from dotenv import load_dotenv

load_dotenv()

True

import os, asyncio, json

from langchain.chat_models import init_chat_model
from langchain.agents import create_agent
from langchain.messages import HumanMessage, AIMessage
from langchain.tools import tool, ToolRuntime
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.checkpoint.memory import InMemorySaver

from typing import Dict, Any
from tavily import TavilyClient
from pprint import pprint
from dataclasses import dataclass



DEEPSEEK_MODEL = "deepseek-chat"
DEEPSEEK_BASE_URL = "https://api.deepseek.com"

def deepseek_model(model: str = DEEPSEEK_MODEL, max_tokens=1000, **kwargs):
    return init_chat_model(
        model=model,
        # DeepSeek uses LangChain's OpenAI-compatible transport.
        model_provider="openai",
        api_key=os.environ["DEEPSEEK_API_KEY"],
        base_url=DEEPSEEK_BASE_URL,
        max_tokens=max_tokens,
        **kwargs,
    )

@dataclass
class ColourContext:
    favourite_colour: str = "blue"
    least_favourite_colour: str = "yellow"

agent = create_agent(
    model=deepseek_model(),
    context_schema=ColourContext  # the agent can receive a context_schema arg with the format of ColourContext
)

#不过要注意：仅仅传入 context_schema 和 context=ColourContext()，不一定代表模型会自动知道怎么使用这个 context。
#通常还需要在 system prompt 或 tools/middleware 里明确告诉 agent 如何读取 context。

response = agent.invoke(
    {"messages": [HumanMessage(content="What is my favourite colour?")]},
    context=ColourContext(),
    system_prompt="Use the runtime context to answer questions about the user's preferences." # to tell model to use the contxt
)

print(response['messages'][-1].content)

I don't actually know what your favourite colour is, since you haven't told me yet. But if you'd like to share it, I'd be happy to remember it for this conversation!

@tool
def get_favourite_colour(runtime: ToolRuntime) -> str:
    """Get the favourite colour of the user"""
    return runtime.context.favourite_colour

@tool
def get_least_favourite_colour(runtime: ToolRuntime) -> str:
    """Get the least favourite colour of the user"""
    return runtime.context.least_favourite_colour

agent = create_agent(
    model=deepseek_model(),
    tools=[get_favourite_colour, get_least_favourite_colour],
    context_schema=ColourContext
)

response = agent.invoke(
    {"messages": [HumanMessage(content="What is my favourite colour?")]},
    context=ColourContext()
)

/path/to/.venv/lib/python3.13/site-packages/pydantic/main.py:464: UserWarning: Pydantic serializer warnings:
  PydanticSerializationUnexpectedValue(Expected `none` - serialized value may not be as expected [field_name='context', input_value=ColourContext(favourite_c...vourite_colour='yellow'), input_type=ColourContext])
  return self.__pydantic_serializer__.to_python(

print(response['messages'][-1].content)

Your favourite colour is **blue**!

response = agent.invoke(
    {"messages": [HumanMessage(content="What is my favourite colour?")]},
    context=ColourContext(favourite_colour="green")
)

/path/to/.venv/lib/python3.13/site-packages/pydantic/main.py:464: UserWarning: Pydantic serializer warnings:
  PydanticSerializationUnexpectedValue(Expected `none` - serialized value may not be as expected [field_name='context', input_value=ColourContext(favourite_c...vourite_colour='yellow'), input_type=ColourContext])
  return self.__pydantic_serializer__.to_python(

print(response['messages'][-1].content)

Your favourite colour is **green**!

Accessing Context¶