| Name | twitter-langchain JSON |
| Version |
0.0.11
JSON |
| download |
| home_page | None |
| Summary | Twitter Langchain Toolkit |
| upload_time | 2025-01-24 23:00:04 |
| maintainer | None |
| docs_url | None |
| author | John Peterson |
| requires_python | <4.0,>=3.10 |
| license | Apache-2.0 |
| keywords |
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| VCS |
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| bugtrack_url |
|
| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# 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](https://developer.x.com/en/docs/x-api). The toolkit provides a wrapper around the Twitter (X) API, allowing agents to perform social operations like posting text.
## Setup
### Prerequisites
- [OpenAI API Key](https://platform.openai.com/api-keys)
- [Twitter (X) App Developer Keys](https://developer.x.com/en/portal/dashboard)
- Python 3.10 or higher
### Installation
```bash
pip install twitter-langchain
```
### Environment Setup
Set the following environment variables:
```bash
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:
```python
tools = twitter_toolkit.get_tools()
for tool in tools:
print(tool.name)
```
### 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
3. **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!
```
## Examples
Check out [twitter-langchain/examples](../examples) for inspiration and help getting started!
- [Chatbot Python](../examples/chatbot-python/README.md): Simple example of a Python Chatbot that can interact on Twitter (X), using OpenAI.
## Contributing
See [CONTRIBUTING.md](../../CONTRIBUTING.md) for detailed setup instructions and contribution guidelines.
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"description": "# Twitter (X) Langchain Toolkit\nTwitter integration with Langchain to enable agentic workflows using the core primitives defined in `cdp-agentkit-core`.\n\nThis toolkit contains tools that enable an LLM agent to interact with [Twitter](https://developer.x.com/en/docs/x-api). The toolkit provides a wrapper around the Twitter (X) API, allowing agents to perform social operations like posting text.\n\n## Setup\n\n### Prerequisites\n\n- [OpenAI API Key](https://platform.openai.com/api-keys)\n- [Twitter (X) App Developer Keys](https://developer.x.com/en/portal/dashboard)\n- Python 3.10 or higher\n\n### Installation\n\n```bash\npip install twitter-langchain\n```\n\n### Environment Setup\n\nSet the following environment variables:\n\n```bash\nexport OPENAI_API_KEY=<your-openai-api-key>\nexport TWITTER_API_KEY=<your-api-key>\nexport TWITTER_API_SECRET=<your-api-secret>\nexport TWITTER_ACCESS_TOKEN=<your-access-token>\nexport TWITTER_ACCESS_TOKEN_SECRET=<your-access-token-secret>\nexport TWITTER_BEARER_TOKEN=<your-bearer-token>\n```\n\n## Usage\n\n### Basic Setup\n\n```python\nfrom twitter_langchain import (\n TwitterApiWrapper,\n TwitterToolkit\n)\n\n# Initialize TwitterApiwrapper\ntwitter_api_wrapper = TwitterApiWrapper()\n\n# Create TwitterToolkit from the api wrapper\ntwitter_toolkit = TwitterToolkit.from_twitter_api_wrapper(twitter_api_wrapper)\n```\n\nView available tools:\n```python\ntools = twitter_toolkit.get_tools()\nfor tool in tools:\n print(tool.name)\n```\n\n### Available Tools\n\nThe toolkit provides the following tools:\n\n1. **account_details** - Get the authenticated account details\n2. **account_mentions** - Get mentions for the account\n3. **post_tweet** - Post a tweet to the account\n3. **post_tweet_reply** - Post a reply to a tweet on Twitter\n\n### Using with an Agent\n\n```python\nimport uuid\n\nfrom langchain_openai import ChatOpenAI\nfrom langchain_core.messages import HumanMessage\nfrom langgraph.prebuilt import create_react_agent\n\nllm = ChatOpenAI(model=\"gpt-4o-mini\")\n\n# Create agent\nagent_executor = create_react_agent(llm, tools)\n\n# Example - post tweet\nevents = agent_executor.stream(\n {\n \"messages\": [\n HumanMessage(content=f\"Please post 'hello, world! {uuid.uuid4().hex}' to twitter\"),\n ],\n },\n stream_mode=\"values\",\n)\n\nfor event in events:\n event[\"messages\"][-1].pretty_print()\n```\n\nExpected output:\n```\n================================ Human Message =================================\nPlease post 'hello, world! c4b8e3744c2e4345be9e0622b4c0a8aa' to twitter\n================================== Ai Message ==================================\nTool Calls:\n post_tweet (call_xVx4BMCSlCmCcbEQG1yyebbq)\n Call ID: call_xVx4BMCSlCmCcbEQG1yyebbq\n Args:\n tweet: hello, world! c4b8e3744c2e4345be9e0622b4c0a8aa\n================================= Tool Message =================================\nName: post_tweet\nSuccessfully posted!\n================================== Ai Message ==================================\nThe message \"hello, world! c4b8e3744c2e4345be9e0622b4c0a8aa\" has been successfully posted to Twitter!\n```\n\n## Examples\n\nCheck out [twitter-langchain/examples](../examples) for inspiration and help getting started!\n- [Chatbot Python](../examples/chatbot-python/README.md): Simple example of a Python Chatbot that can interact on Twitter (X), using OpenAI.\n\n## Contributing\n\nSee [CONTRIBUTING.md](../../CONTRIBUTING.md) for detailed setup instructions and contribution guidelines.\n\n",
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