query classification

Reviewed-on: #7

Dockerfile

@@ -23,6 +23,8 @@ RUN uv pip install --system -e .
 
 # Copy application code
 COPY *.py ./
+COPY blueprints ./blueprints
+COPY migrations ./migrations
 COPY startup.sh ./
 RUN chmod +x startup.sh
 
@@ -32,8 +34,8 @@ WORKDIR /app/raggr-frontend
 RUN yarn install && yarn build
 WORKDIR /app
 
-# Create ChromaDB directory
+# Create ChromaDB and database directories
-RUN mkdir -p /app/chromadb
+RUN mkdir -p /app/chromadb /app/database
 
 # Expose port
 EXPOSE 8080

MIGRATIONS.md

@@ -0,0 +1,54 @@
+# Database Migrations with Aerich
+
+## Initial Setup (Run Once)
+
+1. Install dependencies:
+```bash
+uv pip install -e .
+```
+
+2. Initialize Aerich:
+```bash
+aerich init-db
+```
+
+This will:
+- Create a `migrations/` directory
+- Generate the initial migration based on your models
+- Create all tables in the database
+
+## When You Add/Change Models
+
+1. Generate a new migration:
+```bash
+aerich migrate --name "describe_your_changes"
+```
+
+Example:
+```bash
+aerich migrate --name "add_user_profile_model"
+```
+
+2. Apply the migration:
+```bash
+aerich upgrade
+```
+
+## Common Commands
+
+- `aerich init-db` - Initialize database (first time only)
+- `aerich migrate --name "description"` - Generate new migration
+- `aerich upgrade` - Apply pending migrations
+- `aerich downgrade` - Rollback last migration
+- `aerich history` - Show migration history
+- `aerich heads` - Show current migration heads
+
+## Docker Setup
+
+In Docker, migrations run automatically on container startup via the startup script.
+
+## Notes
+
+- Migration files are stored in `migrations/models/`
+- Always commit migration files to version control
+- Don't modify migration files manually after they're created

add_user.py

@@ -0,0 +1,130 @@
+# GENERATED BY CLAUDE
+
+import sys
+import uuid
+import asyncio
+from tortoise import Tortoise
+from blueprints.users.models import User
+
+
+async def add_user(username: str, email: str, password: str):
+    """Add a new user to the database"""
+    await Tortoise.init(
+        db_url="sqlite://database/raggr.db",
+        modules={
+            "models": [
+                "blueprints.users.models",
+                "blueprints.conversation.models",
+            ]
+        },
+    )
+
+    try:
+        # Check if user already exists
+        existing_user = await User.filter(email=email).first()
+        if existing_user:
+            print(f"Error: User with email '{email}' already exists!")
+            return False
+
+        existing_username = await User.filter(username=username).first()
+        if existing_username:
+            print(f"Error: Username '{username}' is already taken!")
+            return False
+
+        # Create new user
+        user = User(
+            id=uuid.uuid4(),
+            username=username,
+            email=email,
+        )
+        user.set_password(password)
+        await user.save()
+
+        print("✓ User created successfully!")
+        print(f"  Username: {username}")
+        print(f"  Email: {email}")
+        print(f"  ID: {user.id}")
+        return True
+
+    except Exception as e:
+        print(f"Error creating user: {e}")
+        return False
+    finally:
+        await Tortoise.close_connections()
+
+
+async def list_users():
+    """List all users in the database"""
+    await Tortoise.init(
+        db_url="sqlite://database/raggr.db",
+        modules={
+            "models": [
+                "blueprints.users.models",
+                "blueprints.conversation.models",
+            ]
+        },
+    )
+
+    try:
+        users = await User.all()
+        if not users:
+            print("No users found in database.")
+            return
+
+        print(f"\nFound {len(users)} user(s):")
+        print("-" * 60)
+        for user in users:
+            print(f"Username: {user.username}")
+            print(f"Email: {user.email}")
+            print(f"ID: {user.id}")
+            print(f"Created: {user.created_at}")
+            print("-" * 60)
+
+    except Exception as e:
+        print(f"Error listing users: {e}")
+    finally:
+        await Tortoise.close_connections()
+
+
+def print_usage():
+    """Print usage instructions"""
+    print("Usage:")
+    print("  python add_user.py add <username> <email> <password>")
+    print("  python add_user.py list")
+    print("\nExamples:")
+    print("  python add_user.py add ryan ryan@example.com mypassword123")
+    print("  python add_user.py list")
+
+
+async def main():
+    if len(sys.argv) < 2:
+        print_usage()
+        sys.exit(1)
+
+    command = sys.argv[1].lower()
+
+    if command == "add":
+        if len(sys.argv) != 5:
+            print("Error: Missing arguments for 'add' command")
+            print_usage()
+            sys.exit(1)
+
+        username = sys.argv[2]
+        email = sys.argv[3]
+        password = sys.argv[4]
+
+        success = await add_user(username, email, password)
+        sys.exit(0 if success else 1)
+
+    elif command == "list":
+        await list_users()
+        sys.exit(0)
+
+    else:
+        print(f"Error: Unknown command '{command}'")
+        print_usage()
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

aerich_config.py

@@ -0,0 +1,15 @@
+import os
+
+TORTOISE_ORM = {
+    "connections": {"default": os.getenv("DATABASE_URL", "sqlite:///app/database/raggr.db")},
+    "apps": {
+        "models": {
+            "models": [
+                "blueprints.conversation.models",
+                "blueprints.users.models",
+                "aerich.models",
+            ],
+            "default_connection": "default",
+        },
+    },
+}

app.py

@@ -3,13 +3,14 @@ import os
 from quart import Quart, request, jsonify, render_template, send_from_directory
 from tortoise.contrib.quart import register_tortoise
 
-from quart_jwt_extended import JWTManager
+from quart_jwt_extended import JWTManager, jwt_refresh_token_required, get_jwt_identity
 
 from main import consult_simba_oracle
-from blueprints.conversation.logic import (
+
-    get_the_only_conversation,
+import blueprints.users
-    add_message_to_conversation,
+import blueprints.conversation
-)
+import blueprints.conversation.logic
+import blueprints.users.models
 
 app = Quart(
     __name__,
@@ -20,12 +21,29 @@ app = Quart(
 app.config["JWT_SECRET_KEY"] = os.getenv("JWT_SECRET_KEY", "SECRET_KEY")
 jwt = JWTManager(app)
 
+# Register blueprints
+app.register_blueprint(blueprints.users.user_blueprint)
+app.register_blueprint(blueprints.conversation.conversation_blueprint)
+
+
+TORTOISE_CONFIG = {
+    "connections": {"default": "sqlite://database/raggr.db"},
+    "apps": {
+        "models": {
+            "models": [
+                "blueprints.conversation.models",
+                "blueprints.users.models",
+                "aerich.models",
+            ]
+        },
+    },
+}
+
 # Initialize Tortoise ORM
 register_tortoise(
     app,
-    db_url=os.getenv("DATABASE_URL", "sqlite://raggr.db"),
+    config=TORTOISE_CONFIG,
-    modules={"models": ["blueprints.conversation.models"]},
+    generate_schemas=False,  # Disabled - using Aerich for migrations
-    generate_schemas=True,
 )
 
 
@@ -45,26 +63,47 @@ async def serve_react_app(path):
 
 
 @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")
-    # add message to database
+    conversation_id = data.get("conversation_id")
-    conversation = await get_the_only_conversation()
+    conversation = await blueprints.conversation.logic.get_conversation_by_id(
-    print(conversation)
+        conversation_id
-    await add_message_to_conversation(
+    )
-        conversation=conversation, message=query, speaker="user"
+    await conversation.fetch_related("messages")
+    await blueprints.conversation.logic.add_message_to_conversation(
+        conversation=conversation,
+        message=query,
+        speaker="user",
+        user=user,
     )
 
-    response = consult_simba_oracle(query)
+    transcript = await blueprints.conversation.logic.get_conversation_transcript(
-    await add_message_to_conversation(
+        user=user, conversation=conversation
-        conversation=conversation, message=response, speaker="simba"
+    )
+
+    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():
-    conversation = await get_the_only_conversation()
+    current_user_uuid = get_jwt_identity()
+    user = await blueprints.users.models.User.get(id=current_user_uuid)
+
+    conversation = await blueprints.conversation.logic.get_conversation_for_user(
+        user=user
+    )
     # Prefetch related messages
     await conversation.fetch_related("messages")
 
@@ -91,12 +130,5 @@ async def get_messages():
     )
 
 
-# @app.route("/api/ingest", methods=["POST"])
-# def webhook():
-# data = request.get_json()
-# print(data)
-# return jsonify({"status": "received"})
-
-
 if __name__ == "__main__":
     app.run(host="0.0.0.0", port=8080, debug=True)

blueprints/__init__.py

@@ -0,0 +1 @@
+# Blueprints package

blueprints/conversation/__init__.py

@@ -1,9 +1,19 @@
+import datetime
+
+from quart_jwt_extended import (
+    jwt_refresh_token_required,
+    get_jwt_identity,
+)
+
 from quart import Blueprint, jsonify
 from .models import (
     Conversation,
     PydConversation,
+    PydListConversation,
 )
 
+import blueprints.users.models
+
 conversation_blueprint = Blueprint(
     "conversation_api", __name__, url_prefix="/api/conversation"
 )
@@ -12,6 +22,51 @@ conversation_blueprint = Blueprint(
 @conversation_blueprint.route("/<conversation_id>")
 async def get_conversation(conversation_id: str):
     conversation = await Conversation.get(id=conversation_id)
-    serialized_conversation = await PydConversation.from_tortoise_orm(conversation)
+    await conversation.fetch_related("messages")
 
