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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"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": null,
"id": "a4ffa93a",
"metadata": {},
"outputs": [],
"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": null,
"id": "d2a08335",
"metadata": {},
"outputs": [],
"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": null,
"id": "9d649fcc",
"metadata": {},
"outputs": [],
"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",
"\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": null,
"id": "d2250413",
"metadata": {},
"outputs": [],
"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",
"# 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(\"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/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 = \"Hello\"\n",
"app = gr.mount_gradio_app(app, gradio_gui, path=\"/gradio\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f089dfd7",
"metadata": {},
"outputs": [],
"source": [
"%%writefile main.py\n",
"import uvicorn\n",
"\n",
"if __name__ == \"__main__\":\n",
" uvicorn.run(f\"app.app:app\", host=\"0.0.0.0\", port=8000, log_level=\"info\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "cb53f0ae",
"metadata": {},
"outputs": [],
"source": [
"!python -m pipreqs.pipreqs ."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a20f7f8c",
"metadata": {},
"outputs": [],
"source": [
"!python main.py"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "65658ef7",
"metadata": {},
"outputs": [],
"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": "9553c6e6",
"metadata": {},
"outputs": [],
"source": [
"!git commit -m \"adding chatbot\""
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
|