student_api.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4fca2e60",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip -q install gradio fastapi 'fastapi-users-db-sqlalchemy<5.0.0' openai uvicorn httpx requests pydantic sqlalchemy python-dotenv asyncpg pipreqs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a4ffa93a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting app/db.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile app/db.py\n",
    "from typing import AsyncGenerator\n",
    "\n",
    "from fastapi import Depends\n",
    "from fastapi_users.db import SQLAlchemyBaseUserTableUUID, SQLAlchemyUserDatabase\n",
    "from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine\n",
    "from sqlalchemy.ext.declarative import DeclarativeMeta, declarative_base\n",
    "from sqlalchemy.orm import sessionmaker\n",
    "from dotenv import load_dotenv\n",
    "import os\n",
    "\n",
    "# Get the current environment from the environment variable\n",
    "current_environment = os.getenv(\"APP_ENV\", \"dev\")\n",
    "\n",
    "# Load the appropriate .env file based on the current environment\n",
    "if current_environment == \"dev\":\n",
    "    load_dotenv(\".env.dev\")\n",
    "elif current_environment == \"test\":\n",
    "    load_dotenv(\".env.test\")\n",
    "elif current_environment == \"prod\":\n",
    "    load_dotenv(\".env.prod\")\n",
    "else:\n",
    "    raise ValueError(\"Invalid environment specified\")\n",
    "\n",
    "db_connection_string = os.getenv(\"DB_CONNECTION_STRING\")\n",
    "\n",
    "DATABASE_URL = db_connection_string\n",
    "Base: DeclarativeMeta = declarative_base()\n",
    "\n",
    "    \n",
    "class User(SQLAlchemyBaseUserTableUUID, Base):\n",
    "    pass\n",
    "\n",
    "\n",
    "engine = create_async_engine(DATABASE_URL)\n",
    "async_session_maker = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)\n",
    "\n",
    "\n",
    "async def create_db_and_tables():\n",
    "    async with engine.begin() as conn:\n",
    "        await conn.run_sync(Base.metadata.create_all)\n",
    "\n",
    "\n",
    "async def get_async_session() -> AsyncGenerator[AsyncSession, None]:\n",
    "    async with async_session_maker() as session:\n",
    "        yield session\n",
    "\n",
    "\n",
    "async def get_user_db(session: AsyncSession = Depends(get_async_session)):\n",
    "    yield SQLAlchemyUserDatabase(session, User)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d2a08335",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting app/schemas.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile app/schemas.py\n",
    "import uuid\n",
    "\n",
    "from fastapi_users import schemas\n",
    "\n",
    "\n",
    "class UserRead(schemas.BaseUser[uuid.UUID]):\n",
    "    pass\n",
    "\n",
    "\n",
    "class UserCreate(schemas.BaseUserCreate):\n",
    "    pass\n",
    "\n",
    "\n",
    "class UserUpdate(schemas.BaseUserUpdate):\n",
    "    pass\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9d649fcc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting app/users.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile app/users.py\n",
    "import uuid\n",
    "import os\n",
    "from typing import Optional\n",
    "from fastapi import Depends, Request\n",
    "from fastapi_users import BaseUserManager, FastAPIUsers, UUIDIDMixin\n",
    "from fastapi_users.authentication import (\n",
    "    AuthenticationBackend,\n",
    "    BearerTransport,\n",
    "    JWTStrategy,\n",
    ")\n",
    "from fastapi_users.db import SQLAlchemyUserDatabase\n",
    "from app.db import User, get_user_db\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "# Get the current environment from the environment variable\n",
    "current_environment = os.getenv(\"APP_ENV\", \"dev\")\n",
    "\n",
    "# Load the appropriate .env file based on the current environment\n",
    "if current_environment == \"dev\":\n",