-    return jsonify(serialized_conversation.model_dump_json())
+    # Manually serialize the conversation with messages
+    messages = []
+    for msg in conversation.messages:
+        messages.append(
+            {
+                "id": str(msg.id),
+                "text": msg.text,
+                "speaker": msg.speaker.value,
+                "created_at": msg.created_at.isoformat(),
+            }
+        )
+
+    return jsonify(
+        {
+            "id": str(conversation.id),
+            "name": conversation.name,
+            "messages": messages,
+            "created_at": conversation.created_at.isoformat(),
+            "updated_at": conversation.updated_at.isoformat(),
+        }
+    )
+
+
+@conversation_blueprint.post("/")
+@jwt_refresh_token_required
+async def create_conversation():
+    user_uuid = get_jwt_identity()
+    user = await blueprints.users.models.User.get(id=user_uuid)
+    conversation = await Conversation.create(
+        name=f"{user.username} {datetime.datetime.now().timestamp}",
+        user=user,
+    )
+
+    serialized_conversation = await PydConversation.from_tortoise_orm(conversation)
+    return jsonify(serialized_conversation.model_dump())
+
+
+@conversation_blueprint.get("/")
+@jwt_refresh_token_required
+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)
+    serialized_conversations = await PydListConversation.from_queryset(conversations)
+
+    return jsonify(serialized_conversations.model_dump())

blueprints/conversation/logic.py

@@ -1,5 +1,9 @@
+import tortoise.exceptions
+
 from .models import Conversation, ConversationMessage
 
+import blueprints.users.models
+
 
 async def create_conversation(name: str = "") -> Conversation:
     conversation = await Conversation.create(name=name)
@@ -10,6 +14,7 @@ async def add_message_to_conversation(
     conversation: Conversation,
     message: str,
     speaker: str,
+    user: blueprints.users.models.User,
 ) -> ConversationMessage:
     print(conversation, message, speaker)
     message = await ConversationMessage.create(
@@ -30,3 +35,26 @@ async def get_the_only_conversation() -> Conversation:
         conversation = await Conversation.create(name="simba_chat")
 
     return conversation
+
+
+async def get_conversation_for_user(user: blueprints.users.models.User) -> Conversation:
+    try:
+        return await Conversation.get(user=user)
+    except tortoise.exceptions.DoesNotExist:
+        await Conversation.get_or_create(name=f"{user.username}'s chat", user=user)
+
+        return await Conversation.get(user=user)
+
+
+async def get_conversation_by_id(id: str) -> Conversation:
+    return await Conversation.get(id=id)
+
+
+async def get_conversation_transcript(
+    user: blueprints.users.models.User, conversation: Conversation
+) -> str:
+    messages = []
+    for message in conversation.messages:
+        messages.append(f"{message.speaker} at {message.created_at}: {message.text}")
+
+    return "\n".join(messages)

blueprints/conversation/models.py

@@ -18,6 +18,9 @@ class Conversation(Model):
     name = fields.CharField(max_length=255)
     created_at = fields.DatetimeField(auto_now_add=True)
     updated_at = fields.DatetimeField(auto_now=True)
+    user: fields.ForeignKeyRelation = fields.ForeignKeyField(
+        "models.User", related_name="conversations", null=True
+    )
 
     class Meta:
         table = "conversations"
@@ -37,5 +40,15 @@ class ConversationMessage(Model):
 
 
 PydConversationMessage = pydantic_model_creator(ConversationMessage)
-PydConversation = pydantic_model_creator(Conversation, name="Conversation")
+PydConversation = pydantic_model_creator(
+    Conversation, name="Conversation", allow_cycles=True, exclude=("user",)
+)
+PydConversationWithMessages = pydantic_model_creator(
+    Conversation,
+    name="ConversationWithMessages",
+    allow_cycles=True,
+    exclude=("user",),
+    include=("messages",),
+)
+PydListConversation = pydantic_queryset_creator(Conversation)
 PydListConversationMessage = pydantic_queryset_creator(ConversationMessage)

blueprints/users/__init__.py

@@ -0,0 +1,40 @@
+from quart import Blueprint, jsonify, request
+from quart_jwt_extended import (
+    create_access_token,
+    create_refresh_token,
+    jwt_refresh_token_required,
+    get_jwt_identity,
+)
+from .models import User
+
+
+user_blueprint = Blueprint("user_api", __name__, url_prefix="/api/user")
+
+
+@user_blueprint.route("/login", methods=["POST"])
+async def login():
+    data = await request.get_json()
+    username = data.get("username")
+    password = data.get("password")
+
+    user = await User.filter(username=username).first()
+
+    if not user or not user.verify_password(password):
+        return jsonify({"msg": "Invalid credentials"}), 401
+
+    access_token = create_access_token(identity=str(user.id))
+    refresh_token = create_refresh_token(identity=str(user.id))
+
+    return jsonify(
+        access_token=access_token,
+        refresh_token=refresh_token,
+        user={"id": user.id, "username": user.username},
+    )
+
+
+@user_blueprint.route("/refresh", methods=["POST"])
+@jwt_refresh_token_required
+async def refresh():
+    user_id = get_jwt_identity()
+    new_token = create_access_token(identity=user_id)
+    return jsonify(access_token=new_token)

blueprints/users/models.py

@@ -0,0 +1,26 @@
+from tortoise.models import Model
+from tortoise import fields
+
+
+import bcrypt
+
+
+class User(Model):
+    id = fields.UUIDField(primary_key=True)
+    username = fields.CharField(max_length=255)
+    password = fields.BinaryField()  # Hashed
+    email = fields.CharField(max_length=100, unique=True)
+    created_at = fields.DatetimeField(auto_now_add=True)
+    updated_at = fields.DatetimeField(auto_now=True)
+
+    class Meta:
+        table = "users"
+
+    def set_password(self, plain_password: str):
+        self.password = bcrypt.hashpw(
+            plain_password.encode("utf-8"),
+            bcrypt.gensalt(),
+        )
+
+    def verify_password(self, plain_password: str):
+        return bcrypt.checkpw(plain_password.encode("utf-8"), self.password)

chunker.py

@@ -14,7 +14,7 @@ from llm import LLMClient
 load_dotenv()
 
 ollama_client = Client(
-    host=os.getenv("OLLAMA_HOST", "http://localhost:11434"), timeout=10.0
+    host=os.getenv("OLLAMA_HOST", "http://localhost:11434"), timeout=1.0
 )
 
 

docker-compose.yml

@@ -12,6 +12,8 @@ services:
       - OPENAI_API_KEY=${OPENAI_API_KEY}
     volumes:
       - chromadb_data:/app/chromadb
+      - database_data:/app/database
 
 volumes:
   chromadb_data:
+  database_data:

index_immich.py

@@ -27,7 +27,7 @@ headers = {"x-api-key": API_KEY, "Content-Type": "application/json"}
 VISITED = {}
 
 if __name__ == "__main__":
-    conn = sqlite3.connect("./visited.db")
+    conn = sqlite3.connect("./database/visited.db")
     c = conn.cursor()
     c.execute("select immich_id from visited")
     rows = c.fetchall()

llm.py

@@ -4,15 +4,20 @@ from ollama import Client
 from openai import OpenAI
 
 import logging
+from dotenv import load_dotenv
+
+load_dotenv()
 
 logging.basicConfig(level=logging.INFO)
 
+TRY_OLLAMA = os.getenv("TRY_OLLAMA", False)
+
 
 class LLMClient:
     def __init__(self):
         try:
             self.ollama_client = Client(
-                host=os.getenv("OLLAMA_URL", "http://localhost:11434"), timeout=10.0
+                host=os.getenv("OLLAMA_URL", "http://localhost:11434"), timeout=1.0
             )
             self.ollama_client.chat(
                 model="gemma3:4b", messages=[{"role": "system", "content": "test"}]
@@ -30,7 +35,9 @@ class LLMClient:
         prompt: str,
         system_prompt: str,
     ):
+        # Instituting a fallback if my gaming PC is not on
         if self.PROVIDER == "ollama":
+            try:
                 response = self.ollama_client.chat(
                     model="gemma3:4b",
                     messages=[
@@ -41,9 +48,11 @@ class LLMClient:
                         {"role": "user", "content": prompt},
                     ],
                 )
-            print(response)
                 output = response.message.content
-        elif self.PROVIDER == "openai":
+                return output
+            except Exception as e:
+                logging.error(f"Could not connect to OLLAMA: {str(e)}")
+
         response = self.openai_client.responses.create(
             model="gpt-4o-mini",
             input=[

main.py

@@ -7,6 +7,8 @@ import argparse
 import chromadb
 import ollama
 
+import time
+
 
 from request import PaperlessNGXService
 from chunker import Chunker
@@ -36,6 +38,7 @@ 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()
@@ -77,7 +80,7 @@ def chunk_data(docs, collection, doctypes):
 
     logging.info(f"chunking {len(docs)} documents")
     texts: list[str] = [doc["content"] for doc in docs]
-    with sqlite3.connect("visited.db") as conn:
+    with sqlite3.connect("database/visited.db") as conn:
         to_insert = []
         c = conn.cursor()
         for index, text in enumerate(texts):
@@ -113,9 +116,22 @@ def chunk_text(texts: list[str], collection):
         )
 
 
-def consult_oracle(input: str, collection):
+def classify_query(query: str, transcript: str) -> bool:
-    import time
+    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()
@@ -153,7 +169,10 @@ def consult_oracle(input: str, collection):
     logging.info("Starting LLM generation")
     llm_start = time.time()
     system_prompt = "You are a helpful assistant that understands veterinary terms."
-    prompt = f"Using the following data, help answer the user's query by providing as many details as possible. Using this data: {results}. Respond to this prompt: {input}"
+    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")
@@ -164,6 +183,16 @@ def consult_oracle(input: str, collection):
     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 a humorous way as if you were a cat named Simba. Be very coy.
+    {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()
@@ -173,15 +202,24 @@ def paperless_workflow(input):
     consult_oracle(input, simba_docs)
 
