RAG Pipeline with Quality Gates

AI

Embed query, search vector index, retrieve context, generate answer, validate against retrieved sources, deliver or regenerate.

agentdbapi
Why OSOP matters here

RAG pipelines fail silently — bad retrieval, hallucinated answers. OSOP tracks retrieval quality scores, token usage, hallucination confidence, and total latency — giving you data to optimize.

Workflow Steps (5)

1
Embed User Query
api
2
Vector Search
db
3
Generate Answer
agent
4
Hallucination Check
agent
5
Return Response
api

Connections (5)

Embed User Query→Vector Searchsequential
Vector Search→Generate Answersequential
Generate Answer→Hallucination Checksequential
Hallucination Check→Return Responseconditionalvalidation.grounded == true
Hallucination Check→Generate AnswerfallbackRegenerate with stricter prompt
5
Steps
5
Connections
3
Node Types
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