    "    load_dotenv(\".env.dev\")\n",
    "elif current_environment == \"test\":\n",
    "    load_dotenv(\".env.test\")\n",
    "elif current_environment == \"prod\":\n",
    "    load_dotenv(\".env.prod\")\n",
    "else:\n",
    "    raise ValueError(\"Invalid environment specified\")\n",
    "\n",
    "SECRET = os.getenv(\"APP_SECRET\")\n",
    "\n",
    "\n",
    "class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):\n",
    "    reset_password_token_secret = SECRET\n",
    "    verification_token_secret = SECRET\n",
    "\n",
    "    async def on_after_register(self, user: User, request: Optional[Request] = None):\n",
    "        print(f\"User {user.id} has registered.\")\n",
    "\n",
    "    async def on_after_forgot_password(\n",
    "        self, user: User, token: str, request: Optional[Request] = None\n",
    "    ):\n",
    "        print(f\"User {user.id} has forgot their password. Reset token: {token}\")\n",
    "\n",
    "    async def on_after_request_verify(\n",
    "        self, user: User, token: str, request: Optional[Request] = None\n",
    "    ):\n",
    "        print(f\"Verification requested for user {user.id}. Verification token: {token}\")\n",
    "\n",
    "\n",
    "async def get_user_manager(user_db: SQLAlchemyUserDatabase = Depends(get_user_db)):\n",
    "    yield UserManager(user_db)\n",
    "\n",
    "\n",
    "bearer_transport = BearerTransport(tokenUrl=\"auth/jwt/login\")\n",
    "\n",
    "seconds_in_day = 60 * 60 * 24\n",
    "seconds_in_month = seconds_in_day * 31\n",
    "seconds_in_six_months = seconds_in_month * 6\n",
    "\n",
    "def get_jwt_strategy() -> JWTStrategy:\n",
    "    return JWTStrategy(secret=SECRET, lifetime_seconds=3600)\n",
    "\n",
    "\n",
    "auth_backend = AuthenticationBackend(\n",
    "    name=\"jwt\",\n",
    "    transport=bearer_transport,\n",
    "    get_strategy=get_jwt_strategy,\n",
    ")\n",
    "\n",
    "fastapi_users = FastAPIUsers[User, uuid.UUID](get_user_manager, [auth_backend])\n",
    "\n",
    "current_active_user = fastapi_users.current_user(active=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d2250413",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting app/app.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile app/app.py\n",
    "import httpx\n",
    "import os\n",
    "import requests\n",
    "import gradio as gr\n",
    "import openai\n",
    "\n",
    "from fastapi import Depends, FastAPI, Request\n",
    "from app.db import User, create_db_and_tables\n",
    "from app.schemas import UserCreate, UserRead, UserUpdate\n",
    "from app.users import auth_backend, current_active_user, fastapi_users\n",
    "from dotenv import load_dotenv\n",
    "import examples as chatbot_examples\n",
    "\n",
    "# Get the current environment from the environment variable\n",
    "current_environment = os.getenv(\"APP_ENV\", \"dev\")\n",
    "\n",
    "# Load the appropriate .env file based on the current environment\n",
    "if current_environment == \"dev\":\n",
    "    load_dotenv(\".env.dev\")\n",
    "elif current_environment == \"test\":\n",
    "    load_dotenv(\".env.test\")\n",
    "elif current_environment == \"prod\":\n",
    "    load_dotenv(\".env.prod\")\n",
    "else:\n",
    "    raise ValueError(\"Invalid environment specified\")\n",
    "    \n",
    "    \n",
    "def api_login(email, password):\n",
    "    port = os.getenv(\"APP_PORT\")\n",
    "    scheme = os.getenv(\"APP_SCHEME\")\n",
    "    host = os.getenv(\"APP_HOST\")\n",
    "\n",
    "    url = f\"{scheme}://{host}:{port}/auth/jwt/login\"\n",
    "    payload = {\n",
    "        'username': email,\n",
    "        'password': password\n",
    "    }\n",
    "    headers = {\n",
    "      'Content-Type': 'application/x-www-form-urlencoded'\n",
    "    }\n",
    "\n",
    "    response = requests.post(\n",
    "        url,\n",
    "        data=payload,\n",
