import gradio as gr import os import sys import json import requests MODEL = "gpt-3.5-turbo-0125" 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 = """

Free Chat GPT 3.5 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-3.5 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 GPT-3.5 (4096 token limit) 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, Open GPT or Llama 2 app

""") 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)