Added conversation history

.env.example

@@ -1,28 +0,0 @@
-# Database Configuration
-# Use DATABASE_PATH for simple relative/absolute paths (e.g., "database/raggr.db" or "dev.db")
-# Or use DATABASE_URL for full connection strings (e.g., "sqlite://database/raggr.db")
-DATABASE_PATH=database/raggr.db
-# DATABASE_URL=sqlite://database/raggr.db
-
-# JWT Configuration
-JWT_SECRET_KEY=your-secret-key-here
-
-# Paperless Configuration
-PAPERLESS_TOKEN=your-paperless-token
-BASE_URL=192.168.1.5:8000
-
-# Ollama Configuration
-OLLAMA_URL=http://192.168.1.14:11434
-OLLAMA_HOST=http://192.168.1.14:11434
-
-# ChromaDB Configuration
-CHROMADB_PATH=/path/to/chromadb
-
-# OpenAI Configuration
-OPENAI_API_KEY=your-openai-api-key
-
-# Immich Configuration
-IMMICH_URL=http://192.168.1.5:2283
-IMMICH_API_KEY=your-immich-api-key
-SEARCH_QUERY=simba cat
-DOWNLOAD_DIR=./simba_photos

.gitignore

@@ -9,10 +9,5 @@ wheels/
 # Virtual environments
 .venv
 
-# Environment files
-.env
 
-# Database files
+.env
-chromadb/
-database/
-*.db

Dockerfile

@@ -23,8 +23,6 @@ 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
 
@@ -34,8 +32,8 @@ WORKDIR /app/raggr-frontend
 RUN yarn install && yarn build
 WORKDIR /app
 
-# Create ChromaDB and database directories
+# Create ChromaDB directory
-RUN mkdir -p /app/chromadb /app/database
+RUN mkdir -p /app/chromadb
 
 # Expose port
 EXPOSE 8080

app.py

@@ -0,0 +1,102 @@
+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 main import consult_simba_oracle
+from blueprints.conversation.logic import (
+    get_the_only_conversation,
+    add_message_to_conversation,
+)
+
+app = Quart(
+    __name__,
+    static_folder="raggr-frontend/dist/static",
+    template_folder="raggr-frontend/dist",
+)
+
+app.config["JWT_SECRET_KEY"] = os.getenv("JWT_SECRET_KEY", "SECRET_KEY")
+jwt = JWTManager(app)
+
+# Initialize Tortoise ORM
+register_tortoise(
+    app,
+    db_url=os.getenv("DATABASE_URL", "sqlite://raggr.db"),
+    modules={"models": ["blueprints.conversation.models"]},
+    generate_schemas=True,
+)
+
+
+# Serve React static files
+@app.route("/static/<path:filename>")
+async def static_files(filename):
+    return await send_from_directory(app.static_folder, filename)
+
+
+# Serve the React app for all routes (catch-all)
+@app.route("/", defaults={"path": ""})
+@app.route("/<path:path>")
+async def serve_react_app(path):
+    if path and os.path.exists(os.path.join(app.template_folder, path)):
+        return await send_from_directory(app.template_folder, path)
+    return await render_template("index.html")
+
+
+@app.route("/api/query", methods=["POST"])
+async def query():
+    data = await request.get_json()
+    query = data.get("query")
+    # add message to database
+    conversation = await get_the_only_conversation()
+    print(conversation)
+    await add_message_to_conversation(
+        conversation=conversation, message=query, speaker="user"
+    )
+
+    response = consult_simba_oracle(query)
+    await add_message_to_conversation(
+        conversation=conversation, message=response, speaker="simba"
+    )
+    return jsonify({"response": response})
+
+
+@app.route("/api/messages", methods=["GET"])
+async def get_messages():
+    conversation = await get_the_only_conversation()
+    # Prefetch related messages
+    await conversation.fetch_related("messages")
+
+    # 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(),
+        }
+    )
+
+
+# @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/conversation/__init__.py