    "        headers=headers\n",
    "    )\n",
    "    \n",
    "    if(response.status_code==200):\n",
    "        response_json = response.json()\n",
    "        api_key = response_json['access_token']\n",
    "        return True, api_key\n",
    "    else:\n",
    "        response_json = response.json()\n",
    "        detail = response_json['detail']\n",
    "        return False, detail\n",
    "    \n",
    "\n",
    "def get_api_key(email, password):\n",
    "    successful, message = api_login(email, password)\n",
    "    \n",
    "    if(successful):\n",
    "        return os.getenv(\"APP_API_BASE\"), message\n",
    "    else:\n",
    "        raise gr.Error(message)\n",
    "        return \"\", \"\"\n",
    "    \n",
    "# Define a function to get the AI's reply using the OpenAI API\n",
    "def get_ai_reply(message, model=\"gpt-3.5-turbo\", system_message=None, temperature=0, message_history=[]):\n",
    "    # Initialize the messages list\n",
    "    messages = []\n",
    "    \n",
    "    # Add the system message to the messages list\n",
    "    if system_message is not None:\n",
    "        messages += [{\"role\": \"system\", \"content\": system_message}]\n",
    "\n",
    "    # Add the message history to the messages list\n",
    "    if message_history is not None:\n",
    "        messages += message_history\n",
    "    \n",
    "    # Add the user's message to the messages list\n",
    "    messages += [{\"role\": \"user\", \"content\": message}]\n",
    "    \n",
    "    # Make an API call to the OpenAI ChatCompletion endpoint with the model and messages\n",
    "    completion = openai.ChatCompletion.create(\n",
    "        model=model,\n",
    "        messages=messages,\n",
    "        temperature=temperature\n",
    "    )\n",
    "    \n",
    "    # Extract and return the AI's response from the API response\n",
    "    return completion.choices[0].message.content.strip()\n",
    "\n",
    "def get_ai_image(prompt, size=\"512x512\"):\n",
    "    response = openai.Image.create(\n",
    "      prompt=prompt,\n",
    "      n=1,\n",
    "      size=size\n",
    "    )\n",
    "    image_1_url = response.data[0]['url']\n",
    "    return image_1_url\n",
    "\n",
    "def get_ai_transcript(path_to_audio, language=None):\n",
    "    audio_file= open(path_to_audio, \"rb\")\n",
    "    transcript = openai.Audio.transcribe(\"whisper-1\", audio_file, language=language)\n",
    "    return transcript.text\n",
    "\n",
    "def generate_transcription(path_to_audio_file):\n",
    "    try:\n",
    "        transcript = get_ai_transcript(path_to_audio_file)\n",
    "        return transcript\n",
    "    except Exception as e:\n",
    "        raise gr.Error(e)\n",
    "        return \"\"\n",
    "    \n",
    "def generate_image(prompt):\n",
    "    try:\n",
    "        image_url = get_ai_image(prompt)\n",
    "        return image_url\n",
    "    except Exception as e:\n",
    "        raise gr.Error(e)\n",
    "        return None\n",
    "    \n",
    "# Define a function to handle the chat interaction with the AI model\n",
    "def chat(model, system_message, message, chatbot_messages, history_state):\n",
    "    # Initialize chatbot_messages and history_state if they are not provided\n",
    "    chatbot_messages = chatbot_messages or []\n",
    "    history_state = history_state or []\n",
    "    \n",
    "    # Try to get the AI's reply using the get_ai_reply function\n",
    "    try:\n",
    "        ai_reply = get_ai_reply(message, model=model, system_message=system_message, message_history=history_state)\n",
    "    except Exception as e:\n",
    "        # If an error occurs, raise a Gradio error\n",
    "        raise gr.Error(e)\n",
    "    \n",
    "    # Append the user's message and the AI's reply to the chatbot_messages list\n",
    "    chatbot_messages.append((message, ai_reply))\n",
    "    \n",
