docs: align runtime docs with gateway mode (#2868)

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>

CONTRIBUTING.md

@@ -185,9 +185,9 @@ If you need to start services individually:
 
 1. **Start backend service**:
    ```bash
-   # Terminal 1: Start Gateway API and embedded LangGraph-compatible runtime (port 8001)
+   # Terminal 1: Start Gateway API + embedded agent runtime (port 8001)
    cd backend
-   make gateway
+   make dev
 
    # Terminal 2: Start Frontend (port 3000)
    cd frontend
@@ -207,7 +207,7 @@ If you need to start services individually:
 
 The nginx configuration provides:
 - Unified entry point on port 2026
-- Gateway owns `/api/langgraph/*` and translates those public LangGraph-compatible paths to its native `/api/*` routers behind nginx
+- Rewrites `/api/langgraph/*` to Gateway's LangGraph-compatible API (8001)
 - Routes other `/api/*` endpoints to Gateway API (8001)
 - Routes non-API requests to Frontend (3000)
 - Same-origin API routing; split-origin or port-forwarded browser clients should use the Gateway `GATEWAY_CORS_ORIGINS` allowlist
@@ -231,7 +231,7 @@ deer-flow/
 ├── backend/                 # Backend application
 │   ├── src/
 │   │   ├── gateway/        # Gateway API and LangGraph-compatible runtime (port 8001)
-│   │   ├── agents/         # LangGraph agent definitions
+│   │   ├── agents/         # LangGraph agent runtime used by Gateway
 │   │   ├── mcp/            # Model Context Protocol integration
 │   │   ├── skills/         # Skills system
 │   │   └── sandbox/        # Sandbox execution

README_fr.md

@@ -228,7 +228,7 @@ make down   # Stop and remove containers
 ```
 
 > [!NOTE]
-> Le serveur d'agents LangGraph fonctionne actuellement via `langgraph dev` (le serveur CLI open source).
+> Le runtime d'agent s'exécute actuellement dans la Gateway. nginx réécrit `/api/langgraph/*` vers l'API compatible LangGraph servie par la Gateway.
 
 Accès : http://localhost:2026
 
@@ -296,8 +296,8 @@ DeerFlow peut recevoir des tâches depuis des applications de messagerie. Les ca
 
 ```yaml
 channels:
-  # LangGraph Server URL (default: http://localhost:2024)
+  # LangGraph-compatible Gateway API base URL (default: http://localhost:8001/api)
-  langgraph_url: http://localhost:2024
+  langgraph_url: http://localhost:8001/api
   # Gateway API URL (default: http://localhost:8001)
   gateway_url: http://localhost:8001
 

README_ja.md

@@ -181,7 +181,7 @@ make down   # コンテナを停止して削除
 ```
 
 > [!NOTE]
-> LangGraphエージェントサーバーは現在`langgraph dev`（オープンソースCLIサーバー）経由で実行されます。
+> Agentランタイムは現在Gateway内で実行されます。`/api/langgraph/*`はnginxによってGatewayのLangGraph-compatible APIへ書き換えられます。
 
 アクセス: http://localhost:2026
 
@@ -249,8 +249,8 @@ DeerFlowはメッセージングアプリからのタスク受信をサポート
 
 ```yaml
 channels:
-  # LangGraphサーバーURL（デフォルト: http://localhost:2024）
+  # LangGraph-compatible Gateway API base URL（デフォルト: http://localhost:8001/api）
-  langgraph_url: http://localhost:2024
+  langgraph_url: http://localhost:8001/api
   # Gateway API URL（デフォルト: http://localhost:8001）
   gateway_url: http://localhost:8001
 

README_zh.md

@@ -184,7 +184,7 @@ make down   # 停止并移除容器
 ```
 
 > [!NOTE]
-> 当前 LangGraph agent server 通过开源 CLI 服务 `langgraph dev` 运行。
+> 当前 Agent 运行时嵌入在 Gateway 中运行，`/api/langgraph/*` 会由 nginx 重写到 Gateway 的 LangGraph-compatible API。
 
 访问地址：http://localhost:2026
 
@@ -254,8 +254,8 @@ DeerFlow 支持从即时通讯应用接收任务。只要配置完成，对应
 
 ```yaml
 channels:
-  # LangGraph Server URL（默认：http://localhost:2024）
+  # LangGraph-compatible Gateway API base URL（默认：http://localhost:8001/api）
-  langgraph_url: http://localhost:2024
+  langgraph_url: http://localhost:8001/api
   # Gateway API URL（默认：http://localhost:8001）
   gateway_url: http://localhost:8001
 

backend/CONTRIBUTING.md

@@ -56,11 +56,8 @@ export OPENAI_API_KEY="your-api-key"
 ### Run the Development Server
 
 ```bash
-# Terminal 1: LangGraph server
+# Gateway API + embedded agent runtime
 make dev
-
-# Terminal 2: Gateway API
-make gateway
 ```
 