@@ -0,0 +1,17 @@
+from quart import Blueprint, jsonify
+from .models import (
+    Conversation,
+    PydConversation,
+)
+
+conversation_blueprint = Blueprint(
+    "conversation_api", __name__, url_prefix="/api/conversation"
+)
+
+
+@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)
+
+    return jsonify(serialized_conversation.model_dump_json())

blueprints/conversation/logic.py

@@ -1,9 +1,5 @@
-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)
@@ -14,7 +10,6 @@ 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(
@@ -35,26 +30,3 @@ 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

@@ -18,9 +18,6 @@ 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"
@@ -40,15 +37,5 @@ class ConversationMessage(Model):
 
 
 PydConversationMessage = pydantic_model_creator(ConversationMessage)
-PydConversation = pydantic_model_creator(
+PydConversation = pydantic_model_creator(Conversation, name="Conversation")
-    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)

chunker.py

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

docker-compose.yml

@@ -2,9 +2,6 @@ version: "3.8"
 
 services:
   raggr:
-    build:
-      context: ./services/raggr
-      dockerfile: Dockerfile
     image: torrtle/simbarag:latest
     network_mode: host
     environment:
@@ -15,8 +12,6 @@ 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("./database/visited.db")
+    conn = sqlite3.connect("./visited.db")
     c = conn.cursor()
     c.execute("select immich_id from visited")
     rows = c.fetchall()

llm.py

@@ -0,0 +1,64 @@
+import os
+
+from ollama import Client
+from openai import OpenAI
+
+import logging
+
+logging.basicConfig(level=logging.INFO)
+
+
+class LLMClient:
+    def __init__(self):
+        try:
+            self.ollama_client = Client(
+                host=os.getenv("OLLAMA_URL", "http://localhost:11434"), timeout=10.0
+            )
+            self.ollama_client.chat(
+                model="gemma3:4b", messages=[{"role": "system", "content": "test"}]
+            )
+            self.PROVIDER = "ollama"
+            logging.info("Using Ollama as LLM backend")
+        except Exception as e:
+            print(e)
+            self.openai_client = OpenAI()
+            self.PROVIDER = "openai"
+            logging.info("Using OpenAI as LLM backend")
+
+    def chat(
+        self,
+        prompt: str,
+        system_prompt: str,
+    ):
+        if self.PROVIDER == "ollama":
+            response = self.ollama_client.chat(
+                model="gemma3:4b",
+                messages=[
+                    {
+                        "role": "system",
+                        "content": system_prompt,
+                    },
+                    {"role": "user", "content": prompt},
+                ],
+            )
+            print(response)
+            output = response.message.content
+        elif self.PROVIDER == "openai":
+            response = self.openai_client.responses.create(
+                model="gpt-4o-mini",
+                input=[
+                    {
+                        "role": "system",
+                        "content": system_prompt,
+                    },
+                    {"role": "user", "content": prompt},
+                ],
+            )
+            output = response.output_text
+
+        return output
+
+
+if __name__ == "__main__":
+    client = Client()
+    client.chat(model="gemma3:4b", messages=[{"role": "system", "promp": "hack"}])

main.py

@@ -7,8 +7,6 @@ import argparse
 import chromadb
 import ollama
 
-import time
-
 
 from request import PaperlessNGXService
 from chunker import Chunker
@@ -38,7 +36,6 @@ 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()
@@ -80,7 +77,7 @@ 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("database/visited.db") as conn:
+    with sqlite3.connect("visited.db") as conn:
         to_insert = []
         c = conn.cursor()
         for index, text in enumerate(texts):
@@ -116,22 +113,9 @@ def chunk_text(texts: list[str], collection):
         )
 
 
-def classify_query(query: str, transcript: str) -> bool:
+def consult_oracle(input: str, collection):
-    logging.info("Starting query generation")
+    import time
-    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()
@@ -169,10 +153,7 @@ def consult_oracle(
     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}. Respond to this prompt: {input}"
-    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")
@@ -183,16 +164,6 @@ def consult_oracle(
     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()
@@ -202,24 +173,15 @@ def paperless_workflow(input):
     consult_oracle(input, simba_docs)
 
