc # type: ignore[misc]
async def send_file(self, msg: OutboundMessage, attachment: ResolvedAttachment) -> bool:
if not self._api_client:
@@ -284,134 +266,6 @@ class FeishuChannel(Channel):
raise RuntimeError(f"Feishu file upload failed: code={response.code}, msg={response.msg}")
return response.data.file_key
async def receive_file(self, msg: InboundMessage, thread_id: str) -> InboundMessage:
"""Download a Feishu file into the thread uploads directory.
Returns the sandbox virtual path when the image is persisted successfully.
"""
if not msg.thread_ts:
logger.warning("[Feishu] received file message without thread_ts, cannot associate with conversation: %s", msg)
return msg
files = msg.files
if not files:
logger.warning("[Feishu] received message with no files: %s", msg)
return msg
text = msg.text
for file in files:
if file.get("image_key"):
virtual_path = await self._receive_single_file(
msg.thread_ts,
file["image_key"],
"image",
thread_id,
user_id=msg.user_id,
)
text = text.replace("[image]", virtual_path, 1)
elif file.get("file_key"):
virtual_path = await self._receive_single_file(
msg.thread_ts,
file["file_key"],
"file",
thread_id,
user_id=msg.user_id,
)
text = text.replace("[file]", virtual_path, 1)
msg.text = text
return msg
async def _receive_single_file(
self,
message_id: str,
file_key: str,
type: Literal["image", "file"],
thread_id: str,
*,
user_id: str | None = None,
) -> str:
request = self._GetMessageResourceRequest.builder().message_id(message_id).file_key(file_key).type(type).build()
def inner():
return self._api_client.im.v1.message_resource.get(request)
try:
response = await asyncio.to_thread(inner)
except Exception:
logger.exception("[Feishu] resource get request failed for resource_key=%s type=%s", file_key, type)
return f"Failed to obtain the [{type}]"
if not response.success():
logger.warning(
"[Feishu] resource get failed: resource_key=%s, type=%s, code=%s, msg=%s, log_id=%s ",
file_key,
type,
response.code,
response.msg,
response.get_log_id(),
)
return f"Failed to obtain the [{type}]"
image_stream = getattr(response, "file", None)
if image_stream is None:
logger.warning("[Feishu] resource get returned no file stream: resource_key=%s, type=%s", file_key, type)
return f"Failed to obtain the [{type}]"
try:
content: bytes = await asyncio.to_thread(image_stream.read)
except Exception:
logger.exception("[Feishu] failed to read resource stream: resource_key=%s, type=%s", file_key, type)
return f"Failed to obtain the [{type}]"
if not content:
logger.warning("[Feishu] empty resource content: resource_key=%s, type=%s", file_key, type)
return f"Failed to obtain the [{type}]"
paths = get_paths()
with bind_user_actor_context(user_id):
effective_user_id = get_effective_user_id()
paths.ensure_thread_dirs(thread_id, user_id=effective_user_id)
uploads_dir = paths.sandbox_uploads_dir(thread_id, user_id=effective_user_id).resolve()
ext = "png" if type == "image" else "bin"
raw_filename = getattr(response, "file_name", "") or f"feishu_{file_key[-12:]}.{ext}"
# Sanitize filename: preserve extension, replace path chars in name part
if "." in raw_filename:
name_part, ext = raw_filename.rsplit(".", 1)
name_part = re.sub(r"[./\\]", "_", name_part)
filename = f"{name_part}.{ext}"
else:
filename = re.sub(r"[./\\]", "_", raw_filename)
resolved_target = uploads_dir / filename
def down_load():
# use thread_lock to avoid filename conflicts when writing
with self._thread_lock:
resolved_target.write_bytes(content)
try:
await asyncio.to_thread(down_load)
except Exception:
logger.exception("[Feishu] failed to persist downloaded resource: %s, type=%s", resolved_target, type)
return f"Failed to obtain the [{type}]"
virtual_path = f"{VIRTUAL_PATH_PREFIX}/uploads/{resolved_target.name}"
try:
sandbox_provider = get_sandbox_provider()
sandbox_id = sandbox_provider.acquire(thread_id)
if sandbox_id != "local":
sandbox = sandbox_provider.get(sandbox_id)
if sandbox is None:
logger.warning("[Feishu] sandbox not found for thread_id=%s", thread_id)
return f"Failed to obtain the [{type}]"
sandbox.update_file(virtual_path, content)
except Exception:
logger.exception("[Feishu] failed to sync resource into non-local sandbox: %s", virtual_path)
return f"Failed to obtain the [{type}]"
logger.info("[Feishu] downloaded resource mapped: file_key=%s -> %s", file_key, virtual_path)
return virtual_path
# -- message formatting ------------------------------------------------
@staticmethod
@@ -616,28 +470,9 @@ class FeishuChannel(Channel):
# Parse message content
content = json.loads(message.content)
# files_list store the any-file-key in feishu messages, which can be used to download the file content later
# In Feishu channel, image_keys are independent of file_keys.
# The file_key includes files, videos, and audio, but does not include stickers.
files_list = []
if "text" in content:
# Handle plain text messages
text = content["text"]
elif "file_key" in content:
file_key = content.get("file_key")
if isinstance(file_key, str) and file_key:
files_list.append({"file_key": file_key})
text = "[file]"
else:
text = ""
elif "image_key" in content:
image_key = content.get("image_key")
if isinstance(image_key, str) and image_key:
files_list.append({"image_key": image_key})
text = "[image]"
else:
text = ""
elif "content" in content and isinstance(content["content"], list):
# Handle rich-text messages with a top-level "content" list (e.g., topic groups/posts)
text_paragraphs: list[str] = []
@@ -651,16 +486,6 @@ class FeishuChannel(Channel):
text_value = element.get("text", "")
if text_value:
paragraph_text_parts.append(text_value)
elif element.get("tag") == "img":
image_key = element.get("image_key")
if isinstance(image_key, str) and image_key:
files_list.append({"image_key": image_key})
paragraph_text_parts.append("[image]")
elif element.get("tag") in ("file", "media"):
file_key = element.get("file_key")
if isinstance(file_key, str) and file_key:
files_list.append({"file_key": file_key})
paragraph_text_parts.append("[file]")
if paragraph_text_parts:
# Join text segments within a paragraph with spaces to avoid "helloworld"
text_paragraphs.append(" ".join(paragraph_text_parts))
@@ -680,13 +505,12 @@ class FeishuChannel(Channel):
text[:100] if text else "",
)
if not (text or files_list):
if not text:
logger.info("[Feishu] empty text, ignoring message")
return
# Only treat known slash commands as commands; absolute paths and
# other slash-prefixed text should be handled as normal chat.
if _is_feishu_command(text):
# Check if it's a command
if text.startswith("/"):
msg_type = InboundMessageType.COMMAND
else:
msg_type = InboundMessageType.CHAT
@@ -700,7 +524,6 @@ class FeishuChannel(Channel):
text=text,
msg_type=msg_type,
thread_ts=msg_id,
files=files_list,
metadata={"message_id": msg_id, "root_id": root_id},
)
inbound.topic_id = topic_id
+36 -232
View File
@@ -7,18 +7,13 @@ import logging
import mimetypes
import re
import time
from collections.abc import Awaitable, Callable, Mapping
from pathlib import Path
from collections.abc import Mapping
from typing import Any
import httpx
from langgraph_sdk.errors import ConflictError
from app.plugins.auth.security.actor_context import bind_user_actor_context
from app.channels.commands import KNOWN_CHANNEL_COMMANDS
from app.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
from app.channels.store import ChannelStore
from deerflow.runtime.actor_context import get_effective_user_id
logger = logging.getLogger(__name__)
@@ -40,67 +35,8 @@ CHANNEL_CAPABILITIES = {
"feishu": {"supports_streaming": True},
"slack": {"supports_streaming": False},
"telegram": {"supports_streaming": False},
"wechat": {"supports_streaming": False},
"wecom": {"supports_streaming": True},
}
InboundFileReader = Callable[[dict[str, Any], httpx.AsyncClient], Awaitable[bytes | None]]
INBOUND_FILE_READERS: dict[str, InboundFileReader] = {}
def register_inbound_file_reader(channel_name: str, reader: InboundFileReader) -> None:
INBOUND_FILE_READERS[channel_name] = reader
async def _read_http_inbound_file(file_info: dict[str, Any], client: httpx.AsyncClient) -> bytes | None:
url = file_info.get("url")
if not isinstance(url, str) or not url:
return None
resp = await client.get(url)
resp.raise_for_status()
return resp.content
async def _read_wecom_inbound_file(file_info: dict[str, Any], client: httpx.AsyncClient) -> bytes | None:
data = await _read_http_inbound_file(file_info, client)
if data is None:
return None
aeskey = file_info.get("aeskey") if isinstance(file_info.get("aeskey"), str) else None
if not aeskey:
return data
try:
from aibot.crypto_utils import decrypt_file
except Exception:
logger.exception("[Manager] failed to import WeCom decrypt_file")
return None
return decrypt_file(data, aeskey)
async def _read_wechat_inbound_file(file_info: dict[str, Any], client: httpx.AsyncClient) -> bytes | None:
raw_path = file_info.get("path")
if isinstance(raw_path, str) and raw_path.strip():
try:
return await asyncio.to_thread(Path(raw_path).read_bytes)
except OSError:
logger.exception("[Manager] failed to read WeChat inbound file from local path: %s", raw_path)
return None
full_url = file_info.get("full_url")
if isinstance(full_url, str) and full_url.strip():
return await _read_http_inbound_file({"url": full_url}, client)
return None
register_inbound_file_reader("wecom", _read_wecom_inbound_file)
register_inbound_file_reader("wechat", _read_wechat_inbound_file)
class InvalidChannelSessionConfigError(ValueError):
"""Raised when IM channel session overrides contain invalid agent config."""
@@ -329,7 +265,7 @@ def _format_artifact_text(artifacts: list[str]) -> str:
_OUTPUTS_VIRTUAL_PREFIX = "/mnt/user-data/outputs/"
def _resolve_attachments(thread_id: str, artifacts: list[str], *, user_id: str | None = None) -> list[ResolvedAttachment]:
def _resolve_attachments(thread_id: str, artifacts: list[str]) -> list[ResolvedAttachment]:
"""Resolve virtual artifact paths to host filesystem paths with metadata.
Only paths under ``/mnt/user-data/outputs/`` are accepted; any other
@@ -343,40 +279,38 @@ def _resolve_attachments(thread_id: str, artifacts: list[str], *, user_id: str |
attachments: list[ResolvedAttachment] = []
paths = get_paths()
with bind_user_actor_context(user_id):
effective_user_id = get_effective_user_id()
outputs_dir = paths.sandbox_outputs_dir(thread_id, user_id=effective_user_id).resolve()
for virtual_path in artifacts:
# Security: only allow files from the agent outputs directory
if not virtual_path.startswith(_OUTPUTS_VIRTUAL_PREFIX):
logger.warning("[Manager] rejected non-outputs artifact path: %s", virtual_path)
continue
outputs_dir = paths.sandbox_outputs_dir(thread_id).resolve()
for virtual_path in artifacts:
# Security: only allow files from the agent outputs directory
if not virtual_path.startswith(_OUTPUTS_VIRTUAL_PREFIX):
logger.warning("[Manager] rejected non-outputs artifact path: %s", virtual_path)
continue
try:
actual = paths.resolve_virtual_path(thread_id, virtual_path)
# Verify the resolved path is actually under the outputs directory
# (guards against path-traversal even after prefix check)
try:
actual = paths.resolve_virtual_path(thread_id, virtual_path, user_id=effective_user_id)
# Verify the resolved path is actually under the outputs directory
# (guards against path-traversal even after prefix check)
try:
actual.resolve().relative_to(outputs_dir)
except ValueError:
logger.warning("[Manager] artifact path escapes outputs dir: %s -> %s", virtual_path, actual)
continue
if not actual.is_file():
logger.warning("[Manager] artifact not found on disk: %s -> %s", virtual_path, actual)
continue
mime, _ = mimetypes.guess_type(str(actual))
mime = mime or "application/octet-stream"
attachments.append(
ResolvedAttachment(
virtual_path=virtual_path,
actual_path=actual,
filename=actual.name,
mime_type=mime,
size=actual.stat().st_size,
is_image=mime.startswith("image/"),
)
actual.resolve().relative_to(outputs_dir)
except ValueError:
logger.warning("[Manager] artifact path escapes outputs dir: %s -> %s", virtual_path, actual)
continue
if not actual.is_file():
logger.warning("[Manager] artifact not found on disk: %s -> %s", virtual_path, actual)
continue
mime, _ = mimetypes.guess_type(str(actual))
mime = mime or "application/octet-stream"
attachments.append(
ResolvedAttachment(
virtual_path=virtual_path,
actual_path=actual,
filename=actual.name,
mime_type=mime,
size=actual.stat().st_size,
is_image=mime.startswith("image/"),
)
except (ValueError, OSError) as exc:
logger.warning("[Manager] failed to resolve artifact %s: %s", virtual_path, exc)
)
except (ValueError, OSError) as exc:
logger.warning("[Manager] failed to resolve artifact %s: %s", virtual_path, exc)
return attachments
@@ -384,15 +318,13 @@ def _prepare_artifact_delivery(
thread_id: str,
response_text: str,
artifacts: list[str],
*,
user_id: str | None = None,
) -> tuple[str, list[ResolvedAttachment]]:
"""Resolve attachments and append filename fallbacks to the text response."""
attachments: list[ResolvedAttachment] = []
if not artifacts:
return response_text, attachments
attachments = _resolve_attachments(thread_id, artifacts, user_id=user_id)
attachments = _resolve_attachments(thread_id, artifacts)
resolved_virtuals = {attachment.virtual_path for attachment in attachments}
unresolved = [path for path in artifacts if path not in resolved_virtuals]
@@ -409,106 +341,6 @@ def _prepare_artifact_delivery(
return response_text, attachments
async def _ingest_inbound_files(thread_id: str, msg: InboundMessage) -> list[dict[str, Any]]:
if not msg.files:
return []
from deerflow.uploads.manager import claim_unique_filename, ensure_uploads_dir, normalize_filename
with bind_user_actor_context(msg.user_id):
uploads_dir = ensure_uploads_dir(thread_id)
seen_names = {entry.name for entry in uploads_dir.iterdir() if entry.is_file()}
created: list[dict[str, Any]] = []
file_reader = INBOUND_FILE_READERS.get(msg.channel_name, _read_http_inbound_file)
async with httpx.AsyncClient(timeout=httpx.Timeout(20.0)) as client:
for idx, f in enumerate(msg.files):
if not isinstance(f, dict):
continue
ftype = f.get("type") if isinstance(f.get("type"), str) else "file"
filename = f.get("filename") if isinstance(f.get("filename"), str) else ""
try:
data = await file_reader(f, client)
except Exception:
logger.exception(
"[Manager] failed to read inbound file: channel=%s, file=%s",
msg.channel_name,
f.get("url") or filename or idx,
)
continue
if data is None:
logger.warning(
"[Manager] inbound file reader returned no data: channel=%s, file=%s",
msg.channel_name,
f.get("url") or filename or idx,
)
continue
if not filename:
ext = ".bin"
if ftype == "image":
ext = ".png"
filename = f"{msg.thread_ts or 'msg'}_{idx}{ext}"
try:
safe_name = claim_unique_filename(normalize_filename(filename), seen_names)
except ValueError:
logger.warning(
"[Manager] skipping inbound file with unsafe filename: channel=%s, file=%r",
msg.channel_name,
filename,
)
continue
dest = uploads_dir / safe_name
try:
dest.write_bytes(data)
except Exception:
logger.exception("[Manager] failed to write inbound file: %s", dest)
continue
created.append(
{
"filename": safe_name,
"size": len(data),
"path": f"/mnt/user-data/uploads/{safe_name}",
"is_image": ftype == "image",
}
)
return created
def _format_uploaded_files_block(files: list[dict[str, Any]]) -> str:
lines = [
"<uploaded_files>",
"The following files were uploaded in this message:",
"",
]
if not files:
lines.append("(empty)")
else:
for f in files:
filename = f.get("filename", "")
size = int(f.get("size") or 0)
size_kb = size / 1024 if size else 0
size_str = f"{size_kb:.1f} KB" if size_kb < 1024 else f"{size_kb / 1024:.1f} MB"
path = f.get("path", "")
is_image = bool(f.get("is_image"))
file_kind = "image" if is_image else "file"
lines.append(f"- {filename} ({size_str})")
lines.append(f" Type: {file_kind}")
lines.append(f" Path: {path}")
lines.append("")
lines.append("Use `read_file` for text-based files and documents.")
lines.append("Use `view_image` for image files (jpg, jpeg, png, webp) so the model can inspect the image content.")
lines.append("</uploaded_files>")
return "\n".join(lines)
class ChannelManager:
"""Core dispatcher that bridges IM channels to the DeerFlow agent.
@@ -701,25 +533,8 @@ class ChannelManager:
thread_id = await self._create_thread(client, msg)
assistant_id, run_config, run_context = self._resolve_run_params(msg, thread_id)
# If the inbound message contains file attachments, let the channel
# materialize (download) them and update msg.text to include sandbox file paths.
# This enables downstream models to access user-uploaded files by path.
# Channels that do not support file download will simply return the original message.
if msg.files:
from .service import get_channel_service
service = get_channel_service()
channel = service.get_channel(msg.channel_name) if service else None
logger.info("[Manager] preparing receive file context for %d attachments", len(msg.files))
msg = await channel.receive_file(msg, thread_id) if channel else msg
if extra_context:
run_context.update(extra_context)
uploaded = await _ingest_inbound_files(thread_id, msg)
if uploaded:
msg.text = f"{_format_uploaded_files_block(uploaded)}\n\n{msg.text}".strip()
if self._channel_supports_streaming(msg.channel_name):
await self._handle_streaming_chat(
client,
@@ -750,12 +565,7 @@ class ChannelManager:
len(artifacts),
)
response_text, attachments = _prepare_artifact_delivery(
thread_id,
response_text,
artifacts,
user_id=msg.user_id,
)
response_text, attachments = _prepare_artifact_delivery(thread_id, response_text, artifacts)
if not response_text:
if attachments:
@@ -846,12 +656,7 @@ class ChannelManager:
result = last_values if last_values is not None else {"messages": [{"type": "ai", "content": latest_text}]}
response_text = _extract_response_text(result)
artifacts = _extract_artifacts(result)
response_text, attachments = _prepare_artifact_delivery(
thread_id,
response_text,
artifacts,
user_id=msg.user_id,
)
response_text, attachments = _prepare_artifact_delivery(thread_id, response_text, artifacts)
if not response_text:
if attachments:
@@ -930,8 +735,7 @@ class ChannelManager:
"/help — Show this help"
)
else:
available = " | ".join(sorted(KNOWN_CHANNEL_COMMANDS))
reply = f"Unknown command: /{command}. Available commands: {available}"
reply = f"Unknown command: /{command}. Type /help for available commands."
outbound = OutboundMessage(
channel_name=msg.channel_name,
-7
View File
@@ -6,7 +6,6 @@ import logging
import os
from typing import Any
from app.channels.base import Channel
from app.channels.manager import DEFAULT_GATEWAY_URL, DEFAULT_LANGGRAPH_URL, ChannelManager
from app.channels.message_bus import MessageBus
from app.channels.store import ChannelStore
@@ -18,8 +17,6 @@ _CHANNEL_REGISTRY: dict[str, str] = {
"feishu": "app.channels.feishu:FeishuChannel",
"slack": "app.channels.slack:SlackChannel",
"telegram": "app.channels.telegram:TelegramChannel",
"wechat": "app.channels.wechat:WechatChannel",
"wecom": "app.channels.wecom:WeComChannel",
}
_CHANNELS_LANGGRAPH_URL_ENV = "DEER_FLOW_CHANNELS_LANGGRAPH_URL"
@@ -166,10 +163,6 @@ class ChannelService:
"channels": channels_status,
}
def get_channel(self, name: str) -> Channel | None:
"""Return a running channel instance by name when available."""
return self._channels.get(name)
# -- singleton access -------------------------------------------------------
+2 -4
View File
@@ -30,7 +30,7 @@ class SlackChannel(Channel):
self._socket_client = None
self._web_client = None
self._loop: asyncio.AbstractEventLoop | None = None
self._allowed_users: set[str] = {str(user_id) for user_id in config.get("allowed_users", [])}
self._allowed_users: set[str] = set(config.get("allowed_users", []))
async def start(self) -> None:
if self._running:
@@ -126,9 +126,7 @@ class SlackChannel(Channel):
)
except Exception:
pass
if last_exc is None:
raise RuntimeError("Slack send failed without an exception from any attempt")
raise last_exc
raise last_exc # type: ignore[misc]
async def send_file(self, msg: OutboundMessage, attachment: ResolvedAttachment) -> bool:
if not self._web_client:
+1 -3
View File
@@ -125,9 +125,7 @@ class TelegramChannel(Channel):
await asyncio.sleep(delay)
logger.error("[Telegram] send failed after %d attempts: %s", _max_retries, last_exc)
if last_exc is None:
raise RuntimeError("Telegram send failed without an exception from any attempt")
raise last_exc
raise last_exc # type: ignore[misc]
async def send_file(self, msg: OutboundMessage, attachment: ResolvedAttachment) -> bool:
if not self._application:
File diff suppressed because it is too large Load Diff
-394
View File
@@ -1,394 +0,0 @@
from __future__ import annotations
import asyncio
import base64
import hashlib
import logging
from collections.abc import Awaitable, Callable
from typing import Any, cast
from app.channels.base import Channel
from app.channels.message_bus import (
InboundMessageType,
MessageBus,
OutboundMessage,
ResolvedAttachment,
)
logger = logging.getLogger(__name__)
class WeComChannel(Channel):
def __init__(self, bus: MessageBus, config: dict[str, Any]) -> None:
super().__init__(name="wecom", bus=bus, config=config)
self._bot_id: str | None = None
self._bot_secret: str | None = None
self._ws_client = None
self._ws_task: asyncio.Task | None = None
self._ws_frames: dict[str, dict[str, Any]] = {}
self._ws_stream_ids: dict[str, str] = {}
self._working_message = "Working on it..."
def _clear_ws_context(self, thread_ts: str | None) -> None:
if not thread_ts:
return
self._ws_frames.pop(thread_ts, None)
self._ws_stream_ids.pop(thread_ts, None)
async def _send_ws_upload_command(self, req_id: str, body: dict[str, Any], cmd: str) -> dict[str, Any]:
if not self._ws_client:
raise RuntimeError("WeCom WebSocket client is not available")
ws_manager = getattr(self._ws_client, "_ws_manager", None)
send_reply = getattr(ws_manager, "send_reply", None)
if not callable(send_reply):
raise RuntimeError("Installed wecom-aibot-python-sdk does not expose the WebSocket media upload API expected by DeerFlow. Use wecom-aibot-python-sdk==0.1.6 or update the adapter.")
send_reply_async = cast(Callable[[str, dict[str, Any], str], Awaitable[dict[str, Any]]], send_reply)
return await send_reply_async(req_id, body, cmd)
async def start(self) -> None:
if self._running:
return
bot_id = self.config.get("bot_id")
bot_secret = self.config.get("bot_secret")
working_message = self.config.get("working_message")
self._bot_id = bot_id if isinstance(bot_id, str) and bot_id else None
self._bot_secret = bot_secret if isinstance(bot_secret, str) and bot_secret else None
self._working_message = working_message if isinstance(working_message, str) and working_message else "Working on it..."
if not self._bot_id or not self._bot_secret:
logger.error("WeCom channel requires bot_id and bot_secret")
return
try:
from aibot import WSClient, WSClientOptions
except ImportError:
logger.error("wecom-aibot-python-sdk is not installed. Install it with: uv add wecom-aibot-python-sdk")
return
else:
self._ws_client = WSClient(WSClientOptions(bot_id=self._bot_id, secret=self._bot_secret, logger=logger))
self._ws_client.on("message.text", self._on_ws_text)
self._ws_client.on("message.mixed", self._on_ws_mixed)
self._ws_client.on("message.image", self._on_ws_image)
self._ws_client.on("message.file", self._on_ws_file)
self._ws_task = asyncio.create_task(self._ws_client.connect())
self._running = True
self.bus.subscribe_outbound(self._on_outbound)
logger.info("WeCom channel started")
async def stop(self) -> None:
self._running = False
self.bus.unsubscribe_outbound(self._on_outbound)
if self._ws_task:
try:
self._ws_task.cancel()
except Exception:
pass
self._ws_task = None
if self._ws_client:
try:
self._ws_client.disconnect()
except Exception:
pass
self._ws_client = None
self._ws_frames.clear()
self._ws_stream_ids.clear()
logger.info("WeCom channel stopped")
async def send(self, msg: OutboundMessage, *, _max_retries: int = 3) -> None:
if self._ws_client:
await self._send_ws(msg, _max_retries=_max_retries)
return
logger.warning("[WeCom] send called but WebSocket client is not available")
async def _on_outbound(self, msg: OutboundMessage) -> None:
if msg.channel_name != self.name:
return
try:
await self.send(msg)
except Exception:
logger.exception("Failed to send outbound message on channel %s", self.name)
if msg.is_final:
self._clear_ws_context(msg.thread_ts)
return
for attachment in msg.attachments:
try:
success = await self.send_file(msg, attachment)
if not success:
logger.warning("[%s] file upload skipped for %s", self.name, attachment.filename)
except Exception:
logger.exception("[%s] failed to upload file %s", self.name, attachment.filename)
if msg.is_final:
self._clear_ws_context(msg.thread_ts)
async def send_file(self, msg: OutboundMessage, attachment: ResolvedAttachment) -> bool:
if not msg.is_final:
return True
if not self._ws_client:
return False
if not msg.thread_ts:
return False
frame = self._ws_frames.get(msg.thread_ts)
if not frame:
return False
media_type = "image" if attachment.is_image else "file"
size_limit = 2 * 1024 * 1024 if attachment.is_image else 20 * 1024 * 1024
if attachment.size > size_limit:
logger.warning(
"[WeCom] %s too large (%d bytes), skipping: %s",
media_type,
attachment.size,
attachment.filename,
)
return False
try:
media_id = await self._upload_media_ws(
media_type=media_type,
filename=attachment.filename,
path=str(attachment.actual_path),
size=attachment.size,
)
if not media_id:
return False
body = {media_type: {"media_id": media_id}, "msgtype": media_type}
await self._ws_client.reply(frame, body)
logger.debug("[WeCom] %s sent via ws: %s", media_type, attachment.filename)
return True
except Exception:
logger.exception("[WeCom] failed to upload/send file via ws: %s", attachment.filename)
return False
async def _on_ws_text(self, frame: dict[str, Any]) -> None:
body = frame.get("body", {}) or {}
text = ((body.get("text") or {}).get("content") or "").strip()
quote = body.get("quote", {}).get("text", {}).get("content", "").strip()
if not text and not quote:
return
await self._publish_ws_inbound(frame, text + (f"\nQuote message: {quote}" if quote else ""))
async def _on_ws_mixed(self, frame: dict[str, Any]) -> None:
body = frame.get("body", {}) or {}
mixed = body.get("mixed") or {}
items = mixed.get("msg_item") or []
parts: list[str] = []
files: list[dict[str, Any]] = []
for item in items:
item_type = (item or {}).get("msgtype")
if item_type == "text":
content = (((item or {}).get("text") or {}).get("content") or "").strip()
if content:
parts.append(content)
elif item_type in ("image", "file"):
payload = (item or {}).get(item_type) or {}
url = payload.get("url")
aeskey = payload.get("aeskey")
if isinstance(url, str) and url:
files.append(
{
"type": item_type,
"url": url,
"aeskey": (aeskey if isinstance(aeskey, str) and aeskey else None),
}
)
text = "\n\n".join(parts).strip()
if not text and not files:
return
if not text:
text = "receive image/file"
await self._publish_ws_inbound(frame, text, files=files)
async def _on_ws_image(self, frame: dict[str, Any]) -> None:
body = frame.get("body", {}) or {}
image = body.get("image") or {}
url = image.get("url")
aeskey = image.get("aeskey")
if not isinstance(url, str) or not url:
return
await self._publish_ws_inbound(
frame,
"receive image ",
files=[
{
"type": "image",
"url": url,
"aeskey": aeskey if isinstance(aeskey, str) and aeskey else None,
}
],
)
async def _on_ws_file(self, frame: dict[str, Any]) -> None:
body = frame.get("body", {}) or {}
file_obj = body.get("file") or {}
url = file_obj.get("url")
aeskey = file_obj.get("aeskey")
if not isinstance(url, str) or not url:
return
await self._publish_ws_inbound(
frame,
"receive file",
files=[
{
"type": "file",
"url": url,
"aeskey": aeskey if isinstance(aeskey, str) and aeskey else None,
}
],
)
async def _publish_ws_inbound(
self,
frame: dict[str, Any],
text: str,
*,
files: list[dict[str, Any]] | None = None,
) -> None:
if not self._ws_client:
return
try:
from aibot import generate_req_id
except Exception:
return
body = frame.get("body", {}) or {}
msg_id = body.get("msgid")
if not msg_id:
return
user_id = (body.get("from") or {}).get("userid")
inbound_type = InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT
inbound = self._make_inbound(
chat_id=user_id, # keep user's conversation in memory
user_id=user_id,
text=text,
msg_type=inbound_type,
thread_ts=msg_id,
files=files or [],
metadata={"aibotid": body.get("aibotid"), "chattype": body.get("chattype")},
)
inbound.topic_id = user_id # keep the same thread
stream_id = generate_req_id("stream")
self._ws_frames[msg_id] = frame
self._ws_stream_ids[msg_id] = stream_id
try:
await self._ws_client.reply_stream(frame, stream_id, self._working_message, False)
except Exception:
pass
await self.bus.publish_inbound(inbound)
async def _send_ws(self, msg: OutboundMessage, *, _max_retries: int = 3) -> None:
if not self._ws_client:
return
try:
from aibot import generate_req_id
except Exception:
generate_req_id = None
if msg.thread_ts and msg.thread_ts in self._ws_frames:
frame = self._ws_frames[msg.thread_ts]
stream_id = self._ws_stream_ids.get(msg.thread_ts)
if not stream_id and generate_req_id:
stream_id = generate_req_id("stream")
self._ws_stream_ids[msg.thread_ts] = stream_id
if not stream_id:
return
last_exc: Exception | None = None
for attempt in range(_max_retries):
try:
await self._ws_client.reply_stream(frame, stream_id, msg.text, bool(msg.is_final))
return
except Exception as exc:
last_exc = exc
if attempt < _max_retries - 1:
await asyncio.sleep(2**attempt)
if last_exc:
raise last_exc
body = {"msgtype": "markdown", "markdown": {"content": msg.text}}
last_exc = None
for attempt in range(_max_retries):
try:
await self._ws_client.send_message(msg.chat_id, body)
return
except Exception as exc:
last_exc = exc
if attempt < _max_retries - 1:
await asyncio.sleep(2**attempt)
if last_exc:
raise last_exc
async def _upload_media_ws(
self,
*,
media_type: str,
filename: str,
path: str,
size: int,
) -> str | None:
if not self._ws_client:
return None
try:
from aibot import generate_req_id
except Exception:
return None
chunk_size = 512 * 1024
total_chunks = (size + chunk_size - 1) // chunk_size
if total_chunks < 1 or total_chunks > 100:
logger.warning("[WeCom] invalid total_chunks=%d for %s", total_chunks, filename)
return None
md5_hasher = hashlib.md5()
with open(path, "rb") as f:
for chunk in iter(lambda: f.read(1024 * 1024), b""):
md5_hasher.update(chunk)
md5 = md5_hasher.hexdigest()
init_req_id = generate_req_id("aibot_upload_media_init")
init_body = {
"type": media_type,
"filename": filename,
"total_size": int(size),
"total_chunks": int(total_chunks),
"md5": md5,
}
init_ack = await self._send_ws_upload_command(init_req_id, init_body, "aibot_upload_media_init")
upload_id = (init_ack.get("body") or {}).get("upload_id")
if not upload_id:
logger.warning("[WeCom] upload init returned no upload_id: %s", init_ack)
return None
with open(path, "rb") as f:
for idx in range(total_chunks):
data = f.read(chunk_size)
if not data:
break
chunk_req_id = generate_req_id("aibot_upload_media_chunk")
chunk_body = {
"upload_id": upload_id,
"chunk_index": int(idx),
"base64_data": base64.b64encode(data).decode("utf-8"),
}
await self._send_ws_upload_command(chunk_req_id, chunk_body, "aibot_upload_media_chunk")
finish_req_id = generate_req_id("aibot_upload_media_finish")
finish_ack = await self._send_ws_upload_command(finish_req_id, {"upload_id": upload_id}, "aibot_upload_media_finish")
media_id = (finish_ack.get("body") or {}).get("media_id")
if not media_id:
logger.warning("[WeCom] upload finish returned no media_id: %s", finish_ack)
return None
return media_id
+3 -22
View File
@@ -1,23 +1,4 @@
from __future__ import annotations
from .app import app, create_app
from .config import GatewayConfig, get_gateway_config
__all__ = ["GatewayConfig", "app", "get_gateway_config", "register_app"]
def __getattr__(name: str):
if name == "app":
from .app import app
return app
if name == "GatewayConfig":
from .config import GatewayConfig
return GatewayConfig
if name == "get_gateway_config":
from .config import get_gateway_config
return get_gateway_config
if name == "register_app":
from .registrar import register_app
return register_app
raise AttributeError(name)
__all__ = ["app", "create_app", "GatewayConfig", "get_gateway_config"]
+217 -4
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@@ -1,8 +1,221 @@
from app.gateway.registrar import register_app
import logging
from collections.abc import AsyncGenerator
from contextlib import asynccontextmanager
from fastapi import FastAPI
from app.gateway.config import get_gateway_config
from app.gateway.deps import langgraph_runtime
from app.gateway.routers import (
agents,
artifacts,
assistants_compat,
channels,
mcp,
memory,
models,
runs,
skills,
suggestions,
thread_runs,
threads,
uploads,
)
from deerflow.config.app_config import get_app_config
# Configure logging
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
)
logger = logging.getLogger(__name__)
def create_app():
return register_app()
@asynccontextmanager
async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
"""Application lifespan handler."""
# Load config and check necessary environment variables at startup
try:
get_app_config()
logger.info("Configuration loaded successfully")
except Exception as e:
error_msg = f"Failed to load configuration during gateway startup: {e}"
logger.exception(error_msg)
raise RuntimeError(error_msg) from e
config = get_gateway_config()
logger.info(f"Starting API Gateway on {config.host}:{config.port}")
# Initialize LangGraph runtime components (StreamBridge, RunManager, checkpointer, store)
async with langgraph_runtime(app):
logger.info("LangGraph runtime initialised")
# Start IM channel service if any channels are configured
try:
from app.channels.service import start_channel_service
channel_service = await start_channel_service()
logger.info("Channel service started: %s", channel_service.get_status())
except Exception:
logger.exception("No IM channels configured or channel service failed to start")
yield
# Stop channel service on shutdown
try:
from app.channels.service import stop_channel_service
await stop_channel_service()
except Exception:
logger.exception("Failed to stop channel service")
logger.info("Shutting down API Gateway")
app = register_app()
def create_app() -> FastAPI:
"""Create and configure the FastAPI application.
