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--- |
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title: LangGraph Agentic Chatbot |
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app_file: agent/app.py |
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sdk: gradio |
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sdk_version: 5.4.0 |
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--- |
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# LangGraph Agentic Chatbot |
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This repository contains a LangGraph-based chatbot that utilizes Gradio for interface rendering and integrates OpenAI's language model capabilities and custom tools for enhanced functionality. This project allowed me to learn and explore the capabilities of LangGraph and Agnetic workflows. |
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## Tech Stack |
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- **Frontend:** |
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- **[Gradio](https://gradio.app/docs)** |
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- **Backend:** |
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- **[LangGraph](https://langgraph.dev/)** |
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- **[LangChain](https://python.langchain.com/en/latest/)** |
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- **[Python](https://www.python.org/)** |
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- **APIs:** |
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- **[OpenAI API](https://platform.openai.com/docs)** |
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- **[Tavily Search API](https://tavilyapi.com/docs)** |
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- **Version Control:** |
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- **[Git](https://git-scm.com/doc)** |
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## Setup |
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To run this project locally, follow these steps: |
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1. **Clone the repository:** |
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```bash |
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git clone https://github.com/your-repo/langgraph-agentic-chatbot.git |
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``` |
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2. **Navigate to the project directory:** |
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```bash |
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cd langgraph-agentic-chatbot |
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``` |
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3. **Install dependencies:** |
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```bash |
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pip install -r requirements.txt |
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``` |
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4. **Set up environment variables:** |
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Create a `.env` file in the root directory and add your OpenAI API key and LangChain API key to trace the chatbot's interactions. |
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``` |
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LANGCHAIN_TRACING_V2=true |
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LANGCHAIN_ENDPOINT="https://api.example.langchain.com" |
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LANGCHAIN_API_KEY="your_langchain_api_key" |
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LANGCHAIN_PROJECT="your_langchain_project" |
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``` |
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``` |
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OPENAI_API_KEY="your_openai_api_key" |
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TAVILY_API_KEY="your_tavily_api_key" |
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``` |
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5. **Run the Gradio application:** |
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```bash |
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gradio agent/main.py |
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``` |
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6. **Access the chatbot:** |
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Open `http://localhost:7860` in your web browser to interact with the chatbot. |
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