 
-def consult_simba_oracle(input: str, transcript: str = ""):
+def consult_simba_oracle(input: str):
-    is_simba_related = classify_query(query=input, transcript=transcript)
+    return consult_oracle(
-
+        input=input,
-    if is_simba_related:
+        collection=simba_docs,
-        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:
+    with sqlite3.connect("visited.db") as conn:
         c = conn.cursor()
         c.execute(
             "CREATE TABLE IF NOT EXISTS indexed_documents (id INTEGER PRIMARY KEY AUTOINCREMENT, paperless_id INTEGER)"
@@ -232,45 +194,42 @@ def filter_indexed_files(docs):
     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()
-        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()
+        with sqlite3.connect("./visited.db") as conn:
+            c = conn.cursor()
+            c.execute("DELETE FROM indexed_documents")
 
-    if args.classify:
+        logging.info("Fetching documents from Paperless-NGX")
-        consult_simba_oracle(input="yohohoho testing")
+        ppngx = PaperlessNGXService()
-        consult_simba_oracle(input="write an email")
+        docs = ppngx.get_data()
-        consult_simba_oracle(input="how much does simba weigh")
+        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 ...")
+        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:
+    #     extension = args.index.split(".")[-1]
+    #     if extension == "pdf":
+    #         pdf_path = ppngx.download_pdf_from_id(id=document_id)
+    #         image_paths = pdf_to_image(filepath=pdf_path)
+    #         print(f"summarizing {file}")
+    #         generated_summary = summarize_pdf_image(filepaths=image_paths)
+    #     elif extension in [".md", ".txt"]:
+    #         chunk_text(texts=[file.readall()], collection=simba_docs)
 
     if args.query:
         logging.info("Consulting oracle ...")

pyproject.toml

@@ -0,0 +1,27 @@
+[project]
+name = "raggr"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+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",
+]

query.py

@@ -49,20 +49,11 @@ 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
@@ -120,27 +111,6 @@ 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:
@@ -184,33 +154,6 @@ 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/package.json

@@ -6,18 +6,14 @@
   "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",
@@ -26,16 +22,5 @@
     "@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

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

raggr-frontend/src/App.tsx

@@ -0,0 +1,204 @@
+import { useEffect, useState } from "react";
+import axios from "axios";
+import ReactMarkdown from "react-markdown";
+
+import "./App.css";
+
+type QuestionAnswer = {
+  question: string;
+  answer: string;
+};
+
+type QuestionBubbleProps = {
+  text: string;
+};
+
+type AnswerBubbleProps = {
+  text: string;
+  loading: string;
+};
+
+type QuestionAnswerPairProps = {
+  question: string;
+  answer: string;
+  loading: boolean;
+};
+
+type Conversation = {
+  title: string;
+  id: string;
+};
+
+type Message = {
+  text: string;
+  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">
+      <p className="py-2 px-4 rounded-md w-full text-xl font-bold">askSimba!</p>
+      {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 ? (
+        <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>
+  );
+};
+
+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">
+      <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">
+            <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>
+  );
+};
+
+export default App;

services/raggr/MIGRATIONS.md

@@ -1,54 +0,0 @@
-# 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

services/raggr/add_user.py

@@ -1,146 +0,0 @@
-# GENERATED BY CLAUDE
-
-import os
-import sys
-import uuid
-import asyncio
-from tortoise import Tortoise
-from blueprints.users.models import User
-
-from dotenv import load_dotenv
-
-load_dotenv()
-
-# Database configuration with environment variable support
-DATABASE_PATH = os.getenv("DATABASE_PATH", "database/raggr.db")
-DATABASE_URL = os.getenv("DATABASE_URL", f"sqlite://{DATABASE_PATH}")
-
-print(DATABASE_URL)
-
-
-async def add_user(username: str, email: str, password: str):
-    """Add a new user to the database"""
-    await Tortoise.init(
-        db_url=DATABASE_URL,
-        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=DATABASE_URL,
-        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")
-    print("\nEnvironment Variables:")
-    print("  DATABASE_PATH  - Path to database file (default: database/raggr.db)")
-    print("  DATABASE_URL   - Full database URL (overrides DATABASE_PATH)")
-    print("\n  Example with custom database:")
-    print("  DATABASE_PATH=dev.db 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())

