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brightdata-ai-research-agent

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Guvenlik Denetimi
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  • License — License: MIT
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Bu listing icin henuz AI raporu yok.

SUMMARY

AI research agent by MattVidPro: ask a question and it searches the web, reads the pages and writes up the answer. Quick mode and deep-research mode in a simple web app. Built on Bright Data search and scraping plus any LLM.

README.md

Bright Data AI Research Agent 🍋

A MattVidPro project. Built for the MattVidPro YouTube channel, where Matt covers AI tools.

An autonomous AI Research Agent that performs web searches (SERP), scrapes page content, and synthesizes answers using LLMs. Features a "basic" fast mode and a "deep discovery" mode for complex topics, all wrapped in a fresh Lemon-Themed Web GUI.

Features

  • Gemini 3.0 Flash Preview Integration: Uses Google's latest model for high-speed, low-cost reasoning.
  • Lemon Agent GUI: A modern, clean web interface built with React + Vite and FastAPI.
  • Two Modes:
    • Basic (Fast): Classic SERP search + Synthesis. Good for quick facts.
    • Deep Discovery: Advanced multi-step research using Deep Search agents (Scrapers, Social Search).
  • History Tracking: Automatically saves research sessions for later review.
  • Citations: Every claim is backed by a verifiable source link.

Prerequisites

  • Python 3.10+
  • Node.js & npm (for the GUI)
  • Bright Data Account:
    • API Key
    • SERP API Zone (for basic search)
    • Optional: Web Unlocker / Dataset capabilities for deep mode.
  • Google Gemini API Key: Get one here

Installation

  1. Clone the repository:

    git clone https://github.com/your-username/brightdata-ai-research-agent.git
cd brightdata-ai-research-agent

  2. Set up Python Backend:

    python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -r requirements.txt

  3. Set up React Frontend:

    cd web_ui
npm install
cd ..

  4. Configuration:
    Copy .env.example to .env and fill in your keys:

    cp .env.example .env

    Required Settings:

    # LLM Choice (Recommended: Gemini 3.0 Flash)
LLM_PROVIDER="google"
GOOGLE_API_KEY="your_gemini_key"
GOOGLE_MODEL="gemini-3-flash-preview"

# Bright Data
BRIGHTDATA_API_KEY="your_bd_key"
BRIGHTDATA_SERP_ZONE="serp_api1"

    (Note: OpenAI and Ollama providers are theoretically supported but untested in this version).

Usage

Run the GUI (Recommended)

You need two terminal windows:

Terminal 1 (Backend):

source .venv/bin/activate
python -m uvicorn server:app --host 127.0.0.1 --port 8000

Terminal 2 (Frontend):

cd web_ui
npm run dev

Open http://localhost:5173 in your browser.

  • Enter your question.
  • Toggle between Basic and Discovery modes.
  • Access History via the clock icon in the top right.

CLI Usage (Legacy)

You can still run agents directly from the command line:

# Basic Agent
python -m basic_agent "What is the latest on Quantum Computing?"

# Web Discovery Agent
python -m web_discovery_agent "Analyze the market trends for NVDA vs AMD"

Project Structure

  • basic_agent/: Simple SERP-based research logic.
  • web_discovery_agent/: Advanced logic (Social search, Deep scraping).
  • shared/: Common utilities (LLM abstraction, Bright Data client).
  • server.py: FastAPI backend.
  • web_ui/: React frontend.
  • outputs/: JSON/Markdown logs of all runs.

License

MIT

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