local-rag-researcher-deepseek

🚀 Local RAG Researcher with DeepSeek R1 & Langgraph 👉 Learn How to Build a Local RAG Researcher – Step-by-Step Guide Inside! 🚀 I built a local adaptive RAG research agent using LangGraph and a local DeepSeek R1 model running on Ollama. This agent act like a deep researcher, designed to gather, analyze, and summarize information based on user instructions. How It Works Generating Research Queries – The agent takes user input and formulates relevant research questions to find the most useful information. Retrieving Documents – It searches a local Chroma database to pull relevant documents related to the query. Evaluating Relevance – Each document is checked against the original query to ensure it contains meaningful and accurate information. Expanding Search if Needed – If the retrieved documents are not sufficient or relevant, the agent can search the web for additional sources. Summarizing Findings – After gathering all necessary information, the agent processes the data and extracts key insights.