 ## Project Structure

backend/README.md

@@ -11,34 +11,26 @@ DeerFlow is a LangGraph-based AI super agent with sandbox execution, persistent
                         │          Nginx (Port 2026)           │
                         │      Unified reverse proxy           │
                         └───────┬──────────────────┬───────────┘
-                                │                  │
+                                │
-              /api/langgraph/*  │                  │  /api/* (other)
+            /api/langgraph/*    │    /api/* (other)
-                                ▼                  ▼
+            rewritten to /api/* │
-               ┌──────────────────────────────────────────────┐
+                                ▼
+               ┌────────────────────────────────────────┐
                │        Gateway API (8001)              │
-               │  FastAPI REST + LangGraph-compatible runtime │
+               │        FastAPI REST + agent runtime    │
                │                                        │
                │ Models, MCP, Skills, Memory, Uploads,  │
                │ Artifacts, Threads, Runs, Streaming    │
                │                                        │
-               │ ┌────────────────┐                           │
+               │ ┌────────────────────────────────────┐ │
                │ │ Lead Agent                         │ │
-               │ │  ┌──────────┐  │                           │
+               │ │ Middleware Chain, Tools, Subagents │ │
-               │ │  │Middleware│  │                           │
+               │ └────────────────────────────────────┘ │
-               │ │  │  Chain   │  │                           │
+               └────────────────────────────────────────┘
-               │ │  └──────────┘  │                           │
-               │ │  ┌──────────┐  │                           │
-               │ │  │  Tools   │  │                           │
-               │ │  └──────────┘  │                           │
-               │ │  ┌──────────┐  │                           │
-               │ │  │Subagents │  │                           │
-               │ │  └──────────┘  │                           │
-               │ └────────────────┘                           │
-               └──────────────────────────────────────────────┘
 ```
 
 **Request Routing** (via Nginx):
-- `/api/langgraph/*` → Gateway API - LangGraph-compatible agent interactions, threads, runs, and streaming translated to native `/api/*` routers
+- `/api/langgraph/*` → Gateway LangGraph-compatible API - agent interactions, threads, streaming
 - `/api/*` (other) → Gateway API - models, MCP, skills, memory, artifacts, uploads, thread-local cleanup
 - `/` (non-API) → Frontend - Next.js web interface
 
@@ -196,7 +188,7 @@ export OPENAI_API_KEY="your-api-key-here"
 **Full Application** (from project root):
 
 ```bash
-make dev  # Starts LangGraph + Gateway + Frontend + Nginx
+make dev  # Starts Gateway + Frontend + Nginx
 ```
 
 Access at: http://localhost:2026
@@ -204,14 +196,11 @@ Access at: http://localhost:2026
 **Backend Only** (from backend directory):
 
 ```bash
-# Terminal 1: LangGraph server
+# Gateway API + embedded agent runtime
 make dev
-
-# Terminal 2: Gateway API
-make gateway
 ```
 
-Direct access: LangGraph at http://localhost:2024, Gateway at http://localhost:8001
+Direct access: Gateway at http://localhost:8001
 
 ---
 
@@ -247,7 +236,7 @@ backend/
 │   └── utils/                  # Utilities
 ├── docs/                       # Documentation
 ├── tests/                      # Test suite
-├── langgraph.json              # LangGraph server configuration
+├── langgraph.json              # LangGraph graph registry for tooling/Studio compatibility
 ├── pyproject.toml              # Python dependencies
 ├── Makefile                    # Development commands
 └── Dockerfile                  # Container build
@@ -365,8 +354,8 @@ If a provider is explicitly enabled but required credentials are missing, or the
 
 ```bash
 make install    # Install dependencies
-make dev        # Run LangGraph server (port 2024)
+make dev        # Run Gateway API + embedded agent runtime (port 8001)
-make gateway    # Run Gateway API (port 8001)
+make gateway    # Run Gateway API without reload (port 8001)
 make lint       # Run linter (ruff)
 make format     # Format code (ruff)
 ```

backend/docs/API.md

@@ -561,12 +561,13 @@ location /api/ {
 
 ---
 
-## WebSocket Support
+## Streaming Support
 
-The LangGraph server supports WebSocket connections for real-time streaming. Connect to:
+Gateway's LangGraph-compatible API streams run events with Server-Sent Events (SSE):
 
-```
+```http
-ws://localhost:2026/api/langgraph/threads/{thread_id}/runs/stream
+POST /api/langgraph/threads/{thread_id}/runs/stream
+Accept: text/event-stream
 ```
 
 ---
@@ -602,13 +603,21 @@ const response = await fetch('/api/models');
 const data = await response.json();
 console.log(data.models);
 