    "    # Append the user's message and the AI's reply to the history_state list\n",
    "    history_state.append({\"role\": \"user\", \"content\": message})\n",
    "    history_state.append({\"role\": \"assistant\", \"content\": ai_reply})\n",
    "    \n",
    "    # Return None (empty out the user's message textbox), the updated chatbot_messages, and the updated history_state\n",
    "    return None, chatbot_messages, history_state\n",
    "\n",
    "# Define a function to launch the chatbot interface using Gradio\n",
    "def get_chatbot_app(additional_examples=[]):\n",
    "    # Load chatbot examples and merge with any additional examples provided\n",
    "    examples = chatbot_examples.load_examples(additional=additional_examples)\n",
    "    \n",
    "    # Define a function to get the names of the examples\n",
    "    def get_examples():\n",
    "        return [example[\"name\"] for example in examples]\n",
    "\n",
    "    # Define a function to choose an example based on the index\n",
    "    def choose_example(index):\n",
    "        if(index!=None):\n",
    "            system_message = examples[index][\"system_message\"].strip()\n",
    "            user_message = examples[index][\"message\"].strip()\n",
    "            return system_message, user_message, [], []\n",
    "        else:\n",
    "            return \"\", \"\", [], []\n",
    "\n",
    "    # Create the Gradio interface using the Blocks layout\n",
    "    with gr.Blocks() as app:\n",
    "        with gr.Tab(\"Conversation\"):\n",
    "            with gr.Row():\n",
    "                with gr.Column():\n",
    "                    # Create a dropdown to select examples\n",
    "                    example_dropdown = gr.Dropdown(get_examples(), label=\"Examples\", type=\"index\")\n",
    "                    # Create a button to load the selected example\n",
    "                    example_load_btn = gr.Button(value=\"Load\")\n",
    "                    # Create a textbox for the system message (prompt)\n",
    "                    system_message = gr.TextArea(label=\"System Message (Prompt)\", value=\"You are a helpful assistant.\", lines=20, max_lines=400)\n",
    "                with gr.Column():\n",
    "                    # Create a dropdown to select the AI model\n",
    "                    model_selector = gr.Dropdown(\n",
    "                        [\"gpt-3.5-turbo\"],\n",
    "                        label=\"Model\",\n",
    "                        value=\"gpt-3.5-turbo\"\n",
    "                    )\n",
    "                    # Create a chatbot interface for the conversation\n",
    "                    chatbot = gr.Chatbot(label=\"Conversation\")\n",
    "                    # Create a textbox for the user's message\n",
    "                    message = gr.Textbox(label=\"Message\")\n",
    "                    # Create a state object to store the conversation history\n",
    "                    history_state = gr.State()\n",
    "                    # Create a button to send the user's message\n",
    "                    btn = gr.Button(value=\"Send\")\n",
    "\n",
    "                # Connect the example load button to the choose_example function\n",
    "                example_load_btn.click(choose_example, inputs=[example_dropdown], outputs=[system_message, message, chatbot, history_state])\n",
    "                # Connect the send button to the chat function\n",
    "                btn.click(chat, inputs=[model_selector, system_message, message, chatbot, history_state], outputs=[message, chatbot, history_state])\n",
    "        with gr.Tab(\"Image Generation\"):\n",
    "            image_prompt = gr.Textbox(label=\"Prompt\", placeholder=\"A cute puppy wearing sunglasses.\")\n",
    "            image_btn = gr.Button(value=\"Generate\")\n",
    "            image = gr.Image(label=\"Result\", interactive=False, type=\"filepath\")\n",
