langgraph-api

import os from langchain_openai import ChatOpenAI from langchain.agents import AgentExecutor, create_react_agent from langchain_core.prompts import PromptTemplate from langchain_core.tools import tool from langgraph_api import create_langgraph_api from fastapi import FastAPI # Set API key for OpenAI, or any other LLM provider os.environ["OPENAI_API_KEY"] = os.environ.get("OPENAI_API_KEY", "sk-mock-key-for-test") # 1. Define a tool @tool def multiply(a: int, b: int) -> int: """Multiply two integers together.""" return a * b tools = [multiply] # 2. Define an LLM llm = ChatOpenAI(temperature=0) # 3. Define a prompt template prompt = PromptTemplate.from_template(""" You are a helpful assistant. Answer the following questions as best you can. You have access to the following tools: {tools} {agent_scratchpad} """) # 4. Create a React agent agent = create_react_agent(llm, tools, prompt) # 5. Create an AgentExecutor (LangGraph runnable) agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True) # 6. Create the LangGraph API app app = FastAPI(title="My Agent API") langgraph_api_app = create_langgraph_api(app, agent_executor, path="/agent") # To run this application: # Save the code as 'main.py' (or any other name) # Execute from your terminal: uvicorn main:app --port 8000 --reload # Then access via: http://localhost:8000/agent/invoke or /agent/stream_log print("LangGraph API application created. To run, use: uvicorn your_module_name:app --port 8000") print("Example: uvicorn main:app --port 8000 --reload")