Clean up presigned URL implementation: remove dead fields, fix error handling

- Remove unused image_url from upload response and TS type
- Remove bare except in serve_image that masked config errors as 404s
- Add error state and broken-image placeholder in QuestionBubble

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

.env.example

@@ -19,6 +19,11 @@ BASE_URL=192.168.1.5:8000
 LLAMA_SERVER_URL=http://192.168.1.213:8080/v1
 LLAMA_MODEL_NAME=llama-3.1-8b-instruct
 
+# ChromaDB Configuration
+# For Docker: This is automatically set to /app/data/chromadb
+# For local development: Set to a local directory path
+CHROMADB_PATH=./data/chromadb
+
 # OpenAI Configuration
 OPENAI_API_KEY=your-openai-api-key
 

.gitignore

@@ -13,6 +13,9 @@ wheels/
 .env
 
 # Database files
+chromadb/
+chromadb_openai/
+chroma_db/
 database/
 *.db
 

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 PostgreSQL via pgvector, 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 ChromaDB, and uses LLMs (Ollama or OpenAI) to answer questions.
 
 ## Commands
 
@@ -54,8 +54,9 @@ docker compose up -d
 │                     Docker Compose                          │
 ├─────────────────────────────────────────────────────────────┤
 │  raggr (port 8080)              │  postgres (port 5432)    │
-│  ├── Quart backend              │  PostgreSQL 16 + pgvector│
+│  ├── Quart backend              │  PostgreSQL 16           │
-│  └── React frontend (served)    │                          │
+│  ├── React frontend (served)    │                          │
+│  └── ChromaDB (volume)          │                          │
 └─────────────────────────────────────────────────────────────┘
 ```
 
@@ -90,15 +91,6 @@ docker compose up -d
 
 **Auth Flow**: LLDAP → Authelia (OIDC) → Backend JWT → Frontend localStorage
 
-## Testing
-
-Always run `make test` before pushing code to ensure all tests pass.
-
-```bash
-make test       # Run tests
-make test-cov   # Run tests with coverage
-```
-
 ## Key Patterns
 
 - All endpoints are async (`async def`)

Dockerfile

@@ -37,14 +37,15 @@ WORKDIR /app/raggr-frontend
 RUN yarn install && yarn build
 WORKDIR /app
 
-# Create database directory
+# Create ChromaDB and database directories
-RUN mkdir -p /app/database
+RUN mkdir -p /app/chromadb /app/database
 
 # Expose port
 EXPOSE 8080
 
 # Set environment variables
 ENV PYTHONPATH=/app
+ENV CHROMADB_PATH=/app/chromadb
 
 # Run the startup script
 CMD ["./startup.sh"]

Dockerfile.dev

@@ -34,15 +34,16 @@ COPY . .
 WORKDIR /app/raggr-frontend
 RUN yarn build
 
-# Create database directory
+# Create ChromaDB and database directories
 WORKDIR /app
-RUN mkdir -p /app/database
+RUN mkdir -p /app/chromadb /app/database
 
 # Make startup script executable
 RUN chmod +x /app/startup-dev.sh
 
 # Set environment variables
 ENV PYTHONPATH=/app
+ENV CHROMADB_PATH=/app/chromadb
 ENV PYTHONUNBUFFERED=1
 
 # Expose port

Makefile

@@ -1,11 +1,8 @@
-.PHONY: deploy redeploy build up down restart logs migrate migrate-new frontend test
+.PHONY: deploy build up down restart logs migrate migrate-new frontend
 
 # Build and deploy
 deploy: build up
 
-redeploy:
-	git pull && $(MAKE) down && $(MAKE) up
-
 build:
 	docker compose build raggr
 
@@ -32,13 +29,6 @@ migrate-new:
 migrate-history:
 	docker compose exec raggr aerich history
 
-# Tests
-test:
-	pytest tests/ -v
-
-test-cov:
-	pytest tests/ -v --cov
-
 # Frontend
 frontend:
 	cd raggr-frontend && yarn install && yarn build

app.py

@@ -1,9 +1,8 @@
 import logging
 import os
-from datetime import timedelta
 
 from dotenv import load_dotenv
-from quart import Quart, jsonify, render_template, send_from_directory
+from quart import Quart, jsonify, render_template, request, send_from_directory
 from quart_jwt_extended import JWTManager, get_jwt_identity, jwt_refresh_token_required
 from tortoise import Tortoise
 
@@ -15,6 +14,7 @@ import blueprints.users
 import blueprints.whatsapp
 import blueprints.users.models
 from config.db import TORTOISE_CONFIG
+from main import consult_simba_oracle
 
 # Load environment variables
 load_dotenv()
@@ -38,8 +38,6 @@ app = Quart(
 )
 
 app.config["JWT_SECRET_KEY"] = os.getenv("JWT_SECRET_KEY", "SECRET_KEY")
-app.config["JWT_ACCESS_TOKEN_EXPIRES"] = timedelta(hours=1)
-app.config["JWT_REFRESH_TOKEN_EXPIRES"] = timedelta(days=30)
 app.config["MAX_CONTENT_LENGTH"] = 10 * 1024 * 1024  # 10 MB upload limit
 jwt = JWTManager(app)
 
@@ -77,6 +75,39 @@ async def serve_react_app(path):
     return await render_template("index.html")
 
 
+@app.route("/api/query", methods=["POST"])
+@jwt_refresh_token_required
+async def query():
+    current_user_uuid = get_jwt_identity()
+    user = await blueprints.users.models.User.get(id=current_user_uuid)
+    data = await request.get_json()
+    query = data.get("query")
+    conversation_id = data.get("conversation_id")
+    conversation = await blueprints.conversation.logic.get_conversation_by_id(
+        conversation_id
+    )
+    await conversation.fetch_related("messages")
+    await blueprints.conversation.logic.add_message_to_conversation(
+        conversation=conversation,
+        message=query,
+        speaker="user",
+        user=user,
+    )
+
+    transcript = await blueprints.conversation.logic.get_conversation_transcript(
+        user=user, conversation=conversation
+    )
+
+    response = consult_simba_oracle(input=query, transcript=transcript)
+    await blueprints.conversation.logic.add_message_to_conversation(
+        conversation=conversation,
+        message=response,
+        speaker="simba",
+        user=user,
+    )
+    return jsonify({"response": response})
+
+
 @app.route("/api/messages", methods=["GET"])
 @jwt_refresh_token_required
 async def get_messages():
@@ -101,10 +132,17 @@ async def get_messages():
             }
         )
 
+    name = conversation.name
+    if len(messages) > 8:
+        name = await blueprints.conversation.logic.rename_conversation(
+            user=user,
+            conversation=conversation,
+        )
+
     return jsonify(
         {
             "id": str(conversation.id),
-            "name": conversation.name,
+            "name": name,
             "messages": messages,
             "created_at": conversation.created_at.isoformat(),
             "updated_at": conversation.updated_at.isoformat(),

blueprints/conversation/__init__.py

@@ -1,3 +1,4 @@
+import datetime
 import json
 import logging
 import uuid
@@ -19,8 +20,8 @@ from .agents import main_agent
 from .logic import (
     add_message_to_conversation,
     get_conversation_by_id,
+    rename_conversation,
 )
-from .memory import get_memories_for_user
 from .models import (
     Conversation,
     PydConversation,
@@ -35,27 +36,15 @@ conversation_blueprint = Blueprint(
 _SYSTEM_PROMPT = SIMBA_SYSTEM_PROMPT
 
 
-async def _build_system_prompt_with_memories(user_id: str) -> str:
-    """Append user memories to the base system prompt."""
-    memories = await get_memories_for_user(user_id)
-    if not memories:
-        return _SYSTEM_PROMPT
-    memory_block = "\n".join(f"- {m}" for m in memories)
-    return f"{_SYSTEM_PROMPT}\n\nUSER MEMORIES (facts the user has asked you to remember):\n{memory_block}"
-
-
 def _build_messages_payload(
-    conversation,
+    conversation, query_text: str, image_description: str | None = None
-    query_text: str,
-    image_description: str | None = None,
-    system_prompt: str | None = None,
 ) -> list:
     recent_messages = (
         conversation.messages[-10:]
         if len(conversation.messages) > 10
         else conversation.messages
     )
-    messages_payload = [{"role": "system", "content": system_prompt or _SYSTEM_PROMPT}]
+    messages_payload = [{"role": "system", "content": _SYSTEM_PROMPT}]
     for msg in recent_messages[:-1]:  # Exclude the message we just added
         role = "user" if msg.speaker == "user" else "assistant"
         text = msg.text
@@ -91,14 +80,10 @@ async def query():
         user=user,
     )
 
-    system_prompt = await _build_system_prompt_with_memories(str(user.id))
+    messages_payload = _build_messages_payload(conversation, query)
-    messages_payload = _build_messages_payload(
-        conversation, query, system_prompt=system_prompt
-    )
     payload = {"messages": messages_payload}
-    agent_config = {"configurable": {"user_id": str(user.id)}}
 
-    response = await main_agent.ainvoke(payload, config=agent_config)
+    response = await main_agent.ainvoke(payload)
     message = response.get("messages", [])[-1].content
     await add_message_to_conversation(
         conversation=conversation,
@@ -178,19 +163,15 @@ async def stream_query():
             logging.error(f"Failed to analyze image: {e}")
             image_description = "[Image could not be analyzed]"
 
-    system_prompt = await _build_system_prompt_with_memories(str(user.id))
     messages_payload = _build_messages_payload(
-        conversation, query_text or "", image_description, system_prompt=system_prompt
+        conversation, query_text or "", image_description
     )
     payload = {"messages": messages_payload}
-    agent_config = {"configurable": {"user_id": str(user.id)}}
 
     async def event_generator():
         final_message = None
         try:
-            async for event in main_agent.astream_events(
+            async for event in main_agent.astream_events(payload, version="v2"):
-                payload, version="v2", config=agent_config
-            ):
                 event_type = event.get("event")
 
                 if event_type == "on_tool_start":
@@ -240,6 +221,8 @@ async def stream_query():
 @jwt_refresh_token_required
 async def get_conversation(conversation_id: str):
     conversation = await Conversation.get(id=conversation_id)
+    current_user_uuid = get_jwt_identity()
+    user = await blueprints.users.models.User.get(id=current_user_uuid)
     await conversation.fetch_related("messages")
 
     # Manually serialize the conversation with messages
@@ -254,10 +237,18 @@ async def get_conversation(conversation_id: str):
                 "image_key": msg.image_key,
             }
         )
+    name = conversation.name
+    if len(messages) > 8 and "datetime" in name.lower():
+        name = await rename_conversation(
+            user=user,
+            conversation=conversation,
+        )
+        print(name)
+
     return jsonify(
         {
             "id": str(conversation.id),
-            "name": conversation.name,
+            "name": name,
             "messages": messages,
             "created_at": conversation.created_at.isoformat(),
             "updated_at": conversation.updated_at.isoformat(),
@@ -271,7 +262,7 @@ async def create_conversation():
     user_uuid = get_jwt_identity()
     user = await blueprints.users.models.User.get(id=user_uuid)
     conversation = await Conversation.create(
-        name="New Conversation",
+        name=f"{user.username} {datetime.datetime.now().timestamp}",
         user=user,
     )
 
@@ -284,7 +275,7 @@ async def create_conversation():
 async def get_all_conversations():
     user_uuid = get_jwt_identity()
     user = await blueprints.users.models.User.get(id=user_uuid)
-    conversations = Conversation.filter(user=user).order_by("-updated_at")
+    conversations = Conversation.filter(user=user)
     serialized_conversations = await PydListConversation.from_queryset(conversations)
 
     return jsonify(serialized_conversations.model_dump())

blueprints/conversation/agents.py

@@ -5,11 +5,9 @@ from dotenv import load_dotenv
 from langchain.agents import create_agent
 from langchain.chat_models import BaseChatModel
 from langchain.tools import tool
-from langchain_core.runnables import RunnableConfig
 from langchain_openai import ChatOpenAI
 from tavily import AsyncTavilyClient
 
-from blueprints.conversation.memory import save_memory
 from blueprints.rag.logic import query_vector_store
 from utils.obsidian_service import ObsidianService
 from utils.ynab_service import YNABService
@@ -328,7 +326,7 @@ async def obsidian_search_notes(query: str) -> str:
         return "Obsidian integration is not configured. Please set OBSIDIAN_VAULT_PATH environment variable."
