import gradio as gr
import os
import json
import requests
#Streaming endpoint
API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "/generate_stream"
# def handle_file(file_path, openai_gpt4_key, system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):
# """
# New function to handle file content.
# Reads the uploaded Python file and uses its content in the conversation.
# """
# # Read the content of the uploaded file
# with open(file_path, "r") as file:
# file_content = file.read()
# # Use the content of the file as part of your conversation
# # For example, prepend the file content to the inputs or system message
# # Here, we'll just pass the file_content as the system message for simplicity
# return predict(openai_gpt4_key, file_content, inputs, top_p, temperature, chat_counter, chatbot, history)
def handle_file(file_info, openai_gpt4_key, system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):
if file_info is not None:
# Read the content of the uploaded file directly from the file_info object
file_content = file_info["content"].read().decode("utf-8")
# Use the content as needed, for example, as the system message
return predict(openai_gpt4_key, file_content, inputs, top_p, temperature, chat_counter, chatbot, history)
else:
return "No file uploaded."
#Inferenec function
def predict(openai_gpt4_key, system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[]):
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {openai_gpt4_key}" #Users will provide their own OPENAI_API_KEY
}
print(f"system message is ^^ {system_msg}")
if system_msg.strip() == '':
initial_message = [{"role": "user", "content": f"{inputs}"},]
multi_turn_message = []
else:
initial_message= [{"role": "system", "content": system_msg},
{"role": "user", "content": f"{inputs}"},]
multi_turn_message = [{"role": "system", "content": system_msg},]
if chat_counter == 0 :
payload = {
"model": "gpt-4",
"messages": initial_message ,
"temperature" : 1.0,
"top_p":1.0,
"n" : 1,
"stream": True,
"presence_penalty":0,
"frequency_penalty":0,
}
print(f"chat_counter - {chat_counter}")
else: #if chat_counter != 0 :
messages=multi_turn_message # Of the type of - [{"role": "system", "content": system_msg},]
for data in chatbot:
user = {}
user["role"] = "user"
user["content"] = data[0]
assistant = {}
assistant["role"] = "assistant"
assistant["content"] = data[1]
messages.append(user)
messages.append(assistant)
temp = {}
temp["role"] = "user"
temp["content"] = inputs
messages.append(temp)
#messages
payload = {
"model": "gpt-4",
"messages": messages, # Of the type of [{"role": "user", "content": f"{inputs}"}],
"temperature" : temperature, #1.0,
"top_p": top_p, #1.0,
"n" : 1,
"stream": True,
"presence_penalty":0,
"frequency_penalty":0,}
chat_counter+=1
history.append(inputs)
print(f"Logging : payload is - {payload}")
# 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)
print(f"Logging : response code - {response}")
token_counter = 0
partial_words = ""
counter=0
for chunk in response.iter_lines():
#Skipping 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) > 12 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, response # resembles {chatbot: chat, state: history}
#Resetting to blank
def reset_textbox():
return gr.update(value='')
#to set a component as visible=False
def set_visible_false():
return gr.update(visible=False)
#to set a component as visible=True
def set_visible_true():
return gr.update(visible=True)
title = """
🔥GPT4 using Chat-Completions API & 🚀Gradio-Streaming
"""
#display message for themes feature
theme_addon_msg = """🌟 This Demo also introduces you to Gradio Themes. Discover more on Gradio website using our Themeing-Guide🎨! You can develop from scratch, modify an existing Gradio theme, and share your themes with community by uploading them to huggingface-hub easily using theme.push_to_hub()
.
"""
#Using info to add additional information about System message in GPT4
system_msg_info = """A conversation could begin with a system message to gently instruct the assistant.
System message helps set the behavior of the AI Assistant. For example, the assistant could be instructed with 'You are a helpful assistant.'"""
#Modifying existing Gradio Theme
theme = gr.themes.Soft(primary_hue="zinc", secondary_hue="green", neutral_hue="green",
text_size=gr.themes.sizes.text_lg)
with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;} #chatbot {height: 520px; overflow: auto;}""",
theme=theme) as demo:
gr.HTML(title)
gr.HTML("""🔥This Huggingface Gradio Demo provides you access to GPT4 API with System Messages. Please note that you would be needing an OPENAI API key for GPT4 access🙌""")
gr.HTML(theme_addon_msg)
gr.HTML('''
Duplicate the Space and run securely with your OpenAI API Key''')
with gr.Column(elem_id = "col_container"):
#Users need to provide their own GPT4 API key, it is no longer provided by Huggingface
with gr.Row():
openai_gpt4_key = gr.Textbox(label="OpenAI GPT4 Key", value="", type="password", placeholder="sk..", info = "You have to provide your own GPT4 keys for this app to function properly",)
with gr.Accordion(label="System message:", open=False):
system_msg = gr.Textbox(label="Instruct the AI Assistant to set its beaviour", info = system_msg_info, value="",placeholder="Type here..")
