LangGraph Integration

Introduction

LangGraph is a framework for building stateful, multi-agent applications with LLMs. The integration with Helicone AI Gateway is nearly identical to the LangChain integration, with the addition of agent-specific features.

This integration requires only two changes to your existing LangGraph code - updating the base URL and API key. See the LangChain AI Gateway docs for full feature details.

Quick Start

Follow the same setup as LangChain AI Gateway integration, then create your agent:

import { ChatOpenAI } from "@langchain/openai";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { MemorySaver } from "@langchain/langgraph";

const model = new ChatOpenAI({
    model: 'gpt-4.1-mini',
    apiKey: process.env.HELICONE_API_KEY,
    configuration: {
        baseURL: "https://ai-gateway.helicone.ai/v1",
    },
});

const agent = createReactAgent({
    llm: model,
    tools: yourTools,
    checkpointer: new MemorySaver(),
});

from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
from langgraph.checkpoint.memory import MemorySaver

model = ChatOpenAI(
    model='gpt-4.1-mini',
    api_key=os.getenv('HELICONE_API_KEY'),
    base_url="https://ai-gateway.helicone.ai/v1",
)

agent = create_react_agent(
    model,
    tools=your_tools,
    checkpointer=MemorySaver(),
)

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Migration Example

Before (Direct Provider)

import { ChatOpenAI } from "@langchain/openai";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const model = new ChatOpenAI({
    model: 'gpt-4o-mini',
    apiKey: process.env.OPENAI_API_KEY,
});

const agent = createReactAgent({
    llm: model,
    tools: myTools,
});

from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

model = ChatOpenAI(
    model='gpt-4o-mini',
    api_key=os.getenv('OPENAI_API_KEY'),
)

agent = create_react_agent(model, tools=my_tools)

After (Helicone AI Gateway)

import { ChatOpenAI } from "@langchain/openai";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const model = new ChatOpenAI({
    model: 'gpt-4.1-mini',                      // 100+ models supported
    apiKey: process.env.HELICONE_API_KEY,      // Your Helicone API key
    configuration: {
        baseURL: "https://ai-gateway.helicone.ai/v1"  // Add this!
    },
});

const agent = createReactAgent({
    llm: model,
    tools: myTools,
});

from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

model = ChatOpenAI(
    model='gpt-4.1-mini',                      # 100+ models supported
    api_key=os.getenv('HELICONE_API_KEY'),    # Your Helicone API key
    base_url="https://ai-gateway.helicone.ai/v1"  # Add this!
)

agent = create_react_agent(model, tools=my_tools)

Adding Custom Headers to Agent Invocations

You can add custom properties when calling your agent with invoke():

import { HumanMessage } from "@langchain/core/messages";
import { v4 as uuidv4 } from 'uuid';

const result = await agent.invoke(
    { messages: [new HumanMessage("What is the weather in San Francisco?")] },
    {
        options: {
            headers: {
                "Helicone-Session-Id": uuidv4(),
                "Helicone-Session-Path": "/weather/query",
                "Helicone-Property-Query-Type": "weather",
            },
        },
    }
);

from langchain_core.messages import HumanMessage
import uuid

result = agent.invoke(
    {"messages": [HumanMessage(content="What is the weather in San Francisco?")]},
    {
        "configurable": {
            "headers": {
                "Helicone-Session-Id": str(uuid.uuid4()),
                "Helicone-Session-Path": "/weather/query",
                "Helicone-Property-Query-Type": "weather",
            }
        }
    }
)

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AI Gateway Overview

Learn about Helicone’s AI Gateway features and capabilities

Provider Routing

Configure intelligent routing and automatic failover

Model Registry

Browse all available models and providers

LangChain Integration

Full AI Gateway feature documentation

Sessions

Track multi-turn conversations and agent workflows

Custom Properties

Add metadata to track and filter your requests

Getting Started

AI Gateway

Observability & Analytics

Prompt Management

Legacy Integrations

References

Introduction

Quick Start

Migration Example

Before (Direct Provider)

After (Helicone AI Gateway)

Adding Custom Headers to Agent Invocations

AI Gateway Overview

Provider Routing

Model Registry

LangChain Integration

Sessions

Custom Properties

​Introduction

​Quick Start

​Migration Example

​Before (Direct Provider)

​After (Helicone AI Gateway)

​Adding Custom Headers to Agent Invocations

​Related Documentation

AI Gateway Overview

Provider Routing

Model Registry

LangChain Integration

Sessions

Custom Properties

Introduction

Quick Start

Migration Example

Before (Direct Provider)

After (Helicone AI Gateway)

Adding Custom Headers to Agent Invocations

Related Documentation