 
     try:
-        # Query vector store for obsidian documents
+        # Query ChromaDB for obsidian documents
         serialized, docs = await query_vector_store(query=query)
         return serialized
 
@@ -591,35 +589,8 @@ async def obsidian_create_task(
         return f"Error creating task: {str(e)}"
 
 
-@tool
-async def save_user_memory(content: str, config: RunnableConfig) -> str:
-    """Save a fact or preference about the user for future conversations.
-
-    Use this tool when the user:
-    - Explicitly asks you to remember something ("remember that...", "keep in mind...")
-    - Shares a personal preference that would be useful in future conversations
-      (e.g., "I prefer metric units", "my cat's name is Luna")
-    - Tells you a meaningful personal fact (e.g., "I'm allergic to peanuts")
-
-    Do NOT save:
-    - Trivial or ephemeral info (e.g., "I'm tired today")
-    - Information already in the system prompt or documents
-    - Conversation-specific context that won't matter later
-
-    Args:
-        content: A concise statement of the fact or preference to remember.
-                 Write it as a standalone sentence (e.g., "User prefers dark mode"
-                 rather than "likes dark mode").
-
-    Returns:
-        Confirmation that the memory was saved.
-    """
-    user_id = config["configurable"]["user_id"]
-    return await save_memory(user_id=user_id, content=content)
-
-
 # Create tools list based on what's available
-tools = [get_current_date, simba_search, web_search, save_user_memory]
+tools = [get_current_date, simba_search, web_search]
 if ynab_enabled:
     tools.extend(
         [

blueprints/conversation/logic.py

@@ -1,8 +1,9 @@
 import tortoise.exceptions
+from langchain_openai import ChatOpenAI
 
 import blueprints.users.models
 
-from .models import Conversation, ConversationMessage
+from .models import Conversation, ConversationMessage, RenameConversationOutputSchema
 
 
 async def create_conversation(name: str = "") -> Conversation:
@@ -18,12 +19,6 @@ async def add_message_to_conversation(
     image_key: str | None = None,
 ) -> ConversationMessage:
     print(conversation, message, speaker)
-
-    # Name the conversation after the first user message
-    if speaker == "user" and not await conversation.messages.all().exists():
-        conversation.name = message[:100]
-        await conversation.save()
-
     message = await ConversationMessage.create(
         text=message,
         speaker=speaker,
@@ -66,3 +61,22 @@ async def get_conversation_transcript(
         messages.append(f"{message.speaker} at {message.created_at}: {message.text}")
 
     return "\n".join(messages)
+
+
+async def rename_conversation(
+    user: blueprints.users.models.User,
+    conversation: Conversation,
+) -> str:
+    messages: str = await get_conversation_transcript(
+        user=user, conversation=conversation
+    )
+
+    llm = ChatOpenAI(model="gpt-4o-mini")
+    structured_llm = llm.with_structured_output(RenameConversationOutputSchema)
+
+    prompt = f"Summarize the following conversation into a sassy one-liner title:\n\n{messages}"
+    response = structured_llm.invoke(prompt)
+    new_name: str = response.get("title", "")
+    conversation.name = new_name
+    await conversation.save()
+    return new_name

blueprints/conversation/memory.py

@@ -1,19 +0,0 @@
-from .models import UserMemory
-
-
-async def get_memories_for_user(user_id: str) -> list[str]:
-    """Return all memory content strings for a user, ordered by most recently updated."""
-    memories = await UserMemory.filter(user_id=user_id).order_by("-updated_at")
-    return [m.content for m in memories]
-
-
-async def save_memory(user_id: str, content: str) -> str:
-    """Save a new memory or touch an existing one (exact-match dedup)."""
-    existing = await UserMemory.filter(user_id=user_id, content=content).first()
-    if existing:
-        existing.updated_at = None  # auto_now=True will refresh it on save
-        await existing.save(update_fields=["updated_at"])
-        return "Memory already exists (refreshed)."
-
-    await UserMemory.create(user_id=user_id, content=content)
-    return "Memory saved."

blueprints/conversation/models.py

@@ -1,4 +1,5 @@
 import enum
+from dataclasses import dataclass
 
 from tortoise import fields
 from tortoise.contrib.pydantic import (
@@ -8,6 +9,12 @@ from tortoise.contrib.pydantic import (
 from tortoise.models import Model
 
 
+@dataclass
+class RenameConversationOutputSchema:
+    title: str
+    justification: str
+
+
 class Speaker(enum.Enum):
     USER = "user"
     SIMBA = "simba"
@@ -40,17 +47,6 @@ class ConversationMessage(Model):
         table = "conversation_messages"
 
 
-class UserMemory(Model):
-    id = fields.UUIDField(primary_key=True)
-    user = fields.ForeignKeyField("models.User", related_name="memories")
-    content = fields.TextField()
-    created_at = fields.DatetimeField(auto_now_add=True)
-    updated_at = fields.DatetimeField(auto_now=True)
-
-    class Meta:
-        table = "user_memories"
-
-
 PydConversationMessage = pydantic_model_creator(ConversationMessage)
 PydConversation = pydantic_model_creator(
     Conversation, name="Conversation", allow_cycles=True, exclude=("user",)

blueprints/conversation/prompts.py

@@ -54,7 +54,4 @@ You have access to Ryan's daily journal notes. Each note lives at journal/YYYY/Y
 - Use journal_get_tasks to list tasks (done/pending) for today or a specific date
 - Use journal_add_task to add a new task to today's (or a given date's) note
 - Use journal_complete_task to check off a task as done
-Use these tools when Ryan asks about today's tasks, wants to add something to his list, or wants to mark a task complete.
+Use these tools when Ryan asks about today's tasks, wants to add something to his list, or wants to mark a task complete."""
-
-USER MEMORY:
-You can remember facts about the user across conversations using the save_user_memory tool. When a user explicitly asks you to remember something, or shares a meaningful preference or personal fact, save it. Saved memories will automatically appear at the end of this prompt in future conversations under "USER MEMORIES"."""

blueprints/rag/__init__.py

@@ -1,12 +1,7 @@
 from quart import Blueprint, jsonify
 from quart_jwt_extended import jwt_refresh_token_required
 
-from .logic import (
+from .logic import fetch_obsidian_documents, get_vector_store_stats, index_documents, index_obsidian_documents, vector_store
-    delete_all_documents,
-    get_vector_store_stats,
-    index_documents,
-    index_obsidian_documents,
-)
 from blueprints.users.decorators import admin_required
 
 rag_blueprint = Blueprint("rag_api", __name__, url_prefix="/api/rag")
@@ -37,7 +32,14 @@ async def trigger_index():
 async def trigger_reindex():
     """Clear and reindex all documents. Admin only."""
     try:
-        delete_all_documents()
+        # Clear existing documents
+        collection = vector_store._collection
+        all_docs = collection.get()
+
+        if all_docs["ids"]:
+            collection.delete(ids=all_docs["ids"])
+
+        # Reindex
         await index_documents()
         stats = get_vector_store_stats()
         return jsonify({"status": "success", "stats": stats})

blueprints/rag/logic.py

@@ -1,13 +1,11 @@
 import datetime
-import logging
 import os
 
 from dotenv import load_dotenv
+from langchain_chroma import Chroma
 from langchain_core.documents import Document
 from langchain_openai import OpenAIEmbeddings
-from langchain_postgres import PGVector
 from langchain_text_splitters import RecursiveCharacterTextSplitter
-from sqlalchemy import create_engine, text
 
 from .fetchers import PaperlessNGXService
 from utils.obsidian_service import ObsidianService
@@ -15,40 +13,13 @@ from utils.obsidian_service import ObsidianService
 # Load environment variables
 load_dotenv()
 
-logger = logging.getLogger(__name__)
-
 embeddings = OpenAIEmbeddings(model="text-embedding-3-small")
 
-# Convert Tortoise-style postgres:// URL to SQLAlchemy-style postgresql+psycopg://
+vector_store = Chroma(
-_db_url = os.getenv(
-    "DATABASE_URL", "postgres://raggr:raggr_dev_password@localhost:5432/raggr"
-)
-_pgvector_url = _db_url.replace("postgres://", "postgresql+psycopg://")
-
-# Lazy-initialized vector store (defers DB connection to first use)
-_vector_store = None
-
-
-def _get_vector_store() -> PGVector:
-    global _vector_store
-    if _vector_store is None:
-        _vector_store = PGVector(
-            embeddings=embeddings,
     collection_name="simba_docs",
-            connection=_pgvector_url,
+    embedding_function=embeddings,
-            use_jsonb=True,
+    persist_directory=os.getenv("CHROMADB_PATH", ""),
-            create_extension=False,  # created by docker init script
+)
-            async_mode=True,
-        )
-    return _vector_store
-
-
-def _get_engine():
-    """Get a SQLAlchemy engine for direct queries."""
-    if not hasattr(_get_engine, "_engine"):
-        _get_engine._engine = create_engine(_pgvector_url)
-    return _get_engine._engine
-
 
 text_splitter = RecursiveCharacterTextSplitter(
     chunk_size=1000,  # chunk size (characters)
@@ -57,22 +28,6 @@ text_splitter = RecursiveCharacterTextSplitter(
 )
 
 
-def _get_collection_id():
-    """Get the UUID of our collection from the langchain_pg_collection table."""
-    engine = _get_engine()
-    try:
-        with engine.connect() as conn:
-            result = conn.execute(
-                text("SELECT uuid FROM langchain_pg_collection WHERE name = :name"),
-                {"name": "simba_docs"},
-            )
-            row = result.fetchone()
-            return row[0] if row else None
-    except Exception:
-        # Table doesn't exist yet (first run before any indexing)
-        return None
-
-
 def date_to_epoch(date_str: str) -> float:
     split_date = date_str.split("-")
     date = datetime.datetime(
@@ -108,7 +63,6 @@ async def index_documents():
     documents = await fetch_documents_from_paperless_ngx()
 
     splits = text_splitter.split_documents(documents)
-    vector_store = _get_vector_store()
     await vector_store.aadd_documents(documents=splits)
 
 
@@ -138,17 +92,13 @@ async def fetch_obsidian_documents() -> list[Document]:
                     "filepath": parsed["filepath"],
                     "tags": parsed["tags"],
                     "created_at": parsed["metadata"].get("created_at"),
-                    **{
+                    **{k: v for k, v in parsed["metadata"].items() if k not in ["created_at", "created_by"]},
-                        k: v
-                        for k, v in parsed["metadata"].items()
-                        if k not in ["created_at", "created_by"]
-                    },
                 },
             )
             documents.append(document)
 
         except Exception as e:
-            logger.warning(f"Error reading {md_path}: {e}")
+            print(f"Error reading {md_path}: {e}")
             continue
 
     return documents
@@ -159,25 +109,26 @@ async def index_obsidian_documents():
 
     Deletes existing obsidian source chunks before re-indexing.