    "            image_btn.click(generate_image, inputs=[image_prompt], outputs=[image])\n",
    "        with gr.Tab(\"Speech-to-text\"):\n",
    "            audio_file = gr.Audio(label=\"Audio\", source=\"microphone\", type=\"filepath\")\n",
    "            transcribe = gr.Button(value=\"Transcribe\")\n",
    "            audio_transcript = gr.Textbox(label=\"Transcription\", interactive=False)\n",
    "            transcribe.click(generate_transcription, inputs=[audio_file], outputs=[audio_transcript])\n",
    "        with gr.Tab(\"Get API Key\"):\n",
    "            email_box = gr.Textbox(label=\"Email Address\", placeholder=\"Student Email\")\n",
    "            password_box = gr.Textbox(label=\"Password\", type=\"password\", placeholder=\"Student ID\")\n",
    "            btn = gr.Button(value =\"Generate\")\n",
    "            api_host_box = gr.Textbox(label=\"OpenAI API Base\", interactive=False)\n",
    "            api_key_box = gr.Textbox(label=\"OpenAI API Key\", interactive=False)\n",
    "            btn.click(get_api_key, inputs = [email_box, password_box], outputs = [api_host_box, api_key_box])\n",
    "        # Return the app\n",
    "        return app\n",
    "\n",
    "app = FastAPI()\n",
    "\n",
    "app.include_router(\n",
    "    fastapi_users.get_auth_router(auth_backend), prefix=\"/auth/jwt\", tags=[\"auth\"]\n",
    ")\n",
    "app.include_router(\n",
    "    fastapi_users.get_register_router(UserRead, UserCreate),\n",
    "    prefix=\"/auth\",\n",
    "    tags=[\"auth\"],\n",
    ")\n",
    "app.include_router(\n",
    "    fastapi_users.get_users_router(UserRead, UserUpdate),\n",
    "    prefix=\"/users\",\n",
    "    tags=[\"users\"],\n",
    ")\n",
    "\n",
    "@app.get(\"/authenticated-route\")\n",
    "async def authenticated_route(user: User = Depends(current_active_user)):\n",
    "    return {\"message\": f\"Hello {user.email}!\"}\n",
    "\n",
    "@app.post(\"/v1/completions\")\n",
    "async def openai_api_completions_passthrough(\n",
    "    request: Request,\n",
    "    user: User = Depends(fastapi_users.current_user()),\n",
    "):\n",
    "    if not user:\n",
    "        raise HTTPException(status_code=401, detail=\"Unauthorized\")\n",
    "\n",
    "    # Get the request data and headers\n",
    "    request_data = await request.json()\n",
    "    request_headers = request.headers\n",
    "    openai_api_key = os.getenv(\"OPENAI_API_KEY\")\n",
    "\n",
    "    # Forward the request to the OpenAI API\n",
    "    response = requests.post(\n",
    "        \"https://api.openai.com/v1/completions\",\n",
    "        json=request_data,\n",
    "        headers={\n",
    "            \"Content-Type\": request_headers.get(\"Content-Type\"),\n",
    "            \"Authorization\": f\"Bearer {openai_api_key}\",\n",
    "        },\n",
    "    )\n",
    "    print(response)\n",
    "\n",
    "    # Return the OpenAI API response\n",
    "    return response.json()\n",
    "\n",
    "\n",
    "@app.post(\"/v1/chat/completions\")\n",
    "async def openai_api_chat_completions_passthrough(\n",
    "    request: Request,\n",
    "    user: User = Depends(fastapi_users.current_user()),\n",
    "):\n",
    "    if not user:\n",
    "        raise HTTPException(status_code=401, detail=\"Unauthorized\")\n",
    "\n",
    "    # Get the request data and headers\n",
    "    request_data = await request.json()\n",
    "    request_headers = request.headers\n",
    "    openai_api_key = os.getenv(\"OPENAI_API_KEY\")\n",
    "    \n",
    "    if(request_data['model']=='gpt-4' or request_data['model'] == 'gpt-4-32k'):\n",
    "        print(\"User requested gpt-4, falling back to gpt-3.5-turbo\")\n",
    "        request_data['model'] = 'gpt-3.5-turbo'\n",
    "\n",
    "    # Forward the request to the OpenAI API\n",
    "    response = requests.post(\n",
    "        \"https://api.openai.com/v1/chat/completions\",\n",
