security(auth): wire @require_permission(owner_check=True) on isolation routes

Apply the require_permission decorator to all 28 routes that take a
{thread_id} path parameter. Combined with the strict middleware
(previous commit), this gives the double-layer protection that
AUTH_TEST_PLAN test 7.5.9 documents:

  Layer 1 (AuthMiddleware): cookie + JWT validation, rejects junk
                            cookies and stamps request.state.user
  Layer 2 (@require_permission with owner_check=True): per-resource
                            ownership verification via
                            ThreadMetaStore.check_access — returns
                            404 if a different user owns the thread

The decorator's owner_check branch is rewritten to use the SQL
thread_meta_repo (the 2.0-rc persistence layer) instead of the
LangGraph store path that PR #1728 used (_store_get / get_store
in routers/threads.py). The inject_record convenience is dropped
— no caller in 2.0 needs the LangGraph blob, and the SQL repo has
a different shape.

Routes decorated (28 total):
- threads.py: delete, patch, get, get-state, post-state, post-history
- thread_runs.py: post-runs, post-runs-stream, post-runs-wait,
  list_runs, get_run, cancel_run, join_run, stream_existing_run,
  list_thread_messages, list_run_messages, list_run_events,
  thread_token_usage
- feedback.py: create, list, stats, delete
- uploads.py: upload (added Request param), list, delete
- artifacts.py: get_artifact
- suggestions.py: generate (renamed body parameter to avoid
  conflict with FastAPI Request)

Test fixes:
- test_suggestions_router.py: bypass the decorator via __wrapped__
  (the unit tests cover parsing logic, not auth — no point spinning
  up a thread_meta_repo just to test JSON unwrapping)
- test_auth_middleware.py 4 fake-cookie tests: already updated in
  the previous commit (745bf432)

Tests: 293 passed (auth + persistence + isolation + suggestions)
Lint: clean

.agent/skills/smoke-test/SKILL.md

@@ -1,181 +0,0 @@
----
-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

.agent/skills/smoke-test/references/SOP.md

@@ -1,452 +0,0 @@
-# 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.

.agent/skills/smoke-test/references/troubleshooting.md

@@ -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

.agent/skills/smoke-test/scripts/check_docker.sh

@@ -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 "=========================================="

.agent/skills/smoke-test/scripts/check_local_env.sh

@@ -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

.agent/skills/smoke-test/scripts/deploy_docker.sh

@@ -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"

.agent/skills/smoke-test/scripts/deploy_local.sh

@@ -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"

.agent/skills/smoke-test/scripts/frontend_check.sh

@@ -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

.agent/skills/smoke-test/scripts/health_check.sh

@@ -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

.agent/skills/smoke-test/scripts/pull_code.sh

@@ -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 "=========================================="

.agent/skills/smoke-test/templates/report.docker.template.md

@@ -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}}*

.agent/skills/smoke-test/templates/report.local.template.md

@@ -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}}*

CODE_OF_CONDUCT.md

@@ -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.

CONTRIBUTING.md

@@ -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:

Makefile

@@ -1,25 +1,19 @@
 # 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-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
 
 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"
@@ -50,18 +44,11 @@ help:
 	@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:
@@ -119,46 +106,78 @@ setup-sandbox:
 # Start all services in development mode (with hot-reloading)
 dev:
 	@$(PYTHON) ./scripts/check.py
-	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev
+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 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 --gateway
+else
+	@./scripts/serve.sh --dev --gateway
+endif
 
 # Start all services in production mode (with optimizations)
 start:
 	@$(PYTHON) ./scripts/check.py
-	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod
+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 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 --gateway
+else
+	@./scripts/serve.sh --prod --gateway
+endif
 
 # Start all services in daemon mode (background)
 dev-daemon:
 	@$(PYTHON) ./scripts/check.py
-	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --daemon
+ifeq ($(OS),Windows_NT)
+	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --dev --daemon
+else
+	@./scripts/serve.sh --dev --daemon
+endif
 
 # Start daemon + Gateway mode (experimental)
 dev-daemon-pro:
 	@$(PYTHON) ./scripts/check.py
-	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --dev --gateway --daemon
+ifeq ($(OS),Windows_NT)
+	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --dev --gateway --daemon
+else
+	@./scripts/serve.sh --dev --gateway --daemon
+endif
 
 # Start prod services in daemon mode (background)
 start-daemon:
 	@$(PYTHON) ./scripts/check.py
-	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --daemon
+ifeq ($(OS),Windows_NT)
+	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --prod --daemon
+else
+	@./scripts/serve.sh --prod --daemon
+endif
 
 # Start prod daemon + Gateway mode (experimental)
 start-daemon-pro:
 	@$(PYTHON) ./scripts/check.py
-	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --prod --gateway --daemon
+ifeq ($(OS),Windows_NT)
+	@call scripts\run-with-git-bash.cmd ./scripts/serve.sh --prod --gateway --daemon
+else
+	@./scripts/serve.sh --prod --gateway --daemon
+endif
 
 # Stop all services
 stop:
-	@$(RUN_WITH_GIT_BASH) ./scripts/serve.sh --stop
+	@./scripts/serve.sh --stop
 
 # Clean up
 clean: stop
@@ -174,29 +193,29 @@ 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
+	@./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 --gateway
 
 # 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 +223,12 @@ docker-logs-gateway:
 
 # Build and start production services
 up:
-	@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh
+	@./scripts/deploy.sh
 
 # Build and start production services in Gateway mode
 up-pro:
-	@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh --gateway
+	@./scripts/deploy.sh --gateway
 
 # Stop and remove production containers
 down:
-	@$(RUN_WITH_GIT_BASH) ./scripts/deploy.sh down
+	@./scripts/deploy.sh down

README.md

@@ -53,7 +53,6 @@ DeerFlow has newly integrated the intelligent search and crawling toolset indepe
   - [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)
@@ -104,38 +103,35 @@ 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
@@ -185,39 +181,50 @@ 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):
@@ -254,7 +261,7 @@ 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.
+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`).
 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`.
 
 1. **Check prerequisites**:
@@ -368,7 +375,6 @@ 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`:**
@@ -413,19 +419,6 @@ 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
@@ -459,10 +452,6 @@ SLACK_APP_TOKEN=xapp-...
 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
@@ -488,14 +477,6 @@ 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`.

README_zh.md

@@ -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）：

backend/CLAUDE.md

@@ -158,7 +158,7 @@ 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 +216,6 @@ 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 +229,7 @@ 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"`
 
@@ -272,7 +269,7 @@ 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/`)
@@ -341,27 +338,18 @@ 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 +357,7 @@ 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)
@@ -407,16 +395,14 @@ 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):
 

backend/Dockerfile

@@ -88,4 +88,4 @@ COPY --from=builder /app/backend ./backend
 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"]

backend/app/channels/feishu.py

@@ -13,7 +13,6 @@ 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.user_context import get_effective_user_id
 from deerflow.sandbox.sandbox_provider import get_sandbox_provider
 
 logger = logging.getLogger(__name__)
@@ -345,9 +344,8 @@ class FeishuChannel(Channel):
             return f"Failed to obtain the [{type}]"
 
         paths = get_paths()
-        user_id = get_effective_user_id()
-        paths.ensure_thread_dirs(thread_id, user_id=user_id)
-        uploads_dir = paths.sandbox_uploads_dir(thread_id, user_id=user_id).resolve()
+        paths.ensure_thread_dirs(thread_id)
+        uploads_dir = paths.sandbox_uploads_dir(thread_id).resolve()
 
         ext = "png" if type == "image" else "bin"
         raw_filename = getattr(response, "file_name", "") or f"feishu_{file_key[-12:]}.{ext}"

backend/app/channels/manager.py

@@ -8,7 +8,6 @@ import mimetypes
 import re
 import time
 from collections.abc import Awaitable, Callable, Mapping
-from pathlib import Path
 from typing import Any
 
 import httpx
@@ -17,7 +16,6 @@ from langgraph_sdk.errors import ConflictError
 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.user_context import get_effective_user_id
 
 logger = logging.getLogger(__name__)
 
@@ -39,7 +37,6 @@ CHANNEL_CAPABILITIES = {
     "feishu": {"supports_streaming": True},
     "slack": {"supports_streaming": False},
     "telegram": {"supports_streaming": False},
-    "wechat": {"supports_streaming": False},
     "wecom": {"supports_streaming": True},
 }
 
@@ -81,24 +78,7 @@ async def _read_wecom_inbound_file(file_info: dict[str, Any], client: httpx.Asyn
     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):
@@ -342,15 +322,14 @@ def _resolve_attachments(thread_id: str, artifacts: list[str]) -> list[ResolvedA
 
     attachments: list[ResolvedAttachment] = []
     paths = get_paths()
-    user_id = get_effective_user_id()
-    outputs_dir = paths.sandbox_outputs_dir(thread_id, user_id=user_id).resolve()
+    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, user_id=user_id)
+            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:

backend/app/channels/service.py

@@ -18,7 +18,6 @@ _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",
 }
 

backend/app/gateway/app.py

@@ -2,6 +2,7 @@ import logging
 import os
 from collections.abc import AsyncGenerator
 from contextlib import asynccontextmanager
+from datetime import UTC
 
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
@@ -40,60 +41,75 @@ logger = logging.getLogger(__name__)
 
 
 async def _ensure_admin_user(app: FastAPI) -> None:
-    """Startup hook: handle first boot and migrate orphan threads otherwise.
+    """Auto-create the admin user on first boot if no users exist.
 
     After admin creation, migrate orphan threads from the LangGraph
-    store (metadata.user_id unset) to the admin account. This is the
+    store (metadata.owner_id unset) to the admin account. This is the
     "no-auth → with-auth" upgrade path: users who ran DeerFlow without
     authentication have existing LangGraph thread data that needs an
     owner assigned.
-        First boot (no admin exists):
-            - Does NOT create any user accounts automatically.
-            - The operator must visit ``/setup`` to create the first admin.
 
-    Subsequent boots (admin already exists):
-      - Runs the one-time "no-auth → with-auth" orphan thread migration for
-        existing LangGraph thread metadata that has no owner_id.
-
-    No SQL persistence migration is needed: the four user_id columns
+    No SQL persistence migration is needed: the four owner_id columns
     (threads_meta, runs, run_events, feedback) only come into existence
     alongside the auth module via create_all, so freshly created tables
-    never contain NULL-owner rows.
+    never contain NULL-owner rows. "Existing persistence DB + new auth"
+    is not a supported upgrade path — fresh install or wipe-and-retry.
+
+    Multi-worker safe: relies on SQLite UNIQUE constraint to resolve
+    races during admin creation. Only the worker that successfully
+    creates/updates the admin prints the password; losers silently skip.
     """
-    from sqlalchemy import select
+    import secrets
 
     from app.gateway.deps import get_local_provider
-    from deerflow.persistence.engine import get_session_factory
-    from deerflow.persistence.user.model import UserRow
 
     provider = get_local_provider()
-    admin_count = await provider.count_admin_users()
+    user_count = await provider.count_users()
 
-    if admin_count == 0:
-        logger.info("=" * 60)
-        logger.info("  First boot detected — no admin account exists.")
-        logger.info("  Visit /setup to complete admin account creation.")
-        logger.info("=" * 60)
-        return
+    admin = None
+    fresh_admin_created = False
 
-    # Admin already exists — run orphan thread migration for any
-    # LangGraph thread metadata that pre-dates the auth module.
-    sf = get_session_factory()
-    if sf is None:
-        return
+    if user_count == 0:
+        password = secrets.token_urlsafe(16)
+        try:
+            admin = await provider.create_user(email="admin@deerflow.dev", password=password, system_role="admin", needs_setup=True)
+            fresh_admin_created = True
+        except ValueError:
+            return  # Another worker already created the admin.
+    else:
+        # Admin exists but setup never completed — reset password so operator
+        # can always find it in the console without needing the CLI.
+        # Multi-worker guard: if admin was created less than 30s ago, another
+        # worker just created it and will print the password — skip reset.
+        admin = await provider.get_user_by_email("admin@deerflow.dev")
+        if admin and admin.needs_setup:
+            import time
 
-    async with sf() as session:
-        stmt = select(UserRow).where(UserRow.system_role == "admin").limit(1)
-        row = (await session.execute(stmt)).scalar_one_or_none()
+            age = time.time() - admin.created_at.replace(tzinfo=UTC).timestamp()
+            if age >= 30:
+                from app.gateway.auth.credential_file import write_initial_credentials
+                from app.gateway.auth.password import hash_password_async
 
-    if row is None:
-        return  # Should not happen (admin_count > 0 above), but be safe.
+                password = secrets.token_urlsafe(16)
+                admin.password_hash = await hash_password_async(password)
+                admin.token_version += 1
+                await provider.update_user(admin)
 
-    admin_id = str(row.id)
+                cred_path = write_initial_credentials(admin.email, password, label="reset")
+                logger.info("=" * 60)
+                logger.info("  Admin account setup incomplete — password reset")
+                logger.info("  Credentials written to: %s (mode 0600)", cred_path)
+                logger.info("  Change it after login: Settings -> Account")
+                logger.info("=" * 60)
+
+    if admin is None:
+        return  # Nothing to bind orphans to.
+
+    admin_id = str(admin.id)
 
     # LangGraph store orphan migration — non-fatal.
     # This covers the "no-auth → with-auth" upgrade path for users
-    # whose existing LangGraph thread metadata has no user_id set.
+    # whose existing LangGraph thread metadata has no owner_id set.
     store = getattr(app.state, "store", None)
     if store is not None:
         try:
@@ -103,6 +119,16 @@ async def _ensure_admin_user(app: FastAPI) -> None:
         except Exception:
             logger.exception("LangGraph thread migration failed (non-fatal)")
 
+    if fresh_admin_created:
+        from app.gateway.auth.credential_file import write_initial_credentials
+
+        cred_path = write_initial_credentials(admin.email, password, label="initial")  # noqa: F821 — defined in the fresh_admin branch
+        logger.info("=" * 60)
+        logger.info("  Admin account created on first boot")
+        logger.info("  Credentials written to: %s (mode 0600)", cred_path)
+        logger.info("  Change it after login: Settings -> Account")
+        logger.info("=" * 60)
+
 
 async def _iter_store_items(store, namespace, *, page_size: int = 500):
     """Paginated async iterator over a LangGraph store namespace.
@@ -125,7 +151,7 @@ async def _iter_store_items(store, namespace, *, page_size: int = 500):
 
 
 async def _migrate_orphaned_threads(store, admin_user_id: str) -> int:
-    """Migrate LangGraph store threads with no user_id to the given admin.
+    """Migrate LangGraph store threads with no owner_id to the given admin.
 
     Uses cursor pagination so all orphans are migrated regardless of
     count. Returns the number of rows migrated.
@@ -133,8 +159,8 @@ async def _migrate_orphaned_threads(store, admin_user_id: str) -> int:
     migrated = 0
     async for item in _iter_store_items(store, ("threads",)):
         metadata = item.value.get("metadata", {})
-        if not metadata.get("user_id"):
-            metadata["user_id"] = admin_user_id
+        if not metadata.get("owner_id"):
+            metadata["owner_id"] = admin_user_id
             item.value["metadata"] = metadata
             await store.aput(("threads",), item.key, item.value)
             migrated += 1

backend/app/gateway/auth/credential_file.py

@@ -13,36 +13,26 @@ from __future__ import annotations
 import os
 from pathlib import Path
 
-from deerflow.config.paths import get_paths
-
-_CREDENTIAL_FILENAME = "admin_initial_credentials.txt"
+_CREDENTIAL_FILE = Path(".deer-flow") / "admin_initial_credentials.txt"
 
 
 def write_initial_credentials(email: str, password: str, *, label: str = "initial") -> Path:
-    """Write the admin email + password to ``{base_dir}/admin_initial_credentials.txt``.
+    """Write the admin email + password to ``.deer-flow/admin_initial_credentials.txt``.
 
-    The file is created **atomically** with mode 0600 via ``os.open``
-    so the password is never world-readable, even for the single syscall
-    window between ``write_text`` and ``chmod``.
+    Creates the parent directory if it does not exist. Sets the file
+    mode to 0600 so only the owning process user can read it.
 
     ``label`` distinguishes "initial" (fresh creation) from "reset"
-    (password reset) in the file header so an operator picking up the
-    file after a restart can tell which event produced it.
+    (password reset) in the file header, so an operator picking up
+    the file after a restart can tell which event produced it.
 
     Returns the absolute :class:`Path` to the file.
     """
-    target = get_paths().base_dir / _CREDENTIAL_FILENAME
-    target.parent.mkdir(parents=True, exist_ok=True)
+    _CREDENTIAL_FILE.parent.mkdir(parents=True, exist_ok=True)
 
     content = (
         f"# DeerFlow admin {label} credentials\n# This file is generated on first boot or password reset.\n# Change the password after login via Settings -> Account,\n# then delete this file.\n#\nemail: {email}\npassword: {password}\n"
     )
-
-    # Atomic 0600 create-or-truncate. O_TRUNC (not O_EXCL) so the
-    # reset-password path can rewrite an existing file without a
-    # separate unlink-then-create dance.
-    fd = os.open(target, os.O_WRONLY | os.O_CREAT | os.O_TRUNC, 0o600)
-    with os.fdopen(fd, "w", encoding="utf-8") as fh:
-        fh.write(content)
-
-    return target.resolve()
+    _CREDENTIAL_FILE.write_text(content)
+    os.chmod(_CREDENTIAL_FILE, 0o600)
+    return _CREDENTIAL_FILE.resolve()

backend/app/gateway/auth/errors.py

@@ -20,7 +20,6 @@ class AuthErrorCode(StrEnum):
     EMAIL_ALREADY_EXISTS = "email_already_exists"
     PROVIDER_NOT_FOUND = "provider_not_found"
     NOT_AUTHENTICATED = "not_authenticated"
-    SYSTEM_ALREADY_INITIALIZED = "system_already_initialized"
 
 
 class TokenError(StrEnum):

backend/app/gateway/auth/local_provider.py

@@ -78,10 +78,6 @@ class LocalAuthProvider(AuthProvider):
         """Return total number of registered users."""
         return await self._repo.count_users()
 
-    async def count_admin_users(self) -> int:
-        """Return number of admin users."""
-        return await self._repo.count_admin_users()
-
     async def update_user(self, user: User) -> User:
         """Update an existing user."""
         return await self._repo.update_user(user)

backend/app/gateway/auth/repositories/base.py

@@ -5,16 +5,6 @@ from abc import ABC, abstractmethod
 from app.gateway.auth.models import User
 
 
-class UserNotFoundError(LookupError):
-    """Raised when a user repository operation targets a non-existent row.
-
-    Subclass of :class:`LookupError` so callers that already catch
-    ``LookupError`` for "missing entity" can keep working unchanged,
-    while specific call sites can pin to this class to distinguish
-    "concurrent delete during update" from other lookups.
-    """
-
-
 class UserRepository(ABC):
     """Abstract interface for user data storage.
 
@@ -70,11 +60,6 @@ class UserRepository(ABC):
 
         Returns:
             Updated User
-
-        Raises:
-            UserNotFoundError: If no row exists for ``user.id``. This is
-                a hard failure (not a no-op) so callers cannot mistake a
-                concurrent-delete race for a successful update.
         """
         ...
 
@@ -83,11 +68,6 @@ class UserRepository(ABC):
         """Return total number of registered users."""
         ...
 
-    @abstractmethod
-    async def count_admin_users(self) -> int:
-        """Return number of users with system_role == 'admin'."""
-        ...
-
     @abstractmethod
     async def get_user_by_oauth(self, provider: str, oauth_id: str) -> User | None:
         """Get user by OAuth provider and ID.

backend/app/gateway/auth/repositories/sqlite.py

@@ -20,7 +20,7 @@ from sqlalchemy.exc import IntegrityError
 from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
 
 from app.gateway.auth.models import User
-from app.gateway.auth.repositories.base import UserNotFoundError, UserRepository
+from app.gateway.auth.repositories.base import UserRepository
 from deerflow.persistence.user.model import UserRow
 
 
@@ -92,13 +92,7 @@ class SQLiteUserRepository(UserRepository):
         async with self._sf() as session:
             row = await session.get(UserRow, str(user.id))
             if row is None:
-                # Hard fail on concurrent delete: callers (reset_admin,
-                # password change handlers, _ensure_admin_user) all
-                # fetched the user just before this call, so a missing
-                # row here means the row vanished underneath us. Silent
-                # success would let the caller log "password reset" for
-                # a row that no longer exists.
-                raise UserNotFoundError(f"User {user.id} no longer exists")
+                return user
             row.email = user.email
             row.password_hash = user.password_hash
             row.system_role = user.system_role
@@ -114,11 +108,6 @@ class SQLiteUserRepository(UserRepository):
         async with self._sf() as session:
             return await session.scalar(stmt) or 0
 
-    async def count_admin_users(self) -> int:
-        stmt = select(func.count()).select_from(UserRow).where(UserRow.system_role == "admin")
-        async with self._sf() as session:
-            return await session.scalar(stmt) or 0
-
     async def get_user_by_oauth(self, provider: str, oauth_id: str) -> User | None:
         stmt = select(UserRow).where(UserRow.oauth_provider == provider, UserRow.oauth_id == oauth_id)
         async with self._sf() as session:

backend/app/gateway/auth_middleware.py

@@ -11,13 +11,12 @@ Fine-grained permission checks remain in authz.py decorators.
 
 from collections.abc import Callable
 
-from fastapi import HTTPException, Request, Response
+from fastapi import Request, Response
 from starlette.middleware.base import BaseHTTPMiddleware
 from starlette.responses import JSONResponse
 from starlette.types import ASGIApp
 
-from app.gateway.auth.errors import AuthErrorCode, AuthErrorResponse
-from app.gateway.authz import _ALL_PERMISSIONS, AuthContext
+from app.gateway.auth.errors import AuthErrorCode
 from deerflow.runtime.user_context import reset_current_user, set_current_user
 
 # Paths that never require authentication.
@@ -36,7 +35,6 @@ _PUBLIC_EXACT_PATHS: frozenset[str] = frozenset(
         "/api/v1/auth/register",
         "/api/v1/auth/logout",
         "/api/v1/auth/setup-status",
-        "/api/v1/auth/initialize",
     }
 )
 
@@ -80,10 +78,10 @@ class AuthMiddleware(BaseHTTPMiddleware):
             return JSONResponse(
                 status_code=401,
                 content={
-                    "detail": AuthErrorResponse(
-                        code=AuthErrorCode.NOT_AUTHENTICATED,
-                        message="Authentication required",
-                    ).model_dump()
+                    "detail": {
+                        "code": AuthErrorCode.NOT_AUTHENTICATED,
+                        "message": "Authentication required",
+                    }
                 },
             )
 
@@ -98,6 +96,12 @@ class AuthMiddleware(BaseHTTPMiddleware):
         # propagate from AuthErrorCode, not get flattened into one
         # generic code. BaseHTTPMiddleware doesn't let HTTPException
         # bubble up, so we catch and render it as JSONResponse here.
+        #
+        # On success we stamp request.state.user and the contextvar
+        # so repository-layer owner filters work downstream without
+        # every route needing a decorator.
+        from fastapi import HTTPException
+
         from app.gateway.deps import get_current_user_from_request
 
         try:
@@ -105,12 +109,7 @@ class AuthMiddleware(BaseHTTPMiddleware):
         except HTTPException as exc:
             return JSONResponse(status_code=exc.status_code, content={"detail": exc.detail})
 
-        # Stamp both request.state.user (for the contextvar pattern)
-        # and request.state.auth (so @require_permission's "auth is
-        # None" branch short-circuits instead of running the entire
-        # JWT-decode + DB-lookup pipeline a second time per request).
         request.state.user = user
-        request.state.auth = AuthContext(user=user, permissions=_ALL_PERMISSIONS)
         token = set_current_user(user)
         try:
             return await call_next(request)

backend/app/gateway/authz.py

@@ -169,7 +169,8 @@ def require_permission(
     resource: str,
     action: str,
     owner_check: bool = False,
-    require_existing: bool = False,
+    owner_filter_key: str = "owner_id",
+    inject_record: bool = False,
 ) -> Callable[[Callable[P, T]], Callable[P, T]]:
     """Decorator that checks permission for resource:action.
 
@@ -180,24 +181,27 @@ def require_permission(
         action: Action name (e.g., "read", "write", "delete")
         owner_check: If True, validates that the current user owns the resource.
                      Requires 'thread_id' path parameter and performs ownership check.
-        require_existing: Only meaningful with ``owner_check=True``. If True, a
-                          missing ``threads_meta`` row counts as a denial (404)
-                          instead of "untracked legacy thread, allow". Use on
-                          **destructive / mutating** routes (DELETE, PATCH,
-                          state-update) so a deleted thread can't be re-targeted
-                          by another user via the missing-row code path.
+        owner_filter_key: Field name for ownership filter (default: "owner_id")
+        inject_record: If True and owner_check is True, injects the thread record
+                      into kwargs['thread_record'] for use in the handler.
 
     Usage:
-        # Read-style: legacy untracked threads are allowed
-        @require_permission("threads", "read", owner_check=True)
+        # Simple permission check
+        @require_permission("threads", "read")
         async def get_thread(thread_id: str, request: Request):
             ...
 
-        # Destructive: thread row MUST exist and be owned by caller
-        @require_permission("threads", "delete", owner_check=True, require_existing=True)
+        # With ownership check (for /threads/{thread_id} endpoints)
+        @require_permission("threads", "delete", owner_check=True)
         async def delete_thread(thread_id: str, request: Request):
             ...
 
+        # With ownership check and record injection
+        @require_permission("threads", "delete", owner_check=True, inject_record=True)
+        async def delete_thread(thread_id: str, request: Request, thread_record: dict = None):
+            # thread_record is injected if found
+            ...
+
     Raises:
         HTTPException 401: If authentication required but user is anonymous
         HTTPException 403: If user lacks permission
@@ -231,24 +235,27 @@ def require_permission(
             #
             # 2.0-rc moved thread metadata into the SQL persistence layer
             # (``threads_meta`` table). We verify ownership via
-            # ``ThreadMetaStore.check_access``: it returns True for
-            # missing rows (untracked legacy thread) and for rows whose
-            # ``user_id`` is NULL (shared / pre-auth data), so this is
-            # strict-deny rather than strict-allow — only an *existing*
-            # row with a *different* user_id triggers 404.
+            # ``ThreadMetaStore.check_access`` instead of the LangGraph
+            # store path that the original PR #1728 used. ``check_access``
+            # returns True for missing rows (untracked legacy thread) and
+            # for rows whose ``owner_id`` is NULL (shared / pre-auth data),
+            # so this is a strict-deny check rather than strict-allow:
+            # only an *existing* row with a *different* owner_id triggers
+            # 404.
+            #
+            # ``inject_record`` is no longer supported — it was a
+            # convenience for handlers that wanted the LangGraph store
+            # blob; the SQL repo would need a different shape and no
+            # caller in 2.0 needs it.
             if owner_check:
                 thread_id = kwargs.get("thread_id")
                 if thread_id is None:
                     raise ValueError("require_permission with owner_check=True requires 'thread_id' parameter")
 
-                from app.gateway.deps import get_thread_store
+                from app.gateway.deps import get_thread_meta_repo
 
-                thread_store = get_thread_store(request)
-                allowed = await thread_store.check_access(
-                    thread_id,
-                    str(auth.user.id),
-                    require_existing=require_existing,
-                )
+                thread_meta_repo = get_thread_meta_repo(request)
+                allowed = await thread_meta_repo.check_access(thread_id, str(auth.user.id))
                 if not allowed:
                     raise HTTPException(
                         status_code=404,

backend/app/gateway/csrf_middleware.py

@@ -48,7 +48,6 @@ _AUTH_EXEMPT_PATHS: frozenset[str] = frozenset(
         "/api/v1/auth/login/local",
         "/api/v1/auth/logout",
         "/api/v1/auth/register",
-        "/api/v1/auth/initialize",
     }
 )
 

backend/app/gateway/deps.py

@@ -1,32 +1,25 @@
 """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``.
+missing, except ``get_store`` and ``get_thread_meta_repo`` which return
+``None``.
 
 Initialization is handled directly in ``app.py`` via :class:`AsyncExitStack`.
 """
 
 from __future__ import annotations
 
-from collections.abc import AsyncGenerator, Callable
+from collections.abc import AsyncGenerator
 from contextlib import AsyncExitStack, asynccontextmanager
-from typing import TYPE_CHECKING, TypeVar, cast
+from typing import TYPE_CHECKING
 
 from fastapi import FastAPI, HTTPException, Request
-from langgraph.types import Checkpointer
 
-from deerflow.persistence.feedback import FeedbackRepository
-from deerflow.runtime import RunContext, RunManager, StreamBridge
-from deerflow.runtime.events.store.base import RunEventStore
-from deerflow.runtime.runs.store.base import RunStore
+from deerflow.runtime import RunContext, RunManager
 
 if TYPE_CHECKING:
     from app.gateway.auth.local_provider import LocalAuthProvider
     from app.gateway.auth.repositories.sqlite import SQLiteUserRepository
-    from deerflow.persistence.thread_meta.base import ThreadMetaStore
-
-
-T = TypeVar("T")
 
 
 @asynccontextmanager
@@ -38,10 +31,10 @@ async def langgraph_runtime(app: FastAPI) -> AsyncGenerator[None, None]:
         async with langgraph_runtime(app):
             yield
     """
+    from deerflow.agents.checkpointer.async_provider import make_checkpointer
     from deerflow.config import get_app_config
     from deerflow.persistence.engine import close_engine, get_session_factory, init_engine_from_config
     from deerflow.runtime import make_store, make_stream_bridge
-    from deerflow.runtime.checkpointer.async_provider import make_checkpointer
     from deerflow.runtime.events.store import make_run_event_store
 
     async with AsyncExitStack() as stack:
@@ -60,18 +53,18 @@ async def langgraph_runtime(app: FastAPI) -> AsyncGenerator[None, None]:
         if sf is not None:
             from deerflow.persistence.feedback import FeedbackRepository
             from deerflow.persistence.run import RunRepository
+            from deerflow.persistence.thread_meta import ThreadMetaRepository
 
             app.state.run_store = RunRepository(sf)
             app.state.feedback_repo = FeedbackRepository(sf)
+            app.state.thread_meta_repo = ThreadMetaRepository(sf)
         else:
+            from deerflow.persistence.thread_meta import MemoryThreadMetaStore
             from deerflow.runtime.runs.store.memory import MemoryRunStore
 
             app.state.run_store = MemoryRunStore()
             app.state.feedback_repo = None
-
-        from deerflow.persistence.thread_meta import make_thread_store
-
-        app.state.thread_store = make_thread_store(sf, app.state.store)
+            app.state.thread_meta_repo = MemoryThreadMetaStore(app.state.store)
 
         # Run event store (has its own factory with config-driven backend selection)
         run_events_config = getattr(config, "run_events", None)
@@ -87,29 +80,29 @@ async def langgraph_runtime(app: FastAPI) -> AsyncGenerator[None, None]:
 
 
 # ---------------------------------------------------------------------------
-# Getters – called by routers per-request
+# Getters -- called by routers per-request
 # ---------------------------------------------------------------------------
 
 
-def _require(attr: str, label: str) -> Callable[[Request], T]:
+def _require(attr: str, label: str):
     """Create a FastAPI dependency that returns ``app.state.<attr>`` or 503."""
 
-    def dep(request: Request) -> T:
+    def dep(request: Request):
         val = getattr(request.app.state, attr, None)
         if val is None:
             raise HTTPException(status_code=503, detail=f"{label} not available")
-        return cast(T, val)
+        return val
 
     dep.__name__ = dep.__qualname__ = f"get_{attr}"
     return dep
 
 
-get_stream_bridge: Callable[[Request], StreamBridge] = _require("stream_bridge", "Stream bridge")
-get_run_manager: Callable[[Request], RunManager] = _require("run_manager", "Run manager")
-get_checkpointer: Callable[[Request], Checkpointer] = _require("checkpointer", "Checkpointer")
-get_run_event_store: Callable[[Request], RunEventStore] = _require("run_event_store", "Run event store")
-get_feedback_repo: Callable[[Request], FeedbackRepository] = _require("feedback_repo", "Feedback")
-get_run_store: Callable[[Request], RunStore] = _require("run_store", "Run store")
+get_stream_bridge = _require("stream_bridge", "Stream bridge")
+get_run_manager = _require("run_manager", "Run manager")
+get_checkpointer = _require("checkpointer", "Checkpointer")
+get_run_event_store = _require("run_event_store", "Run event store")
+get_feedback_repo = _require("feedback_repo", "Feedback")
+get_run_store = _require("run_store", "Run store")
 
 
 def get_store(request: Request):
@@ -117,18 +110,16 @@ def get_store(request: Request):
     return getattr(request.app.state, "store", None)
 
 
-def get_thread_store(request: Request) -> ThreadMetaStore:
-    """Return the thread metadata store (SQL or memory-backed)."""
-    val = getattr(request.app.state, "thread_store", None)
-    if val is None:
-        raise HTTPException(status_code=503, detail="Thread metadata store not available")
-    return val
+get_thread_meta_repo = _require("thread_meta_repo", "Thread metadata store")
 
 
 def get_run_context(request: Request) -> RunContext:
     """Build a :class:`RunContext` from ``app.state`` singletons.
 
-    Returns a *base* context with infrastructure dependencies.
+    Returns a *base* context with infrastructure dependencies.  Callers that
+    need per-run fields (e.g. ``follow_up_to_run_id``) should use
+    ``dataclasses.replace(ctx, follow_up_to_run_id=...)`` before passing it
+    to :func:`run_agent`.
     """
     from deerflow.config import get_app_config
 
@@ -137,7 +128,7 @@ def get_run_context(request: Request) -> RunContext:
         store=get_store(request),
         event_store=get_run_event_store(request),
         run_events_config=getattr(get_app_config(), "run_events", None),
-        thread_store=get_thread_store(request),
+        thread_meta_repo=get_thread_meta_repo(request),
     )
 
 

backend/app/gateway/langgraph_auth.py

@@ -93,14 +93,14 @@ async def authenticate(request):
 
 @auth.on
 async def add_owner_filter(ctx: Auth.types.AuthContext, value: dict):
-    """Inject user_id metadata on writes; filter by user_id on reads.
+    """Inject owner_id metadata on writes; filter by owner_id on reads.
 