Returns:
Configured FastAPI application instance.
"""
app = FastAPI(
title="DeerFlow API Gateway",
description="""
## DeerFlow API Gateway
API Gateway for DeerFlow - A LangGraph-based AI agent backend with sandbox execution capabilities.
### Features
- **Models Management**: Query and retrieve available AI models
- **MCP Configuration**: Manage Model Context Protocol (MCP) server configurations
- **Memory Management**: Access and manage global memory data for personalized conversations
- **Skills Management**: Query and manage skills and their enabled status
- **Artifacts**: Access thread artifacts and generated files
- **Health Monitoring**: System health check endpoints
### Architecture
LangGraph requests are handled by nginx reverse proxy.
This gateway provides custom endpoints for models, MCP configuration, skills, and artifacts.
""",
version="0.1.0",
lifespan=lifespan,
docs_url="/docs",
redoc_url="/redoc",
openapi_url="/openapi.json",
openapi_tags=[
{
"name": "models",
"description": "Operations for querying available AI models and their configurations",
},
{
"name": "mcp",
"description": "Manage Model Context Protocol (MCP) server configurations",
},
{
"name": "memory",
"description": "Access and manage global memory data for personalized conversations",
},
{
"name": "skills",
"description": "Manage skills and their configurations",
},
{
"name": "artifacts",
"description": "Access and download thread artifacts and generated files",
},
{
"name": "uploads",
"description": "Upload and manage user files for threads",
},
{
"name": "threads",
"description": "Manage DeerFlow thread-local filesystem data",
},
{
"name": "agents",
"description": "Create and manage custom agents with per-agent config and prompts",
},
{
"name": "suggestions",
"description": "Generate follow-up question suggestions for conversations",
},
{
"name": "channels",
"description": "Manage IM channel integrations (Feishu, Slack, Telegram)",
},
{
"name": "assistants-compat",
"description": "LangGraph Platform-compatible assistants API (stub)",
},
{
"name": "runs",
"description": "LangGraph Platform-compatible runs lifecycle (create, stream, cancel)",
},
{
"name": "health",
"description": "Health check and system status endpoints",
},
],
)
# CORS is handled by nginx - no need for FastAPI middleware
# Include routers
# Models API is mounted at /api/models
app.include_router(models.router)
# MCP API is mounted at /api/mcp
app.include_router(mcp.router)
# Memory API is mounted at /api/memory
app.include_router(memory.router)
# Skills API is mounted at /api/skills
app.include_router(skills.router)
# Artifacts API is mounted at /api/threads/{thread_id}/artifacts
app.include_router(artifacts.router)
# Uploads API is mounted at /api/threads/{thread_id}/uploads
app.include_router(uploads.router)
# Thread cleanup API is mounted at /api/threads/{thread_id}
app.include_router(threads.router)
# Agents API is mounted at /api/agents
app.include_router(agents.router)
# Suggestions API is mounted at /api/threads/{thread_id}/suggestions
app.include_router(suggestions.router)
# Channels API is mounted at /api/channels
app.include_router(channels.router)
# Assistants compatibility API (LangGraph Platform stub)
app.include_router(assistants_compat.router)
# Thread Runs API (LangGraph Platform-compatible runs lifecycle)
app.include_router(thread_runs.router)
# Stateless Runs API (stream/wait without a pre-existing thread)
app.include_router(runs.router)
@app.get("/health", tags=["health"])
async def health_check() -> dict:
"""Health check endpoint.
Returns:
Service health status information.
"""
return {"status": "healthy", "service": "deer-flow-gateway"}
return app
# Create app instance for uvicorn
app = create_app()
-3
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@@ -1,3 +0,0 @@
from .lifespan import lifespan_manager
__all__ = ["lifespan_manager"]
-52
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@@ -1,52 +0,0 @@
from collections.abc import Callable
from contextlib import AbstractAsyncContextManager, AsyncExitStack, asynccontextmanager
from typing import Any
from fastapi import FastAPI
LifespanFunc = Callable[[FastAPI], AbstractAsyncContextManager[dict[str, Any] | None]]
class LifespanManager:
"""FastAPI lifespan manager"""
def __init__(self) -> None:
self._lifespans: list[LifespanFunc] = []
def register(self, func: LifespanFunc) -> LifespanFunc:
"""
Register a lifespan hook.
:param func: lifespan hook
:return:
"""
if func not in self._lifespans:
self._lifespans.append(func)
return func
def build(self) -> LifespanFunc:
"""
Build the combined lifespan hook.
:return:
"""
@asynccontextmanager
async def combined_lifespan(app: FastAPI): # noqa: ANN202
state: dict[str, Any] = {}
async with AsyncExitStack() as exit_stack:
for lifespan_fn in self._lifespans:
result = await exit_stack.enter_async_context(lifespan_fn(app))
if isinstance(result, dict):
state.update(result)
for key, value in state.items():
setattr(app.state, key, value)
yield state or None
return combined_lifespan
# Singleton lifespan_manager instance
lifespan_manager = LifespanManager()
@@ -1,59 +0,0 @@
from app.gateway.dependencies.checkpointer import (
CurrentCheckpointer,
get_checkpointer,
)
from app.plugins.auth.security.dependencies import (
CurrentAuthService,
CurrentUserRepository,
get_auth_service,
get_current_user_from_request,
get_current_user_id,
get_optional_user_from_request,
get_user_repository,
)
from app.gateway.dependencies.db import (
CurrentSession,
CurrentSessionTransaction,
get_db_session,
get_db_session_transaction,
)
from app.gateway.dependencies.repositories import (
CurrentFeedbackRepository,
CurrentRunRepository,
CurrentThreadMetaRepository,
CurrentThreadMetaStorage,
get_feedback_repository,
get_run_repository,
get_thread_meta_repository,
get_thread_meta_storage,
)
from app.gateway.dependencies.stream_bridge import (
CurrentStreamBridge,
get_stream_bridge,
)
__all__ = [
"CurrentCheckpointer",
"CurrentAuthService",
"CurrentFeedbackRepository",
"CurrentRunRepository",
"CurrentSession",
"CurrentSessionTransaction",
"CurrentStreamBridge",
"CurrentThreadMetaRepository",
"CurrentThreadMetaStorage",
"CurrentUserRepository",
"get_auth_service",
"get_checkpointer",
"get_current_user_from_request",
"get_current_user_id",
"get_db_session",
"get_db_session_transaction",
"get_feedback_repository",
"get_optional_user_from_request",
"get_run_repository",
"get_stream_bridge",
"get_thread_meta_repository",
"get_thread_meta_storage",
"get_user_repository",
]
@@ -1,20 +0,0 @@
from __future__ import annotations
from typing import Annotated
from fastapi import Depends, HTTPException, Request
from langgraph.types import Checkpointer
def get_checkpointer(request: Request) -> Checkpointer:
"""Get checkpointer from app.state.persistence."""
persistence = getattr(request.app.state, "persistence", None)
if persistence is None:
raise HTTPException(status_code=503, detail="Persistence not available")
checkpointer = getattr(persistence, "checkpointer", None)
if checkpointer is None:
raise HTTPException(status_code=503, detail="Checkpointer not available")
return checkpointer
CurrentCheckpointer = Annotated[Checkpointer, Depends(get_checkpointer)]
-37
View File
@@ -1,37 +0,0 @@
from __future__ import annotations
from collections.abc import AsyncIterator
from typing import Annotated
from fastapi import Depends, HTTPException, Request
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
def _get_session_factory(request: Request) -> async_sessionmaker[AsyncSession]:
factory = getattr(request.app.state.persistence, "session_factory", None)
if factory is None:
raise HTTPException(status_code=503, detail="Database session factory not available")
return factory
async def get_db_session(request: Request) -> AsyncIterator[AsyncSession]:
"""Open a session without auto-commit. Use for read-only endpoints."""
session_factory = _get_session_factory(request)
async with session_factory() as session:
yield session
async def get_db_session_transaction(request: Request) -> AsyncIterator[AsyncSession]:
"""Open a session and commit on success, rollback on error."""
session_factory = _get_session_factory(request)
async with session_factory() as session:
try:
yield session
await session.commit()
except Exception:
await session.rollback()
raise
CurrentSession = Annotated[AsyncSession, Depends(get_db_session)]
CurrentSessionTransaction = Annotated[AsyncSession, Depends(get_db_session_transaction)]
@@ -1,41 +0,0 @@
from __future__ import annotations
from typing import Annotated
from fastapi import Depends, HTTPException, Request
from app.infra.storage import ThreadMetaStorage
from store.repositories.contracts import (
FeedbackRepositoryProtocol,
RunRepositoryProtocol,
ThreadMetaRepositoryProtocol,
)
def _require_state(request: Request, attr: str, label: str):
value = getattr(request.app.state, attr, None)
if value is None:
raise HTTPException(status_code=503, detail=f"{label} not available")
return value
def get_run_repository(request: Request) -> RunRepositoryProtocol:
return _require_state(request, "run_store", "Run store")
def get_thread_meta_repository(request: Request) -> ThreadMetaRepositoryProtocol:
return _require_state(request, "thread_meta_repo", "Thread metadata store")
def get_thread_meta_storage(request: Request) -> ThreadMetaStorage:
return _require_state(request, "thread_meta_storage", "Thread metadata storage")
def get_feedback_repository(request: Request) -> FeedbackRepositoryProtocol:
return _require_state(request, "feedback_repo", "Feedback")
CurrentRunRepository = Annotated[RunRepositoryProtocol, Depends(get_run_repository)]
CurrentThreadMetaRepository = Annotated[ThreadMetaRepositoryProtocol, Depends(get_thread_meta_repository)]
CurrentThreadMetaStorage = Annotated[ThreadMetaStorage, Depends(get_thread_meta_storage)]
CurrentFeedbackRepository = Annotated[FeedbackRepositoryProtocol, Depends(get_feedback_repository)]
@@ -1,18 +0,0 @@
from __future__ import annotations
from typing import Annotated
from fastapi import Depends, HTTPException, Request
from deerflow.runtime import StreamBridge
def get_stream_bridge(request: Request) -> StreamBridge:
"""Get stream bridge from app.state."""
bridge = getattr(request.app.state, "stream_bridge", None)
if bridge is None:
raise HTTPException(status_code=503, detail="Stream bridge not available")
return bridge
CurrentStreamBridge = Annotated[StreamBridge, Depends(get_stream_bridge)]
+70
View File
@@ -0,0 +1,70 @@
"""Centralized accessors for singleton objects stored on ``app.state``.
**Getters** (used by routers): raise 503 when a required dependency is
missing, except ``get_store`` which returns ``None``.
Initialization is handled directly in ``app.py`` via :class:`AsyncExitStack`.
"""
from __future__ import annotations
from collections.abc import AsyncGenerator
from contextlib import AsyncExitStack, asynccontextmanager
from fastapi import FastAPI, HTTPException, Request
from deerflow.runtime import RunManager, StreamBridge
@asynccontextmanager
async def langgraph_runtime(app: FastAPI) -> AsyncGenerator[None, None]:
"""Bootstrap and tear down all LangGraph runtime singletons.
Usage in ``app.py``::
async with langgraph_runtime(app):
yield
"""
from deerflow.agents.checkpointer.async_provider import make_checkpointer
from deerflow.runtime import make_store, make_stream_bridge
async with AsyncExitStack() as stack:
app.state.stream_bridge = await stack.enter_async_context(make_stream_bridge())
app.state.checkpointer = await stack.enter_async_context(make_checkpointer())
app.state.store = await stack.enter_async_context(make_store())
app.state.run_manager = RunManager()
yield
# ---------------------------------------------------------------------------
# Getters called by routers per-request
# ---------------------------------------------------------------------------
def get_stream_bridge(request: Request) -> StreamBridge:
"""Return the global :class:`StreamBridge`, or 503."""
bridge = getattr(request.app.state, "stream_bridge", None)
if bridge is None:
raise HTTPException(status_code=503, detail="Stream bridge not available")
return bridge
def get_run_manager(request: Request) -> RunManager:
"""Return the global :class:`RunManager`, or 503."""
mgr = getattr(request.app.state, "run_manager", None)
if mgr is None:
raise HTTPException(status_code=503, detail="Run manager not available")
return mgr
def get_checkpointer(request: Request):
"""Return the global checkpointer, or 503."""
cp = getattr(request.app.state, "checkpointer", None)
if cp is None:
raise HTTPException(status_code=503, detail="Checkpointer not available")
return cp
def get_store(request: Request):
"""Return the global store (may be ``None`` if not configured)."""
return getattr(request.app.state, "store", None)
+2 -5
View File
@@ -5,17 +5,15 @@ from pathlib import Path
from fastapi import HTTPException
from deerflow.config.paths import get_paths
from deerflow.runtime.actor_context import get_effective_user_id
def resolve_thread_virtual_path(thread_id: str, virtual_path: str, *, user_id: str | None = None) -> Path:
def resolve_thread_virtual_path(thread_id: str, virtual_path: str) -> Path:
"""Resolve a virtual path to the actual filesystem path under thread user-data.
Args:
thread_id: The thread ID.
virtual_path: The virtual path as seen inside the sandbox
(e.g., /mnt/user-data/outputs/file.txt).
user_id: Explicit user id override. Falls back to the current actor context.
Returns:
The resolved filesystem path.
@@ -24,8 +22,7 @@ def resolve_thread_virtual_path(thread_id: str, virtual_path: str, *, user_id: s
HTTPException: If the path is invalid or outside allowed directories.
"""
try:
resolved_user_id = get_effective_user_id() if user_id is None else user_id
return get_paths().resolve_virtual_path(thread_id, virtual_path, user_id=resolved_user_id)
return get_paths().resolve_virtual_path(thread_id, virtual_path)
except ValueError as e:
status = 403 if "traversal" in str(e) else 400
raise HTTPException(status_code=status, detail=str(e))
-132
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@@ -1,132 +0,0 @@
from collections.abc import AsyncGenerator
from contextlib import asynccontextmanager
from pathlib import Path
from typing import Any
from fastapi import FastAPI
from fastapi.responses import HTMLResponse
from fastapi.staticfiles import StaticFiles
from scalar_fastapi import AgentScalarConfig, get_scalar_api_reference
from starlette.middleware.cors import CORSMiddleware
from store.persistence import create_persistence
from app.gateway.common import lifespan_manager
from app.gateway.router import router as gateway_router
from app.infra.run_events import build_run_event_store
from app.infra.storage import FeedbackStoreAdapter, RunStoreAdapter, ThreadMetaStorage, ThreadMetaStoreAdapter
from app.plugins.auth.authorization.hooks import build_authz_hooks
from app.plugins.auth.injection import install_route_guards, load_route_policy_registry, validate_route_policy_registry
from app.plugins.auth.security import AuthMiddleware, CSRFMiddleware
STATIC_DIR = Path(__file__).resolve().parents[1] / "static"
STATIC_MOUNT = "/api/static"
SCALAR_JS_URL = f"{STATIC_MOUNT}/scalar.js"
@lifespan_manager.register
@asynccontextmanager
async def init_persistence(app: FastAPI) -> AsyncGenerator[dict[str, Any], None]:
"""Initialize persistence layer (DB, checkpointer, store)."""
app_persistence = await create_persistence()
await app_persistence.setup()
run_store = RunStoreAdapter(app_persistence.session_factory)
thread_meta_store = ThreadMetaStoreAdapter(app_persistence.session_factory)
feedback_store = FeedbackStoreAdapter(app_persistence.session_factory)
try:
yield {
"persistence": app_persistence,
"checkpointer": app_persistence.checkpointer,
"store": None,
"session_factory": app_persistence.session_factory,
"run_store": run_store,
"run_read_repo": run_store,
"run_write_repo": run_store,
"run_delete_repo": run_store,
"feedback_repo": feedback_store,
"thread_meta_repo": thread_meta_store,
"thread_meta_storage": ThreadMetaStorage(thread_meta_store),
"run_event_store": build_run_event_store(app_persistence.session_factory),
}
finally:
await app_persistence.aclose()
@lifespan_manager.register
@asynccontextmanager
async def init_runtime(app: FastAPI) -> AsyncGenerator[dict[str, Any], None]:
"""Initialize StreamBridge for LangGraph-compatible runtime endpoints."""
from app.infra.stream_bridge import build_stream_bridge
async with build_stream_bridge() as stream_bridge:
yield {
"stream_bridge": stream_bridge,
}
def register_app() -> FastAPI:
app = FastAPI(
title="DeerFlow API Gateway",
version="0.1.0",
docs_url=None,
redoc_url=None,
lifespan=lifespan_manager.build(),
openapi_tags=[
{
"name": "threads",
"description": "Endpoints for managing threads, which are conversations between a human and an assistant. A thread can have multiple runs as the conversation progresses."
}
]
)
app.state.authz_hooks = build_authz_hooks()
_register_static(app)
_register_routes(app)
_register_scalar(app)
_register_auth_route_policies(app)
_register_middlewares(app)
return app
def _register_static(app: FastAPI) -> None:
app.mount(STATIC_MOUNT, StaticFiles(directory=STATIC_DIR), name="static")
def _register_routes(app: FastAPI) -> None:
app.include_router(gateway_router)
def _register_auth_route_policies(app: FastAPI) -> None:
registry = load_route_policy_registry()
validate_route_policy_registry(app, registry)
app.state.auth_route_policy_registry = registry
install_route_guards(app)
def _register_middlewares(app: FastAPI) -> None:
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
expose_headers=["*"],
)
app.add_middleware(CSRFMiddleware)
app.add_middleware(AuthMiddleware)
def _register_scalar(app: FastAPI) -> None:
@app.get("/docs", include_in_schema=False)
def scalar_docs() -> HTMLResponse:
return get_scalar_api_reference(
openapi_url=app.openapi_url,
title=app.title,
scalar_js_url=SCALAR_JS_URL,
agent=AgentScalarConfig(disabled=True),
hide_client_button=True,
overrides={"mcp": {"disabled": True}},
)
-22
View File
@@ -1,22 +0,0 @@
from fastapi import APIRouter
from app.plugins.auth.api.router import router as auth_router
from .routers import artifacts, channels, mcp, models, skills, uploads
from .routers.agents import router as agents_router
from .routers.langgraph import feedback_router, runs_router, suggestion_router, threads_router
router = APIRouter()
router.include_router(auth_router)
router.include_router(threads_router, prefix="/api/threads")
router.include_router(runs_router, prefix="/api/threads")
router.include_router(feedback_router, prefix="/api/threads")
router.include_router(suggestion_router)
router.include_router(agents_router)
router.include_router(channels.router)
router.include_router(artifacts.router)
router.include_router(mcp.router)
router.include_router(models.router)
router.include_router(skills.router)
router.include_router(uploads.router)
+2 -2
View File
@@ -1,3 +1,3 @@
from . import artifacts, mcp, models, skills, suggestions, uploads
from . import artifacts, assistants_compat, mcp, models, skills, suggestions, thread_runs, threads, uploads
__all__ = ["artifacts", "mcp", "models", "skills", "suggestions", "uploads"]
__all__ = ["artifacts", "assistants_compat", "mcp", "models", "skills", "suggestions", "threads", "thread_runs", "uploads"]
+4 -4
View File
@@ -24,7 +24,7 @@ class AgentResponse(BaseModel):
description: str = Field(default="", description="Agent description")
model: str | None = Field(default=None, description="Optional model override")
tool_groups: list[str] | None = Field(default=None, description="Optional tool group whitelist")
soul: str | None = Field(default=None, description="SOUL.md content")
soul: str | None = Field(default=None, description="SOUL.md content (included on GET /{name})")
class AgentsListResponse(BaseModel):
@@ -92,17 +92,17 @@ def _agent_config_to_response(agent_cfg: AgentConfig, include_soul: bool = False
"/agents",
response_model=AgentsListResponse,
summary="List Custom Agents",
description="List all custom agents available in the agents directory, including their soul content.",
description="List all custom agents available in the agents directory.",
)
async def list_agents() -> AgentsListResponse:
"""List all custom agents.
Returns:
List of all custom agents with their metadata and soul content.
List of all custom agents with their metadata (without soul content).
"""
try:
agents = list_custom_agents()
return AgentsListResponse(agents=[_agent_config_to_response(a, include_soul=True) for a in agents])
return AgentsListResponse(agents=[_agent_config_to_response(a) for a in agents])
except Exception as e:
logger.error(f"Failed to list agents: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to list agents: {str(e)}")
@@ -0,0 +1,149 @@
"""Assistants compatibility endpoints.
Provides LangGraph Platform-compatible assistants API backed by the
``langgraph.json`` graph registry and ``config.yaml`` agent definitions.
This is a minimal stub that satisfies the ``useStream`` React hook's
initialization requirements (``assistants.search()`` and ``assistants.get()``).
"""
from __future__ import annotations
import logging
from datetime import UTC, datetime
from typing import Any
from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/assistants", tags=["assistants-compat"])
class AssistantResponse(BaseModel):
assistant_id: str
graph_id: str
name: str
config: dict[str, Any] = Field(default_factory=dict)
metadata: dict[str, Any] = Field(default_factory=dict)
description: str | None = None
created_at: str = ""
updated_at: str = ""
version: int = 1
class AssistantSearchRequest(BaseModel):
graph_id: str | None = None
name: str | None = None
metadata: dict[str, Any] | None = None
limit: int = 10
offset: int = 0
def _get_default_assistant() -> AssistantResponse:
"""Return the default lead_agent assistant."""
now = datetime.now(UTC).isoformat()
return AssistantResponse(
assistant_id="lead_agent",
graph_id="lead_agent",
name="lead_agent",
config={},
metadata={"created_by": "system"},
description="DeerFlow lead agent",
created_at=now,
updated_at=now,
version=1,
)
def _list_assistants() -> list[AssistantResponse]:
"""List all available assistants from config."""
assistants = [_get_default_assistant()]
# Also include custom agents from config.yaml agents directory
try:
from deerflow.config.agents_config import list_custom_agents
for agent_cfg in list_custom_agents():
now = datetime.now(UTC).isoformat()
assistants.append(
AssistantResponse(
assistant_id=agent_cfg.name,
graph_id="lead_agent", # All agents use the same graph
name=agent_cfg.name,
config={},
metadata={"created_by": "user"},
description=agent_cfg.description or "",
created_at=now,
updated_at=now,
version=1,
)
)
except Exception:
logger.debug("Could not load custom agents for assistants list")
return assistants
@router.post("/search", response_model=list[AssistantResponse])
async def search_assistants(body: AssistantSearchRequest | None = None) -> list[AssistantResponse]:
"""Search assistants.
Returns all registered assistants (lead_agent + custom agents from config).
"""
assistants = _list_assistants()
if body and body.graph_id:
assistants = [a for a in assistants if a.graph_id == body.graph_id]
if body and body.name:
assistants = [a for a in assistants if body.name.lower() in a.name.lower()]
offset = body.offset if body else 0
limit = body.limit if body else 10
return assistants[offset : offset + limit]
@router.get("/{assistant_id}", response_model=AssistantResponse)
async def get_assistant_compat(assistant_id: str) -> AssistantResponse:
"""Get an assistant by ID."""
for a in _list_assistants():
if a.assistant_id == assistant_id:
return a
raise HTTPException(status_code=404, detail=f"Assistant {assistant_id} not found")
@router.get("/{assistant_id}/graph")
async def get_assistant_graph(assistant_id: str) -> dict:
"""Get the graph structure for an assistant.
Returns a minimal graph description. Full graph introspection is
not supported in the Gateway — this stub satisfies SDK validation.
"""
found = any(a.assistant_id == assistant_id for a in _list_assistants())
if not found:
raise HTTPException(status_code=404, detail=f"Assistant {assistant_id} not found")
return {
"graph_id": "lead_agent",
"nodes": [],
"edges": [],
}
@router.get("/{assistant_id}/schemas")
async def get_assistant_schemas(assistant_id: str) -> dict:
"""Get JSON schemas for an assistant's input/output/state.
Returns empty schemas — full introspection not supported in Gateway.
"""
found = any(a.assistant_id == assistant_id for a in _list_assistants())
if not found:
raise HTTPException(status_code=404, detail=f"Assistant {assistant_id} not found")
return {
"graph_id": "lead_agent",
"input_schema": {},
"output_schema": {},
"state_schema": {},
"config_schema": {},
}
@@ -1,6 +0,0 @@
from .feedback import router as feedback_router
from .runs import router as runs_router
from .suggestions import router as suggestion_router
from .threads import router as threads_router
__all__ = ["feedback_router", "runs_router", "threads_router", "suggestion_router"]
@@ -1,179 +0,0 @@
"""LangGraph-compatible run feedback endpoints."""
from __future__ import annotations
import logging
from typing import Any
from fastapi import APIRouter, HTTPException, Request
from pydantic import BaseModel, Field
from app.gateway.dependencies import get_feedback_repository, get_run_repository
from app.plugins.auth.security.actor_context import bind_request_actor_context, resolve_request_user_id
from app.plugins.auth.security.dependencies import get_current_user_id
logger = logging.getLogger(__name__)
router = APIRouter(tags=["feedback"])
class FeedbackCreateRequest(BaseModel):
rating: int = Field(..., description="Feedback rating: +1 (positive) or -1 (negative)")
comment: str | None = Field(default=None, description="Optional text feedback")
message_id: str | None = Field(default=None, description="Optional: scope feedback to a specific message")
class FeedbackResponse(BaseModel):
feedback_id: str
run_id: str
thread_id: str
owner_id: str | None = None
message_id: str | None = None
rating: int
comment: str | None = None
created_at: str = ""
class FeedbackStatsResponse(BaseModel):
run_id: str
total: int = 0
positive: int = 0
negative: int = 0
async def _validate_run_scope(thread_id: str, run_id: str, request: Request) -> None:
run_store = get_run_repository(request)
if resolve_request_user_id(request) is None:
run = await run_store.get(run_id, user_id=None)
else:
with bind_request_actor_context(request):
run = await run_store.get(run_id)
if run is None:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
if run.get("thread_id") != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found in thread {thread_id}")
async def _get_current_user(request: Request) -> str | None:
"""Extract current user id from auth dependencies when available."""
return await get_current_user_id(request)
async def _create_feedback(
thread_id: str,
run_id: str,
body: FeedbackCreateRequest,
request: Request,
) -> dict[str, Any]:
if body.rating not in (1, -1):
raise HTTPException(status_code=400, detail="rating must be +1 or -1")
await _validate_run_scope(thread_id, run_id, request)
user_id = await _get_current_user(request)
feedback_repo = get_feedback_repository(request)
return await feedback_repo.create(
run_id=run_id,
thread_id=thread_id,
rating=body.rating,
user_id=user_id,
message_id=body.message_id,
comment=body.comment,
)
@router.put("/{thread_id}/runs/{run_id}/feedback", response_model=FeedbackResponse)
async def upsert_feedback(
thread_id: str,
run_id: str,
body: FeedbackCreateRequest,
request: Request,
) -> dict[str, Any]:
"""Create or replace the run-level feedback record."""
feedback_repo = get_feedback_repository(request)
user_id = await _get_current_user(request)
if user_id is not None:
return await feedback_repo.upsert(
run_id=run_id,
thread_id=thread_id,
rating=body.rating,
user_id=user_id,
comment=body.comment,
)
existing = await feedback_repo.list_by_run(thread_id, run_id, limit=100, user_id=None)
for item in existing:
feedback_id = item.get("feedback_id")
if isinstance(feedback_id, str):
await feedback_repo.delete(feedback_id)
return await _create_feedback(thread_id, run_id, body, request)
@router.post("/{thread_id}/runs/{run_id}/feedback", response_model=FeedbackResponse)
async def create_feedback(
thread_id: str,
run_id: str,
body: FeedbackCreateRequest,
request: Request,
) -> dict[str, Any]:
"""Submit feedback for a run."""
return await _create_feedback(thread_id, run_id, body, request)
@router.get("/{thread_id}/runs/{run_id}/feedback", response_model=list[FeedbackResponse])
async def list_feedback(
thread_id: str,
run_id: str,
request: Request,
) -> list[dict[str, Any]]:
"""List all feedback for a run."""
feedback_repo = get_feedback_repository(request)
user_id = await _get_current_user(request)
return await feedback_repo.list_by_run(thread_id, run_id, user_id=user_id)
@router.get("/{thread_id}/runs/{run_id}/feedback/stats", response_model=FeedbackStatsResponse)
async def feedback_stats(
thread_id: str,
run_id: str,
request: Request,
) -> dict[str, Any]:
"""Get aggregated feedback stats for a run."""
feedback_repo = get_feedback_repository(request)
return await feedback_repo.aggregate_by_run(thread_id, run_id)
@router.delete("/{thread_id}/runs/{run_id}/feedback")
async def delete_run_feedback(
thread_id: str,
run_id: str,
request: Request,
) -> dict[str, bool]:
"""Delete all feedback records for a run."""
feedback_repo = get_feedback_repository(request)
user_id = await _get_current_user(request)
if user_id is not None:
return {"success": await feedback_repo.delete_by_run(thread_id=thread_id, run_id=run_id, user_id=user_id)}
existing = await feedback_repo.list_by_run(thread_id, run_id, limit=100, user_id=None)
for item in existing:
feedback_id = item.get("feedback_id")
if isinstance(feedback_id, str):
await feedback_repo.delete(feedback_id)
return {"success": True}
@router.delete("/{thread_id}/runs/{run_id}/feedback/{feedback_id}")
async def delete_feedback(
thread_id: str,
run_id: str,
feedback_id: str,
request: Request,
) -> dict[str, bool]:
"""Delete a single feedback record."""
feedback_repo = get_feedback_repository(request)
existing = await feedback_repo.get(feedback_id)
if existing is None:
raise HTTPException(status_code=404, detail=f"Feedback {feedback_id} not found")
if existing.get("thread_id") != thread_id or existing.get("run_id") != run_id:
raise HTTPException(status_code=404, detail=f"Feedback {feedback_id} not found in run {run_id}")
deleted = await feedback_repo.delete(feedback_id)
if not deleted:
raise HTTPException(status_code=404, detail=f"Feedback {feedback_id} not found")
return {"success": True}
@@ -1,501 +0,0 @@
"""LangGraph-compatible runs endpoints backed by RunsFacade."""
from __future__ import annotations
import json
from collections.abc import AsyncIterator
from typing import Literal
from fastapi import APIRouter, HTTPException, Request
from fastapi.responses import Response, StreamingResponse
from pydantic import BaseModel, Field
from app.plugins.auth.security.actor_context import bind_request_actor_context
from app.gateway.services.runs.facade_factory import build_runs_facade_from_request
from app.gateway.services.runs.input import (
AdaptedRunRequest,
RunSpecBuilder,
UnsupportedRunFeatureError,
adapt_create_run_request,
adapt_create_stream_request,
adapt_create_wait_request,
adapt_join_stream_request,
adapt_join_wait_request,
)
from deerflow.runtime.runs.types import RunRecord, RunSpec
from deerflow.runtime.stream_bridge import JSONValue, StreamEvent
router = APIRouter(tags=["runs"])
class RunCreateRequest(BaseModel):
assistant_id: str | None = Field(default=None, description="Agent / assistant to use")
follow_up_to_run_id: str | None = Field(default=None, description="Lineage link to the prior run")
input: dict[str, JSONValue] | None = Field(default=None, description="Graph input (e.g. {messages: [...]})")
command: dict[str, JSONValue] | None = Field(default=None, description="LangGraph Command")
metadata: dict[str, JSONValue] | None = Field(default=None, description="Run metadata")
config: dict[str, JSONValue] | None = Field(default=None, description="RunnableConfig overrides")
context: dict[str, JSONValue] | None = Field(default=None, description="DeerFlow context overrides (model_name, thinking_enabled, etc.)")
webhook: str | None = Field(default=None, description="Completion callback URL")
checkpoint_id: str | None = Field(default=None, description="Resume from checkpoint")
checkpoint: dict[str, JSONValue] | None = Field(default=None, description="Full checkpoint object")
interrupt_before: list[str] | Literal["*"] | None = Field(default=None, description="Nodes to interrupt before")
interrupt_after: list[str] | Literal["*"] | None = Field(default=None, description="Nodes to interrupt after")
stream_mode: list[str] | str | None = Field(default=None, description="Stream mode(s)")
stream_subgraphs: bool = Field(default=False, description="Include subgraph events")
stream_resumable: bool | None = Field(default=None, description="SSE resumable mode")
on_disconnect: Literal["cancel", "continue"] = Field(default="cancel", description="Behaviour on SSE disconnect")
on_completion: Literal["delete", "keep"] = Field(default="keep", description="Delete temp thread on completion")
multitask_strategy: Literal["reject", "rollback", "interrupt", "enqueue"] = Field(default="reject", description="Concurrency strategy")
after_seconds: float | None = Field(default=None, description="Delayed execution")
if_not_exists: Literal["reject", "create"] = Field(default="create", description="Thread creation policy")
feedback_keys: list[str] | None = Field(default=None, description="LangSmith feedback keys")
class RunResponse(BaseModel):
run_id: str
thread_id: str
assistant_id: str | None = None
status: str
metadata: dict[str, JSONValue] = Field(default_factory=dict)
multitask_strategy: str = "reject"
created_at: str = ""
updated_at: str = ""
class RunDeleteResponse(BaseModel):
deleted: bool
class RunMessageResponse(BaseModel):
run_id: str
content: JSONValue
metadata: dict[str, JSONValue] = Field(default_factory=dict)
created_at: str
seq: int
class RunMessagesResponse(BaseModel):
data: list[RunMessageResponse]
hasMore: bool = False
def format_sse(event: str, data: JSONValue, *, event_id: str | None = None) -> str:
"""Format a single SSE frame."""