 
-def consult_simba_oracle(input: str):
+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("visited.db") as conn:
+    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)"
@@ -194,12 +232,16 @@ def filter_indexed_files(docs):
     return [doc for doc in docs if doc["id"] not in visited]
 
 
-if __name__ == "__main__":
+def reindex():
-    args = parser.parse_args()
+    with sqlite3.connect("database/visited.db") as conn:
-    if args.reindex:
-        with sqlite3.connect("./visited.db") as conn:
         c = conn.cursor()
         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()
@@ -215,21 +257,20 @@ if __name__ == "__main__":
 
     # Chunk documents
     logging.info("Chunking documents now ...")
-        tag_lookup = ppngx.get_tags()
     doctype_lookup = ppngx.get_doctypes()
     chunk_data(docs, collection=simba_docs, doctypes=doctype_lookup)
     logging.info("Done chunking documents")
 
-    # if args.index:
+
-    # with open(args.index) as file:
+if __name__ == "__main__":
-    #     extension = args.index.split(".")[-1]
+    args = parser.parse_args()
-    #     if extension == "pdf":
+    if args.reindex:
-    #         pdf_path = ppngx.download_pdf_from_id(id=document_id)
+        reindex()
-    #         image_paths = pdf_to_image(filepath=pdf_path)
+
-    #         print(f"summarizing {file}")
+    if args.classify:
-    #         generated_summary = summarize_pdf_image(filepaths=image_paths)
+        consult_simba_oracle(input="yohohoho testing")
-    #     elif extension in [".md", ".txt"]:
+        consult_simba_oracle(input="write an email")
-    #         chunk_text(texts=[file.readall()], collection=simba_docs)
+        consult_simba_oracle(input="how much does simba weigh")
 
     if args.query:
         logging.info("Consulting oracle ...")

migrations/models/0_20251025081744_init.py

@@ -0,0 +1,63 @@
+from tortoise import BaseDBAsyncClient
+
+RUN_IN_TRANSACTION = True
+
+
+async def upgrade(db: BaseDBAsyncClient) -> str:
+    return """
+        CREATE TABLE IF NOT EXISTS "conversations" (
+    "id" CHAR(36) NOT NULL PRIMARY KEY,
+    "name" VARCHAR(255) NOT NULL,
+    "created_at" TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "updated_at" TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
+);
+CREATE TABLE IF NOT EXISTS "conversation_messages" (
+    "id" CHAR(36) NOT NULL PRIMARY KEY,
+    "text" TEXT NOT NULL,
+    "created_at" TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "speaker" VARCHAR(10) NOT NULL /* USER: user\nSIMBA: simba */,
+    "conversation_id" CHAR(36) NOT NULL REFERENCES "conversations" ("id") ON DELETE CASCADE
+);
+CREATE TABLE IF NOT EXISTS "users" (
+    "id" CHAR(36) NOT NULL PRIMARY KEY,
+    "username" VARCHAR(255) NOT NULL,
+    "password" BLOB NOT NULL,
+    "email" VARCHAR(100) NOT NULL UNIQUE,
+    "created_at" TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "updated_at" TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
+);
+CREATE TABLE IF NOT EXISTS "aerich" (
+    "id" INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
+    "version" VARCHAR(255) NOT NULL,
+    "app" VARCHAR(100) NOT NULL,
+    "content" JSON NOT NULL
+);"""
+
+
+async def downgrade(db: BaseDBAsyncClient) -> str:
+    return """
+        """
+
+
+MODELS_STATE = (
+    "eJztmG1v4jgQx79KlFddaa9q2W53VZ1OCpTecrvACcLdPtwqMskAVhMnazvboorvfrbJE4"
+    "kJpWq3UPGmhRkPtn8ztv/2nRmEHvjsuBWSn0AZ4jgk5oVxZxIUgPig9b82TBRFuVcaOBr7"
+    "KsAttFQeNGacIpcL5wT5DITJA+ZSHCWdkdj3pTF0RUNMprkpJvhHDA4Pp8BnQIXj23dhxs"
+    "SDW2Dp1+jamWDwvZVxY0/2rewOn0fKNhp1Lq9US9nd2HFDPw5I3jqa81lIsuZxjL1jGSN9"
+    "UyBAEQevMA05ymTaqWk5YmHgNIZsqF5u8GCCYl/CMH+fxMSVDAzVk/xz9oe5BR6BWqLFhE"
+    "sWd4vlrPI5K6spu2p9sAZHb85fqVmGjE+pcioi5kIFIo6WoYprDlL9r6BszRDVo0zbl2CK"
+    "gT4EY2rIOeY1lIJMAT2MmhmgW8cHMuUz8bXx9m0Nxn+sgSIpWimUoajrZdX3Eldj6ZNIc4"
+    "QuBTllB/EqyEvh4TgAPczVyBJSLwk9Tj/sKGAxB69P/HmyCGr42p1ue2hb3b/lTALGfvgK"
+    "kWW3paehrPOS9ei8lIrsR4x/O/YHQ341vvZ77XLtZ+3sr6YcE4p56JDwxkFeYb2m1hTMSm"
+    "LjyHtgYlcjD4l91sSqwcuTZHJd2AKlYYzc6xtEPWfFUzgdgTE0BVZNfzOJvPo4AD87NkuJ"
+    "1hyu3eUv7mbGF2kZp9YivLARrqNXdQWNoGxBRMzbS/qWPdXQ2aBQChDvJ1ScYiIPgmWvBQ"
+    "uHW812bAurHmXafl8ES9022/5sr+ywqSw56lqfX63ssp/6vT/T5gUZ0/rUbx7Uy0s85Krq"
+    "hUWAroHqxX2bxIHKakfgQMSFSnYL4c+8dMzRsD24MGIG9D8y7HSb1oXBcDBG5gNuAKcn97"
+    "gAnJ6s1f/SVVpAxYNmu21eE/qYe/6zblYbtviKHtMDrdK8CingKfkI80r9bpZfO02xoruE"
+    "maKbTEzoykV8EJMEvlzY1rBlXbbNxXpt+5RKbsSUJKpIN2Wv1WpyaR+02f5rM5nHbR+Uij"
+    "H7otF+waNShBi7CammMpuYIDrXwyxGlWCO53x5/9k9nDX0mlKwFvWWYNbs9KzBF73mTdsX"
+    "C7f5xW5bJbwQIOxvU6ZZwOPU6OYl/5gVenpyP9VTJ3uquudwcXiZF4fDs+eLSOy2z55PKQ"
+    "0toNid6cRh4qmVhyhvszP6sEPWvDdp5aHU9KVqTxL2rIeEemr9rXF69u7s/Zvzs/eiiRpJ"
+    "ZnlXU/2dnr1BDsrLivYOt/6YLYQcxGAGUi6NLSAmzfcT4NNolZBwIJrz7K9hv7f2bSYNKY"
+    "EcETHBbx52+WvDx4x/302sNRTlrOsfkstvxqXDSP5AU/eK8yuPl8X/Etg7Fw=="
+)