     """
+    obsidian_service = ObsidianService()
     documents = await fetch_obsidian_documents()
 
     if not documents:
-        logger.info("No Obsidian documents found to index")
+        print("No Obsidian documents found to index")
         return {"indexed": 0}
 
     # Delete existing obsidian chunks
-    delete_documents_by_metadata("source", "obsidian")
+    existing_results = vector_store.get(where={"source": "obsidian"})
+    if existing_results.get("ids"):
+        await vector_store.adelete(existing_results["ids"])
 
     # Split and index documents
     splits = text_splitter.split_documents(documents)
-    vector_store = _get_vector_store()
     await vector_store.aadd_documents(documents=splits)
 
     return {"indexed": len(documents)}
 
 
 async def query_vector_store(query: str):
-    vector_store = _get_vector_store()
     retrieved_docs = await vector_store.asimilarity_search(query, k=2)
     serialized = "\n\n".join(
         (f"Source: {doc.metadata}\nContent: {doc.page_content}")
@@ -186,79 +137,32 @@ async def query_vector_store(query: str):
     return serialized, retrieved_docs
 
 
-def delete_all_documents():
-    """Delete all documents from the vector store collection."""
-    collection_id = _get_collection_id()
-    if not collection_id:
-        return
-    engine = _get_engine()
-    with engine.connect() as conn:
-        conn.execute(
-            text("DELETE FROM langchain_pg_embedding WHERE collection_id = :cid"),
-            {"cid": collection_id},
-        )
-        conn.commit()
-
-
-def delete_documents_by_metadata(key: str, value: str):
-    """Delete documents matching a metadata key/value pair."""
-    collection_id = _get_collection_id()
-    if not collection_id:
-        return
-    engine = _get_engine()
-    with engine.connect() as conn:
-        conn.execute(
-            text(
-                "DELETE FROM langchain_pg_embedding "
-                "WHERE collection_id = :cid AND cmetadata->>:key = :value"
-            ),
-            {"cid": collection_id, "key": key, "value": value},
-        )
-        conn.commit()
-
-
 def get_vector_store_stats():
     """Get statistics about the vector store."""
-    collection_id = _get_collection_id()
+    collection = vector_store._collection
-    count = 0
+    count = collection.count()
-    if collection_id:
-        engine = _get_engine()
-        with engine.connect() as conn:
-            result = conn.execute(
-                text(
-                    "SELECT COUNT(*) FROM langchain_pg_embedding WHERE collection_id = :cid"
-                ),
-                {"cid": collection_id},
-            )
-            count = result.scalar()
     return {
         "total_documents": count,
-        "collection_name": "simba_docs",
+        "collection_name": collection.name,
     }
 
 
 def list_all_documents(limit: int = 10):
     """List documents in the vector store with their metadata."""
-    collection_id = _get_collection_id()
+    collection = vector_store._collection
-    if not collection_id:
+    results = collection.get(limit=limit, include=["metadatas", "documents"])
-        return []
 
-    engine = _get_engine()
-    with engine.connect() as conn:
-        result = conn.execute(
-            text(
-                "SELECT id, document, cmetadata FROM langchain_pg_embedding "
-                "WHERE collection_id = :cid LIMIT :limit"
-            ),
-            {"cid": collection_id, "limit": limit},
-        )
     documents = []
-        for row in result:
+    for i, doc_id in enumerate(results["ids"]):
         documents.append(
             {
-                    "id": str(row[0]),
+                "id": doc_id,
-                    "metadata": row[2],
+                "metadata": results["metadatas"][i]
-                    "content_preview": row[1][:200] if row[1] else None,
+                if results.get("metadatas")
+                else None,
+                "content_preview": results["documents"][i][:200]
+                if results.get("documents")
+                else None,
             }
         )
 

blueprints/users/oidc_service.py

@@ -35,7 +35,7 @@ class OIDCUserService:
                 claims.get("preferred_username") or claims.get("name") or user.username
             )
             # Update LDAP groups from claims
-            user.ldap_groups = claims.get("groups") or []
+            user.ldap_groups = claims.get("groups", [])
             await user.save()
             return user
 
@@ -48,7 +48,7 @@ class OIDCUserService:
                 user.oidc_subject = oidc_subject
                 user.auth_provider = "oidc"
                 user.password = None  # Clear password
-                user.ldap_groups = claims.get("groups") or []
+                user.ldap_groups = claims.get("groups", [])
                 await user.save()
                 return user
 
@@ -61,7 +61,7 @@ class OIDCUserService:
         )
 
         # Extract LDAP groups from claims
-        groups = claims.get("groups") or []
+        groups = claims.get("groups", [])
 
         user = await User.create(
             id=uuid4(),

docker-compose.yml

@@ -2,7 +2,7 @@ version: "3.8"
 
 services:
   postgres:
-    image: pgvector/pgvector:pg16
+    image: postgres:16-alpine
     ports:
       - "5432:5432"
     environment:
@@ -11,7 +11,6 @@ services:
       - POSTGRES_DB=${POSTGRES_DB:-raggr}
     volumes:
       - postgres_data:/var/lib/postgresql/data
-      - ./docker/init-pgvector.sql:/docker-entrypoint-initdb.d/init-pgvector.sql
     healthcheck:
       test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-raggr}"]
       interval: 10s
@@ -30,6 +29,7 @@ services:
       - PAPERLESS_TOKEN=${PAPERLESS_TOKEN}
       - BASE_URL=${BASE_URL}
       - OLLAMA_URL=${OLLAMA_URL:-http://localhost:11434}
+      - CHROMADB_PATH=/app/data/chromadb
       - OPENAI_API_KEY=${OPENAI_API_KEY}
       - JWT_SECRET_KEY=${JWT_SECRET_KEY}
       - LLAMA_SERVER_URL=${LLAMA_SERVER_URL}
@@ -66,8 +66,10 @@ services:
       postgres:
         condition: service_healthy
     volumes:
+      - chromadb_data:/app/data/chromadb
       - ./obvault:/app/data/obsidian
     restart: unless-stopped
 
 volumes:
+  chromadb_data:
   postgres_data:

docker/init-pgvector.sql

@@ -1 +0,0 @@
-CREATE EXTENSION IF NOT EXISTS vector;

main.py

@@ -0,0 +1,278 @@
+import argparse
+import datetime
+import logging
+import os
+import sqlite3
+import time
+
+from dotenv import load_dotenv
+
+import chromadb
+from utils.chunker import Chunker
+from utils.cleaner import pdf_to_image, summarize_pdf_image
+from llm import LLMClient
+from scripts.query import QueryGenerator
+from utils.request import PaperlessNGXService
+
+_dotenv_loaded = load_dotenv()
+
+client = chromadb.PersistentClient(path=os.getenv("CHROMADB_PATH", ""))
+simba_docs = client.get_or_create_collection(name="simba_docs2")
+feline_vet_lookup = client.get_or_create_collection(name="feline_vet_lookup")
+
+parser = argparse.ArgumentParser(
+    description="An LLM tool to query information about Simba <3"
+)
+
+parser.add_argument("query", type=str, help="questions about simba's health")
+parser.add_argument(
+    "--reindex", action="store_true", help="re-index the simba documents"
+)
+parser.add_argument("--classify", action="store_true", help="test classification")
+parser.add_argument("--index", help="index a file")
+
+ppngx = PaperlessNGXService()
+
+llm_client = LLMClient()
+
+
+def index_using_pdf_llm(doctypes):
+    logging.info("reindex data...")
+    files = ppngx.get_data()
+    for file in files:
+        document_id: int = file["id"]
+        pdf_path = ppngx.download_pdf_from_id(id=document_id)
+        image_paths = pdf_to_image(filepath=pdf_path)
+        logging.info(f"summarizing {file}")
+        generated_summary = summarize_pdf_image(filepaths=image_paths)
+        file["content"] = generated_summary
+
+    chunk_data(files, simba_docs, doctypes=doctypes)
+
+
+def date_to_epoch(date_str: str) -> float:
+    split_date = date_str.split("-")
+    date = datetime.datetime(
+        int(split_date[0]),
+        int(split_date[1]),
+        int(split_date[2]),
+        0,
+        0,
+        0,
+    )
+
+    return date.timestamp()
+
+
+def chunk_data(docs, collection, doctypes):
+    # Step 2: Create chunks
+    chunker = Chunker(collection)
+
+    logging.info(f"chunking {len(docs)} documents")
+    texts: list[str] = [doc["content"] for doc in docs]
+    with sqlite3.connect("database/visited.db") as conn:
+        to_insert = []
+        c = conn.cursor()
+        for index, text in enumerate(texts):
+            metadata = {
+                "created_date": date_to_epoch(docs[index]["created_date"]),
+                "filename": docs[index]["original_file_name"],
+                "document_type": doctypes.get(docs[index]["document_type"], ""),
+            }
+
+            if doctypes:
+                metadata["type"] = doctypes.get(docs[index]["document_type"])
+
+            chunker.chunk_document(
+                document=text,
+                metadata=metadata,
+            )
+            to_insert.append((docs[index]["id"],))
+
+        c.executemany(
+            "INSERT INTO indexed_documents (paperless_id) values (?)", to_insert
+        )
+        conn.commit()
+
+
+def chunk_text(texts: list[str], collection):
+    chunker = Chunker(collection)
+
+    for index, text in enumerate(texts):
+        metadata = {}
+        chunker.chunk_document(
+            document=text,
+            metadata=metadata,
+        )
+
+
+def classify_query(query: str, transcript: str) -> bool:
+    logging.info("Starting query generation")
+    qg_start = time.time()
+    qg = QueryGenerator()
+    query_type = qg.get_query_type(input=query, transcript=transcript)
+    logging.info(query_type)
+    qg_end = time.time()
+    logging.info(f"Query generation took {qg_end - qg_start:.2f} seconds")
+    return query_type == "Simba"
+
+
+def consult_oracle(
+    input: str,
+    collection,
+    transcript: str = "",
+):
+    chunker = Chunker(collection)
+
+    start_time = time.time()
+
+    # Ask
+    logging.info("Starting query generation")
+    qg_start = time.time()
+    qg = QueryGenerator()
+    doctype_query = qg.get_doctype_query(input=input)
+    # metadata_filter = qg.get_query(input)
+    metadata_filter = {**doctype_query}
+    logging.info(metadata_filter)
+    qg_end = time.time()
+    logging.info(f"Query generation took {qg_end - qg_start:.2f} seconds")
+
+    logging.info("Starting embedding generation")
+    embedding_start = time.time()
+    embeddings = chunker.embedding_fx(inputs=[input])
+    embedding_end = time.time()
+    logging.info(
+        f"Embedding generation took {embedding_end - embedding_start:.2f} seconds"
+    )
+
+    logging.info("Starting collection query")
+    query_start = time.time()
+    results = collection.query(
+        query_texts=[input],
+        query_embeddings=embeddings,
+        where=metadata_filter,
+    )
+    query_end = time.time()
+    logging.info(f"Collection query took {query_end - query_start:.2f} seconds")
+
+    # Generate
+    logging.info("Starting LLM generation")
+    llm_start = time.time()
+    system_prompt = "You are a helpful assistant that understands veterinary terms."
+    transcript_prompt = f"Here is the message transcript thus far {transcript}."
+    prompt = f"""Using the following data, help answer the user's query by providing as many details as possible.
+    Using this data: {results}. {transcript_prompt if len(transcript) > 0 else ""}
+    Respond to this prompt: {input}"""
+    output = llm_client.chat(prompt=prompt, system_prompt=system_prompt)
+    llm_end = time.time()
+    logging.info(f"LLM generation took {llm_end - llm_start:.2f} seconds")
+
+    total_time = time.time() - start_time
+    logging.info(f"Total consult_oracle execution took {total_time:.2f} seconds")
+
+    return output
+
+
+def llm_chat(input: str, transcript: str = "") -> str:
+    system_prompt = "You are a helpful assistant that understands veterinary terms."
+    transcript_prompt = f"Here is the message transcript thus far {transcript}."
+    prompt = f"""Answer the user in as if you were a cat named Simba. Don't act too catlike. Be assertive.