-    Gateway stores thread ownership as ``metadata.user_id``.
+    Gateway stores thread ownership as ``metadata.owner_id``.
     This handler ensures LangGraph Server enforces the same isolation.
     """
-    # On create/update: stamp user_id into metadata
+    # On create/update: stamp owner_id into metadata
     metadata = value.setdefault("metadata", {})
-    metadata["user_id"] = ctx.user.identity
+    metadata["owner_id"] = ctx.user.identity
 
     # Return filter dict — LangGraph applies it to search/read/delete
-    return {"user_id": ctx.user.identity}
+    return {"owner_id": ctx.user.identity}

backend/app/gateway/path_utils.py

@@ -5,7 +5,6 @@ from pathlib import Path
 from fastapi import HTTPException
 
 from deerflow.config.paths import get_paths
-from deerflow.runtime.user_context import get_effective_user_id
 
 
 def resolve_thread_virtual_path(thread_id: str, virtual_path: str) -> Path:
@@ -23,7 +22,7 @@ def resolve_thread_virtual_path(thread_id: str, virtual_path: str) -> Path:
         HTTPException: If the path is invalid or outside allowed directories.
     """
     try:
-        return get_paths().resolve_virtual_path(thread_id, virtual_path, user_id=get_effective_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))

backend/app/gateway/routers/auth.py

@@ -1,13 +1,11 @@
 """Authentication endpoints."""
 
 import logging
-import os
 import time
-from ipaddress import ip_address, ip_network
 
 from fastapi import APIRouter, Depends, HTTPException, Request, Response, status
 from fastapi.security import OAuth2PasswordRequestForm
-from pydantic import BaseModel, EmailStr, Field, field_validator
+from pydantic import BaseModel, EmailStr, Field
 
 from app.gateway.auth import (
     UserResponse,
@@ -33,84 +31,12 @@ class LoginResponse(BaseModel):
     needs_setup: bool = False
 
 
-# Top common-password blocklist. Drawn from the public SecLists "10k worst
-# passwords" set, lowercased + length>=8 only (shorter ones already fail
-# the min_length check). Kept tight on purpose: this is the **lower bound**
-# defense, not a full HIBP / passlib check, and runs in-process per request.
-_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",
-    }
-)
-
-
-def _password_is_common(password: str) -> bool:
-    """Case-insensitive blocklist check.
-
-    Lowercases the input so trivial mutations like ``Password`` /
-    ``PASSWORD`` are also rejected. Does not normalize digit substitutions
-    (``p@ssw0rd`` is included as a literal entry instead) — keeping the
-    rule cheap and predictable.
-    """
-    return password.lower() in _COMMON_PASSWORDS
-
-
-def _validate_strong_password(value: str) -> str:
-    """Pydantic field-validator body shared by Register + ChangePassword.
-
-    Constraint = function, not type-level mixin. The two request models
-    have no "is-a" relationship; they only share the password-strength
-    rule. Lifting it into a free function lets each model bind it via
-    ``@field_validator(field_name)`` without inheritance gymnastics.
-    """
-    if _password_is_common(value):
-        raise ValueError("Password is too common; choose a stronger password.")
-    return value
-
-
 class RegisterRequest(BaseModel):
     """Request model for user registration."""
 
     email: EmailStr
     password: str = Field(..., min_length=8)
 
-    _strong_password = field_validator("password")(classmethod(lambda cls, v: _validate_strong_password(v)))
-
 
 class ChangePasswordRequest(BaseModel):
     """Request model for password change (also handles setup flow)."""
@@ -119,8 +45,6 @@ class ChangePasswordRequest(BaseModel):
     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):
     """Generic message response."""
@@ -155,65 +79,26 @@ _LOCKOUT_SECONDS = 300  # 5 minutes
 _login_attempts: dict[str, tuple[int, float]] = {}
 
 
-def _trusted_proxies() -> list:
-    """Parse ``AUTH_TRUSTED_PROXIES`` env var into a list of ip_network objects.
-
-    Comma-separated CIDR or single-IP entries. Empty / unset = no proxy is
-    trusted (direct mode). Invalid entries are skipped with a logger warning.
-    Read live so env-var overrides take effect immediately and tests can
-    ``monkeypatch.setenv`` without poking a module-level cache.
-    """
-    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:
-            logger.warning("AUTH_TRUSTED_PROXIES: ignoring invalid entry %r", entry)
-    return nets
-
-
 def _get_client_ip(request: Request) -> str:
     """Extract the real client IP for rate limiting.
 
-    Trust model:
+    Uses ``X-Real-IP`` header set by nginx (``proxy_set_header X-Real-IP
+    $remote_addr``).  Nginx unconditionally overwrites any client-supplied
+    ``X-Real-IP``, so the value seen by Gateway is always the TCP peer IP
+    that nginx observed — it cannot be spoofed by the client.
 
-    - The TCP peer (``request.client.host``) is always the baseline. It is
-      whatever the kernel reports as the connecting socket — unforgeable
-      by the client itself.
-    - ``X-Real-IP`` is **only** honored if the TCP peer is in the
-      ``AUTH_TRUSTED_PROXIES`` allowlist (set via env var, comma-separated
-      CIDR or single IPs). When set, the gateway is assumed to be behind a
-      reverse proxy (nginx, Cloudflare, ALB, …) that overwrites
-      ``X-Real-IP`` with the original client address.
-    - With no ``AUTH_TRUSTED_PROXIES`` set, ``X-Real-IP`` is silently
-      ignored — closing the bypass where any client could rotate the
-      header to dodge per-IP rate limits in dev / direct-gateway mode.
+    ``request.client.host`` is NOT reliable because uvicorn's default
+    ``proxy_headers=True`` replaces it with the *first* entry from
+    ``X-Forwarded-For``, which IS client-spoofable.
 
-    ``X-Forwarded-For`` is intentionally NOT used because it is naturally
-    client-controlled at the *first* hop and the trust chain is harder to
-    audit per-request.
+    ``X-Forwarded-For`` is intentionally NOT used for the same reason.
     """
-    peer_host = request.client.host if request.client else None
+    real_ip = request.headers.get("x-real-ip", "").strip()
+    if real_ip:
+        return real_ip
 
-    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:
-            # peer_host wasn't a parseable IP (e.g. "unknown") — fall through
-            pass
-
-    return peer_host or "unknown"
+    # Fallback: direct connection without nginx (e.g. unit tests, dev).
+    return request.client.host if request.client else "unknown"
 
 
 def _check_rate_limit(ip: str) -> None:
@@ -378,50 +263,9 @@ async def get_me(request: Request):
 
 @router.get("/setup-status")
 async def setup_status():
-    """Check if an admin account exists. Returns needs_setup=True when no admin exists."""
-    admin_count = await get_local_provider().count_admin_users()
-    return {"needs_setup": admin_count == 0}
-
-
-class InitializeAdminRequest(BaseModel):
-    """Request model for first-boot admin account creation."""
-
-    email: EmailStr
-    password: str = Field(..., min_length=8)
-
-    _strong_password = field_validator("password")(classmethod(lambda cls, v: _validate_strong_password(v)))
-
-
-@router.post("/initialize", response_model=UserResponse, status_code=status.HTTP_201_CREATED)
-async def initialize_admin(request: Request, response: Response, body: InitializeAdminRequest):
-    """Create the first admin account on initial system setup.
-
-    Only callable when no admin exists. Returns 409 Conflict if an admin
-    already exists.
-
-    On success, the admin account is created with ``needs_setup=False`` and
-    the session cookie is set.
-    """
-    admin_count = await get_local_provider().count_admin_users()
-    if admin_count > 0:
-        raise HTTPException(
-            status_code=status.HTTP_409_CONFLICT,
-            detail=AuthErrorResponse(code=AuthErrorCode.SYSTEM_ALREADY_INITIALIZED, message="System already initialized").model_dump(),
-        )
-
-    try:
-        user = await get_local_provider().create_user(email=body.email, password=body.password, system_role="admin", needs_setup=False)
-    except ValueError:
-        # DB unique-constraint race: another concurrent request beat us.
-        raise HTTPException(
-            status_code=status.HTTP_409_CONFLICT,
-            detail=AuthErrorResponse(code=AuthErrorCode.SYSTEM_ALREADY_INITIALIZED, message="System already initialized").model_dump(),
-        )
-
-    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)
+    """Check if admin account exists. Always False after first boot."""
+    user_count = await get_local_provider().count_users()
+    return {"needs_setup": user_count == 0}
 
 
 # ── OAuth Endpoints (Future/Placeholder) ─────────────────────────────────

backend/app/gateway/routers/feedback.py

@@ -30,16 +30,11 @@ class FeedbackCreateRequest(BaseModel):
     message_id: str | None = Field(default=None, description="Optional: scope feedback to a specific message")
 
 
-class FeedbackUpsertRequest(BaseModel):
-    rating: int = Field(..., description="Feedback rating: +1 (positive) or -1 (negative)")
-    comment: str | None = Field(default=None, description="Optional text feedback")
-
-
 class FeedbackResponse(BaseModel):
     feedback_id: str
     run_id: str
     thread_id: str
-    user_id: str | None = None
+    owner_id: str | None = None
     message_id: str | None = None
     rating: int
     comment: str | None = None
@@ -58,59 +53,8 @@ class FeedbackStatsResponse(BaseModel):
 # ---------------------------------------------------------------------------
 
 
-@router.put("/{thread_id}/runs/{run_id}/feedback", response_model=FeedbackResponse)
-@require_permission("threads", "write", owner_check=True, require_existing=True)
-async def upsert_feedback(
-    thread_id: str,
-    run_id: str,
-    body: FeedbackUpsertRequest,
-    request: Request,
-) -> dict[str, Any]:
-    """Create or update feedback for a run (idempotent)."""
-    if body.rating not in (1, -1):
-        raise HTTPException(status_code=400, detail="rating must be +1 or -1")
-
-    user_id = await get_current_user(request)
-
-    run_store = get_run_store(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}")
-
-    feedback_repo = get_feedback_repo(request)
-    return await feedback_repo.upsert(
-        run_id=run_id,
-        thread_id=thread_id,
-        rating=body.rating,
-        user_id=user_id,
-        comment=body.comment,
-    )
-
-
-@router.delete("/{thread_id}/runs/{run_id}/feedback")
-@require_permission("threads", "delete", owner_check=True, require_existing=True)
-async def delete_run_feedback(
-    thread_id: str,
-    run_id: str,
-    request: Request,
-) -> dict[str, bool]:
-    """Delete the current user's feedback for a run."""
-    user_id = await get_current_user(request)
-    feedback_repo = get_feedback_repo(request)
-    deleted = await feedback_repo.delete_by_run(
-        thread_id=thread_id,
-        run_id=run_id,
-        user_id=user_id,
-    )
-    if not deleted:
-        raise HTTPException(status_code=404, detail="No feedback found for this run")
-    return {"success": True}
-
-
 @router.post("/{thread_id}/runs/{run_id}/feedback", response_model=FeedbackResponse)
-@require_permission("threads", "write", owner_check=True, require_existing=True)
+@require_permission("threads", "write", owner_check=True)
 async def create_feedback(
     thread_id: str,
     run_id: str,
@@ -136,7 +80,7 @@ async def create_feedback(
         run_id=run_id,
         thread_id=thread_id,
         rating=body.rating,
-        user_id=user_id,
+        owner_id=user_id,
         message_id=body.message_id,
         comment=body.comment,
     )
@@ -167,7 +111,7 @@ async def feedback_stats(
 
 
 @router.delete("/{thread_id}/runs/{run_id}/feedback/{feedback_id}")
-@require_permission("threads", "delete", owner_check=True, require_existing=True)
+@require_permission("threads", "delete", owner_check=True)
 async def delete_feedback(
     thread_id: str,
     run_id: str,

backend/app/gateway/routers/memory.py

@@ -13,7 +13,6 @@ from deerflow.agents.memory.updater import (
     update_memory_fact,
 )
 from deerflow.config.memory_config import get_memory_config
-from deerflow.runtime.user_context import get_effective_user_id
 
 router = APIRouter(prefix="/api", tags=["memory"])
 
@@ -148,7 +147,7 @@ async def get_memory() -> MemoryResponse:
         }
         ```
     """
-    memory_data = get_memory_data(user_id=get_effective_user_id())
+    memory_data = get_memory_data()
     return MemoryResponse(**memory_data)
 
 
@@ -168,7 +167,7 @@ async def reload_memory() -> MemoryResponse:
     Returns:
         The reloaded memory data.
     """
-    memory_data = reload_memory_data(user_id=get_effective_user_id())
+    memory_data = reload_memory_data()
     return MemoryResponse(**memory_data)
 
 
@@ -182,7 +181,7 @@ async def reload_memory() -> MemoryResponse:
 async def clear_memory() -> MemoryResponse:
     """Clear all persisted memory data."""
     try:
-        memory_data = clear_memory_data(user_id=get_effective_user_id())
+        memory_data = clear_memory_data()
     except OSError as exc:
         raise HTTPException(status_code=500, detail="Failed to clear memory data.") from exc
 
@@ -203,7 +202,6 @@ async def create_memory_fact_endpoint(request: FactCreateRequest) -> MemoryRespo
             content=request.content,
             category=request.category,
             confidence=request.confidence,
-            user_id=get_effective_user_id(),
         )
     except ValueError as exc:
         raise _map_memory_fact_value_error(exc) from exc
@@ -223,7 +221,7 @@ async def create_memory_fact_endpoint(request: FactCreateRequest) -> MemoryRespo
 async def delete_memory_fact_endpoint(fact_id: str) -> MemoryResponse:
     """Delete a single fact from memory by fact id."""
     try:
-        memory_data = delete_memory_fact(fact_id, user_id=get_effective_user_id())
+        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:
@@ -247,7 +245,6 @@ async def update_memory_fact_endpoint(fact_id: str, request: FactPatchRequest) -
             content=request.content,
             category=request.category,
             confidence=request.confidence,
-            user_id=get_effective_user_id(),
         )
     except ValueError as exc:
         raise _map_memory_fact_value_error(exc) from exc
@@ -268,7 +265,7 @@ async def update_memory_fact_endpoint(fact_id: str, request: FactPatchRequest) -
 )
 async def export_memory() -> MemoryResponse:
     """Export the current memory data."""
-    memory_data = get_memory_data(user_id=get_effective_user_id())
+    memory_data = get_memory_data()
     return MemoryResponse(**memory_data)
 
 
@@ -282,7 +279,7 @@ async def export_memory() -> MemoryResponse:
 async def import_memory(request: MemoryResponse) -> MemoryResponse:
     """Import and persist memory data."""
     try:
-        memory_data = import_memory_data(request.model_dump(), user_id=get_effective_user_id())
+        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
 
@@ -340,7 +337,7 @@ async def get_memory_status() -> MemoryStatusResponse:
         Combined memory configuration and current data.
     """
     config = get_memory_config()
-    memory_data = get_memory_data(user_id=get_effective_user_id())
+    memory_data = get_memory_data()
 
     return MemoryStatusResponse(
         config=MemoryConfigResponse(

backend/app/gateway/routers/runs.py

@@ -11,11 +11,10 @@ import asyncio
 import logging
 import uuid
 
-from fastapi import APIRouter, HTTPException, Query, Request
+from fastapi import APIRouter, Request
 from fastapi.responses import StreamingResponse
 
-from app.gateway.authz import require_permission
-from app.gateway.deps import get_checkpointer, get_feedback_repo, get_run_event_store, get_run_manager, get_run_store, get_stream_bridge
+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
@@ -86,58 +85,3 @@ async def stateless_wait(body: RunCreateRequest, request: Request) -> dict:
         logger.exception("Failed to fetch final state for run %s", record.run_id)
 
     return {"status": record.status.value, "error": record.error}
-
-
-# ---------------------------------------------------------------------------
-# Run-scoped read endpoints
-# ---------------------------------------------------------------------------
-
-
-async def _resolve_run(run_id: str, request: Request) -> dict:
-    """Fetch run by run_id with user ownership check. Raises 404 if not found."""
-    run_store = get_run_store(request)
-    record = await run_store.get(run_id)  # user_id=AUTO filters by contextvar
-    if record is None:
-        raise HTTPException(status_code=404, detail=f"Run {run_id} not found")
-    return record
-
-
-@router.get("/{run_id}/messages")
-@require_permission("runs", "read")
-async def run_messages(
-    run_id: str,
-    request: Request,
-    limit: int = Query(default=50, le=200, ge=1),
-    before_seq: int | None = Query(default=None),
-    after_seq: int | None = Query(default=None),
-) -> dict:
-    """Return paginated messages for a run (cursor-based).
-
-    Pagination:
-    - after_seq: messages with seq > after_seq (forward)
-    - before_seq: messages with seq < before_seq (backward)
-    - neither: latest messages
-
-    Response: { data: [...], has_more: bool }
-    """
-    run = await _resolve_run(run_id, request)
-    event_store = get_run_event_store(request)
-    rows = await event_store.list_messages_by_run(
-        run["thread_id"],
-        run_id,
-        limit=limit + 1,
-        before_seq=before_seq,
-        after_seq=after_seq,
-    )
-    has_more = len(rows) > limit
-    data = rows[:limit] if has_more else rows
-    return {"data": data, "has_more": has_more}
-
-
-@router.get("/{run_id}/feedback")
-@require_permission("runs", "read")
-async def run_feedback(run_id: str, request: Request) -> list[dict]:
-    """Return all feedback for a run."""
-    run = await _resolve_run(run_id, request)
-    feedback_repo = get_feedback_repo(request)
-    return await feedback_repo.list_by_run(run["thread_id"], run_id)

backend/app/gateway/routers/skills.py

@@ -7,7 +7,7 @@ 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.agents.lead_agent.prompt import clear_skills_system_prompt_cache
 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
@@ -119,7 +119,6 @@ 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))
@@ -182,7 +181,7 @@ async def update_custom_skill(skill_name: str, request: CustomSkillUpdateRequest
                 "scanner": {"decision": scan.decision, "reason": scan.reason},
             },
         )
-        await refresh_skills_system_prompt_cache_async()
+        clear_skills_system_prompt_cache()
         return await get_custom_skill(skill_name)
     except HTTPException:
         raise
@@ -214,7 +213,7 @@ async def delete_custom_skill(skill_name: str) -> dict[str, bool]:
             },
         )
         shutil.rmtree(skill_dir)
-        await refresh_skills_system_prompt_cache_async()
+        clear_skills_system_prompt_cache()
         return {"success": True}
     except FileNotFoundError as e:
         raise HTTPException(status_code=404, detail=str(e))
@@ -269,7 +268,7 @@ async def rollback_custom_skill(skill_name: str, request: SkillRollbackRequest)
             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()
+        clear_skills_system_prompt_cache()
         return await get_custom_skill(skill_name)
     except HTTPException:
         raise
@@ -338,7 +337,6 @@ 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)

backend/app/gateway/routers/thread_runs.py

@@ -20,7 +20,7 @@ from fastapi.responses import Response, StreamingResponse
 from pydantic import BaseModel, Field
 
 from app.gateway.authz import require_permission
-from app.gateway.deps import get_checkpointer, get_current_user, get_feedback_repo, get_run_event_store, get_run_manager, get_run_store, get_stream_bridge
+from app.gateway.deps import get_checkpointer, get_run_event_store, get_run_manager, get_run_store, get_stream_bridge
 from app.gateway.services import sse_consumer, start_run
 from deerflow.runtime import RunRecord, serialize_channel_values
 
@@ -54,6 +54,7 @@ class RunCreateRequest(BaseModel):
     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")
+    follow_up_to_run_id: str | None = Field(default=None, description="Run ID this message follows up on. Auto-detected from latest successful run if not provided.")
 
 
 class RunResponse(BaseModel):
@@ -93,7 +94,7 @@ def _record_to_response(record: RunRecord) -> RunResponse:
 
 
 @router.post("/{thread_id}/runs", response_model=RunResponse)
-@require_permission("runs", "create", owner_check=True, require_existing=True)
+@require_permission("runs", "create", owner_check=True)
 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)
@@ -101,7 +102,7 @@ async def create_run(thread_id: str, body: RunCreateRequest, request: Request) -
 
 
 @router.post("/{thread_id}/runs/stream")
-@require_permission("runs", "create", owner_check=True, require_existing=True)
+@require_permission("runs", "create", owner_check=True)
 async def stream_run(thread_id: str, body: RunCreateRequest, request: Request) -> StreamingResponse:
     """Create a run and stream events via SSE.
 
@@ -129,7 +130,7 @@ async def stream_run(thread_id: str, body: RunCreateRequest, request: Request) -
 
 
 @router.post("/{thread_id}/runs/wait", response_model=dict)
-@require_permission("runs", "create", owner_check=True, require_existing=True)
+@require_permission("runs", "create", owner_check=True)
 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)
@@ -175,7 +176,7 @@ async def get_run(thread_id: str, run_id: str, request: Request) -> RunResponse:
 
 
 @router.post("/{thread_id}/runs/{run_id}/cancel")
-@require_permission("runs", "cancel", owner_check=True, require_existing=True)
+@require_permission("runs", "cancel", owner_check=True)
 async def cancel_run(
     thread_id: str,
     run_id: str,
@@ -290,67 +291,17 @@ async def list_thread_messages(
     before_seq: int | None = Query(default=None),
     after_seq: int | None = Query(default=None),
 ) -> list[dict]:
-    """Return displayable messages for a thread (across all runs), with feedback attached."""
+    """Return displayable messages for a thread (across all runs)."""
     event_store = get_run_event_store(request)
-    messages = await event_store.list_messages(thread_id, limit=limit, before_seq=before_seq, after_seq=after_seq)
-
-    # Attach feedback to the last AI message of each run
-    feedback_repo = get_feedback_repo(request)
-    user_id = await get_current_user(request)
-    feedback_map = await feedback_repo.list_by_thread_grouped(thread_id, user_id=user_id)
-
-    # Find the last ai_message per run_id
-    last_ai_per_run: dict[str, int] = {}  # run_id -> index in messages list
-    for i, msg in enumerate(messages):
-        if msg.get("event_type") == "ai_message":
-            last_ai_per_run[msg["run_id"]] = i
-
-    # Attach feedback field
-    last_ai_indices = set(last_ai_per_run.values())
-    for i, msg in enumerate(messages):
-        if i in last_ai_indices:
-            run_id = msg["run_id"]
-            fb = feedback_map.get(run_id)
-            msg["feedback"] = (
-                {
-                    "feedback_id": fb["feedback_id"],
-                    "rating": fb["rating"],
-                    "comment": fb.get("comment"),
-                }
-                if fb
-                else None
-            )
-        else:
-            msg["feedback"] = None
-
-    return messages
+    return await event_store.list_messages(thread_id, limit=limit, before_seq=before_seq, after_seq=after_seq)
 
 
 @router.get("/{thread_id}/runs/{run_id}/messages")
 @require_permission("runs", "read", owner_check=True)
-async def list_run_messages(
-    thread_id: str,
-    run_id: str,
-    request: Request,
-    limit: int = Query(default=50, le=200, ge=1),
-    before_seq: int | None = Query(default=None),
-    after_seq: int | None = Query(default=None),
-) -> dict:
-    """Return paginated messages for a specific run.
-
-    Response: { data: [...], has_more: bool }
-    """
+async def list_run_messages(thread_id: str, run_id: str, request: Request) -> list[dict]:
+    """Return displayable messages for a specific run."""
     event_store = get_run_event_store(request)
-    rows = await event_store.list_messages_by_run(
-        thread_id,
-        run_id,
-        limit=limit + 1,
-        before_seq=before_seq,
-        after_seq=after_seq,
-    )
-    has_more = len(rows) > limit
-    data = rows[:limit] if has_more else rows
-    return {"data": data, "has_more": has_more}
+    return await event_store.list_messages_by_run(thread_id, run_id)
 
 
 @router.get("/{thread_id}/runs/{run_id}/events")

backend/app/gateway/routers/threads.py

@@ -13,41 +13,23 @@ matching the LangGraph Platform wire format expected by the
 from __future__ import annotations
 
 import logging
-import re
 import time
 import uuid
 from typing import Any
 
 from fastapi import APIRouter, HTTPException, Request
-from pydantic import BaseModel, Field, field_validator
+from pydantic import BaseModel, Field
 
 from app.gateway.authz import require_permission
 from app.gateway.deps import get_checkpointer
 from app.gateway.utils import sanitize_log_param
 from deerflow.config.paths import Paths, get_paths
 from deerflow.runtime import serialize_channel_values
-from deerflow.runtime.user_context import get_effective_user_id
 
 logger = logging.getLogger(__name__)
 router = APIRouter(prefix="/api/threads", tags=["threads"])
 
 
-# Metadata keys that the server controls; clients are not allowed to set
-# them. Pydantic ``@field_validator("metadata")`` strips them on every
-# inbound model below so a malicious client cannot reflect a forged
-# owner identity through the API surface. Defense-in-depth — the
-# row-level invariant is still ``threads_meta.user_id`` populated from
-# the auth contextvar; this list closes the metadata-blob echo gap.
-_SERVER_RESERVED_METADATA_KEYS: frozenset[str] = frozenset({"owner_id", "user_id"})
-
-
-def _strip_reserved_metadata(metadata: dict[str, Any] | None) -> dict[str, Any]:
-    """Return ``metadata`` with server-controlled keys removed."""
-    if not metadata:
-        return metadata or {}
-    return {k: v for k, v in metadata.items() if k not in _SERVER_RESERVED_METADATA_KEYS}
-
-
 # ---------------------------------------------------------------------------
 # Response / request models
 # ---------------------------------------------------------------------------
@@ -79,8 +61,6 @@ class ThreadCreateRequest(BaseModel):
     assistant_id: str | None = Field(default=None, description="Associate thread with an assistant")
     metadata: dict[str, Any] = Field(default_factory=dict, description="Initial metadata")
 
-    _strip_reserved = field_validator("metadata")(classmethod(lambda cls, v: _strip_reserved_metadata(v)))
-
 
 class ThreadSearchRequest(BaseModel):
     """Request body for searching threads."""
@@ -109,8 +89,6 @@ class ThreadPatchRequest(BaseModel):
 
     metadata: dict[str, Any] = Field(default_factory=dict, description="Metadata to merge")
 
-    _strip_reserved = field_validator("metadata")(classmethod(lambda cls, v: _strip_reserved_metadata(v)))
-
 
 class ThreadStateUpdateRequest(BaseModel):
     """Request body for updating thread state (human-in-the-loop resume)."""
@@ -144,11 +122,11 @@ class ThreadHistoryRequest(BaseModel):
 # ---------------------------------------------------------------------------
 
 
-def _delete_thread_data(thread_id: str, paths: Paths | None = None, *, user_id: str | None = None) -> ThreadDeleteResponse:
+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, user_id=user_id)
+        path_manager.delete_thread_dir(thread_id)
     except ValueError as exc:
         raise HTTPException(status_code=422, detail=str(exc)) from exc
     except FileNotFoundError:
@@ -188,7 +166,7 @@ def _derive_thread_status(checkpoint_tuple) -> str:
 
 
 @router.delete("/{thread_id}", response_model=ThreadDeleteResponse)
-@require_permission("threads", "delete", owner_check=True, require_existing=True)
+@require_permission("threads", "delete", owner_check=True)
 async def delete_thread_data(thread_id: str, request: Request) -> ThreadDeleteResponse:
     """Delete local persisted filesystem data for a thread.
 
@@ -196,10 +174,10 @@ async def delete_thread_data(thread_id: str, request: Request) -> ThreadDeleteRe
     and removes the thread_meta row from the configured ThreadMetaStore
     (sqlite or memory).
     """
-    from app.gateway.deps import get_thread_store
+    from app.gateway.deps import get_thread_meta_repo
 
     # Clean local filesystem
-    response = _delete_thread_data(thread_id, user_id=get_effective_user_id())
+    response = _delete_thread_data(thread_id)
 
     # Remove checkpoints (best-effort)
     checkpointer = getattr(request.app.state, "checkpointer", None)
@@ -213,8 +191,8 @@ async def delete_thread_data(thread_id: str, request: Request) -> ThreadDeleteRe
     # Remove thread_meta row (best-effort) — required for sqlite backend
     # so the deleted thread no longer appears in /threads/search.
     try:
-        thread_store = get_thread_store(request)
-        await thread_store.delete(thread_id)
+        thread_meta_repo = get_thread_meta_repo(request)
+        await thread_meta_repo.delete(thread_id)
     except Exception:
         logger.debug("Could not delete thread_meta for %s (not critical)", sanitize_log_param(thread_id))
 
@@ -229,17 +207,15 @@ async def create_thread(body: ThreadCreateRequest, request: Request) -> ThreadRe
     and an empty checkpoint (so state endpoints work immediately).
     Idempotent: returns the existing record when ``thread_id`` already exists.
     """
-    from app.gateway.deps import get_thread_store
+    from app.gateway.deps import get_thread_meta_repo
 
     checkpointer = get_checkpointer(request)
-    thread_store = get_thread_store(request)
+    thread_meta_repo = get_thread_meta_repo(request)
     thread_id = body.thread_id or str(uuid.uuid4())
     now = time.time()
-    # ``body.metadata`` is already stripped of server-reserved keys by
-    # ``ThreadCreateRequest._strip_reserved`` — see the model definition.
 
     # Idempotency: return existing record when already present
-    existing_record = await thread_store.get(thread_id)
+    existing_record = await thread_meta_repo.get(thread_id)
     if existing_record is not None:
         return ThreadResponse(
             thread_id=thread_id,
@@ -251,7 +227,7 @@ async def create_thread(body: ThreadCreateRequest, request: Request) -> ThreadRe
 
     # Write thread_meta so the thread appears in /threads/search immediately
     try:
-        await thread_store.create(
+        await thread_meta_repo.create(
             thread_id,
             assistant_id=getattr(body, "assistant_id", None),
             metadata=body.metadata,
@@ -295,9 +271,9 @@ async def search_threads(body: ThreadSearchRequest, request: Request) -> list[Th
     Delegates to the configured ThreadMetaStore implementation
     (SQL-backed for sqlite/postgres, Store-backed for memory mode).
     """
-    from app.gateway.deps import get_thread_store
+    from app.gateway.deps import get_thread_meta_repo
 
-    repo = get_thread_store(request)
+    repo = get_thread_meta_repo(request)
     rows = await repo.search(
         metadata=body.metadata or None,
         status=body.status,
@@ -319,25 +295,24 @@ async def search_threads(body: ThreadSearchRequest, request: Request) -> list[Th
 
 
 @router.patch("/{thread_id}", response_model=ThreadResponse)
-@require_permission("threads", "write", owner_check=True, require_existing=True)
+@require_permission("threads", "write", owner_check=True)
 async def patch_thread(thread_id: str, body: ThreadPatchRequest, request: Request) -> ThreadResponse:
     """Merge metadata into a thread record."""
-    from app.gateway.deps import get_thread_store
+    from app.gateway.deps import get_thread_meta_repo
 
-    thread_store = get_thread_store(request)
-    record = await thread_store.get(thread_id)
+    thread_meta_repo = get_thread_meta_repo(request)
+    record = await thread_meta_repo.get(thread_id)
     if record is None:
         raise HTTPException(status_code=404, detail=f"Thread {thread_id} not found")
 
-    # ``body.metadata`` already stripped by ``ThreadPatchRequest._strip_reserved``.
     try:
-        await thread_store.update_metadata(thread_id, body.metadata)
+        await thread_meta_repo.update_metadata(thread_id, body.metadata)
     except Exception:
         logger.exception("Failed to patch thread %s", sanitize_log_param(thread_id))
         raise HTTPException(status_code=500, detail="Failed to update thread")
 
     # Re-read to get the merged metadata + refreshed updated_at
-    record = await thread_store.get(thread_id) or record
+    record = await thread_meta_repo.get(thread_id) or record
     return ThreadResponse(
         thread_id=thread_id,
         status=record.get("status", "idle"),
@@ -356,12 +331,12 @@ async def get_thread(thread_id: str, request: Request) -> ThreadResponse:
     execution status from the checkpointer.  Falls back to the checkpointer
     alone for threads that pre-date ThreadMetaStore adoption (backward compat).
     """
-    from app.gateway.deps import get_thread_store
+    from app.gateway.deps import get_thread_meta_repo
 
-    thread_store = get_thread_store(request)
+    thread_meta_repo = get_thread_meta_repo(request)
     checkpointer = get_checkpointer(request)
 
-    record: dict | None = await thread_store.get(thread_id)
+    record: dict | None = await thread_meta_repo.get(thread_id)
 
     # Derive accurate status from the checkpointer
     config = {"configurable": {"thread_id": thread_id, "checkpoint_ns": ""}}
@@ -404,7 +379,6 @@ async def get_thread(thread_id: str, request: Request) -> ThreadResponse:
     )
 
 
-# ---------------------------------------------------------------------------
 @router.get("/{thread_id}/state", response_model=ThreadStateResponse)
 @require_permission("threads", "read", owner_check=True)
 async def get_thread_state(thread_id: str, request: Request) -> ThreadStateResponse:
@@ -443,10 +417,8 @@ async def get_thread_state(thread_id: str, request: Request) -> ThreadStateRespo
     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]
 
-    values = serialize_channel_values(channel_values)
-
     return ThreadStateResponse(
-        values=values,
+        values=serialize_channel_values(channel_values),
         next=next_tasks,
         metadata=metadata,
         checkpoint={"id": checkpoint_id, "ts": str(metadata.get("created_at", ""))},
@@ -458,7 +430,7 @@ async def get_thread_state(thread_id: str, request: Request) -> ThreadStateRespo
 
 
 @router.post("/{thread_id}/state", response_model=ThreadStateResponse)
-@require_permission("threads", "write", owner_check=True, require_existing=True)
+@require_permission("threads", "write", owner_check=True)
 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).
 