services/raggr/aerich_config.py

@@ -1,20 +0,0 @@
-import os
-
-# Database configuration with environment variable support
-# Use DATABASE_PATH for relative paths or DATABASE_URL for full connection strings
-DATABASE_PATH = os.getenv("DATABASE_PATH", "database/raggr.db")
-DATABASE_URL = os.getenv("DATABASE_URL", f"sqlite://{DATABASE_PATH}")
-
-TORTOISE_ORM = {
-    "connections": {"default": DATABASE_URL},
-    "apps": {
-        "models": {
-            "models": [
-                "blueprints.conversation.models",
-                "blueprints.users.models",
-                "aerich.models",
-            ],
-            "default_connection": "default",
-        },
-    },
-}

services/raggr/app.py

@@ -1,135 +0,0 @@
-import os
-
-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.contrib.quart import register_tortoise
-
-import blueprints.conversation
-import blueprints.conversation.logic
-import blueprints.users
-import blueprints.users.models
-from main import consult_simba_oracle
-
-app = Quart(
-    __name__,
-    static_folder="raggr-frontend/dist/static",
-    template_folder="raggr-frontend/dist",
-)
-
-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)
-
-
-# Database configuration with environment variable support
-DATABASE_PATH = os.getenv("DATABASE_PATH", "database/raggr.db")
-
-TORTOISE_CONFIG = {
-    "connections": {"default": f"sqlite://{DATABASE_PATH}"},
-    "apps": {
-        "models": {
-            "models": [
-                "blueprints.conversation.models",
-                "blueprints.users.models",
-                "aerich.models",
-            ]
-        },
-    },
-}
-
-# Initialize Tortoise ORM
-register_tortoise(
-    app,
-    config=TORTOISE_CONFIG,
-    generate_schemas=False,  # Disabled - using Aerich for migrations
-)
-
-
-# Serve React static files
-@app.route("/static/<path:filename>")
-async def static_files(filename):
-    return await send_from_directory(app.static_folder, filename)
-
-
-# Serve the React app for all routes (catch-all)
-@app.route("/", defaults={"path": ""})
-@app.route("/<path:path>")
-async def serve_react_app(path):
-    if path and os.path.exists(os.path.join(app.template_folder, path)):
-        return await send_from_directory(app.template_folder, 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():
-    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")
-
-    # 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(),
-        }
-    )
-
-
-if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=8080, debug=True)

services/raggr/blueprints/__init__.py

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

services/raggr/blueprints/conversation/__init__.py

@@ -1,72 +0,0 @@
-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"
-)
-
-
-@conversation_blueprint.route("/<conversation_id>")
-async def get_conversation(conversation_id: str):
-    conversation = await Conversation.get(id=conversation_id)
-    await conversation.fetch_related("messages")
-
-    # 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())

services/raggr/blueprints/users/__init__.py

@@ -1,40 +0,0 @@
-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)

services/raggr/blueprints/users/models.py

@@ -1,26 +0,0 @@
-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)

services/raggr/llm.py

@@ -1,73 +0,0 @@
-import os
-
-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=1.0
-            )
-            self.ollama_client.chat(
-                model="gemma3:4b", messages=[{"role": "system", "content": "test"}]
-            )
-            self.PROVIDER = "ollama"
-            logging.info("Using Ollama as LLM backend")
-        except Exception as e:
-            print(e)
-            self.openai_client = OpenAI()
-            self.PROVIDER = "openai"
-            logging.info("Using OpenAI as LLM backend")
-
-    def chat(
-        self,
-        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=[
-                        {
-                            "role": "system",
-                            "content": system_prompt,
-                        },
-                        {"role": "user", "content": prompt},
-                    ],
-                )
-                output = response.message.content
-                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=[
-                {
-                    "role": "system",
-                    "content": system_prompt,
-                },
-                {"role": "user", "content": prompt},
-            ],
-        )
-        output = response.output_text
-
-        return output
-
-
-if __name__ == "__main__":
-    client = Client()
-    client.chat(model="gemma3:4b", messages=[{"role": "system", "promp": "hack"}])

services/raggr/migrations/models/0_20251025081744_init.py

@@ -1,63 +0,0 @@
-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=="
-)

services/raggr/migrations/models/1_20251025091926_update.py

@@ -1,60 +0,0 @@
-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=="
-)

services/raggr/pyproject.toml

@@ -1,12 +0,0 @@
-[project]
-name = "raggr"
-version = "0.1.0"
-description = "Add your description here"
-readme = "README.md"
-requires-python = ">=3.13"
-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"]
-
-[tool.aerich]
-tortoise_orm = "app.TORTOISE_CONFIG"
-location = "./migrations"
-src_folder = "./."