+    {transcript_prompt if len(transcript) > 0 else ""}
+    Respond to this prompt: {input}"""
+    output = llm_client.chat(prompt=prompt, system_prompt=system_prompt)
+    return output
+
+
+def paperless_workflow(input):
+    # Step 1: Get the text
+    ppngx = PaperlessNGXService()
+    docs = ppngx.get_data()
+
+    chunk_data(docs, collection=simba_docs)
+    consult_oracle(input, simba_docs)
+
+
+def consult_simba_oracle(input: str, transcript: str = ""):
+    is_simba_related = classify_query(query=input, transcript=transcript)
+
+    if is_simba_related:
+        logging.info("Query is related to simba")
+        return consult_oracle(
+            input=input,
+            collection=simba_docs,
+            transcript=transcript,
+        )
+
+    logging.info("Query is NOT related to simba")
+
+    return llm_chat(input=input, transcript=transcript)
+
+
+def filter_indexed_files(docs):
+    with sqlite3.connect("database/visited.db") as conn:
+        c = conn.cursor()
+        c.execute(
+            "CREATE TABLE IF NOT EXISTS indexed_documents (id INTEGER PRIMARY KEY AUTOINCREMENT, paperless_id INTEGER)"
+        )
+        c.execute("SELECT paperless_id FROM indexed_documents")
+        rows = c.fetchall()
+        conn.commit()
+
+    visited = {row[0] for row in rows}
+    return [doc for doc in docs if doc["id"] not in visited]
+
+
+def reindex():
+    with sqlite3.connect("database/visited.db") as conn:
+        c = conn.cursor()
+        # Ensure the table exists before trying to delete from it
+        c.execute(
+            "CREATE TABLE IF NOT EXISTS indexed_documents (id INTEGER PRIMARY KEY AUTOINCREMENT, paperless_id INTEGER)"
+        )
+        c.execute("DELETE FROM indexed_documents")
+        conn.commit()
+
+    # Delete all documents from the collection
+    all_docs = simba_docs.get()
+    if all_docs["ids"]:
+        simba_docs.delete(ids=all_docs["ids"])
+
+    logging.info("Fetching documents from Paperless-NGX")
+    ppngx = PaperlessNGXService()
+    docs = ppngx.get_data()
+    docs = filter_indexed_files(docs)
+    logging.info(f"Fetched {len(docs)} documents")
+
+    # Delete all chromadb data
+    ids = simba_docs.get(ids=None, limit=None, offset=0)
+    all_ids = ids["ids"]
+    if len(all_ids) > 0:
+        simba_docs.delete(ids=all_ids)
+
+    # Chunk documents
+    logging.info("Chunking documents now ...")
+    doctype_lookup = ppngx.get_doctypes()
+    chunk_data(docs, collection=simba_docs, doctypes=doctype_lookup)
+    logging.info("Done chunking documents")
+
+
+if __name__ == "__main__":
+    args = parser.parse_args()
+    if args.reindex:
+        reindex()
+
+    if args.classify:
+        consult_simba_oracle(input="yohohoho testing")
+        consult_simba_oracle(input="write an email")
+        consult_simba_oracle(input="how much does simba weigh")
+
+    if args.query:
+        logging.info("Consulting oracle ...")
+        print(
+            consult_oracle(
+                input=args.query,
+                collection=simba_docs,
+            )
+        )
+    else:
+        logging.info("please provide a query")

migrations/models/5_20260409215154_add_user_memories.py

@@ -1,112 +0,0 @@
-from tortoise import BaseDBAsyncClient
-
-RUN_IN_TRANSACTION = True
-
-
-async def upgrade(db: BaseDBAsyncClient) -> str:
-    return """
-        CREATE TABLE IF NOT EXISTS "user_memories" (
-    "id" UUID NOT NULL PRIMARY KEY,
-    "content" TEXT NOT NULL,
-    "created_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    "updated_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    "user_id" UUID NOT NULL REFERENCES "users" ("id") ON DELETE CASCADE
-);
-        CREATE TABLE IF NOT EXISTS "email_accounts" (
-    "id" UUID NOT NULL PRIMARY KEY,
-    "email_address" VARCHAR(255) NOT NULL UNIQUE,
-    "display_name" VARCHAR(255),
-    "imap_host" VARCHAR(255) NOT NULL,
-    "imap_port" INT NOT NULL DEFAULT 993,
-    "imap_username" VARCHAR(255) NOT NULL,
-    "imap_password" TEXT NOT NULL,
-    "is_active" BOOL NOT NULL DEFAULT True,
-    "last_error" TEXT,
-    "created_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    "updated_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    "user_id" UUID NOT NULL REFERENCES "users" ("id") ON DELETE CASCADE
-);
-COMMENT ON TABLE "email_accounts" IS 'Email account configuration for IMAP connections.';
-        CREATE TABLE IF NOT EXISTS "emails" (
-    "id" UUID NOT NULL PRIMARY KEY,
-    "message_id" VARCHAR(255) NOT NULL UNIQUE,
-    "subject" VARCHAR(500) NOT NULL,
-    "from_address" VARCHAR(255) NOT NULL,
-    "to_address" TEXT NOT NULL,
-    "date" TIMESTAMPTZ NOT NULL,
-    "body_text" TEXT,
-    "body_html" TEXT,
-    "chromadb_doc_id" VARCHAR(255),
-    "created_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    "expires_at" TIMESTAMPTZ NOT NULL,
-    "account_id" UUID NOT NULL REFERENCES "email_accounts" ("id") ON DELETE CASCADE
-);
-CREATE INDEX IF NOT EXISTS "idx_emails_message_981ddd" ON "emails" ("message_id");
-COMMENT ON TABLE "emails" IS 'Email message metadata and content.';
-        CREATE TABLE IF NOT EXISTS "email_sync_status" (
-    "id" UUID NOT NULL PRIMARY KEY,
-    "last_sync_date" TIMESTAMPTZ,
-    "last_message_uid" INT NOT NULL DEFAULT 0,
-    "message_count" INT NOT NULL DEFAULT 0,
-    "consecutive_failures" INT NOT NULL DEFAULT 0,
-    "last_failure_date" TIMESTAMPTZ,
-    "updated_at" TIMESTAMPTZ NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    "account_id" UUID NOT NULL REFERENCES "email_accounts" ("id") ON DELETE CASCADE
-);
-COMMENT ON TABLE "email_sync_status" IS 'Tracks sync progress and state per email account.';"""
-
-
-async def downgrade(db: BaseDBAsyncClient) -> str:
-    return """
-        DROP TABLE IF EXISTS "user_memories";
-        DROP TABLE IF EXISTS "email_accounts";
-        DROP TABLE IF EXISTS "emails";
-        DROP TABLE IF EXISTS "email_sync_status";"""
-
-
-MODELS_STATE = (
-    "eJztXGtv2zYU/SuCPrVAFjTPbcUwwE7czVudDLGz9ZFCoCXa1ixRGkk1NYr+911Skq0HZV"
-    "t+RUr1oU1C8lLU4SV57tGVvuquZ2GHHV955DOmDHHbI/pr7atOkIvhF2X9kaYj31/UigKO"
-    "ho40MBMtZQ0aMk6RyaFyhByGocjCzKS2H12MBI4jCj0TGtpkvCgKiP1fgA3ujTGfYAoVHz"
-    "9BsU0s/AWz+E9/aoxs7FipcduWuLYsN/jMl2X3993rN7KluNzQMD0ncMmitT/jE4/MmweB"
-    "bR0LG1E3xgRTxLGVuA0xyui246JwxFDAaYDnQ7UWBRYeocARYOi/jAJiCgw0eSXx3/mveg"
-    "l4AGoBrU24wOLrt/CuFvcsS3VxqavfW3cvzi5fyrv0GB9TWSkR0b9JQ8RRaCpxXQApf+ag"
-    "vJogqoYybp8BEwa6CYxxwQLHhQ/FQMYAbYaa7qIvhoPJmE/gz9OLiyUw/t26k0hCKwmlB3"
-    "4dev1NVHUa1glIFxCaFItbNhDPA3kNNdx2sRrMtGUGUisyPY5/qSjAcA/WLXFm0SJYgu+g"
-    "2+v0B63eX+JOXMb+cyRErUFH1JzK0lmm9MVlZirmnWj/dAe/a+JP7cPtTSfr+/N2gw+6GB"
-    "MKuGcQ79FAVmK9xqUxMKmJDXxrw4lNWzYT+6QTGw0+Ma8MU6PcCZIw2eIYicZ2wEnc/NAQ"
-    "R+9oqjwzBBh58N54FNtj8ieeSQi7MA5ETNVhEZGO+6ibqoK2KF2MgqLHORtJOgXcHdwT5u"
-    "Hp2epfta47usRwiMzpI6KWUQCmixlDY8zygLYjyzd/3mFnTs3UWCYJXC/ssZq7ShG2Eivv"
-    "1EtglEIvX+WeutkSROC+reja4kpL0FnBghMgrkeGjeRENqS41qSY4y+KI38ApWoo4/Z1Ic"
-    "XLjvLOu0HqFI+p74te693L1En+9vbmt7h5gipfvb1tNwz5ORKpPENmPkZTFRkQAWSHBG6O"
-    "CqRmN2H+xEtHv+937l5r4kR/IP1ur916rTHbHSJ9vSlORZknr9YIMk9eFcaYoiq9gGwXTh"
-    "ZjimdlQvWU0Ub4Hp56pYG8ODldA0loVQilrMtsRslDu9yRqTDd5flZ03DAzIiHW4YFWS2y"
-    "siiujA8U7lI2TtgnKxbxVw+7Hp3pCjKcqF3KgWUQ5IqGdsN9nwH3hYtwTErR34RJw4AbBv"
-    "xdMeBGI34WE1sdjbham2FdROIKs8AtVOJ9s78i3rea8TVMr/5MT8xj2cf/SZu6cL0DpAD4"
-    "iLFHjyo8s20TRGdqMJNWGTCHMx5GU5VTaJaA1xa8N3m6A2Tt7k3r7r2aOsftk37bfj/otD"
-    "LoYhfZThkvnRvsxkVXr/hdOujJq/Xkw2X6YU5AfJwgzmBLN0jgDosEWzWYCtOdiImHRfVs"
-    "HVDPijE9y0EqnczARNyeauF7noMRWeKgSdvs8gfjfW2mZY/qEuv/9vZtav23u9nQ+L7X7o"
-    "DzSpihkR1Soe7NQAnuxEUmcIQpVuiKK1Z/xraGHntyuc42kI2QErvAZdZjPdsyDRYM/8Wm"
-    "IlotBjRrV0Mw93LqQ/w4MXzqfbatcltqzvBwVEp3PBM5W3DRzBOadbbVi+Jt9SK3rToW8o"
-    "0x9QJfkRLzR//2Rg1pxiwD6D2Bu/xo2SY/0hyb8U97g/fjp/3wfHHny1XJrACZIVaig0aV"
-    "fJbiVaNKPtOJnSfG5VShVVmFudc0dpNaWOWINJ9SmFwRySeUm2ORfihaPc9fC4qQHyPT9A"
-    "JhthUgHdFXK+yqZpDsU1yVsOgKdbUTKxPF8qqcnvX0VV12p0WZp/CTI6H2aYhYWvRQ9ljP"
-    "oLSOzQN5IH3uwbal+YgybGlyUJps+GjzCYTTP1hoplEs2sNgjrW3NpkyjXva1YR6LrpuP5"
-    "CRR7XPEDPAD4YRNSeaiXw0tCHsg5UoR9bowDvih1vowJErKJ92Fccwaas6Cm17iQk3CK+3"
-    "jayfXFK/WEuxvFiiWF7kFcsR7CKCGIEfK86oYjSzdvWEdC++CbyyENAlye1eHeE8dIKPiI"
-    "jKxlqxTT2jrJpEVfFtL42Xh541M8q+9ZEyqkl+9aGXhcRowl3F47sVwMZGDbDqhELJsuGK"
-    "MLSSzE1hWhOQm5f5G+VsU0kUf/Ft6G2DiU1b1nNiazKRax3WkXJVMjszbdUkaMaA5DEsna"
-    "NZXxHwKJOrmXaSKqVrpjAuEhYTc7BCX0zJv+vqjJGNkAlH9jigUhvWhMrX7bX+EsUES7mL"
-    "FamOJXpIaJBzK4otITfCGEMVEhOTznxwNC1OpTtK9KExzDlcnh09EKFuxt2AO/OAHWv9wP"
-    "c9ypnmgovZvoPjFkzzMZXvgjYaZUU0yshpy8tBOcNGqYwVC5v5DpoZZVOAs3ZN7JB4S9s3"
-    "JuDYZeBMGdVFXTsUmGJ/zoPZJQXCQcomg6W9P27y889nW0Apv0Xzw+nJ+Y/nP51dnv8ETe"
-    "RQ5iU/LgE3nzkpMdgktT9n2DhjxhkLk/w7MQ8p1rRyPdQF3UMLWzYE2sBHPit8d2lKdcru"
-    "gOnU84O/wtnUDmLcwJR6iizVYpdNW9XkmG9e7G70wiaFspnY5sXu5sXu6r7YnRE2dpGEWS"