migrations/models/1_20251025091926_update.py

@@ -0,0 +1,60 @@
+from tortoise import BaseDBAsyncClient
+
+RUN_IN_TRANSACTION = True
+
+
+async def upgrade(db: BaseDBAsyncClient) -> str:
+    return """
+        -- SQLite doesn't support ADD CONSTRAINT, so we need to recreate the table
+        CREATE TABLE "conversations_new" (
+            "id" CHAR(36) NOT NULL PRIMARY KEY,
+            "name" VARCHAR(255) NOT NULL,
+            "created_at" TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
+            "updated_at" TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
+            "user_id" CHAR(36),
+            FOREIGN KEY ("user_id") REFERENCES "users" ("id") ON DELETE CASCADE
+        );
+        INSERT INTO "conversations_new" ("id", "name", "created_at", "updated_at")
+        SELECT "id", "name", "created_at", "updated_at" FROM "conversations";
+        DROP TABLE "conversations";
+        ALTER TABLE "conversations_new" RENAME TO "conversations";"""
+
+
+async def downgrade(db: BaseDBAsyncClient) -> str:
+    return """
+        -- Recreate table without user_id column
+        CREATE TABLE "conversations_new" (
+            "id" CHAR(36) NOT NULL PRIMARY KEY,
+            "name" VARCHAR(255) NOT NULL,
+            "created_at" TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
+            "updated_at" TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
+        );
+        INSERT INTO "conversations_new" ("id", "name", "created_at", "updated_at")
+        SELECT "id", "name", "created_at", "updated_at" FROM "conversations";
+        DROP TABLE "conversations";
+        ALTER TABLE "conversations_new" RENAME TO "conversations";"""
+
+
+MODELS_STATE = (
+    "eJztmWtP2zAUhv9KlE8gbQg6xhCaJqWlbB20ndp0F9gUuYnbWiROiJ1Bhfjvs91cnMRNKe"
+    "PSon6B9vic2H5s57w+vdU934Eu2Wn4+C8MCaDIx/qRdqtj4EH2Qdn+RtNBEGSt3EDB0BUB"
+    "tuQpWsCQ0BDYlDWOgEsgMzmQ2CEK4s5w5Lrc6NvMEeFxZoowuoqgRf0xpBMYsoaLP8yMsA"
+    "NvIEm+BpfWCEHXyY0bObxvYbfoNBC2waB1fCI8eXdDy/bdyMOZdzClEx+n7lGEnB0ew9vG"
+    "EMMQUOhI0+CjjKedmGYjZgYaRjAdqpMZHDgCkcth6B9HEbY5A030xP/sf9KXwMNQc7QIU8"
+    "7i9m42q2zOwqrzrhpfjN7Wu4NtMUuf0HEoGgUR/U4EAgpmoYJrBlL8L6FsTECoRpn4F2Cy"
+    "gT4EY2LIOGZ7KAGZAHoYNd0DN5YL8ZhO2Nfa+/cVGL8bPUGSeQmUPtvXs13fiZtqszaONE"
+    "Noh5BP2QK0DPKYtVDkQTXMfGQBqROH7iQfVhQwm4PTxe40PgQVfM1Wu9k3jfY3PhOPkCtX"
+    "IDLMJm+pCeu0YN06KCxF+hDtR8v8ovGv2nm30yzu/dTPPNf5mEBEfQv71xZwpPOaWBMwuY"
+    "WNAueBC5uP3Czsiy5sPHhpXQkMreUyiBTyH2kkHtszLuLDkwZPvaNLZc7gMMrwTvwQojE+"
+    "hVOBsMXGAbCtShax6BjEj1lVaJk1G0UIrlM1Im8KNjs2J0hn2dPoN4zjpi4YDoF9eQ1Cx5"
+    "oD04OEgDEkZaD1OPLktAfdVJqpWcoCrj174mq+VeaxFaz8mi8xytErN3k1r2gBmM3bifvm"
+    "PVXQWaCCJYj3E8OWvJAbUbzWopjCG0XKN5lVjTLxXxdRXJXKmz/NXBZPpO9W2/i5ncvkZ9"
+    "3O58RdksqNs259o5Bfo5AqK2QSQHCpEgP8AtnEkVeSArnVlcJf+Ojog36zd6TxjP4b91vt"
+    "unGkEeQNgX6/Jc7dMvd273HJ3Nude8fkTYUDJCea5V7zitDHfOevqYS1CwWv/5SyxfrZyl"
+    "JcqGkV22VZbfuUSk7cGRTSLblLzNdq/GhvtNn6azO+jssWLeWYddFoz1C4DAAh136o2Jl1"
+    "hEE4VcOUowowh1M6u/+sHs4KenUuWGW9xZjVWx2j90uteRN/eePWf5lNo4AXegC5y2zTNO"
+    "Bx9ujiI/+YO3Rv936qp0r2lHXP5uLwOi8Om9L6q1jYtHJXEoCLyp6l35Efp/a5VvXkJ615"
+    "GjBE9kRXaOW4pVItg8xnZeRyC88pvynVMsdc2Azxyr9ozhSV57e1vf0P+4fvDvYPmYsYSW"
+    "r5UPEyaHXMBeqYHwTllXa+6pBCNto4BcmPxhIQY/f1BPg00s3HFGJFev/a73bmlqqSkALI"
+    "AWYTvHCQTd9oLiL0z2piraDIZ11dVy+W0Au5mT+gripqPWch5u4f/FVgYA=="
+)

pyproject.toml

@@ -4,24 +4,9 @@ version = "0.1.0"
 description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.13"
-dependencies = [
+dependencies = ["chromadb>=1.1.0", "python-dotenv>=1.0.0", "flask>=3.1.2", "httpx>=0.28.1", "ollama>=0.6.0", "openai>=2.0.1", "pydantic>=2.11.9", "pillow>=10.0.0", "pymupdf>=1.24.0", "black>=25.9.0", "pillow-heif>=1.1.1", "flask-jwt-extended>=4.7.1", "bcrypt>=5.0.0", "pony>=0.7.19", "flask-login>=0.6.3", "quart>=0.20.0", "tortoise-orm>=0.25.1", "quart-jwt-extended>=0.1.0", "pre-commit>=4.3.0", "tortoise-orm-stubs>=1.0.2", "aerich>=0.8.0", "tomlkit>=0.13.3"]
-    "chromadb>=1.1.0",
+
-    "python-dotenv>=1.0.0",
+[tool.aerich]
-    "flask>=3.1.2",
+tortoise_orm = "app.TORTOISE_CONFIG"
-    "httpx>=0.28.1",
+location = "./migrations"
-    "ollama>=0.6.0",
+src_folder = "./."
-    "openai>=2.0.1",
-    "pydantic>=2.11.9",
-    "pillow>=10.0.0",
-    "pymupdf>=1.24.0",
-    "black>=25.9.0",
-    "pillow-heif>=1.1.1",
-    "flask-jwt-extended>=4.7.1",
-    "bcrypt>=5.0.0",
-    "pony>=0.7.19",
-    "flask-login>=0.6.3",
-    "quart>=0.20.0",
-    "tortoise-orm>=0.25.1",
-    "quart-jwt-extended>=0.1.0",
-    "pre-commit>=4.3.0",
-]

query.py

@@ -49,11 +49,20 @@ DOCTYPE_OPTIONS = [
     "Letter",
 ]
 
+QUERY_TYPE_OPTIONS = [
+    "Simba",
+    "Other",
+]
+
 
 class DocumentType(BaseModel):
     type: list[str] = Field(description="type of document", enum=DOCTYPE_OPTIONS)
 
 
+class QueryType(BaseModel):
+    type: str = Field(desciption="type of query", enum=QUERY_TYPE_OPTIONS)
+
+
 PROMPT = """
 You are an information specialist that processes user queries. The current year is 2025. The user queries are all about
 a cat, Simba, and its records. The types of records are listed below. Using the query, extract the
@@ -111,6 +120,27 @@ Query: "Who does Simba know?"
 Tags: ["Letter", "Documentation"]
 """
 
+QUERY_TYPE_PROMPT = f"""You are an information specialist that processes user queries.
+A query can have one tag attached from the following options. Based on the query and the transcript which is listed below, determine
+ which of the following options is most appropriate: {",".join(QUERY_TYPE_OPTIONS)}
+
+### Example 1
+Query: "Who is Simba's current vet?"
+Tags: ["Simba"]
+
+
+### Example 2
+Query: "What is the capital of Tokyo?"
+Tags: ["Other"]
+
+
+### Example 3
+Query: "Can you help me write an email?"
+Tags: ["Other"]
+
+TRANSCRIPT:
+"""
+
 
 class QueryGenerator:
     def __init__(self) -> None:
@@ -154,6 +184,33 @@ class QueryGenerator:
         metadata_query = {"document_type": {"$in": type_data["type"]}}
         return metadata_query
 
+    def get_query_type(self, input: str, transcript: str):
+        client = OpenAI()
+        response = client.chat.completions.create(
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are an information specialist that is really good at deciding what tags a query should have",
+                },
+                {
+                    "role": "user",
+                    "content": f"{QUERY_TYPE_PROMPT}\nTRANSCRIPT:\n{transcript}\nQUERY:{input}",
+                },
+            ],
+            model="gpt-4o",
+            response_format={
+                "type": "json_schema",
+                "json_schema": {
+                    "name": "query_type",
+                    "schema": QueryType.model_json_schema(),
+                },
+            },
+        )
+
+        response_json_str = response.choices[0].message.content
+        type_data = json.loads(response_json_str)
+        return type_data["type"]
+
     def get_query(self, input: str):
         client = OpenAI()
         response = client.responses.parse(

raggr-frontend/TOKEN_REFRESH_IMPLEMENTATION.md

@@ -0,0 +1,63 @@
+# Token Refresh Implementation
+
+## Overview
+
+The API services now automatically handle token refresh when access tokens expire. This provides a seamless user experience without requiring manual re-authentication.
+
+## How It Works
+
+### 1. **userService.ts**
+
+The `userService` now includes:
+
+- **`refreshToken()`**: Automatically gets the refresh token from localStorage, calls the `/api/user/refresh` endpoint, and updates the access token
+- **`fetchWithAuth()`**: A wrapper around `fetch()` that:
+  1. Automatically adds the Authorization header with the access token
+  2. Detects 401 (Unauthorized) responses
+  3. Automatically refreshes the token using the refresh token
+  4. Retries the original request with the new access token
+  5. Throws an error if refresh fails (e.g., refresh token expired)
+
+### 2. **conversationService.ts**
+
+Now uses `userService.fetchWithAuth()` for all API calls:
+- `sendQuery()` - No longer needs token parameter
+- `getMessages()` - No longer needs token parameter
+
+### 3. **Components Updated**
+
+**ChatScreen.tsx**:
+- Removed manual token handling
+- Now simply calls `conversationService.sendQuery(query)` and `conversationService.getMessages()`
+
+## Benefits
+
+✅ **Automatic token refresh** - Users stay logged in longer
+✅ **Transparent retry logic** - Failed requests due to expired tokens are automatically retried
+✅ **Cleaner code** - Components don't need to manage tokens
+✅ **Better UX** - No interruptions when access token expires
+✅ **Centralized auth logic** - All auth handling in one place
+
+## Error Handling
+
+- If refresh token is missing or invalid, the error is thrown
+- Components can catch these errors and redirect to login
+- LocalStorage is automatically cleared when refresh fails
+
+## Usage Example
+
+```typescript
+// Old way (manual token management)
+const token = localStorage.getItem("access_token");
+const result = await conversationService.sendQuery(query, token);
+
+// New way (automatic token refresh)
+const result = await conversationService.sendQuery(query);
+```
+
+## Token Storage
+
+- **Access Token**: `localStorage.getItem("access_token")`
+- **Refresh Token**: `localStorage.getItem("refresh_token")`
+
+Both are automatically managed by the services.