@@ -467,10 +439,10 @@ async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, re
     ThreadMetaStore abstraction so that ``/threads/search`` reflects the
     change immediately in both sqlite and memory backends.
     """
-    from app.gateway.deps import get_thread_store
+    from app.gateway.deps import get_thread_meta_repo
 
     checkpointer = get_checkpointer(request)
-    thread_store = get_thread_store(request)
+    thread_meta_repo = get_thread_meta_repo(request)
 
     # checkpoint_ns must be present in the config for aput — default to ""
     # (the root graph namespace).  checkpoint_id is optional; omitting it
@@ -534,7 +506,7 @@ async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, re
         new_title = body.values["title"]
         if new_title:  # Skip empty strings and None
             try:
-                await thread_store.update_display_name(thread_id, new_title)
+                await thread_meta_repo.update_display_name(thread_id, new_title)
             except Exception:
                 logger.debug("Failed to sync title to thread_meta for %s (non-fatal)", sanitize_log_param(thread_id))
 
@@ -587,7 +559,7 @@ async def get_thread_history(thread_id: str, body: ThreadHistoryRequest, request
             if thread_data := channel_values.get("thread_data"):
                 values["thread_data"] = thread_data
 
-            # Attach messages only to the latest checkpoint entry.
+            # Attach messages from checkpointer only for the latest checkpoint
             if is_latest_checkpoint:
                 messages = channel_values.get("messages")
                 if messages:

backend/app/gateway/routers/uploads.py

@@ -9,7 +9,6 @@ from pydantic import BaseModel
 
 from app.gateway.authz import require_permission
 from deerflow.config.paths import get_paths
-from deerflow.runtime.user_context import get_effective_user_id
 from deerflow.sandbox.sandbox_provider import get_sandbox_provider
 from deerflow.uploads.manager import (
     PathTraversalError,
@@ -56,7 +55,7 @@ def _make_file_sandbox_writable(file_path: os.PathLike[str] | str) -> None:
 
 
 @router.post("", response_model=UploadResponse)
-@require_permission("threads", "write", owner_check=True, require_existing=False)
+@require_permission("threads", "write", owner_check=True)
 async def upload_files(
     thread_id: str,
     request: Request,
@@ -70,7 +69,7 @@ async def upload_files(
         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())
+    sandbox_uploads = get_paths().sandbox_uploads_dir(thread_id)
     uploaded_files = []
 
     sandbox_provider = get_sandbox_provider()
@@ -148,7 +147,7 @@ async def list_uploaded_files(thread_id: str, request: Request) -> dict:
     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())
+    sandbox_uploads = get_paths().sandbox_uploads_dir(thread_id)
     for f in result["files"]:
         f["path"] = str(sandbox_uploads / f["filename"])
 
@@ -156,7 +155,7 @@ async def list_uploaded_files(thread_id: str, request: Request) -> dict:
 
 
 @router.delete("/{filename}")
-@require_permission("threads", "delete", owner_check=True, require_existing=True)
+@require_permission("threads", "delete", owner_check=True)
 async def delete_uploaded_file(thread_id: str, filename: str, request: Request) -> dict:
     """Delete a file from a thread's uploads directory."""
     try:

backend/app/gateway/services.py

@@ -195,6 +195,21 @@ async def start_run(
 
     disconnect = DisconnectMode.cancel if body.on_disconnect == "cancel" else DisconnectMode.continue_
 
+    # Resolve follow_up_to_run_id: explicit from request, or auto-detect from latest successful run
+    follow_up_to_run_id = getattr(body, "follow_up_to_run_id", None)
+    if follow_up_to_run_id is None:
+        run_store = get_run_store(request)
+        try:
+            recent_runs = await run_store.list_by_thread(thread_id, limit=1)
+            if recent_runs and recent_runs[0].get("status") == "success":
+                follow_up_to_run_id = recent_runs[0]["run_id"]
+        except Exception:
+            pass  # Don't block run creation
+
+    # Enrich base context with per-run field
+    if follow_up_to_run_id:
+        run_ctx = dataclasses.replace(run_ctx, follow_up_to_run_id=follow_up_to_run_id)
+
     try:
         record = await run_mgr.create_or_reject(
             thread_id,
@@ -203,6 +218,7 @@ async def start_run(
             metadata=body.metadata or {},
             kwargs={"input": body.input, "config": body.config},
             multitask_strategy=body.multitask_strategy,
+            follow_up_to_run_id=follow_up_to_run_id,
         )
     except ConflictError as exc:
         raise HTTPException(status_code=409, detail=str(exc)) from exc
@@ -213,15 +229,15 @@ async def start_run(
     # even for threads that were never explicitly created via POST /threads
     # (e.g. stateless runs).
     try:
-        existing = await run_ctx.thread_store.get(thread_id)
+        existing = await run_ctx.thread_meta_repo.get(thread_id)
         if existing is None:
-            await run_ctx.thread_store.create(
+            await run_ctx.thread_meta_repo.create(
                 thread_id,
                 assistant_id=body.assistant_id,
                 metadata=body.metadata,
             )
         else:
-            await run_ctx.thread_store.update_status(thread_id, "running")
+            await run_ctx.thread_meta_repo.update_status(thread_id, "running")
     except Exception:
         logger.warning("Failed to upsert thread_meta for %s (non-fatal)", sanitize_log_param(thread_id))
 
@@ -269,7 +285,7 @@ async def start_run(
     record.task = task
 
     # Title sync is handled by worker.py's finally block which reads the
-    # title from the checkpoint and calls thread_store.update_display_name
+    # title from the checkpoint and calls thread_meta_repo.update_display_name
     # after the run completes.
 
     return record

backend/docs/API.md

@@ -86,7 +86,6 @@ Content-Type: application/json
     ]
   },
   "config": {
-    "recursion_limit": 100,
     "configurable": {
       "model_name": "gpt-4",
       "thinking_enabled": false,
@@ -101,21 +100,6 @@ Content-Type: application/json
 - Use: `values`, `messages-tuple`, `custom`, `updates`, `events`, `debug`, `tasks`, `checkpoints`
 - Do not use: `tools` (deprecated/invalid in current `langgraph-api` and will trigger schema validation errors)
 
-**Recursion Limit:**
-
-`config.recursion_limit` caps the number of graph steps LangGraph will execute
-in a single run. The `/api/langgraph/*` endpoints go straight to the LangGraph
-server and therefore inherit LangGraph's native default of **25**, which is
-too low for plan-mode or subagent-heavy runs — the agent typically errors out
-with `GraphRecursionError` after the first round of subagent results comes
-back, before the lead agent can synthesize the final answer.
-
-DeerFlow's own Gateway and IM-channel paths mitigate this by defaulting to
-`100` in `build_run_config` (see `backend/app/gateway/services.py`), but
-clients calling the LangGraph API directly must set `recursion_limit`
-explicitly in the request body. `100` matches the Gateway default and is a
-safe starting point; increase it if you run deeply nested subagent graphs.
-
 **Configurable Options:**
 - `model_name` (string): Override the default model
 - `thinking_enabled` (boolean): Enable extended thinking for supported models
@@ -642,14 +626,6 @@ curl -X POST http://localhost:2026/api/langgraph/threads/abc123/runs \
   -H "Content-Type: application/json" \
   -d '{
     "input": {"messages": [{"role": "user", "content": "Hello"}]},
-    "config": {
-      "recursion_limit": 100,
-      "configurable": {"model_name": "gpt-4"}
-    }
+    "config": {"configurable": {"model_name": "gpt-4"}}
   }'
 ```
-
-> The `/api/langgraph/*` endpoints bypass DeerFlow's Gateway and inherit
-> LangGraph's native `recursion_limit` default of 25, which is too low for
-> plan-mode or subagent runs. Set `config.recursion_limit` explicitly — see
-> the [Create Run](#create-run) section for details.

backend/docs/AUTH_TEST_DOCKER_GAP.md

@@ -1,77 +0,0 @@
-# Docker Test Gap (Section 七 7.4)
-
-This file documents the only **un-executed** test cases from
-`backend/docs/AUTH_TEST_PLAN.md` after the full release validation pass.
-
-## Why this gap exists
-
-The release validation environment (sg_dev: `10.251.229.92`) **does not have
-a Docker daemon installed**. The TC-DOCKER cases are container-runtime
-behavior tests that need an actual Docker engine to spin up
-`docker/docker-compose.yaml` services.
-
-```bash
-$ ssh sg_dev "which docker; docker --version"
-# (empty)
-# bash: docker: command not found
-```
-
-All other test plan sections were executed against either:
-- The local dev box (Mac, all services running locally), or
-- The deployed sg_dev instance (gateway + frontend + nginx via SSH tunnel)
-
-## Cases not executed
-
-| Case | Title | What it covers | Why not run |
-|---|---|---|---|
-| TC-DOCKER-01 | `users.db` volume persistence | Verify the `DEER_FLOW_HOME` bind mount survives container restart | needs `docker compose up` |
-| TC-DOCKER-02 | Session persistence across container restart | `AUTH_JWT_SECRET` env var keeps cookies valid after `docker compose down && up` | needs `docker compose down/up` |
-| TC-DOCKER-03 | Per-worker rate limiter divergence | Confirms in-process `_login_attempts` dict doesn't share state across `gunicorn` workers (4 by default in the compose file); known limitation, documented | needs multi-worker container |
-| TC-DOCKER-04 | IM channels skip AuthMiddleware | Verify Feishu/Slack/Telegram dispatchers run in-container against `http://langgraph:2024` without going through nginx | needs `docker logs` |
-| TC-DOCKER-05 | Admin credentials surfacing | **Updated post-simplify** — was "log scrape", now "0600 credential file in `DEER_FLOW_HOME`". The file-based behavior is already validated by TC-1.1 + TC-UPG-13 on sg_dev (non-Docker), so the only Docker-specific gap is verifying the volume mount carries the file out to the host | needs container + host volume |
-| TC-DOCKER-06 | Gateway-mode Docker deploy | `./scripts/deploy.sh --gateway` produces a 3-container topology (no `langgraph` container); same auth flow as standard mode | needs `docker compose --profile gateway` |
-
-## Coverage already provided by non-Docker tests
-
-The **auth-relevant** behavior in each Docker case is already exercised by
-the test cases that ran on sg_dev or local:
-
-| Docker case | Auth behavior covered by |
-|---|---|
-| TC-DOCKER-01 (volume persistence) | TC-REENT-01 on sg_dev (admin row survives gateway restart) — same SQLite file, just no container layer between |
-| TC-DOCKER-02 (session persistence) | TC-API-02/03/06 (cookie roundtrip), plus TC-REENT-04 (multi-cookie) — JWT verification is process-state-free, container restart is equivalent to `pkill uvicorn && uv run uvicorn` |
-| TC-DOCKER-03 (per-worker rate limit) | TC-GW-04 + TC-REENT-09 (single-worker rate limit + 5min expiry). The cross-worker divergence is an architectural property of the in-memory dict; no auth code path differs |
-| TC-DOCKER-04 (IM channels skip auth) | Code-level only: `app/channels/manager.py` uses `langgraph_sdk` directly with no cookie handling. The langgraph_auth handler is bypassed by going through SDK, not HTTP |
-| TC-DOCKER-05 (credential surfacing) | TC-1.1 on sg_dev (file at `~/deer-flow/backend/.deer-flow/admin_initial_credentials.txt`, mode 0600, password 22 chars) — the only Docker-unique step is whether the bind mount projects this path onto the host, which is a `docker compose` config check, not a runtime behavior change |
-| TC-DOCKER-06 (gateway-mode container) | Section 七 7.2 covered by TC-GW-01..05 + Section 二 (gateway-mode auth flow on sg_dev) — same Gateway code, container is just a packaging change |
-
-## Reproduction steps when Docker becomes available
-
-Anyone with `docker` + `docker compose` installed can reproduce the gap by
-running the test plan section verbatim. Pre-flight:
-
-```bash
-# Required on the host
-docker --version           # >=24.x
-docker compose version     # plugin >=2.x
-
-# Required env var (otherwise sessions reset on every container restart)
-echo "AUTH_JWT_SECRET=$(python3 -c 'import secrets; print(secrets.token_urlsafe(32))')" \
-  >> .env
-
-# Optional: pin DEER_FLOW_HOME to a stable host path
-echo "DEER_FLOW_HOME=$HOME/deer-flow-data" >> .env
-```
-
-Then run TC-DOCKER-01..06 from the test plan as written.
-
-## Decision log
-
-- **Not blocking the release.** The auth-relevant behavior in every Docker
-  case has an already-validated equivalent on bare metal. The gap is purely
-  about *container packaging* details (bind mounts, multi-worker, log
-  collection), not about whether the auth code paths work.
-- **TC-DOCKER-05 was updated in place** in `AUTH_TEST_PLAN.md` to reflect
-  the post-simplify reality (credentials file → 0600 file, no log leak).
-  The old "grep 'Password:' in docker logs" expectation would have failed
-  silently and given a false sense of coverage.

backend/docs/AUTH_TEST_PLAN.md

@@ -1478,28 +1478,13 @@ docker logs deer-flow-gateway 2>&1 | grep -E "ChannelManager|channel" | head -10
 
 **预期：** 无 auth 相关错误。渠道通过 `langgraph-sdk` 直连 LangGraph Server（`http://langgraph:2024`），不走 auth 层。
 
-#### TC-DOCKER-05: admin 密码写入 0600 凭证文件（不再走日志）
+#### TC-DOCKER-05: admin 密码在容器日志中可见
 
 ```bash
-# 凭证文件写在挂载到宿主机的 DEER_FLOW_HOME 下
-ls -la ${DEER_FLOW_HOME:-backend/.deer-flow}/admin_initial_credentials.txt
-# 预期文件权限: -rw------- (0600)
-
-cat ${DEER_FLOW_HOME:-backend/.deer-flow}/admin_initial_credentials.txt
-# 预期内容: email + password 行
-
-# 容器日志只输出文件路径，不输出密码本身
-docker logs deer-flow-gateway 2>&1 | grep -E "Credentials written to|Admin account"
-# 预期看到: "Credentials written to: /...../admin_initial_credentials.txt (mode 0600)"
-
-# 反向验证: 日志里 NEVER 出现明文密码
-docker logs deer-flow-gateway 2>&1 | grep -iE "Password: .{15,}" && echo "FAIL: leaked" || echo "OK: not leaked"
+docker logs deer-flow-gateway 2>&1 | grep "Password:"
 ```
 
-**预期：**
-- 凭证文件存在于 `DEER_FLOW_HOME` 下，权限 `0600`
-- 容器日志输出**路径**（不是密码本身），符合 CodeQL `py/clear-text-logging-sensitive-data` 规则
-- `grep "Password:"` 在日志中**应当无匹配**（旧行为已废弃，simplify pass 移除了日志泄露路径）
+**预期：** 首次启动时输出 admin 密码，运维可通过 `docker logs` 获取。
 
 #### TC-DOCKER-06: Gateway 模式 Docker 部署
 

backend/docs/CONFIGURATION.md

@@ -192,8 +192,8 @@ tools:
 ```
 
 **Built-in Tools**:
-- `web_search` - Search the web (DuckDuckGo, Tavily, Exa, InfoQuest, Firecrawl)
-- `web_fetch` - Fetch web pages (Jina AI, Exa, InfoQuest, Firecrawl)
+- `web_search` - Search the web (Tavily)
+- `web_fetch` - Fetch web pages (Jina AI)
 - `ls` - List directory contents
 - `read_file` - Read file contents
 - `write_file` - Write file contents

backend/docs/README.md

@@ -15,7 +15,6 @@ This directory contains detailed documentation for the DeerFlow backend.
 
 | Document | Description |
 |----------|-------------|
-| [STREAMING.md](STREAMING.md) | Token-level streaming design: Gateway vs DeerFlowClient paths, `stream_mode` semantics, per-id dedup |
 | [FILE_UPLOAD.md](FILE_UPLOAD.md) | File upload functionality |
 | [PATH_EXAMPLES.md](PATH_EXAMPLES.md) | Path types and usage examples |
 | [summarization.md](summarization.md) | Context summarization feature |
@@ -48,7 +47,6 @@ docs/
 ├── PATH_EXAMPLES.md           # Path usage examples
 ├── summarization.md           # Summarization feature
 ├── plan_mode_usage.md         # Plan mode feature
-├── STREAMING.md               # Token-level streaming design
 ├── AUTO_TITLE_GENERATION.md   # Title generation
 ├── TITLE_GENERATION_IMPLEMENTATION.md  # Title implementation details
 └── TODO.md                    # Roadmap and issues

backend/docs/STREAMING.md

@@ -1,351 +0,0 @@
-# DeerFlow 流式输出设计
-
-本文档解释 DeerFlow 是如何把 LangGraph agent 的事件流端到端送到两类消费者（HTTP 客户端、嵌入式 Python 调用方）的：两条路径为什么**必须**并存、它们各自的契约是什么、以及设计里那些 non-obvious 的不变式。
-
----
-
-## TL;DR
-
-- DeerFlow 有**两条并行**的流式路径：**Gateway 路径**（async / HTTP SSE / JSON 序列化）服务浏览器和 IM 渠道；**DeerFlowClient 路径**（sync / in-process / 原生 LangChain 对象）服务 Jupyter、脚本、测试。它们**无法合并**——消费者模型不同。
-- 两条路径都从 `create_agent()` 工厂出发，核心都是订阅 LangGraph 的 `stream_mode=["values", "messages", "custom"]`。`values` 是节点级 state 快照，`messages` 是 LLM token 级 delta，`custom` 是显式 `StreamWriter` 事件。**这三种模式不是详细程度的梯度，是三个独立的事件源**，要 token 流就必须显式订阅 `messages`。
-- 嵌入式 client 为每个 `stream()` 调用维护三个 `set[str]`：`seen_ids` / `streamed_ids` / `counted_usage_ids`。三者看起来相似但管理**三个独立的不变式**，不能合并。
-
----
-
-## 为什么有两条流式路径
-
-两条路径服务的消费者模型根本不同：
-
-| 维度 | Gateway 路径 | DeerFlowClient 路径 |
-|---|---|---|
-| 入口 | FastAPI `/runs/stream` endpoint | `DeerFlowClient.stream(message)` |
-| 触发层 | `runtime/runs/worker.py::run_agent` | `packages/harness/deerflow/client.py::DeerFlowClient.stream` |
-| 执行模型 | `async def` + `agent.astream()` | sync generator + `agent.stream()` |
-| 事件传输 | `StreamBridge`（asyncio Queue）+ `sse_consumer` | 直接 `yield` |
-| 序列化 | `serialize(chunk)` → 纯 JSON dict，匹配 LangGraph Platform wire 格式 | `StreamEvent.data`，携带原生 LangChain 对象 |
-| 消费者 | 前端 `useStream` React hook、飞书/Slack/Telegram channel、LangGraph SDK 客户端 | Jupyter notebook、集成测试、内部 Python 脚本 |
-| 生命周期管理 | `RunManager`：run_id 跟踪、disconnect 语义、multitask 策略、heartbeat | 无；函数返回即结束 |
-| 断连恢复 | `Last-Event-ID` SSE 重连 | 无需要 |
-
-**两条路径的存在是 DRY 的刻意妥协**：Gateway 的全部基础设施（async + Queue + JSON + RunManager）**都是为了跨网络边界把事件送给 HTTP 消费者**。当生产者（agent）和消费者（Python 调用栈）在同一个进程时，这整套东西都是纯开销。
-
-### 为什么不能让 DeerFlowClient 复用 Gateway
-
-曾经考虑过三种复用方案，都被否决：
-
-1. **让 `client.stream()` 变成 `async def client.astream()`**  
-   breaking change。用户用不上的 `async for` / `asyncio.run()` 要硬塞进 Jupyter notebook 和同步脚本。DeerFlowClient 的一大卖点（"把 agent 当普通函数调用"）直接消失。
-
-2. **在 `client.stream()` 内部起一个独立事件循环线程，用 `StreamBridge` 在 sync/async 之间做桥接**  
-   引入线程池、队列、信号量。为了"消除重复"，把**复杂度**代替代码行数引进来。是典型的"wrong abstraction"——开销高于复用收益。
-
-3. **让 `run_agent` 自己兼容 sync mode**  
-   给 Gateway 加一条用不到的死分支，污染 worker.py 的焦点。
-
-所以两条路径的事件处理逻辑会**相似但不共享**。这是刻意设计，不是疏忽。
-
----
-
-## LangGraph `stream_mode` 三层语义
-
-LangGraph 的 `agent.stream(stream_mode=[...])` 是**多路复用**接口：一次订阅多个 mode，每个 mode 是一个独立的事件源。三种核心 mode：
-
-```mermaid
-flowchart LR
-    classDef values fill:#B8C5D1,stroke:#5A6B7A,color:#2C3E50
-    classDef messages fill:#C9B8A8,stroke:#7A6B5A,color:#2C3E50
-    classDef custom fill:#B5C4B1,stroke:#5A7A5A,color:#2C3E50
-
-    subgraph LG["LangGraph agent graph"]
-        direction TB
-        Node1["node: LLM call"]
-        Node2["node: tool call"]
-        Node3["node: reducer"]
-    end
-
-    LG -->|"每个节点完成后"| V["values: 完整 state 快照"]
-    Node1 -->|"LLM 每产生一个 token"| M["messages: (AIMessageChunk, meta)"]
-    Node1 -->|"StreamWriter.write()"| C["custom: 任意 dict"]
-
-    class V values
-    class M messages
-    class C custom
-```
-
-| Mode | 发射时机 | Payload | 粒度 |
-|---|---|---|---|
-| `values` | 每个 graph 节点完成后 | 完整 state dict（title、messages、artifacts）| 节点级 |
-| `messages` | LLM 每次 yield 一个 chunk；tool 节点完成时 | `(AIMessageChunk \| ToolMessage, metadata_dict)` | token 级 |
-| `custom` | 用户代码显式调用 `StreamWriter.write()` | 任意 dict | 应用定义 |
-
-### 两套命名的由来
-
-同一件事在**三个协议层**有三个名字：
-
-```
-Application                    HTTP / SSE                    LangGraph Graph
-┌──────────────┐               ┌──────────────┐              ┌──────────────┐
-│ frontend     │               │ LangGraph    │              │ agent.astream│
-│ useStream    │──"messages-   │ Platform SDK │──"messages"──│ graph.astream│
-│ Feishu IM    │   tuple"──────│ HTTP wire    │              │              │
-└──────────────┘               └──────────────┘              └──────────────┘
-```
-
-- **Graph 层**（`agent.stream` / `agent.astream`）：LangGraph Python 直接 API，mode 叫 **`"messages"`**。
-- **Platform SDK 层**（`langgraph-sdk` HTTP client）：跨进程 HTTP 契约，mode 叫 **`"messages-tuple"`**。
-- **Gateway worker** 显式做翻译：`if m == "messages-tuple": lg_modes.append("messages")`（`runtime/runs/worker.py:117-121`）。
-
-**后果**：`DeerFlowClient.stream()` 直接调 `agent.stream()`（Graph 层），所以必须传 `"messages"`。`app/channels/manager.py` 通过 `langgraph-sdk` 走 HTTP SDK，所以传 `"messages-tuple"`。**这两个字符串不能互相替代**，也不能抽成"一个共享常量"——它们是不同协议层的 type alias，共享只会让某一层说不是它母语的话。
-
----
-
-## Gateway 路径：async + HTTP SSE
-
-```mermaid
-sequenceDiagram
-    participant Client as HTTP Client
-    participant API as FastAPI<br/>thread_runs.py
-    participant Svc as services.py<br/>start_run
-    participant Worker as worker.py<br/>run_agent (async)
-    participant Bridge as StreamBridge<br/>(asyncio.Queue)
-    participant Agent as LangGraph<br/>agent.astream
-    participant SSE as sse_consumer
-
-    Client->>API: POST /runs/stream
-    API->>Svc: start_run(body)
-    Svc->>Bridge: create bridge
-    Svc->>Worker: asyncio.create_task(run_agent(...))
-    Svc-->>API: StreamingResponse(sse_consumer)
-    API-->>Client: event-stream opens
-
-    par worker (producer)
-        Worker->>Agent: astream(stream_mode=lg_modes)
-        loop 每个 chunk
-            Agent-->>Worker: (mode, chunk)
-            Worker->>Bridge: publish(run_id, event, serialize(chunk))
-        end
-        Worker->>Bridge: publish_end(run_id)
-    and sse_consumer (consumer)
-        SSE->>Bridge: subscribe(run_id)
-        loop 每个 event
-            Bridge-->>SSE: StreamEvent
-            SSE-->>Client: "event: <name>\ndata: <json>\n\n"
-        end
-    end
-```
-
-关键组件：
-
-- `runtime/runs/worker.py::run_agent` — 在 `asyncio.Task` 里跑 `agent.astream()`，把每个 chunk 通过 `serialize(chunk, mode=mode)` 转成 JSON，再 `bridge.publish()`。
-- `runtime/stream_bridge` — 抽象 Queue。`publish/subscribe` 解耦生产者和消费者，支持 `Last-Event-ID` 重连、心跳、多订阅者 fan-out。
-- `app/gateway/services.py::sse_consumer` — 从 bridge 订阅，格式化为 SSE wire 帧。
-- `runtime/serialization.py::serialize` — mode-aware 序列化；`messages` mode 下 `serialize_messages_tuple` 把 `(chunk, metadata)` 转成 `[chunk.model_dump(), metadata]`。
-
-**`StreamBridge` 的存在价值**：当生产者（`run_agent` 任务）和消费者（HTTP 连接）在不同的 asyncio task 里运行时，需要一个可以跨 task 传递事件的中介。Queue 同时还承担断连重连的 buffer 和多订阅者的 fan-out。
-
----
-
-## DeerFlowClient 路径：sync + in-process
-
-```mermaid
-sequenceDiagram
-    participant User as Python caller
-    participant Client as DeerFlowClient.stream
-    participant Agent as LangGraph<br/>agent.stream (sync)
-
-    User->>Client: for event in client.stream("hi"):
-    Client->>Agent: stream(stream_mode=["values","messages","custom"])
-    loop 每个 chunk
-        Agent-->>Client: (mode, chunk)
-        Client->>Client: 分发 mode<br/>构建 StreamEvent
-        Client-->>User: yield StreamEvent
-    end
-    Client-->>User: yield StreamEvent(type="end")
-```
-
-对比之下，sync 路径的每个环节都是显著更少的移动部件：
-
-- 没有 `RunManager` —— 一次 `stream()` 调用对应一次生命周期，无需 run_id。
-- 没有 `StreamBridge` —— 直接 `yield`，生产和消费在同一个 Python 调用栈，不需要跨 task 中介。
-- 没有 JSON 序列化 —— `StreamEvent.data` 直接装原生 LangChain 对象（`AIMessage.content`、`usage_metadata` 的 `UsageMetadata` TypedDict）。Jupyter 用户拿到的是真正的类型，不是匿名 dict。
-- 没有 asyncio —— 调用者可以直接 `for event in ...`，不必写 `async for`。
-
----
-
-## 消费语义：delta vs cumulative
-
-LangGraph `messages` mode 给出的是 **delta**：每个 `AIMessageChunk.content` 只包含这一次新 yield 的 token，**不是**从头的累计文本。
-
-这个语义和 LangChain 的 `fs2 Stream` 风格一致：**上游发增量，下游负责累加**。Gateway 路径里前端 `useStream` React hook 自己维护累加器；DeerFlowClient 路径里 `chat()` 方法替调用者做累加。
-
-### `DeerFlowClient.chat()` 的 O(n) 累加器
-
-```python
-chunks: dict[str, list[str]] = {}
-last_id: str = ""
-for event in self.stream(message, thread_id=thread_id, **kwargs):
-    if event.type == "messages-tuple" and event.data.get("type") == "ai":
-        msg_id = event.data.get("id") or ""
-        delta = event.data.get("content", "")
-        if delta:
-            chunks.setdefault(msg_id, []).append(delta)
-            last_id = msg_id
-return "".join(chunks.get(last_id, ()))
-```
-
-**为什么不是 `buffers[id] = buffers.get(id,"") + delta`**：CPython 的字符串 in-place concat 优化仅在 refcount=1 且 LHS 是 local name 时生效；这里字符串存在 dict 里被 reassign，优化失效，每次都是 O(n) 拷贝 → 总体 O(n²)。实测 50 KB / 5000 chunk 的回复要 100-300ms 纯拷贝开销。用 `list` + `"".join()` 是 O(n)。
-
----
-
-## 三个 id set 为什么不能合并
-
-`DeerFlowClient.stream()` 在一次调用生命周期内维护三个 `set[str]`：
-
-```python
-seen_ids: set[str] = set()           # values 路径内部 dedup
-streamed_ids: set[str] = set()       # messages → values 跨模式 dedup
-counted_usage_ids: set[str] = set()  # usage_metadata 幂等计数
-```
-
-乍看像是"三份几乎一样的东西"，实际每个管**不同的不变式**。
-
-| Set | 负责的不变式 | 被谁填充 | 被谁查询 |
-|---|---|---|---|
-| `seen_ids` | 连续两个 `values` 快照里同一条 message 只生成一个 `messages-tuple` 事件 | values 分支每处理一条消息就加入 | values 分支处理下一条消息前检查 |
-| `streamed_ids` | 如果一条消息已经通过 `messages` 模式 token 级流过，values 快照到达时**不要**再合成一次完整 `messages-tuple` | messages 分支每发一个 AI/tool 事件就加入 | values 分支看到消息时检查 |
-| `counted_usage_ids` | 同一个 `usage_metadata` 在 messages 末尾 chunk 和 values 快照的 final AIMessage 里各带一份，**累计总量只算一次** | `_account_usage()` 每次接受 usage 就加入 | `_account_usage()` 每次调用时检查 |
-
-### 为什么不能只用一个 set
-
-关键观察：**同一个 message id 在这三个 set 里的加入时机不同**。
-
-```mermaid
-sequenceDiagram
-    participant M as messages mode
-    participant V as values mode
-    participant SS as streamed_ids
-    participant SU as counted_usage_ids
-    participant SE as seen_ids
-
-    Note over M: 第一个 AI text chunk 到达
-    M->>SS: add(msg_id)
-    Note over M: 最后一个 chunk 带 usage
-    M->>SU: add(msg_id)
-    Note over V: snapshot 到达，包含同一条 AI message
-    V->>SE: add(msg_id)
-    V->>SS: 查询 → 已存在，跳过文本合成
-    V->>SU: 查询 → 已存在，不重复计数
-```
-
-- `seen_ids` **永远在 values 快照到达时**加入，所以它是 "values 已处理" 的标记。一条只出现在 messages 流里的消息（罕见但可能），`seen_ids` 里永远没有它。
-- `streamed_ids` **在 messages 流的第一个有效事件时**加入。一条只通过 values 快照到达的非 AI 消息（HumanMessage、被 truncate 的 tool 消息），`streamed_ids` 里永远没有它。
-- `counted_usage_ids` **只在看到非空 `usage_metadata` 时**加入。一条完全没有 usage 的消息（tool message、错误消息）永远不会进去。
-
-**集合包含关系**：`counted_usage_ids ⊆ (streamed_ids ∪ seen_ids)` 大致成立，但**不是严格子集**，因为一条消息可以在 messages 模式流完 text 但**在最后那个带 usage 的 chunk 之前**就被 values snapshot 赶上——此时它已经在 `streamed_ids` 里，但还不在 `counted_usage_ids` 里。把它们合并成一个 dict-of-flags 会让这个微妙的时序依赖**从类型系统里消失**，变成注释里的一句话。三个独立的 set 把不变式显式化了：每个 set 名对应一个可以口头回答的问题。
-
----
-
-## 端到端：一次真实对话的事件时序
-
-假设调用 `client.stream("Count from 1 to 15")`，LLM 给出 "one\ntwo\n...\nfifteen"（88 字符），tokenizer 把它拆成 ~35 个 BPE chunk。下面是事件到达序列的精简版：
-
-```mermaid
-sequenceDiagram
-    participant U as User
-    participant C as DeerFlowClient
-    participant A as LangGraph<br/>agent.stream
-
-    U->>C: stream("Count ... 15")
-    C->>A: stream(mode=["values","messages","custom"])
-
-    A-->>C: ("values", {messages: [HumanMessage]})
-    C-->>U: StreamEvent(type="values", ...)
-
-    Note over A,C: LLM 开始 yield token
-    loop 35 次，约 476ms
-        A-->>C: ("messages", (AIMessageChunk(content="ele"), meta))
-        C->>C: streamed_ids.add(ai-1)
-        C-->>U: StreamEvent(type="messages-tuple",<br/>data={type:ai, content:"ele", id:ai-1})
-    end
-
-    Note over A: LLM finish_reason=stop，最后一个 chunk 带 usage
-    A-->>C: ("messages", (AIMessageChunk(content="", usage_metadata={...}), meta))
-    C->>C: counted_usage_ids.add(ai-1)<br/>(无文本，不 yield)
-
-    A-->>C: ("values", {messages: [..., AIMessage(complete)]})
-    C->>C: ai-1 in streamed_ids → 跳过合成
-    C->>C: 捕获 usage (已在 counted_usage_ids，no-op)
-    C-->>U: StreamEvent(type="values", ...)
-
-    C-->>U: StreamEvent(type="end", data={usage:{...}})
-```
-
-关键观察：
-
-1. 用户看到 **35 个 messages-tuple 事件**，跨越约 476ms，每个事件带一个 token delta 和同一个 `id=ai-1`。
-2. 最后一个 `values` 快照里的 `AIMessage` **不会**再触发一个完整的 `messages-tuple` 事件——因为 `ai-1 in streamed_ids` 跳过了合成。
-3. `end` 事件里的 `usage` 正好等于那一份 cumulative usage，**不是它的两倍**——`counted_usage_ids` 在 messages 末尾 chunk 上已经吸收了，values 分支的重复访问是 no-op。
-4. 消费者拿到的 `content` 是**增量**："ele" 只包含 3 个字符，不是 "one\ntwo\n...ele"。想要完整文本要按 `id` 累加，`chat()` 已经帮你做了。
-
----
-
-## 为什么这个设计容易出 bug，以及测试策略
-
-本文档的直接起因是 bytedance/deer-flow#1969：`DeerFlowClient.stream()` 原本只订阅 `["values", "custom"]`，**漏了 `"messages"`**。结果 `client.stream("hello")` 等价于一次性返回，视觉上和 `chat()` 没区别。
-
-这类 bug 有三个结构性原因：
-
-1. **多协议层命名**：`messages` / `messages-tuple` / HTTP SSE `messages` 是同一概念的三个名字。在其中一层出错不会在另外两层报错。
-2. **多消费者模型**：Gateway 和 DeerFlowClient 是两套独立实现，**没有单一的"订阅哪些 mode"的 single source of truth**。前者订阅对了不代表后者也订阅对了。
-3. **mock 测试绕开了真实路径**：老测试用 `agent.stream.return_value = iter([dict_chunk, ...])` 喂 values 形状的 dict 模拟 state 快照。这样构造的输入**永远不会进入 `messages` mode 分支**，所以即使 `stream_mode` 里少一个元素，CI 依然全绿。
-
-### 防御手段
-
-真正的防线是**显式断言 "messages" mode 被订阅 + 用真实 chunk shape mock**：
-
-```python
-# tests/test_client.py::test_messages_mode_emits_token_deltas
-agent.stream.return_value = iter([
-    ("messages", (AIMessageChunk(content="Hel", id="ai-1"), {})),
-    ("messages", (AIMessageChunk(content="lo ", id="ai-1"), {})),
-    ("messages", (AIMessageChunk(content="world!", id="ai-1"), {})),
-    ("values", {"messages": [HumanMessage(...), AIMessage(content="Hello world!", id="ai-1")]}),
-])
-# ...
-assert [e.data["content"] for e in ai_text_events] == ["Hel", "lo ", "world!"]
-assert len(ai_text_events) == 3  # values snapshot must NOT re-synthesize
-assert "messages" in agent.stream.call_args.kwargs["stream_mode"]
-```
-
-**为什么这比"抽一个共享常量"更有效**：共享常量只能保证"用它的人写对字符串"，但新增消费者的人可能根本不知道常量在哪。行为断言强制任何改动都要穿过**实际执行路径**，改回 `["values", "custom"]` 会立刻让 `assert "messages" in ...` 失败。
-
-### 活体信号：BPE 子词边界
-
-回归的最终验证是让真实 LLM 数 1-15，然后看是否能在输出里看到 tokenizer 的子词切分：
-
-```
-[5.460s] 'ele' / 'ven'      eleven 被拆成两个 token
-[5.508s] 'tw'  / 'elve'     twelve 拆两个
-[5.568s] 'th'  / 'irteen'   thirteen 拆两个
-[5.623s] 'four'/ 'teen'     fourteen 拆两个
-[5.677s] 'f'   / 'if' / 'teen'  fifteen 拆三个
-```
-
-子词切分是 tokenizer 的外部事实，**无法伪造**。能看到它就说明数据流**逐 chunk** 地穿过了整条管道，没有被任何中间层缓冲成整段。这种"活体信号"在流式系统里是比单元测试更高置信度的证据。
-
----
-
-## 相关源码定位
-
-| 关心什么 | 看这里 |
-|---|---|
-| DeerFlowClient 嵌入式流 | `packages/harness/deerflow/client.py::DeerFlowClient.stream` |
-| `chat()` 的 delta 累加器 | `packages/harness/deerflow/client.py::DeerFlowClient.chat` |
-| Gateway async 流 | `packages/harness/deerflow/runtime/runs/worker.py::run_agent` |
-| HTTP SSE 帧输出 | `app/gateway/services.py::sse_consumer` / `format_sse` |
-| 序列化到 wire 格式 | `packages/harness/deerflow/runtime/serialization.py` |
-| LangGraph mode 命名翻译 | `packages/harness/deerflow/runtime/runs/worker.py:117-121` |
-| 飞书渠道的增量卡片更新 | `app/channels/manager.py::_handle_streaming_chat` |
-| Channels 自带的 delta/cumulative 防御性累加 | `app/channels/manager.py::_merge_stream_text` |
-| Frontend useStream 支持的 mode 集合 | `frontend/src/core/api/stream-mode.ts` |
-| 核心回归测试 | `backend/tests/test_client.py::TestStream::test_messages_mode_emits_token_deltas` |

backend/docs/TITLE_GENERATION_IMPLEMENTATION.md

@@ -124,7 +124,7 @@ title:
 # checkpointer.py
 from langgraph.checkpoint.sqlite import SqliteSaver
 
-checkpointer = SqliteSaver.from_conn_string("deerflow.db")
+checkpointer = SqliteSaver.from_conn_string("checkpoints.db")
 ```
 
 ```json

backend/packages/harness/deerflow/agents/__init__.py

@@ -1,14 +1,9 @@
+from .checkpointer import get_checkpointer, make_checkpointer, reset_checkpointer
 from .factory import create_deerflow_agent
 from .features import Next, Prev, RuntimeFeatures
 from .lead_agent import make_lead_agent
-from .lead_agent.prompt import prime_enabled_skills_cache
 from .thread_state import SandboxState, ThreadState
 
-# LangGraph imports deerflow.agents when registering the graph. Prime the
-# enabled-skills cache here so the request path can usually read a warm cache
-# without forcing synchronous filesystem work during prompt module import.
-prime_enabled_skills_cache()
-
 __all__ = [
     "create_deerflow_agent",
     "RuntimeFeatures",
@@ -17,4 +12,7 @@ __all__ = [
     "make_lead_agent",
     "SandboxState",
     "ThreadState",
+    "get_checkpointer",
+    "reset_checkpointer",
+    "make_checkpointer",
 ]

backend/packages/harness/deerflow/agents/checkpointer/async_provider.py

@@ -7,29 +7,28 @@ Supported backends: memory, sqlite, postgres.
 
