📝 docs(readme): update documentation for LangGraph v0.6.6 integration and model configuration

- Clarify seamless integration with LangGraph Studio and update README badges
- Add LangGraph v0.6.6 features highlighting context-driven configuration API changes
- Provide detailed model configuration methods: runtime context, env vars, Studio assistant
- Expand API key setup instructions for OpenAI, Anthropic, Qwen, and OpenAI-compatible providers
- Introduce sample LangSmith execution traces with DeepWiki and web search examples
- Update MCP server examples to include Context7 documentation tools with usage tips
- Improve Chinese readme with corresponding updates and new configuration guidance
- Refine project descriptions and badge links for both English and Chinese docs

Author: webup

CLAUDE.md

@@ -82,7 +82,7 @@ make dev_ui                 # Start LangGraph development server with UI
 
 ## LangGraph Studio Integration
 
-This project is designed for LangGraph Studio. The `langgraph.json` config file defines:
+This project works seamlessly with LangGraph Studio. The `langgraph.json` config file defines:
 - Graph entry point: `./src/react_agent/graph.py:graph`
 - Environment file: `.env`
 - Dependencies: current directory (`.`)

README.md

@@ -1,14 +1,14 @@
 # LangGraph ReAct Agent Template
 
 [![Version](https://img.shields.io/badge/version-v0.1.0-blue.svg)](https://github.com/webup/langgraph-up-react)
+[![LangGraph](https://img.shields.io/badge/LangGraph-v0.6.6-blue.svg)](https://github.com/langchain-ai/langgraph)
 [![Build](https://github.com/webup/langgraph-up-react/actions/workflows/unit-tests.yml/badge.svg)](https://github.com/webup/langgraph-up-react/actions/workflows/unit-tests.yml)
 [![License](https://img.shields.io/badge/license-MIT-green.svg)](https://opensource.org/licenses/MIT)
-[![README EN](https://img.shields.io/badge/README-English-blue.svg)](./README.md)
 [![README CN](https://img.shields.io/badge/README-中文-red.svg)](./README_CN.md)
 [![DeepWiki](https://img.shields.io/badge/Powered_by-DeepWiki-blue.svg)](https://deepwiki.com/webup/langgraph-up-react)
 [![Twitter](https://img.shields.io/twitter/follow/zhanghaili0610?style=social)](https://twitter.com/zhanghaili0610)
 
-This template showcases a [ReAct agent](https://arxiv.org/abs/2210.03629) implemented using [LangGraph](https://github.com/langchain-ai/langgraph), designed for [LangGraph Studio](https://github.com/langchain-ai/langgraph-studio). ReAct agents are uncomplicated, prototypical agents that can be flexibly extended to many tools.
+This template showcases a [ReAct agent](https://arxiv.org/abs/2210.03629) implemented using [LangGraph](https://github.com/langchain-ai/langgraph), works seamlessly with [LangGraph Studio](https://docs.langchain.com/langgraph-platform/quick-start-studio#use-langgraph-studio). ReAct agents are uncomplicated, prototypical agents that can be flexibly extended to many tools.
 
 ![Graph view in LangGraph studio UI](./static/studio_ui.png)
 
@@ -35,6 +35,15 @@ The core logic, defined in `src/react_agent/graph.py`, demonstrates a flexible R
 - **Caching**: Optimized performance with client and tools caching
 - **Configurable**: Enable via environment variables or context parameters
 
+### LangGraph v0.6.6 Features
+
+> [!NOTE]
+> **New in LangGraph v0.6**: [LangGraph Context](https://docs.langchain.com/oss/python/context#context-overview) replaces the traditional `config['configurable']` pattern. Runtime context is now passed to the `context` argument of `invoke/stream`, providing a cleaner and more intuitive way to configure your agents.
+
+- **Context-Driven Configuration**: Runtime context passed via `context` parameter instead of `config['configurable']`
+- **Simplified API**: Cleaner interface for passing runtime configuration to your agents
+- **Backward Compatibility**: Gradual migration path from the old configuration pattern
+
 ### Comprehensive Testing
 - **70+ Test Cases**: Unit, integration, and end-to-end testing
 - **MCP Integration Coverage**: Full testing of DeepWiki tool loading and execution
@@ -53,6 +62,13 @@ The ReAct agent:
 
 The agent comes with web search capabilities and optional DeepWiki MCP documentation tools, but can be easily extended with custom tools to suit various use cases.
 