raggr-frontend/package.json

@@ -6,14 +6,18 @@
   "scripts": {
     "build": "rsbuild build",
     "dev": "rsbuild dev --open",
-    "preview": "rsbuild preview"
+    "preview": "rsbuild preview",
+    "watch": "npm-watch build",
+    "watch:build": "rsbuild build --watch"
   },
   "dependencies": {
     "axios": "^1.12.2",
     "marked": "^16.3.0",
+    "npm-watch": "^0.13.0",
     "react": "^19.1.1",
     "react-dom": "^19.1.1",
-    "react-markdown": "^10.1.0"
+    "react-markdown": "^10.1.0",
+    "watch": "^1.0.2"
   },
   "devDependencies": {
     "@rsbuild/core": "^1.5.6",
@@ -22,5 +26,16 @@
     "@types/react": "^19.1.13",
     "@types/react-dom": "^19.1.9",
     "typescript": "^5.9.2"
+  },
+  "watch": {
+    "build": {
+      "patterns": [
+        "src"
+      ],
+      "extensions": "ts,tsx,css,js,jsx",
+      "delay": 1000,
+      "quiet": false,
+      "inherit": true
+    }
   }
 }

raggr-frontend/rsbuild.config.ts

@@ -3,4 +3,8 @@ import { pluginReact } from '@rsbuild/plugin-react';
 
 export default defineConfig({
   plugins: [pluginReact()],
+  html: {
+    title: 'Raggr',
+    favicon: './src/assets/favicon.svg',
+  },
 });

raggr-frontend/src/App.tsx

@@ -1,203 +1,71 @@
-import { useEffect, useState } from "react";
+import { useState, useEffect } from "react";
-import axios from "axios";
-import ReactMarkdown from "react-markdown";
 
 import "./App.css";
+import { AuthProvider } from "./contexts/AuthContext";
+import { ChatScreen } from "./components/ChatScreen";
+import { LoginScreen } from "./components/LoginScreen";
+import { conversationService } from "./api/conversationService";
 
-type QuestionAnswer = {
+const AppContainer = () => {
-  question: string;
+  const [isAuthenticated, setAuthenticated] = useState<boolean>(false);
-  answer: string;
+  const [isChecking, setIsChecking] = useState<boolean>(true);
-};
 
-type QuestionBubbleProps = {
+  useEffect(() => {
-  text: string;
+    const checkAuth = async () => {
-};
+      const accessToken = localStorage.getItem("access_token");
+      const refreshToken = localStorage.getItem("refresh_token");
 
-type AnswerBubbleProps = {
+      // No tokens at all, not authenticated
-  text: string;
+      if (!accessToken && !refreshToken) {
-  loading: string;
+        setIsChecking(false);
-};
+        setAuthenticated(false);
+        return;
+      }
 
-type QuestionAnswerPairProps = {
+      // Try to verify token by making a request
-  question: string;
+      try {
-  answer: string;
+        await conversationService.getMessages();
-  loading: boolean;
+        // If successful, user is authenticated
-};
+        setAuthenticated(true);
+      } catch (error) {
+        // Token is invalid or expired
+        console.error("Authentication check failed:", error);
+        localStorage.removeItem("access_token");
+        localStorage.removeItem("refresh_token");
+        setAuthenticated(false);
+      } finally {
+        setIsChecking(false);
+      }
+    };
 
-type Conversation = {
+    checkAuth();
-  title: string;
+  }, []);
-  id: string;
-};
 
-type Message = {
+  // Show loading state while checking authentication
-  text: string;
+  if (isChecking) {
-  speaker: "simba" | "user";
-};
-
-type ConversationMenuProps = {
-  conversations: Conversation[];
-};
-
-const ConversationMenu = ({ conversations }: ConversationMenuProps) => {
     return (
-    <div className="absolute bg-white w-md rounded-md shadow-xl m-4 p-4">
+      <div className="h-screen flex items-center justify-center bg-white/85">
-      <p className="py-2 px-4 rounded-md w-full text-xl font-bold">askSimba!</p>
+        <div className="text-xl">Loading...</div>
-      {conversations.map((conversation) => (
-        <p className="py-2 px-4 rounded-md hover:bg-stone-200 w-full text-xl font-bold cursor-pointer">
-          {conversation.title}
-        </p>
-      ))}
       </div>
     );
-};
+  }
 
-const QuestionBubble = ({ text }: QuestionBubbleProps) => {
-  return <div className="rounded-md bg-stone-200 p-3">🤦: {text}</div>;
-};
-
-const AnswerBubble = ({ text, loading }: AnswerBubbleProps) => {
   return (
-    <div className="rounded-md bg-orange-100 p-3">
+    <>
-      {loading ? (
+      {isAuthenticated ? (
-        <div className="flex flex-col w-full animate-pulse gap-2">
+        <ChatScreen setAuthenticated={setAuthenticated} />
-          <div className="flex flex-row gap-2 w-full">
-            <div className="bg-gray-400 w-1/2 p-3 rounded-lg" />
-            <div className="bg-gray-400 w-1/2 p-3 rounded-lg" />
-          </div>
-          <div className="flex flex-row gap-2 w-full">
-            <div className="bg-gray-400 w-1/3 p-3 rounded-lg" />
-            <div className="bg-gray-400 w-2/3 p-3 rounded-lg" />
-          </div>
-        </div>
       ) : (
-        <div className="flex flex-col">
+        <LoginScreen setAuthenticated={setAuthenticated} />
-          <ReactMarkdown>{"🐈: " + text}</ReactMarkdown>
-        </div>
       )}
-    </div>
+    </>
-  );
-};
-
-const QuestionAnswerPair = ({
-  question,
-  answer,
-  loading,
-}: QuestionAnswerPairProps) => {
-  return (
-    <div className="flex flex-col gap-4">
-      <QuestionBubble text={question} />
-      <AnswerBubble text={answer} loading={loading} />
-    </div>
   );
 };
 
 const App = () => {
-  const [query, setQuery] = useState<string>("");
-  const [answer, setAnswer] = useState<string>("");
-  const [simbaMode, setSimbaMode] = useState<boolean>(false);
-  const [questionsAnswers, setQuestionsAnswers] = useState<QuestionAnswer[]>(
-    [],
-  );
-  const [messages, setMessages] = useState<Message[]>([]);
-  const [conversations, setConversations] = useState<Conversation[]>([
-    { title: "simba meow meow", id: "uuid" },
-  ]);
-
-  const simbaAnswers = ["meow.", "hiss...", "purrrrrr", "yowOWROWWowowr"];
-
-  useEffect(() => {
-    axios.get("/api/messages").then((result) => {
-      setMessages(
-        result.data.messages.map((message) => {
-          return {
-            text: message.text,
-            speaker: message.speaker,
-          };
-        }),
-      );
-    });
-  }, []);
-
-  const handleQuestionSubmit = () => {
-    let currMessages = messages.concat([{ text: query, speaker: "user" }]);
-    setMessages(currMessages);
-    if (simbaMode) {
-      console.log("simba mode activated");
-      const randomIndex = Math.floor(Math.random() * simbaAnswers.length);
-      const randomElement = simbaAnswers[randomIndex];
-      setAnswer(randomElement);
-      setQuestionsAnswers(
-        questionsAnswers.concat([
-          {
-            question: query,
-            answer: randomElement,
-          },
-        ]),
-      );
-      return;
-    }
-    const payload = { query: query };
-    axios.post("/api/query", payload).then((result) => {
-      setQuestionsAnswers(
-        questionsAnswers.concat([
-          { question: query, answer: result.data.response },
-        ]),
-      );
-      setMessages(
-        currMessages.concat([{ text: result.data.response, speaker: "simba" }]),
-      );
-    });
-  };
-  const handleQueryChange = (event) => {
-    setQuery(event.target.value);
-  };
   return (
-    <div className="h-screen bg-opacity-20">
+    <AuthProvider>
-      <div className="bg-white/85 h-screen">
+      <AppContainer />
-        <div className="flex flex-row justify-center py-4">
+    </AuthProvider>
-          <div className="flex flex-col gap-4 min-w-xl max-w-xl">
-            <header className="flex flex-row justify-center gap-2 grow sticky top-0 z-10 bg-white">
-              <h1 className="text-3xl">ask simba!</h1>
-            </header>
-            {/*{questionsAnswers.map((qa) => (
-              <QuestionAnswerPair question={qa.question} answer={qa.answer} />
-            ))}*/}
-            {messages.map((msg) => {
-              if (msg.speaker == "simba") {
-                return <AnswerBubble text={msg.text} loading="" />;
-              }
-
-              return <QuestionBubble text={msg.text} />;
-            })}
-            <footer className="flex flex-col gap-2 sticky bottom-0">
-              <div className="flex flex-row justify-between gap-2 grow">
-                <textarea
-                  type="text"
-                  className="p-4 border border-blue-200 rounded-md grow bg-white"
-                  onChange={handleQueryChange}
-                />
-              </div>
-              <div className="flex flex-row justify-between gap-2 grow">
-                <button
-                  className="p-4 border border-blue-400 bg-blue-200 hover:bg-blue-400 cursor-pointer rounded-md flex-grow"
-                  onClick={() => handleQuestionSubmit()}
-                  type="submit"
-                >
-                  Submit
-                </button>
-              </div>
-              <div className="flex flex-row justify-center gap-2 grow">
-                <input
-                  type="checkbox"
-                  onChange={(event) => setSimbaMode(event.target.checked)}
-                />
-                <p>simba mode?</p>
-              </div>
-            </footer>
-          </div>
-        </div>
-      </div>
-    </div>
   );
 };
 

