langgraph

LangGraph Framework

This module provides integration between LangGraph and the Vercel AI Data Stream protocol, allowing you to stream LangGraph agent responses to clients.

Installation

To use the LangGraph framework, install it with pip:

pip install ai-datastream[langgraph]

Usage

Here's a basic example of how to use the LangGraph framework:

from langgraph.graph import StateGraph
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
from ai_datastream.agent.langgraph import LanggraphStreamer
from ai_datastream.messages import ChatMessage, MessageRole

# Initialize your LangGraph agent
model = ChatOpenAI(model="gpt-4")
tools = [...]  # your tools
prompt = "You are a helpful assistant."
agent = create_react_agent(model, tools)

# Create a streamer for the agent
streamer = LanggraphStreamer(agent)

# Create a message to send to the agent
message = ChatMessage(
    role=MessageRole.USER,
    content="What's the weather like in San Francisco?"
)

# Stream the response
for chunk in streamer.stream(prompt, [message]):
    print(chunk)  # Each chunk will be in the Vercel AI Data Stream protocol format

Features

• Supports both synchronous and asynchronous streaming
• Handles tool calls and their results
• Converts LangGraph messages to the Vercel AI Data Stream protocol format
• Maintains conversation state and message history

Requirements

• Python 3.9+
• LangGraph 0.3.0 or higher
• LangChain (for the agent implementation)

Documentation

• LangGraph Documentation
• Vercel AI Data Stream Protocol
• LangChain Documentation