Tavily Agent Example

👋 Welcome to the Tavily Chat Web Agent Repository!

This repository provides a simple yet powerful example of building a conversational agent with real-time web access, leveraging Tavily's search, extract, and crawl capabilities.

Designed for ease of customization, you can extend this core implementation to:

• Integrate proprietary data
• Modify the chatbot architecture
• Modify LLMs

Features

• 🔍 Intelligent question routing between base knowledge and tavily search, extract, and crawl.
• 🧠 Conversational memory with LangGraph
• 🚀 FastAPI backend with async support
• 🔄 Streaming of Agentic Substeps
• 💬 Markdown support in chat responses
• 🔗 Citations for web results
• 👁️ Observability with Weave

Architecture Diagram

📂 Repository Structure

This repository includes everything required to create a functional chatbot with web access:

📡 Backend (backend/)

The core backend logic, powered by Tavily and LangGraph:

• agent.py – Defines the ReAct agent architecture, state management, and processing nodes.
• prompts.py – Contains customizable prompt templates.

🌐 Frontend (ui/)

Interactive React frontend for dynamic user interactions and chatbot responses.

Server

• app.py – FastAPI server that handles API endpoints and streaming responses.

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Setup Instructions

Set up environment variables:

a. Create a .env file in the root directory with:

TAVILY_API_KEY="your-tavily-api-key"
OPENAI_API_KEY="your-openai-api-key"
GROQ_API_KEY="your-groq-api-key"
VITE_APP_URL=http://localhost:5173

b. Create a .env file in the ui directory with:

VITE_BACKEND_URL=http://localhost:8080

Backend Setup

Python Virtual Environment

1. Create a virtual environment and activate it:

python3.11 -m venv venv
source venv/bin/activate  # On Windows: .\venv\Scripts\activate

2. Install dependencies:

python3.11 -m pip install -r requirements.txt

3. From the root of the project, run the backend server:

python app.py

Frontend Setup

1. In a new terminal, navigate to the frontend directory:

cd ui

2. Install dependencies:

npm install

3. Start the development server:

npm run dev

Open the app in your browser at the locally hosted url (e.g. http://localhost:5173/)

API Endpoints

• POST /stream_agent: Chat endpoint that handles streamed LangGraph execution

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Contributing

Feel free to submit issues and enhancement requests!

📞 Contact Us

Have questions, feedback, or looking to build something custom? We'd love to hear from you!

• Email our team directly:
  • Dean Sacoransky
  • Michael Griff

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