-// Using EventSource for streaming
+// Create a run and stream SSE events
-const eventSource = new EventSource(
+const streamResponse = await fetch(`/api/langgraph/threads/${threadId}/runs/stream`, {
-  `/api/langgraph/threads/${threadId}/runs/stream`
+  method: "POST",
-);
+  headers: {
-eventSource.onmessage = (event) => {
+    "Content-Type": "application/json",
-  console.log(JSON.parse(event.data));
+    Accept: "text/event-stream",
-};
+  },
+  body: JSON.stringify({
+    input: { messages: [{ role: "user", content: "Hello" }] },
+    stream_mode: ["values", "messages-tuple", "custom"],
+  }),
+});
+
+const reader = streamResponse.body?.getReader();
+// Decode and parse SSE frames from reader in your client code.
 ```
 
 ### cURL Examples

backend/docs/ARCHITECTURE.md

@@ -20,24 +20,22 @@ This document provides a comprehensive overview of the DeerFlow backend architec
 │  └────────────────────────────────────────────────────────────────────┘  │
 └─────────────────────────────────┬────────────────────────────────────────┘
                                   │
-          ┌───────────────────────┼───────────────────────┐
+          ┌───────────────────────┴───────────────────────┐
-          │                       │                       │
-          ▼                       ▼                       ▼
-┌─────────────────────┐ ┌─────────────────────┐ ┌─────────────────────┐
-│ Embedded Runtime    │ │    Gateway API      │ │     Frontend        │
-│  (inside Gateway)   │ │    (Port 8001)      │ │    (Port 3000)      │
-│                     │ │                     │ │                     │
-│  - Agent Runtime    │ │  - Models API       │ │  - Next.js App      │
-│  - Thread Mgmt      │ │  - MCP Config       │ │  - React UI         │
-│  - SSE Streaming    │ │  - Skills Mgmt      │ │  - Chat Interface   │
-│  - Checkpointing    │ │  - File Uploads     │ │                     │
-│                     │ │  - Thread Cleanup   │ │                     │
-│                     │ │  - Artifacts        │ │                     │
-└─────────────────────┘ └─────────────────────┘ └─────────────────────┘
-          │                       │
-          │     ┌─────────────────┘
           │                                               │
           ▼                                               ▼
+┌─────────────────────────────────────────────┐ ┌─────────────────────┐
+│              Gateway API                    │ │     Frontend        │
+│              (Port 8001)                    │ │    (Port 3000)      │
+│                                             │ │                     │
+│  - LangGraph-compatible runs/threads API    │ │  - Next.js App      │
+│  - Embedded Agent Runtime                   │ │  - React UI         │
+│  - SSE Streaming                            │ │  - Chat Interface   │
+│  - Checkpointing                            │ │                     │
+│  - Models, MCP, Skills, Uploads, Artifacts  │ │                     │
+│  - Thread Cleanup                           │ │                     │
+└─────────────────────────────────────────────┘ └─────────────────────┘
+          │
+          ▼
 ┌──────────────────────────────────────────────────────────────────────────┐
 │                         Shared Configuration                              │
 │  ┌─────────────────────────┐  ┌────────────────────────────────────────┐ │
@@ -52,9 +50,9 @@ This document provides a comprehensive overview of the DeerFlow backend architec
 
 ## Component Details
 
-### Embedded LangGraph Runtime
+### Gateway Embedded Agent Runtime
 
-The LangGraph-compatible runtime runs inside the Gateway process and is built on LangGraph for robust multi-agent workflow orchestration.
+The agent runtime is embedded in the FastAPI Gateway and built on LangGraph for robust multi-agent workflow orchestration. Nginx rewrites `/api/langgraph/*` to Gateway's native `/api/*` routes, so the public API remains compatible with LangGraph SDK clients without running a separate LangGraph server.
 
 **Entry Point**: `packages/harness/deerflow/agents/lead_agent/agent.py:make_lead_agent`
 
@@ -65,7 +63,7 @@ The LangGraph-compatible runtime runs inside the Gateway process and is built on
 - Tool execution orchestration
 - SSE streaming for real-time responses
 
-**Configuration**: `langgraph.json`
+**Graph registry**: `langgraph.json` remains available for tooling and Studio compatibility.
 
 ```json
 {
@@ -84,6 +82,7 @@ FastAPI application providing REST endpoints plus the public LangGraph-compatibl
 
 **Routers**:
 - `models.py` - `/api/models` - Model listing and details
+- `thread_runs.py` / `runs.py` - `/api/threads/{id}/runs`, `/api/runs/*` - LangGraph-compatible runs and streaming
 - `mcp.py` - `/api/mcp` - MCP server configuration
 - `skills.py` - `/api/skills` - Skills management
 - `uploads.py` - `/api/threads/{id}/uploads` - File upload
@@ -91,7 +90,7 @@ FastAPI application providing REST endpoints plus the public LangGraph-compatibl
 - `artifacts.py` - `/api/threads/{id}/artifacts` - Artifact serving
 - `suggestions.py` - `/api/threads/{id}/suggestions` - Follow-up suggestion generation
 
-The web conversation delete flow is now split across both backend surfaces: LangGraph handles `DELETE /api/langgraph/threads/{thread_id}` for thread state, then the Gateway `threads.py` router removes DeerFlow-managed filesystem data via `Paths.delete_thread_dir()`.
+The web conversation delete flow first deletes Gateway-managed thread state through the LangGraph-compatible route, then the Gateway `threads.py` router removes DeerFlow-managed filesystem data via `Paths.delete_thread_dir()`.
 
 ### Agent Architecture
 
@@ -354,9 +353,9 @@ SKILL.md Format:
    {"input": {"messages": [{"role": "user", "content": "Hello"}]}}
 
 2. Nginx → Gateway API (8001)
-   Routes `/api/langgraph/*` to the Gateway's LangGraph-compatible runtime
+   `/api/langgraph/*` is rewritten to Gateway's LangGraph-compatible `/api/*` routes
 
-3. Embedded LangGraph runtime
+3. Gateway embedded runtime
    a. Load/create thread state
    b. Execute middleware chain:
       - ThreadDataMiddleware: Set up paths
@@ -412,7 +411,7 @@ SKILL.md Format:
 ### Thread Cleanup Flow
 
 ```
-1. Client deletes conversation via LangGraph
+1. Client deletes conversation via the LangGraph-compatible Gateway route
    DELETE /api/langgraph/threads/{thread_id}
 
 2. Web UI follows up with Gateway cleanup

frontend/README.md

@@ -82,10 +82,10 @@ pnpm start
 Key environment variables (see `.env.example` for full list):
 