-    "8s0zlTM2IaoSq3AyD60Ft/3lmNINm7fJxApkhBToO3SkTOTNxqHXkA1VOmCTvNp57YdJjM"
-    "PBWdYCm74qRQnNeRS/cgdOSegBn+MU1w2tBYnL1g4/pHYSF0ZkJf2JqnxsJOGCnHI+gwoF"
-    "gTdzeFgYg0Vxaqx5oNsR92MfTvhB0LA8matQn86kDzRkWuiIosIxrptJuka+Wtd8DtqhUh"
-    "VYjKrfUoWE5JnIkcqNZJoVaoMj2cZPhqC2q+Y8EwxqDgaXAhgDm77xI90T02AyE8GdExoS"
-    "AxhSAWmX+XWMolGaGw+Q6d7aDZpJ94k26UlOeppDR5WM8sD2vfSQ31z8JqYWqbE10RPUc1"
-    "R8uCZrRoU5kv5xU/S1+TEUcT+KTJMjvhIcVho3j9Xflt8+KH6QmTujzoPcQHc2BplAAxal"
-    "5PAPfyGbfCj3MXfxin+OPcB/sozt4O3Z19FKfENzZ2f7x8+x8fHBMe"
-)

pyproject.toml

@@ -5,8 +5,7 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [
-    "langchain-postgres>=0.0.13",
+    "chromadb>=1.1.0",
-    "psycopg[binary]>=3.1.0",
     "python-dotenv>=1.0.0",
     "flask>=3.1.2",
     "httpx>=0.28.1",
@@ -31,6 +30,7 @@ dependencies = [
     "asyncpg>=0.30.0",
     "langchain-openai>=1.1.6",
     "langchain>=1.2.0",
+    "langchain-chroma>=1.0.0",
     "langchain-community>=0.4.1",
     "jq>=1.10.0",
     "tavily-python>=0.7.17",
@@ -42,17 +42,6 @@ dependencies = [
     "aioboto3>=13.0.0",
 ]
 
-[project.optional-dependencies]
-test = [
-    "pytest>=8.0.0",
-    "pytest-asyncio>=0.25.0",
-    "pytest-cov>=6.0.0",
-]
-
-[tool.pytest.ini_options]
-testpaths = ["tests"]
-asyncio_mode = "auto"
-
 [tool.aerich]
 tortoise_orm = "config.db.TORTOISE_CONFIG"
 location = "./migrations"

raggr-frontend/src/components/ChatScreen.tsx

@@ -1,4 +1,4 @@
-import { useCallback, useEffect, useState, useRef } from "react";
+import { useEffect, useState, useRef } from "react";
 import { LogOut, Shield, PanelLeftClose, PanelLeftOpen, Menu, X } from "lucide-react";
 import { conversationService } from "../api/conversationService";
 import { userService } from "../api/userService";
@@ -63,13 +63,9 @@ export const ChatScreen = ({ setAuthenticated }: ChatScreenProps) => {
   const abortControllerRef = useRef<AbortController | null>(null);
   const simbaAnswers = ["meow.", "hiss...", "purrrrrr", "yowOWROWWowowr"];
 
-  const scrollToBottom = useCallback(() => {
+  const scrollToBottom = () => {
-    requestAnimationFrame(() => {
+    messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
-      messagesEndRef.current?.scrollIntoView({
+  };
-        behavior: isLoading ? "instant" : "smooth",
-      });
-    });
-  }, [isLoading]);
 
   useEffect(() => {
     isMountedRef.current = true;
@@ -120,7 +116,21 @@ export const ChatScreen = ({ setAuthenticated }: ChatScreenProps) => {
     scrollToBottom();
   }, [messages]);
 
-  const handleQuestionSubmit = useCallback(async () => {
+  useEffect(() => {
+    const load = async () => {
+      if (!selectedConversation) return;
+      try {
+        const conv = await conversationService.getConversation(selectedConversation.id);
+        setSelectedConversation({ id: conv.id, title: conv.name });
+        setMessages(conv.messages.map((m) => ({ text: m.text, speaker: m.speaker, image_key: m.image_key })));
+      } catch (err) {
+        console.error("Failed to load messages:", err);
+      }
+    };
+    load();
+  }, [selectedConversation?.id]);
+
+  const handleQuestionSubmit = async () => {
     if ((!query.trim() && !pendingImage) || isLoading) return;
 
     let activeConversation = selectedConversation;
@@ -201,28 +211,22 @@ export const ChatScreen = ({ setAuthenticated }: ChatScreenProps) => {
         }
       }
     } finally {
-      if (isMountedRef.current) {
+      if (isMountedRef.current) setIsLoading(false);
-        setIsLoading(false);
-        loadConversations();
-      }
       abortControllerRef.current = null;
     }
-  }, [query, pendingImage, isLoading, selectedConversation, simbaMode, messages, setAuthenticated]);
+  };
 
-  const handleQueryChange = useCallback((event: React.ChangeEvent<HTMLTextAreaElement>) => {
+  const handleQueryChange = (event: React.ChangeEvent<HTMLTextAreaElement>) => {
     setQuery(event.target.value);
-  }, []);
+  };
 
-  const handleKeyDown = useCallback((event: React.ChangeEvent<HTMLTextAreaElement>) => {
+  const handleKeyDown = (event: React.ChangeEvent<HTMLTextAreaElement>) => {
     const kev = event as unknown as React.KeyboardEvent<HTMLTextAreaElement>;
     if (kev.key === "Enter" && !kev.shiftKey) {
       kev.preventDefault();
       handleQuestionSubmit();
     }
-  }, [handleQuestionSubmit]);
+  };
-
-  const handleImageSelect = useCallback((file: File) => setPendingImage(file), []);
-  const handleClearImage = useCallback(() => setPendingImage(null), []);
 
   const handleLogout = () => {
     localStorage.removeItem("access_token");
@@ -376,8 +380,8 @@ export const ChatScreen = ({ setAuthenticated }: ChatScreenProps) => {
                 setSimbaMode={setSimbaMode}
                 isLoading={isLoading}
                 pendingImage={pendingImage}
-                onImageSelect={handleImageSelect}
+                onImageSelect={(file) => setPendingImage(file)}
-                onClearImage={handleClearImage}
+                onClearImage={() => setPendingImage(null)}
               />
             </div>
           </div>
@@ -412,7 +416,7 @@ export const ChatScreen = ({ setAuthenticated }: ChatScreenProps) => {
               </div>
             </div>
 
-            <footer className="border-t border-sand-light/40 bg-cream">
+            <footer className="border-t border-sand-light/40 bg-cream/80 backdrop-blur-sm">
               <div className="max-w-2xl mx-auto px-4 py-3">
                 <MessageInput
                   query={query}
@@ -421,9 +425,6 @@ export const ChatScreen = ({ setAuthenticated }: ChatScreenProps) => {
                   handleQuestionSubmit={handleQuestionSubmit}
                   setSimbaMode={setSimbaMode}
                   isLoading={isLoading}
-                  pendingImage={pendingImage}
-                  onImageSelect={(file) => setPendingImage(file)}
-                  onClearImage={() => setPendingImage(null)}
                 />
               </div>
             </footer>

raggr-frontend/src/components/MessageInput.tsx

@@ -1,4 +1,4 @@
-import React, { useEffect, useMemo, useRef, useState } from "react";
+import { useRef, useState } from "react";
 import { ArrowUp, ImagePlus, X } from "lucide-react";
 import { cn } from "../lib/utils";
 import { Textarea } from "./ui/textarea";
@@ -15,7 +15,7 @@ type MessageInputProps = {
   onClearImage: () => void;
 };
 
-export const MessageInput = React.memo(({
+export const MessageInput = ({
   query,
   handleKeyDown,
   handleQueryChange,
@@ -29,18 +29,6 @@ export const MessageInput = React.memo(({
   const [simbaMode, setLocalSimbaMode] = useState(false);
   const fileInputRef = useRef<HTMLInputElement>(null);
 
-  // Create blob URL once per file, revoke on cleanup
-  const previewUrl = useMemo(
-    () => (pendingImage ? URL.createObjectURL(pendingImage) : null),
-    [pendingImage],
-  );
-
-  useEffect(() => {
-    return () => {
-      if (previewUrl) URL.revokeObjectURL(previewUrl);
-    };
-  }, [previewUrl]);
-
   const toggleSimbaMode = () => {
     const next = !simbaMode;
     setLocalSimbaMode(next);
@@ -71,7 +59,7 @@ export const MessageInput = React.memo(({
         <div className="px-3 pt-3">
           <div className="relative inline-block">
             <img
-              src={previewUrl!}
+              src={URL.createObjectURL(pendingImage)}
               alt="Pending upload"
               className="h-20 rounded-lg object-cover border border-sand"
             />
@@ -157,4 +145,4 @@ export const MessageInput = React.memo(({
       </div>
     </div>
   );
-});
+};

scripts/manage_vectorstore.py

@@ -6,19 +6,19 @@ import asyncio
 import sys
 
 from blueprints.rag.logic import (
-    delete_all_documents,
     get_vector_store_stats,
     index_documents,
     list_all_documents,
+    vector_store,
 )
 
 
 def stats():
     """Show vector store statistics."""
-    s = get_vector_store_stats()
+    stats = get_vector_store_stats()
     print("=== Vector Store Statistics ===")
-    print(f"Collection: {s['collection_name']}")
+    print(f"Collection: {stats['collection_name']}")
-    print(f"Total Documents: {s['total_documents']}")
+    print(f"Total Documents: {stats['total_documents']}")
 
 
 async def index():
@@ -26,15 +26,23 @@ async def index():
     print("Starting indexing process...")
     print("Fetching documents from Paperless-NGX...")
     await index_documents()
-    print("Indexing complete!")
+    print("✓ Indexing complete!")
     stats()
 
 
 async def reindex():
     """Clear and reindex all documents."""
     print("Clearing existing documents...")
-    delete_all_documents()
+    collection = vector_store._collection
-    print("Cleared")
+    all_docs = collection.get()
+
+    if all_docs["ids"]:
+        print(f"Deleting {len(all_docs['ids'])} existing documents...")