    "        json=request_data,\n",
    "        headers={\n",
    "            \"Content-Type\": request_headers.get(\"Content-Type\"),\n",
    "            \"Authorization\": f\"Bearer {openai_api_key}\",\n",
    "        },\n",
    "    )\n",
    "    print(response)\n",
    "\n",
    "    # Return the OpenAI API response\n",
    "    return response.json()\n",
    "\n",
    "@app.on_event(\"startup\")\n",
    "async def on_startup():\n",
    "    # Not needed if you setup a migration system like Alembic\n",
    "    await create_db_and_tables()\n",
    "    \n",
    "gradio_gui = get_chatbot_app()\n",
    "gradio_gui.auth = api_login\n",
    "gradio_gui.auth_message = \"Welcome, to the 3341 OpenAI Service\"\n",
    "app = gr.mount_gradio_app(app, gradio_gui, path=\"/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f089dfd7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Overwriting main.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile main.py\n",
    "import subprocess\n",
    "\n",
    "subprocess.run(\"uvicorn app.app:app --host 0.0.0.0 --port 7860\", shell=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9039be08",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%writefile requirements.txt\n",
    "fastapi==0.95.1\n",
    "fastapi-users-db-sqlalchemy<5.0.0\n",
    "gradio==3.27.0\n",
    "httpx==0.24.0\n",
    "openai==0.27.4\n",
    "python-dotenv==1.0.0\n",
    "Requests==2.28.2\n",
    "SQLAlchemy==1.4.47\n",
    "uvicorn==0.21.1\n",
    "asyncpg==0.27.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a20f7f8c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32mINFO\u001b[0m:     Started server process [\u001b[36m77691\u001b[0m]\n",
      "\u001b[32mINFO\u001b[0m:     Waiting for application startup.\n",
      "\u001b[32mINFO\u001b[0m:     Application startup complete.\n",
      "\u001b[32mINFO\u001b[0m:     Uvicorn running on \u001b[1mhttp://0.0.0.0:7860\u001b[0m (Press CTRL+C to quit)\n",
      "\u001b[32mINFO\u001b[0m:     127.0.0.1:58808 - \"\u001b[1mGET / HTTP/1.1\u001b[0m\" \u001b[32m200 OK\u001b[0m\n",
      "\u001b[32mINFO\u001b[0m:     127.0.0.1:58808 - \"\u001b[1mGET /theme.css HTTP/1.1\u001b[0m\" \u001b[32m200 OK\u001b[0m\n",
      "\u001b[32mINFO\u001b[0m:     127.0.0.1:58810 - \"\u001b[1mPOST /auth/jwt/login HTTP/1.1\u001b[0m\" \u001b[32m200 OK\u001b[0m\n",
      "\u001b[32mINFO\u001b[0m:     127.0.0.1:58809 - \"\u001b[1mPOST /login HTTP/1.1\u001b[0m\" \u001b[32m200 OK\u001b[0m\n",
      "\u001b[32mINFO\u001b[0m:     127.0.0.1:58809 - \"\u001b[1mGET / HTTP/1.1\u001b[0m\" \u001b[32m200 OK\u001b[0m\n",
      "\u001b[32mINFO\u001b[0m:     127.0.0.1:58809 - \"\u001b[1mGET /theme.css HTTP/1.1\u001b[0m\" \u001b[32m200 OK\u001b[0m\n",
      "\u001b[32mINFO\u001b[0m:     127.0.0.1:58855 - \"\u001b[1mGET /docs HTTP/1.1\u001b[0m\" \u001b[32m200 OK\u001b[0m\n",
      "\u001b[32mINFO\u001b[0m:     127.0.0.1:58855 - \"\u001b[1mGET /openapi.json HTTP/1.1\u001b[0m\" \u001b[32m200 OK\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!python main.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "65658ef7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "User 30d58c0b-04c8-4e55-89e5-878b08472884 has registered.\n",
      "User created <app.db.User object at 0x1061dec80>\n",
      "User 2a622947-16bd-4963-abc8-30a3766338c4 has registered.\n",
      "User created <app.db.User object at 0x1061de440>\n",
      "User 23e72a35-10e0-469d-8fc6-7b6f1f8fc5a3 has registered.\n",
      "User created <app.db.User object at 0x1061de470>\n",
      "User 85bcf4f4-db65-404d-b2ef-e23283462bfa has registered.\n",
      "User created <app.db.User object at 0x1064ca410>\n",
      "User 7df12d26-1f30-4b74-9d8c-975d68e0df9f has registered.\n",
      "User created <app.db.User object at 0x1064c9c60>\n",
      "User 1cd64c6e-bcde-4009-af24-6bee05e7afd8 has registered.\n",
      "User created <app.db.User object at 0x1064ca410>\n",
