langchain-vercel-ai-sdk-adapter 0.1.0

Adapter to integrate LangChain with Vercel AI SDK SSE streaming

LangChain AI SDK Adapter

Adapter to integrate Python LangChain backends with Vercel AI SDK frontend clients.

Features

• to_base_messages() - Convert AI SDK UIMessage format to LangChain messages
• to_ui_message_stream() - Convert LangChain stream to AI SDK SSE format
• create_ui_message_stream_response() - Create a Starlette/FastAPI StreamingResponse

Installation

pip install langchain-ai-sdk-adapter

With FastAPI support:

pip install langchain-ai-sdk-adapter[fastapi]

Usage

Basic Integration with FastAPI

from fastapi import FastAPI
from fastapi.responses import StreamingResponse
from langchain_anthropic import ChatAnthropic
from langchain_ai_sdk_adapter import to_base_messages, to_ui_message_stream, create_ui_message_stream_response

app = FastAPI()

@app.post("/chat")
async def chat(request: Request):
    model = ChatAnthropic(model="claude-3-5-sonnet-20241022")
    langchain_messages = await to_base_messages(await request.json())
    stream = await model.astream(langchain_messages)
    return create_ui_message_stream_response(to_ui_message_stream(stream))

Integration with LangGraph

from langgraph.graph import StateGraph
from langchain_ai_sdk_adapter import to_base_messages, to_ui_message_stream, create_ui_message_stream_response

@app.post("/chat")
async def chat(request: Request):
    langchain_messages = await to_base_messages(await request.json())
    graph = create_graph()
    stream = graph.astream_events(
        {"messages": langchain_messages},
        version="v2"
    )
    return create_ui_message_stream_response(to_ui_message_stream(stream))

SSE Format

The adapter produces SSE in AI SDK useChat format:

data: {"id":"msg_abc123","role":"assistant","content":"Hello"}\n\n
data: {"id":"msg_abc123","role":"assistant","content":" world"}\n\n
...
data: [DONE]\n\n

License

MIT