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# Import necessary libraries
import os
import time
import openai
from dotenv import load_dotenv
load_dotenv()
openai.api_key = os.getenv("OPENAI_API_KEY")
import gradio as gr
# Create an empty list to store chat messages
messages = []
# Function to add user's text to chat history
def add_user_text(chat_history, user_text):
print('user_text_from_typing: ', user_text)
global messages
messages += [{"role":'user', 'content': user_text}]
chat_history = chat_history + [(user_text, None)]
return chat_history, gr.update(value="", interactive=False)
# Function for the bot to respond
def bot_respond(chat_history, openai_gpt_key):
global messages
if openai_gpt_key is not "":
openai.api_key = openai_gpt_key
# Generate response from OpenAI Chat API
bot_response = openai.ChatCompletion.create(
model='gpt-3.5-turbo',
messages=messages,
)
bot_text = bot_response["choices"][0]["message"]["content"]
print("bot_text: ", bot_text)
messages = messages + [{"role":'assistant', 'content': bot_text}]
print(chat_history)
chat_history[-1][1] = ""
# Yield the chat history with the bot's response character by character
for character in bot_text:
chat_history[-1][1] += character
time.sleep(0.02)
yield chat_history
# Create a Gradio interface
with gr.Blocks() as demo:
openai_gpt_key = gr.Textbox(label="OpenAI GPT API Key", value="", placeholder="sk..", info="If an error is raised, you need to provide your own GPT keys for this app to function properly")
clear_btn = gr.Button("Clear for Restart")
chat_history = gr.Chatbot([], elem_id="chat_history").style(height=500)
with gr.Box():
user_text = gr.Textbox(
show_label=False,
placeholder="Enter text and press enter",
).style(container=False)
# Handle user input and bot response
user_text.submit(
add_user_text, [chat_history, user_text], [chat_history, user_text], queue=False).then(
bot_respond, [chat_history, openai_gpt_key], chat_history).then(
lambda: gr.update(interactive=True), None, [user_text], queue=False)
clear_btn.click(lambda: None, None, chat_history, queue=False)
if __name__ == "__main__":
demo.queue()
demo.launch()
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