RAG Context Playgroundgpt-4o
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Retrieval Inspector
Qdrant + BM25Top Ranked Chunks (4)
Contextra retrieval pipeline: 1) Query normalization & entity extraction. 2) Concurrent Qdrant dense vector search & Postgres BM25 keyword search. 3) Reciprocal Rank Fusion (RRF k=60). 4) Cross-encoder neural reranking.
Memory importance scoring uses exponential recency decay coupled with frequency-weighted keyword overlap to maintain a dynamic 4KB conversation summary buffer.
POST /api/v1/conversations/{id}/messages/stream returns a Server-Sent Events (SSE) stream delivering token deltas, citation references, and final execution metrics.
Context Assembler enforces a hard token limit by packing system prompt, long-term memory summary, and retrieved chunks into an optimized prompt tree.