+### Sample Execution Traces
+
+See these LangSmith traces to understand how the agent works in practice:
+
+- **[DeepWiki Documentation Query](https://smith.langchain.com/public/d0594549-7363-46a7-b1a2-d85b55aaa2bd/r)** - Shows agent using DeepWiki MCP tools to query GitHub repository documentation
+- **[Web Search Query](https://smith.langchain.com/public/6ce92fd2-c0e4-409b-9ce2-02499ae16800/r)** - Demonstrates Tavily web search integration and reasoning loop
+
 ## Getting Started
 
 ### Setup with uv (Recommended)
@@ -102,61 +118,41 @@ ENABLE_DEEPWIKI=true
 
 The primary [search tool](./src/common/tools.py) uses [Tavily](https://tavily.com/). Create an API key [here](https://app.tavily.com/sign-in).
 
-## Model Setup
-
-The default model configuration is:
+## Model Configuration
 
-```yaml
-model: qwen:qwen-turbo
-```
+The template uses `qwen:qwen-turbo` as the default model, defined in [`src/common/context.py`](./src/common/context.py). You can configure different models in three ways:
 
-### OpenAI
+1. **Runtime Context** (recommended for programmatic usage)
+2. **Environment Variables** 
+3. **LangGraph Studio Assistant Configuration**
 
-To use OpenAI's chat models:
+### API Key Setup by Provider
 
-1. Sign up for an [OpenAI API key](https://platform.openai.com/signup)
-2. Add it to your `.env` file:
+#### OpenAI
 ```bash
-OPENAI_API_KEY=your-api-key
+OPENAI_API_KEY=your-openai-api-key
 ```
+Get your API key: [OpenAI Platform](https://platform.openai.com/signup)
 
-### Anthropic
-
-To use Anthropic's chat models:
-
-1. Sign up for an [Anthropic API key](https://console.anthropic.com/)
-2. Add it to your `.env` file:
+#### Anthropic  
 ```bash
-ANTHROPIC_API_KEY=your-api-key
+ANTHROPIC_API_KEY=your-anthropic-api-key
 ```
-3. Update the model in LangGraph Studio to `anthropic:claude-3-5-sonnet-20240620`
-
-### Qwen Models (Default)
+Get your API key: [Anthropic Console](https://console.anthropic.com/)
 
-For Alibaba's Qwen models (Qwen3, QwQ-32B, etc.):
-
-1. Sign up for a [DashScope API key](https://dashscope.console.aliyun.com/)
-2. Add it to your `.env` file:
+#### Qwen Models (Default)
 ```bash
-DASHSCOPE_API_KEY=your-api-key
+DASHSCOPE_API_KEY=your-dashscope-api-key
 REGION=international  # or 'prc' for China mainland
 ```
-3. Update the model in LangGraph Studio to `qwen:qwen3-32b` or `qwen:qwen-plus`
-
-### OpenAI-Compatible Providers
+Get your API key: [DashScope Console](https://dashscope.console.aliyun.com/)
 
-For any OpenAI-compatible API (SiliconFlow, Together AI, Groq, etc.):
-
-1. Get your API key from the provider
-2. Add to your `.env` file:
+#### OpenAI-Compatible Providers
 ```bash
-# Example for custom OpenAI-compatible provider
 OPENAI_API_KEY=your-provider-api-key
 OPENAI_API_BASE=https://your-provider-api-base-url/v1
 ```
-3. Update the model in LangGraph Studio to `openai:provider-model-name`
-
-This flexible architecture allows you to use any OpenAI-compatible API by simply providing the API key and base URL.
+Supports SiliconFlow, Together AI, Groq, and other OpenAI-compatible APIs.
 