+        collection.delete(ids=all_docs["ids"])
+        print("✓ Cleared")
+    else:
+        print("Collection is already empty")
+
     await index()
 
 
@@ -105,7 +113,7 @@ Examples:
         print("\n\nOperation cancelled by user")
         sys.exit(1)
     except Exception as e:
-        print(f"\nError: {e}", file=sys.stderr)
+        print(f"\n❌ Error: {e}", file=sys.stderr)
         sys.exit(1)
 
 

scripts/petmd_scrape_index.py

@@ -0,0 +1,24 @@
+from bs4 import BeautifulSoup
+import chromadb
+import httpx
+
+client = chromadb.PersistentClient(path="/Users/ryanchen/Programs/raggr/chromadb")
+
+# Scrape
+BASE_URL = "https://www.vet.cornell.edu"
+LIST_URL = "/departments-centers-and-institutes/cornell-feline-health-center/health-information/feline-health-topics"
+
+QUERY_URL = BASE_URL + LIST_URL
+r = httpx.get(QUERY_URL)
+soup = BeautifulSoup(r.text)
+
+container = soup.find("div", class_="field-body")
+a_s = container.find_all("a", href=True)
+
+new_texts = []
+
+for link in a_s:
+    endpoint = link["href"]
+    query_url = BASE_URL + endpoint
+    r2 = httpx.get(query_url)
+    article_soup = BeautifulSoup(r2.text)

startup-dev.sh

@@ -1,6 +1,9 @@
 #!/bin/bash
 set -e
 
+echo "Initializing directories..."
+mkdir -p /app/data/chromadb
+
 echo "Rebuilding frontend..."
 cd /app/raggr-frontend
 yarn build

tests/conftest.py

@@ -1,11 +0,0 @@
-import os
-import sys
-
-# Ensure project root is on the path so imports work
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
-
-# Set FERNET_KEY for tests that import email models (EncryptedTextField needs it at import time)
-if "FERNET_KEY" not in os.environ:
-    from cryptography.fernet import Fernet
-
-    os.environ["FERNET_KEY"] = Fernet.generate_key().decode()

tests/unit/test_crypto_service.py

@@ -1,91 +0,0 @@
-"""Tests for encryption/decryption in blueprints/email/crypto_service.py."""
-
-import os
-from unittest.mock import patch
-
-import pytest
-from cryptography.fernet import Fernet
-
-
-# Generate a valid key for testing
-TEST_FERNET_KEY = Fernet.generate_key().decode()
-
-
-class TestEncryptedTextField:
-    @pytest.fixture
-    def field(self):
-        with patch.dict(os.environ, {"FERNET_KEY": TEST_FERNET_KEY}):
-            from blueprints.email.crypto_service import EncryptedTextField
-
-            return EncryptedTextField()
-
-    def test_encrypt_decrypt_roundtrip(self, field):
-        original = "my secret password"
-        encrypted = field.to_db_value(original, None)
-        decrypted = field.to_python_value(encrypted)
-        assert decrypted == original
-        assert encrypted != original
-
-    def test_none_passthrough(self, field):
-        assert field.to_db_value(None, None) is None
-        assert field.to_python_value(None) is None
-
-    def test_unicode_roundtrip(self, field):
-        original = "Hello 世界 🐱"
-        encrypted = field.to_db_value(original, None)
-        decrypted = field.to_python_value(encrypted)
-        assert decrypted == original
-
-    def test_empty_string_roundtrip(self, field):
-        encrypted = field.to_db_value("", None)
-        decrypted = field.to_python_value(encrypted)
-        assert decrypted == ""
-
-    def test_long_text_roundtrip(self, field):
-        original = "x" * 10000
-        encrypted = field.to_db_value(original, None)
-        decrypted = field.to_python_value(encrypted)
-        assert decrypted == original
-
-    def test_different_encryptions_differ(self, field):
-        """Fernet includes a timestamp, so two encryptions of the same value differ."""
-        e1 = field.to_db_value("same", None)
-        e2 = field.to_db_value("same", None)
-        assert e1 != e2  # Different ciphertexts
-        assert field.to_python_value(e1) == field.to_python_value(e2) == "same"
-
-    def test_wrong_key_fails(self, field):
-        encrypted = field.to_db_value("secret", None)
-
-        # Create a field with a different key
-        other_key = Fernet.generate_key().decode()
-        with patch.dict(os.environ, {"FERNET_KEY": other_key}):
-            from blueprints.email.crypto_service import EncryptedTextField
-
-            other_field = EncryptedTextField()
-
-        with pytest.raises(Exception):
-            other_field.to_python_value(encrypted)
-
-
-class TestValidateFernetKey:
-    def test_valid_key(self):
-        with patch.dict(os.environ, {"FERNET_KEY": TEST_FERNET_KEY}):
-            from blueprints.email.crypto_service import validate_fernet_key
-
-            validate_fernet_key()  # Should not raise
-
-    def test_missing_key(self):
-        with patch.dict(os.environ, {}, clear=True):
-            os.environ.pop("FERNET_KEY", None)
-            from blueprints.email.crypto_service import validate_fernet_key
-
-            with pytest.raises(ValueError, match="not set"):
-                validate_fernet_key()
-
-    def test_invalid_key(self):
-        with patch.dict(os.environ, {"FERNET_KEY": "not-a-valid-key"}):
-            from blueprints.email.crypto_service import validate_fernet_key
-
-            with pytest.raises(ValueError, match="validation failed"):
-                validate_fernet_key()

tests/unit/test_email_helpers.py

@@ -1,38 +0,0 @@
-"""Tests for email helper functions in blueprints/email/helpers.py."""
-
-from blueprints.email.helpers import generate_email_token, get_user_email_address
-
-
-class TestGenerateEmailToken:
-    def test_returns_16_char_hex(self):
-        token = generate_email_token("user-123", "my-secret")
-        assert len(token) == 16
-        assert all(c in "0123456789abcdef" for c in token)
-
-    def test_deterministic(self):
-        t1 = generate_email_token("user-123", "my-secret")
-        t2 = generate_email_token("user-123", "my-secret")
-        assert t1 == t2
-
-    def test_different_users_different_tokens(self):
-        t1 = generate_email_token("user-1", "secret")
-        t2 = generate_email_token("user-2", "secret")
-        assert t1 != t2
-
-    def test_different_secrets_different_tokens(self):
-        t1 = generate_email_token("user-1", "secret-a")
-        t2 = generate_email_token("user-1", "secret-b")
-        assert t1 != t2
-
-
-class TestGetUserEmailAddress:
-    def test_formats_correctly(self):
-        addr = get_user_email_address("abc123", "example.com")
-        assert addr == "ask+abc123@example.com"
-
-    def test_preserves_token(self):
-        token = "deadbeef12345678"
-        addr = get_user_email_address(token, "mail.test.org")
-        assert token in addr
-        assert addr.startswith("ask+")
-        assert "@mail.test.org" in addr

tests/unit/test_obsidian_service.py

@@ -1,259 +0,0 @@
-"""Tests for ObsidianService markdown parsing and file operations."""
-
-import os
-from datetime import datetime
-from pathlib import Path
-from unittest.mock import patch
-
-import pytest
-
-# Set vault path before importing so __init__ validation passes
-_test_vault_dir = None
-
-
-@pytest.fixture(autouse=True)
-def vault_dir(tmp_path):
-    """Create a temporary vault directory with a sample .md file."""
-    global _test_vault_dir
-    _test_vault_dir = tmp_path
-
-    # Create a sample markdown file so vault validation passes
-    sample = tmp_path / "sample.md"
-    sample.write_text("# Sample\nHello world")
-
-    with patch.dict(os.environ, {"OBSIDIAN_VAULT_PATH": str(tmp_path)}):
-        yield tmp_path
-
-
-@pytest.fixture
-def service(vault_dir):
-    from utils.obsidian_service import ObsidianService
-
-    return ObsidianService()
-
-
-class TestParseMarkdown:
-    def test_extracts_frontmatter(self, service):
-        content = "---\ntitle: Test Note\ntags: [cat, vet]\n---\n\nBody content"
-        result = service.parse_markdown(content)
-        assert result["metadata"]["title"] == "Test Note"
-        assert result["metadata"]["tags"] == ["cat", "vet"]
-
-    def test_no_frontmatter(self, service):
-        content = "Just body content with no frontmatter"
-        result = service.parse_markdown(content)
-        assert result["metadata"] == {}
-        assert "Just body content" in result["content"]
-
-    def test_invalid_yaml_frontmatter(self, service):
-        content = "---\n: invalid: yaml: [[\n---\n\nBody"
-        result = service.parse_markdown(content)
-        assert result["metadata"] == {}
-
-    def test_extracts_tags(self, service):
-        content = "Some text with #tag1 and #tag2 here"
-        result = service.parse_markdown(content)
-        assert "tag1" in result["tags"]
-        assert "tag2" in result["tags"]
-
-    def test_extracts_wikilinks(self, service):
-        content = "Link to [[Other Note]] and [[Another Page]]"
-        result = service.parse_markdown(content)
-        assert "Other Note" in result["wikilinks"]
-        assert "Another Page" in result["wikilinks"]
-
-    def test_extracts_embeds(self, service):
-        content = "An embed [[!my_embed]] here"
-        result = service.parse_markdown(content)
-        assert "my_embed" in result["embeds"]
-
-    def test_cleans_wikilinks_from_content(self, service):
-        content = "Text with [[link]] included"
-        result = service.parse_markdown(content)
-        assert "[[" not in result["content"]
-        assert "]]" not in result["content"]
-
-    def test_filepath_passed_through(self, service):
-        result = service.parse_markdown("text", filepath=Path("/vault/note.md"))
-        assert result["filepath"] == "/vault/note.md"
-
-    def test_filepath_none_by_default(self, service):
-        result = service.parse_markdown("text")
-        assert result["filepath"] is None
-
-    def test_empty_content(self, service):
-        result = service.parse_markdown("")
-        assert result["metadata"] == {}
-        assert result["tags"] == []
-        assert result["wikilinks"] == []
-        assert result["embeds"] == []
-
-
-class TestGetDailyNotePath:
-    def test_formats_path_correctly(self, service):
-        date = datetime(2026, 3, 15)
-        path = service.get_daily_note_path(date)
-        assert path == "journal/2026/2026-03-15.md"
-
-    def test_defaults_to_today(self, service):
-        path = service.get_daily_note_path()
-        today = datetime.now()
-        assert today.strftime("%Y-%m-%d") in path
-        assert path.startswith(f"journal/{today.strftime('%Y')}/")
-
-
-class TestWalkVault:
-    def test_finds_markdown_files(self, service, vault_dir):
-        (vault_dir / "note1.md").write_text("# Note 1")
-        (vault_dir / "subdir").mkdir()
-        (vault_dir / "subdir" / "note2.md").write_text("# Note 2")
-
-        files = service.walk_vault()
-        filenames = [f.name for f in files]
-        assert "sample.md" in filenames
-        assert "note1.md" in filenames
-        assert "note2.md" in filenames
-
-    def test_excludes_obsidian_dir(self, service, vault_dir):
-        obsidian_dir = vault_dir / ".obsidian"
-        obsidian_dir.mkdir()
-        (obsidian_dir / "config.md").write_text("config")
-
-        files = service.walk_vault()
-        filenames = [f.name for f in files]
-        assert "config.md" not in filenames
-
-    def test_ignores_non_md_files(self, service, vault_dir):
-        (vault_dir / "image.png").write_bytes(b"\x89PNG")
-
-        files = service.walk_vault()
-        filenames = [f.name for f in files]
-        assert "image.png" not in filenames
-
-
-class TestCreateNote:
-    def test_creates_file(self, service, vault_dir):
-        path = service.create_note("My Test Note", "Body content")
-        full_path = vault_dir / path
-        assert full_path.exists()
-
-    def test_sanitizes_title(self, service, vault_dir):
-        path = service.create_note("Hello World! @#$", "Body")
-        assert "hello-world" in path
-        assert "@" not in path
-        assert "#" not in path
-
-    def test_includes_frontmatter(self, service, vault_dir):
