Reliable, fully local RAG agents with LLaMA3
From the video description
With the release of LLaMA3, we're seeing great interest in agents that can run reliably and locally (e.g., on your laptop). Here, we show to how build reliable local agents using LangGraph and LLaMA3-8b from scratch. We combine ideas from 3 advanced RAG papers (Adaptive RAG, Corrective RAG, and Self-RAG) into a single control flow. We run this locally w/ a local vectorstore c/o @nomic_ai & @trychroma, @tavilyai for web search, and LLaMA3-8b via @ollama.
Topics
Sources
Video by LangChain, played through YouTube.
- Indie Picks
Data and selection notes
Indie Picks uses video metadata for classification. The description above is an uploader excerpt, not an independent review.
Indie Picks: Independently collected SaaS and AI product videos, organized by a founder handbook. Topics and relevance are metadata-indexed; full-video editorial review has not been completed. Descriptions are uploader excerpts where available.
Views, duration and playback status refresh separately from the published catalog. When an update fails, existing data remains visible.
Selection checks
- SaaS & AI candidates: Matches the configured criteria
- Editor-approved picks: Editorial review is required