accordion_msg = gr.HTML(value="🚧 To set System message you will have to refresh the app", visible=False)
chatbot = gr.Chatbot(label='GPT4', elem_id="chatbot")
inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter")
state = gr.State([])
# Add a file upload component for Python files
# file_upload = gr.File(label="Upload Python File", type="file", placeholder="Upload a Python file to start the conversation with its content")
file_upload = gr.File(label="Upload Python File", type="file") # Removed 'placeholder' and corrected 'type'
#top_p, temperature
with gr.Accordion("Parameters", open=False):
top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p (nucleus sampling)",)
temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
chat_counter = gr.Number(value=0, visible=False, precision=0)
with gr.Row():
with gr.Column(scale=7):
b1 = gr.Button().style(full_width=True)
with gr.Column(scale=3):
server_status_code = gr.Textbox(label="Status code from OpenAI server", )
# Example modification for the input submission handler
inputs.submit(handle_file, inputs=[file_upload, openai_gpt4_key, system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], outputs=[chatbot, state, chat_counter, server_status_code])
# inputs.submit(handle_file, inputs=[file_upload, openai_gpt4_key, system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], outputs=[chatbot, state, chat_counter, server_status_code])
# inputs.submit(handle_file, [file_upload, openai_gpt4_key, system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code])
# If you have a button for submission, modify its click handler similarly
# b1.click(handle_file, [file_upload, openai_gpt4_key, system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code])
b1.click(handle_file, inputs=[file_upload, openai_gpt4_key, system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], outputs=[chatbot, state, chat_counter, server_status_code])
#top_p, temperature
with gr.Accordion("Parameters", open=False):
top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p (nucleus sampling)",)
temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
chat_counter = gr.Number(value=0, visible=False, precision=0)
#Event handling
inputs.submit( predict, [openai_gpt4_key, system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code],) #openai_api_key
b1.click( predict, [openai_gpt4_key, system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code],) #openai_api_key
inputs.submit(set_visible_false, [], [system_msg])
b1.click(set_visible_false, [], [system_msg])
inputs.submit(set_visible_true, [], [accordion_msg])
b1.click(set_visible_true, [], [accordion_msg])
b1.click(reset_textbox, [], [inputs])
inputs.submit(reset_textbox, [], [inputs])
#Examples
with gr.Accordion(label="Examples for System message:", open=False):
gr.Examples(
examples = [["""You are an AI programming assistant.
- Follow the user's requirements carefully and to the letter.
- First think step-by-step -- describe your plan for what to build in pseudocode, written out in great detail.
- Then output the code in a single code block.
- Minimize any other prose."""], ["""You are ComedianGPT who is a helpful assistant. You answer everything with a joke and witty replies."""],
["You are ChefGPT, a helpful assistant who answers questions with culinary expertise and a pinch of humor."],
["You are FitnessGuruGPT, a fitness expert who shares workout tips and motivation with a playful twist."],
["You are SciFiGPT, an AI assistant who discusses science fiction topics with a blend of knowledge and wit."],
["You are PhilosopherGPT, a thoughtful assistant who responds to inquiries with philosophical insights and a touch of humor."],
["You are EcoWarriorGPT, a helpful assistant who shares environment-friendly advice with a lighthearted approach."],
["You are MusicMaestroGPT, a knowledgeable AI who discusses music and its history with a mix of facts and playful banter."],
["You are SportsFanGPT, an enthusiastic assistant who talks about sports and shares amusing anecdotes."],
["You are TechWhizGPT, a tech-savvy AI who can help users troubleshoot issues and answer questions with a dash of humor."],
["You are FashionistaGPT, an AI fashion expert who shares style advice and trends with a sprinkle of wit."],
["You are ArtConnoisseurGPT, an AI assistant who discusses art and its history with a blend of knowledge and playful commentary."],
["You are a helpful assistant that provides detailed and accurate information."],
["You are an assistant that speaks like Shakespeare."],
["You are a friendly assistant who uses casual language and humor."],
["You are a financial advisor who gives expert advice on investments and budgeting."],
["You are a health and fitness expert who provides advice on nutrition and exercise."],
["You are a travel consultant who offers recommendations for destinations, accommodations, and attractions."],
["You are a movie critic who shares insightful opinions on films and their themes."],
["You are a history enthusiast who loves to discuss historical events and figures."],
["You are a tech-savvy assistant who can help users troubleshoot issues and answer questions about gadgets and software."],
["You are an AI poet who can compose creative and evocative poems on any given topic."],],
inputs = system_msg,)
demo.queue(max_size=99, concurrency_count=20).launch(debug=True)