 ```bash
-# Backend API URLs (optional, uses nginx proxy by default)
+# Backend API URL (optional, uses local Next.js/nginx proxy by default)
 NEXT_PUBLIC_BACKEND_BASE_URL="http://localhost:8001"
-# LangGraph API URLs (optional, uses nginx proxy by default)
+# LangGraph-compatible API URL (optional, uses local Next.js/nginx proxy by default)
-NEXT_PUBLIC_LANGGRAPH_BASE_URL="http://localhost:2024"
+NEXT_PUBLIC_LANGGRAPH_BASE_URL="http://localhost:8001/api"
 ```
 
 ## Project Structure

frontend/src/content/en/application/agents-and-threads.mdx

@@ -111,10 +111,9 @@ checkpointer:
 ```
 
 <Callout type="info">
-  The LangGraph Server manages its own state separately. The
+  The Gateway embedded runtime uses the <code>checkpointer</code> setting in
-  <code>checkpointer</code> setting in <code>config.yaml</code> applies to the
+  <code>config.yaml</code>. The same setting is also used by
-  embedded <code>DeerFlowClient</code> (used in direct Python integrations), not
+  <code>DeerFlowClient</code> in direct Python integrations.
-  to the LangGraph Server deployment used by DeerFlow App.
 </Callout>
 
 ### Thread data storage

frontend/src/content/en/application/deployment-guide.mdx

@@ -23,8 +23,7 @@ Services started:
 
 | Service     | Port | Description              |
 | ----------- | ---- | ------------------------ |
-| LangGraph   | 2024 | DeerFlow Harness runtime |
+| Gateway API | 8001 | FastAPI backend + embedded agent runtime |
-| Gateway API | 8001 | FastAPI backend          |
 | Frontend    | 3000 | Next.js UI               |
 | nginx       | 2026 | Unified reverse proxy    |
 
@@ -36,13 +35,12 @@ Access the app at **http://localhost:2026**.
 make stop
 ```
 
-Stops all four services. Safe to run even if a service is not running.
+Stops all services. Safe to run even if a service is not running.
 
   </Tabs.Tab>
   <Tabs.Tab>
 ```
-logs/langgraph.log   # Agent runtime logs
+logs/gateway.log     # API gateway and agent runtime logs
-logs/gateway.log     # API gateway logs
 logs/frontend.log    # Next.js dev server logs
 logs/nginx.log       # nginx access/error logs
 ```
@@ -50,7 +48,7 @@ logs/nginx.log       # nginx access/error logs
 Tail a log in real time:
 
 ```bash
-tail -f logs/langgraph.log
+tail -f logs/gateway.log
 ```
 
   </Tabs.Tab>
@@ -74,7 +72,7 @@ export DEER_FLOW_ROOT=/path/to/deer-flow
 docker compose -f docker/docker-compose-dev.yaml up --build
 ```
 
-Services: nginx, frontend, gateway, langgraph, and optionally provisioner (for K8s-managed sandboxes).
+Services: nginx, frontend, gateway, and optionally provisioner (for K8s-managed sandboxes).
 
 Access the app at **http://localhost:2026**.
 
@@ -99,7 +97,7 @@ The `docker-compose*.yaml` files include an `env_file: ../.env` directive that l
 
 ### Data persistence
 
-Thread data is stored in `backend/.deer-flow/threads/`. In Docker deployments, this directory is bind-mounted into the langgraph container.
+Thread data is stored in `backend/.deer-flow/threads/`. In Docker deployments, this directory is bind-mounted into the gateway container.
 
 To avoid data loss when containers are recreated:
 
@@ -161,14 +159,7 @@ When `USERDATA_PVC_NAME` is set, the provisioner automatically uses subPath (`th
 
 ### nginx configuration
 
-nginx routes all traffic. Key environment variables that control routing:
+nginx routes all traffic to the frontend or Gateway. `/api/langgraph/*` is rewritten to Gateway's LangGraph-compatible `/api/*` routes, so no separate LangGraph upstream is required.
-
-| Variable             | Default          | Description                             |
-| -------------------- | ---------------- | --------------------------------------- |
-| `LANGGRAPH_UPSTREAM` | `langgraph:2024` | LangGraph service address               |
-| `LANGGRAPH_REWRITE`  | `/`              | URL rewrite prefix for LangGraph routes |
-
-These are set in the Docker Compose environment and processed by `envsubst` at container startup.
 
 ### Authentication
 
@@ -186,8 +177,7 @@ openssl rand -base64 32
 
 | Service                         | Minimum          | Recommended      |
 | ------------------------------- | ---------------- | ---------------- |
-| LangGraph (agent runtime)       | 2 vCPU, 4 GB RAM | 4 vCPU, 8 GB RAM |
+| Gateway + agent runtime         | 2 vCPU, 4 GB RAM | 4 vCPU, 8 GB RAM |
-| Gateway                         | 0.5 vCPU, 512 MB | 1 vCPU, 1 GB     |
 | Frontend                        | 0.5 vCPU, 512 MB | 1 vCPU, 1 GB     |
 | Sandbox container (per session) | 1 vCPU, 1 GB     | 2 vCPU, 2 GB     |
 