services/raggr/raggr-frontend/TOKEN_REFRESH_IMPLEMENTATION.md

@@ -1,63 +0,0 @@
-# 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.

services/raggr/raggr-frontend/src/App.tsx

@@ -1,72 +0,0 @@
-import { useState, useEffect } from "react";
-
-import "./App.css";
-import { AuthProvider } from "./contexts/AuthContext";
-import { ChatScreen } from "./components/ChatScreen";
-import { LoginScreen } from "./components/LoginScreen";
-import { conversationService } from "./api/conversationService";
-
-const AppContainer = () => {
-  const [isAuthenticated, setAuthenticated] = useState<boolean>(false);
-  const [isChecking, setIsChecking] = useState<boolean>(true);
-
-  useEffect(() => {
-    const checkAuth = async () => {
-      const accessToken = localStorage.getItem("access_token");
-      const refreshToken = localStorage.getItem("refresh_token");
-
-      // No tokens at all, not authenticated
-      if (!accessToken && !refreshToken) {
-        setIsChecking(false);
-        setAuthenticated(false);
-        return;
-      }
-
-      // Try to verify token by making a request
-      try {
-        await conversationService.getAllConversations();
-        // 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);
-      }
-    };
-
-    checkAuth();
-  }, []);
-
-  // Show loading state while checking authentication
-  if (isChecking) {
-    return (
-      <div className="h-screen flex items-center justify-center bg-white/85">
-        <div className="text-xl">Loading...</div>
-      </div>
-    );
-  }
-
-  return (
-    <>
-      {isAuthenticated ? (
-        <ChatScreen setAuthenticated={setAuthenticated} />
-      ) : (
-        <LoginScreen setAuthenticated={setAuthenticated} />
-      )}
-    </>
-  );
-};
-
-const App = () => {
-  return (
-    <AuthProvider>
-      <AppContainer />
-    </AuthProvider>
-  );
-};
-
-export default App;

services/raggr/raggr-frontend/src/api/conversationService.ts

@@ -1,115 +0,0 @@
-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();

services/raggr/raggr-frontend/src/api/userService.ts

@@ -1,138 +0,0 @@
-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 validateToken(): Promise<boolean> {
-    const refreshToken = localStorage.getItem("refresh_token");
-
-    if (!refreshToken) {
-      return false;
-    }
-
-    try {
-      await this.refreshToken();
-      return true;
-    } catch (error) {
-      return false;
-    }
-  }
-
-  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();

services/raggr/raggr-frontend/src/assets/favicon.svg

@@ -1,3 +0,0 @@
-<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>

services/raggr/raggr-frontend/src/components/AnswerBubble.tsx

@@ -1,31 +0,0 @@
-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 sm:p-4">
-      {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 break-words overflow-wrap-anywhere">
-          <ReactMarkdown className="text-sm sm:text-base [&>*]:break-words">
-            {"🐈: " + text}
-          </ReactMarkdown>
-        </div>
-      )}
-    </div>
-  );
-};

