Replace ChromaDB with pgvector for vector storage

Consolidate onto PostgreSQL by using pgvector instead of a separate
ChromaDB instance. This removes a Docker volume, a large dependency,
and simplifies the stack without meaningful performance impact at
our document scale.

- Swap langchain-chroma for langchain-postgres (PGVector)
- Use pgvector/pgvector:pg16 Docker image with init script
- Lazy-initialize vector store to avoid eager DB connections
- Add SQL helpers for stats/delete/list (replacing _collection access)
- Remove legacy main.py, chunker, petmd scraper, and /api/query endpoint

Re-index required after deploy (POST /api/rag/index + /index-obsidian).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

CLAUDE.md

@@ -4,7 +4,7 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
 
 ## Project Overview
 
-SimbaRAG is a RAG (Retrieval-Augmented Generation) conversational AI system for querying information about Simba (a cat). It ingests documents from Paperless-NGX, stores embeddings in ChromaDB, and uses LLMs (Ollama or OpenAI) to answer questions.
+SimbaRAG is a RAG (Retrieval-Augmented Generation) conversational AI system for querying information about Simba (a cat). It ingests documents from Paperless-NGX, stores embeddings in PostgreSQL via pgvector, and uses LLMs (Ollama or OpenAI) to answer questions.
 
 ## Commands
 
@@ -54,9 +54,8 @@ docker compose up -d
 │                     Docker Compose                          │
 ├─────────────────────────────────────────────────────────────┤
 │  raggr (port 8080)              │  postgres (port 5432)    │
-│  ├── Quart backend              │  PostgreSQL 16           │
-│  ├── React frontend (served)    │                          │
-│  └── ChromaDB (volume)          │                          │
+│  ├── Quart backend              │  PostgreSQL 16 + pgvector│
+│  └── React frontend (served)    │                          │
 └─────────────────────────────────────────────────────────────┘
 ```