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>
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@@ -3,7 +3,7 @@ import os
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from datetime import timedelta
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from dotenv import load_dotenv
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from quart import Quart, jsonify, render_template, request, send_from_directory
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from quart import Quart, jsonify, render_template, send_from_directory
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from quart_jwt_extended import JWTManager, get_jwt_identity, jwt_refresh_token_required
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from tortoise import Tortoise
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@@ -15,7 +15,6 @@ import blueprints.users
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import blueprints.whatsapp
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import blueprints.users.models
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from config.db import TORTOISE_CONFIG
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from main import consult_simba_oracle
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# Load environment variables
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load_dotenv()
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@@ -78,39 +77,6 @@ async def serve_react_app(path):
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return await render_template("index.html")
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@app.route("/api/query", methods=["POST"])
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@jwt_refresh_token_required
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async def query():
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current_user_uuid = get_jwt_identity()
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user = await blueprints.users.models.User.get(id=current_user_uuid)
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data = await request.get_json()
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query = data.get("query")
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conversation_id = data.get("conversation_id")
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conversation = await blueprints.conversation.logic.get_conversation_by_id(
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conversation_id
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)
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await conversation.fetch_related("messages")
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await blueprints.conversation.logic.add_message_to_conversation(
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conversation=conversation,
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message=query,
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speaker="user",
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user=user,
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)
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transcript = await blueprints.conversation.logic.get_conversation_transcript(
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user=user, conversation=conversation
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)
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response = consult_simba_oracle(input=query, transcript=transcript)
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await blueprints.conversation.logic.add_message_to_conversation(
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conversation=conversation,
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message=response,
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speaker="simba",
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user=user,
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)
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return jsonify({"response": response})
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@app.route("/api/messages", methods=["GET"])
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@jwt_refresh_token_required
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async def get_messages():
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