https://github.com/hmshb/langgraph-ai-agent-claude

This repo contains an AI Agent using LangGraph, LangSmith, Claude and Tavily Search Tool
https://github.com/hmshb/langgraph-ai-agent-claude

ai ai-agents api automation bots chatbot chatbots-framework claude-ai cli conversational-ai generative-ai langchain langchain-python langgraph langgraph-python machine-learning nlp nlp-machine-learning

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This repo contains an AI Agent using LangGraph, LangSmith, Claude and Tavily Search Tool

• Host: GitHub
• URL: https://github.com/hmshb/langgraph-ai-agent-claude
• Owner: hmshb
• License: mit
• Created: 2024-12-16T08:13:36.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2025-01-30T06:41:16.000Z (4 months ago)
• Last Synced: 2025-02-09T20:33:48.519Z (3 months ago)
• Topics: ai, ai-agents, api, automation, bots, chatbot, chatbots-framework, claude-ai, cli, conversational-ai, generative-ai, langchain, langchain-python, langgraph, langgraph-python, machine-learning, nlp, nlp-machine-learning
• Language: Python
• Homepage:
• Size: 2.09 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# AI Agent with LangGraph, LangSmith, Claude, and Tavily

This repository demonstrates how to create an AI Agent using [LangGraph](https://langchain-ai.github.io/langgraph/) with [LangSmith](https://www.langchain.com/langsmith), [Claude](https://www.anthropic.com/claude) and [Tavily](https://tavily.com/) to build AI-powered applications using multimodal capabilities. It's designed as a starting point for developers looking to explore and experiment with LangGraph AI Agents.

## 🚀 Features

- **Beginner-friendly**: Simple setup to get started quickly.

- **LLM Integration:** Powered by Claude for advanced reasoning and natural language capabilities.

- **Search Integration:** Employs Tavily as a tool, allowing the agent to query the web, retrieve information, and enhance its knowledge of current events or data outside the training corpus.

- **Extensible:** Easily adapt the agent to incorporate new tools, models, or additional data sources.

---

[![Demo](https://img.shields.io/badge/Demo-Live-blue?style=for-the-badge)](intro.gif)

![intro.gif](intro.gif)

---

## 🛠️ Setup Instructions

Follow these steps to set up and run the project on your local machine:

### 1. Clone the Repository

```bash

git clone https://github.com/hmshb/langgraph-ai-agent-claude.git

cd langgraph-ai-agent-claude

```

### 2. Create a Virtual Environment

```bash

python -m venv venv

source venv/bin/activate  # For Linux/Mac

.\venv\Scripts\activate # For Windows

```

### 3. Install LangGraph CLI

```bash

pip install -U "langgraph-cli[inmem]"

```

![img.png](img.png)

### 4. Install Other Dependencies

```bash

pip install -e .

```

![img_1.png](img_1.png)

### 5. Generate LangSmith API Key

1. Visit [LangSmith](https://smith.langchain.com/settings).

2. Create an API key for accessing LangSmith logs.

3. Copy the generated API key.

![img_6.png](img_6.png)

### 6. Generate Anthropic Claude API Key

1. Visit [Anthropic](https://console.anthropic.com/settings/keys).

2. Create an API key for accessing Claude.

3. Copy the generated API key.

![img_2.png](img_2.png)

### 7. Generate Tavily API Key

1. Visit [Tavily](https://app.tavily.com/home).

2. Create an API key for accessing tavily.

3. Copy the generated API key.

![img_3.png](img_3.png)

### 8. Update ```.env``` File

 - Add the following line to the .env file for actual keys

    ```

    LANGCHAIN_TRACING_V2=true

    LANGCHAIN_API_KEY=lsv2_pt_*************************

    TAVILY_API_KEY=tvly-*******************************

    ANTHROPIC_API_KEY=sk-ant-**************************

    ```

   

### 9. Run the project

```bash

langgraph dev

```

![img_4.png](img_4.png)

---

### 10. LangGraph of the AI Agent

![img_5.png](img_5.png)

---

## 📂 Project Structure

```

langchain-ai-agent-google-gemini/

├── .env                 # API key configuration file

├── agent                # Actual AI Agent lives here

├── langgraph.json       # Configuration file for LangGraph

├── pyproject.toml       # configuration file to defines build system requirements and metadata for Python projects.

├── README.md            # Documentation file

├── venv/                # Virtual environment

```

---

## ⭐ Acknowledgments

Special thanks to:

- **[LangGraph](https://langchain-ai.github.io/langgraph/)** for providing a robust framework for building AI Agents.

- **[LangSmith](https://www.langchain.com/langsmith)** for providing a platform for monitoring, debugging, and evaluating applications built with LangChain

- **[Claude](https://www.anthropic.com/claude)** for their powerful multimodal AI capabilities.

- **[Tavily](https://tavily.com/)** for allowing the agent to query the web.

- **[LangGraph Example](https://langchain-ai.github.io/langgraph/tutorials/introduction/)** official example, inspiration behind my example

---

## 📜 License

This project is open-source and licensed under the [MIT License](LICENSE).

---

## 📢 Get Involved!

If you find this repository helpful, please consider:

- ⭐ **Starring the Repository** to show your support.

- 📤 **Forking the Repository** to explore further and make your own customizations.

- 💬 **Sharing Your Feedback** by opening issues or discussions.

---

## 📝 Notes

 **LangGraph**, **LangSmith**, **Claude** and **Tavily** is currently in limited or preview release (depending on your region and timing), and integration details may change as the service evolves. 

 

Always refer to official documentation for the most up-to-date guidance.

### Let's build amazing AI-powered applications together!