import gradio as gr import os import sys import json import requests MODEL = os.getenv("MODEL") API_URL = os.getenv("API_URL") DISABLED = os.getenv("DISABLED") == 'True' OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") NUM_THREADS = int(os.getenv("NUM_THREADS")) print (NUM_THREADS) def exception_handler(exception_type, exception, traceback): print("%s: %s" % (exception_type.__name__, exception)) sys.excepthook = exception_handler sys.tracebacklimit = 0 #https://github.com/gradio-app/gradio/issues/3531#issuecomment-1484029099 def parse_codeblock(text): lines = text.split("\n") for i, line in enumerate(lines): if "```" in line: if line != "```": lines[i] = f'
'
            else:
                lines[i] = '
' else: if i > 0: lines[i] = "
" + line.replace("<", "<").replace(">", ">") return "".join(lines) def predict(inputs, top_p, temperature, chat_counter, chatbot, history, request:gr.Request): payload = { "model": MODEL, "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}" } # print(f"chat_counter - {chat_counter}") if chat_counter != 0 : messages = [] for i, data in enumerate(history): if i % 2 == 0: role = 'user' else: role = 'assistant' message = {} message["role"] = role message["content"] = data messages.append(message) message = {} message["role"] = "user" message["content"] = inputs messages.append(message) payload = { "model": MODEL, "messages": messages, "temperature" : temperature, "top_p": top_p, "n" : 1, "stream": True, "presence_penalty":0, "frequency_penalty":0, } chat_counter += 1 history.append(inputs) token_counter = 0 partial_words = "" counter = 0 try: # 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) response_code = f"{response}" #if response_code.strip() != "": # #print(f"response code - {response}") # raise Exception(f"Sorry, hitting rate limit. Please try again later. {response}") for chunk in response.iter_lines(): #Skipping first chunk if counter == 0: counter += 1 continue #counter+=1 # 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 token_counter += 1 yield [(parse_codeblock(history[i]), parse_codeblock(history[i + 1])) for i in range(0, len(history) - 1, 2) ], history, chat_counter, response, gr.update(interactive=False), gr.update(interactive=False) # resembles {chatbot: chat, state: history} except Exception as e: print (f'error found: {e}') yield [(parse_codeblock(history[i]), parse_codeblock(history[i + 1])) for i in range(0, len(history) - 1, 2) ], history, chat_counter, response, gr.update(interactive=True), gr.update(interactive=True) print(json.dumps({"chat_counter": chat_counter, "payload": payload, "partial_words": partial_words, "token_counter": token_counter, "counter": counter})) def reset_textbox(): return gr.update(value='', interactive=False), gr.update(interactive=False) title = """

Chat GPT 4 online

""" if DISABLED: title = """

This app has reached OpenAI's usage limit. We are currently requesting an increase in our quota. Please check back in a few days.

""" description = """Language models can be conditioned to act like dialogue agents through a conversational prompt that typically takes the form: ``` User: Assistant: User: Assistant: ... ``` In this app, you can explore the outputs of a gpt-4 LLM. """ theme = gr.themes.Default(primary_hue="green") 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 app provides you full access to Chat GPT-4 thanks to Stable Diffusion AI online. You don't need any OPENAI API key.

If this app doesn't respond, it's likely due to too much visitors. Consider trying Chat GPT-3.5 or Llama 2 apps.

""") with gr.Column(elem_id = "col_container", visible=True) as main_block: #openai_api_key = gr.Textbox(type='password', label="Enter only your OpenAI API key here") chatbot = gr.Chatbot(elem_id='chatbot') #c inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter") #t state = gr.State([]) #s with gr.Row(): with gr.Column(scale=7): b1 = gr.Button(visible=not DISABLED) with gr.Column(scale=3): server_status_code = gr.Textbox(label="Status code from OpenAI server", ) #inputs, top_p, temperature, top_k, repetition_penalty 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",) #top_k = gr.Slider( minimum=1, maximum=50, value=4, step=1, interactive=True, label="Top-k",) #repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.03, step=0.01, interactive=True, label="Repetition Penalty", ) chat_counter = gr.Number(value=0, visible=False, precision=0) def enable_inputs(): return main_block.update(visible=True) inputs.submit(reset_textbox, [], [inputs, b1], queue=False) inputs.submit(predict, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code, inputs, b1],) #openai_api_key b1.click(reset_textbox, [], [inputs, b1], queue=False) b1.click(predict, [inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code, inputs, b1],) #openai_api_key demo.queue(max_size=10, api_open=False).launch(share=False)