 ## How to Customize
 
@@ -181,50 +177,78 @@ MCP_SERVERS = {
         "url": "https://mcp.deepwiki.com/mcp",
         "transport": "streamable_http",
     },
-    "your_mcp_server": {  # Add your MCP server
-        "url": "https://your-mcp-server.com/mcp",
-        "transport": "streamable_http",
-    }
+    # Example: Context7 for library documentation
+    "context7": {
+        "url": "https://mcp.context7.com/sse",
+        "transport": "sse",
+    },
 }
 ```
 
 2. **Add Server Function**:
 ```python
-async def get_your_mcp_tools() -> List[Callable[..., Any]]:
-    """Get tools from your MCP server."""
-    return await get_mcp_tools("your_mcp_server")
+async def get_context7_tools() -> List[Callable[..., Any]]:
+    """Get Context7 documentation tools."""
+    return await get_mcp_tools("context7")
 ```
 
-3. **Enable in Context** - Add context flag and load tools in `get_tools()` function.
+3. **Enable in Context** - Add context flag and load tools in `get_tools()` function:
+```python
+# In src/common/tools.py
+if context.enable_context7:
+    tools.extend(await get_context7_tools())
+```
+
+> [!TIP]
+> **Context7 Example**: The MCP configuration already includes a commented Context7 server setup. Context7 provides up-to-date library documentation and examples - simply uncomment the configuration and add the context flag to enable it.
+
+### Model Configuration Methods
+
+#### 1. Runtime Context (Recommended)
+
+Use the new LangGraph v0.6.6 context parameter to configure models at runtime:
 
-### Configure Models
-Our key extended method `load_chat_model` in [`src/common/utils.py`](./src/common/utils.py) uses LangChain's [`init_chat_model`](https://python.langchain.com/api_reference/langchain/chat_models/langchain.chat_models.base.init_chat_model.html#init-chat-model) as the underlying utility.
+```python
+from common.context import Context
+from react_agent import graph
+
+# Configure model via context
+result = await graph.ainvoke(
+    {"messages": [("user", "Your question here")]},
+    context=Context(model="openai:gpt-4o-mini")
+)
+```
+
+#### 2. Environment Variables
+
+Set the `MODEL` environment variable in your `.env` file:
+
+```bash
+MODEL=anthropic:claude-3.5-haiku
+```
+
+#### 3. LangGraph Studio Assistant Configuration
+
+In LangGraph Studio, configure models through [Assistant management](https://docs.langchain.com/langgraph-platform/configuration-cloud#manage-assistants). Create or update assistants with different model configurations for easy switching between setups.
+
+### Supported Model Formats
 
 **Model String Format**: `provider:model-name` (follows LangChain's naming convention)
 
-**Examples**:
 ```python
 # OpenAI models
-model = "openai:gpt-4o-mini"
-model = "openai:gpt-4o"
+"openai:gpt-4o-mini"
+"openai:gpt-4o"
 
 # Qwen models (with regional support)
-model = "qwen:qwen-turbo"    # Default model
-model = "qwen:qwen-plus"     # Balanced performance
-model = "qwen:qwq-32b-preview"  # Reasoning model
-model = "qwen:qvq-72b-preview"  # Multimodal reasoning
+"qwen:qwen-turbo"          # Default model
+"qwen:qwen-plus"           # Balanced performance
+"qwen:qwq-32b-preview"     # Reasoning model
+"qwen:qvq-72b-preview"     # Multimodal reasoning
 
 # Anthropic models
-model = "anthropic:claude-4-sonnet"
-model = "anthropic:claude-3.5-haiku"
-```
-
-**Configuration**:
-```bash
-# Set via environment variable
-MODEL=qwen:qwen-turbo
-
-# Or in LangGraph Studio configurable settings
+"anthropic:claude-4-sonnet"
+"anthropic:claude-3.5-haiku"
 ```
 
 ### Customize Prompts