القائمة
RAG pipeline production — ingestion, chunking chiến lược, embedding, hybrid search, rerank. Không index trùng, search dưới 200ms.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | ais-rag |
| description | RAG pipeline production — ingestion, chunking chiến lược, embedding, hybrid search, rerank. Không index trùng, search dưới 200ms. |
| File | Mục đích |
|---|---|
templates/chunking.py | chunk_document() — markdown/code/text splitters with overlap |
templates/embedding.py | EmbedCache (SQLite) + embed_batch() with OpenAI |
templates/schema.sql | pgvector DDL — documents table, IVFFlat + GIN indexes |
templates/hybrid-search.py | hybrid_search() — vector cosine + keyword ts_rank combined |
templates/rerank.py | LLM-based reranking with RERANK_PROMPT |
from templates.chunking import chunk_document
chunks = chunk_document(text, "markdown")
Performance targets: search < 200ms, rerank top-3 < 1s. Deduplication: hash content before insert to avoid duplicates.
| Excuse | Reality |
|---|---|
| "Hybrid search không cần, vector đủ" | Keyword miss → 0 results cho thuật ngữ chính xác |
| "Chunk overlap 0 là đủ" | Câu bị cắt giữa chừng → context incomplete |
| "pgvector index sau, data ít" | Full scan khi có 10k+ docs → search > 1s |
Expert in building 3D experiences for the web - Three.js, React Three Fiber, Spline, WebGL, and interactive 3D scenes. Covers product configurators, 3D portfolios, immersive websites, and bringing depth to web experiences. Use when: 3D website, three.js, WebGL, react three fiber, 3D experience.
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