payload = json.dumps(data, default=str, ensure_ascii=False)
parts = [f"event: {event}", f"data: {payload}"]
if event_id:
parts.append(f"id: {event_id}")
parts.append("")
parts.append("")
return "\n".join(parts)
def _record_to_response(record: RunRecord) -> RunResponse:
return RunResponse(
run_id=record.run_id,
thread_id=record.thread_id,
assistant_id=record.assistant_id,
status=record.status,
metadata=record.metadata,
multitask_strategy=record.multitask_strategy,
created_at=record.created_at,
updated_at=record.updated_at,
)
def _trim_paginated_rows(
rows: list[dict],
*,
limit: int,
after_seq: int | None,
) -> tuple[list[dict], bool]:
has_more = len(rows) > limit
if not has_more:
return rows, False
if after_seq is not None:
return rows[:limit], True
return rows[-limit:], True
def _event_to_run_message(event: dict) -> RunMessageResponse:
return RunMessageResponse(
run_id=str(event["run_id"]),
content=event.get("content"),
metadata=dict(event.get("metadata") or {}),
created_at=str(event.get("created_at") or ""),
seq=int(event["seq"]),
)
async def _sse_consumer(
stream: AsyncIterator[StreamEvent],
request: Request,
*,
cancel_on_disconnect: bool,
cancel_run,
run_id: str,
) -> AsyncIterator[str]:
try:
async for event in stream:
if await request.is_disconnected():
break
if event.event == "__heartbeat__":
yield ": heartbeat\n\n"
continue
if event.event == "__end__":
yield format_sse("end", None, event_id=event.id or None)
return
if event.event == "__cancelled__":
yield format_sse("cancel", None, event_id=event.id or None)
return
yield format_sse(event.event, event.data, event_id=event.id or None)
finally:
if cancel_on_disconnect:
await cancel_run(run_id)
def _get_run_event_store(request: Request):
event_store = getattr(request.app.state, "run_event_store", None)
if event_store is None:
raise HTTPException(status_code=503, detail="Run event store not available")
return event_store
@router.get("/{thread_id}/runs", response_model=list[RunResponse])
async def list_runs(
thread_id: str,
request: Request,
limit: int = 100,
offset: int = 0,
status: str | None = None,
) -> list[RunResponse]:
# Accepted for API compatibility; field projection is not implemented yet.
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
records = await facade.list_runs(thread_id)
if status is not None:
records = [record for record in records if record.status == status]
records = records[offset : offset + limit]
return [_record_to_response(record) for record in records]
@router.get("/{thread_id}/runs/{run_id}", response_model=RunResponse)
async def get_run(thread_id: str, run_id: str, request: Request) -> RunResponse:
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record = await facade.get_run(run_id)
if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
return _record_to_response(record)
@router.get("/{thread_id}/runs/{run_id}/messages", response_model=RunMessagesResponse)
async def run_messages(
thread_id: str,
run_id: str,
request: Request,
limit: int = 50,
before_seq: int | None = None,
after_seq: int | None = None,
) -> RunMessagesResponse:
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record = await facade.get_run(run_id)
if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
event_store = _get_run_event_store(request)
with bind_request_actor_context(request):
rows = await event_store.list_messages_by_run(
thread_id,
run_id,
limit=limit + 1,
before_seq=before_seq,
after_seq=after_seq,
)
page, has_more = _trim_paginated_rows(rows, limit=limit, after_seq=after_seq)
return RunMessagesResponse(data=[_event_to_run_message(row) for row in page], hasMore=has_more)
def _build_spec(
*,
adapted: AdaptedRunRequest,
) -> RunSpec:
try:
return RunSpecBuilder().build(adapted)
except UnsupportedRunFeatureError as exc:
raise HTTPException(status_code=501, detail=str(exc)) from exc
@router.post("/{thread_id}/runs", response_model=RunResponse)
async def create_run(
thread_id: str,
body: RunCreateRequest,
request: Request,
) -> Response:
adapted = adapt_create_run_request(
thread_id=thread_id,
body=body.model_dump(),
headers=dict(request.headers),
query=dict(request.query_params),
)
spec = _build_spec(adapted=adapted)
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record = await facade.create_background(spec)
return Response(
content=_record_to_response(record).model_dump_json(),
media_type="application/json",
headers={"Content-Location": f"/api/threads/{thread_id}/runs/{record.run_id}"},
)
@router.post("/{thread_id}/runs/stream")
async def stream_run(
thread_id: str,
body: RunCreateRequest,
request: Request,
) -> StreamingResponse:
adapted = adapt_create_stream_request(
thread_id=thread_id,
body=body.model_dump(),
headers=dict(request.headers),
query=dict(request.query_params),
)
spec = _build_spec(adapted=adapted)
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record, stream = await facade.create_and_stream(spec)
return StreamingResponse(
_sse_consumer(
stream,
request,
cancel_on_disconnect=spec.on_disconnect == "cancel",
cancel_run=facade.cancel,
run_id=record.run_id,
),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
"Content-Location": f"/api/threads/{thread_id}/runs/{record.run_id}",
},
)
@router.post("/{thread_id}/runs/wait")
async def wait_run(
thread_id: str,
body: RunCreateRequest,
request: Request,
) -> Response:
adapted = adapt_create_wait_request(
thread_id=thread_id,
body=body.model_dump(),
headers=dict(request.headers),
query=dict(request.query_params),
)
spec = _build_spec(adapted=adapted)
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record, result = await facade.create_and_wait(spec)
return Response(
content=json.dumps(result, default=str, ensure_ascii=False),
media_type="application/json",
headers={"Content-Location": f"/api/threads/{thread_id}/runs/{record.run_id}"},
)
@router.post("/runs", response_model=RunResponse)
async def create_stateless_run(body: RunCreateRequest, request: Request) -> Response:
adapted = adapt_create_run_request(
thread_id=None,
body=body.model_dump(),
headers=dict(request.headers),
query=dict(request.query_params),
)
spec = _build_spec(adapted=adapted)
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record = await facade.create_background(spec)
return Response(
content=_record_to_response(record).model_dump_json(),
media_type="application/json",
headers={"Content-Location": f"/api/threads/{record.thread_id}/runs/{record.run_id}"},
)
@router.post("/runs/stream")
async def create_stateless_stream_run(body: RunCreateRequest, request: Request) -> StreamingResponse:
adapted = adapt_create_stream_request(
thread_id=None,
body=body.model_dump(),
headers=dict(request.headers),
query=dict(request.query_params),
)
spec = _build_spec(adapted=adapted)
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record, stream = await facade.create_and_stream(spec)
return StreamingResponse(
_sse_consumer(
stream,
request,
cancel_on_disconnect=spec.on_disconnect == "cancel",
cancel_run=facade.cancel,
run_id=record.run_id,
),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
"Content-Location": f"/api/threads/{record.thread_id}/runs/{record.run_id}",
},
)
@router.post("/runs/wait")
async def wait_stateless_run(body: RunCreateRequest, request: Request) -> Response:
adapted = adapt_create_wait_request(
thread_id=None,
body=body.model_dump(),
headers=dict(request.headers),
query=dict(request.query_params),
)
spec = _build_spec(adapted=adapted)
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record, result = await facade.create_and_wait(spec)
return Response(
content=json.dumps(result, default=str, ensure_ascii=False),
media_type="application/json",
headers={"Content-Location": f"/api/threads/{record.thread_id}/runs/{record.run_id}"},
)
@router.api_route("/{thread_id}/runs/{run_id}/stream", methods=["GET", "POST"], response_model=None)
async def stream_existing_run(
thread_id: str,
run_id: str,
request: Request,
action: Literal["interrupt", "rollback"] | None = None,
wait: bool = False,
cancel_on_disconnect: bool = False,
stream_mode: str | None = None,
) -> StreamingResponse | Response:
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record = await facade.get_run(run_id)
if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
if action is not None:
with bind_request_actor_context(request):
cancelled = await facade.cancel(run_id, action=action)
if not cancelled:
raise HTTPException(status_code=409, detail=f"Run {run_id} is not cancellable")
if wait:
with bind_request_actor_context(request):
await facade.join_wait(run_id)
return Response(status_code=204)
adapted = adapt_join_stream_request(
thread_id=thread_id,
run_id=run_id,
headers=dict(request.headers),
query=dict(request.query_params),
)
with bind_request_actor_context(request):
stream = await facade.join_stream(run_id, last_event_id=adapted.last_event_id)
return StreamingResponse(
_sse_consumer(
stream,
request,
cancel_on_disconnect=cancel_on_disconnect,
cancel_run=facade.cancel,
run_id=run_id,
),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
},
)
@router.get("/{thread_id}/runs/{run_id}/join")
async def join_existing_run(
thread_id: str,
run_id: str,
request: Request,
cancel_on_disconnect: bool = False,
) -> JSONValue:
# Accepted for API compatibility; current join_wait path does not change
# behavior based on client disconnect.
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record = await facade.get_run(run_id)
if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
adapted = adapt_join_wait_request(
thread_id=thread_id,
run_id=run_id,
headers=dict(request.headers),
query=dict(request.query_params),
)
with bind_request_actor_context(request):
return await facade.join_wait(run_id, last_event_id=adapted.last_event_id)
@router.post("/{thread_id}/runs/{run_id}/cancel")
async def cancel_existing_run(
thread_id: str,
run_id: str,
request: Request,
wait: bool = False,
action: Literal["interrupt", "rollback"] = "interrupt",
) -> JSONValue:
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record = await facade.get_run(run_id)
if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
with bind_request_actor_context(request):
cancelled = await facade.cancel(run_id, action=action)
if not cancelled:
raise HTTPException(status_code=409, detail=f"Run {run_id} is not cancellable")
if wait:
with bind_request_actor_context(request):
return await facade.join_wait(run_id)
return {}
@router.delete("/{thread_id}/runs/{run_id}", response_model=RunDeleteResponse)
async def delete_run(
thread_id: str,
run_id: str,
request: Request,
) -> RunDeleteResponse:
facade = build_runs_facade_from_request(request)
with bind_request_actor_context(request):
record = await facade.get_run(run_id)
if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
with bind_request_actor_context(request):
deleted = await facade.delete_run(run_id)
return RunDeleteResponse(deleted=deleted)
@@ -1,132 +0,0 @@
import json
import logging
from fastapi import APIRouter
from langchain_core.messages import HumanMessage, SystemMessage
from pydantic import BaseModel, Field
from deerflow.models import create_chat_model
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api", tags=["suggestions"])
class SuggestionMessage(BaseModel):
role: str = Field(..., description="Message role: user|assistant")
content: str = Field(..., description="Message content as plain text")
class SuggestionsRequest(BaseModel):
messages: list[SuggestionMessage] = Field(..., description="Recent conversation messages")
n: int = Field(default=3, ge=1, le=5, description="Number of suggestions to generate")
model_name: str | None = Field(default=None, description="Optional model override")
class SuggestionsResponse(BaseModel):
suggestions: list[str] = Field(default_factory=list, description="Suggested follow-up questions")
def _strip_markdown_code_fence(text: str) -> str:
stripped = text.strip()
if not stripped.startswith("```"):
return stripped
lines = stripped.splitlines()
if len(lines) >= 3 and lines[0].startswith("```") and lines[-1].startswith("```"):
return "\n".join(lines[1:-1]).strip()
return stripped
def _parse_json_string_list(text: str) -> list[str] | None:
candidate = _strip_markdown_code_fence(text)
start = candidate.find("[")
end = candidate.rfind("]")
if start == -1 or end == -1 or end <= start:
return None
candidate = candidate[start : end + 1]
try:
data = json.loads(candidate)
except Exception:
return None
if not isinstance(data, list):
return None
out: list[str] = []
for item in data:
if not isinstance(item, str):
continue
s = item.strip()
if not s:
continue
out.append(s)
return out
def _extract_response_text(content: object) -> str:
if isinstance(content, str):
return content
if isinstance(content, list):
parts: list[str] = []
for block in content:
if isinstance(block, str):
parts.append(block)
elif isinstance(block, dict) and block.get("type") in {"text", "output_text"}:
text = block.get("text")
if isinstance(text, str):
parts.append(text)
return "\n".join(parts) if parts else ""
if content is None:
return ""
return str(content)
def _format_conversation(messages: list[SuggestionMessage]) -> str:
parts: list[str] = []
for m in messages:
role = m.role.strip().lower()
if role in ("user", "human"):
parts.append(f"User: {m.content.strip()}")
elif role in ("assistant", "ai"):
parts.append(f"Assistant: {m.content.strip()}")
else:
parts.append(f"{m.role}: {m.content.strip()}")
return "\n".join(parts).strip()
@router.post(
"/threads/{thread_id}/suggestions",
response_model=SuggestionsResponse,
summary="Generate Follow-up Questions",
description="Generate short follow-up questions a user might ask next, based on recent conversation context.",
)
async def generate_suggestions(thread_id: str, request: SuggestionsRequest) -> SuggestionsResponse:
if not request.messages:
return SuggestionsResponse(suggestions=[])
n = request.n
conversation = _format_conversation(request.messages)
if not conversation:
return SuggestionsResponse(suggestions=[])
system_instruction = (
"You are generating follow-up questions to help the user continue the conversation.\n"
f"Based on the conversation below, produce EXACTLY {n} short questions the user might ask next.\n"
"Requirements:\n"
"- Questions must be relevant to the preceding conversation.\n"
"- Questions must be written in the same language as the user.\n"
"- Keep each question concise (ideally <= 20 words / <= 40 Chinese characters).\n"
"- Do NOT include numbering, markdown, or any extra text.\n"
"- Output MUST be a JSON array of strings only.\n"
)
user_content = f"Conversation Context:\n{conversation}\n\nGenerate {n} follow-up questions"
try:
model = create_chat_model(name=request.model_name, thinking_enabled=False)
response = await model.ainvoke([SystemMessage(content=system_instruction), HumanMessage(content=user_content)])
raw = _extract_response_text(response.content)
suggestions = _parse_json_string_list(raw) or []
cleaned = [s.replace("\n", " ").strip() for s in suggestions if s.strip()]
cleaned = cleaned[:n]
return SuggestionsResponse(suggestions=cleaned)
except Exception as exc:
logger.exception("Failed to generate suggestions: thread_id=%s err=%s", thread_id, exc)
return SuggestionsResponse(suggestions=[])
@@ -1,455 +0,0 @@
"""Thread management endpoints.
Provides CRUD operations for threads and checkpoint state management.
"""
from __future__ import annotations
import logging
import time
import uuid
from typing import Any
from fastapi import APIRouter, HTTPException, Request
from pydantic import BaseModel, Field
from app.gateway.dependencies import CurrentCheckpointer, CurrentRunRepository, CurrentThreadMetaStorage
from app.infra.storage import ThreadMetaStorage
from app.plugins.auth.security.actor_context import bind_request_actor_context, resolve_request_user_id
from deerflow.config.paths import Paths, get_paths
from deerflow.runtime import serialize_channel_values
logger = logging.getLogger(__name__)
router = APIRouter(tags=["threads"])
# ---------------------------------------------------------------------------
# Request / Response Models
# ---------------------------------------------------------------------------
class ThreadCreateRequest(BaseModel):
thread_id: str | None = Field(default=None, description="Optional thread ID (auto-generated if omitted)")
assistant_id: str | None = Field(default=None, description="Associate thread with an assistant")
metadata: dict[str, Any] = Field(default_factory=dict, description="Initial metadata")
class ThreadSearchRequest(BaseModel):
metadata: dict[str, Any] = Field(default_factory=dict, description="Metadata filter (exact match)")
limit: int = Field(default=100, ge=1, le=1000, description="Maximum results")
offset: int = Field(default=0, ge=0, description="Pagination offset")
status: str | None = Field(default=None, description="Filter by thread status")
user_id: str | None = Field(default=None, description="Filter by user ID")
assistant_id: str | None = Field(default=None, description="Filter by assistant ID")
class ThreadResponse(BaseModel):
thread_id: str = Field(description="Unique thread identifier")
status: str = Field(default="idle", description="Thread status")
created_at: str = Field(default="", description="ISO timestamp")
updated_at: str = Field(default="", description="ISO timestamp")
metadata: dict[str, Any] = Field(default_factory=dict, description="Thread metadata")
values: dict[str, Any] = Field(default_factory=dict, description="Current state values")
interrupts: dict[str, Any] = Field(default_factory=dict, description="Pending interrupts")
class ThreadDeleteResponse(BaseModel):
success: bool
message: str
class ThreadStateUpdateRequest(BaseModel):
values: dict[str, Any] | None = Field(default=None, description="Channel values to merge")
checkpoint_id: str | None = Field(default=None, description="Checkpoint to branch from")
checkpoint: dict[str, Any] | None = Field(default=None, description="Full checkpoint object")
as_node: str | None = Field(default=None, description="Node identity for the update")
class ThreadStateResponse(BaseModel):
values: dict[str, Any] = Field(default_factory=dict, description="Current channel values")
next: list[str] = Field(default_factory=list, description="Next nodes to execute")
tasks: list[dict[str, Any]] = Field(default_factory=list, description="Interrupted task details")
checkpoint: dict[str, Any] = Field(default_factory=dict, description="Checkpoint info")
checkpoint_id: str | None = Field(default=None, description="Current checkpoint ID")
parent_checkpoint_id: str | None = Field(default=None, description="Parent checkpoint ID")
metadata: dict[str, Any] = Field(default_factory=dict, description="Checkpoint metadata")
created_at: str | None = Field(default=None, description="Checkpoint timestamp")
class ThreadHistoryRequest(BaseModel):
limit: int = Field(default=10, ge=1, le=100, description="Maximum entries")
before: str | None = Field(default=None, description="Cursor for pagination (checkpoint_id)")
class HistoryEntry(BaseModel):
checkpoint_id: str
parent_checkpoint_id: str | None = None
metadata: dict[str, Any] = Field(default_factory=dict)
values: dict[str, Any] = Field(default_factory=dict)
created_at: str | None = None
next: list[str] = Field(default_factory=list)
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def sanitize_log_param(value: str) -> str:
"""Strip control characters to prevent log injection."""
return value.replace("\n", "").replace("\r", "").replace("\x00", "")
def _delete_thread_data(thread_id: str, paths: Paths | None = None) -> ThreadDeleteResponse:
"""Delete local filesystem data for a thread."""
path_manager = paths or get_paths()
try:
path_manager.delete_thread_dir(thread_id)
except ValueError as exc:
raise HTTPException(status_code=422, detail=str(exc)) from exc
except FileNotFoundError:
logger.debug("No local thread data to delete for %s", sanitize_log_param(thread_id))
return ThreadDeleteResponse(success=True, message=f"No local data for {thread_id}")
except Exception as exc:
logger.exception("Failed to delete thread data for %s", sanitize_log_param(thread_id))
raise HTTPException(status_code=500, detail="Failed to delete local thread data.") from exc
logger.info("Deleted local thread data for %s", sanitize_log_param(thread_id))
return ThreadDeleteResponse(success=True, message=f"Deleted local thread data for {thread_id}")
async def _thread_or_run_exists(
*,
request: Request,
thread_id: str,
thread_meta_storage: ThreadMetaStorage,
run_repo,
) -> bool:
request_user_id = resolve_request_user_id(request)
if request_user_id is None:
thread = await thread_meta_storage.get_thread(thread_id, user_id=None)
if thread is not None:
return True
runs = await run_repo.list_by_thread(thread_id, limit=1, user_id=None)
return bool(runs)
with bind_request_actor_context(request):
thread = await thread_meta_storage.get_thread(thread_id)
if thread is not None:
return True
runs = await run_repo.list_by_thread(thread_id, limit=1)
return bool(runs)
# ---------------------------------------------------------------------------
# Endpoints
# ---------------------------------------------------------------------------
@router.post("", response_model=ThreadResponse)
async def create_thread(
body: ThreadCreateRequest,
request: Request,
thread_meta_storage: CurrentThreadMetaStorage,
) -> ThreadResponse:
"""Create a new thread."""
thread_id = body.thread_id or str(uuid.uuid4())
request_user_id = resolve_request_user_id(request)
if request_user_id is None:
existing = await thread_meta_storage.get_thread(thread_id, user_id=None)
else:
with bind_request_actor_context(request):
existing = await thread_meta_storage.get_thread(thread_id)
if existing is not None:
return ThreadResponse(
thread_id=thread_id,
status=existing.status,
created_at=existing.created_time.isoformat() if existing.created_time else "",
updated_at=existing.updated_time.isoformat() if existing.updated_time else "",
metadata=existing.metadata,
)
try:
if request_user_id is None:
created = await thread_meta_storage.ensure_thread(
thread_id=thread_id,
assistant_id=body.assistant_id,
metadata=body.metadata,
user_id=None,
)
else:
with bind_request_actor_context(request):
created = await thread_meta_storage.ensure_thread(
thread_id=thread_id,
assistant_id=body.assistant_id,
metadata=body.metadata,
)
except Exception:
logger.exception("Failed to create thread %s", sanitize_log_param(thread_id))
raise HTTPException(status_code=500, detail="Failed to create thread")
logger.info("Thread created: %s", sanitize_log_param(thread_id))
return ThreadResponse(
thread_id=thread_id,
status=created.status,
created_at=created.created_time.isoformat() if created.created_time else "",
updated_at=created.updated_time.isoformat() if created.updated_time else "",
metadata=created.metadata,
)
@router.post("/search", response_model=list[ThreadResponse])
async def search_threads(
body: ThreadSearchRequest,
request: Request,
thread_meta_storage: CurrentThreadMetaStorage,
) -> list[ThreadResponse]:
"""Search threads with filters."""
try:
request_user_id = resolve_request_user_id(request)
if request_user_id is None:
threads = await thread_meta_storage.search_threads(
metadata=body.metadata or None,
status=body.status,
user_id=body.user_id,
assistant_id=body.assistant_id,
limit=body.limit,
offset=body.offset,
)
else:
with bind_request_actor_context(request):
threads = await thread_meta_storage.search_threads(
metadata=body.metadata or None,
status=body.status,
assistant_id=body.assistant_id,
limit=body.limit,
offset=body.offset,
)
except Exception:
logger.exception("Failed to search threads")
raise HTTPException(status_code=500, detail="Failed to search threads")
return [
ThreadResponse(
thread_id=t.thread_id,
status=t.status,
created_at=t.created_time.isoformat() if t.created_time else "",
updated_at=t.updated_time.isoformat() if t.updated_time else "",
metadata=t.metadata,
values={"title": t.display_name} if t.display_name else {},
interrupts={},
)
for t in threads
]
@router.delete("/{thread_id}", response_model=ThreadDeleteResponse)
async def delete_thread(
thread_id: str,
checkpointer: CurrentCheckpointer,
thread_meta_storage: CurrentThreadMetaStorage,
) -> ThreadDeleteResponse:
"""Delete a thread and all associated data."""
response = _delete_thread_data(thread_id)
# Remove checkpoints (best-effort)
try:
if hasattr(checkpointer, "adelete_thread"):
await checkpointer.adelete_thread(thread_id)
except Exception:
logger.debug("Could not delete checkpoints for thread %s", sanitize_log_param(thread_id))
# Remove thread_meta (best-effort)
try:
await thread_meta_storage.delete_thread(thread_id)
except Exception:
logger.debug("Could not delete thread_meta for %s", sanitize_log_param(thread_id))
return response
@router.get("/{thread_id}/state", response_model=ThreadStateResponse)
async def get_thread_state(
thread_id: str,
request: Request,
checkpointer: CurrentCheckpointer,
thread_meta_storage: CurrentThreadMetaStorage,
run_repo: CurrentRunRepository,
) -> ThreadStateResponse:
"""Get the latest state snapshot for a thread."""
config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
try:
checkpoint_tuple = await checkpointer.aget_tuple(config)
except Exception:
logger.exception("Failed to get state for thread %s", sanitize_log_param(thread_id))
raise HTTPException(status_code=500, detail="Failed to get thread state")
if checkpoint_tuple is None:
if await _thread_or_run_exists(
request=request,
thread_id=thread_id,
thread_meta_storage=thread_meta_storage,
run_repo=run_repo,
):
return ThreadStateResponse()
raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found")
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {}
metadata = getattr(checkpoint_tuple, "metadata", {}) or {}
channel_values = checkpoint.get("channel_values", {})
ckpt_config = getattr(checkpoint_tuple, "config", {}) or {}
checkpoint_id = ckpt_config.get("configurable", {}).get("checkpoint_id")
parent_config = getattr(checkpoint_tuple, "parent_config", None)
parent_checkpoint_id = parent_config.get("configurable", {}).get("checkpoint_id") if parent_config else None
tasks_raw = getattr(checkpoint_tuple, "tasks", []) or []
next_nodes = [t.name for t in tasks_raw if hasattr(t, "name")]
tasks = [{"id": getattr(t, "id", ""), "name": getattr(t, "name", "")} for t in tasks_raw]
return ThreadStateResponse(
values=serialize_channel_values(channel_values),
next=next_nodes,
tasks=tasks,
checkpoint={"id": checkpoint_id, "ts": str(metadata.get("created_at", ""))},
checkpoint_id=checkpoint_id,
parent_checkpoint_id=parent_checkpoint_id,
metadata=metadata,
created_at=str(metadata.get("created_at", "")),
)
@router.post("/{thread_id}/state", response_model=ThreadStateResponse)
async def update_thread_state(
thread_id: str,
body: ThreadStateUpdateRequest,
checkpointer: CurrentCheckpointer,
thread_meta_storage: CurrentThreadMetaStorage,
) -> ThreadStateResponse:
"""Update thread state (human-in-the-loop or title rename)."""
read_config: dict[str, Any] = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
if body.checkpoint_id:
read_config["configurable"]["checkpoint_id"] = body.checkpoint_id
try:
checkpoint_tuple = await checkpointer.aget_tuple(read_config)
except Exception:
logger.exception("Failed to get state for thread %s", sanitize_log_param(thread_id))
raise HTTPException(status_code=500, detail="Failed to get thread state")
if checkpoint_tuple is None:
raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found")
checkpoint: dict[str, Any] = dict(getattr(checkpoint_tuple, "checkpoint", {}) or {})
metadata: dict[str, Any] = dict(getattr(checkpoint_tuple, "metadata", {}) or {})
channel_values: dict[str, Any] = dict(checkpoint.get("channel_values", {}))
if body.values:
channel_values.update(body.values)
checkpoint["channel_values"] = channel_values
metadata["updated_at"] = time.time()
if body.as_node:
metadata["source"] = "update"
metadata["step"] = metadata.get("step", 0) + 1
metadata["writes"] = {body.as_node: body.values}
write_config: dict[str, Any] = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
try:
new_config = await checkpointer.aput(write_config, checkpoint, metadata, {})
except Exception:
logger.exception("Failed to update state for thread %s", sanitize_log_param(thread_id))
raise HTTPException(status_code=500, detail="Failed to update thread state")
new_checkpoint_id: str | None = None
if isinstance(new_config, dict):
new_checkpoint_id = new_config.get("configurable", {}).get("checkpoint_id")
# Sync title to thread_meta
if body.values and "title" in body.values:
new_title = body.values["title"]
if new_title:
try:
await thread_meta_storage.sync_thread_title(
thread_id=thread_id,
title=new_title,
)
except Exception:
logger.debug("Failed to sync title for %s", sanitize_log_param(thread_id))
return ThreadStateResponse(
values=serialize_channel_values(channel_values),
next=[],
metadata=metadata,
checkpoint_id=new_checkpoint_id,
created_at=str(metadata.get("created_at", "")),
)
@router.post("/{thread_id}/history", response_model=list[HistoryEntry])
async def get_thread_history(
thread_id: str,
body: ThreadHistoryRequest,
request: Request,
checkpointer: CurrentCheckpointer,
thread_meta_storage: CurrentThreadMetaStorage,
run_repo: CurrentRunRepository,
) -> list[HistoryEntry]:
"""Get checkpoint history for a thread."""
config: dict[str, Any] = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
if body.before:
config["configurable"]["checkpoint_id"] = body.before
entries: list[HistoryEntry] = []
is_first = True
try:
async for checkpoint_tuple in checkpointer.alist(config, limit=body.limit):
ckpt_config = getattr(checkpoint_tuple, "config", {}) or {}
parent_config = getattr(checkpoint_tuple, "parent_config", None)
metadata = getattr(checkpoint_tuple, "metadata", {}) or {}
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {}
checkpoint_id = ckpt_config.get("configurable", {}).get("checkpoint_id", "")
parent_id = parent_config.get("configurable", {}).get("checkpoint_id") if parent_config else None
channel_values = checkpoint.get("channel_values", {})
values: dict[str, Any] = {}
if title := channel_values.get("title"):
values["title"] = title
if is_first and (messages := channel_values.get("messages")):
values["messages"] = serialize_channel_values({"messages": messages}).get("messages", [])
is_first = False
tasks_raw = getattr(checkpoint_tuple, "tasks", []) or []
next_nodes = [t.name for t in tasks_raw if hasattr(t, "name")]
entries.append(
HistoryEntry(
checkpoint_id=checkpoint_id,
parent_checkpoint_id=parent_id,
metadata=metadata,
values=values,
created_at=str(metadata.get("created_at", "")),
next=next_nodes,
)
)
except Exception:
logger.exception("Failed to get history for thread %s", sanitize_log_param(thread_id))
raise HTTPException(status_code=500, detail="Failed to get thread history")
if not entries and await _thread_or_run_exists(
request=request,
thread_id=thread_id,
thread_meta_storage=thread_meta_storage,
run_repo=run_repo,
):
return []
return entries
+72 -95
View File
@@ -1,9 +1,8 @@
"""Memory API router for retrieving and managing global memory data."""
from fastapi import APIRouter, HTTPException, Request
from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field
from app.plugins.auth.security.actor_context import bind_request_actor_context
from deerflow.agents.memory.updater import (
clear_memory_data,
create_memory_fact,
@@ -14,7 +13,6 @@ from deerflow.agents.memory.updater import (
update_memory_fact,
)
from deerflow.config.memory_config import get_memory_config
from deerflow.runtime.actor_context import get_effective_user_id
router = APIRouter(prefix="/api", tags=["memory"])
@@ -51,7 +49,6 @@ class Fact(BaseModel):
confidence: float = Field(default=0.5, description="Confidence score (0-1)")
createdAt: str = Field(default="", description="Creation timestamp")
source: str = Field(default="unknown", description="Source thread ID")
sourceError: str | None = Field(default=None, description="Optional description of the prior mistake or wrong approach")
class MemoryResponse(BaseModel):
@@ -111,11 +108,10 @@ class MemoryStatusResponse(BaseModel):
@router.get(
"/memory",
response_model=MemoryResponse,
response_model_exclude_none=True,
summary="Get Memory Data",
description="Retrieve the current global memory data including user context, history, and facts.",
)
async def get_memory(request: Request) -> MemoryResponse:
async def get_memory() -> MemoryResponse:
"""Get the current global memory data.
Returns:
@@ -149,19 +145,17 @@ async def get_memory(request: Request) -> MemoryResponse:
}
```
"""
with bind_request_actor_context(request):
memory_data = get_memory_data(user_id=get_effective_user_id())
return MemoryResponse(**memory_data)
memory_data = get_memory_data()
return MemoryResponse(**memory_data)
@router.post(
"/memory/reload",
response_model=MemoryResponse,
response_model_exclude_none=True,
summary="Reload Memory Data",
description="Reload memory data from the storage file, refreshing the in-memory cache.",
)
async def reload_memory(request: Request) -> MemoryResponse:
async def reload_memory() -> MemoryResponse:
"""Reload memory data from file.
This forces a reload of the memory data from the storage file,
@@ -170,132 +164,117 @@ async def reload_memory(request: Request) -> MemoryResponse:
Returns:
The reloaded memory data.
"""
with bind_request_actor_context(request):
memory_data = reload_memory_data(user_id=get_effective_user_id())
return MemoryResponse(**memory_data)
memory_data = reload_memory_data()
return MemoryResponse(**memory_data)
@router.delete(
"/memory",
response_model=MemoryResponse,
response_model_exclude_none=True,
summary="Clear All Memory Data",
description="Delete all saved memory data and reset the memory structure to an empty state.",
)
async def clear_memory(request: Request) -> MemoryResponse:
async def clear_memory() -> MemoryResponse:
"""Clear all persisted memory data."""
with bind_request_actor_context(request):
try:
memory_data = clear_memory_data(user_id=get_effective_user_id())
except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to clear memory data.") from exc
try:
memory_data = clear_memory_data()
except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to clear memory data.") from exc
return MemoryResponse(**memory_data)
return MemoryResponse(**memory_data)
@router.post(
"/memory/facts",
response_model=MemoryResponse,
response_model_exclude_none=True,
summary="Create Memory Fact",
description="Create a single saved memory fact manually.",
)
async def create_memory_fact_endpoint(request: Request, payload: FactCreateRequest) -> MemoryResponse:
async def create_memory_fact_endpoint(request: FactCreateRequest) -> MemoryResponse:
"""Create a single fact manually."""
with bind_request_actor_context(request):
try:
memory_data = create_memory_fact(
content=payload.content,
category=payload.category,
confidence=payload.confidence,
user_id=get_effective_user_id(),
)
except ValueError as exc:
raise _map_memory_fact_value_error(exc) from exc
except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to create memory fact.") from exc
try:
memory_data = create_memory_fact(
content=request.content,
category=request.category,
confidence=request.confidence,
)
except ValueError as exc:
raise _map_memory_fact_value_error(exc) from exc
except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to create memory fact.") from exc
return MemoryResponse(**memory_data)
return MemoryResponse(**memory_data)
@router.delete(
"/memory/facts/{fact_id}",
response_model=MemoryResponse,
response_model_exclude_none=True,
summary="Delete Memory Fact",
description="Delete a single saved memory fact by its fact id.",
)
async def delete_memory_fact_endpoint(fact_id: str, request: Request) -> MemoryResponse:
async def delete_memory_fact_endpoint(fact_id: str) -> MemoryResponse:
"""Delete a single fact from memory by fact id."""
with bind_request_actor_context(request):
try:
memory_data = delete_memory_fact(fact_id, user_id=get_effective_user_id())
except KeyError as exc:
raise HTTPException(status_code=404, detail=f"Memory fact '{fact_id}' not found.") from exc
except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to delete memory fact.") from exc
try:
memory_data = delete_memory_fact(fact_id)
except KeyError as exc:
raise HTTPException(status_code=404, detail=f"Memory fact '{fact_id}' not found.") from exc
except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to delete memory fact.") from exc
return MemoryResponse(**memory_data)
return MemoryResponse(**memory_data)
@router.patch(
"/memory/facts/{fact_id}",
response_model=MemoryResponse,
response_model_exclude_none=True,
summary="Patch Memory Fact",
description="Partially update a single saved memory fact by its fact id while preserving omitted fields.",
)
async def update_memory_fact_endpoint(fact_id: str, request: Request, payload: FactPatchRequest) -> MemoryResponse:
async def update_memory_fact_endpoint(fact_id: str, request: FactPatchRequest) -> MemoryResponse:
"""Partially update a single fact manually."""
with bind_request_actor_context(request):
try:
memory_data = update_memory_fact(
fact_id=fact_id,
content=payload.content,
category=payload.category,
confidence=payload.confidence,
user_id=get_effective_user_id(),
)
except ValueError as exc:
raise _map_memory_fact_value_error(exc) from exc
except KeyError as exc:
raise HTTPException(status_code=404, detail=f"Memory fact '{fact_id}' not found.") from exc
except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to update memory fact.") from exc
try:
memory_data = update_memory_fact(
fact_id=fact_id,
content=request.content,
category=request.category,
confidence=request.confidence,
)
except ValueError as exc:
raise _map_memory_fact_value_error(exc) from exc
except KeyError as exc:
raise HTTPException(status_code=404, detail=f"Memory fact '{fact_id}' not found.") from exc
except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to update memory fact.") from exc
return MemoryResponse(**memory_data)
return MemoryResponse(**memory_data)
@router.get(
"/memory/export",
response_model=MemoryResponse,
response_model_exclude_none=True,
summary="Export Memory Data",
description="Export the current global memory data as JSON for backup or transfer.",
)
async def export_memory(request: Request) -> MemoryResponse:
async def export_memory() -> MemoryResponse:
"""Export the current memory data."""
with bind_request_actor_context(request):
memory_data = get_memory_data(user_id=get_effective_user_id())
return MemoryResponse(**memory_data)
memory_data = get_memory_data()
return MemoryResponse(**memory_data)
@router.post(
"/memory/import",
response_model=MemoryResponse,
response_model_exclude_none=True,
summary="Import Memory Data",
description="Import and overwrite the current global memory data from a JSON payload.",
)
async def import_memory(request: Request, payload: MemoryResponse) -> MemoryResponse:
async def import_memory(request: MemoryResponse) -> MemoryResponse:
"""Import and persist memory data."""
with bind_request_actor_context(request):
try:
memory_data = import_memory_data(payload.model_dump(), user_id=get_effective_user_id())
except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to import memory data.") from exc
try:
memory_data = import_memory_data(request.model_dump())
except OSError as exc:
raise HTTPException(status_code=500, detail="Failed to import memory data.") from exc
return MemoryResponse(**memory_data)
return MemoryResponse(**memory_data)
@router.get(
@@ -338,29 +317,27 @@ async def get_memory_config_endpoint() -> MemoryConfigResponse:
@router.get(
"/memory/status",
response_model=MemoryStatusResponse,
response_model_exclude_none=True,
summary="Get Memory Status",
description="Retrieve both memory configuration and current data in a single request.",
)
async def get_memory_status(request: Request) -> MemoryStatusResponse:
async def get_memory_status() -> MemoryStatusResponse:
"""Get the memory system status including configuration and data.