 Usage (e.g. FastAPI lifespan)::
 
-    from deerflow.runtime.checkpointer.async_provider import make_checkpointer
+    from deerflow.agents.checkpointer.async_provider import make_checkpointer
 
     async with make_checkpointer() as checkpointer:
         app.state.checkpointer = checkpointer  # InMemorySaver if not configured
 
-For sync usage see :mod:`deerflow.runtime.checkpointer.provider`.
+For sync usage see :mod:`deerflow.agents.checkpointer.provider`.
 """
 
 from __future__ import annotations
 
-import asyncio
 import contextlib
 import logging
 from collections.abc import AsyncIterator
 
 from langgraph.types import Checkpointer
 
-from deerflow.config.app_config import get_app_config
-from deerflow.runtime.checkpointer.provider import (
+from deerflow.agents.checkpointer.provider import (
     POSTGRES_CONN_REQUIRED,
     POSTGRES_INSTALL,
     SQLITE_INSTALL,
 )
+from deerflow.config.app_config import get_app_config
 from deerflow.runtime.store._sqlite_utils import ensure_sqlite_parent_dir, resolve_sqlite_conn_str
 
 logger = logging.getLogger(__name__)
@@ -55,7 +54,7 @@ async def _async_checkpointer(config) -> AsyncIterator[Checkpointer]:
             raise ImportError(SQLITE_INSTALL) from exc
 
         conn_str = resolve_sqlite_conn_str(config.connection_string or "store.db")
-        await asyncio.to_thread(ensure_sqlite_parent_dir, conn_str)
+        ensure_sqlite_parent_dir(conn_str)
         async with AsyncSqliteSaver.from_conn_string(conn_str) as saver:
             await saver.setup()
             yield saver

backend/packages/harness/deerflow/agents/checkpointer/provider.py

@@ -7,7 +7,7 @@ Supported backends: memory, sqlite, postgres.
 
 Usage::
 
-    from deerflow.runtime.checkpointer.provider import get_checkpointer, checkpointer_context
+    from deerflow.agents.checkpointer.provider import get_checkpointer, checkpointer_context
 
     # Singleton — reused across calls, closed on process exit
     cp = get_checkpointer()

backend/packages/harness/deerflow/agents/lead_agent/agent.py

@@ -1,7 +1,7 @@
 import logging
 
 from langchain.agents import create_agent
-from langchain.agents.middleware import AgentMiddleware
+from langchain.agents.middleware import AgentMiddleware, SummarizationMiddleware
 from langchain_core.runnables import RunnableConfig
 
 from deerflow.agents.lead_agent.prompt import apply_prompt_template
@@ -9,7 +9,6 @@ from deerflow.agents.middlewares.clarification_middleware import ClarificationMi
 from deerflow.agents.middlewares.loop_detection_middleware import LoopDetectionMiddleware
 from deerflow.agents.middlewares.memory_middleware import MemoryMiddleware
 from deerflow.agents.middlewares.subagent_limit_middleware import SubagentLimitMiddleware
-from deerflow.agents.middlewares.summarization_middleware import SummarizationMiddleware
 from deerflow.agents.middlewares.title_middleware import TitleMiddleware
 from deerflow.agents.middlewares.todo_middleware import TodoMiddleware
 from deerflow.agents.middlewares.token_usage_middleware import TokenUsageMiddleware
@@ -290,14 +289,14 @@ def make_lead_agent(config: RunnableConfig):
     agent_name = cfg.get("agent_name")
 
     agent_config = load_agent_config(agent_name) if not is_bootstrap else None
-    # Custom agent model from agent config (if any), or None to let _resolve_model_name pick the default
-    agent_model_name = agent_config.model if agent_config and agent_config.model else None
+    # Custom agent model or fallback to global/default model resolution
+    agent_model_name = agent_config.model if agent_config and agent_config.model else _resolve_model_name()
 
-    # Final model name resolution: request → agent config → global default, with fallback for unknown names
-    model_name = _resolve_model_name(requested_model_name or agent_model_name)
+    # Final model name resolution with request override, then agent config, then global default
+    model_name = requested_model_name or agent_model_name
 
     app_config = get_app_config()
-    model_config = app_config.get_model_config(model_name)
+    model_config = app_config.get_model_config(model_name) if model_name else None
 
     if model_config is None:
         raise ValueError("No chat model could be resolved. Please configure at least one model in config.yaml or provide a valid 'model_name'/'model' in the request.")

backend/packages/harness/deerflow/agents/lead_agent/prompt.py

@@ -1,114 +1,20 @@
-import asyncio
 import logging
-import threading
 from datetime import datetime
 from functools import lru_cache
 
 from deerflow.config.agents_config import load_agent_soul
 from deerflow.skills import load_skills
-from deerflow.skills.types import Skill
 from deerflow.subagents import get_available_subagent_names
 
 logger = logging.getLogger(__name__)
 
-_ENABLED_SKILLS_REFRESH_WAIT_TIMEOUT_SECONDS = 5.0
-_enabled_skills_lock = threading.Lock()
-_enabled_skills_cache: list[Skill] | None = None
-_enabled_skills_refresh_active = False
-_enabled_skills_refresh_version = 0
-_enabled_skills_refresh_event = threading.Event()
-
-
-def _load_enabled_skills_sync() -> list[Skill]:
-    return list(load_skills(enabled_only=True))
-
-
-def _start_enabled_skills_refresh_thread() -> None:
-    threading.Thread(
-        target=_refresh_enabled_skills_cache_worker,
-        name="deerflow-enabled-skills-loader",
-        daemon=True,
-    ).start()
-
-
-def _refresh_enabled_skills_cache_worker() -> None:
-    global _enabled_skills_cache, _enabled_skills_refresh_active
-
-    while True:
-        with _enabled_skills_lock:
-            target_version = _enabled_skills_refresh_version
-
-        try:
-            skills = _load_enabled_skills_sync()
-        except Exception:
-            logger.exception("Failed to load enabled skills for prompt injection")
-            skills = []
-
-        with _enabled_skills_lock:
-            if _enabled_skills_refresh_version == target_version:
-                _enabled_skills_cache = skills
-                _enabled_skills_refresh_active = False
-                _enabled_skills_refresh_event.set()
-                return
-
-            # A newer invalidation happened while loading. Keep the worker alive
-            # and loop again so the cache always converges on the latest version.
-            _enabled_skills_cache = None
-
-
-def _ensure_enabled_skills_cache() -> threading.Event:
-    global _enabled_skills_refresh_active
-
-    with _enabled_skills_lock:
-        if _enabled_skills_cache is not None:
-            _enabled_skills_refresh_event.set()
-            return _enabled_skills_refresh_event
-        if _enabled_skills_refresh_active:
-            return _enabled_skills_refresh_event
-        _enabled_skills_refresh_active = True
-        _enabled_skills_refresh_event.clear()
-
-    _start_enabled_skills_refresh_thread()
-    return _enabled_skills_refresh_event
-
-
-def _invalidate_enabled_skills_cache() -> threading.Event:
-    global _enabled_skills_cache, _enabled_skills_refresh_active, _enabled_skills_refresh_version
-
-    _get_cached_skills_prompt_section.cache_clear()
-    with _enabled_skills_lock:
-        _enabled_skills_cache = None
-        _enabled_skills_refresh_version += 1
-        _enabled_skills_refresh_event.clear()
-        if _enabled_skills_refresh_active:
-            return _enabled_skills_refresh_event
-        _enabled_skills_refresh_active = True
-
-    _start_enabled_skills_refresh_thread()
-    return _enabled_skills_refresh_event
-
-
-def prime_enabled_skills_cache() -> None:
-    _ensure_enabled_skills_cache()
-
-
-def warm_enabled_skills_cache(timeout_seconds: float = _ENABLED_SKILLS_REFRESH_WAIT_TIMEOUT_SECONDS) -> bool:
-    if _ensure_enabled_skills_cache().wait(timeout=timeout_seconds):
-        return True
-
-    logger.warning("Timed out waiting %.1fs for enabled skills cache warm-up", timeout_seconds)
-    return False
-
 
 def _get_enabled_skills():
-    with _enabled_skills_lock:
-        cached = _enabled_skills_cache
-
-    if cached is not None:
-        return list(cached)
-
-    _ensure_enabled_skills_cache()
-    return []
+    try:
+        return list(load_skills(enabled_only=True))
+    except Exception:
+        logger.exception("Failed to load enabled skills for prompt injection")
+        return []
 
 
 def _skill_mutability_label(category: str) -> str:
@@ -116,36 +22,7 @@ def _skill_mutability_label(category: str) -> str:
 
 
 def clear_skills_system_prompt_cache() -> None:
-    _invalidate_enabled_skills_cache()
-
-
-async def refresh_skills_system_prompt_cache_async() -> None:
-    await asyncio.to_thread(_invalidate_enabled_skills_cache().wait)
-
-
-def _reset_skills_system_prompt_cache_state() -> None:
-    global _enabled_skills_cache, _enabled_skills_refresh_active, _enabled_skills_refresh_version
-
     _get_cached_skills_prompt_section.cache_clear()
-    with _enabled_skills_lock:
-        _enabled_skills_cache = None
-        _enabled_skills_refresh_active = False
-        _enabled_skills_refresh_version = 0
-        _enabled_skills_refresh_event.clear()
-
-
-def _refresh_enabled_skills_cache() -> None:
-    """Backward-compatible test helper for direct synchronous reload."""
-    try:
-        skills = _load_enabled_skills_sync()
-    except Exception:
-        logger.exception("Failed to load enabled skills for prompt injection")
-        skills = []
-
-    with _enabled_skills_lock:
-        _enabled_skills_cache = skills
-        _enabled_skills_refresh_active = False
-        _enabled_skills_refresh_event.set()
 
 
 def _build_skill_evolution_section(skill_evolution_enabled: bool) -> str:
@@ -417,9 +294,6 @@ You: "Deploying to staging..." [proceed]
 - Use `read_file` tool to read uploaded files using their paths from the list
 - For PDF, PPT, Excel, and Word files, converted Markdown versions (*.md) are available alongside originals
 - All temporary work happens in `/mnt/user-data/workspace`
-- Treat `/mnt/user-data/workspace` as your default current working directory for coding and file-editing tasks
-- When writing scripts or commands that create/read files from the workspace, prefer relative paths such as `hello.txt`, `../uploads/data.csv`, and `../outputs/report.md`
-- Avoid hardcoding `/mnt/user-data/...` inside generated scripts when a relative path from the workspace is enough
 - Final deliverables must be copied to `/mnt/user-data/outputs` and presented using `present_file` tool
 {acp_section}
 </working_directory>
@@ -519,13 +393,12 @@ def _get_memory_context(agent_name: str | None = None) -> str:
     try:
         from deerflow.agents.memory import format_memory_for_injection, get_memory_data
         from deerflow.config.memory_config import get_memory_config
-        from deerflow.runtime.user_context import get_effective_user_id
 
         config = get_memory_config()
         if not config.enabled or not config.injection_enabled:
             return ""
 
-        memory_data = get_memory_data(agent_name, user_id=get_effective_user_id())
+        memory_data = get_memory_data(agent_name)
         memory_content = format_memory_for_injection(memory_data, max_tokens=config.max_injection_tokens)
 
         if not memory_content.strip():

backend/packages/harness/deerflow/agents/memory/queue.py

@@ -4,7 +4,7 @@ import logging
 import threading
 import time
 from dataclasses import dataclass, field
-from datetime import UTC, datetime
+from datetime import datetime
 from typing import Any
 
 from deerflow.config.memory_config import get_memory_config
@@ -18,9 +18,8 @@ class ConversationContext:
 
     thread_id: str
     messages: list[Any]
-    timestamp: datetime = field(default_factory=lambda: datetime.now(UTC))
+    timestamp: datetime = field(default_factory=datetime.utcnow)
     agent_name: str | None = None
-    user_id: str | None = None
     correction_detected: bool = False
     reinforcement_detected: bool = False
 
@@ -45,7 +44,6 @@ class MemoryUpdateQueue:
         thread_id: str,
         messages: list[Any],
         agent_name: str | None = None,
-        user_id: str | None = None,
         correction_detected: bool = False,
         reinforcement_detected: bool = False,
     ) -> None:
@@ -55,9 +53,6 @@ class MemoryUpdateQueue:
             thread_id: The thread ID.
             messages: The conversation messages.
             agent_name: If provided, memory is stored per-agent. If None, uses global memory.
-            user_id: The user ID captured at enqueue time. Stored in ConversationContext so it
-                survives the threading.Timer boundary (ContextVar does not propagate across
-                raw threads).
             correction_detected: Whether recent turns include an explicit correction signal.
             reinforcement_detected: Whether recent turns include a positive reinforcement signal.
         """
@@ -76,7 +71,6 @@ class MemoryUpdateQueue:
                 thread_id=thread_id,
                 messages=messages,
                 agent_name=agent_name,
-                user_id=user_id,
                 correction_detected=merged_correction_detected,
                 reinforcement_detected=merged_reinforcement_detected,
             )
@@ -142,7 +136,6 @@ class MemoryUpdateQueue:
                         agent_name=context.agent_name,
                         correction_detected=context.correction_detected,
                         reinforcement_detected=context.reinforcement_detected,
-                        user_id=context.user_id,
                     )
                     if success:
                         logger.info("Memory updated successfully for thread %s", context.thread_id)

backend/packages/harness/deerflow/agents/memory/storage.py

@@ -4,7 +4,7 @@ import abc
 import json
 import logging
 import threading
-from datetime import UTC, datetime
+from datetime import datetime
 from pathlib import Path
 from typing import Any
 
@@ -15,16 +15,11 @@ from deerflow.config.paths import get_paths
 logger = logging.getLogger(__name__)
 
 
-def utc_now_iso_z() -> str:
-    """Current UTC time as ISO-8601 with ``Z`` suffix (matches prior naive-UTC output)."""
-    return datetime.now(UTC).isoformat().removesuffix("+00:00") + "Z"
-
-
 def create_empty_memory() -> dict[str, Any]:
     """Create an empty memory structure."""
     return {
         "version": "1.0",
-        "lastUpdated": utc_now_iso_z(),
+        "lastUpdated": datetime.utcnow().isoformat() + "Z",
         "user": {
             "workContext": {"summary": "", "updatedAt": ""},
             "personalContext": {"summary": "", "updatedAt": ""},
@@ -43,17 +38,17 @@ class MemoryStorage(abc.ABC):
     """Abstract base class for memory storage providers."""
 
     @abc.abstractmethod
-    def load(self, agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
+    def load(self, agent_name: str | None = None) -> dict[str, Any]:
         """Load memory data for the given agent."""
         pass
 
     @abc.abstractmethod
-    def reload(self, agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
+    def reload(self, agent_name: str | None = None) -> dict[str, Any]:
         """Force reload memory data for the given agent."""
         pass
 
     @abc.abstractmethod
-    def save(self, memory_data: dict[str, Any], agent_name: str | None = None, *, user_id: str | None = None) -> bool:
+    def save(self, memory_data: dict[str, Any], agent_name: str | None = None) -> bool:
         """Save memory data for the given agent."""
         pass
 
@@ -63,9 +58,9 @@ class FileMemoryStorage(MemoryStorage):
 
     def __init__(self):
         """Initialize the file memory storage."""
-        # Per-user/agent memory cache: keyed by (user_id, agent_name) tuple (None = global)
+        # Per-agent memory cache: keyed by agent_name (None = global)
         # Value: (memory_data, file_mtime)
-        self._memory_cache: dict[tuple[str | None, str | None], tuple[dict[str, Any], float | None]] = {}
+        self._memory_cache: dict[str | None, tuple[dict[str, Any], float | None]] = {}
 
     def _validate_agent_name(self, agent_name: str) -> None:
         """Validate that the agent name is safe to use in filesystem paths.
@@ -78,29 +73,21 @@ class FileMemoryStorage(MemoryStorage):
         if not AGENT_NAME_PATTERN.match(agent_name):
             raise ValueError(f"Invalid agent name {agent_name!r}: names must match {AGENT_NAME_PATTERN.pattern}")
 
-    def _get_memory_file_path(self, agent_name: str | None = None, *, user_id: str | None = None) -> Path:
+    def _get_memory_file_path(self, agent_name: str | None = None) -> Path:
         """Get the path to the memory file."""
-        if user_id is not None:
-            if agent_name is not None:
-                self._validate_agent_name(agent_name)
-                return get_paths().user_agent_memory_file(user_id, agent_name)
-            config = get_memory_config()
-            if config.storage_path and Path(config.storage_path).is_absolute():
-                return Path(config.storage_path)
-            return get_paths().user_memory_file(user_id)
-        # Legacy: no user_id
         if agent_name is not None:
             self._validate_agent_name(agent_name)
             return get_paths().agent_memory_file(agent_name)
+
         config = get_memory_config()
         if config.storage_path:
             p = Path(config.storage_path)
             return p if p.is_absolute() else get_paths().base_dir / p
         return get_paths().memory_file
 
-    def _load_memory_from_file(self, agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
+    def _load_memory_from_file(self, agent_name: str | None = None) -> dict[str, Any]:
         """Load memory data from file."""
-        file_path = self._get_memory_file_path(agent_name, user_id=user_id)
+        file_path = self._get_memory_file_path(agent_name)
 
         if not file_path.exists():
             return create_empty_memory()
@@ -113,46 +100,44 @@ class FileMemoryStorage(MemoryStorage):
             logger.warning("Failed to load memory file: %s", e)
             return create_empty_memory()
 
-    def load(self, agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
+    def load(self, agent_name: str | None = None) -> dict[str, Any]:
         """Load memory data (cached with file modification time check)."""
-        file_path = self._get_memory_file_path(agent_name, user_id=user_id)
+        file_path = self._get_memory_file_path(agent_name)
 
         try:
             current_mtime = file_path.stat().st_mtime if file_path.exists() else None
         except OSError:
             current_mtime = None
 
-        cache_key = (user_id, agent_name)
-        cached = self._memory_cache.get(cache_key)
+        cached = self._memory_cache.get(agent_name)
 
         if cached is None or cached[1] != current_mtime:
-            memory_data = self._load_memory_from_file(agent_name, user_id=user_id)
-            self._memory_cache[cache_key] = (memory_data, current_mtime)
+            memory_data = self._load_memory_from_file(agent_name)
+            self._memory_cache[agent_name] = (memory_data, current_mtime)
             return memory_data
 
         return cached[0]
 
-    def reload(self, agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
+    def reload(self, agent_name: str | None = None) -> dict[str, Any]:
         """Reload memory data from file, forcing cache invalidation."""
-        file_path = self._get_memory_file_path(agent_name, user_id=user_id)
-        memory_data = self._load_memory_from_file(agent_name, user_id=user_id)
+        file_path = self._get_memory_file_path(agent_name)
+        memory_data = self._load_memory_from_file(agent_name)
 
         try:
             mtime = file_path.stat().st_mtime if file_path.exists() else None
         except OSError:
             mtime = None
 
-        cache_key = (user_id, agent_name)
-        self._memory_cache[cache_key] = (memory_data, mtime)
+        self._memory_cache[agent_name] = (memory_data, mtime)
         return memory_data
 
-    def save(self, memory_data: dict[str, Any], agent_name: str | None = None, *, user_id: str | None = None) -> bool:
+    def save(self, memory_data: dict[str, Any], agent_name: str | None = None) -> bool:
         """Save memory data to file and update cache."""
-        file_path = self._get_memory_file_path(agent_name, user_id=user_id)
+        file_path = self._get_memory_file_path(agent_name)
 
         try:
             file_path.parent.mkdir(parents=True, exist_ok=True)
-            memory_data["lastUpdated"] = utc_now_iso_z()
+            memory_data["lastUpdated"] = datetime.utcnow().isoformat() + "Z"
 
             temp_path = file_path.with_suffix(".tmp")
             with open(temp_path, "w", encoding="utf-8") as f:
@@ -165,8 +150,7 @@ class FileMemoryStorage(MemoryStorage):
             except OSError:
                 mtime = None
 
-            cache_key = (user_id, agent_name)
-            self._memory_cache[cache_key] = (memory_data, mtime)
+            self._memory_cache[agent_name] = (memory_data, mtime)
             logger.info("Memory saved to %s", file_path)
             return True
         except OSError as e:

backend/packages/harness/deerflow/agents/memory/updater.py

@@ -5,17 +5,14 @@ import logging
 import math
 import re
 import uuid
+from datetime import datetime
 from typing import Any
 
 from deerflow.agents.memory.prompt import (
     MEMORY_UPDATE_PROMPT,
     format_conversation_for_update,
 )
-from deerflow.agents.memory.storage import (
-    create_empty_memory,
-    get_memory_storage,
-    utc_now_iso_z,
-)
+from deerflow.agents.memory.storage import create_empty_memory, get_memory_storage
 from deerflow.config.memory_config import get_memory_config
 from deerflow.models import create_chat_model
 
@@ -27,28 +24,27 @@ def _create_empty_memory() -> dict[str, Any]:
     return create_empty_memory()
 
 
-def _save_memory_to_file(memory_data: dict[str, Any], agent_name: str | None = None, *, user_id: str | None = None) -> bool:
+def _save_memory_to_file(memory_data: dict[str, Any], agent_name: str | None = None) -> bool:
     """Backward-compatible wrapper around the configured memory storage save path."""
-    return get_memory_storage().save(memory_data, agent_name, user_id=user_id)
+    return get_memory_storage().save(memory_data, agent_name)
 
 
-def get_memory_data(agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
+def get_memory_data(agent_name: str | None = None) -> dict[str, Any]:
     """Get the current memory data via storage provider."""
-    return get_memory_storage().load(agent_name, user_id=user_id)
+    return get_memory_storage().load(agent_name)
 
 
-def reload_memory_data(agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
+def reload_memory_data(agent_name: str | None = None) -> dict[str, Any]:
     """Reload memory data via storage provider."""
-    return get_memory_storage().reload(agent_name, user_id=user_id)
+    return get_memory_storage().reload(agent_name)
 
 
-def import_memory_data(memory_data: dict[str, Any], agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
+def import_memory_data(memory_data: dict[str, Any], agent_name: str | None = None) -> dict[str, Any]:
     """Persist imported memory data via storage provider.
 
     Args:
         memory_data: Full memory payload to persist.
         agent_name: If provided, imports into per-agent memory.
-        user_id: If provided, scopes memory to a specific user.
 
     Returns:
         The saved memory data after storage normalization.
@@ -57,15 +53,15 @@ def import_memory_data(memory_data: dict[str, Any], agent_name: str | None = Non
         OSError: If persisting the imported memory fails.
     """
     storage = get_memory_storage()
-    if not storage.save(memory_data, agent_name, user_id=user_id):
+    if not storage.save(memory_data, agent_name):
         raise OSError("Failed to save imported memory data")
-    return storage.load(agent_name, user_id=user_id)
+    return storage.load(agent_name)
 
 
-def clear_memory_data(agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
+def clear_memory_data(agent_name: str | None = None) -> dict[str, Any]:
     """Clear all stored memory data and persist an empty structure."""
     cleared_memory = create_empty_memory()
-    if not _save_memory_to_file(cleared_memory, agent_name, user_id=user_id):
+    if not _save_memory_to_file(cleared_memory, agent_name):
         raise OSError("Failed to save cleared memory data")
     return cleared_memory
 
@@ -82,8 +78,6 @@ def create_memory_fact(
     category: str = "context",
     confidence: float = 0.5,
     agent_name: str | None = None,
-    *,
-    user_id: str | None = None,
 ) -> dict[str, Any]:
     """Create a new fact and persist the updated memory data."""
     normalized_content = content.strip()
@@ -92,8 +86,8 @@ def create_memory_fact(
 
     normalized_category = category.strip() or "context"
     validated_confidence = _validate_confidence(confidence)
-    now = utc_now_iso_z()
-    memory_data = get_memory_data(agent_name, user_id=user_id)
+    now = datetime.utcnow().isoformat() + "Z"
+    memory_data = get_memory_data(agent_name)
     updated_memory = dict(memory_data)
     facts = list(memory_data.get("facts", []))
     facts.append(
@@ -108,15 +102,15 @@ def create_memory_fact(
     )
     updated_memory["facts"] = facts
 
-    if not _save_memory_to_file(updated_memory, agent_name, user_id=user_id):
+    if not _save_memory_to_file(updated_memory, agent_name):
         raise OSError("Failed to save memory data after creating fact")
 
     return updated_memory
 
 
-def delete_memory_fact(fact_id: str, agent_name: str | None = None, *, user_id: str | None = None) -> dict[str, Any]:
+def delete_memory_fact(fact_id: str, agent_name: str | None = None) -> dict[str, Any]:
     """Delete a fact by its id and persist the updated memory data."""
-    memory_data = get_memory_data(agent_name, user_id=user_id)
+    memory_data = get_memory_data(agent_name)
     facts = memory_data.get("facts", [])
     updated_facts = [fact for fact in facts if fact.get("id") != fact_id]
     if len(updated_facts) == len(facts):
@@ -125,7 +119,7 @@ def delete_memory_fact(fact_id: str, agent_name: str | None = None, *, user_id:
     updated_memory = dict(memory_data)
     updated_memory["facts"] = updated_facts
 
-    if not _save_memory_to_file(updated_memory, agent_name, user_id=user_id):
+    if not _save_memory_to_file(updated_memory, agent_name):
         raise OSError(f"Failed to save memory data after deleting fact '{fact_id}'")
 
     return updated_memory
@@ -137,11 +131,9 @@ def update_memory_fact(
     category: str | None = None,
     confidence: float | None = None,
     agent_name: str | None = None,
-    *,
-    user_id: str | None = None,
 ) -> dict[str, Any]:
     """Update an existing fact and persist the updated memory data."""
-    memory_data = get_memory_data(agent_name, user_id=user_id)
+    memory_data = get_memory_data(agent_name)
     updated_memory = dict(memory_data)
     updated_facts: list[dict[str, Any]] = []
     found = False
@@ -168,7 +160,7 @@ def update_memory_fact(
 
     updated_memory["facts"] = updated_facts
 
-    if not _save_memory_to_file(updated_memory, agent_name, user_id=user_id):
+    if not _save_memory_to_file(updated_memory, agent_name):
         raise OSError(f"Failed to save memory data after updating fact '{fact_id}'")
 
     return updated_memory
@@ -281,7 +273,6 @@ class MemoryUpdater:
         agent_name: str | None = None,
         correction_detected: bool = False,
         reinforcement_detected: bool = False,
-        user_id: str | None = None,
     ) -> bool:
         """Update memory based on conversation messages.
 
@@ -291,7 +282,6 @@ class MemoryUpdater:
             agent_name: If provided, updates per-agent memory. If None, updates global memory.
             correction_detected: Whether recent turns include an explicit correction signal.
             reinforcement_detected: Whether recent turns include a positive reinforcement signal.
-            user_id: If provided, scopes memory to a specific user.
 
         Returns:
             True if update was successful, False otherwise.
@@ -305,7 +295,7 @@ class MemoryUpdater:
 
         try:
             # Get current memory
-            current_memory = get_memory_data(agent_name, user_id=user_id)
+            current_memory = get_memory_data(agent_name)
 
             # Format conversation for prompt
             conversation_text = format_conversation_for_update(messages)
@@ -360,7 +350,7 @@ class MemoryUpdater:
             updated_memory = _strip_upload_mentions_from_memory(updated_memory)
 
             # Save
-            return get_memory_storage().save(updated_memory, agent_name, user_id=user_id)
+            return get_memory_storage().save(updated_memory, agent_name)
 
         except json.JSONDecodeError as e:
             logger.warning("Failed to parse LLM response for memory update: %s", e)
@@ -386,7 +376,7 @@ class MemoryUpdater:
             Updated memory data.
         """
         config = get_memory_config()
-        now = utc_now_iso_z()
+        now = datetime.utcnow().isoformat() + "Z"
 
         # Update user sections
         user_updates = update_data.get("user", {})
@@ -462,7 +452,6 @@ def update_memory_from_conversation(
     agent_name: str | None = None,
     correction_detected: bool = False,
     reinforcement_detected: bool = False,
-    user_id: str | None = None,
 ) -> bool:
     """Convenience function to update memory from a conversation.
 
@@ -472,10 +461,9 @@ def update_memory_from_conversation(
         agent_name: If provided, updates per-agent memory. If None, updates global memory.
         correction_detected: Whether recent turns include an explicit correction signal.
         reinforcement_detected: Whether recent turns include a positive reinforcement signal.
-        user_id: If provided, scopes memory to a specific user.
 
     Returns:
         True if successful, False otherwise.
     """
     updater = MemoryUpdater()
-    return updater.update_memory(messages, thread_id, agent_name, correction_detected, reinforcement_detected, user_id=user_id)
+    return updater.update_memory(messages, thread_id, agent_name, correction_detected, reinforcement_detected)

backend/packages/harness/deerflow/agents/middlewares/clarification_middleware.py

@@ -1,6 +1,5 @@
 """Middleware for intercepting clarification requests and presenting them to the user."""
 
-import json
 import logging
 from collections.abc import Callable
 from typing import override
@@ -61,20 +60,6 @@ class ClarificationMiddleware(AgentMiddleware[ClarificationMiddlewareState]):
         context = args.get("context")
         options = args.get("options", [])
 
-        # Some models (e.g. Qwen3-Max) serialize array parameters as JSON strings
-        # instead of native arrays. Deserialize and normalize so `options`
-        # is always a list for the rendering logic below.
-        if isinstance(options, str):
-            try:
-                options = json.loads(options)
-            except (json.JSONDecodeError, TypeError):
-                options = [options]
-
-        if options is None:
-            options = []
-        elif not isinstance(options, list):
-            options = [options]
-
         # Type-specific icons
         type_icons = {
             "missing_info": "❓",

backend/packages/harness/deerflow/agents/middlewares/loop_detection_middleware.py

@@ -33,92 +33,30 @@ _DEFAULT_WINDOW_SIZE = 20  # track last N tool calls
 _DEFAULT_MAX_TRACKED_THREADS = 100  # LRU eviction limit
 
 
-def _normalize_tool_call_args(raw_args: object) -> tuple[dict, str | None]:
-    """Normalize tool call args to a dict plus an optional fallback key.
-
-    Some providers serialize ``args`` as a JSON string instead of a dict.
-    We defensively parse those cases so loop detection does not crash while
-    still preserving a stable fallback key for non-dict payloads.
-    """
-    if isinstance(raw_args, dict):
-        return raw_args, None
-
-    if isinstance(raw_args, str):
-        try:
-            parsed = json.loads(raw_args)
-        except (TypeError, ValueError, json.JSONDecodeError):
-            return {}, raw_args
-
-        if isinstance(parsed, dict):
-            return parsed, None
-        return {}, json.dumps(parsed, sort_keys=True, default=str)
-
-    if raw_args is None:
-        return {}, None
-
-    return {}, json.dumps(raw_args, sort_keys=True, default=str)
-
-
-def _stable_tool_key(name: str, args: dict, fallback_key: str | None) -> str:
-    """Derive a stable key from salient args without overfitting to noise."""
-    if name == "read_file" and fallback_key is None:
-        path = args.get("path") or ""
-        start_line = args.get("start_line")
-        end_line = args.get("end_line")
-
-        bucket_size = 200
-        try:
-            start_line = int(start_line) if start_line is not None else 1
-        except (TypeError, ValueError):
-            start_line = 1
-        try:
-            end_line = int(end_line) if end_line is not None else start_line
-        except (TypeError, ValueError):
-            end_line = start_line
-
-        start_line, end_line = sorted((start_line, end_line))
-        bucket_start = max(start_line, 1)
-        bucket_end = max(end_line, 1)
-        bucket_start = (bucket_start - 1) // bucket_size
-        bucket_end = (bucket_end - 1) // bucket_size
-        return f"{path}:{bucket_start}-{bucket_end}"
-
-    # write_file / str_replace are content-sensitive: same path may be updated
-    # with different payloads during iteration. Using only salient fields (path)
-    # can collapse distinct calls, so we hash full args to reduce false positives.
-    if name in {"write_file", "str_replace"}:
-        if fallback_key is not None:
-            return fallback_key
-        return json.dumps(args, sort_keys=True, default=str)
-
-    salient_fields = ("path", "url", "query", "command", "pattern", "glob", "cmd")
-    stable_args = {field: args[field] for field in salient_fields if args.get(field) is not None}
-    if stable_args:
-        return json.dumps(stable_args, sort_keys=True, default=str)
-
-    if fallback_key is not None:
-        return fallback_key
-
-    return json.dumps(args, sort_keys=True, default=str)
-
-
 def _hash_tool_calls(tool_calls: list[dict]) -> str:
-    """Deterministic hash of a set of tool calls (name + stable key).
+    """Deterministic hash of a set of tool calls (name + args).
 
