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| import gradio as gr | |
| import os | |
| import json | |
| import requests | |
| from thinking_routines import thinking_routine_prompt, thinking_routine_examples | |
| #Streaming endpoint | |
| API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "/generate_stream" | |
| #Huggingface provided GPT4 OpenAI API Key | |
| OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") | |
| #Inferenec function | |
| def predict(system_msg, inputs, top_p, temperature, chat_counter, chatbot=[], history=[]): | |
| headers = { | |
| "Content-Type": "application/json", | |
| "Authorization": f"Bearer {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 = """<h1 align="center">ππ Super Learning Buddy for Primary School Students π€β¨</h1>""" | |
| #Using info to add additional information about System message in GPT4 | |
| system_msg_info = """π€β¨ Choose your own learning buddy from the list! ππ""" | |
| # Modifying existing Gradio Theme | |
| theme = gr.themes.Soft(primary_hue="indigo", secondary_hue="blue", neutral_hue="blue", | |
| 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("""<h3 align="center">ππ Meet your fun Learning Buddy, ready for all thinking adventures! π§ β¨</h1>""") | |
| with gr.Column(elem_id = "col_container"): | |
| #GPT4 API Key is provided by Huggingface | |
| with gr.Accordion(label="Select you Coach:", open=False): | |
| system_msg = gr.Textbox(label="Choose the type of Coach to help guide you", info = system_msg_info, value="") | |
| accordion_msg = gr.HTML(value="π§ To set System message you will have to refresh the app", visible=False) | |
| with gr.Accordion(label="Examples of Coaches using thinking routines:", open=False): | |
| gr.Examples( | |
| examples=[[thinking_routine_prompt(subject, routine)] for subject, routine in thinking_routine_examples], | |
| inputs=system_msg, | |
| ) | |
| chatbot = gr.Chatbot(label='Learning Buddy', elem_id="chatbot") | |
| inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter") | |
| state = gr.State([]) | |
| 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", ) | |
| #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, [system_msg, inputs, top_p, temperature, chat_counter, chatbot, state], [chatbot, state, chat_counter, server_status_code],) #openai_api_key | |
| b1.click( predict, [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]) | |
| demo.queue(max_size=99, concurrency_count=20).launch(share=False) |