ProjectIntent Over Keywords: From Stitched Embeddings to a Production Fashion Agent · Module 5: Two collections and rank fusion · part 7 of 26
Part 7 · Module 5: Two collections and rank fusion

Module 5: Two collections and rank fusion

19 min read·
About 45 minutes · Needs: Module 3 (frames and CLIP vectors), Module 4 (transcript chunks and MiniLM) · Code: part1-video-rag-stitched/src/vectorstore/qdrant_store.py, part1-video-rag-stitched/src/retrieval/fusion.py, part1-video-rag-stitched/src/retrieval/retriever.py

Where this fits

WHERE THIS FITS Intent Over Keywords this module PART 1: STITCHED VIDEO RAG three models, two spaces, RRF PART 2: UNIFIED VIDEO RAG one model, one space PART 3: STYLEME FastAPI, LangGraph, React QUALITY AND OPERATIONS evals, Docker, Cloud Run Frames ffmpeg, one per 5 s CLIP ViT-B/32 frames + text, 512 d Whisper base speech to text MiniLM 64-word chunks, 384 d Two collections p1_visual, p1_text Rank fusion RRF, k = 60 Gemini answer from transcript text API + Streamlit upload, ask, sources Windows ffmpeg, video + audio Embedding 2 Gemini, one vector One collection p2_unified, no fusion Notes + answer Gemini, cited times React web chat, photo, chips nginx one URL, /api proxy FastAPI /api/chat, limits Sessions in memory, cap of 3 Planner intent before retrieval Implementer batched embed, search Generator stylist reply, ids Grounding check no LLM, drops invented Gemini flash-lite, embedding 2 Qdrant styleme_products Catalogue ingest image + title vectors Langfuse optional traces Test video 26 questions, 4 kinds Video eval Part 1 vs Part 2 Agent evals intent, grounding Guards uploads, limits, secrets Containers compose profiles Cloud Run StyleMe only CI/CD GitHub Actions, WIF Original code v1, v2, fashion-agent
This module: the two Qdrant collections and the rank fusion that merges their results (blue); CLIP and MiniLM (amber) make the two query vectors.

Modules 3 and 4 turned the test video into 40 frame vectors and 12 transcript vectors. This module is where they are stored and searched: two Qdrant collections, one per vector space, and a 12-line function that merges the two result lists by rank. That merge is the only place in Part 1 where picture and speech meet, which makes it the heart of the design and of its failure.

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