Research Agent

A multi-source research agent built with LangGraph that searches Google, Bing, and Reddit to gather and synthesize information on any topic.

Overview

This agent performs parallel web searches across multiple platforms, retrieves relevant Reddit discussions with comments, and uses an LLM to analyze and synthesize the findings into a comprehensive answer.

How It Works

1. Parallel Search - Simultaneously searches Google, Bing, and Reddit for the user's query
2. Reddit Deep Dive - Analyzes Reddit search results and retrieves full post comments from relevant discussions
3. Multi-Source Analysis - Independently analyzes results from each source (Google, Bing, Reddit)
4. Synthesis - Combines all analyses into a final, comprehensive answer

Tech Stack

• LangGraph - Orchestrates the agent workflow as a directed graph
• LangChain - LLM integration (GPT-4)
• Bright Data - Web scraping API for SERP results and Reddit data

Prerequisites

• Python 3.12+
• uv (recommended) or pip
• OpenAI API key
• Bright Data API key

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/researchAgent.git
   cd researchAgent

2. Install dependencies:

   uv sync

3. Create a .env file with your API keys:

   OPENAI_API_KEY=your_openai_api_key
   BRIGHTDATA_API_KEY=your_brightdata_api_key

Usage

Command Line

uv run python main.py

Then type your research question at the prompt.

LangGraph Studio

For a visual interface with graph visualization and debugging:

1. Install the LangGraph CLI (included in dependencies):

   uv pip install langgraph-cli langgraph-api

2. Launch LangGraph Studio:

   uv run langgraph dev

3. Open the provided URL in your browser to interact with the agent visually.

Project Structure

researchAgent/
├── main.py              # Main agent graph definition and CLI
├── web_operations.py    # Google, Bing, and Reddit search functions
├── snapshot_operations.py # Bright Data snapshot polling/download
├── prompts.py           # LLM prompts for analysis
├── langgraph.json       # LangGraph Studio configuration
└── .env                 # API keys (not tracked)

Credits

This project was built following the tutorial by @TechWithTim:

How to Build an Advanced AI Agent with Search (LangGraph, Python, Bright Data & More)

License

MIT