Returns:
Combined memory configuration and current data.
"""
with bind_request_actor_context(request):
config = get_memory_config()
memory_data = get_memory_data(user_id=get_effective_user_id())
config = get_memory_config()
memory_data = get_memory_data()
return MemoryStatusResponse(
config=MemoryConfigResponse(
enabled=config.enabled,
storage_path=config.storage_path,
debounce_seconds=config.debounce_seconds,
max_facts=config.max_facts,
fact_confidence_threshold=config.fact_confidence_threshold,
injection_enabled=config.injection_enabled,
max_injection_tokens=config.max_injection_tokens,
),
data=MemoryResponse(**memory_data),
)
return MemoryStatusResponse(
config=MemoryConfigResponse(
enabled=config.enabled,
storage_path=config.storage_path,
debounce_seconds=config.debounce_seconds,
max_facts=config.max_facts,
fact_confidence_threshold=config.fact_confidence_threshold,
injection_enabled=config.injection_enabled,
max_injection_tokens=config.max_injection_tokens,
),
data=MemoryResponse(**memory_data),
)
+86
View File
@@ -0,0 +1,86 @@
"""Stateless runs endpoints -- stream and wait without a pre-existing thread.
These endpoints auto-create a temporary thread when no ``thread_id`` is
supplied in the request body. When a ``thread_id`` **is** provided, it
is reused so that conversation history is preserved across calls.
"""
from __future__ import annotations
import asyncio
import logging
import uuid
from fastapi import APIRouter, Request
from fastapi.responses import StreamingResponse
from app.gateway.deps import get_checkpointer, get_run_manager, get_stream_bridge
from app.gateway.routers.thread_runs import RunCreateRequest
from app.gateway.services import sse_consumer, start_run
from deerflow.runtime import serialize_channel_values
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/runs", tags=["runs"])
def _resolve_thread_id(body: RunCreateRequest) -> str:
"""Return the thread_id from the request body, or generate a new one."""
thread_id = (body.config or {}).get("configurable", {}).get("thread_id")
if thread_id:
return str(thread_id)
return str(uuid.uuid4())
@router.post("/stream")
async def stateless_stream(body: RunCreateRequest, request: Request) -> StreamingResponse:
"""Create a run and stream events via SSE.
If ``config.configurable.thread_id`` is provided, the run is created
on the given thread so that conversation history is preserved.
Otherwise a new temporary thread is created.
"""
thread_id = _resolve_thread_id(body)
bridge = get_stream_bridge(request)
run_mgr = get_run_manager(request)
record = await start_run(body, thread_id, request)
return StreamingResponse(
sse_consumer(bridge, record, request, run_mgr),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
},
)
@router.post("/wait", response_model=dict)
async def stateless_wait(body: RunCreateRequest, request: Request) -> dict:
"""Create a run and block until completion.
If ``config.configurable.thread_id`` is provided, the run is created
on the given thread so that conversation history is preserved.
Otherwise a new temporary thread is created.
"""
thread_id = _resolve_thread_id(body)
record = await start_run(body, thread_id, request)
if record.task is not None:
try:
await record.task
except asyncio.CancelledError:
pass
checkpointer = get_checkpointer(request)
config = {"configurable": {"thread_id": thread_id}}
try:
checkpoint_tuple = await checkpointer.aget_tuple(config)
if checkpoint_tuple is not None:
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {}
channel_values = checkpoint.get("channel_values", {})
return serialize_channel_values(channel_values)
except Exception:
logger.exception("Failed to fetch final state for run %s", record.run_id)
return {"status": record.status.value, "error": record.error}
+24 -207
View File
@@ -1,29 +1,14 @@
import json
import logging
import shutil
from pathlib import Path
from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field
from app.gateway.path_utils import resolve_thread_virtual_path
from deerflow.agents.lead_agent.prompt import refresh_skills_system_prompt_cache_async
from deerflow.config.extensions_config import ExtensionsConfig, SkillStateConfig, get_extensions_config, reload_extensions_config
from deerflow.skills import Skill, load_skills
from deerflow.skills.installer import SkillAlreadyExistsError, install_skill_from_archive
from deerflow.skills.manager import (
append_history,
atomic_write,
custom_skill_exists,
ensure_custom_skill_is_editable,
get_custom_skill_dir,
get_custom_skill_file,
get_skill_history_file,
read_custom_skill_content,
read_history,
validate_skill_markdown_content,
)
from deerflow.skills.security_scanner import scan_skill_content
logger = logging.getLogger(__name__)
@@ -67,22 +52,6 @@ class SkillInstallResponse(BaseModel):
message: str = Field(..., description="Installation result message")
class CustomSkillContentResponse(SkillResponse):
content: str = Field(..., description="Raw SKILL.md content")
class CustomSkillUpdateRequest(BaseModel):
content: str = Field(..., description="Replacement SKILL.md content")
class CustomSkillHistoryResponse(BaseModel):
history: list[dict]
class SkillRollbackRequest(BaseModel):
history_index: int = Field(default=-1, description="History entry index to restore from, defaulting to the latest change.")
def _skill_to_response(skill: Skill) -> SkillResponse:
"""Convert a Skill object to a SkillResponse."""
return SkillResponse(
@@ -109,181 +78,6 @@ async def list_skills() -> SkillsListResponse:
raise HTTPException(status_code=500, detail=f"Failed to load skills: {str(e)}")
@router.post(
"/skills/install",
response_model=SkillInstallResponse,
summary="Install Skill",
description="Install a skill from a .skill file (ZIP archive) located in the thread's user-data directory.",
)
async def install_skill(request: SkillInstallRequest) -> SkillInstallResponse:
try:
skill_file_path = resolve_thread_virtual_path(request.thread_id, request.path)
result = install_skill_from_archive(skill_file_path)
await refresh_skills_system_prompt_cache_async()
return SkillInstallResponse(**result)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except SkillAlreadyExistsError as e:
raise HTTPException(status_code=409, detail=str(e))
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except HTTPException:
raise
except Exception as e:
logger.error(f"Failed to install skill: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to install skill: {str(e)}")
@router.get("/skills/custom", response_model=SkillsListResponse, summary="List Custom Skills")
async def list_custom_skills() -> SkillsListResponse:
try:
skills = [skill for skill in load_skills(enabled_only=False) if skill.category == "custom"]
return SkillsListResponse(skills=[_skill_to_response(skill) for skill in skills])
except Exception as e:
logger.error("Failed to list custom skills: %s", e, exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to list custom skills: {str(e)}")
@router.get("/skills/custom/{skill_name}", response_model=CustomSkillContentResponse, summary="Get Custom Skill Content")
async def get_custom_skill(skill_name: str) -> CustomSkillContentResponse:
try:
skills = load_skills(enabled_only=False)
skill = next((s for s in skills if s.name == skill_name and s.category == "custom"), None)
if skill is None:
raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found")
return CustomSkillContentResponse(**_skill_to_response(skill).model_dump(), content=read_custom_skill_content(skill_name))
except HTTPException:
raise
except Exception as e:
logger.error("Failed to get custom skill %s: %s", skill_name, e, exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to get custom skill: {str(e)}")
@router.put("/skills/custom/{skill_name}", response_model=CustomSkillContentResponse, summary="Edit Custom Skill")
async def update_custom_skill(skill_name: str, request: CustomSkillUpdateRequest) -> CustomSkillContentResponse:
try:
ensure_custom_skill_is_editable(skill_name)
validate_skill_markdown_content(skill_name, request.content)
scan = await scan_skill_content(request.content, executable=False, location=f"{skill_name}/SKILL.md")
if scan.decision == "block":
raise HTTPException(status_code=400, detail=f"Security scan blocked the edit: {scan.reason}")
skill_file = get_custom_skill_dir(skill_name) / "SKILL.md"
prev_content = skill_file.read_text(encoding="utf-8")
atomic_write(skill_file, request.content)
append_history(
skill_name,
{
"action": "human_edit",
"author": "human",
"thread_id": None,
"file_path": "SKILL.md",
"prev_content": prev_content,
"new_content": request.content,
"scanner": {"decision": scan.decision, "reason": scan.reason},
},
)
await refresh_skills_system_prompt_cache_async()
return await get_custom_skill(skill_name)
except HTTPException:
raise
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
logger.error("Failed to update custom skill %s: %s", skill_name, e, exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to update custom skill: {str(e)}")
@router.delete("/skills/custom/{skill_name}", summary="Delete Custom Skill")
async def delete_custom_skill(skill_name: str) -> dict[str, bool]:
try:
ensure_custom_skill_is_editable(skill_name)
skill_dir = get_custom_skill_dir(skill_name)
prev_content = read_custom_skill_content(skill_name)
append_history(
skill_name,
{
"action": "human_delete",
"author": "human",
"thread_id": None,
"file_path": "SKILL.md",
"prev_content": prev_content,
"new_content": None,
"scanner": {"decision": "allow", "reason": "Deletion requested."},
},
)
shutil.rmtree(skill_dir)
await refresh_skills_system_prompt_cache_async()
return {"success": True}
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
logger.error("Failed to delete custom skill %s: %s", skill_name, e, exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to delete custom skill: {str(e)}")
@router.get("/skills/custom/{skill_name}/history", response_model=CustomSkillHistoryResponse, summary="Get Custom Skill History")
async def get_custom_skill_history(skill_name: str) -> CustomSkillHistoryResponse:
try:
if not custom_skill_exists(skill_name) and not get_skill_history_file(skill_name).exists():
raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found")
return CustomSkillHistoryResponse(history=read_history(skill_name))
except HTTPException:
raise
except Exception as e:
logger.error("Failed to read history for %s: %s", skill_name, e, exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to read history: {str(e)}")
@router.post("/skills/custom/{skill_name}/rollback", response_model=CustomSkillContentResponse, summary="Rollback Custom Skill")
async def rollback_custom_skill(skill_name: str, request: SkillRollbackRequest) -> CustomSkillContentResponse:
try:
if not custom_skill_exists(skill_name) and not get_skill_history_file(skill_name).exists():
raise HTTPException(status_code=404, detail=f"Custom skill '{skill_name}' not found")
history = read_history(skill_name)
if not history:
raise HTTPException(status_code=400, detail=f"Custom skill '{skill_name}' has no history")
record = history[request.history_index]
target_content = record.get("prev_content")
if target_content is None:
raise HTTPException(status_code=400, detail="Selected history entry has no previous content to roll back to")
validate_skill_markdown_content(skill_name, target_content)
scan = await scan_skill_content(target_content, executable=False, location=f"{skill_name}/SKILL.md")
skill_file = get_custom_skill_file(skill_name)
current_content = skill_file.read_text(encoding="utf-8") if skill_file.exists() else None
history_entry = {
"action": "rollback",
"author": "human",
"thread_id": None,
"file_path": "SKILL.md",
"prev_content": current_content,
"new_content": target_content,
"rollback_from_ts": record.get("ts"),
"scanner": {"decision": scan.decision, "reason": scan.reason},
}
if scan.decision == "block":
append_history(skill_name, history_entry)
raise HTTPException(status_code=400, detail=f"Rollback blocked by security scanner: {scan.reason}")
atomic_write(skill_file, target_content)
append_history(skill_name, history_entry)
await refresh_skills_system_prompt_cache_async()
return await get_custom_skill(skill_name)
except HTTPException:
raise
except IndexError:
raise HTTPException(status_code=400, detail="history_index is out of range")
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
logger.error("Failed to roll back custom skill %s: %s", skill_name, e, exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to roll back custom skill: {str(e)}")
@router.get(
"/skills/{skill_name}",
response_model=SkillResponse,
@@ -338,7 +132,6 @@ async def update_skill(skill_name: str, request: SkillUpdateRequest) -> SkillRes
logger.info(f"Skills configuration updated and saved to: {config_path}")
reload_extensions_config()
await refresh_skills_system_prompt_cache_async()
skills = load_skills(enabled_only=False)
updated_skill = next((s for s in skills if s.name == skill_name), None)
@@ -354,3 +147,27 @@ async def update_skill(skill_name: str, request: SkillUpdateRequest) -> SkillRes
except Exception as e:
logger.error(f"Failed to update skill {skill_name}: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to update skill: {str(e)}")
@router.post(
"/skills/install",
response_model=SkillInstallResponse,
summary="Install Skill",
description="Install a skill from a .skill file (ZIP archive) located in the thread's user-data directory.",
)
async def install_skill(request: SkillInstallRequest) -> SkillInstallResponse:
try:
skill_file_path = resolve_thread_virtual_path(request.thread_id, request.path)
result = install_skill_from_archive(skill_file_path)
return SkillInstallResponse(**result)
except FileNotFoundError as e:
raise HTTPException(status_code=404, detail=str(e))
except SkillAlreadyExistsError as e:
raise HTTPException(status_code=409, detail=str(e))
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
except HTTPException:
raise
except Exception as e:
logger.error(f"Failed to install skill: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to install skill: {str(e)}")
+12 -12
View File
@@ -1,8 +1,7 @@
import json
import logging
from fastapi import APIRouter, Request
from langchain_core.messages import HumanMessage, SystemMessage
from fastapi import APIRouter
from pydantic import BaseModel, Field
from deerflow.models import create_chat_model
@@ -98,30 +97,31 @@ def _format_conversation(messages: list[SuggestionMessage]) -> str:
summary="Generate Follow-up Questions",
description="Generate short follow-up questions a user might ask next, based on recent conversation context.",
)
async def generate_suggestions(thread_id: str, body: SuggestionsRequest, request: Request) -> SuggestionsResponse:
if not body.messages:
async def generate_suggestions(thread_id: str, request: SuggestionsRequest) -> SuggestionsResponse:
if not request.messages:
return SuggestionsResponse(suggestions=[])
n = body.n
conversation = _format_conversation(body.messages)
n = request.n
conversation = _format_conversation(request.messages)
if not conversation:
return SuggestionsResponse(suggestions=[])
system_instruction = (
prompt = (
"You are generating follow-up questions to help the user continue the conversation.\n"
f"Based on the conversation below, produce EXACTLY {n} short questions the user might ask next.\n"
"Requirements:\n"
"- Questions must be relevant to the preceding conversation.\n"
"- Questions must be relevant to the conversation.\n"
"- Questions must be written in the same language as the user.\n"
"- Keep each question concise (ideally <= 20 words / <= 40 Chinese characters).\n"
"- Do NOT include numbering, markdown, or any extra text.\n"
"- Output MUST be a JSON array of strings only.\n"
"- Output MUST be a JSON array of strings only.\n\n"
"Conversation:\n"
f"{conversation}\n"
)
user_content = f"Conversation Context:\n{conversation}\n\nGenerate {n} follow-up questions"
try:
model = create_chat_model(name=body.model_name, thinking_enabled=False)
response = await model.ainvoke([SystemMessage(content=system_instruction), HumanMessage(content=user_content)])
model = create_chat_model(name=request.model_name, thinking_enabled=False)
response = model.invoke(prompt)
raw = _extract_response_text(response.content)
suggestions = _parse_json_string_list(raw) or []
cleaned = [s.replace("\n", " ").strip() for s in suggestions if s.strip()]
+265
View File
@@ -0,0 +1,265 @@
"""Runs endpoints — create, stream, wait, cancel.
Implements the LangGraph Platform runs API on top of
:class:`deerflow.agents.runs.RunManager` and
:class:`deerflow.agents.stream_bridge.StreamBridge`.
SSE format is aligned with the LangGraph Platform protocol so that
the ``useStream`` React hook from ``@langchain/langgraph-sdk/react``
works without modification.
"""
from __future__ import annotations
import asyncio
import logging
from typing import Any, Literal
from fastapi import APIRouter, HTTPException, Query, Request
from fastapi.responses import Response, StreamingResponse
from pydantic import BaseModel, Field
from app.gateway.deps import get_checkpointer, get_run_manager, get_stream_bridge
from app.gateway.services import sse_consumer, start_run
from deerflow.runtime import RunRecord, serialize_channel_values
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/threads", tags=["runs"])
# ---------------------------------------------------------------------------
# Request / response models
# ---------------------------------------------------------------------------
class RunCreateRequest(BaseModel):
assistant_id: str | None = Field(default=None, description="Agent / assistant to use")
input: dict[str, Any] | None = Field(default=None, description="Graph input (e.g. {messages: [...]})")
command: dict[str, Any] | None = Field(default=None, description="LangGraph Command")
metadata: dict[str, Any] | None = Field(default=None, description="Run metadata")
config: dict[str, Any] | None = Field(default=None, description="RunnableConfig overrides")
webhook: str | None = Field(default=None, description="Completion callback URL")
checkpoint_id: str | None = Field(default=None, description="Resume from checkpoint")
checkpoint: dict[str, Any] | None = Field(default=None, description="Full checkpoint object")
interrupt_before: list[str] | Literal["*"] | None = Field(default=None, description="Nodes to interrupt before")
interrupt_after: list[str] | Literal["*"] | None = Field(default=None, description="Nodes to interrupt after")
stream_mode: list[str] | str | None = Field(default=None, description="Stream mode(s)")
stream_subgraphs: bool = Field(default=False, description="Include subgraph events")
stream_resumable: bool | None = Field(default=None, description="SSE resumable mode")
on_disconnect: Literal["cancel", "continue"] = Field(default="cancel", description="Behaviour on SSE disconnect")
on_completion: Literal["delete", "keep"] = Field(default="keep", description="Delete temp thread on completion")
multitask_strategy: Literal["reject", "rollback", "interrupt", "enqueue"] = Field(default="reject", description="Concurrency strategy")
after_seconds: float | None = Field(default=None, description="Delayed execution")
if_not_exists: Literal["reject", "create"] = Field(default="create", description="Thread creation policy")
feedback_keys: list[str] | None = Field(default=None, description="LangSmith feedback keys")
class RunResponse(BaseModel):
run_id: str
thread_id: str
assistant_id: str | None = None
status: str
metadata: dict[str, Any] = Field(default_factory=dict)
kwargs: dict[str, Any] = Field(default_factory=dict)
multitask_strategy: str = "reject"
created_at: str = ""
updated_at: str = ""
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _record_to_response(record: RunRecord) -> RunResponse:
return RunResponse(
run_id=record.run_id,
thread_id=record.thread_id,
assistant_id=record.assistant_id,
status=record.status.value,
metadata=record.metadata,
kwargs=record.kwargs,
multitask_strategy=record.multitask_strategy,
created_at=record.created_at,
updated_at=record.updated_at,
)
# ---------------------------------------------------------------------------
# Endpoints
# ---------------------------------------------------------------------------
@router.post("/{thread_id}/runs", response_model=RunResponse)
async def create_run(thread_id: str, body: RunCreateRequest, request: Request) -> RunResponse:
"""Create a background run (returns immediately)."""
record = await start_run(body, thread_id, request)
return _record_to_response(record)
@router.post("/{thread_id}/runs/stream")
async def stream_run(thread_id: str, body: RunCreateRequest, request: Request) -> StreamingResponse:
"""Create a run and stream events via SSE.
The response includes a ``Content-Location`` header with the run's
resource URL, matching the LangGraph Platform protocol. The
``useStream`` React hook uses this to extract run metadata.
"""
bridge = get_stream_bridge(request)
run_mgr = get_run_manager(request)
record = await start_run(body, thread_id, request)
return StreamingResponse(
sse_consumer(bridge, record, request, run_mgr),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
# LangGraph Platform includes run metadata in this header.
# The SDK's _get_run_metadata_from_response() parses it.
"Content-Location": (f"/api/threads/{thread_id}/runs/{record.run_id}/stream?thread_id={thread_id}&run_id={record.run_id}"),
},
)
@router.post("/{thread_id}/runs/wait", response_model=dict)
async def wait_run(thread_id: str, body: RunCreateRequest, request: Request) -> dict:
"""Create a run and block until it completes, returning the final state."""
record = await start_run(body, thread_id, request)
if record.task is not None:
try:
await record.task
except asyncio.CancelledError:
pass
checkpointer = get_checkpointer(request)
config = {"configurable": {"thread_id": thread_id}}
try:
checkpoint_tuple = await checkpointer.aget_tuple(config)
if checkpoint_tuple is not None:
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {}
channel_values = checkpoint.get("channel_values", {})
return serialize_channel_values(channel_values)
except Exception:
logger.exception("Failed to fetch final state for run %s", record.run_id)
return {"status": record.status.value, "error": record.error}
@router.get("/{thread_id}/runs", response_model=list[RunResponse])
async def list_runs(thread_id: str, request: Request) -> list[RunResponse]:
"""List all runs for a thread."""
run_mgr = get_run_manager(request)
records = await run_mgr.list_by_thread(thread_id)
return [_record_to_response(r) for r in records]
@router.get("/{thread_id}/runs/{run_id}", response_model=RunResponse)
async def get_run(thread_id: str, run_id: str, request: Request) -> RunResponse:
"""Get details of a specific run."""
run_mgr = get_run_manager(request)
record = run_mgr.get(run_id)
if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
return _record_to_response(record)
@router.post("/{thread_id}/runs/{run_id}/cancel")
async def cancel_run(
thread_id: str,
run_id: str,
request: Request,
wait: bool = Query(default=False, description="Block until run completes after cancel"),
action: Literal["interrupt", "rollback"] = Query(default="interrupt", description="Cancel action"),
) -> Response:
"""Cancel a running or pending run.
- action=interrupt: Stop execution, keep current checkpoint (can be resumed)
- action=rollback: Stop execution, revert to pre-run checkpoint state
- wait=true: Block until the run fully stops, return 204
- wait=false: Return immediately with 202
"""
run_mgr = get_run_manager(request)
record = run_mgr.get(run_id)
if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
cancelled = await run_mgr.cancel(run_id, action=action)
if not cancelled:
raise HTTPException(
status_code=409,
detail=f"Run {run_id} is not cancellable (status: {record.status.value})",
)
if wait and record.task is not None:
try:
await record.task
except asyncio.CancelledError:
pass
return Response(status_code=204)
return Response(status_code=202)
@router.get("/{thread_id}/runs/{run_id}/join")
async def join_run(thread_id: str, run_id: str, request: Request) -> StreamingResponse:
"""Join an existing run's SSE stream."""
bridge = get_stream_bridge(request)
run_mgr = get_run_manager(request)
record = run_mgr.get(run_id)
if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
return StreamingResponse(
sse_consumer(bridge, record, request, run_mgr),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
},
)
@router.api_route("/{thread_id}/runs/{run_id}/stream", methods=["GET", "POST"], response_model=None)
async def stream_existing_run(
thread_id: str,
run_id: str,
request: Request,
action: Literal["interrupt", "rollback"] | None = Query(default=None, description="Cancel action"),
wait: int = Query(default=0, description="Block until cancelled (1) or return immediately (0)"),
):
"""Join an existing run's SSE stream (GET), or cancel-then-stream (POST).
The LangGraph SDK's ``joinStream`` and ``useStream`` stop button both use
``POST`` to this endpoint. When ``action=interrupt`` or ``action=rollback``
is present the run is cancelled first; the response then streams any
remaining buffered events so the client observes a clean shutdown.
"""
run_mgr = get_run_manager(request)
record = run_mgr.get(run_id)
if record is None or record.thread_id != thread_id:
raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
# Cancel if an action was requested (stop-button / interrupt flow)
if action is not None:
cancelled = await run_mgr.cancel(run_id, action=action)
if cancelled and wait and record.task is not None:
try:
await record.task
except (asyncio.CancelledError, Exception):
pass
return Response(status_code=204)
bridge = get_stream_bridge(request)
return StreamingResponse(
sse_consumer(bridge, record, request, run_mgr),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
},
)
+679
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@@ -0,0 +1,679 @@
"""Thread CRUD, state, and history endpoints.
Combines the existing thread-local filesystem cleanup with LangGraph
Platform-compatible thread management backed by the checkpointer.
Channel values returned in state responses are serialized through
:func:`deerflow.runtime.serialization.serialize_channel_values` to
ensure LangChain message objects are converted to JSON-safe dicts
matching the LangGraph Platform wire format expected by the
``useStream`` React hook.
"""
from __future__ import annotations
import logging
import time
import uuid
from typing import Any
from fastapi import APIRouter, HTTPException, Request
from pydantic import BaseModel, Field
from app.gateway.deps import get_checkpointer, get_store
from deerflow.config.paths import Paths, get_paths
from deerflow.runtime import serialize_channel_values
# ---------------------------------------------------------------------------
# Store namespace
# ---------------------------------------------------------------------------
THREADS_NS: tuple[str, ...] = ("threads",)
"""Namespace used by the Store for thread metadata records."""
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/threads", tags=["threads"])
# ---------------------------------------------------------------------------
# Response / request models
# ---------------------------------------------------------------------------
class ThreadDeleteResponse(BaseModel):
"""Response model for thread cleanup."""
success: bool
message: str
class ThreadResponse(BaseModel):
"""Response model for a single thread."""
thread_id: str = Field(description="Unique thread identifier")
status: str = Field(default="idle", description="Thread status: idle, busy, interrupted, error")
created_at: str = Field(default="", description="ISO timestamp")
updated_at: str = Field(default="", description="ISO timestamp")
metadata: dict[str, Any] = Field(default_factory=dict, description="Thread metadata")
values: dict[str, Any] = Field(default_factory=dict, description="Current state channel values")
interrupts: dict[str, Any] = Field(default_factory=dict, description="Pending interrupts")
class ThreadCreateRequest(BaseModel):
"""Request body for creating a thread."""
thread_id: str | None = Field(default=None, description="Optional thread ID (auto-generated if omitted)")
metadata: dict[str, Any] = Field(default_factory=dict, description="Initial metadata")
class ThreadSearchRequest(BaseModel):
"""Request body for searching threads."""
metadata: dict[str, Any] = Field(default_factory=dict, description="Metadata filter (exact match)")
limit: int = Field(default=100, ge=1, le=1000, description="Maximum results")
offset: int = Field(default=0, ge=0, description="Pagination offset")
status: str | None = Field(default=None, description="Filter by thread status")
class ThreadStateResponse(BaseModel):
"""Response model for thread state."""
values: dict[str, Any] = Field(default_factory=dict, description="Current channel values")
next: list[str] = Field(default_factory=list, description="Next tasks to execute")
metadata: dict[str, Any] = Field(default_factory=dict, description="Checkpoint metadata")
checkpoint: dict[str, Any] = Field(default_factory=dict, description="Checkpoint info")
checkpoint_id: str | None = Field(default=None, description="Current checkpoint ID")
parent_checkpoint_id: str | None = Field(default=None, description="Parent checkpoint ID")
created_at: str | None = Field(default=None, description="Checkpoint timestamp")
tasks: list[dict[str, Any]] = Field(default_factory=list, description="Interrupted task details")
class ThreadPatchRequest(BaseModel):
"""Request body for patching thread metadata."""
metadata: dict[str, Any] = Field(default_factory=dict, description="Metadata to merge")
class ThreadStateUpdateRequest(BaseModel):
"""Request body for updating thread state (human-in-the-loop resume)."""
values: dict[str, Any] | None = Field(default=None, description="Channel values to merge")
checkpoint_id: str | None = Field(default=None, description="Checkpoint to branch from")
checkpoint: dict[str, Any] | None = Field(default=None, description="Full checkpoint object")
as_node: str | None = Field(default=None, description="Node identity for the update")
class HistoryEntry(BaseModel):
"""Single checkpoint history entry."""
checkpoint_id: str
parent_checkpoint_id: str | None = None
metadata: dict[str, Any] = Field(default_factory=dict)
values: dict[str, Any] = Field(default_factory=dict)
created_at: str | None = None
next: list[str] = Field(default_factory=list)
class ThreadHistoryRequest(BaseModel):
"""Request body for checkpoint history."""
limit: int = Field(default=10, ge=1, le=100, description="Maximum entries")
before: str | None = Field(default=None, description="Cursor for pagination")
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _delete_thread_data(thread_id: str, paths: Paths | None = None) -> ThreadDeleteResponse:
"""Delete local persisted filesystem data for a thread."""
path_manager = paths or get_paths()
try:
path_manager.delete_thread_dir(thread_id)
except ValueError as exc:
raise HTTPException(status_code=422, detail=str(exc)) from exc
except FileNotFoundError:
# Not critical — thread data may not exist on disk
logger.debug("No local thread data to delete for %s", thread_id)
return ThreadDeleteResponse(success=True, message=f"No local data for {thread_id}")
except Exception as exc:
logger.exception("Failed to delete thread data for %s", thread_id)
raise HTTPException(status_code=500, detail="Failed to delete local thread data.") from exc
logger.info("Deleted local thread data for %s", thread_id)
return ThreadDeleteResponse(success=True, message=f"Deleted local thread data for {thread_id}")
async def _store_get(store, thread_id: str) -> dict | None:
"""Fetch a thread record from the Store; returns ``None`` if absent."""
item = await store.aget(THREADS_NS, thread_id)
return item.value if item is not None else None
async def _store_put(store, record: dict) -> None:
"""Write a thread record to the Store."""
await store.aput(THREADS_NS, record["thread_id"], record)
async def _store_upsert(store, thread_id: str, *, metadata: dict | None = None, values: dict | None = None) -> None:
"""Create or refresh a thread record in the Store.
On creation the record is written with ``status="idle"``. On update only
``updated_at`` (and optionally ``metadata`` / ``values``) are changed so
that existing fields are preserved.
``values`` carries the agent-state snapshot exposed to the frontend
(currently just ``{"title": "..."}``).
"""
now = time.time()
existing = await _store_get(store, thread_id)
if existing is None:
await _store_put(
store,
{
"thread_id": thread_id,
"status": "idle",
"created_at": now,
"updated_at": now,
"metadata": metadata or {},
"values": values or {},
},
)
else:
val = dict(existing)
val["updated_at"] = now
if metadata:
val.setdefault("metadata", {}).update(metadata)
if values:
val.setdefault("values", {}).update(values)
await _store_put(store, val)
def _derive_thread_status(checkpoint_tuple) -> str:
"""Derive thread status from checkpoint metadata."""
if checkpoint_tuple is None:
return "idle"
pending_writes = getattr(checkpoint_tuple, "pending_writes", None) or []
# Check for error in pending writes
for pw in pending_writes:
if len(pw) >= 2 and pw[1] == "__error__":
return "error"
# Check for pending next tasks (indicates interrupt)
tasks = getattr(checkpoint_tuple, "tasks", None)
if tasks:
return "interrupted"
return "idle"
# ---------------------------------------------------------------------------
# Endpoints
# ---------------------------------------------------------------------------
@router.delete("/{thread_id}", response_model=ThreadDeleteResponse)
async def delete_thread_data(thread_id: str, request: Request) -> ThreadDeleteResponse:
"""Delete local persisted filesystem data for a thread.
Cleans DeerFlow-managed thread directories, removes checkpoint data,
and removes the thread record from the Store.
"""
# Clean local filesystem
response = _delete_thread_data(thread_id)
# Remove from Store (best-effort)
store = get_store(request)
if store is not None:
try:
await store.adelete(THREADS_NS, thread_id)
except Exception:
logger.debug("Could not delete store record for thread %s (not critical)", thread_id)
# Remove checkpoints (best-effort)
checkpointer = getattr(request.app.state, "checkpointer", None)
if checkpointer is not None:
try:
if hasattr(checkpointer, "adelete_thread"):
await checkpointer.adelete_thread(thread_id)
except Exception:
logger.debug("Could not delete checkpoints for thread %s (not critical)", thread_id)
return response
@router.post("", response_model=ThreadResponse)
async def create_thread(body: ThreadCreateRequest, request: Request) -> ThreadResponse:
"""Create a new thread.
The thread record is written to the Store (for fast listing) and an
empty checkpoint is written to the checkpointer (for state reads).
Idempotent: returns the existing record when ``thread_id`` already exists.
"""
store = get_store(request)
checkpointer = get_checkpointer(request)
thread_id = body.thread_id or str(uuid.uuid4())
now = time.time()
# Idempotency: return existing record from Store when already present
if store is not None:
existing_record = await _store_get(store, thread_id)
if existing_record is not None:
return ThreadResponse(
thread_id=thread_id,
status=existing_record.get("status", "idle"),
created_at=str(existing_record.get("created_at", "")),
updated_at=str(existing_record.get("updated_at", "")),
metadata=existing_record.get("metadata", {}),
)
# Write thread record to Store
if store is not None:
try:
await _store_put(
store,
{
"thread_id": thread_id,
"status": "idle",
"created_at": now,
"updated_at": now,
"metadata": body.metadata,
},
)
except Exception:
logger.exception("Failed to write thread %s to store", thread_id)
raise HTTPException(status_code=500, detail="Failed to create thread")
# Write an empty checkpoint so state endpoints work immediately
config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
try:
from langgraph.checkpoint.base import empty_checkpoint
ckpt_metadata = {
"step": -1,
"source": "input",
"writes": None,
"parents": {},
**body.metadata,
"created_at": now,
}
await checkpointer.aput(config, empty_checkpoint(), ckpt_metadata, {})
except Exception:
logger.exception("Failed to create checkpoint for thread %s", thread_id)
raise HTTPException(status_code=500, detail="Failed to create thread")
logger.info("Thread created: %s", thread_id)
return ThreadResponse(
thread_id=thread_id,
status="idle",
created_at=str(now),
updated_at=str(now),
metadata=body.metadata,
)
@router.post("/search", response_model=list[ThreadResponse])
async def search_threads(body: ThreadSearchRequest, request: Request) -> list[ThreadResponse]:
"""Search and list threads.
Two-phase approach:
**Phase 1 — Store (fast path, O(threads))**: returns threads that were
created or run through this Gateway. Store records are tiny metadata
dicts so fetching all of them at once is cheap.
**Phase 2 — Checkpointer supplement (lazy migration)**: threads that
were created directly by LangGraph Server (and therefore absent from the
Store) are discovered here by iterating the shared checkpointer. Any
newly found thread is immediately written to the Store so that the next
search skips Phase 2 for that thread — the Store converges to a full
index over time without a one-shot migration job.