-        path = service.create_note("Test", "Body", tags=["cat", "vet"])
-        full_path = vault_dir / path
-        content = full_path.read_text()
-        assert "---" in content
-        assert "created_by: simbarag" in content
-        assert "cat" in content
-        assert "vet" in content
-
-    def test_custom_folder(self, service, vault_dir):
-        path = service.create_note("Test", "Body", folder="custom/subfolder")
-        assert path.startswith("custom/subfolder/")
-        assert (vault_dir / path).exists()
-
-
-class TestDailyNoteTasks:
-    def test_get_tasks_from_daily_note(self, service, vault_dir):
-        # Create a daily note with tasks
-        date = datetime(2026, 1, 15)
-        rel_path = service.get_daily_note_path(date)
-        note_path = vault_dir / rel_path
-        note_path.parent.mkdir(parents=True, exist_ok=True)
-        note_path.write_text(
-            "---\nmodified: 2026-01-15\n---\n"
-            "### tasks\n\n"
-            "- [ ] Feed the cat\n"
-            "- [x] Clean litter box\n"
-            "- [ ] Buy cat food\n\n"
-            "### log\n"
-        )
-
-        result = service.get_daily_tasks(date)
-        assert result["found"] is True
-        assert len(result["tasks"]) == 3
-        assert result["tasks"][0] == {"text": "Feed the cat", "done": False}
-        assert result["tasks"][1] == {"text": "Clean litter box", "done": True}
-        assert result["tasks"][2] == {"text": "Buy cat food", "done": False}
-
-    def test_get_tasks_no_note(self, service):
-        date = datetime(2099, 12, 31)
-        result = service.get_daily_tasks(date)
-        assert result["found"] is False
-        assert result["tasks"] == []
-
-    def test_add_task_creates_note(self, service, vault_dir):
-        date = datetime(2026, 6, 1)
-        result = service.add_task_to_daily_note("Walk the cat", date)
-        assert result["success"] is True
-        assert result["created_note"] is True
-
-        # Verify file was created with the task
-        note_path = vault_dir / result["path"]
-        content = note_path.read_text()
-        assert "- [ ] Walk the cat" in content
-
-    def test_add_task_to_existing_note(self, service, vault_dir):
-        date = datetime(2026, 6, 2)
-        rel_path = service.get_daily_note_path(date)
-        note_path = vault_dir / rel_path
-        note_path.parent.mkdir(parents=True, exist_ok=True)
-        note_path.write_text(
-            "---\nmodified: 2026-06-02\n---\n"
-            "### tasks\n\n"
-            "- [ ] Existing task\n\n"
-            "### log\n"
-        )
-
-        result = service.add_task_to_daily_note("New task", date)
-        assert result["success"] is True
-        assert result["created_note"] is False
-
-        content = note_path.read_text()
-        assert "- [ ] Existing task" in content
-        assert "- [ ] New task" in content
-
-    def test_complete_task_exact_match(self, service, vault_dir):
-        date = datetime(2026, 6, 3)
-        rel_path = service.get_daily_note_path(date)
-        note_path = vault_dir / rel_path
-        note_path.parent.mkdir(parents=True, exist_ok=True)
-        note_path.write_text("### tasks\n\n" "- [ ] Feed the cat\n" "- [ ] Buy food\n")
-
-        result = service.complete_task_in_daily_note("Feed the cat", date)
-        assert result["success"] is True
-
-        content = note_path.read_text()
-        assert "- [x] Feed the cat" in content
-        assert "- [ ] Buy food" in content  # Other task unchanged
-
-    def test_complete_task_partial_match(self, service, vault_dir):
-        date = datetime(2026, 6, 4)
-        rel_path = service.get_daily_note_path(date)
-        note_path = vault_dir / rel_path
-        note_path.parent.mkdir(parents=True, exist_ok=True)
-        note_path.write_text("### tasks\n\n- [ ] Feed the cat at 5pm\n")
-
-        result = service.complete_task_in_daily_note("Feed the cat", date)
-        assert result["success"] is True
-
-    def test_complete_task_not_found(self, service, vault_dir):
-        date = datetime(2026, 6, 5)
-        rel_path = service.get_daily_note_path(date)
-        note_path = vault_dir / rel_path
-        note_path.parent.mkdir(parents=True, exist_ok=True)
-        note_path.write_text("### tasks\n\n- [ ] Feed the cat\n")
-
-        result = service.complete_task_in_daily_note("Walk the dog", date)
-        assert result["success"] is False
-        assert "not found" in result["error"]
-
-    def test_complete_task_no_note(self, service):
-        date = datetime(2099, 12, 31)
-        result = service.complete_task_in_daily_note("Something", date)
-        assert result["success"] is False

tests/unit/test_rate_limiting.py

@@ -1,92 +0,0 @@
-"""Tests for rate limiting logic in email and WhatsApp blueprints."""
-
-import time
-
-
-class TestEmailRateLimit:
-    def setup_method(self):
-        """Reset rate limit store before each test."""
-        from blueprints.email import _rate_limit_store
-
-        _rate_limit_store.clear()
-
-    def test_allows_under_limit(self):
-        from blueprints.email import _check_rate_limit, RATE_LIMIT_MAX
-
-        for _ in range(RATE_LIMIT_MAX):
-            assert _check_rate_limit("sender@test.com") is True
-
-    def test_blocks_at_limit(self):
-        from blueprints.email import _check_rate_limit, RATE_LIMIT_MAX
-
-        for _ in range(RATE_LIMIT_MAX):
-            _check_rate_limit("sender@test.com")
-
-        assert _check_rate_limit("sender@test.com") is False
-
-    def test_different_senders_independent(self):
-        from blueprints.email import _check_rate_limit, RATE_LIMIT_MAX
-
-        for _ in range(RATE_LIMIT_MAX):
-            _check_rate_limit("user1@test.com")
-
-        # user1 is at limit, but user2 should be fine
-        assert _check_rate_limit("user1@test.com") is False
-        assert _check_rate_limit("user2@test.com") is True
-
-    def test_window_expiry(self):
-        from blueprints.email import (
-            _check_rate_limit,
-            _rate_limit_store,
-            RATE_LIMIT_MAX,
-        )
-
-        # Fill up the rate limit with timestamps in the past
-        past = time.monotonic() - 999  # Well beyond any window
-        _rate_limit_store["old@test.com"] = [past] * RATE_LIMIT_MAX
-
-        # Should be allowed because all timestamps are expired
-        assert _check_rate_limit("old@test.com") is True
-
-
-class TestWhatsAppRateLimit:
-    def setup_method(self):
-        """Reset rate limit store before each test."""
-        from blueprints.whatsapp import _rate_limit_store
-
-        _rate_limit_store.clear()
-
-    def test_allows_under_limit(self):
-        from blueprints.whatsapp import _check_rate_limit, RATE_LIMIT_MAX
-
-        for _ in range(RATE_LIMIT_MAX):
-            assert _check_rate_limit("whatsapp:+1234567890") is True
-
-    def test_blocks_at_limit(self):
-        from blueprints.whatsapp import _check_rate_limit, RATE_LIMIT_MAX
-
-        for _ in range(RATE_LIMIT_MAX):
-            _check_rate_limit("whatsapp:+1234567890")
-
-        assert _check_rate_limit("whatsapp:+1234567890") is False
-
-    def test_different_numbers_independent(self):
-        from blueprints.whatsapp import _check_rate_limit, RATE_LIMIT_MAX
-
-        for _ in range(RATE_LIMIT_MAX):
-            _check_rate_limit("whatsapp:+1111111111")
-
-        assert _check_rate_limit("whatsapp:+1111111111") is False
-        assert _check_rate_limit("whatsapp:+2222222222") is True
-
-    def test_window_expiry(self):
-        from blueprints.whatsapp import (
-            _check_rate_limit,
-            _rate_limit_store,
-            RATE_LIMIT_MAX,
-        )
-
-        past = time.monotonic() - 999
-        _rate_limit_store["whatsapp:+9999999999"] = [past] * RATE_LIMIT_MAX
-
-        assert _check_rate_limit("whatsapp:+9999999999") is True

tests/unit/test_user_model.py

@@ -1,86 +0,0 @@
-"""Tests for User model methods in blueprints/users/models.py."""
-
-from unittest.mock import MagicMock
-
-import bcrypt
-
-
-class TestUserModelMethods:
-    """Test User model methods without requiring a database connection.
-
-    We instantiate a mock object with the same methods as User
-    to avoid Tortoise ORM initialization.
-    """
-
-    def _make_user(self, ldap_groups=None, password=None):
-        """Create a mock user with real method implementations."""
-        from blueprints.users.models import User
-
-        user = MagicMock(spec=User)
-        user.ldap_groups = ldap_groups
-        user.password = password
-
-        # Bind real methods
-        user.has_group = lambda group: group in (user.ldap_groups or [])
-        user.is_admin = lambda: user.has_group("lldap_admin")
-
-        def set_password(plain):
-            user.password = bcrypt.hashpw(plain.encode("utf-8"), bcrypt.gensalt())
-
-        user.set_password = set_password
-
-        def verify_password(plain):
-            if not user.password:
-                return False
-            return bcrypt.checkpw(plain.encode("utf-8"), user.password)
-
-        user.verify_password = verify_password
-
-        return user
-
-    def test_has_group_true(self):
-        user = self._make_user(ldap_groups=["lldap_admin", "users"])
-        assert user.has_group("lldap_admin") is True
-        assert user.has_group("users") is True
-
-    def test_has_group_false(self):
-        user = self._make_user(ldap_groups=["users"])
-        assert user.has_group("lldap_admin") is False
-
-    def test_has_group_empty_list(self):
-        user = self._make_user(ldap_groups=[])
-        assert user.has_group("anything") is False
-
-    def test_has_group_none(self):
-        user = self._make_user(ldap_groups=None)
-        assert user.has_group("anything") is False
-
-    def test_is_admin_true(self):
-        user = self._make_user(ldap_groups=["lldap_admin"])
-        assert user.is_admin() is True
-
-    def test_is_admin_false(self):
-        user = self._make_user(ldap_groups=["users"])
-        assert user.is_admin() is False
-
-    def test_is_admin_empty(self):
-        user = self._make_user(ldap_groups=[])
-        assert user.is_admin() is False
-
-    def test_set_and_verify_password(self):
-        user = self._make_user()
-        user.set_password("hunter2")
-        assert user.password is not None
-        assert user.verify_password("hunter2") is True
-        assert user.verify_password("wrong") is False
-
-    def test_verify_password_no_password_set(self):
-        user = self._make_user(password=None)
-        assert user.verify_password("anything") is False
-
-    def test_password_is_hashed(self):
-        user = self._make_user()
-        user.set_password("mypassword")
-        # The stored password should not be the plaintext
-        assert user.password != b"mypassword"
-        assert user.password != "mypassword"

tests/unit/test_ynab_service.py

@@ -1,254 +0,0 @@
-"""Tests for YNAB service data formatting and filtering logic."""
-
-import os
-from unittest.mock import MagicMock, patch
-
-import pytest
-
-
-def _mock_category(
-    name, budgeted, activity, balance, deleted=False, hidden=False, goal_type=None
-):
-    cat = MagicMock()
-    cat.name = name
-    cat.budgeted = budgeted
-    cat.activity = activity
-    cat.balance = balance
-    cat.deleted = deleted
-    cat.hidden = hidden
-    cat.goal_type = goal_type
-    return cat
-
-
-def _mock_transaction(
-    var_date, payee_name, category_name, amount, memo="", deleted=False, approved=True
-):
-    txn = MagicMock()
-    txn.var_date = var_date
-    txn.payee_name = payee_name
-    txn.category_name = category_name
-    txn.amount = amount
-    txn.memo = memo
-    txn.deleted = deleted
-    txn.approved = approved
-    return txn
-
-
-@pytest.fixture
-def ynab_service():
-    """Create a YNABService with mocked API client."""
