app.py

import os
import gradio as gr
import json
import requests
import openai

try:
     openai.api_key = os.environ["OPENAI_API_KEY"]

except KeyError:
    error_message = "System is at capacity right now.Please try again later"
    print(error_message)
    def chatbot(input):
        return error_message
else:
    messages = [
        {"role": "system", "content": "My AI Assistant"},
    ]

#Streaming endpoint for OPENAI ChatGPT
API_URL = "https://api.openai.com/v1/chat/completions"
top_p_chatgpt = 1.0
temperature_chatgpt = 1.0

#Predict function for CHATGPT
def chatbot(inputs, chat_counter_chatgpt, chatbot_chatgpt=[], history=[]):  
    #Define payload and header for chatgpt API
    payload = {
    "model": "gpt-3.5-turbo",
    "messages": [{"role": "user", "content": f"{inputs}"}],
    "temperature" : 1.0,
    "top_p":1.0,
    "n" : 1,
    "stream": True,
    "presence_penalty":0,
    "frequency_penalty":0,
    }

    headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {openai.api_key}"
    }
    
    #Handling the different roles for ChatGPT
    if chat_counter_chatgpt != 0 :
        messages=[]
        for data in chatbot_chatgpt:
          temp1 = {}
          temp1["role"] = "user" 
          temp1["content"] = data[0] 
          temp2 = {}
          temp2["role"] = "assistant" 
          temp2["content"] = data[1]
          messages.append(temp1)
          messages.append(temp2)
        temp3 = {}
        temp3["role"] = "user" 
        temp3["content"] = inputs
        messages.append(temp3)
        payload = {
        "model": "gpt-3.5-turbo",
        "messages": messages, #[{"role": "user", "content": f"{inputs}"}],
        "temperature" : temperature_chatgpt, #1.0,
        "top_p": top_p_chatgpt, #1.0,
        "n" : 1,
        "stream": True,
        "presence_penalty":0,
        "frequency_penalty":0,
        }

    chat_counter_chatgpt+=1

    history.append("You asked:  "+ inputs)

    # make a POST request to the API endpoint using the requests.post method, passing in stream=True
    response = requests.post(API_URL, headers=headers, json=payload, stream=True)
    token_counter = 0 
    partial_words = ""  

    counter=0
    for chunk in response.iter_lines():
        #Skipping the first chunk
        if counter == 0:
          counter+=1
          continue
        # check whether each line is non-empty
        if chunk.decode() :
          chunk = chunk.decode()
          # decode each line as response data is in bytes
          if len(chunk) > 13 and "content" in json.loads(chunk[6:])['choices'][0]["delta"]:
              partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
              if token_counter == 0:
                history.append(" " + partial_words)
              else:
                history[-1] = partial_words
              chat = [(history[i], history[i + 1]) for i in range(0, len(history) - 1, 2) ]  # convert to tuples of list
              token_counter+=1
              yield chat, history, chat_counter_chatgpt  # this resembles {chatbot: chat, state: history}  


def reset_textbox():
    return gr.update(value="")

def reset_chat(chatbot, state):
    return None, []

with gr.Blocks(css="""#col_container {width: 1000px; margin-left: auto; margin-right: auto;}
                #chatgpt {height: 400px; overflow: auto;}} """, theme=gr.themes.Default(primary_hue="slate") ) as demo:
    with gr.Row():
      with gr.Column(scale=14):
          with gr.Box():
              with gr.Row():
                  with gr.Column(scale=13):
                    inputs = gr.Textbox(label="Ask me anything ⤵️   Try: Value of pi" )
                  with gr.Column(scale=1):
                      b1 = gr.Button('Submit', elem_id = 'submit').style(full_width=True)
                      b2 = gr.Button('Clear', elem_id = 'clear').style(full_width=True)
                  state_chatgpt = gr.State([])

          with gr.Box():
              with gr.Row():
                  chatbot_chatgpt = gr.Chatbot(elem_id="chatgpt", label='')
    chat_counter_chatgpt = gr.Number(value=0, visible=False, precision=0)
             

    inputs.submit(reset_textbox, [], [inputs])
    
    b1.click( chatbot, 
                [ inputs,  chat_counter_chatgpt, chatbot_chatgpt, state_chatgpt], 
                [chatbot_chatgpt, state_chatgpt],)

    b2.click(reset_chat, [chatbot_chatgpt, state_chatgpt], [chatbot_chatgpt, state_chatgpt])

    demo.queue(concurrency_count=16).launch(height= 2500, debug=True)