"""
store = get_store(request)
checkpointer = get_checkpointer(request)
# -----------------------------------------------------------------------
# Phase 1: Store
# -----------------------------------------------------------------------
merged: dict[str, ThreadResponse] = {}
if store is not None:
try:
items = await store.asearch(THREADS_NS, limit=10_000)
except Exception:
logger.warning("Store search failed — falling back to checkpointer only", exc_info=True)
items = []
for item in items:
val = item.value
merged[val["thread_id"]] = ThreadResponse(
thread_id=val["thread_id"],
status=val.get("status", "idle"),
created_at=str(val.get("created_at", "")),
updated_at=str(val.get("updated_at", "")),
metadata=val.get("metadata", {}),
values=val.get("values", {}),
)
# -----------------------------------------------------------------------
# Phase 2: Checkpointer supplement
# Discovers threads not yet in the Store (e.g. created by LangGraph
# Server) and lazily migrates them so future searches skip this phase.
# -----------------------------------------------------------------------
try:
async for checkpoint_tuple in checkpointer.alist(None):
cfg = getattr(checkpoint_tuple, "config", {})
thread_id = cfg.get("configurable", {}).get("thread_id")
if not thread_id or thread_id in merged:
continue
# Skip sub-graph checkpoints (checkpoint_ns is non-empty for those)
if cfg.get("configurable", {}).get("checkpoint_ns", ""):
continue
ckpt_meta = getattr(checkpoint_tuple, "metadata", {}) or {}
# Strip LangGraph internal keys from the user-visible metadata dict
user_meta = {k: v for k, v in ckpt_meta.items() if k not in ("created_at", "updated_at", "step", "source", "writes", "parents")}
# Extract state values (title) from the checkpoint's channel_values
checkpoint_data = getattr(checkpoint_tuple, "checkpoint", {}) or {}
channel_values = checkpoint_data.get("channel_values", {})
ckpt_values = {}
if title := channel_values.get("title"):
ckpt_values["title"] = title
thread_resp = ThreadResponse(
thread_id=thread_id,
status=_derive_thread_status(checkpoint_tuple),
created_at=str(ckpt_meta.get("created_at", "")),
updated_at=str(ckpt_meta.get("updated_at", ckpt_meta.get("created_at", ""))),
metadata=user_meta,
values=ckpt_values,
)
merged[thread_id] = thread_resp
# Lazy migration — write to Store so the next search finds it there
if store is not None:
try:
await _store_upsert(store, thread_id, metadata=user_meta, values=ckpt_values or None)
except Exception:
logger.debug("Failed to migrate thread %s to store (non-fatal)", thread_id)
except Exception:
logger.exception("Checkpointer scan failed during thread search")
# Don't raise — return whatever was collected from Store + partial scan
# -----------------------------------------------------------------------
# Phase 3: Filter → sort → paginate
# -----------------------------------------------------------------------
results = list(merged.values())
if body.metadata:
results = [r for r in results if all(r.metadata.get(k) == v for k, v in body.metadata.items())]
if body.status:
results = [r for r in results if r.status == body.status]
results.sort(key=lambda r: r.updated_at, reverse=True)
return results[body.offset : body.offset + body.limit]
@router.patch("/{thread_id}", response_model=ThreadResponse)
async def patch_thread(thread_id: str, body: ThreadPatchRequest, request: Request) -> ThreadResponse:
"""Merge metadata into a thread record."""
store = get_store(request)
if store is None:
raise HTTPException(status_code=503, detail="Store not available")
record = await _store_get(store, thread_id)
if record is None:
raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found")
now = time.time()
updated = dict(record)
updated.setdefault("metadata", {}).update(body.metadata)
updated["updated_at"] = now
try:
await _store_put(store, updated)
except Exception:
logger.exception("Failed to patch thread %s", thread_id)
raise HTTPException(status_code=500, detail="Failed to update thread")
return ThreadResponse(
thread_id=thread_id,
status=updated.get("status", "idle"),
created_at=str(updated.get("created_at", "")),
updated_at=str(now),
metadata=updated.get("metadata", {}),
)
@router.get("/{thread_id}", response_model=ThreadResponse)
async def get_thread(thread_id: str, request: Request) -> ThreadResponse:
"""Get thread info.
Reads metadata from the Store and derives the accurate execution
status from the checkpointer. Falls back to the checkpointer alone
for threads that pre-date Store adoption (backward compat).
"""
store = get_store(request)
checkpointer = get_checkpointer(request)
record: dict | None = None
if store is not None:
record = await _store_get(store, thread_id)
# Derive accurate status from the checkpointer
config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
try:
checkpoint_tuple = await checkpointer.aget_tuple(config)
except Exception:
logger.exception("Failed to get checkpoint for thread %s", thread_id)
raise HTTPException(status_code=500, detail="Failed to get thread")
if record is None and checkpoint_tuple is None:
raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found")
# If the thread exists in the checkpointer but not the store (e.g. legacy
# data), synthesize a minimal store record from the checkpoint metadata.
if record is None and checkpoint_tuple is not None:
ckpt_meta = getattr(checkpoint_tuple, "metadata", {}) or {}
record = {
"thread_id": thread_id,
"status": "idle",
"created_at": ckpt_meta.get("created_at", ""),
"updated_at": ckpt_meta.get("updated_at", ckpt_meta.get("created_at", "")),
"metadata": {k: v for k, v in ckpt_meta.items() if k not in ("created_at", "updated_at", "step", "source", "writes", "parents")},
}
status = _derive_thread_status(checkpoint_tuple) if checkpoint_tuple is not None else record.get("status", "idle") # type: ignore[union-attr]
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {} if checkpoint_tuple is not None else {}
channel_values = checkpoint.get("channel_values", {})
return ThreadResponse(
thread_id=thread_id,
status=status,
created_at=str(record.get("created_at", "")), # type: ignore[union-attr]
updated_at=str(record.get("updated_at", "")), # type: ignore[union-attr]
metadata=record.get("metadata", {}), # type: ignore[union-attr]
values=serialize_channel_values(channel_values),
)
@router.get("/{thread_id}/state", response_model=ThreadStateResponse)
async def get_thread_state(thread_id: str, request: Request) -> ThreadStateResponse:
"""Get the latest state snapshot for a thread.
Channel values are serialized to ensure LangChain message objects
are converted to JSON-safe dicts.
"""
checkpointer = get_checkpointer(request)
config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
try:
checkpoint_tuple = await checkpointer.aget_tuple(config)
except Exception:
logger.exception("Failed to get state for thread %s", thread_id)
raise HTTPException(status_code=500, detail="Failed to get thread state")
if checkpoint_tuple is None:
raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found")
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {}
metadata = getattr(checkpoint_tuple, "metadata", {}) or {}
checkpoint_id = None
ckpt_config = getattr(checkpoint_tuple, "config", {})
if ckpt_config:
checkpoint_id = ckpt_config.get("configurable", {}).get("checkpoint_id")
channel_values = checkpoint.get("channel_values", {})
parent_config = getattr(checkpoint_tuple, "parent_config", None)
parent_checkpoint_id = None
if parent_config:
parent_checkpoint_id = parent_config.get("configurable", {}).get("checkpoint_id")
tasks_raw = getattr(checkpoint_tuple, "tasks", []) or []
next_tasks = [t.name for t in tasks_raw if hasattr(t, "name")]
tasks = [{"id": getattr(t, "id", ""), "name": getattr(t, "name", "")} for t in tasks_raw]
return ThreadStateResponse(
values=serialize_channel_values(channel_values),
next=next_tasks,
metadata=metadata,
checkpoint={"id": checkpoint_id, "ts": str(metadata.get("created_at", ""))},
checkpoint_id=checkpoint_id,
parent_checkpoint_id=parent_checkpoint_id,
created_at=str(metadata.get("created_at", "")),
tasks=tasks,
)
@router.post("/{thread_id}/state", response_model=ThreadStateResponse)
async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, request: Request) -> ThreadStateResponse:
"""Update thread state (e.g. for human-in-the-loop resume or title rename).
Writes a new checkpoint that merges *body.values* into the latest
channel values, then syncs any updated ``title`` field back to the Store
so that ``/threads/search`` reflects the change immediately.
"""
checkpointer = get_checkpointer(request)
store = get_store(request)
# checkpoint_ns must be present in the config for aput — default to ""
# (the root graph namespace). checkpoint_id is optional; omitting it
# fetches the latest checkpoint for the thread.
read_config: dict[str, Any] = {
"configurable": {
"thread_id": thread_id,
"checkpoint_ns": "",
}
}
if body.checkpoint_id:
read_config["configurable"]["checkpoint_id"] = body.checkpoint_id
try:
checkpoint_tuple = await checkpointer.aget_tuple(read_config)
except Exception:
logger.exception("Failed to get state for thread %s", thread_id)
raise HTTPException(status_code=500, detail="Failed to get thread state")
if checkpoint_tuple is None:
raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found")
# Work on mutable copies so we don't accidentally mutate cached objects.
checkpoint: dict[str, Any] = dict(getattr(checkpoint_tuple, "checkpoint", {}) or {})
metadata: dict[str, Any] = dict(getattr(checkpoint_tuple, "metadata", {}) or {})
channel_values: dict[str, Any] = dict(checkpoint.get("channel_values", {}))
if body.values:
channel_values.update(body.values)
checkpoint["channel_values"] = channel_values
metadata["updated_at"] = time.time()
if body.as_node:
metadata["source"] = "update"
metadata["step"] = metadata.get("step", 0) + 1
metadata["writes"] = {body.as_node: body.values}
# aput requires checkpoint_ns in the config — use the same config used for the
# read (which always includes checkpoint_ns=""). Do NOT include checkpoint_id
# so that aput generates a fresh checkpoint ID for the new snapshot.
write_config: dict[str, Any] = {
"configurable": {
"thread_id": thread_id,
"checkpoint_ns": "",
}
}
try:
new_config = await checkpointer.aput(write_config, checkpoint, metadata, {})
except Exception:
logger.exception("Failed to update state for thread %s", thread_id)
raise HTTPException(status_code=500, detail="Failed to update thread state")
new_checkpoint_id: str | None = None
if isinstance(new_config, dict):
new_checkpoint_id = new_config.get("configurable", {}).get("checkpoint_id")
# Sync title changes to the Store so /threads/search reflects them immediately.
if store is not None and body.values and "title" in body.values:
try:
await _store_upsert(store, thread_id, values={"title": body.values["title"]})
except Exception:
logger.debug("Failed to sync title to store for thread %s (non-fatal)", thread_id)
return ThreadStateResponse(
values=serialize_channel_values(channel_values),
next=[],
metadata=metadata,
checkpoint_id=new_checkpoint_id,
created_at=str(metadata.get("created_at", "")),
)
@router.post("/{thread_id}/history", response_model=list[HistoryEntry])
async def get_thread_history(thread_id: str, body: ThreadHistoryRequest, request: Request) -> list[HistoryEntry]:
"""Get checkpoint history for a thread."""
checkpointer = get_checkpointer(request)
config: dict[str, Any] = {"configurable": {"thread_id": thread_id}}
if body.before:
config["configurable"]["checkpoint_id"] = body.before
entries: list[HistoryEntry] = []
try:
async for checkpoint_tuple in checkpointer.alist(config, limit=body.limit):
ckpt_config = getattr(checkpoint_tuple, "config", {})
parent_config = getattr(checkpoint_tuple, "parent_config", None)
metadata = getattr(checkpoint_tuple, "metadata", {}) or {}
checkpoint = getattr(checkpoint_tuple, "checkpoint", {}) or {}
checkpoint_id = ckpt_config.get("configurable", {}).get("checkpoint_id", "")
parent_id = None
if parent_config:
parent_id = parent_config.get("configurable", {}).get("checkpoint_id")
channel_values = checkpoint.get("channel_values", {})
# Derive next tasks
tasks_raw = getattr(checkpoint_tuple, "tasks", []) or []
next_tasks = [t.name for t in tasks_raw if hasattr(t, "name")]
entries.append(
HistoryEntry(
checkpoint_id=checkpoint_id,
parent_checkpoint_id=parent_id,
metadata=metadata,
values=serialize_channel_values(channel_values),
created_at=str(metadata.get("created_at", "")),
next=next_tasks,
)
)
except Exception:
logger.exception("Failed to get history for thread %s", thread_id)
raise HTTPException(status_code=500, detail="Failed to get thread history")
return entries
+66 -71
View File
@@ -4,13 +4,11 @@ import logging
import os
import stat
from fastapi import APIRouter, File, HTTPException, Request, UploadFile
from fastapi import APIRouter, File, HTTPException, UploadFile
from pydantic import BaseModel
from app.plugins.auth.security.actor_context import bind_request_actor_context
from deerflow.sandbox.sandbox_provider import get_sandbox_provider
from deerflow.config.paths import get_paths
from deerflow.runtime.actor_context import get_effective_user_id
from deerflow.sandbox.sandbox_provider import get_sandbox_provider
from deerflow.uploads.manager import (
PathTraversalError,
delete_file_safe,
@@ -58,76 +56,74 @@ def _make_file_sandbox_writable(file_path: os.PathLike[str] | str) -> None:
@router.post("", response_model=UploadResponse)
async def upload_files(
thread_id: str,
request: Request,
files: list[UploadFile] = File(...),
) -> UploadResponse:
"""Upload multiple files to a thread's uploads directory."""
if not files:
raise HTTPException(status_code=400, detail="No files provided")
with bind_request_actor_context(request):
try:
uploads_dir = ensure_uploads_dir(thread_id)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
sandbox_uploads = get_paths().sandbox_uploads_dir(thread_id)
uploaded_files = []
sandbox_provider = get_sandbox_provider()
sandbox_id = sandbox_provider.acquire(thread_id)
sandbox = sandbox_provider.get(sandbox_id)
for file in files:
if not file.filename:
continue
try:
uploads_dir = ensure_uploads_dir(thread_id)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
sandbox_uploads = get_paths().sandbox_uploads_dir(thread_id, user_id=get_effective_user_id())
uploaded_files = []
safe_filename = normalize_filename(file.filename)
except ValueError:
logger.warning(f"Skipping file with unsafe filename: {file.filename!r}")
continue
sandbox_provider = get_sandbox_provider()
sandbox_id = sandbox_provider.acquire(thread_id)
sandbox = sandbox_provider.get(sandbox_id)
try:
content = await file.read()
file_path = uploads_dir / safe_filename
file_path.write_bytes(content)
for file in files:
if not file.filename:
continue
virtual_path = upload_virtual_path(safe_filename)
try:
safe_filename = normalize_filename(file.filename)
except ValueError:
logger.warning(f"Skipping file with unsafe filename: {file.filename!r}")
continue
if sandbox_id != "local":
_make_file_sandbox_writable(file_path)
sandbox.update_file(virtual_path, content)
try:
content = await file.read()
file_path = uploads_dir / safe_filename
file_path.write_bytes(content)
file_info = {
"filename": safe_filename,
"size": str(len(content)),
"path": str(sandbox_uploads / safe_filename),
"virtual_path": virtual_path,
"artifact_url": upload_artifact_url(thread_id, safe_filename),
}
virtual_path = upload_virtual_path(safe_filename)
logger.info(f"Saved file: {safe_filename} ({len(content)} bytes) to {file_info['path']}")
if sandbox_id != "local":
_make_file_sandbox_writable(file_path)
sandbox.update_file(virtual_path, content)
file_ext = file_path.suffix.lower()
if file_ext in CONVERTIBLE_EXTENSIONS:
md_path = await convert_file_to_markdown(file_path)
if md_path:
md_virtual_path = upload_virtual_path(md_path.name)
file_info = {
"filename": safe_filename,
"size": str(len(content)),
"path": str(sandbox_uploads / safe_filename),
"virtual_path": virtual_path,
"artifact_url": upload_artifact_url(thread_id, safe_filename),
}
if sandbox_id != "local":
_make_file_sandbox_writable(md_path)
sandbox.update_file(md_virtual_path, md_path.read_bytes())
logger.info(f"Saved file: {safe_filename} ({len(content)} bytes) to {file_info['path']}")
file_info["markdown_file"] = md_path.name
file_info["markdown_path"] = str(sandbox_uploads / md_path.name)
file_info["markdown_virtual_path"] = md_virtual_path
file_info["markdown_artifact_url"] = upload_artifact_url(thread_id, md_path.name)
file_ext = file_path.suffix.lower()
if file_ext in CONVERTIBLE_EXTENSIONS:
md_path = await convert_file_to_markdown(file_path)
if md_path:
md_virtual_path = upload_virtual_path(md_path.name)
uploaded_files.append(file_info)
if sandbox_id != "local":
_make_file_sandbox_writable(md_path)
sandbox.update_file(md_virtual_path, md_path.read_bytes())
file_info["markdown_file"] = md_path.name
file_info["markdown_path"] = str(sandbox_uploads / md_path.name)
file_info["markdown_virtual_path"] = md_virtual_path
file_info["markdown_artifact_url"] = upload_artifact_url(thread_id, md_path.name)
uploaded_files.append(file_info)
except Exception as e:
logger.error(f"Failed to upload {file.filename}: {e}")
raise HTTPException(status_code=500, detail=f"Failed to upload {file.filename}: {str(e)}")
except Exception as e:
logger.error(f"Failed to upload {file.filename}: {e}")
raise HTTPException(status_code=500, detail=f"Failed to upload {file.filename}: {str(e)}")
return UploadResponse(
success=True,
@@ -137,26 +133,25 @@ async def upload_files(
@router.get("/list", response_model=dict)
async def list_uploaded_files(thread_id: str, request: Request) -> dict:
async def list_uploaded_files(thread_id: str) -> dict:
"""List all files in a thread's uploads directory."""
with bind_request_actor_context(request):
try:
uploads_dir = get_uploads_dir(thread_id)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
result = list_files_in_dir(uploads_dir)
enrich_file_listing(result, thread_id)
try:
uploads_dir = get_uploads_dir(thread_id)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
result = list_files_in_dir(uploads_dir)
enrich_file_listing(result, thread_id)
# Gateway additionally includes the sandbox-relative path.
sandbox_uploads = get_paths().sandbox_uploads_dir(thread_id, user_id=get_effective_user_id())
for f in result["files"]:
f["path"] = str(sandbox_uploads / f["filename"])
# Gateway additionally includes the sandbox-relative path.
sandbox_uploads = get_paths().sandbox_uploads_dir(thread_id)
for f in result["files"]:
f["path"] = str(sandbox_uploads / f["filename"])
return result
return result
@router.delete("/{filename}")
async def delete_uploaded_file(thread_id: str, filename: str, request: Request) -> dict:
async def delete_uploaded_file(thread_id: str, filename: str) -> dict:
"""Delete a file from a thread's uploads directory."""
try:
uploads_dir = get_uploads_dir(thread_id)
+296
View File
@@ -0,0 +1,296 @@
"""Run lifecycle service layer.
Centralizes the business logic for creating runs, formatting SSE
frames, and consuming stream bridge events. Router modules
(``thread_runs``, ``runs``) are thin HTTP handlers that delegate here.
"""
from __future__ import annotations
import asyncio
import json
import logging
import time
from typing import Any
from fastapi import HTTPException, Request
from langchain_core.messages import HumanMessage
from app.gateway.deps import get_checkpointer, get_run_manager, get_store, get_stream_bridge
from deerflow.runtime import (
END_SENTINEL,
HEARTBEAT_SENTINEL,
ConflictError,
DisconnectMode,
RunManager,
RunRecord,
RunStatus,
StreamBridge,
UnsupportedStrategyError,
run_agent,
)
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# SSE formatting
# ---------------------------------------------------------------------------
def format_sse(event: str, data: Any, *, event_id: str | None = None) -> str:
"""Format a single SSE frame.
Field order: ``event:`` -> ``data:`` -> ``id:`` (optional) -> blank line.
This matches the LangGraph Platform wire format consumed by the
``useStream`` React hook and the Python ``langgraph-sdk`` SSE decoder.
"""
payload = json.dumps(data, default=str, ensure_ascii=False)
parts = [f"event: {event}", f"data: {payload}"]
if event_id:
parts.append(f"id: {event_id}")
parts.append("")
parts.append("")
return "\n".join(parts)
# ---------------------------------------------------------------------------
# Input / config helpers
# ---------------------------------------------------------------------------
def normalize_stream_modes(raw: list[str] | str | None) -> list[str]:
"""Normalize the stream_mode parameter to a list.
Default matches what ``useStream`` expects: values + messages-tuple.
"""
if raw is None:
return ["values"]
if isinstance(raw, str):
return [raw]
return raw if raw else ["values"]
def normalize_input(raw_input: dict[str, Any] | None) -> dict[str, Any]:
"""Convert LangGraph Platform input format to LangChain state dict."""
if raw_input is None:
return {}
messages = raw_input.get("messages")
if messages and isinstance(messages, list):
converted = []
for msg in messages:
if isinstance(msg, dict):
role = msg.get("role", msg.get("type", "user"))
content = msg.get("content", "")
if role in ("user", "human"):
converted.append(HumanMessage(content=content))
else:
# TODO: handle other message types (system, ai, tool)
converted.append(HumanMessage(content=content))
else:
converted.append(msg)
return {**raw_input, "messages": converted}
return raw_input
def resolve_agent_factory(assistant_id: str | None):
"""Resolve the agent factory callable from config."""
from deerflow.agents.lead_agent.agent import make_lead_agent
if assistant_id and assistant_id != "lead_agent":
logger.info("assistant_id=%s requested; falling back to lead_agent", assistant_id)
return make_lead_agent
def build_run_config(thread_id: str, request_config: dict[str, Any] | None, metadata: dict[str, Any] | None) -> dict[str, Any]:
"""Build a RunnableConfig dict for the agent."""
configurable = {"thread_id": thread_id}
if request_config:
configurable.update(request_config.get("configurable", {}))
config: dict[str, Any] = {"configurable": configurable, "recursion_limit": 100}
if request_config:
for k, v in request_config.items():
if k != "configurable":
config[k] = v
if metadata:
config.setdefault("metadata", {}).update(metadata)
return config
# ---------------------------------------------------------------------------
# Run lifecycle
# ---------------------------------------------------------------------------
async def _upsert_thread_in_store(store, thread_id: str, metadata: dict | None) -> None:
"""Create or refresh the thread record in the Store.
Called from :func:`start_run` so that threads created via the stateless
``/runs/stream`` endpoint (which never calls ``POST /threads``) still
appear in ``/threads/search`` results.
"""
# Deferred import to avoid circular import with the threads router module.
from app.gateway.routers.threads import _store_upsert
try:
await _store_upsert(store, thread_id, metadata=metadata)
except Exception:
logger.warning("Failed to upsert thread %s in store (non-fatal)", thread_id)
async def _sync_thread_title_after_run(
run_task: asyncio.Task,
thread_id: str,
checkpointer: Any,
store: Any,
) -> None:
"""Wait for *run_task* to finish, then persist the generated title to the Store.
TitleMiddleware writes the generated title to the LangGraph agent state
(checkpointer) but the Gateway's Store record is not updated automatically.
This coroutine closes that gap by reading the final checkpoint after the
run completes and syncing ``values.title`` into the Store record so that
subsequent ``/threads/search`` responses include the correct title.
Runs as a fire-and-forget :func:`asyncio.create_task`; failures are
logged at DEBUG level and never propagate.
"""
# Wait for the background run task to complete (any outcome).
# asyncio.wait does not propagate task exceptions — it just returns
# when the task is done, cancelled, or failed.
await asyncio.wait({run_task})
# Deferred import to avoid circular import with the threads router module.
from app.gateway.routers.threads import _store_get, _store_put
try:
ckpt_config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
ckpt_tuple = await checkpointer.aget_tuple(ckpt_config)
if ckpt_tuple is None:
return
channel_values = ckpt_tuple.checkpoint.get("channel_values", {})
title = channel_values.get("title")
if not title:
return
existing = await _store_get(store, thread_id)
if existing is None:
return
updated = dict(existing)
updated.setdefault("values", {})["title"] = title
updated["updated_at"] = time.time()
await _store_put(store, updated)
logger.debug("Synced title %r for thread %s", title, thread_id)
except Exception:
logger.debug("Failed to sync title for thread %s (non-fatal)", thread_id, exc_info=True)
async def start_run(
body: Any,
thread_id: str,
request: Request,
) -> RunRecord:
"""Create a RunRecord and launch the background agent task.
Parameters
----------
body : RunCreateRequest
The validated request body (typed as Any to avoid circular import
with the router module that defines the Pydantic model).
thread_id : str
Target thread.
request : Request
FastAPI request — used to retrieve singletons from ``app.state``.
"""
bridge = get_stream_bridge(request)
run_mgr = get_run_manager(request)
checkpointer = get_checkpointer(request)
store = get_store(request)
disconnect = DisconnectMode.cancel if body.on_disconnect == "cancel" else DisconnectMode.continue_
try:
record = await run_mgr.create_or_reject(
thread_id,
body.assistant_id,
on_disconnect=disconnect,
metadata=body.metadata or {},
kwargs={"input": body.input, "config": body.config},
multitask_strategy=body.multitask_strategy,
)
except ConflictError as exc:
raise HTTPException(status_code=409, detail=str(exc)) from exc
except UnsupportedStrategyError as exc:
raise HTTPException(status_code=501, detail=str(exc)) from exc
# Ensure the thread is visible in /threads/search, even for threads that
# were never explicitly created via POST /threads (e.g. stateless runs).
store = get_store(request)
if store is not None:
await _upsert_thread_in_store(store, thread_id, body.metadata)
agent_factory = resolve_agent_factory(body.assistant_id)
graph_input = normalize_input(body.input)
config = build_run_config(thread_id, body.config, body.metadata)
stream_modes = normalize_stream_modes(body.stream_mode)
task = asyncio.create_task(
run_agent(
bridge,
run_mgr,
record,
checkpointer=checkpointer,
store=store,
agent_factory=agent_factory,
graph_input=graph_input,
config=config,
stream_modes=stream_modes,
stream_subgraphs=body.stream_subgraphs,
interrupt_before=body.interrupt_before,
interrupt_after=body.interrupt_after,
)
)
record.task = task
# After the run completes, sync the title generated by TitleMiddleware from
# the checkpointer into the Store record so that /threads/search returns the
# correct title instead of an empty values dict.
if store is not None:
asyncio.create_task(_sync_thread_title_after_run(task, thread_id, checkpointer, store))
return record
async def sse_consumer(
bridge: StreamBridge,
record: RunRecord,
request: Request,
run_mgr: RunManager,
):
"""Async generator that yields SSE frames from the bridge.
The ``finally`` block implements ``on_disconnect`` semantics:
- ``cancel``: abort the background task on client disconnect.
- ``continue``: let the task run; events are discarded.
"""
try:
async for entry in bridge.subscribe(record.run_id):
if await request.is_disconnected():
break
if entry is HEARTBEAT_SENTINEL:
yield ": heartbeat\n\n"
continue
if entry is END_SENTINEL:
yield format_sse("end", None, event_id=entry.id or None)
return
yield format_sse(entry.event, entry.data, event_id=entry.id or None)
finally:
if record.status in (RunStatus.pending, RunStatus.running):
if record.on_disconnect == DisconnectMode.cancel:
await run_mgr.cancel(record.run_id)
-5
View File
@@ -1,5 +0,0 @@
"""Gateway service layer."""
"""Compatibility package for app service submodules."""
__all__: list[str] = []
@@ -1,29 +0,0 @@
"""Runs app layer services."""
from app.infra.storage import StorageRunObserver
from .input import (
AdaptedRunRequest,
RunSpecBuilder,
UnsupportedRunFeatureError,
adapt_create_run_request,
adapt_create_stream_request,
adapt_create_wait_request,
adapt_join_stream_request,
adapt_join_wait_request,
)
from .store import AppRunCreateStore, AppRunDeleteStore, AppRunQueryStore
__all__ = [
"AdaptedRunRequest",
"AppRunCreateStore",
"AppRunDeleteStore",
"AppRunQueryStore",
"RunSpecBuilder",
"StorageRunObserver",
"UnsupportedRunFeatureError",
"adapt_create_run_request",
"adapt_create_stream_request",
"adapt_create_wait_request",
"adapt_join_stream_request",
"adapt_join_wait_request",
]
@@ -1,150 +0,0 @@
"""Facade factory - assembles RunsFacade with dependencies."""
from __future__ import annotations
from collections.abc import Callable
from typing import TYPE_CHECKING
from fastapi import HTTPException, Request
from app.gateway.dependencies import get_checkpointer, get_stream_bridge
from deerflow.runtime.runs.facade import RunsFacade
from deerflow.runtime.runs.facade import RunsRuntime
from deerflow.runtime.runs.internal.execution.supervisor import RunSupervisor
from deerflow.runtime.runs.internal.planner import ExecutionPlanner
from deerflow.runtime.runs.internal.registry import RunRegistry
from deerflow.runtime.runs.internal.streams import RunStreamService
from deerflow.runtime.runs.internal.wait import RunWaitService
from app.infra.storage import StorageRunObserver, ThreadMetaStorage
from app.infra.storage.runs import RunDeleteRepository, RunReadRepository, RunWriteRepository
from .store import AppRunCreateStore, AppRunDeleteStore, AppRunQueryStore
if TYPE_CHECKING:
from deerflow.runtime.stream_bridge import StreamBridge
type AgentFactory = Callable[..., object]
# Module-level singleton registry (shared across requests)
_registry: RunRegistry | None = None
_supervisor: RunSupervisor | None = None
def _get_state(request: Request, attr: str, label: str):
value = getattr(request.app.state, attr, None)
if value is None:
raise HTTPException(status_code=503, detail=f"{label} not available")
return value
def get_registry() -> RunRegistry:
"""Get or create singleton registry."""
global _registry
if _registry is None:
_registry = RunRegistry()
return _registry
def get_supervisor() -> RunSupervisor:
"""Get or create singleton run supervisor."""
global _supervisor
if _supervisor is None:
_supervisor = RunSupervisor()
return _supervisor
def resolve_agent_factory(assistant_id: str | None) -> AgentFactory:
"""Resolve the agent factory callable from config."""
from deerflow.agents.lead_agent.agent import make_lead_agent
return make_lead_agent
def build_runs_facade(
*,
stream_bridge: "StreamBridge",
checkpointer: object,
store: object | None = None,
run_read_repo: RunReadRepository | None = None,
run_write_repo: RunWriteRepository | None = None,
run_delete_repo: RunDeleteRepository | None = None,
thread_meta_storage: ThreadMetaStorage | None = None,
run_event_store: object | None = None,
) -> RunsFacade:
"""
Build RunsFacade with all dependencies.
Args:
stream_bridge: StreamBridge instance
checkpointer: LangGraph checkpointer
store: Optional LangGraph runtime store
run_read_repo: Optional run repository for durable reads
run_write_repo: Optional run repository for durable writes
run_delete_repo: Optional run repository for durable deletes
thread_meta_storage: Optional thread metadata storage adapter
Returns:
Configured RunsFacade instance
"""
registry = get_registry()
planner = ExecutionPlanner()
supervisor = get_supervisor()
stream_service = RunStreamService(stream_bridge)
wait_service = RunWaitService(stream_service)
query_store = AppRunQueryStore(run_read_repo) if run_read_repo else None
create_store = (
AppRunCreateStore(run_write_repo, thread_meta_storage=thread_meta_storage)
if run_write_repo
else None
)
delete_store = AppRunDeleteStore(run_delete_repo) if run_delete_repo else None
# Build storage observer if repositories provided
storage_observer = None
if run_write_repo or thread_meta_storage:
storage_observer = StorageRunObserver(
run_write_repo=run_write_repo,
thread_meta_storage=thread_meta_storage,
)
return RunsFacade(
registry=registry,
planner=planner,
supervisor=supervisor,
stream_service=stream_service,
wait_service=wait_service,
runtime=RunsRuntime(
bridge=stream_bridge,
checkpointer=checkpointer,
store=store,
event_store=run_event_store,
agent_factory_resolver=resolve_agent_factory,
),
observer=storage_observer,
query_store=query_store,
create_store=create_store,
delete_store=delete_store,
)
def build_runs_facade_from_request(request: "Request") -> RunsFacade:
"""
Build RunsFacade from FastAPI request context.
Extracts dependencies from request.app.state.
"""
app_state = request.app.state
return build_runs_facade(
stream_bridge=get_stream_bridge(request),
checkpointer=get_checkpointer(request),
store=getattr(request.app.state, "store", None),
run_read_repo=getattr(app_state, "run_read_repo", None),
run_write_repo=getattr(app_state, "run_write_repo", None),
run_delete_repo=getattr(app_state, "run_delete_repo", None),
thread_meta_storage=getattr(app_state, "thread_meta_storage", None),
run_event_store=getattr(app_state, "run_event_store", None),
)
@@ -1,22 +0,0 @@
"""Input adapters for app-owned runs entrypoints."""
from .request_adapter import (
AdaptedRunRequest,
adapt_create_run_request,
adapt_create_stream_request,
adapt_create_wait_request,
adapt_join_stream_request,
adapt_join_wait_request,
)
from .spec_builder import RunSpecBuilder, UnsupportedRunFeatureError
__all__ = [
"AdaptedRunRequest",
"RunSpecBuilder",
"UnsupportedRunFeatureError",
"adapt_create_run_request",
"adapt_create_stream_request",
"adapt_create_wait_request",
"adapt_join_stream_request",
"adapt_join_wait_request",
]
@@ -1,127 +0,0 @@
"""App-owned request adapter for runs entrypoints."""
from __future__ import annotations
from dataclasses import dataclass
from deerflow.runtime.stream_bridge import JSONValue
from deerflow.runtime.runs.types import RunIntent
type RequestBody = dict[str, JSONValue]
type RequestQuery = dict[str, str]
@dataclass(frozen=True)
class AdaptedRunRequest:
"""
统一的内部请求 DTO.
