ProjectIntent Over Keywords: From Stitched Embeddings to a Production Fashion Agent · Module 6: "Almost correct": diagnosing the failure · part 8 of 26
Part 8 · Module 6: "Almost correct": diagnosing the failure

Module 6: "Almost correct": diagnosing the failure

22 min read·
About 50 minutes · Needs: Module 1 (the problem with multimodal search), Module 5 (two collections and rank fusion) · Code: samples/build_test_video.py, samples/questions.jsonl, part1-video-rag-stitched/src/generation/generator.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 test video and its questions, the eval that scores Part 1, and the path from rank fusion to the answer model (amber, a model).

Part 1 is built and hardened. This module asks whether it works, and answers with a designed test instead of a few happy questions. The highlighted pieces are the test video and its 26 questions, the eval that scores Part 1 through its API, and the last hop of the query path: from rank fusion to the answer model. The eval harness itself is Module 10; here we read its results for Part 1 and find the cause.

The rest of this project is yours to keep

This project is bought on its own, once, and stays readable afterwards, including the parts added to it later.

Or open everything with a plan