services/raggr/raggr-frontend/src/components/ChatScreen.tsx

@@ -1,252 +0,0 @@
-import { useEffect, useState, useRef } 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 messagesEndRef = useRef<HTMLDivElement>(null);
-  const simbaAnswers = ["meow.", "hiss...", "purrrrrr", "yowOWROWWowowr"];
-
-  const scrollToBottom = () => {
-    messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
-  };
-
-  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(() => {
-    scrollToBottom();
-  }, [messages]);
-
-  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 () => {
-    if (!query.trim()) return; // Don't submit empty messages
-
-    const currMessages = messages.concat([{ text: query, speaker: "user" }]);
-    setMessages(currMessages);
-    setQuery(""); // Clear input immediately after submission
-
-    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" }]),
-      );
-    } 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);
-  };
-
-  const handleKeyDown = (event: React.KeyboardEvent<HTMLTextAreaElement>) => {
-    // Submit on Enter, but allow Shift+Enter for new line
-    if (event.key === "Enter" && !event.shiftKey) {
-      event.preventDefault();
-      handleQuestionSubmit();
-    }
-  };
-
-  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 w-full px-4 sm:w-11/12 sm:max-w-2xl lg:max-w-4xl sm:px-0">
-            <div className="flex flex-col sm:flex-row gap-3 sm:gap-0 sm:justify-between">
-              <header className="flex flex-row justify-center gap-2 sticky top-0 z-10 bg-white">
-                <h1 className="text-2xl sm:text-3xl">ask simba!</h1>
-              </header>
-              <div className="flex flex-row gap-2 justify-center sm:justify-end">
-                <button
-                  className="p-2 h-11 border border-green-400 bg-green-200 hover:bg-green-400 cursor-pointer rounded-md text-sm sm:text-base"
-                  onClick={() => setShowConversations(!showConversations)}
-                >
-                  {showConversations
-                    ? "hide conversations"
-                    : "show conversations"}
-                </button>
-                <button
-                  className="p-2 h-11 border border-red-400 bg-red-200 hover:bg-red-400 cursor-pointer rounded-md text-sm sm:text-base"
-                  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} />;
-            })}
-            <div ref={messagesEndRef} />
-            <footer className="flex flex-col gap-2 sticky bottom-0">
-              <div className="flex flex-row justify-between gap-2 grow">
-                <textarea
-                  className="p-3 sm:p-4 border border-blue-200 rounded-md grow bg-white min-h-[44px] resize-y"
-                  onChange={handleQueryChange}
-                  onKeyDown={handleKeyDown}
-                  value={query}
-                  rows={2}
-                  placeholder="Type your message... (Press Enter to send, Shift+Enter for new line)"
-                />
-              </div>
-              <div className="flex flex-row justify-between gap-2 grow">
-                <button
-                  className="p-3 sm:p-4 min-h-[44px] border border-blue-400 bg-blue-200 hover:bg-blue-400 cursor-pointer rounded-md flex-grow text-sm sm:text-base"
-                  onClick={() => handleQuestionSubmit()}
-                  type="submit"
-                >
-                  Submit
-                </button>
-              </div>
-              <div className="flex flex-row justify-center gap-2 grow items-center">
-                <input
-                  type="checkbox"
-                  onChange={(event) => setSimbaMode(event.target.checked)}
-                  className="w-5 h-5 cursor-pointer"
-                />
-                <p className="text-sm sm:text-base">simba mode?</p>
-              </div>
-            </footer>
-          </div>
-        </div>
-      </div>
-    </div>
-  );
-};

services/raggr/raggr-frontend/src/components/ConversationList.tsx

@@ -1,69 +0,0 @@
-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 {
-        let fetchedConversations =
-          await conversationService.getAllConversations();
-
-        if (conversations.length == 0) {
-          await conversationService.createConversation();
-          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 sm:p-4 flex flex-col gap-1">
-      {conservations.map((conversation) => {
-        return (
-          <div
-            key={conversation.id}
-            className="border-blue-400 bg-indigo-300 hover:bg-indigo-200 cursor-pointer rounded-md p-3 min-h-[44px] flex items-center"
-            onClick={() => onSelectConversation(conversation)}
-          >
-            <p className="text-sm sm:text-base break-words">
-              {conversation.title}
-            </p>
-          </div>
-        );
-      })}
-      <div
-        className="border-blue-400 bg-indigo-300 hover:bg-indigo-200 cursor-pointer rounded-md p-3 min-h-[44px] flex items-center"
-        onClick={() => onCreateNewConversation()}
-      >
-        <p className="text-sm sm:text-base"> + Start a new thread</p>
-      </div>
-    </div>
-  );
-};