raggr-frontend/src/api/conversationService.ts

@@ -0,0 +1,115 @@
+import { userService } from "./userService";
+
+interface Message {
+  id: string;
+  text: string;
+  speaker: "user" | "simba";
+  created_at: string;
+}
+
+interface Conversation {
+  id: string;
+  name: string;
+  messages?: Message[];
+  created_at: string;
+  updated_at: string;
+  user_id?: string;
+}
+
+interface QueryRequest {
+  query: string;
+}
+
+interface QueryResponse {
+  response: string;
+}
+
+interface CreateConversationRequest {
+  user_id: string;
+}
+
+class ConversationService {
+  private baseUrl = "/api";
+  private conversationBaseUrl = "/api/conversation";
+
+  async sendQuery(
+    query: string,
+    conversation_id: string,
+  ): Promise<QueryResponse> {
+    const response = await userService.fetchWithRefreshToken(
+      `${this.baseUrl}/query`,
+      {
+        method: "POST",
+        body: JSON.stringify({ query, conversation_id }),
+      },
+    );
+
+    if (!response.ok) {
+      throw new Error("Failed to send query");
+    }
+
+    return await response.json();
+  }
+
+  async getMessages(): Promise<Conversation> {
+    const response = await userService.fetchWithRefreshToken(
+      `${this.baseUrl}/messages`,
+      {
+        method: "GET",
+      },
+    );
+
+    if (!response.ok) {
+      throw new Error("Failed to fetch messages");
+    }
+
+    return await response.json();
+  }
+
+  async getConversation(conversationId: string): Promise<Conversation> {
+    const response = await userService.fetchWithRefreshToken(
+      `${this.conversationBaseUrl}/${conversationId}`,
+      {
+        method: "GET",
+      },
+    );
+
+    if (!response.ok) {
+      throw new Error("Failed to fetch conversation");
+    }
+
+    return await response.json();
+  }
+
+  async createConversation(): Promise<Conversation> {
+    const response = await userService.fetchWithRefreshToken(
+      `${this.conversationBaseUrl}/`,
+      {
+        method: "POST",
+      },
+    );
+
+    if (!response.ok) {
+      throw new Error("Failed to create conversation");
+    }
+
+    return await response.json();
+  }
+
+  async getAllConversations(): Promise<Conversation[]> {
+    const response = await userService.fetchWithRefreshToken(
+      `${this.conversationBaseUrl}/`,
+      {
+        method: "GET",
+      },
+    );
+
+    if (!response.ok) {
+      throw new Error("Failed to fetch conversations");
+    }
+
+    return await response.json();
+  }
+}
+
+export const conversationService = new ConversationService();

raggr-frontend/src/api/userService.ts

@@ -0,0 +1,123 @@
+interface LoginResponse {
+  access_token: string;
+  refresh_token: string;
+  user: {
+    id: string;
+    username: string;
+  };
+}
+
+interface RefreshResponse {
+  access_token: string;
+}
+
+class UserService {
+  private baseUrl = "/api/user";
+
+  async login(username: string, password: string): Promise<LoginResponse> {
+    const response = await fetch(`${this.baseUrl}/login`, {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({ username, password }),
+    });
+
+    if (!response.ok) {
+      throw new Error("Invalid credentials");
+    }
+
+    return await response.json();
+  }
+
+  async refreshToken(): Promise<string> {
+    const refreshToken = localStorage.getItem("refresh_token");
+
+    if (!refreshToken) {
+      throw new Error("No refresh token available");
+    }
+
+    const response = await fetch(`${this.baseUrl}/refresh`, {
+      method: "POST",
+      headers: {
+        "Content-Type": "application/json",
+        Authorization: `Bearer ${refreshToken}`,
+      },
+    });
+
+    if (!response.ok) {
+      // Refresh token is invalid or expired, clear storage
+      localStorage.removeItem("access_token");
+      localStorage.removeItem("refresh_token");
+      throw new Error("Failed to refresh token");
+    }
+
+    const data: RefreshResponse = await response.json();
+    localStorage.setItem("access_token", data.access_token);
+    return data.access_token;
+  }
+
+  async fetchWithAuth(
+    url: string,
+    options: RequestInit = {},
+  ): Promise<Response> {
+    const accessToken = localStorage.getItem("access_token");
+
+    // Add authorization header
+    const headers = {
+      "Content-Type": "application/json",
+      ...(options.headers || {}),
+      ...(accessToken && { Authorization: `Bearer ${accessToken}` }),
+    };
+
+    let response = await fetch(url, { ...options, headers });
+
+    // If unauthorized, try refreshing the token
+    if (response.status === 401) {
+      try {
+        const newAccessToken = await this.refreshToken();
+
+        // Retry the request with new token
+        headers.Authorization = `Bearer ${newAccessToken}`;
+        response = await fetch(url, { ...options, headers });
+      } catch (error) {
+        // Refresh failed, redirect to login or throw error
+        throw new Error("Session expired. Please log in again.");
+      }
+    }
+
+    return response;
+  }
+
+  async fetchWithRefreshToken(
+    url: string,
+    options: RequestInit = {},
+  ): Promise<Response> {
+    const refreshToken = localStorage.getItem("refresh_token");
+
+    // Add authorization header
+    const headers = {
+      "Content-Type": "application/json",
+      ...(options.headers || {}),
+      ...(refreshToken && { Authorization: `Bearer ${refreshToken}` }),
+    };
+
+    let response = await fetch(url, { ...options, headers });
+
+    // If unauthorized, try refreshing the token
+    if (response.status === 401) {
+      try {
+        const newAccessToken = await this.refreshToken();
+
+        // Retry the request with new token
+        headers.Authorization = `Bearer ${newAccessToken}`;
+        response = await fetch(url, { ...options, headers });
+      } catch (error) {
+        // Refresh failed, redirect to login or throw error
+        throw new Error("Session expired. Please log in again.");
+      }
+    }
+
+    return response;
+  }
+}
+
+export const userService = new UserService();

raggr-frontend/src/assets/favicon.svg

@@ -0,0 +1,3 @@
+<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 100 100">
+  <text y="80" font-size="80" font-family="system-ui, -apple-system, sans-serif">🐱</text>
+</svg>

raggr-frontend/src/components/AnswerBubble.tsx

@@ -0,0 +1,29 @@
+import ReactMarkdown from "react-markdown";
+
+type AnswerBubbleProps = {
+  text: string;
+  loading?: boolean;
+};
+
+export const AnswerBubble = ({ text, loading }: AnswerBubbleProps) => {
+  return (
+    <div className="rounded-md bg-orange-100 p-3">
+      {loading ? (
+        <div className="flex flex-col w-full animate-pulse gap-2">
+          <div className="flex flex-row gap-2 w-full">
+            <div className="bg-gray-400 w-1/2 p-3 rounded-lg" />
+            <div className="bg-gray-400 w-1/2 p-3 rounded-lg" />
+          </div>
+          <div className="flex flex-row gap-2 w-full">
+            <div className="bg-gray-400 w-1/3 p-3 rounded-lg" />
+            <div className="bg-gray-400 w-2/3 p-3 rounded-lg" />
+          </div>
+        </div>
+      ) : (
+        <div className="flex flex-col">
+          <ReactMarkdown>{"🐈: " + text}</ReactMarkdown>
+        </div>
+      )}
+    </div>
+  );
+};

