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VERSION:2.0
PRODID:-//Allsikt//Article Deadline//EN
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BEGIN:VEVENT
UID:828cd01438357a69befe754522e9b2110cfd0638@allsikt.tech
DTSTAMP:20260722T194146Z
DTSTART;VALUE=DATE:20260722
DTEND;VALUE=DATE:20260723
SUMMARY:Build a RAG Agent with LangChain – A Practical Lab for Retrieval‑Augmented Generation
DESCRIPTION:Run `python rag_agent.py ingest` to pull your DEV.to posts\, then `python rag_agent.py chat` to test the three RAG strategies\; enable local embeddings with `ollama pull nomic-embed-text` to keep indexing local.\n\nSource: Dev.to (top)\nOpen: https://allsikt.se/article/build-a-rag-agent-with-langchain-a-practical-lab-for-retrieval-augmented-generation-3f5ebf8c
URL:https://allsikt.se/article/build-a-rag-agent-with-langchain-a-practical-lab-for-retrieval-augmented-generation-3f5ebf8c
STATUS:CONFIRMED
TRANSP:TRANSPARENT
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