services/raggr/raggr-frontend/src/components/ConversationMenu.tsx

@@ -1,24 +0,0 @@
-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>
-  );
-};

services/raggr/raggr-frontend/src/components/LoginScreen.tsx

@@ -1,122 +0,0 @@
-import { useState, useEffect } 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 [isChecking, setIsChecking] = useState<boolean>(true);
-
-  useEffect(() => {
-    // Check if user is already authenticated
-    const checkAuth = async () => {
-      const isValid = await userService.validateToken();
-      if (isValid) {
-        setAuthenticated(true);
-      }
-      setIsChecking(false);
-    };
-    checkAuth();
-  }, [setAuthenticated]);
-
-  const handleLogin = async (e?: React.FormEvent) => {
-    e?.preventDefault();
-
-    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);
-    }
-  };
-
-  const handleKeyPress = (e: React.KeyboardEvent) => {
-    if (e.key === "Enter") {
-      handleLogin();
-    }
-  };
-
-  // Show loading state while checking authentication
-  if (isChecking) {
-    return (
-      <div className="h-screen bg-opacity-20">
-        <div className="bg-white/85 h-screen flex items-center justify-center">
-          <div className="text-center">
-            <p className="text-lg sm:text-xl">Checking authentication...</p>
-          </div>
-        </div>
-      </div>
-    );
-  }
-
-  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 w-full px-4 sm:w-11/12 sm:max-w-2xl lg:max-w-4xl sm:px-0">
-            <div className="flex flex-col gap-1">
-              <div className="flex flex-grow justify-center w-full bg-amber-400 p-2">
-                <h1 className="text-base sm:text-xl font-bold text-center">
-                  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-2xl sm:text-3xl">ask simba!</h1>
-              </header>
-              <label htmlFor="username" className="text-sm sm:text-base">
-                username
-              </label>
-              <input
-                type="text"
-                id="username"
-                name="username"
-                value={username}
-                onChange={(e) => setUsername(e.target.value)}
-                onKeyPress={handleKeyPress}
-                className="border border-s-slate-950 p-3 rounded-md min-h-[44px]"
-              />
-              <label htmlFor="password" className="text-sm sm:text-base">
-                password
-              </label>
-              <input
-                type="password"
-                id="password"
-                name="password"
-                value={password}
-                onChange={(e) => setPassword(e.target.value)}
-                onKeyPress={handleKeyPress}
-                className="border border-s-slate-950 p-3 rounded-md min-h-[44px]"
-              />
-              {error && (
-                <div className="text-red-600 font-semibold text-sm sm:text-base">
-                  {error}
-                </div>
-              )}
-            </div>
-
-            <button
-              className="p-3 sm:p-4 min-h-[44px] border border-blue-400 bg-blue-200 hover:bg-blue-400 cursor-pointer rounded-md flex-grow text-sm sm:text-base"
-              onClick={handleLogin}
-            >
-              login
-            </button>
-          </div>
-        </div>
-      </div>
-    </div>
-  );
-};

services/raggr/raggr-frontend/src/components/QuestionBubble.tsx

@@ -1,11 +0,0 @@
-type QuestionBubbleProps = {
-  text: string;
-};
-
-export const QuestionBubble = ({ text }: QuestionBubbleProps) => {
-  return (
-    <div className="rounded-md bg-stone-200 p-3 sm:p-4 break-words overflow-wrap-anywhere text-sm sm:text-base">
-      🤦: {text}
-    </div>
-  );
-};

services/raggr/raggr-frontend/src/contexts/AuthContext.tsx

@@ -1,56 +0,0 @@
-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

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

uv.lock

@@ -2,21 +2,6 @@ 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"
@@ -60,18 +45,6 @@ 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"
@@ -333,15 +306,6 @@ 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"
@@ -1705,7 +1669,6 @@ name = "raggr"
 version = "0.1.0"
 source = { virtual = "." }
 dependencies = [
-    { name = "aerich" },
     { name = "bcrypt" },
     { name = "black" },
     { name = "chromadb" },
@@ -1724,14 +1687,11 @@ 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" },
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