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# How I Built an Agentic Al Research Assistant Using LangGraph and Large Language Models

**[Medium](https://daily.dev/sources/medium_js)** · 4 min read · 0 upvotes · 0 comments

## Summary

A developer shares how they built AutoResearch-AI, a multi-agent AI system that automates the research workflow using LangGraph. The system chains five specialized agents — Planner, Searcher, Reader, Writer, and Critic — each updating a shared state to produce structured research reports with citations. Built with Python, LangChain, FastAPI, and the Groq API, the project explores agentic AI design patterns including state management, error handling, and workflow orchestration. Key challenges included maintaining context across agents and mitigating hallucinations through citation validation.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://medium.com/@sid2006gupta1/how-i-built-an-agentic-al-research-assistant-using-langgraph-and-large-language-models-4b12159d7e17>

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- [Getting Started with Agentic AI in LangGraph](https://daily.dev/posts/getting-started-with-agentic-ai-in-langgraph-ab1wd94ns) · DigitalOcean Community · 12 upvotes · 0 comments

---

Tags: [#python](https://daily.dev/tags/python), [#ai-agents](https://daily.dev/tags/ai-agents), [#langchain](https://daily.dev/tags/langchain), [#langgraph](https://daily.dev/tags/langgraph)

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