Deep Research AI Agent

Generate comprehensive research reports on any topic in seconds.

🌟 What is This?

Deep Research AI Agent is a web application that helps you research any topic and generates professional research reports automatically. Simply type in what you want to research, and our AI agents will:

• 🔍 Search the web for reliable information
• 📊 Analyze and synthesize the data
• 📝 Create a structured research report
• 📄 Let you download it in multiple formats (PDF, Word, Markdown)

No technical knowledge required! Just visit the website and start researching.

Live Demo

https://deep-research-ai-agent.streamlit.app/

🎥 See It In Action

✨ Key Features

🤖 Intelligent Research System

• Dual AI Agents: One searches the web, another writes your report
• Multi-Language Support: Generate reports in English, Spanish, or German
• Model Selection: Choose models via OpenRouter

📝 Customizable Output

• Writing Styles: Academic, Business, Technical, or Casual
• Citation Formats: APA, MLA, or IEEE standards
• Word Count Control: 500 to 5000 words
• Multiple Export Formats: PDF, Word, Markdown, JSON, or Plain Text

🎨 User-Friendly Interface

• No Login Required: Start researching immediately
• Progress Tracking: Real-time updates as your research generates
• Mobile Responsive: Works on phones, tablets, and desktops

🔧 Advanced Features

• Deep Research Mode: For comprehensive, academic-style papers
• Model Selection: Choose from multiple models
• Duplicate Detection: Automatically removes redundant content
• Memory System (ChromaDB): Reduces API calls by 30-60%, speeds up responses by 20-40% on repeated topics

Architecture (agent‑like)

• Orchestrated with LangGraph as a two‑node state machine:
  • research → gathers sources via Tavily (with domain filtering)
  • draft → composes structured Markdown based on style/language/citations
• Post‑processing normalizes lists, paragraph spacing, and references across PDF/Word/Markdown/Text.
• Optional vector memory stores past research with smart TTL (3 days for news, 30 days for evergreen content)

🎯 Perfect For

• 📚 Students: Research papers, essays, assignments
• 📰 Writers: Article research, fact-checking, content ideas
• 🎓 Educators: Lesson planning, curriculum development
• 💡 Anyone Curious: Learn about any topic quickly!

For Developers

Quick Setup

1. Clone the repository:

    git clone https://github.com/saksham-jain177/AI-Agent-based-Deep-Research.git
    cd AI-Agent-based-Deep-Research

2. Install Python 3.8+ and dependencies:

   pip install -r requirements.txt

3. Get API keys:

   • Tavily API - For web search (free tier available)
   • OpenRouter API - For AI models

4. Create .env file:

   TAVILY_API_KEY=your_tavily_key_here
   OPENROUTER_API_KEY=your_openrouter_key_here
   
   # Optional: Enable vector memory for faster repeated searches
   ENABLE_VECTOR_STORE=true
   
   # Optional: For feedback system (bot email sends to itself)
   [email protected]     # Bot Gmail account
   FEEDBACK_BOT_PASSWORD=16_char_app_password # Gmail App Password (not regular password)
   

5. Run the app:

   streamlit run app.py

Tech Stack

• Frontend: Streamlit (Python web framework)
• AI Framework: LangChain & LangGraph
• Web Search: Tavily API
• LLM Provider: OpenRouter
• Document Generation: ReportLab (PDF), python-docx (Word)

Project Structure

AI-Agent-based-Deep-Research/
├── app.py              # Main Streamlit application
├── main.py             # Orchestrates research workflow
├── research_agent.py   # Web search functionality
├── draft_agent.py      # AI report generation
├── requirements.txt    # Python dependencies
└── .env               # API keys (create this)

Deploy your own instance

If you'd like to deploy your own version of this app with customizations with Streamlit Cloud :

1. Fork this repository
2. Visit share.streamlit.io
3. Connect your GitHub account
4. Deploy your forked repo
5. Add API keys in Streamlit's Secrets (Settings → Secrets)

🤝 Contributing

We welcome contributions! Here's how you can help:

1. Report Bugs: Open an issue describing the problem
2. Suggest Features: Share your ideas in discussions
3. Submit Code: Fork, modify, and create a pull request
4. Improve Docs: Help make this README even better
5. Share: Tell others about this project!

Development Setup

# Clone your fork
git clone https://github.com/YOUR_USERNAME/AI-Agent-based-Deep-Research.git

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode
pip install -r requirements.txt

# Make your changes and test
streamlit run app.py

❓ FAQ

Q: Do I need coding knowledge?
A: No. Open the web app, enter a query, and click Run.

Q: Can I use this for academic work?
A: Yes, but always verify sources and cite appropriately. This is a research tool, not a substitute for critical thinking.

Q: How accurate is the information?
A: We search reputable sources and filter out social media. However, always fact-check important information.

Q: Can I customize the AI model?
A: Yes. Choose a model from the sidebar (OpenRouter).

Q: Is my data private?
A: We don't store your searches. API providers may have their own policies.

📜 License

MIT License - Use freely for personal or commercial projects!

📧 Contact

• GitHub Issues: Report bugs or request features
• Discussions: Join the community

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⭐ Star this repo if you find it helpful!