@@ -199,9 +189,6 @@ After starting, verify the deployment:
 # Check Gateway health
 curl http://localhost:8001/health
 
-# Check LangGraph health
-curl http://localhost:2024/ok
-
 # List configured models (through nginx)
 curl http://localhost:2026/api/models
 ```

frontend/src/content/en/application/index.mdx

@@ -25,11 +25,11 @@ DeerFlow App is the reference implementation of what a production DeerFlow exper
 | **Streaming responses** | Real-time token streaming with thinking steps and tool call visibility                               |
 | **Artifact viewer**     | In-browser preview and download of files and outputs produced by the agent                           |
 | **Extensions UI**       | Enable/disable MCP servers and skills without editing config files                                   |
-| **Gateway API**         | FastAPI-based REST API that bridges the frontend and the LangGraph runtime                           |
+| **Gateway API**         | FastAPI-based REST API with the embedded LangGraph-compatible agent runtime                          |
 
 ## Architecture
 
-The DeerFlow App runs as four services behind a single nginx reverse proxy:
+The DeerFlow App runs behind a single nginx reverse proxy:
 
 ```
                 ┌──────────────────┐
@@ -42,19 +42,11 @@ The DeerFlow App runs as four services behind a single nginx reverse proxy:
 │  Frontend :3000  │       │  Gateway API :8001    │
 │  (Next.js)       │       │  (FastAPI)            │
 └──────────────────┘       └──────────────────────┘
-                                      │
-                            ┌─────────┘
-                            ▼
-                  ┌──────────────────────┐
-                  │  LangGraph :2024     │
-                  │  (DeerFlow Harness)  │
-                  └──────────────────────┘
 ```
 
-- **nginx**: routes requests — `/api/*` to the Gateway, LangGraph streaming endpoints to LangGraph directly, and everything else to the frontend.
+- **nginx**: routes requests — `/api/*` and `/api/langgraph/*` to Gateway, and everything else to the frontend.
-- **Frontend** (Next.js + React): the browser UI. Communicates with both the Gateway and LangGraph.
+- **Frontend** (Next.js + React): the browser UI. Communicates with Gateway.
-- **Gateway** (FastAPI): handles API operations — model listing, agent CRUD, memory, extensions management, file uploads.
+- **Gateway** (FastAPI): handles API operations and the embedded LangGraph-compatible runtime for thread state, agent execution, and streaming.
-- **LangGraph**: the DeerFlow Harness runtime. Manages thread state, agent execution, and streaming.
 
 ## Technology stack
 
@@ -64,7 +56,7 @@ The DeerFlow App runs as four services behind a single nginx reverse proxy:
 | Gateway           | FastAPI, Python 3.12, uvicorn                                        |
 | Agent runtime     | LangGraph, LangChain, DeerFlow Harness                               |
 | Reverse proxy     | nginx                                                                |
-| State persistence | LangGraph Server (default) + optional SQLite/PostgreSQL checkpointer |
+| State persistence | Gateway runtime + optional SQLite/PostgreSQL checkpointer             |
 
 <Cards num={2}>
   <Cards.Card title="Quick Start" href="/docs/application/quick-start" />

frontend/src/content/en/application/operations-and-troubleshooting.mdx

@@ -15,15 +15,13 @@ All services write logs to the `logs/` directory when started with `make dev`:
 
 | File                 | Service                              |
 | -------------------- | ------------------------------------ |
-| `logs/langgraph.log` | LangGraph / DeerFlow Harness runtime |
+| `logs/gateway.log`   | FastAPI Gateway API and agent runtime |
-| `logs/gateway.log`   | FastAPI Gateway API                  |
 | `logs/frontend.log`  | Next.js frontend dev server          |
 | `logs/nginx.log`     | nginx reverse proxy                  |
 
 Tail logs in real time:
 
 ```bash
-tail -f logs/langgraph.log
 tail -f logs/gateway.log
 ```
 
@@ -41,9 +39,6 @@ Verify each service is responding:
 # Gateway health
 curl http://localhost:8001/health
 
-# LangGraph health
-curl http://localhost:2024/ok
-
 # Through nginx (verifies full proxy chain)
 curl http://localhost:2026/api/models
 ```
@@ -66,7 +61,7 @@ grep config_version config.yaml
 
 ### The app loads but the agent doesn't respond
 
-1. Check `logs/langgraph.log` for startup errors.
+1. Check `logs/gateway.log` for startup errors.
 2. Verify your model is correctly configured in `config.yaml` with a valid API key.
 3. Confirm the API key environment variable is set in the shell that ran `make dev`.
 4. Test the model endpoint directly with `curl` to rule out network issues.
@@ -126,7 +121,7 @@ Connection refused: http://provisioner:8002
 
 If MCP tools appear in `extensions_config.json` but are not available in the agent:
 
-1. Check `logs/langgraph.log` for MCP initialization errors.
+1. Check `logs/gateway.log` for MCP initialization errors.
 2. Verify the MCP server command is installed (`npx`, `uvx`, or the relevant binary).
 3. Test the server command manually to confirm it starts without errors.
 4. Set `log_level: debug` to see detailed MCP loading output.
@@ -137,7 +132,7 @@ If MCP tools appear in `extensions_config.json` but are not available in the age
 
 - Verify `memory.enabled: true` in `config.yaml`.
 - Check that the storage path is writable: `ls -la backend/.deer-flow/`.
-- Look for memory update errors in `logs/langgraph.log` (search for "memory").
+- Look for memory update errors in `logs/gateway.log` (search for "memory").
 
