📚 Build a Research AI Agent That Generates Answers with Citations

Описание: 📚 Build a Research AI Agent That Generates Answers with Citations

In this video, I build a real-world Research AI Agent from scratch that not only answers questions — but also provides citations for every claim.
Instead of trusting black-box responses, this agent searches, reasons, and responds with verifiable sources, making it suitable for real research, internal tools, and production-grade AI systems.

We build everything live, encounter real agent bugs, debug them step by step, and finish with a fully working application.

🔗 GitHub Repository (Full Code)
👉 Research Assistant Agent (with Citations)
https://github.com/techindoorboys/ai_...

🧠 What this Research Agent Does:
Accepts a research question from the user
Searches the web for relevant sources
Synthesizes information using an LLM
Generates a structured answer
Automatically attaches citations (sources & URLs)
This project demonstrates how Agentic AI systems differ from simple chatbots and prompt-based workflows.

🧠 What This Project Covers:
Designing a Research AI Agent using LangGraph
Understanding agents as workflows, not prompts
Using Google Gemini for grounded reasoning
Implementing a citation-aware answer generator
Debugging common agent state & hallucination issues
Building a clean FastAPI backend
Creating a simple Streamlit research UI
Managing environments with dotenv
Using UV as a modern Python package manager
Running everything inside GitHub Codespaces

🛠 Tech Stack Used:
Google Gemini (gemini-1.5-pro / flash)
Concepts compatible with ChatGPT, Claude, Codex
LangGraph
FastAPI
Uvicorn
Streamlit
DuckDuckGo (demo-friendly search)
UV (Astral)
Python 3.11+
GitHub Codespaces

🎯 Who This Video Is For
AI / GenAI Engineers
Agentic AI Developers
Machine Learning Engineers
Backend & Full-Stack Developers
Developers learning LangGraph
Anyone building trustworthy LLM systems
Engineers exploring ChatGPT, Claude, Gemini, Codex–style systems

🚀 Why This Project Matters
Most AI demos sound confident but can’t prove anything.
This project shows:
How hallucinations happen
Why agents fail in practice
How citations + structured workflows increase trust
The same architecture can power:
Research tools
Internal knowledge assistants
Enterprise AI systems
AI copilots with verification


👍 If This Helped You
If you found this useful:
👍 Like the video
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💬 Comment if you want a multi-agent or production-scale version


#AgenticAI #AIAgents #LangGraph #GenAI #ResearchAI #Citations #LLMs #ChatGPT #ClaudeAI #GeminiAI #FastAPI #Streamlit #GitHubCodespaces