     This is intended to be order-independent: the same multiset of tool calls
     should always produce the same hash, regardless of their input order.
     """
-    # Normalize each tool call to a stable (name, key) structure.
-    normalized: list[str] = []
+    # First normalize each tool call to a minimal (name, args) structure.
+    normalized: list[dict] = []
     for tc in tool_calls:
-        name = tc.get("name", "")
-        args, fallback_key = _normalize_tool_call_args(tc.get("args", {}))
-        key = _stable_tool_key(name, args, fallback_key)
+        normalized.append(
+            {
+                "name": tc.get("name", ""),
+                "args": tc.get("args", {}),
+            }
+        )
 
-        normalized.append(f"{name}:{key}")
-
-    # Sort so permutations of the same multiset of calls yield the same ordering.
-    normalized.sort()
+    # Sort by both name and a deterministic serialization of args so that
+    # permutations of the same multiset of calls yield the same ordering.
+    normalized.sort(
+        key=lambda tc: (
+            tc["name"],
+            json.dumps(tc["args"], sort_keys=True, default=str),
+        )
+    )
     blob = json.dumps(normalized, sort_keys=True, default=str)
     return hashlib.md5(blob.encode()).hexdigest()[:12]
 
@@ -283,7 +221,7 @@ class LoopDetectionMiddleware(AgentMiddleware[AgentState]):
             # the conversation; injecting one mid-conversation crashes
             # langchain_anthropic's _format_messages(). HumanMessage works
             # with all providers. See #1299.
-            return {"messages": [HumanMessage(content=warning, name="loop_warning")]}
+            return {"messages": [HumanMessage(content=warning)]}
 
         return None
 

backend/packages/harness/deerflow/agents/middlewares/memory_middleware.py

@@ -11,7 +11,6 @@ from langgraph.runtime import Runtime
 
 from deerflow.agents.memory.queue import get_memory_queue
 from deerflow.config.memory_config import get_memory_config
-from deerflow.runtime.user_context import get_effective_user_id
 
 logger = logging.getLogger(__name__)
 
@@ -237,16 +236,11 @@ class MemoryMiddleware(AgentMiddleware[MemoryMiddlewareState]):
         # Queue the filtered conversation for memory update
         correction_detected = detect_correction(filtered_messages)
         reinforcement_detected = not correction_detected and detect_reinforcement(filtered_messages)
-        # Capture user_id at enqueue time while the request context is still alive.
-        # threading.Timer fires on a different thread where ContextVar values are not
-        # propagated, so we must store user_id explicitly in ConversationContext.
-        user_id = get_effective_user_id()
         queue = get_memory_queue()
         queue.add(
             thread_id=thread_id,
             messages=filtered_messages,
             agent_name=self._agent_name,
-            user_id=user_id,
             correction_detected=correction_detected,
             reinforcement_detected=reinforcement_detected,
         )

backend/packages/harness/deerflow/agents/middlewares/sandbox_audit_middleware.py

@@ -23,119 +23,25 @@ logger = logging.getLogger(__name__)
 
 # Each pattern is compiled once at import time.
 _HIGH_RISK_PATTERNS: list[re.Pattern[str]] = [
-    # --- original rules (retained) ---
-    re.compile(r"rm\s+-[^\s]*r[^\s]*\s+(/\*?|~/?\*?|/home\b|/root\b)\s*$"),
+    re.compile(r"rm\s+-[^\s]*r[^\s]*\s+(/\*?|~/?\*?|/home\b|/root\b)\s*$"),  # rm -rf / /* ~ /home /root
+    re.compile(r"(curl|wget).+\|\s*(ba)?sh"),  # curl|sh, wget|sh
     re.compile(r"dd\s+if="),
     re.compile(r"mkfs"),
     re.compile(r"cat\s+/etc/shadow"),
-    re.compile(r">+\s*/etc/"),
-    # --- pipe to sh/bash (generalised, replaces old curl|sh rule) ---
-    re.compile(r"\|\s*(ba)?sh\b"),
-    # --- command substitution (targeted – only dangerous executables) ---
-    re.compile(r"[`$]\(?\s*(curl|wget|bash|sh|python|ruby|perl|base64)"),
-    # --- base64 decode piped to execution ---
-    re.compile(r"base64\s+.*-d.*\|"),
-    # --- overwrite system binaries ---
-    re.compile(r">+\s*(/usr/bin/|/bin/|/sbin/)"),
-    # --- overwrite shell startup files ---
-    re.compile(r">+\s*~/?\.(bashrc|profile|zshrc|bash_profile)"),
-    # --- process environment leakage ---
-    re.compile(r"/proc/[^/]+/environ"),
-    # --- dynamic linker hijack (one-step escalation) ---
-    re.compile(r"\b(LD_PRELOAD|LD_LIBRARY_PATH)\s*="),
-    # --- bash built-in networking (bypasses tool allowlists) ---
-    re.compile(r"/dev/tcp/"),
-    # --- fork bomb ---
-    re.compile(r"\S+\(\)\s*\{[^}]*\|\s*\S+\s*&"),  # :(){ :|:& };:
-    re.compile(r"while\s+true.*&\s*done"),  # while true; do bash & done
+    re.compile(r">\s*/etc/"),  # overwrite /etc/ files
 ]
 
 _MEDIUM_RISK_PATTERNS: list[re.Pattern[str]] = [
-    re.compile(r"chmod\s+777"),
-    re.compile(r"pip3?\s+install"),
+    re.compile(r"chmod\s+777"),  # overly permissive, but reversible
+    re.compile(r"pip\s+install"),
+    re.compile(r"pip3\s+install"),
     re.compile(r"apt(-get)?\s+install"),
-    # sudo/su: no-op under Docker root; warn so LLM is aware
-    re.compile(r"\b(sudo|su)\b"),
-    # PATH modification: long attack chain, warn rather than block
-    re.compile(r"\bPATH\s*="),
 ]
 
 
-def _split_compound_command(command: str) -> list[str]:
-    """Split a compound command into sub-commands (quote-aware).
-
-    Scans the raw command string so unquoted shell control operators are
-    recognised even when they are not surrounded by whitespace
-    (e.g. ``safe;rm -rf /`` or ``rm -rf /&&echo ok``). Operators inside
-    quotes are ignored. If the command ends with an unclosed quote or a
-    dangling escape, return the whole command unchanged (fail-closed —
-    safer to classify the unsplit string than silently drop parts).
-    """
-    parts: list[str] = []
-    current: list[str] = []
-    in_single_quote = False
-    in_double_quote = False
-    escaping = False
-    index = 0
-
-    while index < len(command):
-        char = command[index]
-
-        if escaping:
-            current.append(char)
-            escaping = False
-            index += 1
-            continue
-
-        if char == "\\" and not in_single_quote:
-            current.append(char)
-            escaping = True
-            index += 1
-            continue
-
-        if char == "'" and not in_double_quote:
-            in_single_quote = not in_single_quote
-            current.append(char)
-            index += 1
-            continue
-
-        if char == '"' and not in_single_quote:
-            in_double_quote = not in_double_quote
-            current.append(char)
-            index += 1
-            continue
-
-        if not in_single_quote and not in_double_quote:
-            if command.startswith("&&", index) or command.startswith("||", index):
-                part = "".join(current).strip()
-                if part:
-                    parts.append(part)
-                current = []
-                index += 2
-                continue
-            if char == ";":
-                part = "".join(current).strip()
-                if part:
-                    parts.append(part)
-                current = []
-                index += 1
-                continue
-
-        current.append(char)
-        index += 1
-
-    # Unclosed quote or dangling escape → fail-closed, return whole command
-    if in_single_quote or in_double_quote or escaping:
-        return [command]
-
-    part = "".join(current).strip()
-    if part:
-        parts.append(part)
-    return parts if parts else [command]
-
-
-def _classify_single_command(command: str) -> str:
-    """Classify a single (non-compound) command. Return 'block', 'warn', or 'pass'."""
+def _classify_command(command: str) -> str:
+    """Return 'block', 'warn', or 'pass'."""
+    # Normalize for matching (collapse whitespace)
     normalized = " ".join(command.split())
 
     for pattern in _HIGH_RISK_PATTERNS:
@@ -160,35 +66,6 @@ def _classify_single_command(command: str) -> str:
     return "pass"
 
 
-def _classify_command(command: str) -> str:
-    """Return 'block', 'warn', or 'pass'.
-
-    Strategy:
-    1. First scan the *whole* raw command against high-risk patterns. This
-       catches structural attacks like ``while true; do bash & done`` or
-       ``:(){ :|:& };:`` that span multiple shell statements — splitting them
-       on ``;`` would destroy the pattern context.
-    2. Then split compound commands (e.g. ``cmd1 && cmd2 ; cmd3``) and
-       classify each sub-command independently. The most severe verdict wins.
-    """
-    # Pass 1: whole-command high-risk scan (catches multi-statement patterns)
-    normalized = " ".join(command.split())
-    for pattern in _HIGH_RISK_PATTERNS:
-        if pattern.search(normalized):
-            return "block"
-
-    # Pass 2: per-sub-command classification
-    sub_commands = _split_compound_command(command)
-    worst = "pass"
-    for sub in sub_commands:
-        verdict = _classify_single_command(sub)
-        if verdict == "block":
-            return "block"  # short-circuit: can't get worse
-        if verdict == "warn":
-            worst = "warn"
-    return worst
-
-
 # ---------------------------------------------------------------------------
 # Middleware
 # ---------------------------------------------------------------------------

backend/packages/harness/deerflow/agents/middlewares/summarization_middleware.py

@@ -1,13 +0,0 @@
-from typing import override
-
-from langchain.agents.middleware import SummarizationMiddleware as BaseSummarizationMiddleware
-from langchain_core.messages.human import HumanMessage
-
-
-class SummarizationMiddleware(BaseSummarizationMiddleware):
-    @override
-    def _build_new_messages(self, summary: str) -> list[HumanMessage]:
-        """Override the base implementation to let the human message with the special name 'summary'.
-        And this message will be ignored to display in the frontend, but still can be used as context for the model.
-        """
-        return [HumanMessage(content=f"Here is a summary of the conversation to date:\n\n{summary}", name="summary")]

backend/packages/harness/deerflow/agents/middlewares/thread_data_middleware.py

@@ -1,16 +1,13 @@
 import logging
-from datetime import UTC, datetime
 from typing import NotRequired, override
 
 from langchain.agents import AgentState
 from langchain.agents.middleware import AgentMiddleware
-from langchain_core.messages import HumanMessage
 from langgraph.config import get_config
 from langgraph.runtime import Runtime
 
 from deerflow.agents.thread_state import ThreadDataState
 from deerflow.config.paths import Paths, get_paths
-from deerflow.runtime.user_context import get_effective_user_id
 
 logger = logging.getLogger(__name__)
 
@@ -49,34 +46,32 @@ class ThreadDataMiddleware(AgentMiddleware[ThreadDataMiddlewareState]):
         self._paths = Paths(base_dir) if base_dir else get_paths()
         self._lazy_init = lazy_init
 
-    def _get_thread_paths(self, thread_id: str, user_id: str | None = None) -> dict[str, str]:
+    def _get_thread_paths(self, thread_id: str) -> dict[str, str]:
         """Get the paths for a thread's data directories.
 
         Args:
             thread_id: The thread ID.
-            user_id: Optional user ID for per-user path isolation.
 
         Returns:
             Dictionary with workspace_path, uploads_path, and outputs_path.
         """
         return {
-            "workspace_path": str(self._paths.sandbox_work_dir(thread_id, user_id=user_id)),
-            "uploads_path": str(self._paths.sandbox_uploads_dir(thread_id, user_id=user_id)),
-            "outputs_path": str(self._paths.sandbox_outputs_dir(thread_id, user_id=user_id)),
+            "workspace_path": str(self._paths.sandbox_work_dir(thread_id)),
+            "uploads_path": str(self._paths.sandbox_uploads_dir(thread_id)),
+            "outputs_path": str(self._paths.sandbox_outputs_dir(thread_id)),
         }
 
-    def _create_thread_directories(self, thread_id: str, user_id: str | None = None) -> dict[str, str]:
+    def _create_thread_directories(self, thread_id: str) -> dict[str, str]:
         """Create the thread data directories.
 
         Args:
             thread_id: The thread ID.
-            user_id: Optional user ID for per-user path isolation.
 
         Returns:
             Dictionary with the created directory paths.
         """
-        self._paths.ensure_thread_dirs(thread_id, user_id=user_id)
-        return self._get_thread_paths(thread_id, user_id=user_id)
+        self._paths.ensure_thread_dirs(thread_id)
+        return self._get_thread_paths(thread_id)
 
     @override
     def before_agent(self, state: ThreadDataMiddlewareState, runtime: Runtime) -> dict | None:
@@ -89,30 +84,16 @@ class ThreadDataMiddleware(AgentMiddleware[ThreadDataMiddlewareState]):
         if thread_id is None:
             raise ValueError("Thread ID is required in runtime context or config.configurable")
 
-        user_id = get_effective_user_id()
-
         if self._lazy_init:
             # Lazy initialization: only compute paths, don't create directories
-            paths = self._get_thread_paths(thread_id, user_id=user_id)
+            paths = self._get_thread_paths(thread_id)
         else:
             # Eager initialization: create directories immediately
-            paths = self._create_thread_directories(thread_id, user_id=user_id)
+            paths = self._create_thread_directories(thread_id)
             logger.debug("Created thread data directories for thread %s", thread_id)
 
-        messages = list(state.get("messages", []))
-        last_message = messages[-1] if messages else None
-
-        if last_message and isinstance(last_message, HumanMessage):
-            messages[-1] = HumanMessage(
-                content=last_message.content,
-                id=last_message.id,
-                name=last_message.name or "user-input",
-                additional_kwargs={**last_message.additional_kwargs, "run_id": runtime.context.get("run_id"), "timestamp": datetime.now(UTC).isoformat()},
-            )
-
         return {
             "thread_data": {
                 **paths,
-            },
-            "messages": messages,
+            }
         }

backend/packages/harness/deerflow/agents/middlewares/uploads_middleware.py

@@ -10,7 +10,6 @@ from langchain_core.messages import HumanMessage
 from langgraph.runtime import Runtime
 
 from deerflow.config.paths import Paths, get_paths
-from deerflow.runtime.user_context import get_effective_user_id
 from deerflow.utils.file_conversion import extract_outline
 
 logger = logging.getLogger(__name__)
@@ -222,7 +221,7 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
                 thread_id = get_config().get("configurable", {}).get("thread_id")
             except RuntimeError:
                 pass  # get_config() raises outside a runnable context (e.g. unit tests)
-        uploads_dir = self._paths.sandbox_uploads_dir(thread_id, user_id=get_effective_user_id()) if thread_id else None
+        uploads_dir = self._paths.sandbox_uploads_dir(thread_id) if thread_id else None
 
         # Get newly uploaded files from the current message's additional_kwargs.files
         new_files = self._files_from_kwargs(last_message, uploads_dir) or []
@@ -279,7 +278,6 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
         updated_message = HumanMessage(
             content=f"{files_message}\n\n{original_content}",
             id=last_message.id,
-            name=last_message.name,
             additional_kwargs=last_message.additional_kwargs,
         )
 

backend/packages/harness/deerflow/client.py

@@ -25,7 +25,7 @@ import uuid
 from collections.abc import Generator, Sequence
 from dataclasses import dataclass, field
 from pathlib import Path
-from typing import Any, Literal
+from typing import Any
 
 from langchain.agents import create_agent
 from langchain.agents.middleware import AgentMiddleware
@@ -40,7 +40,6 @@ from deerflow.config.app_config import get_app_config, reload_app_config
 from deerflow.config.extensions_config import ExtensionsConfig, SkillStateConfig, get_extensions_config, reload_extensions_config
 from deerflow.config.paths import get_paths
 from deerflow.models import create_chat_model
-from deerflow.runtime.user_context import get_effective_user_id
 from deerflow.skills.installer import install_skill_from_archive
 from deerflow.uploads.manager import (
     claim_unique_filename,
@@ -56,9 +55,6 @@ from deerflow.uploads.manager import (
 logger = logging.getLogger(__name__)
 
 
-StreamEventType = Literal["values", "messages-tuple", "custom", "end"]
-
-
 @dataclass
 class StreamEvent:
     """A single event from the streaming agent response.
@@ -73,7 +69,7 @@ class StreamEvent:
         data: Event payload. Contents vary by type.
     """
 
-    type: StreamEventType
+    type: str
     data: dict[str, Any] = field(default_factory=dict)
 
 
@@ -241,7 +237,7 @@ class DeerFlowClient:
         }
         checkpointer = self._checkpointer
         if checkpointer is None:
-            from deerflow.runtime.checkpointer import get_checkpointer
+            from deerflow.agents.checkpointer import get_checkpointer
 
             checkpointer = get_checkpointer()
         if checkpointer is not None:
@@ -258,53 +254,13 @@ class DeerFlowClient:
 
         return get_available_tools(model_name=model_name, subagent_enabled=subagent_enabled)
 
-    @staticmethod
-    def _serialize_tool_calls(tool_calls) -> list[dict]:
-        """Reshape LangChain tool_calls into the wire format used in events."""
-        return [{"name": tc["name"], "args": tc["args"], "id": tc.get("id")} for tc in tool_calls]
-
-    @staticmethod
-    def _ai_text_event(msg_id: str | None, text: str, usage: dict | None) -> "StreamEvent":
-        """Build a ``messages-tuple`` AI text event, attaching usage when present."""
-        data: dict[str, Any] = {"type": "ai", "content": text, "id": msg_id}
-        if usage:
-            data["usage_metadata"] = usage
-        return StreamEvent(type="messages-tuple", data=data)
-
-    @staticmethod
-    def _ai_tool_calls_event(msg_id: str | None, tool_calls) -> "StreamEvent":
-        """Build a ``messages-tuple`` AI tool-calls event."""
-        return StreamEvent(
-            type="messages-tuple",
-            data={
-                "type": "ai",
-                "content": "",
-                "id": msg_id,
-                "tool_calls": DeerFlowClient._serialize_tool_calls(tool_calls),
-            },
-        )
-
-    @staticmethod
-    def _tool_message_event(msg: ToolMessage) -> "StreamEvent":
-        """Build a ``messages-tuple`` tool-result event from a ToolMessage."""
-        return StreamEvent(
-            type="messages-tuple",
-            data={
-                "type": "tool",
-                "content": DeerFlowClient._extract_text(msg.content),
-                "name": msg.name,
-                "tool_call_id": msg.tool_call_id,
-                "id": msg.id,
-            },
-        )
-
     @staticmethod
     def _serialize_message(msg) -> dict:
         """Serialize a LangChain message to a plain dict for values events."""
         if isinstance(msg, AIMessage):
             d: dict[str, Any] = {"type": "ai", "content": msg.content, "id": getattr(msg, "id", None)}
             if msg.tool_calls:
-                d["tool_calls"] = DeerFlowClient._serialize_tool_calls(msg.tool_calls)
+                d["tool_calls"] = [{"name": tc["name"], "args": tc["args"], "id": tc.get("id")} for tc in msg.tool_calls]
             if getattr(msg, "usage_metadata", None):
                 d["usage_metadata"] = msg.usage_metadata
             return d
@@ -359,108 +315,6 @@ class DeerFlowClient:
             return "\n".join(pieces) if pieces else ""
         return str(content)
 
-    # ------------------------------------------------------------------
-    # Public API — threads
-    # ------------------------------------------------------------------
-
-    def list_threads(self, limit: int = 10) -> dict:
-        """List the recent N threads.
-
-        Args:
-            limit: Maximum number of threads to return. Default is 10.
-
-        Returns:
-            Dict with "thread_list" key containing list of thread info dicts,
-            sorted by thread creation time descending.
-        """
-        checkpointer = self._checkpointer
-        if checkpointer is None:
-            from deerflow.runtime.checkpointer.provider import get_checkpointer
-
-            checkpointer = get_checkpointer()
-
-        thread_info_map = {}
-
-        for cp in checkpointer.list(config=None, limit=limit):
-            cfg = cp.config.get("configurable", {})
-            thread_id = cfg.get("thread_id")
-            if not thread_id:
-                continue
-
-            ts = cp.checkpoint.get("ts")
-            checkpoint_id = cfg.get("checkpoint_id")
-
-            if thread_id not in thread_info_map:
-                channel_values = cp.checkpoint.get("channel_values", {})
-                thread_info_map[thread_id] = {
-                    "thread_id": thread_id,
-                    "created_at": ts,
-                    "updated_at": ts,
-                    "latest_checkpoint_id": checkpoint_id,
-                    "title": channel_values.get("title"),
-                }
-            else:
-                # Explicitly compare timestamps to ensure accuracy when iterating over unordered namespaces.
-                # Treat None as "missing" and only compare when existing values are non-None.
-                if ts is not None:
-                    current_created = thread_info_map[thread_id]["created_at"]
-                    if current_created is None or ts < current_created:
-                        thread_info_map[thread_id]["created_at"] = ts
-
-                    current_updated = thread_info_map[thread_id]["updated_at"]
-                    if current_updated is None or ts > current_updated:
-                        thread_info_map[thread_id]["updated_at"] = ts
-                        thread_info_map[thread_id]["latest_checkpoint_id"] = checkpoint_id
-                        channel_values = cp.checkpoint.get("channel_values", {})
-                        thread_info_map[thread_id]["title"] = channel_values.get("title")
-
-        threads = list(thread_info_map.values())
-        threads.sort(key=lambda x: x.get("created_at") or "", reverse=True)
-
-        return {"thread_list": threads[:limit]}
-
-    def get_thread(self, thread_id: str) -> dict:
-        """Get the complete thread record, including all node execution records.
-
-        Args:
-            thread_id: Thread ID.
-
-        Returns:
-            Dict containing the thread's full checkpoint history.
-        """
-        checkpointer = self._checkpointer
-        if checkpointer is None:
-            from deerflow.runtime.checkpointer.provider import get_checkpointer
-
-            checkpointer = get_checkpointer()
-
-        config = {"configurable": {"thread_id": thread_id}}
-        checkpoints = []
-
-        for cp in checkpointer.list(config):
-            channel_values = dict(cp.checkpoint.get("channel_values", {}))
-            if "messages" in channel_values:
-                channel_values["messages"] = [self._serialize_message(m) if hasattr(m, "content") else m for m in channel_values["messages"]]
-
-            cfg = cp.config.get("configurable", {})
-            parent_cfg = cp.parent_config.get("configurable", {}) if cp.parent_config else {}
-
-            checkpoints.append(
-                {
-                    "checkpoint_id": cfg.get("checkpoint_id"),
-                    "parent_checkpoint_id": parent_cfg.get("checkpoint_id"),
-                    "ts": cp.checkpoint.get("ts"),
-                    "metadata": cp.metadata,
-                    "values": channel_values,
-                    "pending_writes": [{"task_id": w[0], "channel": w[1], "value": w[2]} for w in getattr(cp, "pending_writes", [])],
-                }
-            )
-
-        # Sort globally by timestamp to prevent partial ordering issues caused by different namespaces (e.g., subgraphs)
-        checkpoints.sort(key=lambda x: x["ts"] if x["ts"] else "")
-
-        return {"thread_id": thread_id, "checkpoints": checkpoints}
-
     # ------------------------------------------------------------------
     # Public API — conversation
     # ------------------------------------------------------------------
@@ -482,53 +336,6 @@ class DeerFlowClient:
         consumers can switch between HTTP streaming and embedded mode
         without changing their event-handling logic.
 
