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 SpaceDuplicate 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)