Building Generative AI Applications in Go- Gari Singh, Google (Part 2)
summary
Walks through a runnable Go flow that indexes text into a vector store, retrieves relevant passages, and calls a model for generation using Gemini Pro, with orchestration libraries like LangChain Go and Firebase’s Gen Kit and local serving via local VC (an in-memory vector DB) and AMA for local models. Demo exposes an HTTP API (port 3400), returns "Paris" when that context is present and otherwise refuses to answer, proving the RAG pipeline works end to end.
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chapters (7)
- 0:00Introduction to GenAI in Go
- 2:18Model orchestration frameworks
- 4:47Application architecture
- 7:07Understanding RAG fundamentals
- 10:49Implementing RAG workflows
- 16:58RAG code walkthrough
- 27:00Q&A and final discussion
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