raggr-frontend/src/components/ChatScreen.tsx

@@ -0,0 +1,228 @@
+import { useEffect, useState } from "react";
+import { conversationService } from "../api/conversationService";
+import { QuestionBubble } from "./QuestionBubble";
+import { AnswerBubble } from "./AnswerBubble";
+import { ConversationList } from "./ConversationList";
+import { parse } from "node:path/win32";
+
+type Message = {
+  text: string;
+  speaker: "simba" | "user";
+};
+
+type QuestionAnswer = {
+  question: string;
+  answer: string;
+};
+
+type Conversation = {
+  title: string;
+  id: string;
+};
+
+type ChatScreenProps = {
+  setAuthenticated: (isAuth: boolean) => void;
+};
+
+export const ChatScreen = ({ setAuthenticated }: ChatScreenProps) => {
+  const [query, setQuery] = useState<string>("");
+  const [answer, setAnswer] = useState<string>("");
+  const [simbaMode, setSimbaMode] = useState<boolean>(false);
+  const [questionsAnswers, setQuestionsAnswers] = useState<QuestionAnswer[]>(
+    [],
+  );
+  const [messages, setMessages] = useState<Message[]>([]);
+  const [conversations, setConversations] = useState<Conversation[]>([
+    { title: "simba meow meow", id: "uuid" },
+  ]);
+  const [showConversations, setShowConversations] = useState<boolean>(false);
+  const [selectedConversation, setSelectedConversation] =
+    useState<Conversation | null>(null);
+
+  const simbaAnswers = ["meow.", "hiss...", "purrrrrr", "yowOWROWWowowr"];
+
+  const handleSelectConversation = (conversation: Conversation) => {
+    setShowConversations(false);
+    setSelectedConversation(conversation);
+    const loadMessages = async () => {
+      try {
+        const fetchedConversation = await conversationService.getConversation(
+          conversation.id,
+        );
+        setMessages(
+          fetchedConversation.messages.map((message) => ({
+            text: message.text,
+            speaker: message.speaker,
+          })),
+        );
+      } catch (error) {
+        console.error("Failed to load messages:", error);
+      }
+    };
+    loadMessages();
+  };
+
+  const loadConversations = async () => {
+    try {
+      const fetchedConversations =
+        await conversationService.getAllConversations();
+      const parsedConversations = fetchedConversations.map((conversation) => ({
+        id: conversation.id,
+        title: conversation.name,
+      }));
+      setConversations(parsedConversations);
+      setSelectedConversation(parsedConversations[0]);
+      console.log(parsedConversations);
+    } catch (error) {
+      console.error("Failed to load messages:", error);
+    }
+  };
+
+  const handleCreateNewConversation = async () => {
+    const newConversation = await conversationService.createConversation();
+    await loadConversations();
+    setSelectedConversation({
+      title: newConversation.name,
+      id: newConversation.id,
+    });
+  };
+
+  useEffect(() => {
+    loadConversations();
+  }, []);
+
+  useEffect(() => {
+    const loadMessages = async () => {
+      if (selectedConversation == null) return;
+      try {
+        const conversation = await conversationService.getConversation(
+          selectedConversation.id,
+        );
+        setMessages(
+          conversation.messages.map((message) => ({
+            text: message.text,
+            speaker: message.speaker,
+          })),
+        );
+      } catch (error) {
+        console.error("Failed to load messages:", error);
+      }
+    };
+    loadMessages();
+  }, [selectedConversation]);
+
+  const handleQuestionSubmit = async () => {
+    const currMessages = messages.concat([{ text: query, speaker: "user" }]);
+    setMessages(currMessages);
+
+    if (simbaMode) {
+      console.log("simba mode activated");
+      const randomIndex = Math.floor(Math.random() * simbaAnswers.length);
+      const randomElement = simbaAnswers[randomIndex];
+      setAnswer(randomElement);
+      setQuestionsAnswers(
+        questionsAnswers.concat([
+          {
+            question: query,
+            answer: randomElement,
+          },
+        ]),
+      );
+      return;
+    }
+
+    try {
+      const result = await conversationService.sendQuery(
+        query,
+        selectedConversation.id,
+      );
+      setQuestionsAnswers(
+        questionsAnswers.concat([{ question: query, answer: result.response }]),
+      );
+      setMessages(
+        currMessages.concat([{ text: result.response, speaker: "simba" }]),
+      );
+      setQuery(""); // Clear input after successful send
+    } catch (error) {
+      console.error("Failed to send query:", error);
+      // If session expired, redirect to login
+      if (error instanceof Error && error.message.includes("Session expired")) {
+        setAuthenticated(false);
+      }
+    }
+  };
+
+  const handleQueryChange = (event: React.ChangeEvent<HTMLTextAreaElement>) => {
+    setQuery(event.target.value);
+  };
+
+  return (
+    <div className="h-screen bg-opacity-20">
+      <div className="bg-white/85 h-screen">
+        <div className="flex flex-row justify-center py-4">
+          <div className="flex flex-col gap-4 min-w-xl max-w-xl">
+            <div className="flex flex-row justify-between">
+              <header className="flex flex-row justify-center gap-2 sticky top-0 z-10 bg-white">
+                <h1 className="text-3xl">ask simba!</h1>
+              </header>
+              <div className="flex flex-row gap-2">
+                <button
+                  className="p-2 border border-green-400 bg-green-200 hover:bg-green-400 cursor-pointer rounded-md"
+                  onClick={() => setShowConversations(!showConversations)}
+                >
+                  {showConversations
+                    ? "hide conversations"
+                    : "show conversations"}
+                </button>
+                <button
+                  className="p-2 border border-red-400 bg-red-200 hover:bg-red-400 cursor-pointer rounded-md"
+                  onClick={() => setAuthenticated(false)}
+                >
+                  logout
+                </button>
+              </div>
+            </div>
+            {showConversations && (
+              <ConversationList
+                conversations={conversations}
+                onCreateNewConversation={handleCreateNewConversation}
+                onSelectConversation={handleSelectConversation}
+              />
+            )}
+            {messages.map((msg, index) => {
+              if (msg.speaker === "simba") {
+                return <AnswerBubble key={index} text={msg.text} />;
+              }
+              return <QuestionBubble key={index} text={msg.text} />;
+            })}
+            <footer className="flex flex-col gap-2 sticky bottom-0">
+              <div className="flex flex-row justify-between gap-2 grow">
+                <textarea
+                  className="p-4 border border-blue-200 rounded-md grow bg-white"
+                  onChange={handleQueryChange}
+                  value={query}
+                />
+              </div>
+              <div className="flex flex-row justify-between gap-2 grow">
+                <button
+                  className="p-4 border border-blue-400 bg-blue-200 hover:bg-blue-400 cursor-pointer rounded-md flex-grow"
+                  onClick={() => handleQuestionSubmit()}
+                  type="submit"
+                >
+                  Submit
+                </button>
+              </div>
+              <div className="flex flex-row justify-center gap-2 grow">
+                <input
+                  type="checkbox"
+                  onChange={(event) => setSimbaMode(event.target.checked)}
+                />
+                <p>simba mode?</p>
+              </div>
+            </footer>
+          </div>
+        </div>
+      </div>
+    </div>
+  );
+};

raggr-frontend/src/components/ConversationList.tsx

@@ -0,0 +1,60 @@
+import { useState, useEffect } from "react";
+
+import { conversationService } from "../api/conversationService";
+type Conversation = {
+  title: string;
+  id: string;
+};
+
+type ConversationProps = {
+  conversations: Conversation[];
+  onSelectConversation: (conversation: Conversation) => void;
+  onCreateNewConversation: () => void;
+};
+
+export const ConversationList = ({
+  conversations,
+  onSelectConversation,
+  onCreateNewConversation,
+}: ConversationProps) => {
+  const [conservations, setConversations] = useState(conversations);
+
+  useEffect(() => {
+    const loadConversations = async () => {
+      try {
+        const fetchedConversations =
+          await conversationService.getAllConversations();
+        setConversations(
+          fetchedConversations.map((conversation) => ({
+            id: conversation.id,
+            title: conversation.name,
+          })),
+        );
+      } catch (error) {
+        console.error("Failed to load messages:", error);
+      }
+    };
+    loadConversations();
+  }, []);
+
+  return (
+    <div className="bg-indigo-300 rounded-md p-3 flex flex-col">
+      {conservations.map((conversation) => {
+        return (
+          <div
+            className="border-blue-400 bg-indigo-300 hover:bg-indigo-200 cursor-pointer rounded-md p-2"
+            onClick={() => onSelectConversation(conversation)}
+          >
+            <p>{conversation.title}</p>
+          </div>
+        );
+      })}
+      <div
+        className="border-blue-400 bg-indigo-300 hover:bg-indigo-200 cursor-pointer rounded-md p-2"
+        onClick={() => onCreateNewConversation()}
+      >
+        <p> + Start a new thread</p>
+      </div>
+    </div>
+  );
+};

raggr-frontend/src/components/ConversationMenu.tsx

@@ -0,0 +1,24 @@
+type Conversation = {
+  title: string;
+  id: string;
+};
+
+type ConversationMenuProps = {
+  conversations: Conversation[];
+};
+
+export const ConversationMenu = ({ conversations }: ConversationMenuProps) => {
+  return (
+    <div className="absolute bg-white w-md rounded-md shadow-xl m-4 p-4">
+      <p className="py-2 px-4 rounded-md w-full text-xl font-bold">askSimba!</p>
+      {conversations.map((conversation) => (
+        <p
+          key={conversation.id}
+          className="py-2 px-4 rounded-md hover:bg-stone-200 w-full text-xl font-bold cursor-pointer"
+        >
+          {conversation.title}
+        </p>
+      ))}
+    </div>
+  );
+};

raggr-frontend/src/components/LoginScreen.tsx

@@ -0,0 +1,80 @@
+import { useState } from "react";
+import { userService } from "../api/userService";
+
+type LoginScreenProps = {
+  setAuthenticated: (isAuth: boolean) => void;
+};
+
+export const LoginScreen = ({ setAuthenticated }: LoginScreenProps) => {
+  const [username, setUsername] = useState<string>("");
+  const [password, setPassword] = useState<string>("");
+  const [error, setError] = useState<string>("");
+
+  const handleLogin = async () => {
+    if (!username || !password) {
+      setError("Please enter username and password");
+      return;
+    }
+
+    try {
+      const result = await userService.login(username, password);
+      localStorage.setItem("access_token", result.access_token);
+      localStorage.setItem("refresh_token", result.refresh_token);
+      setAuthenticated(true);
+      setError("");
+    } catch (err) {
+      setError("Login failed. Please check your credentials.");
+      console.error("Login error:", err);
+    }
+  };
+
+  return (
+    <div className="h-screen bg-opacity-20">
+      <div className="bg-white/85 h-screen">
+        <div className="flex flex-row justify-center py-4">
+          <div className="flex flex-col gap-4 min-w-xl max-w-xl">
+            <div className="flex flex-col gap-1">
+              <div className="flex flex-grow justify-center w-full bg-amber-400">
+                <h1 className="text-xl font-bold">
+                  I AM LOOKING FOR A DESIGNER. THIS APP WILL REMAIN UGLY UNTIL A
+                  DESIGNER COMES.
+                </h1>
+              </div>
+              <header className="flex flex-row justify-center gap-2 grow sticky top-0 z-10 bg-white">
+                <h1 className="text-3xl">ask simba!</h1>
+              </header>
+              <label htmlFor="username">username</label>
+              <input
+                type="text"
+                id="username"
+                name="username"
+                value={username}
+                onChange={(e) => setUsername(e.target.value)}
+                className="border border-s-slate-950 p-3 rounded-md"
+              />
+              <label htmlFor="password">password</label>
+              <input
+                type="password"
+                id="password"
+                name="password"
+                value={password}
+                onChange={(e) => setPassword(e.target.value)}
+                className="border border-s-slate-950 p-3 rounded-md"
+              />
+              {error && (
+                <div className="text-red-600 font-semibold">{error}</div>
+              )}
+            </div>
+
+            <button
+              className="p-4 border border-blue-400 bg-blue-200 hover:bg-blue-400 cursor-pointer rounded-md flex-grow"
+              onClick={handleLogin}
+            >
+              login
+            </button>
+          </div>
+        </div>
+      </div>
+    </div>
+  );
+};

raggr-frontend/src/components/QuestionBubble.tsx

@@ -0,0 +1,7 @@
+type QuestionBubbleProps = {
+  text: string;
+};
+
+export const QuestionBubble = ({ text }: QuestionBubbleProps) => {
+  return <div className="rounded-md bg-stone-200 p-3">🤦: {text}</div>;
+};

