update chatinterface

app/app.py

@@ -2,13 +2,13 @@ from httpx import AsyncClient
 import os
 import requests
 import gradio as gr
-import openai
 
 from fastapi import Depends, FastAPI, Request
 from app.db import User, create_db_and_tables
 from app.schemas import UserCreate, UserRead, UserUpdate
 from app.users import auth_backend, current_active_user, fastapi_users
 from dotenv import load_dotenv
+
 import examples as chatbot_examples
 
 # Get the current environment from the environment variable
@@ -24,6 +24,8 @@ elif current_environment == "prod":
 else:
     raise ValueError("Invalid environment specified")
 
+import openai
+
 
 def api_login(email, password):
     port = os.getenv("APP_PORT")
@@ -119,9 +121,6 @@ def generate_image(prompt):
 
 # Define a function to handle the chat interaction with the AI model
 def chat(message, chatbot_messages, model, temperature, system_message):
-    # Initialize chatbot_messages
-    chatbot_messages = chatbot_messages or []
-
     history_openai_format = []
     for human, assistant in chatbot_messages:
         history_openai_format.append({"role": "user", "content": human})
@@ -140,11 +139,8 @@ def chat(message, chatbot_messages, model, temperature, system_message):
         # If an error occurs, raise a Gradio error
         raise gr.Error(e)
 
-    # Append the user's message and the AI's reply to the chatbot_messages list
-    chatbot_messages.append((message, ai_reply))
-
     # Return None (empty out the user's message textbox), the updated chatbot_messages
-    return None, chatbot_messages
+    return ai_reply
 
 
 # Define a function to launch the chatbot interface using Gradio
@@ -169,55 +165,31 @@ def get_chatbot_app(additional_examples=[]):
     with gr.Blocks() as app:
         with gr.Tab("Conversation"):
             with gr.Row():
-                with gr.Column():
-                    # Create a dropdown to select examples
-                    example_dropdown = gr.Dropdown(
-                        get_examples(), label="Examples", type="index"
-                    )
-                    # Create a button to load the selected example
-                    example_load_btn = gr.Button(value="Load")
-                    # Create a textbox for the system message (prompt)
-                    system_message = gr.TextArea(
-                        label="System Message (Prompt)",
-                        value="You are a helpful assistant.",
-                        lines=20,
-                        max_lines=400,
-                    )
-                with gr.Column():
-                    with gr.Row():
-                        # Create a dropdown to select the AI model
-                        model_selector = gr.Dropdown(
+                # Create a textbox for the system message (prompt)
+                system_message = gr.TextArea(
+                    label="System Message (Prompt)",
+                    value="You are a helpful assistant.",
+                    lines=20,
+                    max_lines=400,
+                )
+                # Create a chatbot interface for the conversation
+                chatbot = gr.ChatInterface(
+                    chat,
+                    additional_inputs=[
+                        gr.Dropdown(
                             ["gpt-3.5-turbo", "gpt-3.5-turbo-16k"],
                             label="Model",
                             value="gpt-3.5-turbo",
-                        )
-                        temperature_slider = gr.Slider(
-                            label="Temperature", minimum=0, maximum=2, step=0.1, value=0
-                        )
-                    # Create a chatbot interface for the conversation
-                    chatbot = gr.Chatbot(label="Conversation")
-                    # Create a textbox for the user's message
-                    message = gr.Textbox(label="Message")
-                    # Create a button to send the user's message
-                    btn = gr.Button(value="Send")
-
-                # Connect the example load button to the choose_example function
-                example_load_btn.click(
-                    choose_example,
-                    inputs=[example_dropdown],
-                    outputs=[system_message, message, chatbot],
-                )
-                # Connect the send button to the chat function
-                btn.click(
-                    chat,
-                    inputs=[
-                        message,
-                        chatbot,
-                        model_selector,
-                        temperature_slider,
+                        ),
+                        gr.Slider(
+                            label="Temperature",
+                            minimum=0,
+                            maximum=2,
+                            step=0.1,
+                            value=0,
+                        ),
                         system_message,
                     ],
-                    outputs=[message, chatbot],
                 )
         with gr.Tab("Image Generation"):
             image_prompt = gr.Textbox(

requirements.txt

@@ -1,10 +1,10 @@
 fastapi
 fastapi-users[sqlalchemy]
-gradio
+gradio==3.44.4
 httpx
 openai
 python-dotenv
 Requests
-SQLAlchemy
+sqlalchemy[asyncio]
 uvicorn
 asyncpg