 ## Data backup
 

frontend/src/content/en/application/quick-start.mdx

@@ -1,6 +1,6 @@
 ---
 title: Quick Start
-description: This guide walks you through starting DeerFlow App on your local machine using the `make dev` workflow. All four services (LangGraph, Gateway, Frontend, nginx) start together and are accessible through a single URL.
+description: This guide walks you through starting DeerFlow App on your local machine using the `make dev` workflow. Gateway, Frontend, and nginx start together and are accessible through a single URL.
 ---
 
 import { Callout, Cards, Steps } from "nextra/components";
@@ -12,7 +12,7 @@ import { Callout, Cards, Steps } from "nextra/components";
   Python 3.12+, Node.js 22+, and at least one LLM API key.
 </Callout>
 
-This guide walks you through starting DeerFlow App on your local machine using the `make dev` workflow. All four services (LangGraph, Gateway, Frontend, nginx) start together and are accessible through a single URL.
+This guide walks you through starting DeerFlow App on your local machine using the `make dev` workflow. Gateway, Frontend, and nginx start together and are accessible through a single URL.
 
 ## Prerequisites
 
@@ -88,8 +88,7 @@ make dev
 
 This starts:
 
-- LangGraph server on port `2024`
+- Gateway API and embedded agent runtime on port `8001`
-- Gateway API on port `8001`
 - Frontend on port `3000`
 - nginx reverse proxy on port `2026`
 
@@ -113,15 +112,13 @@ Log files:
 
 | Service   | Log file             |
 | --------- | -------------------- |
-| LangGraph | `logs/langgraph.log` |
 | Gateway   | `logs/gateway.log`   |
 | Frontend  | `logs/frontend.log`  |
 | nginx     | `logs/nginx.log`     |
 
 <Callout type="tip">
   If something is not working, check the log files first. Most startup errors
-  (missing API keys, config parsing failures) appear in `logs/langgraph.log` or
+  (missing API keys, config parsing failures) appear in `logs/gateway.log`.
-  `logs/gateway.log`.
 </Callout>
 
 <Cards num={2}>

frontend/src/content/en/harness/skills.mdx

@@ -68,7 +68,7 @@ DeerFlow ships with the following public skills:
 
 ### Discovery and loading
 
-`load_skills()` in `skills/loader.py` scans both `public/` and `custom/` directories under the configured skills path. It re-reads `ExtensionsConfig.from_file()` on every call, which means enabling or disabling a skill through the Gateway API takes effect immediately in the running LangGraph server without a restart.
+`load_skills()` in `skills/loader.py` scans both `public/` and `custom/` directories under the configured skills path. It re-reads `ExtensionsConfig.from_file()` on every call, which means enabling or disabling a skill through the Gateway API takes effect immediately in the running agent runtime without a restart.
 
 ### Parsing
 

frontend/src/content/zh/application/configuration.mdx

@@ -215,7 +215,6 @@ BETTER_AUTH_SECRET=local-dev-secret-at-least-32-chars
 | `DEER_FLOW_CONFIG_PATH` | 自动发现         | `config.yaml` 的绝对路径                         |
 | `LOG_LEVEL`             | `info`           | 日志详细程度（`debug`/`info`/`warning`/`error`） |
 | `DEER_FLOW_ROOT`        | 仓库根目录       | 用于 Docker 中的技能和线程挂载                   |
-| `LANGGRAPH_UPSTREAM`    | `langgraph:2024` | nginx 代理的 LangGraph 地址                      |
 
 <Cards num={2}>
   <Cards.Card title="Harness 配置" href="/docs/harness/configuration" />

frontend/src/content/zh/application/deployment-guide.mdx

@@ -23,8 +23,7 @@ make dev
 
 | 服务        | 端口 | 描述                    |
 | ----------- | ---- | ----------------------- |
-| LangGraph   | 2024 | DeerFlow Harness 运行时 |
+| Gateway API | 8001 | FastAPI 后端 + 嵌入式 Agent 运行时 |
-| Gateway API | 8001 | FastAPI 后端            |
 | 前端        | 3000 | Next.js 界面            |
 | nginx       | 2026 | 统一反向代理            |
 
@@ -36,13 +35,12 @@ make dev
 make stop
 ```
 
-停止所有四个服务。即使某个服务没有运行也可以安全执行。
+停止所有服务。即使某个服务没有运行也可以安全执行。
 
   </Tabs.Tab>
   <Tabs.Tab>
 ```
-logs/langgraph.log   # Agent 运行时日志
+logs/gateway.log     # API Gateway 和 Agent 运行时日志
-logs/gateway.log     # API Gateway 日志
 logs/frontend.log    # Next.js 开发服务器日志
 logs/nginx.log       # nginx 访问/错误日志
 ```
@@ -50,7 +48,7 @@ logs/nginx.log       # nginx 访问/错误日志
 实时追踪日志：
 