-        Token-level streaming
-        ~~~~~~~~~~~~~~~~~~~~~
-        This method subscribes to LangGraph's ``messages`` stream mode, so
-        ``messages-tuple`` events for AI text are emitted as **deltas** as
-        the model generates tokens, not as one cumulative dump at node
-        completion.  Each delta carries a stable ``id`` — consumers that
-        want the full text must accumulate ``content`` per ``id``.
-        ``chat()`` already does this for you.
-
-        Tool calls and tool results are still emitted once per logical
-        message.  ``values`` events continue to carry full state snapshots
-        after each graph node finishes; AI text already delivered via the
-        ``messages`` stream is **not** re-synthesized from the snapshot to
-        avoid duplicate deliveries.
-
-        Why not reuse Gateway's ``run_agent``?
-        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-        Gateway (``runtime/runs/worker.py``) has a complete streaming
-        pipeline: ``run_agent`` → ``StreamBridge`` → ``sse_consumer``.  It
-        looks like this client duplicates that work, but the two paths
-        serve different audiences and **cannot** share execution:
-
-        * ``run_agent`` is ``async def`` and uses ``agent.astream()``;
-          this method is a sync generator using ``agent.stream()`` so
-          callers can write ``for event in client.stream(...)`` without
-          touching asyncio.  Bridging the two would require spinning up
-          an event loop + thread per call.
-        * Gateway events are JSON-serialized by ``serialize()`` for SSE
-          wire transmission.  This client yields in-process stream event
-          payloads directly as Python data structures (``StreamEvent``
-          with ``data`` as a plain ``dict``), without the extra
-          JSON/SSE serialization layer used for HTTP delivery.
-        * ``StreamBridge`` is an asyncio-queue decoupling producers from
-          consumers across an HTTP boundary (``Last-Event-ID`` replay,
-          heartbeats, multi-subscriber fan-out).  A single in-process
-          caller with a direct iterator needs none of that.
-
-        So ``DeerFlowClient.stream()`` is a parallel, sync, in-process
-        consumer of the same ``create_agent()`` factory — not a wrapper
-        around Gateway.  The two paths **should** stay in sync on which
-        LangGraph stream modes they subscribe to; that invariant is
-        enforced by ``tests/test_client.py::test_messages_mode_emits_token_deltas``
-        rather than by a shared constant, because the three layers
-        (Graph, Platform SDK, HTTP) each use their own naming
-        (``messages`` vs ``messages-tuple``) and cannot literally share
-        a string.
-
         Args:
             message: User message text.
             thread_id: Thread ID for conversation context. Auto-generated if None.
@@ -539,8 +346,8 @@ class DeerFlowClient:
             StreamEvent with one of:
             - type="values"          data={"title": str|None, "messages": [...], "artifacts": [...]}
             - type="custom"          data={...}
-            - type="messages-tuple"  data={"type": "ai", "content": <delta>, "id": str}
-            - type="messages-tuple"  data={"type": "ai", "content": <delta>, "id": str, "usage_metadata": {...}}
+            - type="messages-tuple"  data={"type": "ai", "content": str, "id": str}
+            - type="messages-tuple"  data={"type": "ai", "content": str, "id": str, "usage_metadata": {...}}
             - type="messages-tuple"  data={"type": "ai", "content": "", "id": str, "tool_calls": [...]}
             - type="messages-tuple"  data={"type": "tool", "content": str, "name": str, "tool_call_id": str, "id": str}
             - type="end"             data={"usage": {"input_tokens": int, "output_tokens": int, "total_tokens": int}}
@@ -557,47 +364,13 @@ class DeerFlowClient:
             context["agent_name"] = self._agent_name
 
         seen_ids: set[str] = set()
-        # Cross-mode handoff: ids already streamed via LangGraph ``messages``
-        # mode so the ``values`` path skips re-synthesis of the same message.
-        streamed_ids: set[str] = set()
-        # The same message id carries identical cumulative ``usage_metadata``
-        # in both the final ``messages`` chunk and the values snapshot —
-        # count it only on whichever arrives first.
-        counted_usage_ids: set[str] = set()
         cumulative_usage: dict[str, int] = {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
 
-        def _account_usage(msg_id: str | None, usage: Any) -> dict | None:
-            """Add *usage* to cumulative totals if this id has not been counted.
-
-            ``usage`` is a ``langchain_core.messages.UsageMetadata`` TypedDict
-            or ``None``; typed as ``Any`` because TypedDicts are not
-            structurally assignable to plain ``dict`` under strict type
-            checking.  Returns the normalized usage dict (for attaching
-            to an event) when we accepted it, otherwise ``None``.
-            """
-            if not usage:
-                return None
-            if msg_id and msg_id in counted_usage_ids:
-                return None
-            if msg_id:
-                counted_usage_ids.add(msg_id)
-            input_tokens = usage.get("input_tokens", 0) or 0
-            output_tokens = usage.get("output_tokens", 0) or 0
-            total_tokens = usage.get("total_tokens", 0) or 0
-            cumulative_usage["input_tokens"] += input_tokens
-            cumulative_usage["output_tokens"] += output_tokens
-            cumulative_usage["total_tokens"] += total_tokens
-            return {
-                "input_tokens": input_tokens,
-                "output_tokens": output_tokens,
-                "total_tokens": total_tokens,
-            }
-
         for item in self._agent.stream(
             state,
             config=config,
             context=context,
-            stream_mode=["values", "messages", "custom"],
+            stream_mode=["values", "custom"],
         ):
             if isinstance(item, tuple) and len(item) == 2:
                 mode, chunk = item
@@ -609,36 +382,6 @@ class DeerFlowClient:
                 yield StreamEvent(type="custom", data=chunk)
                 continue
 
-            if mode == "messages":
-                # LangGraph ``messages`` mode emits ``(message_chunk, metadata)``.
-                if isinstance(chunk, tuple) and len(chunk) == 2:
-                    msg_chunk, _metadata = chunk
-                else:
-                    msg_chunk = chunk
-
-                msg_id = getattr(msg_chunk, "id", None)
-
-                if isinstance(msg_chunk, AIMessage):
-                    text = self._extract_text(msg_chunk.content)
-                    counted_usage = _account_usage(msg_id, msg_chunk.usage_metadata)
-
-                    if text:
-                        if msg_id:
-                            streamed_ids.add(msg_id)
-                        yield self._ai_text_event(msg_id, text, counted_usage)
-
-                    if msg_chunk.tool_calls:
-                        if msg_id:
-                            streamed_ids.add(msg_id)
-                        yield self._ai_tool_calls_event(msg_id, msg_chunk.tool_calls)
-
-                elif isinstance(msg_chunk, ToolMessage):
-                    if msg_id:
-                        streamed_ids.add(msg_id)
-                    yield self._tool_message_event(msg_chunk)
-                continue
-
-            # mode == "values"
             messages = chunk.get("messages", [])
 
             for msg in messages:
@@ -648,25 +391,47 @@ class DeerFlowClient:
                 if msg_id:
                     seen_ids.add(msg_id)
 
-                # Already streamed via ``messages`` mode; only (defensively)
-                # capture usage here and skip re-synthesizing the event.
-                if msg_id and msg_id in streamed_ids:
-                    if isinstance(msg, AIMessage):
-                        _account_usage(msg_id, getattr(msg, "usage_metadata", None))
-                    continue
-
                 if isinstance(msg, AIMessage):
-                    counted_usage = _account_usage(msg_id, msg.usage_metadata)
+                    # Track token usage from AI messages
+                    usage = getattr(msg, "usage_metadata", None)
+                    if usage:
+                        cumulative_usage["input_tokens"] += usage.get("input_tokens", 0) or 0
+                        cumulative_usage["output_tokens"] += usage.get("output_tokens", 0) or 0
+                        cumulative_usage["total_tokens"] += usage.get("total_tokens", 0) or 0
 
                     if msg.tool_calls:
-                        yield self._ai_tool_calls_event(msg_id, msg.tool_calls)
+                        yield StreamEvent(
+                            type="messages-tuple",
+                            data={
+                                "type": "ai",
+                                "content": "",
+                                "id": msg_id,
+                                "tool_calls": [{"name": tc["name"], "args": tc["args"], "id": tc.get("id")} for tc in msg.tool_calls],
+                            },
+                        )
 
                     text = self._extract_text(msg.content)
                     if text:
-                        yield self._ai_text_event(msg_id, text, counted_usage)
+                        event_data: dict[str, Any] = {"type": "ai", "content": text, "id": msg_id}
+                        if usage:
+                            event_data["usage_metadata"] = {
+                                "input_tokens": usage.get("input_tokens", 0) or 0,
+                                "output_tokens": usage.get("output_tokens", 0) or 0,
+                                "total_tokens": usage.get("total_tokens", 0) or 0,
+                            }
+                        yield StreamEvent(type="messages-tuple", data=event_data)
 
                 elif isinstance(msg, ToolMessage):
-                    yield self._tool_message_event(msg)
+                    yield StreamEvent(
+                        type="messages-tuple",
+                        data={
+                            "type": "tool",
+                            "content": self._extract_text(msg.content),
+                            "name": getattr(msg, "name", None),
+                            "tool_call_id": getattr(msg, "tool_call_id", None),
+                            "id": msg_id,
+                        },
+                    )
 
             # Emit a values event for each state snapshot
             yield StreamEvent(
@@ -683,12 +448,10 @@ class DeerFlowClient:
     def chat(self, message: str, *, thread_id: str | None = None, **kwargs) -> str:
         """Send a message and return the final text response.
 
-        Convenience wrapper around :meth:`stream` that accumulates delta
-        ``messages-tuple`` events per ``id`` and returns the text of the
-        **last** AI message to complete.  Intermediate AI messages (e.g.
-        planner drafts) are discarded — only the final id's accumulated
-        text is returned.  Use :meth:`stream` directly if you need every
-        delta as it arrives.
+        Convenience wrapper around :meth:`stream` that returns only the
+        **last** AI text from ``messages-tuple`` events. If the agent emits
+        multiple text segments in one turn, intermediate segments are
+        discarded. Use :meth:`stream` directly to capture all events.
 
         Args:
             message: User message text.
@@ -696,21 +459,15 @@ class DeerFlowClient:
             **kwargs: Override client defaults (same as stream()).
 
         Returns:
-            The accumulated text of the last AI message, or empty string
-            if no AI text was produced.
+            The last AI message text, or empty string if no response.
         """
-        # Per-id delta lists joined once at the end — avoids the O(n²) cost
-        # of repeated ``str + str`` on a growing buffer for long responses.
-        chunks: dict[str, list[str]] = {}
-        last_id: str = ""
+        last_text = ""
         for event in self.stream(message, thread_id=thread_id, **kwargs):
             if event.type == "messages-tuple" and event.data.get("type") == "ai":
-                msg_id = event.data.get("id") or ""
-                delta = event.data.get("content", "")
-                if delta:
-                    chunks.setdefault(msg_id, []).append(delta)
-                    last_id = msg_id
-        return "".join(chunks.get(last_id, ()))
+                content = event.data.get("content", "")
+                if content:
+                    last_text = content
+        return last_text
 
     # ------------------------------------------------------------------
     # Public API — configuration queries
@@ -770,19 +527,19 @@ class DeerFlowClient:
         """
         from deerflow.agents.memory.updater import get_memory_data
 
-        return get_memory_data(user_id=get_effective_user_id())
+        return get_memory_data()
 
     def export_memory(self) -> dict:
         """Export current memory data for backup or transfer."""
         from deerflow.agents.memory.updater import get_memory_data
 
-        return get_memory_data(user_id=get_effective_user_id())
+        return get_memory_data()
 
     def import_memory(self, memory_data: dict) -> dict:
         """Import and persist full memory data."""
         from deerflow.agents.memory.updater import import_memory_data
 
-        return import_memory_data(memory_data, user_id=get_effective_user_id())
+        return import_memory_data(memory_data)
 
     def get_model(self, name: str) -> dict | None:
         """Get a specific model's configuration by name.
@@ -957,13 +714,13 @@ class DeerFlowClient:
         """
         from deerflow.agents.memory.updater import reload_memory_data
 
-        return reload_memory_data(user_id=get_effective_user_id())
+        return reload_memory_data()
 
     def clear_memory(self) -> dict:
         """Clear all persisted memory data."""
         from deerflow.agents.memory.updater import clear_memory_data
 
-        return clear_memory_data(user_id=get_effective_user_id())
+        return clear_memory_data()
 
     def create_memory_fact(self, content: str, category: str = "context", confidence: float = 0.5) -> dict:
         """Create a single fact manually."""
@@ -1180,7 +937,7 @@ class DeerFlowClient:
             ValueError: If the path is invalid.
         """
         try:
-            actual = get_paths().resolve_virtual_path(thread_id, path, user_id=get_effective_user_id())
+            actual = get_paths().resolve_virtual_path(thread_id, path)
         except ValueError as exc:
             if "traversal" in str(exc):
                 from deerflow.uploads.manager import PathTraversalError

backend/packages/harness/deerflow/community/aio_sandbox/aio_sandbox_provider.py

@@ -27,7 +27,6 @@ except ImportError:  # pragma: no cover - Windows fallback
 
 from deerflow.config import get_app_config
 from deerflow.config.paths import VIRTUAL_PATH_PREFIX, get_paths
-from deerflow.runtime.user_context import get_effective_user_id
 from deerflow.sandbox.sandbox import Sandbox
 from deerflow.sandbox.sandbox_provider import SandboxProvider
 
@@ -113,9 +112,6 @@ class AioSandboxProvider(SandboxProvider):
         atexit.register(self.shutdown)
         self._register_signal_handlers()
 
-        # Reconcile orphaned containers from previous process lifecycles
-        self._reconcile_orphans()
-
         # Start idle checker if enabled
         if self._config.get("idle_timeout", DEFAULT_IDLE_TIMEOUT) > 0:
             self._start_idle_checker()
@@ -179,51 +175,6 @@ class AioSandboxProvider(SandboxProvider):
                 resolved[key] = str(value)
         return resolved
 
-    # ── Startup reconciliation ────────────────────────────────────────────
-
-    def _reconcile_orphans(self) -> None:
-        """Reconcile orphaned containers left by previous process lifecycles.
-
-        On startup, enumerate all running containers matching our prefix
-        and adopt them all into the warm pool.  The idle checker will reclaim
-        containers that nobody re-acquires within ``idle_timeout``.
-
-        All containers are adopted unconditionally because we cannot
-        distinguish "orphaned" from "actively used by another process"
-        based on age alone — ``idle_timeout`` represents inactivity, not
-        uptime.  Adopting into the warm pool and letting the idle checker
-        decide avoids destroying containers that a concurrent process may
-        still be using.
-
-        This closes the fundamental gap where in-memory state loss (process
-        restart, crash, SIGKILL) leaves Docker containers running forever.
-        """
-        try:
-            running = self._backend.list_running()
-        except Exception as e:
-            logger.warning(f"Failed to enumerate running containers during startup reconciliation: {e}")
-            return
-
-        if not running:
-            return
-
-        current_time = time.time()
-        adopted = 0
-
-        for info in running:
-            age = current_time - info.created_at if info.created_at > 0 else float("inf")
-            # Single lock acquisition per container: atomic check-and-insert.
-            # Avoids a TOCTOU window between the "already tracked?" check and
-            # the warm-pool insert.
-            with self._lock:
-                if info.sandbox_id in self._sandboxes or info.sandbox_id in self._warm_pool:
-                    continue
-                self._warm_pool[info.sandbox_id] = (info, current_time)
-            adopted += 1
-            logger.info(f"Adopted container {info.sandbox_id} into warm pool (age: {age:.0f}s)")
-
-        logger.info(f"Startup reconciliation complete: {adopted} adopted into warm pool, {len(running)} total found")
-
     # ── Deterministic ID ─────────────────────────────────────────────────
 
     @staticmethod
@@ -261,16 +212,15 @@ class AioSandboxProvider(SandboxProvider):
         mounted Docker socket (DooD), the host Docker daemon can resolve the paths.
         """
         paths = get_paths()
-        user_id = get_effective_user_id()
-        paths.ensure_thread_dirs(thread_id, user_id=user_id)
+        paths.ensure_thread_dirs(thread_id)
 
         return [
-            (paths.host_sandbox_work_dir(thread_id, user_id=user_id), f"{VIRTUAL_PATH_PREFIX}/workspace", False),
-            (paths.host_sandbox_uploads_dir(thread_id, user_id=user_id), f"{VIRTUAL_PATH_PREFIX}/uploads", False),
-            (paths.host_sandbox_outputs_dir(thread_id, user_id=user_id), f"{VIRTUAL_PATH_PREFIX}/outputs", False),
+            (paths.host_sandbox_work_dir(thread_id), f"{VIRTUAL_PATH_PREFIX}/workspace", False),
+            (paths.host_sandbox_uploads_dir(thread_id), f"{VIRTUAL_PATH_PREFIX}/uploads", False),
+            (paths.host_sandbox_outputs_dir(thread_id), f"{VIRTUAL_PATH_PREFIX}/outputs", False),
             # ACP workspace: read-only inside the sandbox (lead agent reads results;
             # the ACP subprocess writes from the host side, not from within the container).
-            (paths.host_acp_workspace_dir(thread_id, user_id=user_id), "/mnt/acp-workspace", True),
+            (paths.host_acp_workspace_dir(thread_id), "/mnt/acp-workspace", True),
         ]
 
     @staticmethod
@@ -366,23 +316,13 @@ class AioSandboxProvider(SandboxProvider):
     # ── Signal handling ──────────────────────────────────────────────────
 
     def _register_signal_handlers(self) -> None:
-        """Register signal handlers for graceful shutdown.
-
-        Handles SIGTERM, SIGINT, and SIGHUP (terminal close) to ensure
-        sandbox containers are cleaned up even when the user closes the terminal.
-        """
+        """Register signal handlers for graceful shutdown."""
         self._original_sigterm = signal.getsignal(signal.SIGTERM)
         self._original_sigint = signal.getsignal(signal.SIGINT)
-        self._original_sighup = signal.getsignal(signal.SIGHUP) if hasattr(signal, "SIGHUP") else None
 
         def signal_handler(signum, frame):
             self.shutdown()
-            if signum == signal.SIGTERM:
-                original = self._original_sigterm
-            elif hasattr(signal, "SIGHUP") and signum == signal.SIGHUP:
-                original = self._original_sighup
-            else:
-                original = self._original_sigint
+            original = self._original_sigterm if signum == signal.SIGTERM else self._original_sigint
             if callable(original):
                 original(signum, frame)
             elif original == signal.SIG_DFL:
@@ -392,8 +332,6 @@ class AioSandboxProvider(SandboxProvider):
         try:
             signal.signal(signal.SIGTERM, signal_handler)
             signal.signal(signal.SIGINT, signal_handler)
-            if hasattr(signal, "SIGHUP"):
-                signal.signal(signal.SIGHUP, signal_handler)
         except ValueError:
             logger.debug("Could not register signal handlers (not main thread)")
 
@@ -482,9 +420,8 @@ class AioSandboxProvider(SandboxProvider):
         across multiple processes, preventing container-name conflicts.
         """
         paths = get_paths()
-        user_id = get_effective_user_id()
-        paths.ensure_thread_dirs(thread_id, user_id=user_id)
-        lock_path = paths.thread_dir(thread_id, user_id=user_id) / f"{sandbox_id}.lock"
+        paths.ensure_thread_dirs(thread_id)
+        lock_path = paths.thread_dir(thread_id) / f"{sandbox_id}.lock"
 
         with open(lock_path, "a", encoding="utf-8") as lock_file:
             locked = False

backend/packages/harness/deerflow/community/aio_sandbox/backend.py

@@ -96,19 +96,3 @@ class SandboxBackend(ABC):
             SandboxInfo if found and healthy, None otherwise.
         """
         ...
-
-    def list_running(self) -> list[SandboxInfo]:
-        """Enumerate all running sandboxes managed by this backend.
-
-        Used for startup reconciliation: when the process restarts, it needs
-        to discover containers started by previous processes so they can be
-        adopted into the warm pool or destroyed if idle too long.
-
-        The default implementation returns an empty list, which is correct
-        for backends that don't manage local containers (e.g., RemoteSandboxBackend
-        delegates lifecycle to the provisioner which handles its own cleanup).
-
-        Returns:
-            A list of SandboxInfo for all currently running sandboxes.
-        """
-        return []

backend/packages/harness/deerflow/community/aio_sandbox/local_backend.py

@@ -6,11 +6,9 @@ Handles container lifecycle, port allocation, and cross-process container discov
 
 from __future__ import annotations
 
-import json
 import logging
 import os
 import subprocess
-from datetime import datetime
 
 from deerflow.utils.network import get_free_port, release_port
 
@@ -20,52 +18,6 @@ from .sandbox_info import SandboxInfo
 logger = logging.getLogger(__name__)
 
 
-def _parse_docker_timestamp(raw: str) -> float:
-    """Parse Docker's ISO 8601 timestamp into a Unix epoch float.
-
-    Docker returns timestamps with nanosecond precision and a trailing ``Z``
-    (e.g. ``2026-04-08T01:22:50.123456789Z``).  Python's ``fromisoformat``
-    accepts at most microseconds and (pre-3.11) does not accept ``Z``, so the
-    string is normalized before parsing.  Returns ``0.0`` on empty input or
-    parse failure so callers can use ``0.0`` as a sentinel for "unknown age".
-    """
-    if not raw:
-        return 0.0
-    try:
-        s = raw.strip()
-        if "." in s:
-            dot_pos = s.index(".")
-            tz_start = dot_pos + 1
-            while tz_start < len(s) and s[tz_start].isdigit():
-                tz_start += 1
-            frac = s[dot_pos + 1 : tz_start][:6]  # truncate to microseconds
-            tz_suffix = s[tz_start:]
-            s = s[: dot_pos + 1] + frac + tz_suffix
-        if s.endswith("Z"):
-            s = s[:-1] + "+00:00"
-        return datetime.fromisoformat(s).timestamp()
-    except (ValueError, TypeError) as e:
-        logger.debug(f"Could not parse docker timestamp {raw!r}: {e}")
-        return 0.0
-
-
-def _extract_host_port(inspect_entry: dict, container_port: int) -> int | None:
-    """Extract the host port mapped to ``container_port/tcp`` from a docker inspect entry.
-
-    Returns None if the container has no port mapping for that port.
-    """
-    try:
-        ports = (inspect_entry.get("NetworkSettings") or {}).get("Ports") or {}
-        bindings = ports.get(f"{container_port}/tcp") or []
-        if bindings:
-            host_port = bindings[0].get("HostPort")
-            if host_port:
-                return int(host_port)
-    except (ValueError, TypeError, AttributeError):
-        pass
-    return None
-
-
 def _format_container_mount(runtime: str, host_path: str, container_path: str, read_only: bool) -> list[str]:
     """Format a bind-mount argument for the selected runtime.
 
@@ -220,12 +172,8 @@ class LocalContainerBackend(SandboxBackend):
 
     def destroy(self, info: SandboxInfo) -> None:
         """Stop the container and release its port."""
-        # Prefer container_id, fall back to container_name (both accepted by docker stop).
-        # This ensures containers discovered via list_running() (which only has the name)
-        # can also be stopped.
-        stop_target = info.container_id or info.container_name
-        if stop_target:
-            self._stop_container(stop_target)
+        if info.container_id:
+            self._stop_container(info.container_id)
         # Extract port from sandbox_url for release
         try:
             from urllib.parse import urlparse
@@ -274,129 +222,6 @@ class LocalContainerBackend(SandboxBackend):
             container_name=container_name,
         )
 
-    def list_running(self) -> list[SandboxInfo]:
-        """Enumerate all running containers matching the configured prefix.
-
-        Uses a single ``docker ps`` call to list container names, then a
-        single batched ``docker inspect`` call to retrieve creation timestamp
-        and port mapping for all containers at once.  Total subprocess calls:
-        2 (down from 2N+1 in the naive per-container approach).
-
-        Note: Docker's ``--filter name=`` performs *substring* matching,
-        so a secondary ``startswith`` check is applied to ensure only
-        containers with the exact prefix are included.
-
-        Containers without port mappings are still included (with empty
-        sandbox_url) so that startup reconciliation can adopt orphans
-        regardless of their port state.
-        """
-        # Step 1: enumerate container names via docker ps
-        try:
-            result = subprocess.run(
-                [
-                    self._runtime,
-                    "ps",
-                    "--filter",
-                    f"name={self._container_prefix}-",
-                    "--format",
-                    "{{.Names}}",
-                ],
-                capture_output=True,
-                text=True,
-                timeout=10,
-            )
-            if result.returncode != 0:
-                stderr = (result.stderr or "").strip()
-                logger.warning(
-                    "Failed to list running containers with %s ps (returncode=%s, stderr=%s)",
-                    self._runtime,
-                    result.returncode,
-                    stderr or "<empty>",
-                )
-                return []
-            if not result.stdout.strip():
-                return []
-        except (subprocess.CalledProcessError, subprocess.TimeoutExpired, FileNotFoundError, OSError) as e:
-            logger.warning(f"Failed to list running containers: {e}")
-            return []
-
-        # Filter to names matching our exact prefix (docker filter is substring-based)
-        container_names = [name.strip() for name in result.stdout.strip().splitlines() if name.strip().startswith(self._container_prefix + "-")]
-        if not container_names:
-            return []
-
-        # Step 2: batched docker inspect — single subprocess call for all containers
-        inspections = self._batch_inspect(container_names)
-
-        infos: list[SandboxInfo] = []
-        sandbox_host = os.environ.get("DEER_FLOW_SANDBOX_HOST", "localhost")
-        for container_name in container_names:
-            data = inspections.get(container_name)
-            if data is None:
-                # Container disappeared between ps and inspect, or inspect failed
-                continue
-            created_at, host_port = data
-            sandbox_id = container_name[len(self._container_prefix) + 1 :]
-            sandbox_url = f"http://{sandbox_host}:{host_port}" if host_port else ""
-
-            infos.append(
-                SandboxInfo(
-                    sandbox_id=sandbox_id,
-                    sandbox_url=sandbox_url,
-                    container_name=container_name,
-                    created_at=created_at,
-                )
-            )
-
-        logger.info(f"Found {len(infos)} running sandbox container(s)")
-        return infos
-
-    def _batch_inspect(self, container_names: list[str]) -> dict[str, tuple[float, int | None]]:
-        """Batch-inspect containers in a single subprocess call.
-
-        Returns a mapping of ``container_name -> (created_at, host_port)``.
-        Missing containers or parse failures are silently dropped from the result.
-        """
-        if not container_names:
-            return {}
-        try:
-            result = subprocess.run(
-                [self._runtime, "inspect", *container_names],
-                capture_output=True,
-                text=True,
-                timeout=15,
-            )
-        except (subprocess.CalledProcessError, subprocess.TimeoutExpired, FileNotFoundError, OSError) as e:
-            logger.warning(f"Failed to batch-inspect containers: {e}")
-            return {}
-
-        if result.returncode != 0:
-            stderr = (result.stderr or "").strip()
-            logger.warning(
-                "Failed to batch-inspect containers with %s inspect (returncode=%s, stderr=%s)",
-                self._runtime,
-                result.returncode,
-                stderr or "<empty>",
-            )
-            return {}
-
-        try:
-            payload = json.loads(result.stdout or "[]")
-        except json.JSONDecodeError as e:
-            logger.warning(f"Failed to parse docker inspect output as JSON: {e}")
-            return {}
-
-        out: dict[str, tuple[float, int | None]] = {}
-        for entry in payload:
-            # ``Name`` is prefixed with ``/`` in the docker inspect response
-            name = (entry.get("Name") or "").lstrip("/")
-            if not name:
-                continue
-            created_at = _parse_docker_timestamp(entry.get("Created", ""))
-            host_port = _extract_host_port(entry, 8080)
-            out[name] = (created_at, host_port)
-        return out
-
     # ── Container operations ─────────────────────────────────────────────
 
     def _start_container(

backend/packages/harness/deerflow/community/exa/tools.py

@@ -1,79 +0,0 @@
-import json
-
-from exa_py import Exa
-from langchain.tools import tool
-
-from deerflow.config import get_app_config
-
-
-def _get_exa_client(tool_name: str = "web_search") -> Exa:
-    config = get_app_config().get_tool_config(tool_name)
-    api_key = None
-    if config is not None and "api_key" in config.model_extra:
-        api_key = config.model_extra.get("api_key")
-    return Exa(api_key=api_key)
-
-
-@tool("web_search", parse_docstring=True)
-def web_search_tool(query: str) -> str:
-    """Search the web.
-
-    Args:
-        query: The query to search for.
-    """
-    try:
-        config = get_app_config().get_tool_config("web_search")
-        max_results = 5
-        search_type = "auto"
-        contents_max_characters = 1000
-        if config is not None:
-            max_results = config.model_extra.get("max_results", max_results)
-            search_type = config.model_extra.get("search_type", search_type)
-            contents_max_characters = config.model_extra.get("contents_max_characters", contents_max_characters)
-
-        client = _get_exa_client()
-        res = client.search(
-            query,
-            type=search_type,
-            num_results=max_results,
-            contents={"highlights": {"max_characters": contents_max_characters}},
-        )
-
-        normalized_results = [
-            {
-                "title": result.title or "",
-                "url": result.url or "",
-                "snippet": "\n".join(result.highlights) if result.highlights else "",
-            }
-            for result in res.results
-        ]
-        json_results = json.dumps(normalized_results, indent=2, ensure_ascii=False)
-        return json_results
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-
-@tool("web_fetch", parse_docstring=True)
-def web_fetch_tool(url: str) -> str:
-    """Fetch the contents of a web page at a given URL.
-    Only fetch EXACT URLs that have been provided directly by the user or have been returned in results from the web_search and web_fetch tools.
-    This tool can NOT access content that requires authentication, such as private Google Docs or pages behind login walls.
-    Do NOT add www. to URLs that do NOT have them.
-    URLs must include the schema: https://example.com is a valid URL while example.com is an invalid URL.
-
-    Args:
-        url: The URL to fetch the contents of.
-    """
-    try:
-        client = _get_exa_client("web_fetch")
-        res = client.get_contents([url], text={"max_characters": 4096})
-
-        if res.results:
-            result = res.results[0]
-            title = result.title or "Untitled"
-            text = result.text or ""
-            return f"# {title}\n\n{text[:4096]}"
-        else:
-            return "Error: No results found"
-    except Exception as e:
-        return f"Error: {str(e)}"

backend/packages/harness/deerflow/community/firecrawl/tools.py

@@ -6,10 +6,10 @@ from langchain.tools import tool
 from deerflow.config import get_app_config
 
 
-def _get_firecrawl_client(tool_name: str = "web_search") -> FirecrawlApp:
-    config = get_app_config().get_tool_config(tool_name)
+def _get_firecrawl_client() -> FirecrawlApp:
+    config = get_app_config().get_tool_config("web_search")
     api_key = None
-    if config is not None and "api_key" in config.model_extra:
+    if config is not None:
         api_key = config.model_extra.get("api_key")
     return FirecrawlApp(api_key=api_key)  # type: ignore[arg-type]
 
@@ -27,7 +27,7 @@ def web_search_tool(query: str) -> str:
         if config is not None:
             max_results = config.model_extra.get("max_results", max_results)
 
-        client = _get_firecrawl_client("web_search")
+        client = _get_firecrawl_client()
         result = client.search(query, limit=max_results)
 
         # result.web contains list of SearchResultWeb objects
@@ -58,7 +58,7 @@ def web_fetch_tool(url: str) -> str:
         url: The URL to fetch the contents of.
     """
     try:
-        client = _get_firecrawl_client("web_fetch")
+        client = _get_firecrawl_client()
         result = client.scrape(url, formats=["markdown"])
 
         markdown_content = result.markdown or ""

backend/packages/harness/deerflow/config/database_config.py

@@ -4,12 +4,8 @@ Controls BOTH the LangGraph checkpointer and the DeerFlow application
 persistence layer (runs, threads metadata, users, etc.). The user
 configures one backend; the system handles physical separation details.
 
-SQLite mode: checkpointer and app share a single .db file
-({sqlite_dir}/deerflow.db) with WAL journal mode enabled on every
-connection. WAL allows concurrent readers and a single writer without
-blocking, making a unified file safe for both workloads.  Writers
-that contend for the lock wait via the default 5-second sqlite3
-busy timeout rather than failing immediately.
+SQLite mode: checkpointer and app use different .db files in the same
+directory to avoid write-lock contention. This is automatic.
 
 Postgres mode: both use the same database URL but maintain independent
 connection pools with different lifecycles.
@@ -44,7 +40,7 @@ class DatabaseConfig(BaseModel):
     )
     sqlite_dir: str = Field(
         default=".deer-flow/data",
-        description=("Directory for the SQLite database file. Both checkpointer and application data share {sqlite_dir}/deerflow.db."),
+        description=("Directory for SQLite database files. Checkpointer uses {sqlite_dir}/checkpoints.db, application data uses {sqlite_dir}/app.db."),
     )
     postgres_url: str = Field(
         default="",
@@ -73,27 +69,21 @@ class DatabaseConfig(BaseModel):
 
         return str(Path(self.sqlite_dir).resolve())
 
-    @property
-    def sqlite_path(self) -> str:
-        """Unified SQLite file path shared by checkpointer and app."""
-        return os.path.join(self._resolved_sqlite_dir, "deerflow.db")
-
-    # Backward-compatible aliases
     @property
     def checkpointer_sqlite_path(self) -> str:
-        """SQLite file path for the LangGraph checkpointer (alias for sqlite_path)."""
-        return self.sqlite_path
+        """SQLite file path for the LangGraph checkpointer."""
+        return os.path.join(self._resolved_sqlite_dir, "checkpoints.db")
 
     @property
     def app_sqlite_path(self) -> str:
-        """SQLite file path for application ORM data (alias for sqlite_path)."""
-        return self.sqlite_path
+        """SQLite file path for application ORM data."""
+        return os.path.join(self._resolved_sqlite_dir, "app.db")
 
     @property
     def app_sqlalchemy_url(self) -> str:
         """SQLAlchemy async URL for the application ORM engine."""
         if self.backend == "sqlite":
-            return f"sqlite+aiosqlite:///{self.sqlite_path}"
+            return f"sqlite+aiosqlite:///{self.app_sqlite_path}"
         if self.backend == "postgres":
             url = self.postgres_url
             if url.startswith("postgresql://"):

backend/packages/harness/deerflow/config/memory_config.py

@@ -14,9 +14,8 @@ class MemoryConfig(BaseModel):
         default="",
         description=(
             "Path to store memory data. "
-            "If empty, defaults to per-user memory at `{base_dir}/users/{user_id}/memory.json`. "
-            "Absolute paths are used as-is and opt out of per-user isolation "
-            "(all users share the same file). "
+            "If empty, defaults to `{base_dir}/memory.json` (see Paths.memory_file). "
+            "Absolute paths are used as-is. "
             "Relative paths are resolved against `Paths.base_dir` "
             "(not the backend working directory). "
             "Note: if you previously set this to `.deer-flow/memory.json`, "

backend/packages/harness/deerflow/config/model_config.py

@@ -27,10 +27,6 @@ class ModelConfig(BaseModel):
         default_factory=lambda: None,
         description="Extra settings to be passed to the model when thinking is enabled",
     )
-    when_thinking_disabled: dict | None = Field(
-        default_factory=lambda: None,
-        description="Extra settings to be passed to the model when thinking is disabled",
-    )
     supports_vision: bool = Field(default_factory=lambda: False, description="Whether the model supports vision/image inputs")
     thinking: dict | None = Field(
         default_factory=lambda: None,

backend/packages/harness/deerflow/config/paths.py

@@ -7,7 +7,6 @@ from pathlib import Path, PureWindowsPath
 VIRTUAL_PATH_PREFIX = "/mnt/user-data"
 
 _SAFE_THREAD_ID_RE = re.compile(r"^[A-Za-z0-9_\-]+$")
-_SAFE_USER_ID_RE = re.compile(r"^[A-Za-z0-9_\-]+$")
 
 
 def _default_local_base_dir() -> Path:
@@ -23,13 +22,6 @@ def _validate_thread_id(thread_id: str) -> str:
     return thread_id
 
 
-def _validate_user_id(user_id: str) -> str:
-    """Validate a user ID before using it in filesystem paths."""
-    if not _SAFE_USER_ID_RE.match(user_id):
-        raise ValueError(f"Invalid user_id {user_id!r}: only alphanumeric characters, hyphens, and underscores are allowed.")
-    return user_id
-
-
 def _join_host_path(base: str, *parts: str) -> str:
     """Join host filesystem path segments while preserving native style.
 
@@ -142,63 +134,44 @@ class Paths:
         """Per-agent memory file: `{base_dir}/agents/{name}/memory.json`."""
         return self.agent_dir(name) / "memory.json"
 
-    def user_dir(self, user_id: str) -> Path:
-        """Directory for a specific user: `{base_dir}/users/{user_id}/`."""
-        return self.base_dir / "users" / _validate_user_id(user_id)
-
-    def user_memory_file(self, user_id: str) -> Path:
-        """Per-user memory file: `{base_dir}/users/{user_id}/memory.json`."""
-        return self.user_dir(user_id) / "memory.json"
-
-    def user_agent_memory_file(self, user_id: str, agent_name: str) -> Path:
-        """Per-user per-agent memory: `{base_dir}/users/{user_id}/agents/{name}/memory.json`."""
-        return self.user_dir(user_id) / "agents" / agent_name.lower() / "memory.json"
-
-    def thread_dir(self, thread_id: str, *, user_id: str | None = None) -> Path:
+    def thread_dir(self, thread_id: str) -> Path:
         """
-        Host path for a thread's data.
-
-        When *user_id* is provided:
-            `{base_dir}/users/{user_id}/threads/{thread_id}/`
-        Otherwise (legacy layout):
-            `{base_dir}/threads/{thread_id}/`
+        Host path for a thread's data: `{base_dir}/threads/{thread_id}/`
 
         This directory contains a `user-data/` subdirectory that is mounted
         as `/mnt/user-data/` inside the sandbox.
 
         Raises:
-            ValueError: If `thread_id` or `user_id` contains unsafe characters (path
-                        separators or `..`) that could cause directory traversal.
+            ValueError: If `thread_id` contains unsafe characters (path separators
+                        or `..`) that could cause directory traversal.
         """
-        if user_id is not None:
-            return self.user_dir(user_id) / "threads" / _validate_thread_id(thread_id)
         return self.base_dir / "threads" / _validate_thread_id(thread_id)
 
-    def sandbox_work_dir(self, thread_id: str, *, user_id: str | None = None) -> Path:
+    def sandbox_work_dir(self, thread_id: str) -> Path:
         """
         Host path for the agent's workspace directory.
         Host: `{base_dir}/threads/{thread_id}/user-data/workspace/`
         Sandbox: `/mnt/user-data/workspace/`
         """
-        return self.thread_dir(thread_id, user_id=user_id) / "user-data" / "workspace"
+        return self.thread_dir(thread_id) / "user-data" / "workspace"
 
-    def sandbox_uploads_dir(self, thread_id: str, *, user_id: str | None = None) -> Path:
+    def sandbox_uploads_dir(self, thread_id: str) -> Path:
         """
         Host path for user-uploaded files.
         Host: `{base_dir}/threads/{thread_id}/user-data/uploads/`
         Sandbox: `/mnt/user-data/uploads/`
         """
-        return self.thread_dir(thread_id, user_id=user_id) / "user-data" / "uploads"
+        return self.thread_dir(thread_id) / "user-data" / "uploads"
 
-    def sandbox_outputs_dir(self, thread_id: str, *, user_id: str | None = None) -> Path:
+    def sandbox_outputs_dir(self, thread_id: str) -> Path:
         """
         Host path for agent-generated artifacts.
         Host: `{base_dir}/threads/{thread_id}/user-data/outputs/`
         Sandbox: `/mnt/user-data/outputs/`
         """
-        return self.thread_dir(thread_id, user_id=user_id) / "user-data" / "outputs"
+        return self.thread_dir(thread_id) / "user-data" / "outputs"
 
-    def acp_workspace_dir(self, thread_id: str, *, user_id: str | None = None) -> Path:
+    def acp_workspace_dir(self, thread_id: str) -> Path:
         """
         Host path for the ACP workspace of a specific thread.
         Host: `{base_dir}/threads/{thread_id}/acp-workspace/`
@@ -207,43 +180,41 @@ class Paths:
         Each thread gets its own isolated ACP workspace so that concurrent
         sessions cannot read each other's ACP agent outputs.
         """
-        return self.thread_dir(thread_id, user_id=user_id) / "acp-workspace"
+        return self.thread_dir(thread_id) / "acp-workspace"
 
-    def sandbox_user_data_dir(self, thread_id: str, *, user_id: str | None = None) -> Path:
+    def sandbox_user_data_dir(self, thread_id: str) -> Path:
