Research Agent

AI-powered research agent that fetches relevant search results, summarizes information, and generates well-structured responses.

Project Description

This project is an AI-powered research agent that retrieves information from the web and generates structured answers using advanced NLP models. It integrates TavilySearchResults for web search and Hugging Face Inference API for text generation. The system follows a two-step workflow:

1. Research Agent: Fetches relevant information on a given topic from the web.
2. Answer Drafter Agent: Processes the retrieved data and generates a structured answer.
3. 

Features

• Web search capabilities using TavilySearchResults
• Text generation using Hugging Face Inference API
• Automated summarization of research topics
• Structured answer generation
• Modular and scalable design using LangChain and LangGraph

Installation

1. Clone the repository:

   git clone https://github.com/hillhack/Research-ai-agent
   cd research_agent

2. Create a virtual environment:

   python3 -m venv research_agent_env
   source research_agent_env/bin/activate  # On Windows use: research_agent_env\Scripts\activate

3. Install dependencies:

   pip install -r installed_packages.txt

4. Set up environment variables:
   • Create a .env file and add:

     TAVILY_API_KEY=your_tavily_api_key
     HUGGING_API_KEY=your_hugging_face_api_key

Dependencies

• langchain
• langgraph
• huggingface_hub
• tavily-python
• dotenv