 ```bash
-tail -f logs/langgraph.log
+tail -f logs/gateway.log
 ```
 
   </Tabs.Tab>
@@ -96,7 +94,7 @@ BETTER_AUTH_SECRET=your-secret-here-min-32-chars
 
 ### 数据持久化
 
-线程数据存储在 `backend/.deer-flow/threads/`。在 Docker 部署中，此目录被绑定挂载到 langgraph 容器中。
+线程数据存储在 `backend/.deer-flow/threads/`。在 Docker 部署中，此目录会绑定挂载到 gateway 容器中。
 
 为避免容器重建时数据丢失：
 
@@ -156,14 +154,7 @@ SKILLS_PVC_NAME=deer-flow-skills-pvc
 
 ### nginx 配置
 
-nginx 路由所有流量，控制路由的关键环境变量：
+nginx 将流量路由到前端或 Gateway。`/api/langgraph/*` 会被重写到 Gateway 的 LangGraph-compatible `/api/*` 路由，因此不需要单独的 LangGraph upstream。
-
-| 变量                 | 默认值           | 描述                          |
-| -------------------- | ---------------- | ----------------------------- |
-| `LANGGRAPH_UPSTREAM` | `langgraph:2024` | LangGraph 服务地址            |
-| `LANGGRAPH_REWRITE`  | `/`              | LangGraph 路由的 URL 重写前缀 |
-
-这些在 Docker Compose 环境中设置，并在容器启动时由 `envsubst` 处理。
 
 ### 认证配置
 
@@ -181,8 +172,7 @@ openssl rand -base64 32
 
 | 服务                      | 最低配置         | 推荐配置         |
 | ------------------------- | ---------------- | ---------------- |
-| LangGraph（Agent 运行时） | 2 vCPU、4 GB RAM | 4 vCPU、8 GB RAM |
+| Gateway + Agent 运行时    | 2 vCPU、4 GB RAM | 4 vCPU、8 GB RAM |
-| Gateway                   | 0.5 vCPU、512 MB | 1 vCPU、1 GB     |
 | 前端                      | 0.5 vCPU、512 MB | 1 vCPU、1 GB     |
 | 沙箱容器（每会话）        | 1 vCPU、1 GB     | 2 vCPU、2 GB     |
 
@@ -194,9 +184,6 @@ openssl rand -base64 32
 # 检查 Gateway 健康状态
 curl http://localhost:8001/health
 
-# 检查 LangGraph 健康状态
-curl http://localhost:2024/ok
-
 # 通过 nginx 列出配置的模型（验证完整代理链）
 curl http://localhost:2026/api/models
 ```

frontend/src/content/zh/application/index.mdx

@@ -25,11 +25,11 @@ DeerFlow 应用是 DeerFlow 生产体验的参考实现。它将 Harness 运行
 | **流式响应**     | 实时 token 流式传输，带思考步骤和工具调用可见性       |
 | **产出物查看器** | Agent 生成文件和输出的浏览器内预览和下载              |
 | **扩展界面**     | 无需编辑配置文件即可启用/禁用 MCP 服务器和技能        |
-| **Gateway API**  | 桥接前端和 LangGraph 运行时的基于 FastAPI 的 REST API |
+| **Gateway API**  | 基于 FastAPI 的 REST API，并内置 LangGraph-compatible Agent 运行时 |
 
 ## 架构
 
-DeerFlow 应用以四个服务的形式运行，通过单个 nginx 反向代理提供：
+DeerFlow 应用通过单个 nginx 反向代理提供：
 
 ```
                 ┌──────────────────┐
@@ -42,19 +42,11 @@ DeerFlow 应用以四个服务的形式运行，通过单个 nginx 反向代理
 │  前端 :3000      │       │  Gateway API :8001    │
 │  (Next.js)       │       │  (FastAPI)            │
 └──────────────────┘       └──────────────────────┘
-                                      │
-                            ┌─────────┘
-                            ▼
-                  ┌──────────────────────┐
-                  │  LangGraph :2024     │
-                  │  (DeerFlow Harness)  │
-                  └──────────────────────┘
 ```
 
-- **nginx**：路由请求——`/api/*` 到 Gateway，LangGraph 流式端点到 LangGraph，其余到前端。
+- **nginx**：路由请求——`/api/*` 和 `/api/langgraph/*` 到 Gateway，其余到前端。
-- **前端**（Next.js + React）：浏览器界面，与 Gateway 和 LangGraph 通信。
+- **前端**（Next.js + React）：浏览器界面，与 Gateway 通信。
-- **Gateway**（FastAPI）：处理 API 操作——模型列表、Agent CRUD、记忆、扩展管理、文件上传。
+- **Gateway**（FastAPI）：处理 API 操作，并通过内置 LangGraph-compatible 运行时管理线程状态、Agent 执行和流式传输。
-- **LangGraph**：DeerFlow Harness 运行时，管理线程状态、Agent 执行和流式传输。
 
 ## 技术栈
 
@@ -64,7 +56,7 @@ DeerFlow 应用以四个服务的形式运行，通过单个 nginx 反向代理
 | Gateway      | FastAPI、Python 3.12、uvicorn                           |
 | Agent 运行时 | LangGraph、LangChain、DeerFlow Harness                  |
 | 反向代理     | nginx                                                   |
-| 状态持久化   | LangGraph Server（默认）+ 可选 SQLite/PostgreSQL 检查点 |
+| 状态持久化   | Gateway 运行时 + 可选 SQLite/PostgreSQL 检查点 |
 