         """
         Host path for the user-data root.
         Host: `{base_dir}/threads/{thread_id}/user-data/`
         Sandbox: `/mnt/user-data/`
         """
-        return self.thread_dir(thread_id, user_id=user_id) / "user-data"
+        return self.thread_dir(thread_id) / "user-data"
 
-    def host_thread_dir(self, thread_id: str, *, user_id: str | None = None) -> str:
+    def host_thread_dir(self, thread_id: str) -> str:
         """Host path for a thread directory, preserving Windows path syntax."""
-        if user_id is not None:
-            return _join_host_path(self._host_base_dir_str(), "users", _validate_user_id(user_id), "threads", _validate_thread_id(thread_id))
         return _join_host_path(self._host_base_dir_str(), "threads", _validate_thread_id(thread_id))
 
-    def host_sandbox_user_data_dir(self, thread_id: str, *, user_id: str | None = None) -> str:
+    def host_sandbox_user_data_dir(self, thread_id: str) -> str:
         """Host path for a thread's user-data root."""
-        return _join_host_path(self.host_thread_dir(thread_id, user_id=user_id), "user-data")
+        return _join_host_path(self.host_thread_dir(thread_id), "user-data")
 
-    def host_sandbox_work_dir(self, thread_id: str, *, user_id: str | None = None) -> str:
+    def host_sandbox_work_dir(self, thread_id: str) -> str:
         """Host path for the workspace mount source."""
-        return _join_host_path(self.host_sandbox_user_data_dir(thread_id, user_id=user_id), "workspace")
+        return _join_host_path(self.host_sandbox_user_data_dir(thread_id), "workspace")
 
-    def host_sandbox_uploads_dir(self, thread_id: str, *, user_id: str | None = None) -> str:
+    def host_sandbox_uploads_dir(self, thread_id: str) -> str:
         """Host path for the uploads mount source."""
-        return _join_host_path(self.host_sandbox_user_data_dir(thread_id, user_id=user_id), "uploads")
+        return _join_host_path(self.host_sandbox_user_data_dir(thread_id), "uploads")
 
-    def host_sandbox_outputs_dir(self, thread_id: str, *, user_id: str | None = None) -> str:
+    def host_sandbox_outputs_dir(self, thread_id: str) -> str:
         """Host path for the outputs mount source."""
-        return _join_host_path(self.host_sandbox_user_data_dir(thread_id, user_id=user_id), "outputs")
+        return _join_host_path(self.host_sandbox_user_data_dir(thread_id), "outputs")
 
-    def host_acp_workspace_dir(self, thread_id: str, *, user_id: str | None = None) -> str:
+    def host_acp_workspace_dir(self, thread_id: str) -> str:
         """Host path for the ACP workspace mount source."""
-        return _join_host_path(self.host_thread_dir(thread_id, user_id=user_id), "acp-workspace")
+        return _join_host_path(self.host_thread_dir(thread_id), "acp-workspace")
 
-    def ensure_thread_dirs(self, thread_id: str, *, user_id: str | None = None) -> None:
+    def ensure_thread_dirs(self, thread_id: str) -> None:
         """Create all standard sandbox directories for a thread.
 
         Directories are created with mode 0o777 so that sandbox containers
@@ -257,24 +228,24 @@ class Paths:
         ACP agent invocation.
         """
         for d in [
-            self.sandbox_work_dir(thread_id, user_id=user_id),
-            self.sandbox_uploads_dir(thread_id, user_id=user_id),
-            self.sandbox_outputs_dir(thread_id, user_id=user_id),
-            self.acp_workspace_dir(thread_id, user_id=user_id),
+            self.sandbox_work_dir(thread_id),
+            self.sandbox_uploads_dir(thread_id),
+            self.sandbox_outputs_dir(thread_id),
+            self.acp_workspace_dir(thread_id),
         ]:
             d.mkdir(parents=True, exist_ok=True)
             d.chmod(0o777)
 
-    def delete_thread_dir(self, thread_id: str, *, user_id: str | None = None) -> None:
+    def delete_thread_dir(self, thread_id: str) -> None:
         """Delete all persisted data for a thread.
 
         The operation is idempotent: missing thread directories are ignored.
         """
-        thread_dir = self.thread_dir(thread_id, user_id=user_id)
+        thread_dir = self.thread_dir(thread_id)
         if thread_dir.exists():
             shutil.rmtree(thread_dir)
 
-    def resolve_virtual_path(self, thread_id: str, virtual_path: str, *, user_id: str | None = None) -> Path:
+    def resolve_virtual_path(self, thread_id: str, virtual_path: str) -> Path:
         """Resolve a sandbox virtual path to the actual host filesystem path.
 
         Args:
@@ -282,7 +253,6 @@ class Paths:
             virtual_path: Virtual path as seen inside the sandbox, e.g.
                           ``/mnt/user-data/outputs/report.pdf``.
                           Leading slashes are stripped before matching.
-            user_id: Optional user ID for user-scoped path resolution.
 
         Returns:
             The resolved absolute host filesystem path.
@@ -300,7 +270,7 @@ class Paths:
             raise ValueError(f"Path must start with /{prefix}")
 
         relative = stripped[len(prefix) :].lstrip("/")
-        base = self.sandbox_user_data_dir(thread_id, user_id=user_id).resolve()
+        base = self.sandbox_user_data_dir(thread_id).resolve()
         actual = (base / relative).resolve()
 
         try:

backend/packages/harness/deerflow/models/factory.py

@@ -56,7 +56,6 @@ def create_chat_model(name: str | None = None, thinking_enabled: bool = False, *
             "supports_thinking",
             "supports_reasoning_effort",
             "when_thinking_enabled",
-            "when_thinking_disabled",
             "thinking",
             "supports_vision",
         },
@@ -73,24 +72,21 @@ def create_chat_model(name: str | None = None, thinking_enabled: bool = False, *
             raise ValueError(f"Model {name} does not support thinking. Set `supports_thinking` to true in the `config.yaml` to enable thinking.") from None
         if effective_wte:
             model_settings_from_config.update(effective_wte)
-    if not thinking_enabled:
-        if model_config.when_thinking_disabled is not None:
-            # User-provided disable settings take full precedence
-            model_settings_from_config.update(model_config.when_thinking_disabled)
-        elif has_thinking_settings and effective_wte.get("extra_body", {}).get("thinking", {}).get("type"):
+    if not thinking_enabled and has_thinking_settings:
+        if effective_wte.get("extra_body", {}).get("thinking", {}).get("type"):
             # OpenAI-compatible gateway: thinking is nested under extra_body
             model_settings_from_config["extra_body"] = _deep_merge_dicts(
                 model_settings_from_config.get("extra_body"),
                 {"thinking": {"type": "disabled"}},
             )
             model_settings_from_config["reasoning_effort"] = "minimal"
-        elif has_thinking_settings and (disable_chat_template_kwargs := _vllm_disable_chat_template_kwargs(effective_wte.get("extra_body", {}).get("chat_template_kwargs") or {})):
+        elif disable_chat_template_kwargs := _vllm_disable_chat_template_kwargs(effective_wte.get("extra_body", {}).get("chat_template_kwargs") or {}):
             # vLLM uses chat template kwargs to switch thinking on/off.
             model_settings_from_config["extra_body"] = _deep_merge_dicts(
                 model_settings_from_config.get("extra_body"),
                 {"chat_template_kwargs": disable_chat_template_kwargs},
             )
-        elif has_thinking_settings and effective_wte.get("thinking", {}).get("type"):
+        elif effective_wte.get("thinking", {}).get("type"):
             # Native langchain_anthropic: thinking is a direct constructor parameter
             model_settings_from_config["thinking"] = {"type": "disabled"}
     if not model_config.supports_reasoning_effort:

backend/packages/harness/deerflow/models/openai_codex_provider.py

@@ -48,10 +48,6 @@ class CodexChatModel(BaseChatModel):
 
     model_config = {"arbitrary_types_allowed": True}
 
-    @classmethod
-    def is_lc_serializable(cls) -> bool:
-        return True
-
     @property
     def _llm_type(self) -> str:
         return "codex-responses"
@@ -220,48 +216,18 @@ class CodexChatModel(BaseChatModel):
     def _stream_response(self, headers: dict, payload: dict) -> dict:
         """Stream SSE from Codex API and collect the final response."""
         completed_response = None
-        streamed_output_items: dict[int, dict[str, Any]] = {}
 
         with httpx.Client(timeout=300) as client:
             with client.stream("POST", f"{CODEX_BASE_URL}/responses", headers=headers, json=payload) as resp:
                 resp.raise_for_status()
                 for line in resp.iter_lines():
                     data = self._parse_sse_data_line(line)
-                    if not data:
-                        continue
-
-                    event_type = data.get("type")
-                    if event_type == "response.output_item.done":
-                        output_index = data.get("output_index")
-                        output_item = data.get("item")
-                        if isinstance(output_index, int) and isinstance(output_item, dict):
-                            streamed_output_items[output_index] = output_item
-                    elif event_type == "response.completed":
+                    if data and data.get("type") == "response.completed":
                         completed_response = data["response"]
 
         if not completed_response:
             raise RuntimeError("Codex API stream ended without response.completed event")
 
-        # ChatGPT Codex can emit the final assistant content only in stream events.
-        # When response.completed arrives, response.output may still be empty.
-        if streamed_output_items:
-            merged_output = []
-            response_output = completed_response.get("output")
-            if isinstance(response_output, list):
-                merged_output = list(response_output)
-
-            max_index = max(max(streamed_output_items), len(merged_output) - 1)
-            if max_index >= 0 and len(merged_output) <= max_index:
-                merged_output.extend([None] * (max_index + 1 - len(merged_output)))
-
-            for output_index, output_item in streamed_output_items.items():
-                existing_item = merged_output[output_index]
-                if not isinstance(existing_item, dict):
-                    merged_output[output_index] = output_item
-
-            completed_response = dict(completed_response)
-            completed_response["output"] = [item for item in merged_output if isinstance(item, dict)]
-
         return completed_response
 
     @staticmethod

backend/packages/harness/deerflow/models/patched_deepseek.py

@@ -23,14 +23,6 @@ class PatchedChatDeepSeek(ChatDeepSeek):
     request payload.
     """
 
-    @classmethod
-    def is_lc_serializable(cls) -> bool:
-        return True
-
-    @property
-    def lc_secrets(self) -> dict[str, str]:
-        return {"api_key": "DEEPSEEK_API_KEY", "openai_api_key": "DEEPSEEK_API_KEY"}
-
     def _get_request_payload(
         self,
         input_: LanguageModelInput,

backend/packages/harness/deerflow/persistence/engine.py

@@ -86,32 +86,8 @@ async def init_engine(
     if backend == "sqlite":
         import os
 
-        from sqlalchemy import event
-
         os.makedirs(sqlite_dir or ".", exist_ok=True)
         _engine = create_async_engine(url, echo=echo, json_serializer=_json_serializer)
-
-        # Enable WAL on every new connection. SQLite PRAGMA settings are
-        # per-connection, so we wire the listener instead of running PRAGMA
-        # once at startup. WAL gives concurrent reads + writers without
-        # blocking and is the standard recommendation for any production
-        # SQLite deployment (TC-UPG-06 in AUTH_TEST_PLAN.md). The companion
-        # ``synchronous=NORMAL`` is the safe-and-fast pairing — fsync only
-        # at WAL checkpoint boundaries instead of every commit.
-        # Note: we do not set PRAGMA busy_timeout here — Python's sqlite3
-        # driver already defaults to a 5-second busy timeout (see the
-        # ``timeout`` kwarg of ``sqlite3.connect``), and aiosqlite /
-        # SQLAlchemy's aiosqlite dialect inherit that default.  Setting
-        # it again would be a no-op.
-        @event.listens_for(_engine.sync_engine, "connect")
-        def _enable_sqlite_wal(dbapi_conn, _record):  # noqa: ARG001 — SQLAlchemy contract
-            cursor = dbapi_conn.cursor()
-            try:
-                cursor.execute("PRAGMA journal_mode=WAL;")
-                cursor.execute("PRAGMA synchronous=NORMAL;")
-                cursor.execute("PRAGMA foreign_keys=ON;")
-            finally:
-                cursor.close()
     elif backend == "postgres":
         _engine = create_async_engine(
             url,

backend/packages/harness/deerflow/persistence/feedback/model.py

@@ -4,7 +4,7 @@ from __future__ import annotations
 
 from datetime import UTC, datetime
 
-from sqlalchemy import DateTime, String, Text, UniqueConstraint
+from sqlalchemy import DateTime, String, Text
 from sqlalchemy.orm import Mapped, mapped_column
 
 from deerflow.persistence.base import Base
@@ -13,14 +13,10 @@ from deerflow.persistence.base import Base
 class FeedbackRow(Base):
     __tablename__ = "feedback"
 
-    __table_args__ = (
-        UniqueConstraint("thread_id", "run_id", "user_id", name="uq_feedback_thread_run_user"),
-    )
-
     feedback_id: Mapped[str] = mapped_column(String(64), primary_key=True)
     run_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
     thread_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
-    user_id: Mapped[str | None] = mapped_column(String(64), index=True)
+    owner_id: Mapped[str | None] = mapped_column(String(64), index=True)
     message_id: Mapped[str | None] = mapped_column(String(64))
     # message_id is an optional RunEventStore event identifier —
     # allows feedback to target a specific message or the entire run

backend/packages/harness/deerflow/persistence/feedback/sql.py

@@ -12,7 +12,7 @@ from sqlalchemy import case, func, select
 from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
 
 from deerflow.persistence.feedback.model import FeedbackRow
-from deerflow.runtime.user_context import AUTO, _AutoSentinel, resolve_user_id
+from deerflow.runtime.user_context import AUTO, _AutoSentinel, resolve_owner_id
 
 
 class FeedbackRepository:
@@ -33,19 +33,19 @@ class FeedbackRepository:
         run_id: str,
         thread_id: str,
         rating: int,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
         message_id: str | None = None,
         comment: str | None = None,
     ) -> dict:
         """Create a feedback record. rating must be +1 or -1."""
         if rating not in (1, -1):
             raise ValueError(f"rating must be +1 or -1, got {rating}")
-        resolved_user_id = resolve_user_id(user_id, method_name="FeedbackRepository.create")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="FeedbackRepository.create")
         row = FeedbackRow(
             feedback_id=str(uuid.uuid4()),
             run_id=run_id,
             thread_id=thread_id,
-            user_id=resolved_user_id,
+            owner_id=resolved_owner_id,
             message_id=message_id,
             rating=rating,
             comment=comment,
@@ -61,14 +61,14 @@ class FeedbackRepository:
         self,
         feedback_id: str,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ) -> dict | None:
-        resolved_user_id = resolve_user_id(user_id, method_name="FeedbackRepository.get")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="FeedbackRepository.get")
         async with self._sf() as session:
             row = await session.get(FeedbackRow, feedback_id)
             if row is None:
                 return None
-            if resolved_user_id is not None and row.user_id != resolved_user_id:
+            if resolved_owner_id is not None and row.owner_id != resolved_owner_id:
                 return None
             return self._row_to_dict(row)
 
@@ -78,12 +78,12 @@ class FeedbackRepository:
         run_id: str,
         *,
         limit: int = 100,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ) -> list[dict]:
-        resolved_user_id = resolve_user_id(user_id, method_name="FeedbackRepository.list_by_run")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="FeedbackRepository.list_by_run")
         stmt = select(FeedbackRow).where(FeedbackRow.thread_id == thread_id, FeedbackRow.run_id == run_id)
-        if resolved_user_id is not None:
-            stmt = stmt.where(FeedbackRow.user_id == resolved_user_id)
+        if resolved_owner_id is not None:
+            stmt = stmt.where(FeedbackRow.owner_id == resolved_owner_id)
         stmt = stmt.order_by(FeedbackRow.created_at.asc()).limit(limit)
         async with self._sf() as session:
             result = await session.execute(stmt)
@@ -94,12 +94,12 @@ class FeedbackRepository:
         thread_id: str,
         *,
         limit: int = 100,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ) -> list[dict]:
-        resolved_user_id = resolve_user_id(user_id, method_name="FeedbackRepository.list_by_thread")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="FeedbackRepository.list_by_thread")
         stmt = select(FeedbackRow).where(FeedbackRow.thread_id == thread_id)
-        if resolved_user_id is not None:
-            stmt = stmt.where(FeedbackRow.user_id == resolved_user_id)
+        if resolved_owner_id is not None:
+            stmt = stmt.where(FeedbackRow.owner_id == resolved_owner_id)
         stmt = stmt.order_by(FeedbackRow.created_at.asc()).limit(limit)
         async with self._sf() as session:
             result = await session.execute(stmt)
@@ -109,97 +109,19 @@ class FeedbackRepository:
         self,
         feedback_id: str,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ) -> bool:
-        resolved_user_id = resolve_user_id(user_id, method_name="FeedbackRepository.delete")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="FeedbackRepository.delete")
         async with self._sf() as session:
             row = await session.get(FeedbackRow, feedback_id)
             if row is None:
                 return False
-            if resolved_user_id is not None and row.user_id != resolved_user_id:
+            if resolved_owner_id is not None and row.owner_id != resolved_owner_id:
                 return False
             await session.delete(row)
             await session.commit()
             return True
 
-    async def upsert(
-        self,
-        *,
-        run_id: str,
-        thread_id: str,
-        rating: int,
-        user_id: str | None | _AutoSentinel = AUTO,
-        comment: str | None = None,
-    ) -> dict:
-        """Create or update feedback for (thread_id, run_id, user_id). rating must be +1 or -1."""
-        if rating not in (1, -1):
-            raise ValueError(f"rating must be +1 or -1, got {rating}")
-        resolved_user_id = resolve_user_id(user_id, method_name="FeedbackRepository.upsert")
-        async with self._sf() as session:
-            stmt = select(FeedbackRow).where(
-                FeedbackRow.thread_id == thread_id,
-                FeedbackRow.run_id == run_id,
-                FeedbackRow.user_id == resolved_user_id,
-            )
-            result = await session.execute(stmt)
-            row = result.scalar_one_or_none()
-            if row is not None:
-                row.rating = rating
-                row.comment = comment
-                row.created_at = datetime.now(UTC)
-            else:
-                row = FeedbackRow(
-                    feedback_id=str(uuid.uuid4()),
-                    run_id=run_id,
-                    thread_id=thread_id,
-                    user_id=resolved_user_id,
-                    rating=rating,
-                    comment=comment,
-                    created_at=datetime.now(UTC),
-                )
-                session.add(row)
-            await session.commit()
-            await session.refresh(row)
-            return self._row_to_dict(row)
-
-    async def delete_by_run(
-        self,
-        *,
-        thread_id: str,
-        run_id: str,
-        user_id: str | None | _AutoSentinel = AUTO,
-    ) -> bool:
-        """Delete the current user's feedback for a run. Returns True if a record was deleted."""
-        resolved_user_id = resolve_user_id(user_id, method_name="FeedbackRepository.delete_by_run")
-        async with self._sf() as session:
-            stmt = select(FeedbackRow).where(
-                FeedbackRow.thread_id == thread_id,
-                FeedbackRow.run_id == run_id,
-                FeedbackRow.user_id == resolved_user_id,
-            )
-            result = await session.execute(stmt)
-            row = result.scalar_one_or_none()
-            if row is None:
-                return False
-            await session.delete(row)
-            await session.commit()
-            return True
-
-    async def list_by_thread_grouped(
-        self,
-        thread_id: str,
-        *,
-        user_id: str | None | _AutoSentinel = AUTO,
-    ) -> dict[str, dict]:
-        """Return feedback grouped by run_id for a thread: {run_id: feedback_dict}."""
-        resolved_user_id = resolve_user_id(user_id, method_name="FeedbackRepository.list_by_thread_grouped")
-        stmt = select(FeedbackRow).where(FeedbackRow.thread_id == thread_id)
-        if resolved_user_id is not None:
-            stmt = stmt.where(FeedbackRow.user_id == resolved_user_id)
-        async with self._sf() as session:
-            result = await session.execute(stmt)
-            return {row.run_id: self._row_to_dict(row) for row in result.scalars()}
-
     async def aggregate_by_run(self, thread_id: str, run_id: str) -> dict:
         """Aggregate feedback stats for a run using database-side counting."""
         stmt = select(

backend/packages/harness/deerflow/persistence/migrations/alembic.ini

@@ -2,7 +2,7 @@
 script_location = %(here)s
 # Default URL for offline mode / autogenerate.
 # Runtime uses engine from DeerFlow config.
-sqlalchemy.url = sqlite+aiosqlite:///./data/deerflow.db
+sqlalchemy.url = sqlite+aiosqlite:///./data/app.db
 
 [loggers]
 keys = root,sqlalchemy,alembic

backend/packages/harness/deerflow/persistence/models/run_event.py

@@ -19,7 +19,7 @@ class RunEventRow(Base):
     # Owner of the conversation this event belongs to. Nullable for data
     # created before auth was introduced; populated by auth middleware on
     # new writes and by the boot-time orphan migration on existing rows.
-    user_id: Mapped[str | None] = mapped_column(String(64), nullable=True, index=True)
+    owner_id: Mapped[str | None] = mapped_column(String(64), nullable=True, index=True)
     event_type: Mapped[str] = mapped_column(String(32), nullable=False)
     category: Mapped[str] = mapped_column(String(16), nullable=False)
     # "message" | "trace" | "lifecycle"

backend/packages/harness/deerflow/persistence/run/model.py

@@ -16,7 +16,7 @@ class RunRow(Base):
     run_id: Mapped[str] = mapped_column(String(64), primary_key=True)
     thread_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
     assistant_id: Mapped[str | None] = mapped_column(String(128))
-    user_id: Mapped[str | None] = mapped_column(String(64), index=True)
+    owner_id: Mapped[str | None] = mapped_column(String(64), index=True)
     status: Mapped[str] = mapped_column(String(20), default="pending")
     # "pending" | "running" | "success" | "error" | "timeout" | "interrupted"
 

backend/packages/harness/deerflow/persistence/run/sql.py

@@ -16,7 +16,7 @@ from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
 
 from deerflow.persistence.run.model import RunRow
 from deerflow.runtime.runs.store.base import RunStore
-from deerflow.runtime.user_context import AUTO, _AutoSentinel, resolve_user_id
+from deerflow.runtime.user_context import AUTO, _AutoSentinel, resolve_owner_id
 
 
 class RunRepository(RunStore):
@@ -69,7 +69,7 @@ class RunRepository(RunStore):
         *,
         thread_id,
         assistant_id=None,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
         status="pending",
         multitask_strategy="reject",
         metadata=None,
@@ -78,13 +78,13 @@ class RunRepository(RunStore):
         created_at=None,
         follow_up_to_run_id=None,
     ):
-        resolved_user_id = resolve_user_id(user_id, method_name="RunRepository.put")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="RunRepository.put")
         now = datetime.now(UTC)
         row = RunRow(
             run_id=run_id,
             thread_id=thread_id,
             assistant_id=assistant_id,
-            user_id=resolved_user_id,
+            owner_id=resolved_owner_id,
             status=status,
             multitask_strategy=multitask_strategy,
             metadata_json=self._safe_json(metadata) or {},
@@ -102,14 +102,14 @@ class RunRepository(RunStore):
         self,
         run_id,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ):
-        resolved_user_id = resolve_user_id(user_id, method_name="RunRepository.get")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="RunRepository.get")
         async with self._sf() as session:
             row = await session.get(RunRow, run_id)
             if row is None:
                 return None
-            if resolved_user_id is not None and row.user_id != resolved_user_id:
+            if resolved_owner_id is not None and row.owner_id != resolved_owner_id:
                 return None
             return self._row_to_dict(row)
 
@@ -117,13 +117,13 @@ class RunRepository(RunStore):
         self,
         thread_id,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
         limit=100,
     ):
-        resolved_user_id = resolve_user_id(user_id, method_name="RunRepository.list_by_thread")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="RunRepository.list_by_thread")
         stmt = select(RunRow).where(RunRow.thread_id == thread_id)
-        if resolved_user_id is not None:
-            stmt = stmt.where(RunRow.user_id == resolved_user_id)
+        if resolved_owner_id is not None:
+            stmt = stmt.where(RunRow.owner_id == resolved_owner_id)
         stmt = stmt.order_by(RunRow.created_at.desc()).limit(limit)
         async with self._sf() as session:
             result = await session.execute(stmt)
@@ -141,14 +141,14 @@ class RunRepository(RunStore):
         self,
         run_id,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ):
-        resolved_user_id = resolve_user_id(user_id, method_name="RunRepository.delete")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="RunRepository.delete")
         async with self._sf() as session:
             row = await session.get(RunRow, run_id)
             if row is None:
                 return
-            if resolved_user_id is not None and row.user_id != resolved_user_id:
+            if resolved_owner_id is not None and row.owner_id != resolved_owner_id:
                 return
             await session.delete(row)
             await session.commit()

backend/packages/harness/deerflow/persistence/thread_meta/__init__.py

@@ -1,38 +1,13 @@
 """Thread metadata persistence — ORM, abstract store, and concrete implementations."""
 
-from __future__ import annotations
-
-from typing import TYPE_CHECKING
-
 from deerflow.persistence.thread_meta.base import ThreadMetaStore
 from deerflow.persistence.thread_meta.memory import MemoryThreadMetaStore
 from deerflow.persistence.thread_meta.model import ThreadMetaRow
 from deerflow.persistence.thread_meta.sql import ThreadMetaRepository
 
-if TYPE_CHECKING:
-    from langgraph.store.base import BaseStore
-    from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
-
 __all__ = [
     "MemoryThreadMetaStore",
     "ThreadMetaRepository",
     "ThreadMetaRow",
     "ThreadMetaStore",
-    "make_thread_store",
 ]
-
-
-def make_thread_store(
-    session_factory: async_sessionmaker[AsyncSession] | None,
-    store: BaseStore | None = None,
-) -> ThreadMetaStore:
-    """Create the appropriate ThreadMetaStore based on available backends.
-
-    Returns a SQL-backed repository when a session factory is available,
-    otherwise falls back to the in-memory LangGraph Store implementation.
-    """
-    if session_factory is not None:
-        return ThreadMetaRepository(session_factory)
-    if store is None:
-        raise ValueError("make_thread_store requires either a session_factory (SQL) or a store (memory)")
-    return MemoryThreadMetaStore(store)

backend/packages/harness/deerflow/persistence/thread_meta/base.py

@@ -3,21 +3,12 @@
 Implementations:
 - ThreadMetaRepository: SQL-backed (sqlite / postgres via SQLAlchemy)
 - MemoryThreadMetaStore: wraps LangGraph BaseStore (memory mode)
-
-All mutating and querying methods accept a ``user_id`` parameter with
-three-state semantics (see :mod:`deerflow.runtime.user_context`):
-
-- ``AUTO`` (default): resolve from the request-scoped contextvar.
-- Explicit ``str``: use the provided value verbatim.
-- Explicit ``None``: bypass owner filtering (migration/CLI only).
 """
 
 from __future__ import annotations
 
 import abc
 
-from deerflow.runtime.user_context import AUTO, _AutoSentinel
-
 
 class ThreadMetaStore(abc.ABC):
     @abc.abstractmethod
@@ -26,14 +17,14 @@ class ThreadMetaStore(abc.ABC):
         thread_id: str,
         *,
         assistant_id: str | None = None,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None = None,
         display_name: str | None = None,
         metadata: dict | None = None,
     ) -> dict:
         pass
 
     @abc.abstractmethod
-    async def get(self, thread_id: str, *, user_id: str | None | _AutoSentinel = AUTO) -> dict | None:
+    async def get(self, thread_id: str) -> dict | None:
         pass
 
     @abc.abstractmethod
@@ -44,33 +35,26 @@ class ThreadMetaStore(abc.ABC):
         status: str | None = None,
         limit: int = 100,
         offset: int = 0,
-        user_id: str | None | _AutoSentinel = AUTO,
     ) -> list[dict]:
         pass
 
     @abc.abstractmethod
-    async def update_display_name(self, thread_id: str, display_name: str, *, user_id: str | None | _AutoSentinel = AUTO) -> None:
+    async def update_display_name(self, thread_id: str, display_name: str) -> None:
         pass
 
     @abc.abstractmethod
-    async def update_status(self, thread_id: str, status: str, *, user_id: str | None | _AutoSentinel = AUTO) -> None:
+    async def update_status(self, thread_id: str, status: str) -> None:
         pass
 
     @abc.abstractmethod
-    async def update_metadata(self, thread_id: str, metadata: dict, *, user_id: str | None | _AutoSentinel = AUTO) -> None:
+    async def update_metadata(self, thread_id: str, metadata: dict) -> None:
         """Merge ``metadata`` into the thread's metadata field.
 
         Existing keys are overwritten by the new values; keys absent from
-        ``metadata`` are preserved. No-op if the thread does not exist
-        or the owner check fails.
+        ``metadata`` are preserved. No-op if the thread does not exist.
         """
         pass
 
     @abc.abstractmethod
-    async def check_access(self, thread_id: str, user_id: str, *, require_existing: bool = False) -> bool:
-        """Check if ``user_id`` has access to ``thread_id``."""
-        pass
-
-    @abc.abstractmethod
-    async def delete(self, thread_id: str, *, user_id: str | None | _AutoSentinel = AUTO) -> None:
+    async def delete(self, thread_id: str) -> None:
         pass

backend/packages/harness/deerflow/persistence/thread_meta/memory.py

@@ -13,7 +13,6 @@ from typing import Any
 from langgraph.store.base import BaseStore
 
 from deerflow.persistence.thread_meta.base import ThreadMetaStore
-from deerflow.runtime.user_context import AUTO, _AutoSentinel, resolve_user_id
 
 THREADS_NS: tuple[str, ...] = ("threads",)
 
@@ -22,37 +21,20 @@ class MemoryThreadMetaStore(ThreadMetaStore):
     def __init__(self, store: BaseStore) -> None:
         self._store = store
 
-    async def _get_owned_record(
-        self,
-        thread_id: str,
-        user_id: str | None | _AutoSentinel,
-        method_name: str,
-    ) -> dict | None:
-        """Fetch a record and verify ownership. Returns a mutable copy, or None."""
-        resolved = resolve_user_id(user_id, method_name=method_name)
-        item = await self._store.aget(THREADS_NS, thread_id)
-        if item is None:
-            return None
-        record = dict(item.value)
-        if resolved is not None and record.get("user_id") != resolved:
-            return None
-        return record
-
     async def create(
         self,
         thread_id: str,
         *,
         assistant_id: str | None = None,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None = None,
         display_name: str | None = None,
         metadata: dict | None = None,
     ) -> dict:
-        resolved_user_id = resolve_user_id(user_id, method_name="MemoryThreadMetaStore.create")
         now = time.time()
         record: dict[str, Any] = {
             "thread_id": thread_id,
             "assistant_id": assistant_id,
-            "user_id": resolved_user_id,
+            "owner_id": owner_id,
             "display_name": display_name,
             "status": "idle",
             "metadata": metadata or {},
@@ -63,8 +45,9 @@ class MemoryThreadMetaStore(ThreadMetaStore):
         await self._store.aput(THREADS_NS, thread_id, record)
         return record
 
-    async def get(self, thread_id: str, *, user_id: str | None | _AutoSentinel = AUTO) -> dict | None:
-        return await self._get_owned_record(thread_id, user_id, "MemoryThreadMetaStore.get")
+    async def get(self, thread_id: str) -> dict | None:
+        item = await self._store.aget(THREADS_NS, thread_id)
+        return item.value if item is not None else None
 
     async def search(
         self,
@@ -73,16 +56,12 @@ class MemoryThreadMetaStore(ThreadMetaStore):
         status: str | None = None,
         limit: int = 100,
         offset: int = 0,
-        user_id: str | None | _AutoSentinel = AUTO,
     ) -> list[dict]:
-        resolved_user_id = resolve_user_id(user_id, method_name="MemoryThreadMetaStore.search")
         filter_dict: dict[str, Any] = {}
         if metadata:
             filter_dict.update(metadata)
         if status:
             filter_dict["status"] = status
-        if resolved_user_id is not None:
-            filter_dict["user_id"] = resolved_user_id
 
         items = await self._store.asearch(
             THREADS_NS,
@@ -92,45 +71,37 @@ class MemoryThreadMetaStore(ThreadMetaStore):
         )
         return [self._item_to_dict(item) for item in items]
 
-    async def check_access(self, thread_id: str, user_id: str, *, require_existing: bool = False) -> bool:
+    async def update_display_name(self, thread_id: str, display_name: str) -> None:
         item = await self._store.aget(THREADS_NS, thread_id)
         if item is None:
-            return not require_existing
-        record_user_id = item.value.get("user_id")
-        if record_user_id is None:
-            return True
-        return record_user_id == user_id
-
-    async def update_display_name(self, thread_id: str, display_name: str, *, user_id: str | None | _AutoSentinel = AUTO) -> None:
-        record = await self._get_owned_record(thread_id, user_id, "MemoryThreadMetaStore.update_display_name")
-        if record is None:
             return
+        record = dict(item.value)
         record["display_name"] = display_name
         record["updated_at"] = time.time()
         await self._store.aput(THREADS_NS, thread_id, record)
 
-    async def update_status(self, thread_id: str, status: str, *, user_id: str | None | _AutoSentinel = AUTO) -> None:
-        record = await self._get_owned_record(thread_id, user_id, "MemoryThreadMetaStore.update_status")
-        if record is None:
+    async def update_status(self, thread_id: str, status: str) -> None:
+        item = await self._store.aget(THREADS_NS, thread_id)
+        if item is None:
             return
+        record = dict(item.value)
         record["status"] = status
         record["updated_at"] = time.time()
         await self._store.aput(THREADS_NS, thread_id, record)
 
-    async def update_metadata(self, thread_id: str, metadata: dict, *, user_id: str | None | _AutoSentinel = AUTO) -> None:
-        record = await self._get_owned_record(thread_id, user_id, "MemoryThreadMetaStore.update_metadata")
-        if record is None:
+    async def update_metadata(self, thread_id: str, metadata: dict) -> None:
+        """Merge ``metadata`` into the in-memory record. No-op if absent."""
+        item = await self._store.aget(THREADS_NS, thread_id)
+        if item is None:
             return
+        record = dict(item.value)
         merged = dict(record.get("metadata") or {})
         merged.update(metadata)
         record["metadata"] = merged
         record["updated_at"] = time.time()
         await self._store.aput(THREADS_NS, thread_id, record)
 
-    async def delete(self, thread_id: str, *, user_id: str | None | _AutoSentinel = AUTO) -> None:
-        record = await self._get_owned_record(thread_id, user_id, "MemoryThreadMetaStore.delete")
-        if record is None:
-            return
+    async def delete(self, thread_id: str) -> None:
         await self._store.adelete(THREADS_NS, thread_id)
 
     @staticmethod
@@ -140,7 +111,7 @@ class MemoryThreadMetaStore(ThreadMetaStore):
         return {
             "thread_id": item.key,
             "assistant_id": val.get("assistant_id"),
-            "user_id": val.get("user_id"),
+            "owner_id": val.get("owner_id"),
             "display_name": val.get("display_name"),
             "status": val.get("status", "idle"),
             "metadata": val.get("metadata", {}),

backend/packages/harness/deerflow/persistence/thread_meta/model.py

@@ -15,7 +15,7 @@ class ThreadMetaRow(Base):
 
     thread_id: Mapped[str] = mapped_column(String(64), primary_key=True)
     assistant_id: Mapped[str | None] = mapped_column(String(128), index=True)
-    user_id: Mapped[str | None] = mapped_column(String(64), index=True)
+    owner_id: Mapped[str | None] = mapped_column(String(64), index=True)
     display_name: Mapped[str | None] = mapped_column(String(256))
     status: Mapped[str] = mapped_column(String(20), default="idle")
     metadata_json: Mapped[dict] = mapped_column(JSON, default=dict)

backend/packages/harness/deerflow/persistence/thread_meta/sql.py

@@ -10,7 +10,7 @@ from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
 
 from deerflow.persistence.thread_meta.base import ThreadMetaStore
 from deerflow.persistence.thread_meta.model import ThreadMetaRow
-from deerflow.runtime.user_context import AUTO, _AutoSentinel, resolve_user_id
+from deerflow.runtime.user_context import AUTO, _AutoSentinel, resolve_owner_id
 
 
 class ThreadMetaRepository(ThreadMetaStore):
@@ -32,18 +32,18 @@ class ThreadMetaRepository(ThreadMetaStore):
         thread_id: str,
         *,
         assistant_id: str | None = None,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
         display_name: str | None = None,
         metadata: dict | None = None,
     ) -> dict:
-        # Auto-resolve user_id from contextvar when AUTO; explicit None
+        # Auto-resolve owner_id from contextvar when AUTO; explicit None
         # creates an orphan row (used by migration scripts).
-        resolved_user_id = resolve_user_id(user_id, method_name="ThreadMetaRepository.create")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="ThreadMetaRepository.create")
         now = datetime.now(UTC)
         row = ThreadMetaRow(
             thread_id=thread_id,
             assistant_id=assistant_id,
-            user_id=resolved_user_id,
+            owner_id=resolved_owner_id,
             display_name=display_name,
             metadata_json=metadata or {},
             created_at=now,
@@ -59,47 +59,37 @@ class ThreadMetaRepository(ThreadMetaStore):
         self,
         thread_id: str,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ) -> dict | None:
-        resolved_user_id = resolve_user_id(user_id, method_name="ThreadMetaRepository.get")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="ThreadMetaRepository.get")
         async with self._sf() as session:
             row = await session.get(ThreadMetaRow, thread_id)
             if row is None:
                 return None
-            # Enforce owner filter unless explicitly bypassed (user_id=None).
-            if resolved_user_id is not None and row.user_id != resolved_user_id:
+            # Enforce owner filter unless explicitly bypassed (owner_id=None).
+            if resolved_owner_id is not None and row.owner_id != resolved_owner_id:
                 return None
             return self._row_to_dict(row)
 
-    async def check_access(self, thread_id: str, user_id: str, *, require_existing: bool = False) -> bool:
-        """Check if ``user_id`` has access to ``thread_id``.
+    async def list_by_owner(self, owner_id: str, *, limit: int = 100, offset: int = 0) -> list[dict]:
+        stmt = select(ThreadMetaRow).where(ThreadMetaRow.owner_id == owner_id).order_by(ThreadMetaRow.updated_at.desc()).limit(limit).offset(offset)
+        async with self._sf() as session:
+            result = await session.execute(stmt)
+            return [self._row_to_dict(r) for r in result.scalars()]
 
-        Two modes — one row, two distinct semantics depending on what
-        the caller is about to do:
+    async def check_access(self, thread_id: str, owner_id: str) -> bool:
+        """Check if owner_id has access to thread_id.
 
-        - ``require_existing=False`` (default, permissive):
-          Returns True for: row missing (untracked legacy thread),
-          ``row.user_id`` is None (shared / pre-auth data),
-          or ``row.user_id == user_id``. Use for **read-style**
-          decorators where treating an untracked thread as accessible
-          preserves backward-compat.
-
-        - ``require_existing=True`` (strict):
-          Returns True **only** when the row exists AND
-          (``row.user_id == user_id`` OR ``row.user_id is None``).
-          Use for **destructive / mutating** decorators (DELETE, PATCH,
-          state-update) so a thread that has *already been deleted*
-          cannot be re-targeted by any caller — closing the
-          delete-idempotence cross-user gap where the row vanishing
-          made every other user appear to "own" it.
+        Returns True if: row doesn't exist (untracked thread), owner_id
+        is None on the row (shared thread), or owner_id matches.
         """
         async with self._sf() as session:
             row = await session.get(ThreadMetaRow, thread_id)
             if row is None:
-                return not require_existing
-            if row.user_id is None:
                 return True
-            return row.user_id == user_id
+            if row.owner_id is None:
+                return True
+            return row.owner_id == owner_id
 
     async def search(
         self,
@@ -108,17 +98,17 @@ class ThreadMetaRepository(ThreadMetaStore):
         status: str | None = None,
         limit: int = 100,
         offset: int = 0,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ) -> list[dict]:
         """Search threads with optional metadata and status filters.
 
         Owner filter is enforced by default: caller must be in a user
-        context. Pass ``user_id=None`` to bypass (migration/CLI).
+        context. Pass ``owner_id=None`` to bypass (migration/CLI).
         """
-        resolved_user_id = resolve_user_id(user_id, method_name="ThreadMetaRepository.search")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="ThreadMetaRepository.search")
         stmt = select(ThreadMetaRow).order_by(ThreadMetaRow.updated_at.desc())
-        if resolved_user_id is not None:
-            stmt = stmt.where(ThreadMetaRow.user_id == resolved_user_id)
+        if resolved_owner_id is not None:
+            stmt = stmt.where(ThreadMetaRow.owner_id == resolved_owner_id)
         if status:
             stmt = stmt.where(ThreadMetaRow.status == status)
 
@@ -138,24 +128,24 @@ class ThreadMetaRepository(ThreadMetaStore):
                 result = await session.execute(stmt)
                 return [self._row_to_dict(r) for r in result.scalars()]
 
-    async def _check_ownership(self, session: AsyncSession, thread_id: str, resolved_user_id: str | None) -> bool:
+    async def _check_ownership(self, session: AsyncSession, thread_id: str, resolved_owner_id: str | None) -> bool:
         """Return True if the row exists and is owned (or filter bypassed)."""