      "User 88b0449c-e604-4d57-bd0c-797a930efa05 has registered.\n",
      "User created <app.db.User object at 0x1064cad10>\n",
      "User 68242f26-a22b-49e8-8b8c-c4475e01dcd4 has registered.\n",
      "User created <app.db.User object at 0x1064c9b70>\n",
      "User 61b685a4-3df5-4baf-bb61-b4f93150699f has registered.\n",
      "User created <app.db.User object at 0x1064cba00>\n",
      "User 8443d506-859e-4f89-b301-6c08e56d34e1 has registered.\n",
      "User created <app.db.User object at 0x1064cad10>\n",
      "User 1adee351-777e-46ff-83be-379db22cc2d7 has registered.\n",
      "User created <app.db.User object at 0x1064c9b70>\n",
      "User 5654743e-fd1e-477d-97e0-f4eb138d2935 has registered.\n",
      "User created <app.db.User object at 0x1064c97b0>\n",
      "User 57c96dd2-6291-447d-9070-ca9c335798ba has registered.\n",
      "User created <app.db.User object at 0x1064cbc70>\n",
      "User 6a105d49-e84f-4d95-98ed-577b4a970854 has registered.\n",
      "User created <app.db.User object at 0x1064cbb80>\n",
      "User 6a17151f-60ad-42ae-8fef-2890a77ee0f8 has registered.\n",
      "User created <app.db.User object at 0x1064c81c0>\n",
      "User badec4ec-fee6-4832-bb89-1bf1501167ff has registered.\n",
      "User created <app.db.User object at 0x1064cba90>\n",
      "User 6c1a749e-fa19-44bd-b937-e508e78866cd has registered.\n",
      "User created <app.db.User object at 0x1064c9cc0>\n",
      "User 7c9aa8fe-d3e4-4af3-919a-20294d68fc4b has registered.\n",
      "User created <app.db.User object at 0x1064c92d0>\n",
      "User a93183b3-5aa1-4e06-a78f-a47be0b2bba1 has registered.\n",
      "User created <app.db.User object at 0x1064cab00>\n",
      "User 3abc7ae3-0185-4742-bf1d-f3749cecb199 has registered.\n",
      "User created <app.db.User object at 0x1064cb850>\n",
      "User e6e9eda6-80e2-40bd-be8c-4d371deddb4e has registered.\n",
      "User created <app.db.User object at 0x1064c9780>\n",
      "User a3587907-b38f-4291-8153-34d480d8ebfe has registered.\n",
      "User created <app.db.User object at 0x1064cab00>\n",
      "User 4de62323-12ba-41cc-bd72-60a53117236e has registered.\n",
      "User created <app.db.User object at 0x1064c9510>\n",
      "User fa7ae58a-e5d4-4495-9aec-d10f1076b291 has registered.\n",
      "User created <app.db.User object at 0x1064c9240>\n",
      "User a3d49925-470c-485b-85c7-b881fc6103bd has registered.\n",
      "User created <app.db.User object at 0x1064cad10>\n",
      "User 1aded816-081c-4c16-b6fb-5a8514acecbd has registered.\n",
      "User created <app.db.User object at 0x1064c9930>\n",
      "User c05807bb-5e02-4e9d-a5dd-870b40beeab9 has registered.\n",
      "User created <app.db.User object at 0x1061de830>\n",
      "User e3840eef-2ccc-43e8-bb98-f67e1d78d595 has registered.\n",
      "User created <app.db.User object at 0x1064ca860>\n",
      "User 177862c8-f84a-4e9a-8a11-325c1af34476 has registered.\n",
      "User created <app.db.User object at 0x106222cb0>\n",
      "User 833a7089-f258-4261-86a9-6aa874ccc7b2 has registered.\n",
      "User created <app.db.User object at 0x106223040>\n",
      "User c9f0147c-b880-4814-a272-3c91625ebfe2 has registered.\n",
      "User created <app.db.User object at 0x106222cb0>\n",
      "User 182b4c76-2cba-407c-965c-eea8ec17ef6f has registered.\n",
      "User created <app.db.User object at 0x106223880>\n",
      "User c79f3346-cf21-4e41-8393-c36aaeab67fe has registered.\n",
      "User created <app.db.User object at 0x106223e50>\n",
      "User 610705ed-b7ac-4296-b566-db6bdf642f5a has registered.\n",
      "User created <app.db.User object at 0x106223ca0>\n",
      "User 09817885-888b-4be9-9d20-fd03366f6791 has registered.\n",
      "User created <app.db.User object at 0x106223880>\n",
      "User 5c38dc47-7c00-4d68-ac7c-9ec2c7c4a6ea has registered.\n",
      "User created <app.db.User object at 0x1064c88b0>\n",
      "User 1009694f-b1e4-4751-a59c-a8ed757f76f1 has registered.\n",
