hskwon
aca1767eb9
- URL 하드코딩 → .env APP_URL 기반 동적 URL로 변경 - DB 연결 하드코딩 → .env 기반으로 변경 - MySQL strict mode DATE 오류 수정
41 lines
1.7 KiB
Markdown
41 lines
1.7 KiB
Markdown
# Implementation Plan - Advanced Vector RAG (Parallel Deployment)
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We will build the "Advanced Vector RAG" system as a separate module to compare with the existing "Live Search RAG".
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## User Review Required
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> [!NOTE]
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> **New Menu Item**: "운영자 vertex RAG 챗봇" will be added to the SAM menu.
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> **Initial Setup**: You must run `chatbot/rag/ingest.php` once to populate the vector database.
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## Proposed Changes
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### 1. New UI & Entry Point
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#### [MODIFY] [myheader.php](file:///c:/Project/5130/myheader.php)
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- Add new menu item: "운영자 vertex RAG 챗봇" linking to `chatbot/rag_index.php`.
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#### [NEW] [chatbot/rag_index.php](file:///c:/Project/5130/chatbot/rag_index.php)
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- Copied from `index.php`.
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- Updated to call `rag_api.php` instead of `api.php`.
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- Updated title/branding to indicate "RAG Version".
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### 2. Vector Backend
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#### [NEW] [chatbot/rag_api.php](file:///c:/Project/5130/chatbot/rag_api.php)
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- Copied from `api.php`.
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- logic: `NotionClient->search()` replaced with `VectorSearch->search()`.
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### 3. Vector Engine (Core Logic)
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#### [NEW] [chatbot/rag/ingest.php](file:///c:/Project/5130/chatbot/rag/ingest.php)
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- EXTRACT: Fetch all Notion pages.
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- EMBED: Generate vectors using Gemini `text-embedding-004`.
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- STORE: Save to `chatbot/rag/data/vectors.json`.
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#### [NEW] [chatbot/rag/search.php](file:///c:/Project/5130/chatbot/rag/search.php)
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- LOAD: Read `vectors.json`.
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- SEARCH: Calculate Cosine Similarity between Query Vector and Stored Vectors.
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- RETRIEVE: Return top 5 matches.
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## Verification Plan
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1. **Menu Check**: Verify new menu item appears and leads to the new page.
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2. **Ingestion**: Run `ingest.php` (via browser or CLI) and check `vectors.json` size.
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3. **Comparison Test**: Ask the same question to both chatbots and compare answers.
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