raggr-frontend/src/contexts/AuthContext.tsx

@@ -0,0 +1,56 @@
+import { createContext, useContext, useState, ReactNode } from "react";
+import { userService } from "../api/userService";
+
+interface AuthContextType {
+  token: string | null;
+  login: (username: string, password: string) => Promise<any>;
+  logout: () => void;
+  isAuthenticated: () => boolean;
+}
+
+const AuthContext = createContext<AuthContextType | undefined>(undefined);
+
+interface AuthProviderProps {
+  children: ReactNode;
+}
+
+export const AuthProvider = ({ children }: AuthProviderProps) => {
+  const [token, setToken] = useState(localStorage.getItem("access_token"));
+
+  const login = async (username: string, password: string) => {
+    try {
+      const data = await userService.login(username, password);
+      setToken(data.access_token);
+      localStorage.setItem("access_token", data.access_token);
+      localStorage.setItem("refresh_token", data.refresh_token);
+      return data;
+    } catch (error) {
+      console.error("Login failed:", error);
+      throw error;
+    }
+  };
+
+  const logout = () => {
+    setToken(null);
+    localStorage.removeItem("access_token");
+    localStorage.removeItem("refresh_token");
+  };
+
+  const isAuthenticated = () => {
+    return token !== null && token !== undefined && token !== "";
+  };
+
+  return (
+    <AuthContext.Provider value={{ token, login, logout, isAuthenticated }}>
+      {children}
+    </AuthContext.Provider>
+  );
+};
+
+export const useAuth = () => {
+  const context = useContext(AuthContext);
+  if (context === undefined) {
+    throw new Error("useAuth must be used within an AuthProvider");
+  }
+  return context;
+};

startup.sh

@@ -1,5 +1,8 @@
 #!/bin/bash
 
+echo "Running database migrations..."
+aerich upgrade
+
 echo "Starting reindex process..."
 python main.py "" --reindex
 

uv.lock

@@ -2,6 +2,21 @@ version = 1
 revision = 2
 requires-python = ">=3.13"
 
+[[package]]
+name = "aerich"
+version = "0.9.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "anyio" },
+    { name = "asyncclick" },
+    { name = "dictdiffer" },
+    { name = "tortoise-orm" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/c4/60/5d3885f531fab2cecec67510e7b821efc403940ed9eefd034b2c21350f3c/aerich-0.9.2.tar.gz", hash = "sha256:02d58658714eebe396fe7bd9f9401db3a60a44dc885910ad3990920d0357317d", size = 74231, upload-time = "2025-10-10T05:53:49.632Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/87/1a/956c6b1e35881bb9835a33c8db1565edcd133f8e45321010489092a0df40/aerich-0.9.2-py3-none-any.whl", hash = "sha256:d0f007acb21f6559f1eccd4e404fb039cf48af2689e0669afa62989389c0582d", size = 46451, upload-time = "2025-10-10T05:53:48.71Z" },
+]
+
 [[package]]
 name = "aiofiles"
 version = "25.1.0"
@@ -45,6 +60,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/15/b3/9b1a8074496371342ec1e796a96f99c82c945a339cd81a8e73de28b4cf9e/anyio-4.11.0-py3-none-any.whl", hash = "sha256:0287e96f4d26d4149305414d4e3bc32f0dcd0862365a4bddea19d7a1ec38c4fc", size = 109097, upload-time = "2025-09-23T09:19:10.601Z" },
 ]
 
+[[package]]
+name = "asyncclick"
+version = "8.3.0.7"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "colorama", marker = "sys_platform == 'win32'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/f9/ca/25e426d16bd0e91c1c9259112cecd17b2c2c239bdd8e5dba430f3bd5e3ef/asyncclick-8.3.0.7.tar.gz", hash = "sha256:8a80d8ac613098ee6a9a8f0248f60c66c273e22402cf3f115ed7f071acfc71d3", size = 277634, upload-time = "2025-10-11T08:35:44.841Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/01/d9/782ffcb4c97b889bc12d8276637d2739b99520390ee8fec77c07416c5d12/asyncclick-8.3.0.7-py3-none-any.whl", hash = "sha256:7607046de39a3f315867cad818849f973e29d350c10d92f251db3ff7600c6c7d", size = 109925, upload-time = "2025-10-11T08:35:43.378Z" },
+]
+
 [[package]]
 name = "attrs"
 version = "25.3.0"
@@ -306,6 +333,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a7/06/3d6badcf13db419e25b07041d9c7b4a2c331d3f4e7134445ec5df57714cd/coloredlogs-15.0.1-py2.py3-none-any.whl", hash = "sha256:612ee75c546f53e92e70049c9dbfcc18c935a2b9a53b66085ce9ef6a6e5c0934", size = 46018, upload-time = "2021-06-11T10:22:42.561Z" },
 ]
 
+[[package]]
+name = "dictdiffer"
+version = "0.9.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/61/7b/35cbccb7effc5d7e40f4c55e2b79399e1853041997fcda15c9ff160abba0/dictdiffer-0.9.0.tar.gz", hash = "sha256:17bacf5fbfe613ccf1b6d512bd766e6b21fb798822a133aa86098b8ac9997578", size = 31513, upload-time = "2021-07-22T13:24:29.276Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/47/ef/4cb333825d10317a36a1154341ba37e6e9c087bac99c1990ef07ffdb376f/dictdiffer-0.9.0-py2.py3-none-any.whl", hash = "sha256:442bfc693cfcadaf46674575d2eba1c53b42f5e404218ca2c2ff549f2df56595", size = 16754, upload-time = "2021-07-22T13:24:26.783Z" },
+]
+
 [[package]]
 name = "distlib"
 version = "0.4.0"
@@ -1669,6 +1705,7 @@ name = "raggr"
 version = "0.1.0"
 source = { virtual = "." }
 dependencies = [
+    { name = "aerich" },
     { name = "bcrypt" },
     { name = "black" },
     { name = "chromadb" },
@@ -1687,11 +1724,14 @@ dependencies = [
     { name = "python-dotenv" },
     { name = "quart" },
     { name = "quart-jwt-extended" },
+    { name = "tomlkit" },
     { name = "tortoise-orm" },
+    { name = "tortoise-orm-stubs" },
 ]
 
 [package.metadata]
 requires-dist = [
+    { name = "aerich", specifier = ">=0.8.0" },
     { name = "bcrypt", specifier = ">=5.0.0" },
     { name = "black", specifier = ">=25.9.0" },
     { name = "chromadb", specifier = ">=1.1.0" },
@@ -1710,7 +1750,9 @@ requires-dist = [
     { name = "python-dotenv", specifier = ">=1.0.0" },
     { name = "quart", specifier = ">=0.20.0" },
     { name = "quart-jwt-extended", specifier = ">=0.1.0" },
+    { name = "tomlkit", specifier = ">=0.13.3" },
     { name = "tortoise-orm", specifier = ">=0.25.1" },
+    { name = "tortoise-orm-stubs", specifier = ">=1.0.2" },
 ]
 
 [[package]]
@@ -1918,6 +1960,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b3/46/e33a8c93907b631a99377ef4c5f817ab453d0b34f93529421f42ff559671/tokenizers-0.22.1-cp39-abi3-win_amd64.whl", hash = "sha256:65fd6e3fb11ca1e78a6a93602490f134d1fdeb13bcef99389d5102ea318ed138", size = 2674684, upload-time = "2025-09-19T09:49:24.953Z" },
 ]
 
+[[package]]
+name = "tomlkit"
+version = "0.13.3"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/cc/18/0bbf3884e9eaa38819ebe46a7bd25dcd56b67434402b66a58c4b8e552575/tomlkit-0.13.3.tar.gz", hash = "sha256:430cf247ee57df2b94ee3fbe588e71d362a941ebb545dec29b53961d61add2a1", size = 185207, upload-time = "2025-06-05T07:13:44.947Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/bd/75/8539d011f6be8e29f339c42e633aae3cb73bffa95dd0f9adec09b9c58e85/tomlkit-0.13.3-py3-none-any.whl", hash = "sha256:c89c649d79ee40629a9fda55f8ace8c6a1b42deb912b2a8fd8d942ddadb606b0", size = 38901, upload-time = "2025-06-05T07:13:43.546Z" },
+]
+
 [[package]]
 name = "tortoise-orm"
 version = "0.25.1"
@@ -1933,6 +1984,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/70/55/2bda7f4445f4c07b734385b46d1647a388d05160cf5b8714a713e8709378/tortoise_orm-0.25.1-py3-none-any.whl", hash = "sha256:df0ef7e06eb0650a7e5074399a51ee6e532043308c612db2cac3882486a3fd9f", size = 167723, upload-time = "2025-06-05T10:43:29.309Z" },
 ]
 
+[[package]]
+name = "tortoise-orm-stubs"
+version = "1.0.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "tortoise-orm" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ba/49/45b06cda907e55226b8ed4ddc71d13ff61505bfe366d72276462eeee9d2b/tortoise_orm_stubs-1.0.2.tar.gz", hash = "sha256:f4d6a810f295bebd83aa71b05ebd2decd883517f3c9530bd2376b9209b0777c6", size = 4559, upload-time = "2023-11-20T14:48:26.806Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/33/b1/f0b111dcf9381987f8acb143dd95b77934a3e9120a6c63b2cf4255c2934c/tortoise_orm_stubs-1.0.2-py3-none-any.whl", hash = "sha256:5ae3c2b0eb0286669563634b98202bbdf46349966b1c85659f3160de4fb655d6", size = 4681, upload-time = "2023-11-20T14:48:22.536Z" },
+]
+
 [[package]]
 name = "tqdm"
 version = "4.67.1"