File size: 1,752 Bytes
252375c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 |
# LangGraph Agentic Chatbot
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.
## Tech Stack
- **Frontend:**
- **[Gradio](https://gradio.app/docs)**
- **Backend:**
- **[LangGraph](https://langgraph.dev/)**
- **[LangChain](https://python.langchain.com/en/latest/)**
- **[Python](https://www.python.org/)**
- **APIs:**
- **[OpenAI API](https://platform.openai.com/docs)**
- **[Tavily Search API](https://tavilyapi.com/docs)**
- **Version Control:**
- **[Git](https://git-scm.com/doc)**
## Setup
To run this project locally, follow these steps:
1. **Clone the repository:**
```bash
git clone https://github.com/your-repo/langgraph-agentic-chatbot.git
```
2. **Navigate to the project directory:**
```bash
cd langgraph-agentic-chatbot
```
3. **Install dependencies:**
```bash
pip install -r requirements.txt
```
4. **Set up environment variables:**
Create a `.env` file in the root directory and add your OpenAI API key and LangChain API key to trace the chatbot's interactions.
```
LANGCHAIN_TRACING_V2=true
LANGCHAIN_ENDPOINT="https://api.example.langchain.com"
LANGCHAIN_API_KEY="your_langchain_api_key"
LANGCHAIN_PROJECT="your_langchain_project"
```
```
OPENAI_API_KEY="your_openai_api_key"
TAVILY_API_KEY="your_tavily_api_key"
```
5. **Run the Gradio application:**
```bash
gradio agent/main.py
```
6. **Access the chatbot:**
Open `http://localhost:7860` in your web browser to interact with the chatbot.
|