      "User created <app.db.User object at 0x1064c9ae0>\n",
      "User b5fb3dbc-a8c0-4221-897f-9eb87ff29ced has registered.\n",
      "User created <app.db.User object at 0x1064cba30>\n",
      "User 3269239e-e87b-4f6f-9539-4d7fffc1d9a1 has registered.\n",
      "User created <app.db.User object at 0x1064c9f00>\n",
      "User 59bb7f37-d029-47a1-8bbd-37adae350fed has registered.\n",
      "User created <app.db.User object at 0x1064c9ae0>\n"
     ]
    }
   ],
   "source": [
    "import contextlib\n",
    "\n",
    "from app.db import get_async_session, get_user_db\n",
    "from app.schemas import UserCreate\n",
    "from app.users import get_user_manager\n",
    "from fastapi_users.exceptions import UserAlreadyExists\n",
    "import csv\n",
    "\n",
    "get_async_session_context = contextlib.asynccontextmanager(get_async_session)\n",
    "get_user_db_context = contextlib.asynccontextmanager(get_user_db)\n",
    "get_user_manager_context = contextlib.asynccontextmanager(get_user_manager)\n",
    "\n",
    "\n",
    "async def create_user(email: str, password: str, is_superuser: bool = False):\n",
    "    try:\n",
    "        async with get_async_session_context() as session:\n",
    "            async with get_user_db_context(session) as user_db:\n",
    "                async with get_user_manager_context(user_db) as user_manager:\n",
    "                    user = await user_manager.create(\n",
    "                        UserCreate(\n",
    "                            email=email, password=password, is_superuser=is_superuser\n",
    "                        )\n",
    "                    )\n",
    "                    print(f\"User created {user}\")\n",
    "    except UserAlreadyExists:\n",
    "        print(f\"User {email} already exists\")\n",
    "        \n",
    "with open(\"seeds.csv\", mode=\"r\") as csv_file:\n",
    "        csv_reader = csv.reader(csv_file)\n",
    "\n",
    "        for row in csv_reader:\n",
    "            email = row[0]\n",
    "            password = row[1]\n",
    "\n",
    "            await create_user(email=email, password=password)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "406b1bd5",
   "metadata": {},
   "outputs": [],
   "source": [
    "!git add app"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4849ce67",
   "metadata": {},
   "outputs": [],
   "source": [
    "!git add requirements.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "54c436ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "!git add main.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9553c6e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "!git commit -m \"adding chatbot\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bda07f88",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip -q install --upgrade huggingface_hub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "39516b2a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from huggingface_hub import notebook_login\n",
    "notebook_login()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "83bdbe1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "!git remote add huggingface https://huggingface.co/spaces/ericmichael/openai-playground-utrgv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "db9d1e70",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enumerating objects: 19, done.\n",
      "Counting objects: 100% (19/19), done.\n",
      "Delta compression using up to 8 threads\n",
      "Compressing objects: 100% (18/18), done.\n",
      "Writing objects: 100% (19/19), 13.39 KiB | 6.70 MiB/s, done.\n",
      "Total 19 (delta 3), reused 0 (delta 0), pack-reused 0\n",
      "error: RPC failed; curl 92 HTTP/2 stream 0 was not closed cleanly: INTERNAL_ERROR (err 2)\n",
      "Everything up-to-date\n"
     ]
    }
   ],
   "source": [
    "!git push --force huggingface main"
   ]
  }
 ],
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