-        if resolved_user_id is None:
+        if resolved_owner_id is None:
             return True  # explicit bypass
         row = await session.get(ThreadMetaRow, thread_id)
-        return row is not None and row.user_id == resolved_user_id
+        return row is not None and row.owner_id == resolved_owner_id
 
     async def update_display_name(
         self,
         thread_id: str,
         display_name: str,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ) -> None:
         """Update the display_name (title) for a thread."""
-        resolved_user_id = resolve_user_id(user_id, method_name="ThreadMetaRepository.update_display_name")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="ThreadMetaRepository.update_display_name")
         async with self._sf() as session:
-            if not await self._check_ownership(session, thread_id, resolved_user_id):
+            if not await self._check_ownership(session, thread_id, resolved_owner_id):
                 return
             await session.execute(update(ThreadMetaRow).where(ThreadMetaRow.thread_id == thread_id).values(display_name=display_name, updated_at=datetime.now(UTC)))
             await session.commit()
@@ -165,11 +155,11 @@ class ThreadMetaRepository(ThreadMetaStore):
         thread_id: str,
         status: str,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ) -> None:
-        resolved_user_id = resolve_user_id(user_id, method_name="ThreadMetaRepository.update_status")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="ThreadMetaRepository.update_status")
         async with self._sf() as session:
-            if not await self._check_ownership(session, thread_id, resolved_user_id):
+            if not await self._check_ownership(session, thread_id, resolved_owner_id):
                 return
             await session.execute(update(ThreadMetaRow).where(ThreadMetaRow.thread_id == thread_id).values(status=status, updated_at=datetime.now(UTC)))
             await session.commit()
@@ -179,20 +169,20 @@ class ThreadMetaRepository(ThreadMetaStore):
         thread_id: str,
         metadata: dict,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ) -> None:
         """Merge ``metadata`` into ``metadata_json``.
 
         Read-modify-write inside a single session/transaction so concurrent
         callers see consistent state. No-op if the row does not exist or
-        the user_id check fails.
+        the owner_id check fails.
         """
-        resolved_user_id = resolve_user_id(user_id, method_name="ThreadMetaRepository.update_metadata")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="ThreadMetaRepository.update_metadata")
         async with self._sf() as session:
             row = await session.get(ThreadMetaRow, thread_id)
             if row is None:
                 return
-            if resolved_user_id is not None and row.user_id != resolved_user_id:
+            if resolved_owner_id is not None and row.owner_id != resolved_owner_id:
                 return
             merged = dict(row.metadata_json or {})
             merged.update(metadata)
@@ -204,14 +194,14 @@ class ThreadMetaRepository(ThreadMetaStore):
         self,
         thread_id: str,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: str | None | _AutoSentinel = AUTO,
     ) -> None:
-        resolved_user_id = resolve_user_id(user_id, method_name="ThreadMetaRepository.delete")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="ThreadMetaRepository.delete")
         async with self._sf() as session:
             row = await session.get(ThreadMetaRow, thread_id)
             if row is None:
                 return
-            if resolved_user_id is not None and row.user_id != resolved_user_id:
+            if resolved_owner_id is not None and row.owner_id != resolved_owner_id:
                 return
             await session.delete(row)
             await session.commit()

backend/packages/harness/deerflow/runtime/__init__.py

@@ -5,18 +5,12 @@ Re-exports the public API of :mod:`~deerflow.runtime.runs` and
 directly from ``deerflow.runtime``.
 """
 
-from .checkpointer import checkpointer_context, get_checkpointer, make_checkpointer, reset_checkpointer
 from .runs import ConflictError, DisconnectMode, RunContext, RunManager, RunRecord, RunStatus, UnsupportedStrategyError, run_agent
 from .serialization import serialize, serialize_channel_values, serialize_lc_object, serialize_messages_tuple
 from .store import get_store, make_store, reset_store, store_context
 from .stream_bridge import END_SENTINEL, HEARTBEAT_SENTINEL, MemoryStreamBridge, StreamBridge, StreamEvent, make_stream_bridge
 
 __all__ = [
-    # checkpointer
-    "checkpointer_context",
-    "get_checkpointer",
-    "make_checkpointer",
-    "reset_checkpointer",
     # runs
     "ConflictError",
     "DisconnectMode",

backend/packages/harness/deerflow/runtime/events/store/base.py

@@ -83,18 +83,8 @@ class RunEventStore(abc.ABC):
         self,
         thread_id: str,
         run_id: str,
-        *,
-        limit: int = 50,
-        before_seq: int | None = None,
-        after_seq: int | None = None,
     ) -> list[dict]:
-        """Return displayable messages (category=message) for a specific run, ordered by seq ascending.
-
-        Supports bidirectional cursor pagination:
-        - after_seq: return the first ``limit`` records with seq > after_seq (ascending)
-        - before_seq: return the last ``limit`` records with seq < before_seq (ascending)
-        - neither: return the latest ``limit`` records (ascending)
-        """
+        """Return displayable messages (category=message) for a specific run, ordered by seq ascending."""
 
     @abc.abstractmethod
     async def count_messages(self, thread_id: str) -> int:

backend/packages/harness/deerflow/runtime/events/store/db.py

@@ -15,7 +15,7 @@ from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
 
 from deerflow.persistence.models.run_event import RunEventRow
 from deerflow.runtime.events.store.base import RunEventStore
-from deerflow.runtime.user_context import AUTO, _AutoSentinel, get_current_user, resolve_user_id
+from deerflow.runtime.user_context import AUTO, _AutoSentinel, get_current_user, resolve_owner_id
 
 logger = logging.getLogger(__name__)
 
@@ -55,22 +55,16 @@ class DbRunEventStore(RunEventStore):
         return content, metadata or {}
 
     @staticmethod
-    def _user_id_from_context() -> str | None:
-        """Soft read of user_id from contextvar for write paths.
+    def _owner_from_context() -> str | None:
+        """Soft read of owner_id from contextvar for write paths.
 
         Returns ``None`` (no filter / no stamp) if contextvar is unset,
         which is the expected case for background worker writes. HTTP
         request writes will have the contextvar set by auth middleware
         and get their user_id stamped automatically.
-
-        Coerces ``user.id`` to ``str`` at the boundary: ``User.id`` is
-        typed as ``UUID`` by the auth layer, but ``run_events.user_id``
-        is ``VARCHAR(64)`` and aiosqlite cannot bind a raw UUID object
-        to a VARCHAR column ("type 'UUID' is not supported") — the
-        INSERT would silently roll back and the worker would hang.
         """
         user = get_current_user()
-        return str(user.id) if user is not None else None
+        return user.id if user is not None else None
 
     async def put(self, *, thread_id, run_id, event_type, category, content="", metadata=None, created_at=None):  # noqa: D401
         """Write a single event — low-frequency path only.
@@ -87,7 +81,7 @@ class DbRunEventStore(RunEventStore):
             metadata = {**(metadata or {}), "content_is_dict": True}
         else:
             db_content = content
-        user_id = self._user_id_from_context()
+        owner_id = self._owner_from_context()
         async with self._sf() as session:
             async with session.begin():
                 # Use FOR UPDATE to serialize seq assignment within a thread.
@@ -98,7 +92,7 @@ class DbRunEventStore(RunEventStore):
                 row = RunEventRow(
                     thread_id=thread_id,
                     run_id=run_id,
-                    user_id=user_id,
+                    owner_id=owner_id,
                     event_type=event_type,
                     category=category,
                     content=db_content,
@@ -112,7 +106,7 @@ class DbRunEventStore(RunEventStore):
     async def put_batch(self, events):
         if not events:
             return []
-        user_id = self._user_id_from_context()
+        owner_id = self._owner_from_context()
         async with self._sf() as session:
             async with session.begin():
                 # Get max seq for the thread (assume all events in batch belong to same thread).
@@ -136,7 +130,7 @@ class DbRunEventStore(RunEventStore):
                     row = RunEventRow(
                         thread_id=e["thread_id"],
                         run_id=e["run_id"],
-                        user_id=e.get("user_id", user_id),
+                        owner_id=e.get("owner_id", owner_id),
                         event_type=e["event_type"],
                         category=category,
                         content=db_content,
@@ -155,12 +149,12 @@ class DbRunEventStore(RunEventStore):
         limit=50,
         before_seq=None,
         after_seq=None,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: "str | None | _AutoSentinel" = AUTO,
     ):
-        resolved_user_id = resolve_user_id(user_id, method_name="DbRunEventStore.list_messages")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="DbRunEventStore.list_messages")
         stmt = select(RunEventRow).where(RunEventRow.thread_id == thread_id, RunEventRow.category == "message")
-        if resolved_user_id is not None:
-            stmt = stmt.where(RunEventRow.user_id == resolved_user_id)
+        if resolved_owner_id is not None:
+            stmt = stmt.where(RunEventRow.owner_id == resolved_owner_id)
         if before_seq is not None:
             stmt = stmt.where(RunEventRow.seq < before_seq)
         if after_seq is not None:
@@ -187,12 +181,12 @@ class DbRunEventStore(RunEventStore):
         *,
         event_types=None,
         limit=500,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: "str | None | _AutoSentinel" = AUTO,
     ):
-        resolved_user_id = resolve_user_id(user_id, method_name="DbRunEventStore.list_events")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="DbRunEventStore.list_events")
         stmt = select(RunEventRow).where(RunEventRow.thread_id == thread_id, RunEventRow.run_id == run_id)
-        if resolved_user_id is not None:
-            stmt = stmt.where(RunEventRow.user_id == resolved_user_id)
+        if resolved_owner_id is not None:
+            stmt = stmt.where(RunEventRow.owner_id == resolved_owner_id)
         if event_types:
             stmt = stmt.where(RunEventRow.event_type.in_(event_types))
         stmt = stmt.order_by(RunEventRow.seq.asc()).limit(limit)
@@ -205,46 +199,27 @@ class DbRunEventStore(RunEventStore):
         thread_id,
         run_id,
         *,
-        limit=50,
-        before_seq=None,
-        after_seq=None,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: "str | None | _AutoSentinel" = AUTO,
     ):
-        resolved_user_id = resolve_user_id(user_id, method_name="DbRunEventStore.list_messages_by_run")
-        stmt = select(RunEventRow).where(
-            RunEventRow.thread_id == thread_id,
-            RunEventRow.run_id == run_id,
-            RunEventRow.category == "message",
-        )
-        if resolved_user_id is not None:
-            stmt = stmt.where(RunEventRow.user_id == resolved_user_id)
-        if before_seq is not None:
-            stmt = stmt.where(RunEventRow.seq < before_seq)
-        if after_seq is not None:
-            stmt = stmt.where(RunEventRow.seq > after_seq)
-
-        if after_seq is not None:
-            stmt = stmt.order_by(RunEventRow.seq.asc()).limit(limit)
-            async with self._sf() as session:
-                result = await session.execute(stmt)
-                return [self._row_to_dict(r) for r in result.scalars()]
-        else:
-            stmt = stmt.order_by(RunEventRow.seq.desc()).limit(limit)
-            async with self._sf() as session:
-                result = await session.execute(stmt)
-                rows = list(result.scalars())
-                return [self._row_to_dict(r) for r in reversed(rows)]
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="DbRunEventStore.list_messages_by_run")
+        stmt = select(RunEventRow).where(RunEventRow.thread_id == thread_id, RunEventRow.run_id == run_id, RunEventRow.category == "message")
+        if resolved_owner_id is not None:
+            stmt = stmt.where(RunEventRow.owner_id == resolved_owner_id)
+        stmt = stmt.order_by(RunEventRow.seq.asc())
+        async with self._sf() as session:
+            result = await session.execute(stmt)
+            return [self._row_to_dict(r) for r in result.scalars()]
 
     async def count_messages(
         self,
         thread_id,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: "str | None | _AutoSentinel" = AUTO,
     ):
-        resolved_user_id = resolve_user_id(user_id, method_name="DbRunEventStore.count_messages")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="DbRunEventStore.count_messages")
         stmt = select(func.count()).select_from(RunEventRow).where(RunEventRow.thread_id == thread_id, RunEventRow.category == "message")
-        if resolved_user_id is not None:
-            stmt = stmt.where(RunEventRow.user_id == resolved_user_id)
+        if resolved_owner_id is not None:
+            stmt = stmt.where(RunEventRow.owner_id == resolved_owner_id)
         async with self._sf() as session:
             return await session.scalar(stmt) or 0
 
@@ -252,13 +227,13 @@ class DbRunEventStore(RunEventStore):
         self,
         thread_id,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: "str | None | _AutoSentinel" = AUTO,
     ):
-        resolved_user_id = resolve_user_id(user_id, method_name="DbRunEventStore.delete_by_thread")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="DbRunEventStore.delete_by_thread")
         async with self._sf() as session:
             count_conditions = [RunEventRow.thread_id == thread_id]
-            if resolved_user_id is not None:
-                count_conditions.append(RunEventRow.user_id == resolved_user_id)
+            if resolved_owner_id is not None:
+                count_conditions.append(RunEventRow.owner_id == resolved_owner_id)
             count_stmt = select(func.count()).select_from(RunEventRow).where(*count_conditions)
             count = await session.scalar(count_stmt) or 0
             if count > 0:
@@ -271,13 +246,13 @@ class DbRunEventStore(RunEventStore):
         thread_id,
         run_id,
         *,
-        user_id: str | None | _AutoSentinel = AUTO,
+        owner_id: "str | None | _AutoSentinel" = AUTO,
     ):
-        resolved_user_id = resolve_user_id(user_id, method_name="DbRunEventStore.delete_by_run")
+        resolved_owner_id = resolve_owner_id(owner_id, method_name="DbRunEventStore.delete_by_run")
         async with self._sf() as session:
             count_conditions = [RunEventRow.thread_id == thread_id, RunEventRow.run_id == run_id]
-            if resolved_user_id is not None:
-                count_conditions.append(RunEventRow.user_id == resolved_user_id)
+            if resolved_owner_id is not None:
+                count_conditions.append(RunEventRow.owner_id == resolved_owner_id)
             count_stmt = select(func.count()).select_from(RunEventRow).where(*count_conditions)
             count = await session.scalar(count_stmt) or 0
             if count > 0:

backend/packages/harness/deerflow/runtime/events/store/jsonl.py

@@ -152,17 +152,9 @@ class JsonlRunEventStore(RunEventStore):
             events = [e for e in events if e.get("event_type") in event_types]
         return events[:limit]
 
-    async def list_messages_by_run(self, thread_id, run_id, *, limit=50, before_seq=None, after_seq=None):
+    async def list_messages_by_run(self, thread_id, run_id):
         events = self._read_run_events(thread_id, run_id)
-        filtered = [e for e in events if e.get("category") == "message"]
-        if before_seq is not None:
-            filtered = [e for e in filtered if e.get("seq", 0) < before_seq]
-        if after_seq is not None:
-            filtered = [e for e in filtered if e.get("seq", 0) > after_seq]
-        if after_seq is not None:
-            return filtered[:limit]
-        else:
-            return filtered[-limit:] if len(filtered) > limit else filtered
+        return [e for e in events if e.get("category") == "message"]
 
     async def count_messages(self, thread_id):
         all_events = self._read_thread_events(thread_id)

backend/packages/harness/deerflow/runtime/events/store/memory.py

@@ -97,17 +97,9 @@ class MemoryRunEventStore(RunEventStore):
             filtered = [e for e in filtered if e["event_type"] in event_types]
         return filtered[:limit]
 
-    async def list_messages_by_run(self, thread_id, run_id, *, limit=50, before_seq=None, after_seq=None):
+    async def list_messages_by_run(self, thread_id, run_id):
         all_events = self._events.get(thread_id, [])
-        filtered = [e for e in all_events if e["run_id"] == run_id and e["category"] == "message"]
-        if before_seq is not None:
-            filtered = [e for e in filtered if e["seq"] < before_seq]
-        if after_seq is not None:
-            filtered = [e for e in filtered if e["seq"] > after_seq]
-        if after_seq is not None:
-            return filtered[:limit]
-        else:
-            return filtered[-limit:] if len(filtered) > limit else filtered
+        return [e for e in all_events if e["run_id"] == run_id and e["category"] == "message"]
 
     async def count_messages(self, thread_id):
         all_events = self._events.get(thread_id, [])

backend/packages/harness/deerflow/runtime/journal.py

@@ -6,10 +6,7 @@ handles token usage accumulation.
 
 Key design decisions:
 - on_llm_new_token is NOT implemented -- only complete messages via on_llm_end
-- on_chat_model_start captures structured prompts as llm_request (OpenAI format) and
-  extracts the first human message for run.input, because it is more reliable than
-  on_chain_start (fires on every node) — messages here are fully structured.
-- on_chain_start with parent_run_id=None emits a run.start trace marking root invocation.
+- on_chat_model_start captures structured prompts as llm_request (OpenAI format)
 - on_llm_end emits llm_response in OpenAI Chat Completions format
 - Token usage accumulated in memory, written to RunRow on run completion
 - Caller identification via tags injection (lead_agent / subagent:{name} / middleware:{name})
@@ -21,12 +18,10 @@ import asyncio
 import logging
 import time
 from datetime import UTC, datetime
-from typing import TYPE_CHECKING, Any, cast
+from typing import TYPE_CHECKING, Any
 from uuid import UUID
 
 from langchain_core.callbacks import BaseCallbackHandler
-from langchain_core.messages import AnyMessage, BaseMessage, HumanMessage, ToolMessage
-from langgraph.types import Command
 
 if TYPE_CHECKING:
     from deerflow.runtime.events.store.base import RunEventStore
@@ -55,7 +50,6 @@ class RunJournal(BaseCallbackHandler):
 
         # Write buffer
         self._buffer: list[dict] = []
-        self._pending_flush_tasks: set[asyncio.Task[None]] = set()
 
         # Token accumulators
         self._total_input_tokens = 0
@@ -77,39 +71,34 @@ class RunJournal(BaseCallbackHandler):
         # LLM request/response tracking
         self._llm_call_index = 0
         self._cached_prompts: dict[str, list[dict]] = {}  # langchain run_id -> OpenAI messages
+        self._cached_models: dict[str, str] = {}  # langchain run_id -> model name
+
+        # Tool call ID cache
+        self._tool_call_ids: dict[str, str] = {}  # langchain run_id -> tool_call_id
 
     # -- Lifecycle callbacks --
 
-    def on_chain_start(
-        self,
-        serialized: dict[str, Any],
-        inputs: dict[str, Any],
-        *,
-        run_id: UUID,
-        parent_run_id: UUID | None = None,
-        tags: list[str] | None = None,
-        metadata: dict[str, Any] | None = None,
-        **kwargs: Any,
-    ) -> None:
-        caller = self._identify_caller(tags)
-        if parent_run_id is None:
-            # Root graph invocation — emit a single trace event for the run start.
-            chain_name = (serialized or {}).get("name", "unknown")
-            self._put(
-                event_type="run.start",
-                category="trace",
-                content={"chain": chain_name},
-                metadata={"caller": caller, **(metadata or {})},
-            )
+    def on_chain_start(self, serialized: dict, inputs: Any, *, run_id: UUID, **kwargs: Any) -> None:
+        if kwargs.get("parent_run_id") is not None:
+            return
+        self._put(
+            event_type="run_start",
+            category="lifecycle",
+            metadata={"input_preview": str(inputs)[:500]},
+        )
 
     def on_chain_end(self, outputs: Any, *, run_id: UUID, **kwargs: Any) -> None:
-        self._put(event_type="run.end", category="outputs", content=outputs, metadata={"status": "success"})
+        if kwargs.get("parent_run_id") is not None:
+            return
+        self._put(event_type="run_end", category="lifecycle", metadata={"status": "success"})
         self._flush_sync()
 
     def on_chain_error(self, error: BaseException, *, run_id: UUID, **kwargs: Any) -> None:
+        if kwargs.get("parent_run_id") is not None:
+            return
         self._put(
-            event_type="run.error",
-            category="error",
+            event_type="run_error",
+            category="lifecycle",
             content=str(error),
             metadata={"error_type": type(error).__name__},
         )
@@ -117,132 +106,253 @@ class RunJournal(BaseCallbackHandler):
 
     # -- LLM callbacks --
 
-    def on_chat_model_start(
-        self,
-        serialized: dict,
-        messages: list[list[BaseMessage]],
-        *,
-        run_id: UUID,
-        tags: list[str] | None = None,
-        **kwargs: Any,
-    ) -> None:
-        """Capture structured prompt messages for llm_request event.
+    def on_chat_model_start(self, serialized: dict, messages: list[list], *, run_id: UUID, **kwargs: Any) -> None:
+        """Capture structured prompt messages for llm_request event."""
+        from deerflow.runtime.converters import langchain_messages_to_openai
 
-        This is also the canonical place to extract the first human message:
-        messages are fully structured here, it fires only on real LLM calls,
-        and the content is never compressed by checkpoint trimming.
-        """
         rid = str(run_id)
         self._llm_start_times[rid] = time.monotonic()
         self._llm_call_index += 1
-        # Mark this run_id as seen so on_llm_end knows not to increment again.
-        self._cached_prompts[rid] = []
 
-        logger.info(f"on_chat_model_start {run_id}: tags={tags} serialized={serialized} messages={messages}")
+        model_name = serialized.get("name", "")
+        self._cached_models[rid] = model_name
 
-        # Capture the first human message sent to any LLM in this run.
-        if not self._first_human_msg:
-            for batch in messages.reversed():
-                for m in batch.reversed():
-                    if isinstance(m, HumanMessage) and m.name != "summary":
-                        caller = self._identify_caller(tags)
-                        self.set_first_human_message(m.text)
-                        self._put(
-                            event_type="llm.human.input",
-                            category="message",
-                            content=m.model_dump(),
-                            metadata={"caller": caller},
-                        )
-                        break
-                if self._first_human_msg:
-                    break
+        # Convert the first message list (LangChain passes list-of-lists)
+        prompt_msgs = messages[0] if messages else []
+        openai_msgs = langchain_messages_to_openai(prompt_msgs)
+        self._cached_prompts[rid] = openai_msgs
 
-    def on_llm_start(self, serialized: dict, prompts: list[str], *, run_id: UUID, parent_run_id: UUID | None = None, tags: list[str] | None = None, metadata: dict[str, Any] | None = None, **kwargs: Any) -> None:
+        caller = self._identify_caller(kwargs)
+        self._put(
+            event_type="llm_request",
+            category="trace",
+            content={"model": model_name, "messages": openai_msgs},
+            metadata={"caller": caller, "llm_call_index": self._llm_call_index},
+        )
+
+    def on_llm_start(self, serialized: dict, prompts: list[str], *, run_id: UUID, **kwargs: Any) -> None:
         # Fallback: on_chat_model_start is preferred. This just tracks latency.
         self._llm_start_times[str(run_id)] = time.monotonic()
 
-    def on_llm_end(self, response, *, run_id, parent_run_id, tags, **kwargs) -> None:
-        messages: list[AnyMessage] = []
-        logger.info(f"on_llm_end {run_id}: response: {tags} {kwargs}")
-        for generation in response.generations:
-            for gen in generation:
-                if hasattr(gen, "message"):
-                    messages.append(gen.message)
-                else:
-                    logger.warning(f"on_llm_end {run_id}: generation has no message attribute: {gen}")
+    def on_llm_end(self, response: Any, *, run_id: UUID, **kwargs: Any) -> None:
+        from deerflow.runtime.converters import langchain_to_openai_completion
 
-        for message in messages:
-            caller = self._identify_caller(tags)
+        try:
+            message = response.generations[0][0].message
+        except (IndexError, AttributeError):
+            logger.debug("on_llm_end: could not extract message from response")
+            return
 
-            # Latency
-            rid = str(run_id)
-            start = self._llm_start_times.pop(rid, None)
-            latency_ms = int((time.monotonic() - start) * 1000) if start else None
+        caller = self._identify_caller(kwargs)
 
-            # Token usage from message
-            usage = getattr(message, "usage_metadata", None)
-            usage_dict = dict(usage) if usage else {}
+        # Latency
+        rid = str(run_id)
+        start = self._llm_start_times.pop(rid, None)
+        latency_ms = int((time.monotonic() - start) * 1000) if start else None
 
-            # Resolve call index
+        # Token usage from message
+        usage = getattr(message, "usage_metadata", None)
+        usage_dict = dict(usage) if usage else {}
+
+        # Resolve call index
+        call_index = self._llm_call_index
+        if rid not in self._cached_prompts:
+            # Fallback: on_chat_model_start was not called
+            self._llm_call_index += 1
             call_index = self._llm_call_index
-            if rid not in self._cached_prompts:
-                # Fallback: on_chat_model_start was not called
-                self._llm_call_index += 1
-                call_index = self._llm_call_index
 
-            # Trace event: llm_response (OpenAI completion format)
-            self._put(
-                event_type="llm.ai.response",
-                category="message",
-                content=message.model_dump(),
-                metadata={
-                    "caller": caller,
-                    "usage": usage_dict,
-                    "latency_ms": latency_ms,
-                    "llm_call_index": call_index,
-                },
-            )
+        # Clean up caches
+        self._cached_prompts.pop(rid, None)
+        self._cached_models.pop(rid, None)
 
-            # Token accumulation
-            if self._track_tokens:
-                input_tk = usage_dict.get("input_tokens", 0) or 0
-                output_tk = usage_dict.get("output_tokens", 0) or 0
-                total_tk = usage_dict.get("total_tokens", 0) or 0
-                if total_tk == 0:
-                    total_tk = input_tk + output_tk
-                if total_tk > 0:
-                    self._total_input_tokens += input_tk
-                    self._total_output_tokens += output_tk
-                    self._total_tokens += total_tk
-                    self._llm_call_count += 1
+        # Trace event: llm_response (OpenAI completion format)
+        content = getattr(message, "content", "")
+        self._put(
+            event_type="llm_response",
+            category="trace",
+            content=langchain_to_openai_completion(message),
+            metadata={
+                "caller": caller,
+                "usage": usage_dict,
+                "latency_ms": latency_ms,
+                "llm_call_index": call_index,
+            },
+        )
+
+        # Message events: only lead_agent gets message-category events.
+        # Content uses message.model_dump() to align with checkpoint format.
+        tool_calls = getattr(message, "tool_calls", None) or []
+        if caller == "lead_agent":
+            resp_meta = getattr(message, "response_metadata", None) or {}
+            model_name = resp_meta.get("model_name") if isinstance(resp_meta, dict) else None
+            if tool_calls:
+                # ai_tool_call: agent decided to use tools
+                self._put(
+                    event_type="ai_tool_call",
+                    category="message",
+                    content=message.model_dump(),
+                    metadata={"model_name": model_name, "finish_reason": "tool_calls"},
+                )
+            elif isinstance(content, str) and content:
+                # ai_message: final text reply
+                self._put(
+                    event_type="ai_message",
+                    category="message",
+                    content=message.model_dump(),
+                    metadata={"model_name": model_name, "finish_reason": "stop"},
+                )
+                self._last_ai_msg = content
+                self._msg_count += 1
+
+        # Token accumulation
+        if self._track_tokens:
+            input_tk = usage_dict.get("input_tokens", 0) or 0
+            output_tk = usage_dict.get("output_tokens", 0) or 0
+            total_tk = usage_dict.get("total_tokens", 0) or 0
+            if total_tk == 0:
+                total_tk = input_tk + output_tk
+            if total_tk > 0:
+                self._total_input_tokens += input_tk
+                self._total_output_tokens += output_tk
+                self._total_tokens += total_tk
+                self._llm_call_count += 1
+                if caller.startswith("subagent:"):
+                    self._subagent_tokens += total_tk
+                elif caller.startswith("middleware:"):
+                    self._middleware_tokens += total_tk
+                else:
+                    self._lead_agent_tokens += total_tk
 
     def on_llm_error(self, error: BaseException, *, run_id: UUID, **kwargs: Any) -> None:
         self._llm_start_times.pop(str(run_id), None)
-        self._put(event_type="llm.error", category="trace", content=str(error))
+        self._put(event_type="llm_error", category="trace", content=str(error))
 
-    def on_tool_start(self, serialized, input_str, *, run_id, parent_run_id=None, tags=None, metadata=None, inputs=None, **kwargs):
-        """Handle tool start event, cache tool call ID for later correlation"""
-        tool_call_id = str(run_id)
-        logger.info(f"Tool start for node {run_id}, tool_call_id={tool_call_id}, tags={tags}, metadata={metadata}")
+    # -- Tool callbacks --
 
-    def on_tool_end(self, output, *, run_id, parent_run_id=None, **kwargs):
-        """Handle tool end event, append message and clear node data"""
-        try:
-            if isinstance(output, ToolMessage):
-                msg = cast(ToolMessage, output)
-                self._put(event_type="llm.tool.result", category="message", content=msg.model_dump())
-            elif isinstance(output, Command):
-                cmd = cast(Command, output)
-                messages = cmd.update.get("messages", [])
-                for message in messages:
-                    if isinstance(message, BaseMessage):
-                        self._put(event_type="llm.tool.result", category="message", content=message.model_dump())
-                    else:
-                        logger.warning(f"on_tool_end {run_id}: command update message is not BaseMessage: {type(message)}")
-            else:
-                logger.warning(f"on_tool_end {run_id}: output is not ToolMessage: {type(output)}")
-        finally:
-            logger.info(f"Tool end for node {run_id}")
+    def on_tool_start(self, serialized: dict, input_str: str, *, run_id: UUID, **kwargs: Any) -> None:
+        tool_call_id = kwargs.get("tool_call_id")
+        if tool_call_id:
+            self._tool_call_ids[str(run_id)] = tool_call_id
+        self._put(
+            event_type="tool_start",
+            category="trace",
+            metadata={
+                "tool_name": serialized.get("name", ""),
+                "tool_call_id": tool_call_id,
+                "args": str(input_str)[:2000],
+            },
+        )
+
+    def on_tool_end(self, output: Any, *, run_id: UUID, **kwargs: Any) -> None:
+        from langchain_core.messages import ToolMessage
+
+        # Extract fields from ToolMessage object when LangChain provides one.
+        # LangChain's _format_output wraps tool results into a ToolMessage
+        # with tool_call_id, name, status, and artifact — more complete than
+        # what kwargs alone provides.
+        if isinstance(output, ToolMessage):
+            tool_call_id = output.tool_call_id or kwargs.get("tool_call_id") or self._tool_call_ids.pop(str(run_id), None)
+            tool_name = output.name or kwargs.get("name", "")
+            status = getattr(output, "status", "success") or "success"
+            content_str = output.content if isinstance(output.content, str) else str(output.content)
+            # Use model_dump() for checkpoint-aligned message content.
+            # Override tool_call_id if it was resolved from cache.
+            msg_content = output.model_dump()
+            if msg_content.get("tool_call_id") != tool_call_id:
+                msg_content["tool_call_id"] = tool_call_id
+        else:
+            tool_call_id = kwargs.get("tool_call_id") or self._tool_call_ids.pop(str(run_id), None)
+            tool_name = kwargs.get("name", "")
+            status = "success"
+            content_str = str(output)
+            # Construct checkpoint-aligned dict when output is a plain string.
+            msg_content = ToolMessage(
+                content=content_str,
+                tool_call_id=tool_call_id or "",
+                name=tool_name,
+                status=status,
+            ).model_dump()
+
+        # Trace event (always)
+        self._put(
+            event_type="tool_end",
+            category="trace",
+            content=content_str,
+            metadata={
+                "tool_name": tool_name,
+                "tool_call_id": tool_call_id,
+                "status": status,
+            },
+        )
+
+        # Message event: tool_result (checkpoint-aligned model_dump format)
+        self._put(
+            event_type="tool_result",
+            category="message",
+            content=msg_content,
+            metadata={"tool_name": tool_name, "status": status},
+        )
+
+    def on_tool_error(self, error: BaseException, *, run_id: UUID, **kwargs: Any) -> None:
+        from langchain_core.messages import ToolMessage
+
+        tool_call_id = kwargs.get("tool_call_id") or self._tool_call_ids.pop(str(run_id), None)
+        tool_name = kwargs.get("name", "")
+
+        # Trace event
+        self._put(
+            event_type="tool_error",
+            category="trace",
+            content=str(error),
+            metadata={
+                "tool_name": tool_name,
+                "tool_call_id": tool_call_id,
+            },
+        )
+
+        # Message event: tool_result with error status (checkpoint-aligned)
+        msg_content = ToolMessage(
+            content=str(error),
+            tool_call_id=tool_call_id or "",
+            name=tool_name,
+            status="error",
+        ).model_dump()
+        self._put(
+            event_type="tool_result",
+            category="message",
+            content=msg_content,
+            metadata={"tool_name": tool_name, "status": "error"},
+        )
+
+    # -- Custom event callback --
+
+    def on_custom_event(self, name: str, data: Any, *, run_id: UUID, **kwargs: Any) -> None:
+        from deerflow.runtime.serialization import serialize_lc_object
+
+        if name == "summarization":
+            data_dict = data if isinstance(data, dict) else {}
+            self._put(
+                event_type="summarization",
+                category="trace",
+                content=data_dict.get("summary", ""),
+                metadata={
+                    "replaced_message_ids": data_dict.get("replaced_message_ids", []),
+                    "replaced_count": data_dict.get("replaced_count", 0),
+                },
+            )
+            self._put(
+                event_type="middleware:summarize",
+                category="middleware",
+                content={"role": "system", "content": data_dict.get("summary", "")},
+                metadata={"replaced_count": data_dict.get("replaced_count", 0)},
+            )
+        else:
+            event_data = serialize_lc_object(data) if not isinstance(data, dict) else data
+            self._put(
+                event_type=name,
+                category="trace",
+                metadata=event_data if isinstance(event_data, dict) else {"data": event_data},
+            )
 
     # -- Internal methods --
 
@@ -271,10 +381,6 @@ class RunJournal(BaseCallbackHandler):
         """
         if not self._buffer:
             return
-        # Skip if a flush is already in flight — avoids concurrent writes
-        # to the same SQLite file from multiple fire-and-forget tasks.
-        if self._pending_flush_tasks:
-            return
         try:
             loop = asyncio.get_running_loop()
         except RuntimeError:
@@ -283,7 +389,6 @@ class RunJournal(BaseCallbackHandler):
         batch = self._buffer.copy()
         self._buffer.clear()
         task = loop.create_task(self._flush_async(batch))
-        self._pending_flush_tasks.add(task)
         task.add_done_callback(self._on_flush_done)
 
     async def _flush_async(self, batch: list[dict]) -> None:
@@ -299,17 +404,16 @@ class RunJournal(BaseCallbackHandler):
             # Return failed events to buffer for retry on next flush
             self._buffer = batch + self._buffer
 
-    def _on_flush_done(self, task: asyncio.Task) -> None:
-        self._pending_flush_tasks.discard(task)
+    @staticmethod
+    def _on_flush_done(task: asyncio.Task) -> None:
         if task.cancelled():
             return
         exc = task.exception()
         if exc:
             logger.warning("Journal flush task failed: %s", exc)
 
-    def _identify_caller(self, tags: list[str] | None, **kwargs) -> str:
-        _tags = tags or kwargs.get("tags", [])
-        for tag in _tags:
+    def _identify_caller(self, kwargs: dict) -> str:
+        for tag in kwargs.get("tags") or []:
             if isinstance(tag, str) and (tag.startswith("subagent:") or tag.startswith("middleware:") or tag == "lead_agent"):
                 return tag
         # Default to lead_agent: the main agent graph does not inject
@@ -346,17 +450,10 @@ class RunJournal(BaseCallbackHandler):
 
     async def flush(self) -> None:
         """Force flush remaining buffer. Called in worker's finally block."""
-        if self._pending_flush_tasks:
-            await asyncio.gather(*tuple(self._pending_flush_tasks), return_exceptions=True)
-
-        while self._buffer:
-            batch = self._buffer[: self._flush_threshold]
-            del self._buffer[: self._flush_threshold]
-            try:
-                await self._store.put_batch(batch)
-            except Exception:
-                self._buffer = batch + self._buffer
-                raise
+        if self._buffer:
+            batch = self._buffer.copy()
+            self._buffer.clear()
+            await self._store.put_batch(batch)
 
     def get_completion_data(self) -> dict:
         """Return accumulated token and message data for run completion."""

backend/packages/harness/deerflow/runtime/runs/manager.py

@@ -54,7 +54,7 @@ class RunManager:
         self._lock = asyncio.Lock()
         self._store = store
 
-    async def _persist_to_store(self, record: RunRecord) -> None:
+    async def _persist_to_store(self, record: RunRecord, *, follow_up_to_run_id: str | None = None) -> None:
         """Best-effort persist run record to backing store."""
         if self._store is None:
             return
@@ -68,6 +68,7 @@ class RunManager:
                 metadata=record.metadata or {},
                 kwargs=record.kwargs or {},
                 created_at=record.created_at,
+                follow_up_to_run_id=follow_up_to_run_id,
             )
         except Exception:
             logger.warning("Failed to persist run %s to store", record.run_id, exc_info=True)
@@ -89,6 +90,7 @@ class RunManager:
         metadata: dict | None = None,
         kwargs: dict | None = None,
         multitask_strategy: str = "reject",
+        follow_up_to_run_id: str | None = None,
     ) -> RunRecord:
         """Create a new pending run and register it."""
         run_id = str(uuid.uuid4())
@@ -107,7 +109,7 @@ class RunManager:
         )
         async with self._lock:
             self._runs[run_id] = record
-        await self._persist_to_store(record)
+        await self._persist_to_store(record, follow_up_to_run_id=follow_up_to_run_id)
         logger.info("Run created: run_id=%s thread_id=%s", run_id, thread_id)
         return record
 
@@ -120,7 +122,7 @@ class RunManager:
         async with self._lock:
             # Dict insertion order matches creation order, so reversing it gives
             # us deterministic newest-first results even when timestamps tie.
-            return [r for r in self._runs.values() if r.thread_id == thread_id]
+            return [r for r in reversed(self._runs.values()) if r.thread_id == thread_id]
 
     async def set_status(self, run_id: str, status: RunStatus, *, error: str | None = None) -> None:
         """Transition a run to a new status."""
@@ -174,6 +176,7 @@ class RunManager:
         metadata: dict | None = None,
         kwargs: dict | None = None,
         multitask_strategy: str = "reject",
+        follow_up_to_run_id: str | None = None,
     ) -> RunRecord:
         """Atomically check for inflight runs and create a new one.
 
@@ -227,7 +230,7 @@ class RunManager:
             )
             self._runs[run_id] = record
 
-        await self._persist_to_store(record)
+        await self._persist_to_store(record, follow_up_to_run_id=follow_up_to_run_id)
         logger.info("Run created: run_id=%s thread_id=%s", run_id, thread_id)
         return record
 

backend/packages/harness/deerflow/runtime/runs/store/base.py

@@ -4,8 +4,8 @@ RunManager depends on this interface. Implementations:
 - MemoryRunStore: in-memory dict (development, tests)
 - Future: RunRepository backed by SQLAlchemy ORM
 
-All methods accept an optional user_id for user isolation.
-When user_id is None, no user filtering is applied (single-user mode).
+All methods accept an optional owner_id for user isolation.
+When owner_id is None, no user filtering is applied (single-user mode).
 """
 
 from __future__ import annotations
@@ -22,13 +22,14 @@ class RunStore(abc.ABC):
         *,
         thread_id: str,
         assistant_id: str | None = None,
-        user_id: str | None = None,
+        owner_id: str | None = None,
         status: str = "pending",
         multitask_strategy: str = "reject",
         metadata: dict[str, Any] | None = None,
         kwargs: dict[str, Any] | None = None,
         error: str | None = None,
         created_at: str | None = None,
+        follow_up_to_run_id: str | None = None,
     ) -> None:
         pass
 
@@ -41,7 +42,7 @@ class RunStore(abc.ABC):
         self,
         thread_id: str,
         *,
-        user_id: str | None = None,
+        owner_id: str | None = None,
         limit: int = 100,
     ) -> list[dict[str, Any]]:
         pass