1 min readfrom Machine Learning

We’ve got a workshop on production retrieval-augmented generation with open models, benchmarked end to end, thought it’d be relevant here [D]

There’s a hands-on workshop on August 29 that builds and benchmarks this properly, end to end, using entirely open models, no API calls involved. Led by Ben Auffarth, AI Consultant and Founder of Chelsea AI Ventures.

What it covers:

Hybrid retrieval (vector + keyword, not vector alone)
Reranking to catch relevant chunks that vector search alone misses
Evaluation with RAGAS, so quality changes are measured, not assumed
Guardrails built in from the design stage
Actual cost and performance benchmarking for open-model deployments

Link if anyone wants to check it out: https://www.eventbrite.co.uk/e/the-genai-build-lab-build-production-ready-rag-on-a-budget-tickets-1994016271345?aff=rml

Happy to answer questions on the methodology or content.

submitted by /u/camerongreen95
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Tagged with

#Retrieval-Augmented Generation (RAG)
#Open Models
#Production
#Benchmarking
#Hybrid Retrieval
#Vector Search
#Keyword Search
#Reranking
#RAGAS
#Evaluation
#Guardrails
#Cost Optimization
#Performance
#End-to-End
#AI Consultant
#Chelsea AI Ventures
#GenAI
#API Calls
#Vector Embeddings
#Workshop