路由层只负责提取 path/query/body,适配器负责转成稳定内部结构。
"""
intent: RunIntent
thread_id: str | None
run_id: str | None
body: RequestBody
headers: dict[str, str]
query: RequestQuery
@property
def last_event_id(self) -> str | None:
"""Extract Last-Event-ID from headers."""
return self.headers.get("last-event-id") or self.headers.get("Last-Event-ID")
@property
def is_stateless(self) -> bool:
"""Check if this is a stateless request."""
return self.thread_id is None
def adapt_create_run_request(
*,
thread_id: str | None,
body: RequestBody,
headers: dict[str, str] | None = None,
query: RequestQuery | None = None,
) -> AdaptedRunRequest:
"""Adapt POST /threads/{thread_id}/runs or POST /runs."""
return AdaptedRunRequest(
intent="create_background",
thread_id=thread_id,
run_id=None,
body=body,
headers=headers or {},
query=query or {},
)
def adapt_create_stream_request(
*,
thread_id: str | None,
body: RequestBody,
headers: dict[str, str] | None = None,
query: RequestQuery | None = None,
) -> AdaptedRunRequest:
"""Adapt POST /threads/{thread_id}/runs/stream or POST /runs/stream."""
return AdaptedRunRequest(
intent="create_and_stream",
thread_id=thread_id,
run_id=None,
body=body,
headers=headers or {},
query=query or {},
)
def adapt_create_wait_request(
*,
thread_id: str | None,
body: RequestBody,
headers: dict[str, str] | None = None,
query: RequestQuery | None = None,
) -> AdaptedRunRequest:
"""Adapt POST /threads/{thread_id}/runs/wait or POST /runs/wait."""
return AdaptedRunRequest(
intent="create_and_wait",
thread_id=thread_id,
run_id=None,
body=body,
headers=headers or {},
query=query or {},
)
def adapt_join_stream_request(
*,
thread_id: str,
run_id: str,
headers: dict[str, str] | None = None,
query: RequestQuery | None = None,
) -> AdaptedRunRequest:
"""Adapt GET /threads/{thread_id}/runs/{run_id}/stream."""
return AdaptedRunRequest(
intent="join_stream",
thread_id=thread_id,
run_id=run_id,
body={},
headers=headers or {},
query=query or {},
)
def adapt_join_wait_request(
*,
thread_id: str,
run_id: str,
headers: dict[str, str] | None = None,
query: RequestQuery | None = None,
) -> AdaptedRunRequest:
"""Adapt GET /threads/{thread_id}/runs/{run_id}/join."""
return AdaptedRunRequest(
intent="join_wait",
thread_id=thread_id,
run_id=run_id,
body={},
headers=headers or {},
query=query or {},
)
@@ -1,254 +0,0 @@
"""App-owned RunSpec builder."""
from __future__ import annotations
import re
import uuid
from langchain_core.messages import HumanMessage
from deerflow.runtime.runs.types import CheckpointRequest, RunScope, RunSpec
from deerflow.runtime.stream_bridge import JSONValue
from .request_adapter import AdaptedRunRequest
type JSONMapping = dict[str, JSONValue]
type GraphInput = dict[str, object]
type RunnableConfigDict = dict[str, object]
class UnsupportedRunFeatureError(ValueError):
"""Raised when a phase1-unsupported feature is requested."""
pass
class RunSpecBuilder:
"""
Build RunSpec from AdaptedRunRequest.
Phase 1 rules:
1. messages-tuple normalized to messages
2. enqueue not supported
3. rollback not supported
4. after_seconds not supported
5. stream_resumable accepted
6. stateless auto-generates temporary thread
"""
# Phase 1 unsupported features
UNSUPPORTED_MULTITASK_STRATEGIES = {"enqueue"}
UNSUPPORTED_ACTIONS = {"rollback"}
# Default stream modes
DEFAULT_STREAM_MODES = ["values", "messages"]
CONTEXT_CONFIGURABLE_KEYS = frozenset({
"model_name",
"mode",
"thinking_enabled",
"reasoning_effort",
"is_plan_mode",
"subagent_enabled",
"max_concurrent_subagents",
})
DEFAULT_ASSISTANT_ID = "lead_agent"
@staticmethod
def _as_json_mapping(value: JSONValue | None) -> JSONMapping | None:
return value if isinstance(value, dict) else None
@staticmethod
def _as_string_list(value: JSONValue | None) -> list[str] | None:
if not isinstance(value, list):
return None
return [item for item in value if isinstance(item, str)]
def build(self, request: AdaptedRunRequest) -> RunSpec:
"""Build RunSpec from adapted request."""
body = request.body
# Validate phase1 constraints
self._validate_constraints(body)
# Build scope
scope = self._build_scope(request)
# Normalize stream modes
stream_modes = self._normalize_stream_modes(body.get("stream_mode"))
# Build checkpoint request
checkpoint_request = self._build_checkpoint_request(body)
config = self._build_runnable_config(
thread_id=scope.thread_id,
request_config=self._as_json_mapping(body.get("config")),
metadata=self._as_json_mapping(body.get("metadata")),
assistant_id=body.get("assistant_id"),
context=self._as_json_mapping(body.get("context")),
)
return RunSpec(
intent=request.intent,
scope=scope,
assistant_id=body.get("assistant_id") if isinstance(body.get("assistant_id"), str) else None,
input=self._normalize_input(self._as_json_mapping(body.get("input"))),
command=self._as_json_mapping(body.get("command")),
runnable_config=config,
context=self._as_json_mapping(body.get("context")),
metadata=self._as_json_mapping(body.get("metadata")) or {},
stream_modes=stream_modes,
stream_subgraphs=bool(body.get("stream_subgraphs", False)),
stream_resumable=bool(body.get("stream_resumable", False)),
on_disconnect=body.get("on_disconnect", "cancel") if body.get("on_disconnect") in {"cancel", "continue"} else "cancel",
on_completion=body.get("on_completion", "keep") if body.get("on_completion") in {"delete", "keep"} else "keep",
multitask_strategy=body.get("multitask_strategy", "reject") if body.get("multitask_strategy") in {"reject", "interrupt"} else "reject",
interrupt_before="*" if body.get("interrupt_before") == "*" else self._as_string_list(body.get("interrupt_before")),
interrupt_after="*" if body.get("interrupt_after") == "*" else self._as_string_list(body.get("interrupt_after")),
checkpoint_request=checkpoint_request,
follow_up_to_run_id=body.get("follow_up_to_run_id") if isinstance(body.get("follow_up_to_run_id"), str) else None,
webhook=body.get("webhook") if isinstance(body.get("webhook"), str) else None,
feedback_keys=self._as_string_list(body.get("feedback_keys")),
)
def _validate_constraints(self, body: JSONMapping) -> None:
"""Validate phase1 constraints, raise UnsupportedRunFeatureError if violated."""
# Check multitask_strategy
strategy = body.get("multitask_strategy", "reject")
if strategy in self.UNSUPPORTED_MULTITASK_STRATEGIES:
raise UnsupportedRunFeatureError(
f"multitask_strategy '{strategy}' is not supported in phase1. "
f"Supported: reject, interrupt"
)
# Check for rollback action
command = self._as_json_mapping(body.get("command")) or {}
if command.get("action") in self.UNSUPPORTED_ACTIONS:
raise UnsupportedRunFeatureError(
f"action '{command.get('action')}' is not supported in phase1"
)
# Check for after_seconds
if body.get("after_seconds") is not None:
raise UnsupportedRunFeatureError("after_seconds is not supported in phase1")
def _build_scope(self, request: AdaptedRunRequest) -> RunScope:
"""Build RunScope from request."""
if request.is_stateless:
# Stateless: generate temporary thread
return RunScope(
kind="stateless",
thread_id=str(uuid.uuid4()),
temporary=True,
)
else:
assert request.thread_id is not None
return RunScope(
kind="stateful",
thread_id=request.thread_id,
temporary=False,
)
def _normalize_stream_modes(self, stream_mode: JSONValue | None) -> list[str]:
"""Normalize stream_mode to list, convert messages-tuple to messages."""
if stream_mode is None:
return self.DEFAULT_STREAM_MODES.copy()
if isinstance(stream_mode, str):
modes = [stream_mode]
elif isinstance(stream_mode, list):
modes = [mode for mode in stream_mode if isinstance(mode, str)]
else:
return self.DEFAULT_STREAM_MODES.copy()
return ["messages" if m == "messages-tuple" else m for m in modes]
def _build_checkpoint_request(self, body: JSONMapping) -> CheckpointRequest | None:
"""Build CheckpointRequest if checkpoint data is provided."""
checkpoint_id = body.get("checkpoint_id")
checkpoint = self._as_json_mapping(body.get("checkpoint"))
if not isinstance(checkpoint_id, str) and checkpoint is None:
return None
return CheckpointRequest(
checkpoint_id=checkpoint_id if isinstance(checkpoint_id, str) else None,
checkpoint=checkpoint,
)
def _normalize_input(self, raw_input: JSONMapping | None) -> GraphInput | None:
"""Convert HTTP-friendly message dicts into LangChain message objects."""
if raw_input is None:
return None
messages = raw_input.get("messages")
if not messages or not isinstance(messages, list):
return raw_input
converted: list[object] = []
for msg in messages:
if isinstance(msg, dict):
role = msg.get("role", msg.get("type", "user"))
content = msg.get("content", "")
if role in ("user", "human"):
converted.append(HumanMessage(content=content))
else:
converted.append(HumanMessage(content=content))
else:
converted.append(msg)
return {**raw_input, "messages": converted}
def _build_runnable_config(
self,
*,
thread_id: str,
request_config: JSONMapping | None,
metadata: JSONMapping | None,
assistant_id: str | None,
context: JSONMapping | None,
) -> RunnableConfigDict:
"""Build RunnableConfig from request payload and app-side rules."""
config: RunnableConfigDict = {"recursion_limit": 100}
if request_config:
if "context" in request_config:
config["context"] = request_config["context"]
else:
configurable = {"thread_id": thread_id}
raw_configurable = request_config.get("configurable")
if isinstance(raw_configurable, dict):
configurable.update(raw_configurable)
config["configurable"] = configurable
for key, value in request_config.items():
if key not in ("configurable", "context"):
config[key] = value
else:
config["configurable"] = {"thread_id": thread_id}
configurable = config.get("configurable")
if (
assistant_id
and assistant_id != self.DEFAULT_ASSISTANT_ID
and isinstance(configurable, dict)
and "agent_name" not in configurable
):
normalized = assistant_id.strip().lower().replace("_", "-")
if not normalized or not re.fullmatch(r"[a-z0-9-]+", normalized):
raise ValueError(
f"Invalid assistant_id {assistant_id!r}: must contain only letters, digits, and hyphens after normalization."
)
configurable["agent_name"] = normalized
if metadata:
existing_metadata = config.get("metadata")
if isinstance(existing_metadata, dict):
existing_metadata.update(metadata)
else:
config["metadata"] = dict(metadata)
if context and isinstance(configurable, dict):
for key in self.CONTEXT_CONFIGURABLE_KEYS:
if key in context:
configurable.setdefault(key, context[key])
return config
@@ -1,5 +0,0 @@
"""Compatibility wrapper for the app-owned storage observer."""
from app.infra.storage.runs import StorageRunObserver
__all__ = ["StorageRunObserver"]
@@ -1,11 +0,0 @@
"""App-owned runs store adapters."""
from .create_store import AppRunCreateStore
from .delete_store import AppRunDeleteStore
from .query_store import AppRunQueryStore
__all__ = [
"AppRunCreateStore",
"AppRunDeleteStore",
"AppRunQueryStore",
]
@@ -1,38 +0,0 @@
"""App-owned durable run creation adapter."""
from __future__ import annotations
from deerflow.runtime.runs.store import RunCreateStore
from deerflow.runtime.runs.types import RunRecord
from app.infra.storage import ThreadMetaStorage
from app.infra.storage.runs import RunWriteRepository
class AppRunCreateStore(RunCreateStore):
"""Write the initial durable row for a newly created run."""
def __init__(self, repo: RunWriteRepository, thread_meta_storage: ThreadMetaStorage | None = None) -> None:
self._repo = repo
self._thread_meta_storage = thread_meta_storage
async def create_run(self, record: RunRecord) -> None:
await self._repo.create(
run_id=record.run_id,
thread_id=record.thread_id,
assistant_id=record.assistant_id,
status=str(record.status),
metadata=record.metadata,
follow_up_to_run_id=record.follow_up_to_run_id,
created_at=record.created_at,
)
if self._thread_meta_storage is not None and record.assistant_id:
thread = await self._thread_meta_storage.ensure_thread(
thread_id=record.thread_id,
assistant_id=record.assistant_id,
)
if thread.assistant_id != record.assistant_id:
await self._thread_meta_storage.sync_thread_assistant_id(
thread_id=record.thread_id,
assistant_id=record.assistant_id,
)
@@ -1,17 +0,0 @@
"""App-owned durable run deletion adapter."""
from __future__ import annotations
from deerflow.runtime.runs.store import RunDeleteStore
from app.infra.storage.runs import RunDeleteRepository
class AppRunDeleteStore(RunDeleteStore):
"""Delete durable run rows via the app storage adapter."""
def __init__(self, repo: RunDeleteRepository) -> None:
self._repo = repo
async def delete_run(self, run_id: str) -> bool:
return await self._repo.delete(run_id)
@@ -1,47 +0,0 @@
"""App-owned durable run query adapter."""
from __future__ import annotations
from deerflow.runtime.runs.store import RunQueryStore
from deerflow.runtime.runs.types import RunRecord, RunStatus
from app.infra.storage.runs import RunReadRepository, RunRow
class AppRunQueryStore(RunQueryStore):
"""Map app-side durable run rows into harness RunRecord DTOs."""
def __init__(self, repo: RunReadRepository) -> None:
self._repo = repo
async def get_run(self, run_id: str) -> RunRecord | None:
row = await self._repo.get(run_id)
if row is None:
return None
return self._to_run_record(row)
async def list_runs(
self,
thread_id: str,
*,
limit: int = 100,
) -> list[RunRecord]:
rows = await self._repo.list_by_thread(thread_id, limit=limit)
return [self._to_run_record(row) for row in rows]
def _to_run_record(self, row: RunRow) -> RunRecord:
return RunRecord(
run_id=row["run_id"],
thread_id=row["thread_id"],
assistant_id=row.get("assistant_id"),
status=RunStatus(row.get("status", "pending")),
temporary=False,
multitask_strategy=row.get("multitask_strategy", "reject"),
metadata=row.get("metadata", {}),
follow_up_to_run_id=row.get("follow_up_to_run_id"),
created_at=row.get("created_at", ""),
updated_at=row.get("updated_at", ""),
started_at=row.get("started_at"),
ended_at=row.get("ended_at"),
error=row.get("error"),
)
-1
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@@ -1 +0,0 @@
"""Application-owned infrastructure adapters and wiring."""
-6
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@@ -1,6 +0,0 @@
"""Run event store backends owned by app infrastructure."""
from .factory import build_run_event_store
from .jsonl_store import JsonlRunEventStore
__all__ = ["JsonlRunEventStore", "build_run_event_store"]
-25
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@@ -1,25 +0,0 @@
"""Factory for app-owned run event store backends."""
from __future__ import annotations
from pathlib import Path
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
from app.infra.storage import AppRunEventStore
from deerflow.config import get_app_config
from .jsonl_store import JsonlRunEventStore
def build_run_event_store(session_factory: async_sessionmaker[AsyncSession]) -> AppRunEventStore | JsonlRunEventStore:
"""Build the run event store selected by app configuration."""
config = get_app_config().run_events
if config.backend == "db":
return AppRunEventStore(session_factory)
if config.backend == "jsonl":
return JsonlRunEventStore(
base_dir=Path(config.jsonl_base_dir),
)
raise ValueError(f"Unsupported run event backend: {config.backend}")
-210
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@@ -1,210 +0,0 @@
"""JSONL run event store backend owned by app infrastructure."""
from __future__ import annotations
import asyncio
import json
import shutil
from collections.abc import Iterable
from datetime import UTC, datetime
from pathlib import Path
from typing import Any
class JsonlRunEventStore:
"""Append-only JSONL implementation of the runs RunEventStore protocol."""
def __init__(
self,
base_dir: Path | str = ".deer-flow/run-events",
) -> None:
self._base_dir = Path(base_dir)
self._locks: dict[str, asyncio.Lock] = {}
self._locks_guard = asyncio.Lock()
async def put_batch(self, events: list[dict[str, Any]]) -> list[dict[str, Any]]:
if not events:
return []
grouped: dict[str, list[dict[str, Any]]] = {}
for event in events:
grouped.setdefault(str(event["thread_id"]), []).append(event)
records_by_thread: dict[str, list[dict[str, Any]]] = {}
for thread_id, thread_events in grouped.items():
async with await self._thread_lock(thread_id):
records_by_thread[thread_id] = self._append_thread_events(thread_id, thread_events)
indexes = {thread_id: 0 for thread_id in records_by_thread}
ordered: list[dict[str, Any]] = []
for event in events:
thread_id = str(event["thread_id"])
index = indexes[thread_id]
ordered.append(records_by_thread[thread_id][index])
indexes[thread_id] = index + 1
return ordered
async def list_messages(
self,
thread_id: str,
*,
limit: int = 50,
before_seq: int | None = None,
after_seq: int | None = None,
) -> list[dict[str, Any]]:
events = [event for event in await self._read_thread_events(thread_id) if event.get("category") == "message"]
if before_seq is not None:
events = [event for event in events if int(event["seq"]) < before_seq]
return events[-limit:]
if after_seq is not None:
events = [event for event in events if int(event["seq"]) > after_seq]
return events[:limit]
return events[-limit:]
async def list_events(
self,
thread_id: str,
run_id: str,
*,
event_types: list[str] | None = None,
limit: int = 500,
) -> list[dict[str, Any]]:
event_type_set = set(event_types or [])
events = [
event
for event in await self._read_thread_events(thread_id)
if event.get("run_id") == run_id and (not event_type_set or event.get("event_type") in event_type_set)
]
return events[:limit]
async def list_messages_by_run(
self,
thread_id: str,
run_id: str,
*,
limit: int = 50,
before_seq: int | None = None,
after_seq: int | None = None,
) -> list[dict[str, Any]]:
events = [
event
for event in await self._read_thread_events(thread_id)
if event.get("run_id") == run_id and event.get("category") == "message"
]
if before_seq is not None:
events = [event for event in events if int(event["seq"]) < before_seq]
return events[-limit:]
if after_seq is not None:
events = [event for event in events if int(event["seq"]) > after_seq]
return events[:limit]
return events[-limit:]
async def count_messages(self, thread_id: str) -> int:
return len(await self.list_messages(thread_id, limit=10**9))
async def delete_by_thread(self, thread_id: str) -> int:
async with await self._thread_lock(thread_id):
count = len(self._read_thread_events_sync(thread_id))
shutil.rmtree(self._thread_dir(thread_id), ignore_errors=True)
return count
async def delete_by_run(self, thread_id: str, run_id: str) -> int:
async with await self._thread_lock(thread_id):
events = self._read_thread_events_sync(thread_id)
kept = [event for event in events if event.get("run_id") != run_id]
deleted = len(events) - len(kept)
if deleted:
self._write_thread_events(thread_id, kept)
return deleted
async def _thread_lock(self, thread_id: str) -> asyncio.Lock:
async with self._locks_guard:
lock = self._locks.get(thread_id)
if lock is None:
lock = asyncio.Lock()
self._locks[thread_id] = lock
return lock
def _append_thread_events(self, thread_id: str, events: list[dict[str, Any]]) -> list[dict[str, Any]]:
thread_dir = self._thread_dir(thread_id)
thread_dir.mkdir(parents=True, exist_ok=True)
seq = self._read_seq(thread_id)
records: list[dict[str, Any]] = []
with self._events_path(thread_id).open("a", encoding="utf-8") as file:
for event in events:
seq += 1
record = self._normalize_event(event, seq=seq)
file.write(json.dumps(record, ensure_ascii=False, default=str))
file.write("\n")
records.append(record)
self._write_seq(thread_id, seq)
return records
def _normalize_event(self, event: dict[str, Any], *, seq: int) -> dict[str, Any]:
created_at = event.get("created_at")
if isinstance(created_at, datetime):
created_at_value = created_at.isoformat()
elif created_at:
created_at_value = str(created_at)
else:
created_at_value = datetime.now(UTC).isoformat()
return {
"thread_id": str(event["thread_id"]),
"run_id": str(event["run_id"]),
"seq": seq,
"event_type": str(event["event_type"]),
"category": str(event["category"]),
"content": event.get("content", ""),
"metadata": dict(event.get("metadata") or {}),
"created_at": created_at_value,
}
async def _read_thread_events(self, thread_id: str) -> list[dict[str, Any]]:
async with await self._thread_lock(thread_id):
return self._read_thread_events_sync(thread_id)
def _read_thread_events_sync(self, thread_id: str) -> list[dict[str, Any]]:
path = self._events_path(thread_id)
if not path.exists():
return []
events: list[dict[str, Any]] = []
with path.open(encoding="utf-8") as file:
for line in file:
stripped = line.strip()
if stripped:
events.append(json.loads(stripped))
return events
def _write_thread_events(self, thread_id: str, events: Iterable[dict[str, Any]]) -> None:
thread_dir = self._thread_dir(thread_id)
thread_dir.mkdir(parents=True, exist_ok=True)
temp_path = self._events_path(thread_id).with_suffix(".jsonl.tmp")
with temp_path.open("w", encoding="utf-8") as file:
for event in events:
file.write(json.dumps(event, ensure_ascii=False, default=str))
file.write("\n")
temp_path.replace(self._events_path(thread_id))
def _read_seq(self, thread_id: str) -> int:
path = self._seq_path(thread_id)
if not path.exists():
return 0
try:
return int(path.read_text(encoding="utf-8").strip() or "0")
except ValueError:
return 0
def _write_seq(self, thread_id: str, seq: int) -> None:
self._seq_path(thread_id).write_text(str(seq), encoding="utf-8")
def _thread_dir(self, thread_id: str) -> Path:
return self._base_dir / "threads" / thread_id
def _events_path(self, thread_id: str) -> Path:
return self._thread_dir(thread_id) / "events.jsonl"
def _seq_path(self, thread_id: str) -> Path:
return self._thread_dir(thread_id) / "seq"
-14
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@@ -1,14 +0,0 @@
"""Storage-facing adapters owned by the app layer."""
from .run_events import AppRunEventStore
from .runs import FeedbackStoreAdapter, RunStoreAdapter, StorageRunObserver
from .thread_meta import ThreadMetaStorage, ThreadMetaStoreAdapter
__all__ = [
"AppRunEventStore",
"FeedbackStoreAdapter",
"RunStoreAdapter",
"StorageRunObserver",
"ThreadMetaStorage",
"ThreadMetaStoreAdapter",
]
-166
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@@ -1,166 +0,0 @@
"""App-owned adapter from runs callbacks to storage run event repository."""
from __future__ import annotations
from datetime import datetime
from typing import Any
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
from store.repositories import RunEvent, RunEventCreate, build_run_event_repository, build_thread_meta_repository
from deerflow.runtime.actor_context import get_actor_context
class AppRunEventStore:
"""Implements the harness RunEventStore protocol using storage repositories."""
def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
self._session_factory = session_factory
async def put_batch(self, events: list[dict[str, Any]]) -> list[dict[str, Any]]:
if not events:
return []
denied = {str(event["thread_id"]) for event in events if not await self._thread_visible(str(event["thread_id"]))}
if denied:
raise PermissionError(f"actor is not allowed to append events for thread(s): {', '.join(sorted(denied))}")
async with self._session_factory() as session:
try:
repo = build_run_event_repository(session)
rows = await repo.append_batch([_event_create_from_dict(event) for event in events])
await session.commit()
except Exception:
await session.rollback()
raise
return [_event_to_dict(row) for row in rows]
async def list_messages(
self,
thread_id: str,
*,
limit: int = 50,
before_seq: int | None = None,
after_seq: int | None = None,
) -> list[dict[str, Any]]:
if not await self._thread_visible(thread_id):
return []
async with self._session_factory() as session:
repo = build_run_event_repository(session)
rows = await repo.list_messages(
thread_id,
limit=limit,
before_seq=before_seq,
after_seq=after_seq,
)
return [_event_to_dict(row) for row in rows]
async def list_events(
self,
thread_id: str,
run_id: str,
*,
event_types: list[str] | None = None,
limit: int = 500,
) -> list[dict[str, Any]]:
if not await self._thread_visible(thread_id):
return []
async with self._session_factory() as session:
repo = build_run_event_repository(session)
rows = await repo.list_events(thread_id, run_id, event_types=event_types, limit=limit)
return [_event_to_dict(row) for row in rows]
async def list_messages_by_run(
self,
thread_id: str,
run_id: str,
*,
limit: int = 50,
before_seq: int | None = None,
after_seq: int | None = None,
) -> list[dict[str, Any]]:
if not await self._thread_visible(thread_id):
return []
async with self._session_factory() as session:
repo = build_run_event_repository(session)
rows = await repo.list_messages_by_run(
thread_id,
run_id,
limit=limit,
before_seq=before_seq,
after_seq=after_seq,
)
return [_event_to_dict(row) for row in rows]
async def count_messages(self, thread_id: str) -> int:
if not await self._thread_visible(thread_id):
return 0
async with self._session_factory() as session:
repo = build_run_event_repository(session)
return await repo.count_messages(thread_id)
async def delete_by_thread(self, thread_id: str) -> int:
if not await self._thread_visible(thread_id):
return 0
async with self._session_factory() as session:
try:
repo = build_run_event_repository(session)
count = await repo.delete_by_thread(thread_id)
await session.commit()
except Exception:
await session.rollback()
raise
return count
async def delete_by_run(self, thread_id: str, run_id: str) -> int:
if not await self._thread_visible(thread_id):
return 0
async with self._session_factory() as session:
try:
repo = build_run_event_repository(session)
count = await repo.delete_by_run(thread_id, run_id)
await session.commit()
except Exception:
await session.rollback()
raise
return count
async def _thread_visible(self, thread_id: str) -> bool:
actor = get_actor_context()
if actor is None or actor.user_id is None:
return True
async with self._session_factory() as session:
thread_repo = build_thread_meta_repository(session)
thread = await thread_repo.get_thread_meta(thread_id)
if thread is None:
return True
return thread.user_id is None or thread.user_id == actor.user_id
def _event_create_from_dict(event: dict[str, Any]) -> RunEventCreate:
created_at = event.get("created_at")
return RunEventCreate(
thread_id=str(event["thread_id"]),
run_id=str(event["run_id"]),
event_type=str(event["event_type"]),
category=str(event["category"]),
content=event.get("content", ""),
metadata=dict(event.get("metadata") or {}),
created_at=datetime.fromisoformat(created_at) if isinstance(created_at, str) else created_at,
)
def _event_to_dict(event: RunEvent) -> dict[str, Any]:
return {
"thread_id": event.thread_id,
"run_id": event.run_id,
"event_type": event.event_type,
"category": event.category,
"content": event.content,
"metadata": event.metadata,
"seq": event.seq,
"created_at": event.created_at.isoformat(),
}
-515
View File
@@ -1,515 +0,0 @@
"""Run lifecycle persistence adapters owned by the app layer."""
from __future__ import annotations
import logging
import uuid
from collections.abc import Callable
from typing import Protocol, TypedDict, Unpack, cast
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
from store.repositories import FeedbackCreate, Run, RunCreate, build_feedback_repository, build_run_repository
from deerflow.runtime.actor_context import AUTO, resolve_user_id
from deerflow.runtime.serialization import serialize_lc_object
from deerflow.runtime.runs.observer import LifecycleEventType, RunLifecycleEvent, RunObserver
from deerflow.runtime.stream_bridge import JSONValue
from .thread_meta import ThreadMetaStorage
logger = logging.getLogger(__name__)
class RunCreateFields(TypedDict, total=False):
status: str
created_at: str
started_at: str
ended_at: str
assistant_id: str | None
user_id: str | None
follow_up_to_run_id: str | None
metadata: dict[str, JSONValue]
kwargs: dict[str, JSONValue]
class RunStatusUpdateFields(TypedDict, total=False):
started_at: str
ended_at: str
metadata: dict[str, JSONValue]
class RunCompletionFields(TypedDict, total=False):
total_input_tokens: int
total_output_tokens: int
total_tokens: int
llm_call_count: int
lead_agent_tokens: int
subagent_tokens: int
middleware_tokens: int
message_count: int
last_ai_message: str | None
first_human_message: str | None
error: str | None
class RunRow(TypedDict, total=False):
run_id: str
thread_id: str
assistant_id: str | None
status: str
multitask_strategy: str
follow_up_to_run_id: str | None
metadata: dict[str, JSONValue]
created_at: str
updated_at: str
started_at: str | None
ended_at: str | None
error: str | None
class RunReadRepository(Protocol):
"""Protocol for durable run queries."""
async def get(self, run_id: str, *, user_id: str | None | object = AUTO) -> RunRow | None: ...
async def list_by_thread(
self,
thread_id: str,
*,
limit: int = 100,
user_id: str | None | object = AUTO,
) -> list[RunRow]: ...
class RunWriteRepository(Protocol):
"""Protocol for durable run writes."""
async def create(self, run_id: str, thread_id: str, **kwargs: Unpack[RunCreateFields]) -> None: ...
async def update_status(
self,
run_id: str,
status: str,
**kwargs: Unpack[RunStatusUpdateFields],
) -> None: ...
async def set_error(self, run_id: str, error: str) -> None: ...
async def update_run_completion(
self,
run_id: str,
*,
status: str,
**kwargs: Unpack[RunCompletionFields],
) -> None: ...
class RunDeleteRepository(Protocol):
"""Protocol for durable run deletion."""
async def delete(self, run_id: str) -> bool: ...
class _RepositoryContext:
def __init__(
self,
session_factory: async_sessionmaker[AsyncSession],
build_repo: Callable[[AsyncSession], object],
*,
commit: bool,
) -> None:
self._session_factory = session_factory
self._build_repo = build_repo
self._commit = commit
self._session: AsyncSession | None = None
async def __aenter__(self):
self._session = self._session_factory()
return self._build_repo(self._session)
async def __aexit__(self, exc_type, exc, tb) -> None:
if self._session is None:
return
try:
if self._commit:
if exc_type is None:
await self._session.commit()
else:
await self._session.rollback()
finally:
await self._session.close()
def _run_to_row(row: Run) -> RunRow:
return {
"run_id": row.run_id,
"thread_id": row.thread_id,
"assistant_id": row.assistant_id,
"user_id": row.user_id,
"status": row.status,
"model_name": row.model_name,
"multitask_strategy": row.multitask_strategy,
"follow_up_to_run_id": row.follow_up_to_run_id,
"metadata": cast(dict[str, JSONValue], row.metadata),
"kwargs": cast(dict[str, JSONValue], row.kwargs),
"created_at": row.created_time.isoformat(),
"updated_at": row.updated_time.isoformat() if row.updated_time else "",
"total_input_tokens": row.total_input_tokens,
"total_output_tokens": row.total_output_tokens,
"total_tokens": row.total_tokens,
"llm_call_count": row.llm_call_count,
"lead_agent_tokens": row.lead_agent_tokens,
"subagent_tokens": row.subagent_tokens,
"middleware_tokens": row.middleware_tokens,
"message_count": row.message_count,
"first_human_message": row.first_human_message,
"last_ai_message": row.last_ai_message,
"error": row.error,
}
class FeedbackStoreAdapter:
"""Expose feedback route semantics on top of storage package repositories."""
def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
self._session_factory = session_factory
async def create(
self,
*,
run_id: str,
thread_id: str,
rating: int,
owner_id: str | None = None,
user_id: str | None = None,
message_id: str | None = None,
comment: str | None = None,
) -> dict[str, object]:
if rating not in (1, -1):
raise ValueError(f"rating must be +1 or -1, got {rating}")
effective_user_id = user_id if user_id is not None else owner_id
async with self._transaction() as repo:
row = await repo.create_feedback(
FeedbackCreate(
feedback_id=str(uuid.uuid4()),
run_id=run_id,
thread_id=thread_id,
rating=rating,
user_id=effective_user_id,
message_id=message_id,
comment=comment,
)
)
return _feedback_to_dict(row)
async def get(self, feedback_id: str) -> dict[str, object] | None:
async with self._read() as repo:
row = await repo.get_feedback(feedback_id)
return _feedback_to_dict(row) if row is not None else None
async def list_by_run(
self,
thread_id: str,
run_id: str,
*,
limit: int = 100,
user_id: str | None = None,
) -> list[dict[str, object]]:
async with self._read() as repo:
rows = await repo.list_feedback_by_run(run_id)
filtered = [row for row in rows if row.thread_id == thread_id]
if user_id is not None:
filtered = [row for row in filtered if row.user_id == user_id]
return [_feedback_to_dict(row) for row in filtered][:limit]
async def list_by_thread(self, thread_id: str, *, limit: int = 100) -> list[dict[str, object]]:
async with self._read() as repo:
rows = await repo.list_feedback_by_thread(thread_id)
return [_feedback_to_dict(row) for row in rows][:limit]
async def aggregate_by_run(self, thread_id: str, run_id: str) -> dict[str, object]:
rows = await self.list_by_run(thread_id, run_id)
positive = sum(1 for row in rows if row["rating"] == 1)
negative = sum(1 for row in rows if row["rating"] == -1)
return {"run_id": run_id, "total": len(rows), "positive": positive, "negative": negative}
async def delete(self, feedback_id: str) -> bool:
async with self._transaction() as repo:
return await repo.delete_feedback(feedback_id)
async def upsert(
self,
*,
run_id: str,
thread_id: str,
rating: int,
user_id: str,
comment: str | None = None,
) -> dict[str, object]:
if rating not in (1, -1):
raise ValueError(f"rating must be +1 or -1, got {rating}")
async with self._transaction() as repo:
rows = await repo.list_feedback_by_run(run_id)
existing = next((row for row in rows if row.thread_id == thread_id and row.user_id == user_id), None)
feedback_id = existing.feedback_id if existing is not None else str(uuid.uuid4())
if existing is not None:
await repo.delete_feedback(existing.feedback_id)
row = await repo.create_feedback(
FeedbackCreate(
feedback_id=feedback_id,
run_id=run_id,
thread_id=thread_id,
rating=rating,
user_id=user_id,
comment=comment,
)
)
return _feedback_to_dict(row)
async def delete_by_run(self, *, thread_id: str, run_id: str, user_id: str) -> bool:
async with self._transaction() as repo:
rows = await repo.list_feedback_by_run(run_id)
existing = next((row for row in rows if row.thread_id == thread_id and row.user_id == user_id), None)
if existing is None:
return False
return await repo.delete_feedback(existing.feedback_id)
async def list_by_thread_grouped(self, thread_id: str, *, user_id: str) -> dict[str, dict[str, object]]:
rows = await self.list_by_thread(thread_id)
return {
row["run_id"]: row
for row in rows
if row["user_id"] == user_id
}
def _read(self) -> _RepositoryContext:
return _RepositoryContext(self._session_factory, build_feedback_repository, commit=False)
def _transaction(self) -> _RepositoryContext:
return _RepositoryContext(self._session_factory, build_feedback_repository, commit=True)
def _feedback_to_dict(row) -> dict[str, object]:
return {
"feedback_id": row.feedback_id,
"run_id": row.run_id,
"thread_id": row.thread_id,
"user_id": row.user_id,
"owner_id": row.user_id,
"message_id": row.message_id,
"rating": row.rating,
"comment": row.comment,
"created_at": row.created_time.isoformat(),
}
class RunStoreAdapter:
"""Expose runs facade storage semantics on top of storage package repositories."""
