app.py

from transformers import pipeline, Conversation
import gradio as gr

from dotenv import load_dotenv

# Load environment variables from the .env file
load_dotenv()
# chatbot = pipeline(model="microsoft/DialoGPT-medium")
# conversation = Conversation("Hi")
# response = chatbot(conversation)
# #conversation.mark_processed()
# #conversation.append_response(response)
# conversation.add_user_input("How old are you?")

# conversation2 = chatbot(conversation)
# print(conversation2)

# def respond(text, conversation):
#     chatbot = pipeline(model="microsoft/DialoGPT-medium")

#     if len(conversation)==0:
#         conversation = Conversation(text)
#         conversation = chatbot(conversation)
#         print(conversation.iter_texts())
#         # test = []
#         # for user,text in conversation.iter_texts():
            

#         return text, conversation.iter_texts()
#     else:
#         conversation.add_user_input(text)
#         conversation = chatbot(conversation)
#         return text, conversation.iter_texts()

import os
import openai
openai.api_key = os.getenv("OPENAI_API_KEY")

# response = openai.ChatCompletion.create(
#   model="gpt-3.5-turbo",
#   messages=[],
#   temperature=0.5,
#   max_tokens=256
# )
# def format_chat_prompt(message, chat_history, instruction):
#     prompt = f"System:{instruction}"
#     for turn in chat_history:
#         user_message, bot_message = turn
#         prompt = f"{prompt}\nUser: {user_message}\nAssistant: {bot_message}"
#     prompt = f"{prompt}\nUser: {message}\nAssistant:"
#     return prompt


def add_new_message(message,chat_history):
     new_chat = []
     for turn in chat_history:
          user, bot = turn
          new_chat.append({"role": "user", "content": user})
          new_chat.append({"role": "assistant","content":bot})
     new_chat.append({"role": "user","content":message})
     return new_chat
    
          

def respond(message, chat_history):
    prompt = add_new_message(message, chat_history)
    # stream = client.generate_stream(prompt,
    #                                   max_new_tokens=1024,
    #                                   stop_sequences=["\nUser:", "<|endoftext|>"],
    #                                   temperature=temperature)
    #                                   #stop_sequences to not generate the user answer
    # acc_text = ""
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages= prompt,
        temperature=0.5,
        max_tokens=120
        ).choices[0].message.content
    chat_history.append((message, response))
    return "",chat_history
    #Streaming the tokens
    # for idx, response in enumerate(stream):
    #         text_token = response.token.text

    #         if response.details:
    #             return

    #         if idx == 0 and text_token.startswith(" "):
    #             text_token = text_token[1:]

    #         acc_text += text_token
    #         last_turn = list(chat_history.pop(-1))
    #         last_turn[-1] += acc_text
    #         chat_history = chat_history + [last_turn]
    #         yield "", chat_history
    #         acc_text = ""

with gr.Blocks() as demo:
    chatbot = gr.Chatbot(height=240) #just to fit the notebook
    msg = gr.Textbox(label="Prompt")
    btn = gr.Button("Submit")
    clear = gr.ClearButton(components=[msg, chatbot], value="Clear console")

    btn.click(respond, inputs=[msg, chatbot], outputs=[msg, chatbot])
    msg.submit(respond, inputs=[msg, chatbot], outputs=[msg, chatbot]) #Press enter to submit

demo.launch()