 <Cards num={2}>
   <Cards.Card title="快速上手" href="/docs/application/quick-start" />

frontend/src/content/zh/application/operations-and-troubleshooting.mdx

@@ -15,16 +15,14 @@ DeerFlow 应用在 `logs/` 目录中写入每个服务的日志：
 
 | 文件                 | 内容                                   |
 | -------------------- | -------------------------------------- |
-| `logs/langgraph.log` | Agent 运行时、工具调用、LangGraph 错误 |
+| `logs/gateway.log`   | API 请求/响应、Agent 运行时和 Gateway 错误 |
-| `logs/gateway.log`   | API 请求/响应、Gateway 错误            |
 | `logs/frontend.log`  | Next.js 服务器日志                     |
 | `logs/nginx.log`     | 代理访问和错误日志                     |
 
 **实时追踪日志**：
 
 ```bash
-tail -f logs/langgraph.log   # 查看 Agent 活动
+tail -f logs/gateway.log     # 查看 API 请求和 Agent 活动
-tail -f logs/gateway.log     # 查看 API 请求
 ```
 
 **调整日志级别**：
@@ -42,9 +40,6 @@ DeerFlow 暴露健康检查端点：
 # Gateway 健康状态
 curl http://localhost:8001/health
 
-# LangGraph 健康状态
-curl http://localhost:2024/ok
-
 # 通过 nginx 完整代理链验证
 curl http://localhost:2026/api/models
 ```
@@ -68,8 +63,8 @@ make config-upgrade
 **诊断**：
 
 ```bash
-# 检查 LangGraph 日志中的模型错误
+# 检查 Gateway 日志中的模型错误
-grep -i "error\|apikey\|unauthorized" logs/langgraph.log | tail -20
+grep -i "error\|apikey\|unauthorized" logs/gateway.log | tail -20
 ```
 
 **解决**：
@@ -118,13 +113,13 @@ SKIP_ENV_VALIDATION=1 pnpm build
 
 ### MCP 服务器连接失败
 
-**症状**：MCP 工具未出现，`logs/langgraph.log` 中有超时错误。
+**症状**：MCP 工具未出现，`logs/gateway.log` 中有超时错误。
 
 **诊断**：
 
 ```bash
 # 检查 MCP 相关错误
-grep -i "mcp\|timeout" logs/langgraph.log | tail -20
+grep -i "mcp\|timeout" logs/gateway.log | tail -20
 ```
 
 **解决**：

frontend/src/content/zh/application/quick-start.mdx

@@ -1,6 +1,6 @@
 ---
 title: 快速上手
-description: 本指南引导你使用 `make dev` 工作流在本地机器上启动 DeerFlow 应用。所有四个服务（LangGraph、Gateway、前端、nginx）一起启动，通过单个 URL 访问。
+description: 本指南引导你使用 `make dev` 工作流在本地机器上启动 DeerFlow 应用。Gateway、前端和 nginx 会一起启动，通过单个 URL 访问。
 ---
 
 import { Callout, Cards, Steps } from "nextra/components";
@@ -12,7 +12,7 @@ import { Callout, Cards, Steps } from "nextra/components";
   3.12+、Node.js 22+ 的机器，以及至少一个 LLM API Key。
 </Callout>
 
-本指南引导你使用 `make dev` 工作流在本地机器上启动 DeerFlow 应用。所有四个服务（LangGraph、Gateway、前端、nginx）一起启动，通过单个 URL 访问。
+本指南引导你使用 `make dev` 工作流在本地机器上启动 DeerFlow 应用。Gateway、前端和 nginx 会一起启动，通过单个 URL 访问。
 
 ## 前置条件
 
@@ -88,8 +88,7 @@ make dev
 
 这会启动：
 
-- LangGraph 服务，端口 `2024`
+- Gateway API 和嵌入式 Agent 运行时，端口 `8001`
-- Gateway API，端口 `8001`
 - 前端，端口 `3000`
 - nginx 反向代理，端口 `2026`
 
@@ -113,15 +112,13 @@ make stop
 
 | 服务      | 日志文件             |
 | --------- | -------------------- |
-| LangGraph | `logs/langgraph.log` |
 | Gateway   | `logs/gateway.log`   |
 | 前端      | `logs/frontend.log`  |
 | nginx     | `logs/nginx.log`     |
 
 <Callout type="tip">
   如果有问题，先检查日志文件。大多数启动错误（缺失 API
-  Key、配置解析失败）会出现在 <code>logs/langgraph.log</code> 或{" "}
+  Key、配置解析失败）会出现在 <code>logs/gateway.log</code> 中。
-  <code>logs/gateway.log</code> 中。
 </Callout>
 
 <Cards num={2}>

skills/public/claude-to-deerflow/SKILL.md

@@ -14,8 +14,8 @@ DeerFlow exposes two API surfaces behind an Nginx reverse proxy:
 
 | Service        | Direct Port | Via Proxy                        | Purpose                          |
 |----------------|-------------|----------------------------------|----------------------------------|
-| Gateway API    | 8001        | `$DEERFLOW_GATEWAY_URL`          | REST endpoints (models, skills, memory, uploads) |
+| Gateway API    | 8001        | `$DEERFLOW_GATEWAY_URL`          | REST endpoints and embedded agent runtime |
-| LangGraph API  | 2024        | `$DEERFLOW_LANGGRAPH_URL`        | Agent threads, runs, streaming   |
+| LangGraph-compatible API | 8001 | `$DEERFLOW_LANGGRAPH_URL`       | Agent threads, runs, streaming   |
 
 ## Environment Variables