def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
self._session_factory = session_factory
async def get(self, run_id: str, *, user_id: str | None | object = AUTO) -> RunRow | None:
effective_user_id = resolve_user_id(user_id, method_name="RunStoreAdapter.get")
async with self._read() as repo:
row = await repo.get_run(run_id)
if row is None:
return None
if effective_user_id is not None and row.user_id != effective_user_id:
return None
return _run_to_row(row)
async def list_by_thread(
self,
thread_id: str,
*,
limit: int = 100,
user_id: str | None | object = AUTO,
) -> list[RunRow]:
effective_user_id = resolve_user_id(user_id, method_name="RunStoreAdapter.list_by_thread")
async with self._read() as repo:
rows = await repo.list_runs_by_thread(thread_id, limit=limit, offset=0)
if effective_user_id is not None:
rows = [row for row in rows if row.user_id == effective_user_id]
return [_run_to_row(row) for row in rows]
async def create(self, run_id: str, thread_id: str, **kwargs: Unpack[RunCreateFields]) -> None:
metadata = cast(dict[str, JSONValue], serialize_lc_object(kwargs.get("metadata") or {}))
run_kwargs = cast(dict[str, JSONValue], serialize_lc_object(kwargs.get("kwargs") or {}))
effective_user_id = resolve_user_id(kwargs.get("user_id", AUTO), method_name="RunStoreAdapter.create")
async with self._transaction() as repo:
await repo.create_run(
RunCreate(
run_id=run_id,
thread_id=thread_id,
assistant_id=kwargs.get("assistant_id"),
user_id=effective_user_id,
status=kwargs.get("status", "pending"),
metadata=dict(metadata),
kwargs=dict(run_kwargs),
follow_up_to_run_id=kwargs.get("follow_up_to_run_id"),
)
)
async def delete(self, run_id: str, *, user_id: str | None | object = AUTO) -> bool:
async with self._transaction() as repo:
existing = await repo.get_run(run_id)
if existing is None:
return False
effective_user_id = resolve_user_id(user_id, method_name="RunStoreAdapter.delete")
if effective_user_id is not None and existing.user_id != effective_user_id:
return False
await repo.delete_run(run_id)
return True
async def update_status(
self,
run_id: str,
status: str,
**kwargs: Unpack[RunStatusUpdateFields],
) -> None:
async with self._transaction() as repo:
await repo.update_run_status(run_id, status)
async def set_error(self, run_id: str, error: str) -> None:
async with self._transaction() as repo:
await repo.update_run_status(run_id, "error", error=error)
async def update_run_completion(
self,
run_id: str,
*,
status: str,
**kwargs: Unpack[RunCompletionFields],
) -> None:
async with self._transaction() as repo:
await repo.update_run_completion(
run_id,
status=status,
total_input_tokens=kwargs.get("total_input_tokens", 0),
total_output_tokens=kwargs.get("total_output_tokens", 0),
total_tokens=kwargs.get("total_tokens", 0),
llm_call_count=kwargs.get("llm_call_count", 0),
lead_agent_tokens=kwargs.get("lead_agent_tokens", 0),
subagent_tokens=kwargs.get("subagent_tokens", 0),
middleware_tokens=kwargs.get("middleware_tokens", 0),
message_count=kwargs.get("message_count", 0),
last_ai_message=kwargs.get("last_ai_message"),
first_human_message=kwargs.get("first_human_message"),
error=kwargs.get("error"),
)
def _read(self) -> _RepositoryContext:
return _RepositoryContext(self._session_factory, build_run_repository, commit=False)
def _transaction(self) -> _RepositoryContext:
return _RepositoryContext(self._session_factory, build_run_repository, commit=True)
class StorageRunObserver(RunObserver):
"""Persist run lifecycle state into app-owned repositories."""
def __init__(
self,
run_write_repo: RunWriteRepository | None = None,
thread_meta_storage: ThreadMetaStorage | None = None,
) -> None:
self._run_write_repo = run_write_repo
self._thread_meta_storage = thread_meta_storage
async def on_event(self, event: RunLifecycleEvent) -> None:
try:
await self._dispatch(event)
except Exception:
logger.exception(
"StorageRunObserver failed to persist event %s for run %s",
event.event_type,
event.run_id,
)
async def _dispatch(self, event: RunLifecycleEvent) -> None:
handlers = {
LifecycleEventType.RUN_STARTED: self._handle_run_started,
LifecycleEventType.RUN_COMPLETED: self._handle_run_completed,
LifecycleEventType.RUN_FAILED: self._handle_run_failed,
LifecycleEventType.RUN_CANCELLED: self._handle_run_cancelled,
LifecycleEventType.THREAD_STATUS_UPDATED: self._handle_thread_status,
}
handler = handlers.get(event.event_type)
if handler:
await handler(event)
async def _handle_run_started(self, event: RunLifecycleEvent) -> None:
if self._run_write_repo:
await self._run_write_repo.update_status(
run_id=event.run_id,
status="running",
started_at=event.occurred_at.isoformat(),
)
async def _handle_run_completed(self, event: RunLifecycleEvent) -> None:
payload = dict(event.payload) if event.payload else {}
if self._run_write_repo:
completion_data = payload.get("completion_data")
if isinstance(completion_data, dict):
await self._run_write_repo.update_run_completion(
run_id=event.run_id,
status="success",
**cast(RunCompletionFields, completion_data),
)
else:
await self._run_write_repo.update_status(
run_id=event.run_id,
status="success",
ended_at=event.occurred_at.isoformat(),
)
if self._thread_meta_storage and "title" in payload:
await self._thread_meta_storage.sync_thread_title(
thread_id=event.thread_id,
title=payload["title"],
)
async def _handle_run_failed(self, event: RunLifecycleEvent) -> None:
if self._run_write_repo:
payload = dict(event.payload) if event.payload else {}
error = payload.get("error", "Unknown error")
completion_data = payload.get("completion_data")
if isinstance(completion_data, dict):
await self._run_write_repo.update_run_completion(
run_id=event.run_id,
status="error",
error=str(error),
**cast(RunCompletionFields, completion_data),
)
else:
await self._run_write_repo.update_status(
run_id=event.run_id,
status="error",
ended_at=event.occurred_at.isoformat(),
)
await self._run_write_repo.set_error(run_id=event.run_id, error=str(error))
async def _handle_run_cancelled(self, event: RunLifecycleEvent) -> None:
if self._run_write_repo:
payload = dict(event.payload) if event.payload else {}
completion_data = payload.get("completion_data")
if isinstance(completion_data, dict):
await self._run_write_repo.update_run_completion(
run_id=event.run_id,
status="interrupted",
**cast(RunCompletionFields, completion_data),
)
else:
await self._run_write_repo.update_status(
run_id=event.run_id,
status="interrupted",
ended_at=event.occurred_at.isoformat(),
)
async def _handle_thread_status(self, event: RunLifecycleEvent) -> None:
if self._thread_meta_storage:
payload = dict(event.payload) if event.payload else {}
status = payload.get("status", "idle")
await self._thread_meta_storage.sync_thread_status(
thread_id=event.thread_id,
status=status,
)
-208
View File
@@ -1,208 +0,0 @@
"""Thread metadata storage adapter owned by the app layer."""
from __future__ import annotations
from typing import Any
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
from store.repositories import build_thread_meta_repository
from store.repositories.contracts import (
ThreadMeta,
ThreadMetaCreate,
ThreadMetaRepositoryProtocol,
)
from deerflow.runtime.actor_context import AUTO, resolve_user_id
class ThreadMetaStoreAdapter:
"""Use storage package thread repositories with per-call sessions."""
def __init__(self, session_factory: async_sessionmaker[AsyncSession]) -> None:
self._session_factory = session_factory
async def create_thread_meta(self, data: ThreadMetaCreate) -> ThreadMeta:
async with self._transaction() as repo:
return await repo.create_thread_meta(data)
async def get_thread_meta(self, thread_id: str) -> ThreadMeta | None:
async with self._read() as repo:
return await repo.get_thread_meta(thread_id)
async def update_thread_meta(
self,
thread_id: str,
*,
assistant_id: str | None = None,
display_name: str | None = None,
status: str | None = None,
metadata: dict[str, Any] | None = None,
) -> None:
async with self._transaction() as repo:
await repo.update_thread_meta(
thread_id,
assistant_id=assistant_id,
display_name=display_name,
status=status,
metadata=metadata,
)
async def delete_thread(self, thread_id: str) -> None:
async with self._transaction() as repo:
await repo.delete_thread(thread_id)
async def search_threads(
self,
*,
metadata: dict[str, Any] | None = None,
status: str | None = None,
user_id: str | None = None,
assistant_id: str | None = None,
limit: int = 100,
offset: int = 0,
) -> list[ThreadMeta]:
async with self._read() as repo:
return await repo.search_threads(
metadata=metadata,
status=status,
user_id=user_id,
assistant_id=assistant_id,
limit=limit,
offset=offset,
)
def _read(self):
return _ThreadMetaRepositoryContext(self._session_factory, commit=False)
def _transaction(self):
return _ThreadMetaRepositoryContext(self._session_factory, commit=True)
class _ThreadMetaRepositoryContext:
def __init__(self, session_factory: async_sessionmaker[AsyncSession], *, commit: bool) -> None:
self._session_factory = session_factory
self._commit = commit
self._session: AsyncSession | None = None
async def __aenter__(self):
self._session = self._session_factory()
return build_thread_meta_repository(self._session)
async def __aexit__(self, exc_type, exc, tb) -> None:
if self._session is None:
return
try:
if self._commit:
if exc_type is None:
await self._session.commit()
else:
await self._session.rollback()
finally:
await self._session.close()
class ThreadMetaStorage:
"""App-facing adapter around the storage thread metadata contract."""
def __init__(self, repo: ThreadMetaRepositoryProtocol) -> None:
self._repo = repo
async def get_thread(self, thread_id: str, *, user_id: str | None | object = AUTO) -> ThreadMeta | None:
thread = await self._repo.get_thread_meta(thread_id)
if thread is None:
return None
effective_user_id = resolve_user_id(user_id, method_name="ThreadMetaStorage.get_thread")
if effective_user_id is not None and thread.user_id != effective_user_id:
return None
return thread
async def ensure_thread(
self,
*,
thread_id: str,
assistant_id: str | None = None,
metadata: dict[str, Any] | None = None,
user_id: str | None | object = AUTO,
) -> ThreadMeta:
effective_user_id = resolve_user_id(user_id, method_name="ThreadMetaStorage.ensure_thread")
existing = await self.get_thread(thread_id, user_id=effective_user_id)
if existing is not None:
return existing
return await self._repo.create_thread_meta(
ThreadMetaCreate(
thread_id=thread_id,
assistant_id=assistant_id,
user_id=effective_user_id,
metadata=metadata or {},
)
)
async def ensure_thread_running(
self,
*,
thread_id: str,
assistant_id: str | None = None,
metadata: dict[str, Any] | None = None,
) -> ThreadMeta | None:
existing = await self._repo.get_thread_meta(thread_id)
if existing is None:
return await self._repo.create_thread_meta(
ThreadMetaCreate(
thread_id=thread_id,
assistant_id=assistant_id,
status="running",
metadata=metadata or {},
)
)
await self._repo.update_thread_meta(thread_id, status="running")
return await self._repo.get_thread_meta(thread_id)
async def sync_thread_title(self, *, thread_id: str, title: str) -> None:
await self._repo.update_thread_meta(thread_id, display_name=title)
async def sync_thread_assistant_id(self, *, thread_id: str, assistant_id: str) -> None:
await self._repo.update_thread_meta(thread_id, assistant_id=assistant_id)
async def sync_thread_status(self, *, thread_id: str, status: str) -> None:
await self._repo.update_thread_meta(thread_id, status=status)
async def sync_thread_metadata(
self,
*,
thread_id: str,
metadata: dict[str, Any],
) -> None:
await self._repo.update_thread_meta(thread_id, metadata=metadata)
async def delete_thread(self, thread_id: str) -> None:
await self._repo.delete_thread(thread_id)
async def search_threads(
self,
*,
metadata: dict[str, Any] | None = None,
status: str | None = None,
user_id: str | None | object = AUTO,
assistant_id: str | None = None,
limit: int = 100,
offset: int = 0,
) -> list[ThreadMeta]:
normalized_status = status.strip() if status is not None else None
resolved_user_id = resolve_user_id(user_id, method_name="ThreadMetaStorage.search_threads")
normalized_user_id = resolved_user_id.strip() if resolved_user_id is not None else None
normalized_assistant_id = (
assistant_id.strip() if assistant_id is not None else None
)
return await self._repo.search_threads(
metadata=metadata,
status=normalized_status or None,
user_id=normalized_user_id or None,
assistant_id=normalized_assistant_id or None,
limit=limit,
offset=offset,
)
__all__ = ["ThreadMetaStorage", "ThreadMetaStoreAdapter"]
@@ -1,6 +0,0 @@
"""App-owned stream bridge adapters and factory."""
from .factory import build_stream_bridge
from .adapters import MemoryStreamBridge, RedisStreamBridge
__all__ = ["MemoryStreamBridge", "RedisStreamBridge", "build_stream_bridge"]
@@ -1,6 +0,0 @@
"""Concrete stream bridge adapters owned by the app layer."""
from .memory import MemoryStreamBridge
from .redis import RedisStreamBridge
__all__ = ["MemoryStreamBridge", "RedisStreamBridge"]
@@ -1,450 +0,0 @@
"""In-memory stream bridge implementation owned by the app layer."""
from __future__ import annotations
import asyncio
import json
import logging
import time
from collections.abc import AsyncIterator
from dataclasses import dataclass, field
from typing import Any, Literal
from deerflow.runtime.stream_bridge import (
CANCELLED_SENTINEL,
END_SENTINEL,
HEARTBEAT_SENTINEL,
TERMINAL_STATES,
ResumeResult,
StreamBridge,
StreamEvent,
StreamStatus,
)
from deerflow.runtime.stream_bridge.exceptions import (
BridgeClosedError,
StreamCapacityExceededError,
StreamTerminatedError,
)
logger = logging.getLogger(__name__)
@dataclass
class _RunStream:
condition: asyncio.Condition = field(default_factory=asyncio.Condition)
events: list[StreamEvent] = field(default_factory=list)
id_to_offset: dict[str, int] = field(default_factory=dict)
start_offset: int = 0
current_bytes: int = 0
seq: int = 0
status: StreamStatus = StreamStatus.ACTIVE
created_at: float = field(default_factory=time.monotonic)
last_publish_at: float | None = None
ended_at: float | None = None
subscriber_count: int = 0
last_subscribe_at: float | None = None
awaiting_input: bool = False
awaiting_since: float | None = None
class MemoryStreamBridge(StreamBridge):
"""Per-run in-memory event log implementation."""
def __init__(
self,
*,
max_events_per_stream: int = 256,
max_bytes_per_stream: int = 10 * 1024 * 1024,
max_active_streams: int = 1000,
stream_eviction_policy: Literal["reject", "lru"] = "lru",
terminal_retention_ttl: float = 300.0,
active_no_publish_timeout: float = 600.0,
orphan_timeout: float = 60.0,
max_stream_age: float = 86400.0,
hitl_extended_timeout: float = 7200.0,
cleanup_interval: float = 30.0,
queue_maxsize: int | None = None,
) -> None:
if queue_maxsize is not None:
max_events_per_stream = queue_maxsize
self._max_events = max_events_per_stream
self._max_bytes = max_bytes_per_stream
self._max_streams = max_active_streams
self._eviction_policy = stream_eviction_policy
self._terminal_ttl = terminal_retention_ttl
self._active_timeout = active_no_publish_timeout
self._orphan_timeout = orphan_timeout
self._max_age = max_stream_age
self._hitl_timeout = hitl_extended_timeout
self._cleanup_interval = cleanup_interval
self._streams: dict[str, _RunStream] = {}
self._registry_lock = asyncio.Lock()
self._closed = False
self._cleanup_task: asyncio.Task[None] | None = None
async def start(self) -> None:
if self._cleanup_task is None:
self._cleanup_task = asyncio.create_task(self._cleanup_loop())
logger.info(
"MemoryStreamBridge started (max_events=%d, max_bytes=%d, max_streams=%d)",
self._max_events,
self._max_bytes,
self._max_streams,
)
async def close(self) -> None:
async with self._registry_lock:
self._closed = True
if self._cleanup_task is not None:
self._cleanup_task.cancel()
try:
await self._cleanup_task
except asyncio.CancelledError:
pass
self._cleanup_task = None
for stream in self._streams.values():
async with stream.condition:
stream.status = StreamStatus.CLOSED
stream.condition.notify_all()
self._streams.clear()
logger.info("MemoryStreamBridge closed")
async def _get_or_create_stream(self, run_id: str) -> _RunStream:
stream = self._streams.get(run_id)
if stream is not None:
return stream
async with self._registry_lock:
if self._closed:
raise BridgeClosedError("Stream bridge is closed")
stream = self._streams.get(run_id)
if stream is not None:
return stream
if len(self._streams) >= self._max_streams:
if self._eviction_policy == "reject":
raise StreamCapacityExceededError(
f"Max {self._max_streams} active streams reached"
)
evicted = self._evict_oldest_terminal()
if evicted is None:
raise StreamCapacityExceededError("All streams active, cannot evict")
logger.info("Evicted stream %s to make room", evicted)
stream = _RunStream()
self._streams[run_id] = stream
logger.debug("Created stream for run %s", run_id)
return stream
def _evict_oldest_terminal(self) -> str | None:
oldest_run_id: str | None = None
oldest_ended_at: float = float("inf")
for run_id, stream in self._streams.items():
if stream.status in TERMINAL_STATES and stream.ended_at is not None:
if stream.ended_at < oldest_ended_at:
oldest_ended_at = stream.ended_at
oldest_run_id = run_id
if oldest_run_id is not None:
del self._streams[oldest_run_id]
return oldest_run_id
return None
def _next_id(self, stream: _RunStream) -> str:
stream.seq += 1
return f"{int(time.time() * 1000)}-{stream.seq}"
def _estimate_size(self, event: StreamEvent) -> int:
base = len(event.id) + len(event.event) + 100
if event.data is None:
return base
if isinstance(event.data, str):
return base + len(event.data)
if isinstance(event.data, (dict, list)):
try:
return base + len(json.dumps(event.data, default=str))
except (TypeError, ValueError):
return base + 200
return base + 50
def _evict_overflow(self, stream: _RunStream) -> None:
while len(stream.events) > self._max_events or stream.current_bytes > self._max_bytes:
if not stream.events:
break
evicted = stream.events.pop(0)
stream.id_to_offset.pop(evicted.id, None)
stream.current_bytes -= self._estimate_size(evicted)
stream.start_offset += 1
async def publish(self, run_id: str, event: str, data: Any) -> str:
stream = await self._get_or_create_stream(run_id)
async with stream.condition:
if stream.status != StreamStatus.ACTIVE:
raise StreamTerminatedError(
f"Cannot publish to {stream.status.value} stream"
)
entry = StreamEvent(id=self._next_id(stream), event=event, data=data)
absolute_offset = stream.start_offset + len(stream.events)
stream.events.append(entry)
stream.id_to_offset[entry.id] = absolute_offset
stream.current_bytes += self._estimate_size(entry)
stream.last_publish_at = time.monotonic()
self._evict_overflow(stream)
stream.condition.notify_all()
return entry.id
async def publish_end(self, run_id: str) -> str:
return await self.publish_terminal(run_id, StreamStatus.ENDED)
async def publish_terminal(
self,
run_id: str,
kind: StreamStatus,
data: Any = None,
) -> str:
if kind not in TERMINAL_STATES:
raise ValueError(f"Invalid terminal kind: {kind}")
stream = await self._get_or_create_stream(run_id)
async with stream.condition:
if stream.status != StreamStatus.ACTIVE:
for evt in reversed(stream.events):
if evt.event in ("end", "cancel", "error", "dead_letter"):
return evt.id
return ""
event_name = {
StreamStatus.ENDED: "end",
StreamStatus.CANCELLED: "cancel",
StreamStatus.ERRORED: "error",
}[kind]
entry = StreamEvent(id=self._next_id(stream), event=event_name, data=data)
absolute_offset = stream.start_offset + len(stream.events)
stream.events.append(entry)
stream.id_to_offset[entry.id] = absolute_offset
stream.current_bytes += self._estimate_size(entry)
stream.status = kind
stream.ended_at = time.monotonic()
stream.awaiting_input = False
stream.condition.notify_all()
logger.debug("Stream %s terminal: %s", run_id, kind.value)
return entry.id
async def cancel(self, run_id: str) -> None:
await self.publish_terminal(run_id, StreamStatus.CANCELLED)
async def subscribe(
self,
run_id: str,
*,
last_event_id: str | None = None,
heartbeat_interval: float = 15.0,
) -> AsyncIterator[StreamEvent]:
stream = await self._get_or_create_stream(run_id)
resume = self._resolve_resume_point(stream, last_event_id)
next_offset = resume.next_offset
async with stream.condition:
stream.subscriber_count += 1
stream.last_subscribe_at = time.monotonic()
try:
while True:
entry_to_yield: StreamEvent | None = None
sentinel_to_yield: StreamEvent | None = None
should_return = False
should_wait = False
async with stream.condition:
if self._closed or stream.status == StreamStatus.CLOSED:
sentinel_to_yield = CANCELLED_SENTINEL
should_return = True
elif next_offset < stream.start_offset:
next_offset = stream.start_offset
else:
local_index = next_offset - stream.start_offset
if 0 <= local_index < len(stream.events):
entry_to_yield = stream.events[local_index]
next_offset += 1
if entry_to_yield.event in ("end", "cancel", "error", "dead_letter"):
should_return = True
elif stream.status in TERMINAL_STATES:
sentinel_to_yield = END_SENTINEL
should_return = True
else:
should_wait = True
try:
await asyncio.wait_for(
stream.condition.wait(),
timeout=heartbeat_interval,
)
except TimeoutError:
pass
if sentinel_to_yield is not None:
yield sentinel_to_yield
if should_return:
return
continue
if entry_to_yield is not None:
yield entry_to_yield
if should_return:
return
continue
if should_wait:
async with stream.condition:
local_index = next_offset - stream.start_offset
has_events = 0 <= local_index < len(stream.events)
is_terminal = stream.status in TERMINAL_STATES
if not has_events and not is_terminal:
yield HEARTBEAT_SENTINEL
finally:
async with stream.condition:
stream.subscriber_count = max(0, stream.subscriber_count - 1)
async def mark_awaiting_input(self, run_id: str) -> None:
stream = self._streams.get(run_id)
if stream is None:
return
async with stream.condition:
if stream.status == StreamStatus.ACTIVE:
stream.awaiting_input = True
stream.awaiting_since = time.monotonic()
logger.debug("Stream %s marked as awaiting input", run_id)
async def cleanup(self, run_id: str, *, delay: float = 0) -> None:
if delay > 0:
await asyncio.sleep(delay)
await self._do_cleanup(run_id, "manual")
async def _do_cleanup(self, run_id: str, reason: str) -> None:
async with self._registry_lock:
stream = self._streams.pop(run_id, None)
if stream is not None:
async with stream.condition:
stream.status = StreamStatus.CLOSED
stream.condition.notify_all()
logger.debug("Cleaned up stream %s (reason: %s)", run_id, reason)
async def _mark_dead_letter(self, run_id: str, reason: str) -> None:
stream = self._streams.get(run_id)
if stream is None:
return
async with stream.condition:
if stream.status != StreamStatus.ACTIVE:
return
entry = StreamEvent(
id=self._next_id(stream),
event="dead_letter",
data={"reason": reason, "timestamp": time.time()},
)
absolute_offset = stream.start_offset + len(stream.events)
stream.events.append(entry)
stream.id_to_offset[entry.id] = absolute_offset
stream.current_bytes += self._estimate_size(entry)
stream.status = StreamStatus.ERRORED
stream.ended_at = time.monotonic()
stream.condition.notify_all()
logger.warning("Stream %s marked as dead letter: %s", run_id, reason)
async def _cleanup_loop(self) -> None:
while not self._closed:
try:
await asyncio.sleep(self._cleanup_interval)
except asyncio.CancelledError:
break
now = time.monotonic()
to_cleanup: list[tuple[str, str]] = []
to_mark_dead: list[tuple[str, str]] = []
async with self._registry_lock:
for run_id, stream in list(self._streams.items()):
if now - stream.created_at > self._max_age:
to_cleanup.append((run_id, "max_age_exceeded"))
continue
if stream.status == StreamStatus.ACTIVE:
timeout = self._hitl_timeout if stream.awaiting_input else self._active_timeout
last_activity = stream.last_publish_at or stream.created_at
if now - last_activity > timeout:
to_mark_dead.append((run_id, "no_publish_timeout"))
continue
if stream.status in TERMINAL_STATES and stream.ended_at:
if stream.subscriber_count > 0:
continue
last_sub = stream.last_subscribe_at or stream.ended_at
if now - last_sub > self._orphan_timeout:
to_cleanup.append((run_id, "orphan"))
continue
if now - stream.ended_at > self._terminal_ttl:
to_cleanup.append((run_id, "ttl_expired"))
for run_id, reason in to_mark_dead:
await self._mark_dead_letter(run_id, reason)
for run_id, reason in to_cleanup:
await self._do_cleanup(run_id, reason)
def get_stats(self) -> dict[str, Any]:
active = sum(1 for s in self._streams.values() if s.status == StreamStatus.ACTIVE)
terminal = sum(1 for s in self._streams.values() if s.status in TERMINAL_STATES)
total_events = sum(len(s.events) for s in self._streams.values())
total_bytes = sum(s.current_bytes for s in self._streams.values())
total_subs = sum(s.subscriber_count for s in self._streams.values())
return {
"total_streams": len(self._streams),
"active_streams": active,
"terminal_streams": terminal,
"total_events": total_events,
"total_bytes": total_bytes,
"total_subscribers": total_subs,
"closed": self._closed,
}
def _resolve_resume_point(
self,
stream: _RunStream,
last_event_id: str | None,
) -> ResumeResult:
if last_event_id is None:
return ResumeResult(next_offset=stream.start_offset, status="fresh")
if last_event_id in stream.id_to_offset:
return ResumeResult(
next_offset=stream.id_to_offset[last_event_id] + 1,
status="resumed",
)
parts = last_event_id.split("-")
if len(parts) != 2:
return ResumeResult(next_offset=stream.start_offset, status="invalid")
try:
event_ts = int(parts[0])
_event_seq = int(parts[1])
except ValueError:
return ResumeResult(next_offset=stream.start_offset, status="invalid")
if stream.events:
try:
oldest_parts = stream.events[0].id.split("-")
oldest_ts = int(oldest_parts[0])
if event_ts < oldest_ts:
return ResumeResult(
next_offset=stream.start_offset,
status="evicted",
gap_count=stream.start_offset,
)
except (ValueError, IndexError):
pass
return ResumeResult(next_offset=stream.start_offset, status="unknown")
__all__ = ["MemoryStreamBridge"]
@@ -1,37 +0,0 @@
"""Redis-backed stream bridge placeholder owned by the app layer."""
from __future__ import annotations
from collections.abc import AsyncIterator
from typing import Any
from deerflow.runtime.stream_bridge import StreamBridge, StreamEvent
class RedisStreamBridge(StreamBridge):
"""Reserved app-owned Redis implementation.
Phase 1 intentionally keeps Redis out of the harness package. The concrete
implementation will live here once cross-process streaming is introduced.
"""
def __init__(self, *, redis_url: str) -> None:
self._redis_url = redis_url
async def publish(self, run_id: str, event: str, data: Any) -> str:
raise NotImplementedError("Redis stream bridge will be implemented in app infra")
async def publish_end(self, run_id: str) -> str:
raise NotImplementedError("Redis stream bridge will be implemented in app infra")
def subscribe(
self,
run_id: str,
*,
last_event_id: str | None = None,
heartbeat_interval: float = 15.0,
) -> AsyncIterator[StreamEvent]:
raise NotImplementedError("Redis stream bridge will be implemented in app infra")
async def cleanup(self, run_id: str, *, delay: float = 0) -> None:
raise NotImplementedError("Redis stream bridge will be implemented in app infra")
@@ -1,50 +0,0 @@
"""App-owned stream bridge factory."""
from __future__ import annotations
import logging
from collections.abc import AsyncIterator
from contextlib import AbstractAsyncContextManager, asynccontextmanager
from deerflow.config.stream_bridge_config import get_stream_bridge_config
from deerflow.runtime.stream_bridge import StreamBridge
from .adapters import MemoryStreamBridge, RedisStreamBridge
logger = logging.getLogger(__name__)
def build_stream_bridge(config=None) -> AbstractAsyncContextManager[StreamBridge]:
"""Build the configured app-owned stream bridge."""
return _build_stream_bridge_impl(config)
@asynccontextmanager
async def _build_stream_bridge_impl(config=None) -> AsyncIterator[StreamBridge]:
if config is None:
config = get_stream_bridge_config()
if config is None or config.type == "memory":
maxsize = config.queue_maxsize if config is not None else 256
bridge = MemoryStreamBridge(queue_maxsize=maxsize)
await bridge.start()
logger.info("Stream bridge initialised: memory (queue_maxsize=%d)", maxsize)
try:
yield bridge
finally:
await bridge.close()
return
if config.type == "redis":
if not config.redis_url:
raise ValueError("Redis stream bridge requires redis_url")
bridge = RedisStreamBridge(redis_url=config.redis_url)
await bridge.start()
logger.info("Stream bridge initialised: redis (%s)", config.redis_url)
try:
yield bridge
finally:
await bridge.close()
return
raise ValueError(f"Unknown stream bridge type: {config.type!r}")
-15
View File
@@ -1,15 +0,0 @@
"""Entry point for running the Gateway API via `python app/main.py`.
Useful for IDE debugging (e.g., PyCharm / VS Code debug configurations).
Equivalent to: PYTHONPATH=. uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001
"""
import uvicorn
if __name__ == "__main__":
uvicorn.run(
"app.gateway.app:app",
host="0.0.0.0",
port=8001,
reload=True,
)
-314
View File
@@ -1,314 +0,0 @@
# app.plugins Design Overview
This document describes the current role of `backend/app/plugins`, its plugin design contract, dependency boundaries, and how the current `auth` plugin provides services with minimal intrusion into the host application.
## 1. Overall Role
`app.plugins` is the application-side plugin boundary.
Its purpose is not to implement a generic plugin marketplace. Instead, it provides a clear boundary inside `app` for separable business capabilities, so that a capability can:
1. carry its own domain model, runtime state, and adapters inside the plugin
2. interact with the host application only through a limited set of seams
3. remain replaceable, removable, and extensible over time
The only real plugin currently implemented under this directory is [`auth`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth).
The current direction is not “put all logic into app”. It is:
1. the host application owns unified bootstrap, shared infrastructure, and top-level router assembly
2. each plugin owns its own business contract, persistence definitions, runtime state, and outward-facing adapters
## 2. Plugin Design Contract
### 2.1 A plugin should carry its own implementation
The primary contract visible in the current codebase is:
A plugins own ORM, runtime, domain, and adapters should be implemented inside the plugin itself. Core business behavior should not be scattered into unrelated external modules.
The `auth` plugin already follows that pattern with a fairly complete internal structure:
1. `domain`
- config, errors, JWT, password logic, domain models, service
2. `storage`
- plugin-owned ORM models, repository contracts, and repository implementations
3. `runtime`
- plugin-owned runtime config state
4. `api`
- plugin-owned HTTP router and schemas
5. `security`
- plugin-owned middleware, dependencies, CSRF logic, and LangGraph adapter
6. `authorization`
- plugin-owned permission model, policy resolution, and hooks
7. `injection`
- plugin-owned route-policy loading, injection, and validation
In other words, a plugin should be a self-contained capability module, not a bag of helpers.
### 2.2 The host app should provide shared infrastructure, not plugin internals
The current contract is not that every plugin must be fully infrastructure-independent.
It is:
1. a plugin may reuse the applications shared `engine`, `session_factory`, FastAPI app, and router tree
2. but the plugin must still own its table definitions, repositories, runtime config, and business/auth behavior
This is stated explicitly in [`auth/plugin.toml`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/plugin.toml):
1. `storage.mode = "shared_infrastructure"`
2. the plugin owns its storage definitions and repositories
3. but it reuses the applications shared persistence infrastructure
So the real rule is not “never reuse infrastructure”. The real rule is “do not outsource plugin business semantics to the rest of the app”.
### 2.3 Dependencies should remain one-way
The intended dependency direction in the current design is:
```text
gateway / app bootstrap
-> plugin public adapters
-> plugin domain / storage / runtime
```
Not:
```text
plugin domain
-> depends on app business modules
```
A plugin may depend on:
1. shared persistence infrastructure
2. `app.state` provided by the host application
3. generic framework capabilities such as FastAPI / Starlette
But its core business rules should not depend on unrelated app business modules, otherwise hot-swappability becomes unrealistic.
## 3. The Current auth Plugin Structure
The current `auth` plugin is effectively a self-contained authentication and authorization package with its own models, services, and adapters.
### 3.1 domain
[`auth/domain`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/domain) owns:
1. `config.py`
- auth-related configuration definition and loading
2. `errors.py`
- error codes and response contracts
3. `jwt.py`
- token encoding and decoding
4. `password.py`
- password hashing and verification
5. `models.py`
- auth domain models
6. `service.py`
- `AuthService` as the core business service
`AuthService` depends only on the plugins own `DbUserRepository` plus the shared session factory. The auth business logic is not reimplemented in `gateway`.
### 3.2 storage
[`auth/storage`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/storage) clearly shows the “ORM is owned by the plugin” contract:
1. [`models.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/storage/models.py)
- defines the plugin-owned `users` table model
2. [`contracts.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/storage/contracts.py)
- defines `User`, `UserCreate`, and `UserRepositoryProtocol`
3. [`repositories.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/storage/repositories.py)
- implements `DbUserRepository`
The key point is:
1. the plugin defines its own ORM model
2. the plugin defines its own repository protocol
3. the plugin implements its own repository
4. external code only needs to provide a session or session factory
That is the minimal shared seam the boundary should preserve.
### 3.3 runtime
[`auth/runtime/config_state.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/runtime/config_state.py) keeps plugin-owned runtime config state:
1. `get_auth_config()`
2. `set_auth_config()`
3. `reset_auth_config()`
This matters because runtime state is also part of the plugin boundary. If future plugins need their own caches, state holders, or feature flags, they should follow the same pattern and keep them inside the plugin.
### 3.4 adapters
The `auth` plugin exposes capability through four main adapter groups:
1. `api/router.py`
- HTTP endpoints
2. `security/*`
- middleware, dependencies, request-user resolution, actor-context bridge
3. `authorization/*`
- capabilities, policy evaluators, auth hooks
4. `injection/*`
- route-policy registry, guard injection, startup validation
These adapters all follow the same rule:
1. entry-point behavior is defined inside the plugin
2. the host app only assembles and wires it
## 4. How a Plugin Interacts with the Host App
### 4.1 The top-level router only includes plugin routers
[`app/gateway/router.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/gateway/router.py) simply:
1. imports `app.plugins.auth.api.router`
2. calls `include_router(auth_router)`
That means the host app integrates auth HTTP behavior by assembly, not by duplicating login/register logic in `gateway`.
### 4.2 registrar performs wiring, not takeover
In [`app/gateway/registrar.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/gateway/registrar.py), the host app mainly does this:
1. `app.state.authz_hooks = build_authz_hooks()`
2. loads and validates the route-policy registry
3. calls `install_route_guards(app)`
4. calls `app.add_middleware(CSRFMiddleware)`
5. calls `app.add_middleware(AuthMiddleware)`
So the host app only wires the plugin in:
1. register middleware
2. install route guards
3. expose hooks and registries through `app.state`
The actual auth logic, authz logic, and route-policy semantics still live inside the plugin.