-    with patch.dict(
-        os.environ, {"YNAB_ACCESS_TOKEN": "fake-token", "YNAB_BUDGET_ID": "test-budget"}
-    ):
-        with patch("utils.ynab_service.ynab") as mock_ynab:
-            # Mock the configuration and API client chain
-            mock_ynab.Configuration.return_value = MagicMock()
-            mock_ynab.ApiClient.return_value = MagicMock()
-            mock_ynab.PlansApi.return_value = MagicMock()
-            mock_ynab.TransactionsApi.return_value = MagicMock()
-            mock_ynab.MonthsApi.return_value = MagicMock()
-            mock_ynab.CategoriesApi.return_value = MagicMock()
-
-            from utils.ynab_service import YNABService
-
-            service = YNABService()
-            yield service
-
-
-class TestGetBudgetSummary:
-    def test_calculates_totals(self, ynab_service):
-        categories = [
-            _mock_category("Groceries", 500_000, -350_000, 150_000),
-            _mock_category("Rent", 1_500_000, -1_500_000, 0),
-        ]
-
-        mock_month = MagicMock()
-        mock_month.to_be_budgeted = 200_000
-
-        mock_budget = MagicMock()
-        mock_budget.name = "My Budget"
-        mock_budget.months = [mock_month]
-        mock_budget.categories = categories
-        mock_budget.currency_format = MagicMock(iso_code="USD")
-
-        mock_response = MagicMock()
-        mock_response.data.budget = mock_budget
-        ynab_service.plans_api.get_plan_by_id.return_value = mock_response
-
-        result = ynab_service.get_budget_summary()
-
-        assert result["budget_name"] == "My Budget"
-        assert result["to_be_budgeted"] == 200.0
-        assert result["total_budgeted"] == 2000.0  # (500k + 1500k) / 1000
-        assert result["total_activity"] == -1850.0
-        assert result["currency_format"] == "USD"
-
-    def test_skips_deleted_and_hidden(self, ynab_service):
-        categories = [
-            _mock_category("Active", 100_000, -50_000, 50_000),
-            _mock_category("Deleted", 999_000, -999_000, 0, deleted=True),
-            _mock_category("Hidden", 999_000, -999_000, 0, hidden=True),
-        ]
-
-        mock_month = MagicMock()
-        mock_month.to_be_budgeted = 0
-        mock_budget = MagicMock()
-        mock_budget.name = "Budget"
-        mock_budget.months = [mock_month]
-        mock_budget.categories = categories
-        mock_budget.currency_format = None
-
-        mock_response = MagicMock()
-        mock_response.data.budget = mock_budget
-        ynab_service.plans_api.get_plan_by_id.return_value = mock_response
-
-        result = ynab_service.get_budget_summary()
-        assert result["total_budgeted"] == 100.0
-        assert result["currency_format"] == "USD"  # Default fallback
-
-
-class TestGetTransactions:
-    def test_filters_by_date_range(self, ynab_service):
-        transactions = [
-            _mock_transaction("2026-01-05", "Store", "Groceries", -25_000),
-            _mock_transaction("2026-01-15", "Gas", "Transport", -40_000),
-            _mock_transaction(
-                "2026-02-01", "Store", "Groceries", -30_000
-            ),  # Out of range
-        ]
-
-        mock_response = MagicMock()
-        mock_response.data.transactions = transactions
-        ynab_service.transactions_api.get_transactions.return_value = mock_response
-
-        result = ynab_service.get_transactions(
-            start_date="2026-01-01", end_date="2026-01-31"
-        )
-
-        assert result["count"] == 2
-        assert result["total_amount"] == -65.0
-
-    def test_filters_by_category(self, ynab_service):
-        transactions = [
-            _mock_transaction("2026-01-05", "Store", "Groceries", -25_000),
-            _mock_transaction("2026-01-06", "Gas", "Transport", -40_000),
-        ]
-
-        mock_response = MagicMock()
-        mock_response.data.transactions = transactions
-        ynab_service.transactions_api.get_transactions.return_value = mock_response
-
-        result = ynab_service.get_transactions(
-            start_date="2026-01-01",
-            end_date="2026-01-31",
-            category_name="groceries",  # Case insensitive
-        )
-
-        assert result["count"] == 1
-        assert result["transactions"][0]["category"] == "Groceries"
-
-    def test_filters_by_payee(self, ynab_service):
-        transactions = [
-            _mock_transaction("2026-01-05", "Whole Foods", "Groceries", -25_000),
-            _mock_transaction("2026-01-06", "Shell Gas", "Transport", -40_000),
-        ]
-
-        mock_response = MagicMock()
-        mock_response.data.transactions = transactions
-        ynab_service.transactions_api.get_transactions.return_value = mock_response
-
-        result = ynab_service.get_transactions(
-            start_date="2026-01-01",
-            end_date="2026-01-31",
-            payee_name="whole",
-        )
-
-        assert result["count"] == 1
-        assert result["transactions"][0]["payee"] == "Whole Foods"
-
-    def test_skips_deleted(self, ynab_service):
-        transactions = [
-            _mock_transaction("2026-01-05", "Store", "Groceries", -25_000),
-            _mock_transaction("2026-01-06", "Deleted", "Other", -10_000, deleted=True),
-        ]
-
-        mock_response = MagicMock()
-        mock_response.data.transactions = transactions
-        ynab_service.transactions_api.get_transactions.return_value = mock_response
-
-        result = ynab_service.get_transactions(
-            start_date="2026-01-01", end_date="2026-01-31"
-        )
-
-        assert result["count"] == 1
-
-    def test_converts_milliunits(self, ynab_service):
-        transactions = [
-            _mock_transaction("2026-01-05", "Store", "Groceries", -12_340),
-        ]
-
-        mock_response = MagicMock()
-        mock_response.data.transactions = transactions
-        ynab_service.transactions_api.get_transactions.return_value = mock_response
-
-        result = ynab_service.get_transactions(
-            start_date="2026-01-01", end_date="2026-01-31"
-        )
-
-        assert result["transactions"][0]["amount"] == -12.34
-
-    def test_sorts_by_date_descending(self, ynab_service):
-        transactions = [
-            _mock_transaction("2026-01-01", "A", "Cat", -10_000),
-            _mock_transaction("2026-01-15", "B", "Cat", -20_000),
-            _mock_transaction("2026-01-10", "C", "Cat", -30_000),
-        ]
-
-        mock_response = MagicMock()
-        mock_response.data.transactions = transactions
-        ynab_service.transactions_api.get_transactions.return_value = mock_response
-
-        result = ynab_service.get_transactions(
-            start_date="2026-01-01", end_date="2026-01-31"
-        )
-
-        dates = [t["date"] for t in result["transactions"]]
-        assert dates == sorted(dates, reverse=True)
-
-
-class TestGetCategorySpending:
-    def test_month_format_normalization(self, ynab_service):
-        """Passing YYYY-MM should be normalized to YYYY-MM-01."""
-        categories = [_mock_category("Food", 100_000, -50_000, 50_000)]
-
-        mock_month = MagicMock()
-        mock_month.categories = categories
-        mock_month.to_be_budgeted = 0
-
-        mock_response = MagicMock()
-        mock_response.data.month = mock_month
-        ynab_service.months_api.get_plan_month.return_value = mock_response
-
-        result = ynab_service.get_category_spending("2026-03")
-
-        assert result["month"] == "2026-03"
-
-    def test_identifies_overspent(self, ynab_service):
-        categories = [
-            _mock_category("Dining", 200_000, -300_000, -100_000),  # Overspent
-            _mock_category("Groceries", 500_000, -400_000, 100_000),  # Fine
-        ]
-
-        mock_month = MagicMock()
-        mock_month.categories = categories
-        mock_month.to_be_budgeted = 0
-
-        mock_response = MagicMock()
-        mock_response.data.month = mock_month
-        ynab_service.months_api.get_plan_month.return_value = mock_response
-
-        result = ynab_service.get_category_spending("2026-03")
-
-        assert len(result["overspent_categories"]) == 1
-        assert result["overspent_categories"][0]["name"] == "Dining"
-        assert result["overspent_categories"][0]["overspent_by"] == 100.0

utils/chunker.py

@@ -0,0 +1,137 @@
+import os
+from math import ceil
+import re
+from typing import Union
+from uuid import UUID, uuid4
+from chromadb.utils.embedding_functions.openai_embedding_function import (
+    OpenAIEmbeddingFunction,
+)
+from dotenv import load_dotenv
+from llm import LLMClient
+
+
+load_dotenv()
+
+
+def remove_headers_footers(text, header_patterns=None, footer_patterns=None):
+    if header_patterns is None:
+        header_patterns = [r"^.*Header.*$"]
+    if footer_patterns is None:
+        footer_patterns = [r"^.*Footer.*$"]
+
+    for pattern in header_patterns + footer_patterns:
+        text = re.sub(pattern, "", text, flags=re.MULTILINE)
+
+    return text.strip()
+
+
+def remove_special_characters(text, special_chars=None):
+    if special_chars is None:
+        special_chars = r"[^A-Za-z0-9\s\.,;:\'\"\?\!\-]"
+
+    text = re.sub(special_chars, "", text)
+    return text.strip()
+
+
+def remove_repeated_substrings(text, pattern=r"\.{2,}"):
+    text = re.sub(pattern, ".", text)
+    return text.strip()
+
+
+def remove_extra_spaces(text):
+    text = re.sub(r"\n\s*\n", "\n\n", text)
+    text = re.sub(r"\s+", " ", text)
+
+    return text.strip()
+
+
+def preprocess_text(text):
+    # Remove headers and footers
+    text = remove_headers_footers(text)
+
+    # Remove special characters
+    text = remove_special_characters(text)
+
+    # Remove repeated substrings like dots
+    text = remove_repeated_substrings(text)
+
+    # Remove extra spaces between lines and within lines
+    text = remove_extra_spaces(text)
+
+    # Additional cleaning steps can be added here
+
+    return text.strip()
+
+
+class Chunk:
+    def __init__(
+        self,
+        text: str,
+        size: int,
+        document_id: UUID,
+        chunk_id: int,
+        embedding,
+    ):
+        self.text = text
+        self.size = size
+        self.document_id = document_id
+        self.chunk_id = chunk_id
+        self.embedding = embedding
+
+
+class Chunker:
+    def __init__(self, collection) -> None:
+        self.collection = collection
+        self.llm_client = LLMClient()
+
+    def embedding_fx(self, inputs):
+        openai_embedding_fx = OpenAIEmbeddingFunction(
+            api_key=os.getenv("OPENAI_API_KEY"),
+            model_name="text-embedding-3-small",
+        )
+        return openai_embedding_fx(inputs)
+
+    def chunk_document(
+        self,
+        document: str,
+        chunk_size: int = 1000,
+        metadata: dict[str, Union[str, float]] = {},
+    ) -> list[Chunk]:
+        doc_uuid = uuid4()
+
+        chunk_size = min(chunk_size, len(document)) or 1
+
+        chunks = []
+        num_chunks = ceil(len(document) / chunk_size)
+        document_length = len(document)
+
+        for i in range(num_chunks):
+            curr_pos = i * num_chunks
+            to_pos = (
+                curr_pos + chunk_size
+                if curr_pos + chunk_size < document_length
+                else document_length
+            )
+            text_chunk = self.clean_document(document[curr_pos:to_pos])
+
+            embedding = self.embedding_fx([text_chunk])
+            self.collection.add(
+                ids=[str(doc_uuid) + ":" + str(i)],
+                documents=[text_chunk],
+                embeddings=embedding,
+                metadatas=[metadata],
+            )
+
+        return chunks
+
+    def clean_document(self, document: str) -> str:
+        """This function will remove information that is noise or already known.
+
+        Example: We already know all the things in here are Simba-related, so we don't need things like
+        "Sumamry of simba's visit"
+        """
+
+        document = document.replace("\\n", "")
+        document = document.strip()
+
+        return preprocess_text(document)