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Twitter (X) Langchain Toolkit

Twitter integration with Langchain to enable agentic workflows using the core primitives defined in cdp-agentkit-core.

This toolkit contains tools that enable an LLM agent to interact with Twitter. The toolkit provides a wrapper around the Twitter (X) API, allowing agents to perform social operations like posting text.

Setup

Prerequisites

OpenAI

Twitter (X)

Python

  • Python 3.10 or higher

Typescript

  • Node.js 18 or higher

Installation

Python

pip install twitter-langchain

Typescript

npm install @coinbase/twitter-langchain

Environment Setup

Set the following environment variables:

export OPENAI_API_KEY=<your-openai-api-key>
export TWITTER_API_KEY=<your-api-key>
export TWITTER_API_SECRET=<your-api-secret>
export TWITTER_ACCESS_TOKEN=<your-access-token>
export TWITTER_ACCESS_TOKEN_SECRET=<your-access-token-secret>
export TWITTER_BEARER_TOKEN=<your-bearer-token>

Usage

Basic Setup

Python

from twitter_langchain import (
    TwitterApiWrapper,
    TwitterToolkit
)

# Initialize TwitterApiwrapper
twitter_api_wrapper = TwitterApiWrapper()

# Create TwitterToolkit from the api wrapper
twitter_toolkit = TwitterToolkit.from_twitter_api_wrapper(twitter_api_wrapper)

View available tools:

tools = twitter_toolkit.get_tools()
for tool in tools:
    print(tool.name)

Typescript

import { TwitterAgentkit } from "@coinbase/cdp-agentkit-core";
import { TwitterToolkit } from "@coinbase/twitter-langchain";

// Initialize Twitter AgentKit
const agentkit = new TwitterAgentkit();

// Create toolkit
const toolkit = new TwitterToolkit(agentkit);

// Get available tools
const tools = toolkit.getTools();

Available Tools

The toolkit provides the following tools:

  1. account_details - Get the authenticated account details
  2. account_mentions - Get mentions for the account
  3. post_tweet - Post a tweet to the account
  4. post_tweet_reply - Post a reply to a tweet on Twitter

Using with an Agent

Python

import uuid

from langchain_openai import ChatOpenAI
from langchain_core.messages import HumanMessage
from langgraph.prebuilt import create_react_agent

llm = ChatOpenAI(model="gpt-4o-mini")

# Create agent
agent_executor = create_react_agent(llm, tools)

# Example - post tweet
events = agent_executor.stream(
    {
        "messages": [
            HumanMessage(content=f"Please post 'hello, world! {uuid.uuid4().hex}' to twitter"),
        ],
    },
    stream_mode="values",
)

for event in events:
    event["messages"][-1].pretty_print()

Expected output:

================================ Human Message =================================
Please post 'hello, world! c4b8e3744c2e4345be9e0622b4c0a8aa' to twitter
================================== Ai Message ==================================
Tool Calls:
    post_tweet (call_xVx4BMCSlCmCcbEQG1yyebbq)
    Call ID: call_xVx4BMCSlCmCcbEQG1yyebbq
    Args:
        tweet: hello, world! c4b8e3744c2e4345be9e0622b4c0a8aa
================================= Tool Message =================================
Name: post_tweet
Successfully posted!
================================== Ai Message ==================================
The message "hello, world! c4b8e3744c2e4345be9e0622b4c0a8aa" has been successfully posted to Twitter!

Typescript

Additional Installations

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

// Initialize LLM
const model = new ChatOpenAI({
  model: "gpt-4o-mini",
});

// Create agent executor
const agent = createReactAgent({
  llm: model,
  tools,
});

// Example usage
const result = await agent.invoke({
  messages: [new HumanMessage("please post 'hello, world!' to twitter")],
});

console.log(result.messages[result.messages.length - 1].content);

Examples

Check out twitter-langchain/examples for inspiration and help getting started!

  • Chatbot Python: Simple example of a Python Chatbot that can interact on Twitter (X), using OpenAI.
  • Chatbot Typescript: Simple example of a Node.js Chatbot that can interact on Twitter (X), using OpenAI.

Contributing

See CONTRIBUTING.md for detailed setup instructions and contribution guidelines.