### 4.3 The plugin reuses shared sessions, but still owns business repositories
In [`auth/security/dependencies.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/security/dependencies.py):
1. the plugin reads the shared session factory from `request.app.state.persistence.session_factory`
2. constructs `DbUserRepository` itself
3. constructs `AuthService` itself
This is a good low-intrusion seam:
1. the outside world provides only shared infrastructure handles
2. the plugin decides how to instantiate its internal dependencies
## 5. Hot-Swappability and Low-Intrusion Principles
### 5.1 If a plugin serves other modules, it should minimize intrusion
When a plugin provides services to the rest of the app, the preferred patterns are:
1. expose a router
2. expose middleware or dependencies
3. expose hooks or protocols
4. inject a small number of shared objects through `app.state`
5. use config-driven route policies or capabilities instead of hardcoding checks inside business routes
Patterns to avoid:
1. large plugin-specific branches spread across `gateway`
2. unrelated business modules importing plugin ORM internals and rebuilding plugin logic themselves
3. plugin state being maintained across many global modules
### 5.2 Low-intrusion seams already visible in auth
The current `auth` plugin already uses four important low-intrusion seams:
1. router integration
- `gateway.router` only calls `include_router`
2. middleware integration
- `registrar` only registers `AuthMiddleware` and `CSRFMiddleware`
3. policy injection
- `install_route_guards(app)` appends `Depends(enforce_route_policy)` uniformly to routes
4. hook seam
- `authz_hooks` is exposed via `app.state`, so permission providers and policy builders can be replaced
This structure has three practical benefits:
1. host-app changes stay concentrated in the assembly layer
2. plugin core logic stays concentrated inside the plugin directory
3. swapping implementations does not require editing business routes one by one
### 5.3 Route policy is a key low-intrusion mechanism
[`auth/injection/registry_loader.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/injection/registry_loader.py), [`validation.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/injection/validation.py), and [`route_injector.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/injection/route_injector.py) together form an important contract:
1. route policies live in the plugin-owned `route_policies.yaml`
2. startup validates that policy entries and real routes stay aligned
3. guards are attached by uniform injection instead of manual per-endpoint code
That allows the plugin to:
1. describe which routes are public, which capabilities are required, and which owner policies apply
2. avoid large invasive changes to the host routing layer
3. remain easier to replace or trim down later
## 6. What “ORM and runtime are implemented inside the plugin” Should Mean
That contract should be read as three concrete rules:
1. data models belong to the plugin
- the plugins own tables, Pydantic contracts, repository protocols, and repository implementations stay inside the plugin directory
2. runtime state belongs to the plugin
- plugin-owned config caches, context bridges, and plugin-level hooks stay inside the plugin
3. the outside world exposes infrastructure, not plugin semantics
- for example shared `session_factory`, FastAPI app, and `app.state`
Using `auth` as the example:
1. the `users` table is defined inside the plugin, not in `app.infra`
2. `AuthService` is implemented inside the plugin, not in `gateway`
3. `get_auth_config()` is maintained inside the plugin, not cached elsewhere
4. `AuthMiddleware`, `route_guard`, and `AuthzHooks` are all provided by the plugin itself
This is the structural prerequisite for meaningful pluginization later.
## 7. Current Scope and Non-Goals
At the current stage, the role of `app.plugins` is mainly:
1. to create module boundaries for separable application-side capabilities
2. to let each plugin own its own domain/storage/runtime/adapters
3. to connect plugins to the host app through assembly-oriented seams
The current non-goals are also clear:
1. this is not yet a full generic plugin discovery/installation system
2. plugins are not dynamically enabled or disabled at runtime
3. shared infrastructure is not being duplicated into every plugin
So at this stage, “hot-swappable” should be interpreted more precisely as:
1. plugin boundaries stay as independent as possible
2. integration points stay concentrated in the assembly layer
3. replacing or removing a plugin should mostly affect a small number of places such as `registrar`, router includes, and `app.state` hooks
## 8. Suggested Evolution Rules
If `app.plugins` is going to become a more stable plugin boundary, the codebase should keep following these rules:
1. each plugin directory should keep a `domain` / `storage` / `runtime` / `adapter` split
2. plugin-owned ORM and repositories should not drift into shared business directories
3. when a plugin serves the rest of the app, it should prefer exposing protocols, hooks, routers, and middleware over forcing external code to import internal implementation details
4. seams between a plugin and the host app should stay mostly limited to:
- `router.include_router(...)`
- `app.add_middleware(...)`
- `app.state.*`
- lifespan/bootstrap wiring
5. config-driven integration should be preferred over scattered hardcoded integration
6. startup validation should be preferred over implicit runtime failure
## 9. Summary
The current `app.plugins` contract can be summarized in one sentence:
Each plugin owns its own business implementation, ORM, and runtime; the host application provides shared infrastructure and assembly seams; and services should be integrated through low-intrusion, replaceable boundaries so the system can evolve toward real hot-swappability.
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# app.plugins 设计说明
本文基于当前代码实现,说明 `backend/app/plugins` 的定位、插件设计契约、依赖边界,以及当前 `auth` 插件是如何在尽量少侵入宿主应用的前提下提供服务的。
## 1. 总体定位
`app.plugins` 是应用侧插件边界。它的目标不是做一个通用插件市场,而是在 `app` 这一层给可拆分的业务能力预留清晰边界,使某一类能力可以:
1. 在插件内部自带领域模型、运行时状态和适配器
2. 只通过有限的接缝与宿主应用交互
3. 在未来保持“可替换、可裁剪、可扩展”
当前目录下实际落地的插件是 [`auth`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth)。
从当前实现看,`app.plugins` 的方向不是“所有逻辑都塞进 app”,而是:
1. 宿主应用负责统一启动、共享基础设施和总路由装配
2. 插件负责自己的业务契约、持久化定义、运行时状态和外部适配器
## 2. 插件设计契约
### 2.1 插件内部要自带完整能力
当前代码体现出的首要契约是:
插件自己的 ORM、runtime、domain、adapter,原则上都应由插件内部实现,不要把核心业务依赖散落到外部模块。
`auth` 插件为例,它内部已经自带了完整分层:
1. `domain`
- 配置、错误、JWT、密码、领域模型、服务
2. `storage`
- 插件自己的 ORM 模型、仓储契约和仓储实现
3. `runtime`
- 插件自己的运行时配置状态
4. `api`
- 插件自己的 HTTP router 和 schema
5. `security`
- 插件自己的 middleware、dependency、csrf、LangGraph 适配
6. `authorization`
- 插件自己的权限模型、policy 解析和 hook
7. `injection`
- 插件自己的路由策略注册、注入和校验逻辑
换句话说,插件不是一组零散 helper,而应该是一个自闭合的功能模块。
### 2.2 宿主应用只提供共享基础设施,不承接插件内部逻辑
当前约束不是“插件完全独立进程”,而是:
1. 插件可以复用应用共享的 `engine``session_factory`、FastAPI app、路由树
2. 但插件自己的表结构、仓储、运行时配置、鉴权逻辑,仍然应由插件自己拥有
这一点在 [`auth/plugin.toml`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/plugin.toml) 里写得很明确:
1. `storage.mode = "shared_infrastructure"`
2. 说明插件拥有自己的 storage definitions 和 repositories
3. 但复用应用共享的 persistence infrastructure
所以这里的契约不是“禁止复用基础设施”,而是“不要把插件内部业务实现外包给 app 其他模块”。
### 2.3 依赖方向要单向
按当前实现,比较理想的依赖方向是:
```text
gateway / app bootstrap
-> plugin public adapters
-> plugin domain / storage / runtime
```
而不是:
```text
plugin domain
-> 依赖 app 里的业务模块
```
插件可以使用:
1. 共享持久化基础设施
2. 宿主应用提供的 `app.state`
3. FastAPI / Starlette 等通用框架能力
但不应该把自己的核心业务规则建立在别的业务模块之上,否则后续无法热插拔。
## 3. 当前 auth 插件的实际结构
当前 `auth` 插件可以概括为一套“自带模型、自带服务、自带适配器”的认证授权包。
### 3.1 domain
[`auth/domain`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/domain) 负责:
1. `config.py`
- 认证相关配置定义与加载
2. `errors.py`
- 错误码和错误响应契约
3. `jwt.py`
- token 编解码
4. `password.py`
- 密码哈希和校验
5. `models.py`
- auth 域模型
6. `service.py`
- `AuthService`,作为核心业务服务
`AuthService` 本身只依赖插件内部的 `DbUserRepository` 和共享 session factory,没有把认证逻辑散到 `gateway`
### 3.2 storage
[`auth/storage`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/storage) 明确体现了“ORM 由插件自己内部实现”的契约:
1. [`models.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/storage/models.py)
- 定义插件自己的 `users` 表模型
2. [`contracts.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/storage/contracts.py)
- 定义 `User``UserCreate``UserRepositoryProtocol`
3. [`repositories.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/storage/repositories.py)
- 实现 `DbUserRepository`
这里的关键点是:
1. 插件自己定义 ORM model
2. 插件自己定义 repository protocol
3. 插件自己实现 repository
4. 外部只需要给它 session / session_factory
这就是插件边界应该保持的最小共享面。
### 3.3 runtime
[`auth/runtime/config_state.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/runtime/config_state.py) 维护插件自己的 runtime config state
1. `get_auth_config()`
2. `set_auth_config()`
3. `reset_auth_config()`
这说明运行时配置状态也属于插件内部,而不是由外部模块代持。后续如果别的插件需要自己的缓存、状态机、feature flag,也应沿这个模式内聚在插件内部。
### 3.4 adapters
`auth` 插件对外暴露能力主要通过四类 adapter:
1. `api/router.py`
- HTTP 接口
2. `security/*`
- middleware、dependency、request user 解析、actor context bridge
3. `authorization/*`
- capability、policy evaluator、auth hooks
4. `injection/*`
- route policy registry、guard 注入、启动校验
这类 adapter 的共同特征是:
1. 入口能力在插件内定义
2. 宿主应用只负责调用和装配
## 4. 插件如何与宿主应用交互
### 4.1 总路由只 include,不重写插件逻辑
[`app/gateway/router.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/gateway/router.py) 只是:
1. 引入 `app.plugins.auth.api.router`
2. `include_router(auth_router)`
这说明宿主应用对 auth HTTP 能力的接入是装配式的,而不是在 `gateway` 里重写一套登录/注册逻辑。
### 4.2 registrar 负责启动装配,不负责接管插件实现
[`app/gateway/registrar.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/gateway/registrar.py) 里,宿主应用做的事情主要是:
1. `app.state.authz_hooks = build_authz_hooks()`
2. 加载并校验 route policy registry
3. `install_route_guards(app)`
4. `app.add_middleware(CSRFMiddleware)`
5. `app.add_middleware(AuthMiddleware)`
也就是说,宿主应用只负责把插件接进来:
1. 注册 middleware
2. 安装 route guard
3. 把 hooks 和 registry 放到 `app.state`
真正的鉴权逻辑、认证逻辑、路由策略语义仍然在插件内部。
### 4.3 共享会话工厂,但业务仓储仍归插件
在 [`auth/security/dependencies.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/security/dependencies.py) 中:
1. 插件从 `request.app.state.persistence.session_factory` 取得共享 session factory
2. 然后自己构造 `DbUserRepository`
3. 再自己构造 `AuthService`
这就是一个很典型的低侵入接缝:
1. 外部只提供共享基础设施句柄
2. 插件自己决定如何实例化内部依赖
## 5. 热插拔与低侵入原则
### 5.1 如果要向其他模块提供服务,应尽量减少入侵
插件给其他模块提供服务时,优先选下面这些方式:
1. 暴露 router
2. 暴露 middleware / dependency
3. 暴露 hook 或 protocol
4. 通过 `app.state` 注入少量共享对象
5. 使用配置驱动的 route policy / capability,而不是把判断逻辑硬编码进业务路由
不推荐的方式是:
1.`gateway` 大量写插件特定分支
2. 让别的业务模块直接 import 插件内部 ORM 细节后自行拼逻辑
3. 把插件状态散落到全局多个模块中共同维护
### 5.2 当前 auth 插件已经体现出的低侵入点
当前 `auth` 插件的低侵入接入点主要有四个:
1. 路由接入
- `gateway.router``include_router`
2. 中间件接入
- `registrar` 只注册 `AuthMiddleware` / `CSRFMiddleware`
3. 策略注入
- `install_route_guards(app)` 给路由统一追加 `Depends(enforce_route_policy)`
4. hook 接缝
- `authz_hooks` 通过 `app.state` 暴露,策略构建和权限提供器可以替换
这套结构的好处是:
1. 宿主应用改动面集中在装配层
2. 插件核心实现集中在插件目录内部
3. 替换实现时,不需要在业务路由里逐个修改
### 5.3 route policy 是低侵入的关键机制
[`auth/injection/registry_loader.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/injection/registry_loader.py)、[`validation.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/injection/validation.py) 和 [`route_injector.py`](/Users/rayhpeng/workspace/open-source/deer-flow/backend/app/plugins/auth/injection/route_injector.py) 共同形成了一套很关键的契约:
1. 路由策略写在插件自己的 `route_policies.yaml`
2. 启动时会校验策略表和真实路由是否一致
3. guard 通过统一注入附着到路由,而不是每个 endpoint 手写一遍
这使得插件能够:
1. 用配置描述“哪些路由公开、需要哪些 capability、需要哪些 owner policy”
2. 避免对宿主路由层做大规模侵入
3. 在未来更容易替换或裁剪某个插件
## 6. 关于“ORM、runtime 都由自己内部实现”的具体说明
这条契约建议明确理解为以下三点:
1. 数据模型归插件
- 插件自己的表、Pydantic contract、repository protocol、repository implementation 都放在插件目录内
2. 运行时状态归插件
- 插件自己的配置缓存、上下文桥、插件级 hooks 都在插件内部维护
3. 外部只暴露基础设施,不接管插件语义
- 例如共享 `session_factory`、FastAPI app、`app.state`
`auth` 举例:
1. `users` 表在插件里定义,不在 `app.infra` 定义
2. `AuthService` 在插件里实现,不在 `gateway` 实现
3. `get_auth_config()` 在插件里维护,不由别的模块缓存
4. `AuthMiddleware``route_guard``AuthzHooks` 都由插件自己提供
这是后续做插件化时最重要的结构前提。
## 7. 当前作用范围与非目标
就当前实现而言,`app.plugins` 的作用范围主要是:
1. 为应用侧可拆分能力建立模块边界
2. 让插件拥有自己的 domain/storage/runtime/adapter
3. 通过装配式接缝接入宿主应用
当前非目标也很明确:
1. 还不是一个完整的通用插件发现/安装系统
2. 还没有做到运行时动态启停插件
3. 也不是把共享基础设施完全复制进每个插件
所以“热插拔”在当前阶段更准确的含义是:
1. 插件边界尽量独立
2. 接入点尽量集中在装配层
3. 替换或移除时,改动尽量局限在 `registrar``router include``app.state` hooks 这些少数位置
## 8. 后续演进建议
如果后续要继续把 `app.plugins` 做成更稳定的插件边界,建议保持这些规则:
1. 每个插件目录内部都保持 `domain` / `storage` / `runtime` / `adapter` 分层
2. 插件自己的 ORM 与 repository 不要下沉到共享业务目录
3. 插件向外提供服务时优先暴露 protocol、hook、router、middleware,而不是要求外部 import 内部实现细节
4. 插件与宿主应用的接缝尽量限制在:
- `router.include_router(...)`
- `app.add_middleware(...)`
- `app.state.*`
- 生命周期装配
5. 配置驱动优先于散落的硬编码接入
6. 启动期校验优先于运行时隐式失败
## 9. 设计总结
可以把当前 `app.plugins` 的契约总结为一句话:
插件内部拥有自己的业务实现、ORM 和 runtime;宿主应用只提供共享基础设施和装配接缝;对外服务时尽量通过低侵入、可替换的方式接入,以便后续做到真正的热插拔和边界演进。
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"""Application plugin packages."""
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# Auth Plugin
This package is the future Level 2 auth plugin boundary for DeerFlow.
Scope:
- Auth domain logic: config, errors, models, JWT, password hashing, service
- Auth adapters: HTTP router, FastAPI dependencies, middleware, LangGraph adapter
- Auth storage: user/account models and repositories
Non-scope:
- Shared app/container bootstrap
- Shared persistence engine/session lifecycle
- Generic plugin discovery/registration framework
Target architecture:
- The plugin owns its storage definitions and business logic
- The plugin reuses the application's shared persistence infrastructure
- The gateway only assembles the plugin instead of owning auth logic directly
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"""Auth plugin package.
Level 2 plugin goal:
- Own auth domain logic
- Own auth adapters (router, dependencies, middleware, LangGraph adapter)
- Own auth storage definitions
- Reuse the application's shared persistence/session infrastructure
"""
from app.plugins.auth.authorization.hooks import build_authz_hooks
__all__ = [
"build_authz_hooks",
]
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@@ -1,17 +0,0 @@
"""HTTP API layer for the auth plugin."""
from app.plugins.auth.api.router import (
ChangePasswordRequest,
LoginResponse,
MessageResponse,
RegisterRequest,
router,
)
__all__ = [
"ChangePasswordRequest",
"LoginResponse",
"MessageResponse",
"RegisterRequest",
"router",
]
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"""Authentication endpoints for the auth plugin."""
from fastapi import APIRouter, Depends, HTTPException, Request, Response, status
from fastapi.security import OAuth2PasswordRequestForm
from app.plugins.auth.api.schemas import (
ChangePasswordRequest,
InitializeAdminRequest,
LoginResponse,
MessageResponse,
RegisterRequest,
_check_rate_limit,
_get_client_ip,
_login_attempts,
_record_login_failure,
_record_login_success,
)
from app.plugins.auth.domain.errors import AuthErrorResponse
from app.plugins.auth.domain.jwt import create_access_token
from app.plugins.auth.domain.models import UserResponse
from app.plugins.auth.domain.service import AuthServiceError
from app.plugins.auth.runtime.config_state import get_auth_config
from app.plugins.auth.security.csrf import is_secure_request
from app.plugins.auth.security.dependencies import CurrentAuthService, get_current_user_from_request
router = APIRouter(prefix="/api/v1/auth", tags=["auth"])
def _set_session_cookie(response: Response, token: str, request: Request) -> None:
config = get_auth_config()
is_https = is_secure_request(request)
response.set_cookie(
key="access_token",
value=token,
httponly=True,
secure=is_https,
samesite="lax",
max_age=config.token_expiry_days * 24 * 3600 if is_https else None,
)
@router.post("/login/local", response_model=LoginResponse)
async def login_local(
request: Request,
response: Response,
auth_service: CurrentAuthService,
form_data: OAuth2PasswordRequestForm = Depends(),
):
client_ip = _get_client_ip(request)
_check_rate_limit(client_ip)
try:
user = await auth_service.login_local(form_data.username, form_data.password)
except AuthServiceError as exc:
_record_login_failure(client_ip)
raise HTTPException(
status_code=exc.status_code,
detail=AuthErrorResponse(code=exc.code, message=exc.message).model_dump(),
) from exc
_record_login_success(client_ip)
token = create_access_token(str(user.id), token_version=user.token_version)
_set_session_cookie(response, token, request)
return LoginResponse(
expires_in=get_auth_config().token_expiry_days * 24 * 3600,
needs_setup=user.needs_setup,
)
@router.post("/register", response_model=UserResponse, status_code=status.HTTP_201_CREATED)
async def register(request: Request, response: Response, body: RegisterRequest, auth_service: CurrentAuthService):
try:
user = await auth_service.register(body.email, body.password)
except AuthServiceError as exc:
raise HTTPException(
status_code=exc.status_code,
detail=AuthErrorResponse(code=exc.code, message=exc.message).model_dump(),
) from exc
token = create_access_token(str(user.id), token_version=user.token_version)
_set_session_cookie(response, token, request)
return UserResponse(id=str(user.id), email=user.email, system_role=user.system_role)
@router.post("/logout", response_model=MessageResponse)
async def logout(request: Request, response: Response):
response.delete_cookie(key="access_token", secure=is_secure_request(request), samesite="lax")
return MessageResponse(message="Successfully logged out")
@router.post("/change-password", response_model=MessageResponse)
async def change_password(
request: Request,
response: Response,
body: ChangePasswordRequest,
auth_service: CurrentAuthService,
):
user = await get_current_user_from_request(request)
try:
user = await auth_service.change_password(
user,
current_password=body.current_password,
new_password=body.new_password,
new_email=body.new_email,
)
except AuthServiceError as exc:
raise HTTPException(
status_code=exc.status_code,
detail=AuthErrorResponse(code=exc.code, message=exc.message).model_dump(),
) from exc
token = create_access_token(str(user.id), token_version=user.token_version)
_set_session_cookie(response, token, request)
return MessageResponse(message="Password changed successfully")
@router.get("/me", response_model=UserResponse)
async def get_me(request: Request):
user = await get_current_user_from_request(request)
return UserResponse(id=str(user.id), email=user.email, system_role=user.system_role, needs_setup=user.needs_setup)
@router.get("/setup-status")
async def setup_status(auth_service: CurrentAuthService):
return {"needs_setup": await auth_service.get_setup_status()}
@router.post("/initialize", response_model=UserResponse, status_code=status.HTTP_201_CREATED)
async def initialize_admin(
request: Request,
response: Response,
body: InitializeAdminRequest,
auth_service: CurrentAuthService,
):
try:
user = await auth_service.initialize_admin(body.email, body.password)
except AuthServiceError as exc:
raise HTTPException(
status_code=exc.status_code,
detail=AuthErrorResponse(code=exc.code, message=exc.message).model_dump(),
) from exc
token = create_access_token(str(user.id), token_version=user.token_version)
_set_session_cookie(response, token, request)
return UserResponse(id=str(user.id), email=user.email, system_role=user.system_role)
@router.get("/oauth/{provider}")
async def oauth_login(provider: str):
if provider not in ["github", "google"]:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=f"Unsupported OAuth provider: {provider}")
raise HTTPException(status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="OAuth login not yet implemented")
@router.get("/callback/{provider}")
async def oauth_callback(provider: str, code: str, state: str):
raise HTTPException(status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="OAuth callback not yet implemented")
__all__ = [
"ChangePasswordRequest",
"InitializeAdminRequest",
"LoginResponse",
"MessageResponse",
"RegisterRequest",
"_check_rate_limit",
"_get_client_ip",
"_login_attempts",
"_record_login_failure",
"_record_login_success",
"router",
]
-176
View File
@@ -1,176 +0,0 @@
"""HTTP schemas and request helpers for the auth plugin API."""
from __future__ import annotations
import os
import time
from ipaddress import ip_address, ip_network
from fastapi import HTTPException, Request
from pydantic import BaseModel, EmailStr, Field, field_validator
_COMMON_PASSWORDS: frozenset[str] = frozenset(
{
"password",
"password1",
"password12",
"password123",
"password1234",
"12345678",
"123456789",
"1234567890",
"qwerty12",
"qwertyui",
"qwerty123",
"abc12345",
"abcd1234",
"iloveyou",
"letmein1",
"welcome1",
"welcome123",
"admin123",
"administrator",
"passw0rd",
"p@ssw0rd",
"monkey12",
"trustno1",
"sunshine",
"princess",
"football",
"baseball",
"superman",
"batman123",
"starwars",
"dragon123",
"master123",
"shadow12",
"michael1",
"jennifer",
"computer",
}
)
_MAX_LOGIN_ATTEMPTS = 5
_LOCKOUT_SECONDS = 300
_MAX_TRACKED_IPS = 10000
_login_attempts: dict[str, tuple[int, float]] = {}
class LoginResponse(BaseModel):
expires_in: int
needs_setup: bool = False
class RegisterRequest(BaseModel):
email: EmailStr
password: str = Field(..., min_length=8)
_strong_password = field_validator("password")(classmethod(lambda cls, v: _validate_strong_password(v)))
class ChangePasswordRequest(BaseModel):
current_password: str
new_password: str = Field(..., min_length=8)
new_email: EmailStr | None = None
_strong_password = field_validator("new_password")(classmethod(lambda cls, v: _validate_strong_password(v)))
class MessageResponse(BaseModel):
message: str
class InitializeAdminRequest(BaseModel):
email: EmailStr
password: str = Field(..., min_length=8)
_strong_password = field_validator("password")(classmethod(lambda cls, v: _validate_strong_password(v)))
def _password_is_common(password: str) -> bool:
return password.lower() in _COMMON_PASSWORDS
def _validate_strong_password(value: str) -> str:
if _password_is_common(value):
raise ValueError("Password is too common; choose a stronger password.")
return value
def _trusted_proxies() -> list:
raw = os.getenv("AUTH_TRUSTED_PROXIES", "").strip()
if not raw:
return []
nets = []
for entry in raw.split(","):
entry = entry.strip()
if not entry:
continue
try:
nets.append(ip_network(entry, strict=False))
except ValueError:
pass
return nets
def _get_client_ip(request: Request) -> str:
peer_host = request.client.host if request.client else None
trusted = _trusted_proxies()
if trusted and peer_host:
try:
peer_ip = ip_address(peer_host)
if any(peer_ip in net for net in trusted):
real_ip = request.headers.get("x-real-ip", "").strip()
if real_ip:
return real_ip
except ValueError:
pass
return peer_host or "unknown"
def _check_rate_limit(ip: str) -> None:
record = _login_attempts.get(ip)
if record is None:
return
fail_count, lock_until = record
if fail_count >= _MAX_LOGIN_ATTEMPTS:
if time.time() < lock_until:
raise HTTPException(status_code=429, detail="Too many login attempts. Try again later.")
del _login_attempts[ip]
def _record_login_failure(ip: str) -> None:
if len(_login_attempts) >= _MAX_TRACKED_IPS:
now = time.time()
expired = [k for k, (c, t) in _login_attempts.items() if c >= _MAX_LOGIN_ATTEMPTS and now >= t]
for key in expired:
del _login_attempts[key]
if len(_login_attempts) >= _MAX_TRACKED_IPS:
by_time = sorted(_login_attempts.items(), key=lambda kv: kv[1][1])
for key, _ in by_time[: len(by_time) // 2]:
del _login_attempts[key]
record = _login_attempts.get(ip)
if record is None:
_login_attempts[ip] = (1, 0.0)
else:
new_count = record[0] + 1
lock_until = time.time() + _LOCKOUT_SECONDS if new_count >= _MAX_LOGIN_ATTEMPTS else 0.0
_login_attempts[ip] = (new_count, lock_until)
def _record_login_success(ip: str) -> None:
_login_attempts.pop(ip, None)
__all__ = [
"ChangePasswordRequest",
"InitializeAdminRequest",
"LoginResponse",
"MessageResponse",
"RegisterRequest",
"_check_rate_limit",
"_get_client_ip",
"_login_attempts",
"_record_login_failure",
"_record_login_success",
]
@@ -1,31 +0,0 @@
"""Authorization layer for the auth plugin."""
from app.plugins.auth.authorization.authentication import get_auth_context
from app.plugins.auth.authorization.hooks import (
AuthzHooks,
build_authz_hooks,
build_permission_provider,
build_policy_chain_builder,
get_authz_hooks,
get_default_authz_hooks,
)
from app.plugins.auth.authorization.types import (
AuthContext,
Permissions,
ALL_PERMISSIONS,
)
_ALL_PERMISSIONS = ALL_PERMISSIONS
__all__ = [
"AuthContext",
"AuthzHooks",
"Permissions",
"_ALL_PERMISSIONS",
"build_authz_hooks",
"build_permission_provider",
"build_policy_chain_builder",
"get_auth_context",
"get_authz_hooks",
"get_default_authz_hooks",
]
@@ -1,43 +0,0 @@
"""Authentication helpers used by auth-plugin authorization decorators."""
from __future__ import annotations
from fastapi import Request
from app.plugins.auth.authorization.providers import PermissionProvider, default_permission_provider
from app.plugins.auth.authorization.types import AuthContext
def get_auth_context(request: Request) -> AuthContext | None:
"""Get AuthContext, preferring Starlette-style request.auth."""
auth = request.scope.get("auth")
if isinstance(auth, AuthContext):
return auth
return getattr(request.state, "auth", None)
def set_auth_context(request: Request, auth_context: AuthContext) -> AuthContext:
"""Persist AuthContext on the standard request surfaces."""
request.scope["auth"] = auth_context
request.state.auth = auth_context
return auth_context
async def authenticate_request(
request: Request,
*,
permission_provider: PermissionProvider = default_permission_provider,
) -> AuthContext:
"""Authenticate request and build AuthContext."""
from app.plugins.auth.security.dependencies import get_optional_user_from_request
user = await get_optional_user_from_request(request)
if user is None:
return AuthContext(user=None, permissions=[])
return AuthContext(user=user, permissions=permission_provider(user))
__all__ = ["authenticate_request", "get_auth_context", "set_auth_context"]
@@ -1,84 +0,0 @@
"""Authorization requirement and policy evaluation helpers."""
from __future__ import annotations
from collections.abc import Awaitable, Callable, Mapping
from dataclasses import dataclass
from typing import Any
from fastapi import HTTPException, Request
from app.plugins.auth.authorization.policies import require_thread_owner
from app.plugins.auth.authorization.types import AuthContext
@dataclass(frozen=True)
class PermissionRequirement:
"""Authorization requirement for a single route action."""
resource: str
action: str
owner_check: bool = False
require_existing: bool = False
@property
def permission(self) -> str:
return f"{self.resource}:{self.action}"
PolicyEvaluator = Callable[[Request, AuthContext, PermissionRequirement, Mapping[str, Any]], Awaitable[None]]
def ensure_authenticated(auth: AuthContext) -> None:
if not auth.is_authenticated:
raise HTTPException(status_code=401, detail="Authentication required")
def ensure_capability(auth: AuthContext, requirement: PermissionRequirement) -> None:
if not auth.has_permission(requirement.resource, requirement.action):
raise HTTPException(status_code=403, detail=f"Permission denied: {requirement.permission}")
async def evaluate_owner_policy(
request: Request,
auth: AuthContext,
requirement: PermissionRequirement,
route_params: Mapping[str, Any],
) -> None:
if not requirement.owner_check:
return
thread_id = route_params.get("thread_id")
if thread_id is None:
raise ValueError("require_permission with owner_check=True requires 'thread_id' parameter")
await require_thread_owner(
request,
auth,
thread_id=thread_id,
require_existing=requirement.require_existing,
)
async def evaluate_requirement(
request: Request,
auth: AuthContext,
requirement: PermissionRequirement,
route_params: Mapping[str, Any],
*,
policy_evaluators: tuple[PolicyEvaluator, ...],
) -> None:
ensure_authenticated(auth)
ensure_capability(auth, requirement)
for evaluator in policy_evaluators:
await evaluator(request, auth, requirement, route_params)
__all__ = [
"PermissionRequirement",
"PolicyEvaluator",
"ensure_authenticated",
"ensure_capability",
"evaluate_owner_policy",
"evaluate_requirement",
]
@@ -1,62 +0,0 @@
"""Auth-plugin authz extension hooks."""
from __future__ import annotations
from dataclasses import dataclass
from typing import Any
from fastapi import Request
from app.plugins.auth.authorization.providers import PermissionProvider, default_permission_provider
from app.plugins.auth.authorization.registry import PolicyChainBuilder, build_default_policy_evaluators
@dataclass(frozen=True)
class AuthzHooks:
"""Extension hooks for permission and policy resolution."""
permission_provider: PermissionProvider = default_permission_provider
policy_chain_builder: PolicyChainBuilder = build_default_policy_evaluators
DEFAULT_AUTHZ_HOOKS = AuthzHooks()
def get_default_authz_hooks() -> AuthzHooks:
return DEFAULT_AUTHZ_HOOKS
def get_authz_hooks(request: Request | Any | None = None) -> AuthzHooks:
if request is not None:
app = getattr(request, "app", None)
state = getattr(app, "state", None)
hooks = getattr(state, "authz_hooks", None)
if isinstance(hooks, AuthzHooks):
return hooks
return DEFAULT_AUTHZ_HOOKS
def build_permission_provider() -> PermissionProvider:
return default_permission_provider
def build_policy_chain_builder() -> PolicyChainBuilder:
return build_default_policy_evaluators
def build_authz_hooks() -> AuthzHooks:
return AuthzHooks(
permission_provider=build_permission_provider(),
policy_chain_builder=build_policy_chain_builder(),
)
__all__ = [
"AuthzHooks",
"DEFAULT_AUTHZ_HOOKS",
"build_authz_hooks",
"build_permission_provider",
"build_policy_chain_builder",
"get_authz_hooks",
"get_default_authz_hooks",
]
@@ -1,101 +0,0 @@
"""Authorization policies for resource ownership and access checks."""
from __future__ import annotations
from typing import Any
from fastapi import HTTPException, Request
from app.plugins.auth.authorization.types import AuthContext
def _get_thread_owner_id(thread_meta: Any) -> str | None:
owner_id = getattr(thread_meta, "user_id", None)
if owner_id is not None:
return str(owner_id)
metadata = getattr(thread_meta, "metadata", None) or {}
metadata_owner_id = metadata.get("user_id")
if metadata_owner_id is not None:
return str(metadata_owner_id)
return None
async def _thread_exists_via_legacy_sources(request: Request, auth: AuthContext, *, thread_id: str) -> bool:
from app.gateway.dependencies.repositories import get_run_repository
principal_id = auth.principal_id
run_store = get_run_repository(request)
runs = await run_store.list_by_thread(
thread_id,
limit=1,
user_id=principal_id,
)
if runs:
return True
checkpointer = getattr(request.app.state, "checkpointer", None)
if checkpointer is None:
return False
checkpoint_tuple = await checkpointer.aget_tuple(
{"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
)
return checkpoint_tuple is not None
async def require_thread_owner(
request: Request,
auth: AuthContext,
*,
thread_id: str,
require_existing: bool,
) -> None:
"""Ensure the current user owns the thread referenced by ``thread_id``."""
from app.gateway.dependencies.repositories import get_thread_meta_repository
thread_repo = get_thread_meta_repository(request)
thread_meta = await thread_repo.get_thread_meta(thread_id)
if thread_meta is None:
allowed = not require_existing
if not allowed:
allowed = await _thread_exists_via_legacy_sources(request, auth, thread_id=thread_id)
else:
owner_id = _get_thread_owner_id(thread_meta)
allowed = owner_id in (None, str(auth.user.id))
if not allowed:
raise HTTPException(
status_code=404,
detail=f"Thread {thread_id} not found",
)
async def require_run_owner(
request: Request,
auth: AuthContext,
*,
thread_id: str,
run_id: str,
require_existing: bool,
) -> None:
"""Ensure the current user owns the run referenced by ``run_id``."""
from app.gateway.dependencies import get_run_repository
run_store = get_run_repository(request)
run = await run_store.get(run_id)
if run is None:
allowed = not require_existing
else:
allowed = run.get("thread_id") == thread_id
if not allowed:
raise HTTPException(
status_code=404,
detail=f"Run {run_id} not found",
)
__all__ = ["require_run_owner", "require_thread_owner"]
@@ -1,18 +0,0 @@
"""Default permission provider hooks for auth-plugin authorization."""
from __future__ import annotations
from collections.abc import Callable
from app.plugins.auth.authorization.types import ALL_PERMISSIONS
PermissionProvider = Callable[[object], list[str]]
def default_permission_provider(user: object) -> list[str]:
"""Return the current static permission set for an authenticated user."""
return list(ALL_PERMISSIONS)
__all__ = ["PermissionProvider", "default_permission_provider"]

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