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Standard RAG lacks context, but full agentic scanning is too slow—so I designed a “Dual-Path” architecture to fix this. In this video, we build a hybrid system using DuckDB and Gemini that combines semantic search with metadata filtering to achieve high-accuracy retrieval without the latency. Join me as we upgrade our open-source agent with smart chunking and backtracking capabilities.
LINK:
Repo: https://github.com/PromtEngineer/agentic-file-search
Intro video: https://youtu.be/rMADSuus6jg
With Local Models: https://youtu.be/xG3eS_zHR3k
LangExtract Videos: https://youtu.be/RPpGIxmdZYs
https://youtu.be/dPL2vRDunMw
My voice to text App: whryte.com
Website: https://engineerprompt.ai/
RAG Beyond Basics Course:
https://prompt-s-site.thinkific.com/courses/rag
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Let’s Connect:
🦾 Discord: https://discord.com/invite/t4eYQRUcXB
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|🔴 Patreon: https://www.patreon.com/PromptEngineering
💼Consulting: https://calendly.com/engineerprompt/consulting-call
📧 Business Contact: engineerprompt@gmail.com
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💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off).
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