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| 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" | |
| #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" : 0.6, | |
| "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, | |
| "max_tokens": 100 # Limiting the token count to 400 | |
| } | |
| 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">🔥Design Thinking Assistant for Primary 6 Students 🚀</h1>""" | |
| #Using info to add additional information about System message in GPT4 | |
| system_msg_info = """The system message is used to set the context and behavior of the AI assistant at the beginning of a conversation.""" | |
| #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">🔥This application provides AI assistance for Primary 6 Social Studies students in Singapore focusing on South East Asian Kingdoms 🎉🥳🎉🙌</h1>""") | |
| with gr.Column(elem_id = "col_container"): | |
| #GPT4 API Key is provided by Huggingface | |
| with gr.Accordion(label="System message:", open=False): | |
| system_msg = gr.Textbox(label="Instruct the AI Assistant to set its behaviour", | |
| info = system_msg_info, | |
| value="You are an AI assistant acting as a coach for Primary 6 students working on an environmental awareness project. Guide the students through the design thinking process to develop an effective campaign using upcycled materials. Motivate them to fully empathize with sustainability issues through research. Encourage creative solutions and provide constructive feedback. Make sure your explanations of the design thinking steps are clear and suitable for Primary 6 students.") | |
| accordion_msg = gr.HTML(value="🚧 To set System message you will have to refresh the app", visible=False) | |
| chatbot = gr.Chatbot(label='SS Coach', 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]) | |
| # Fix the indentation here | |
| with gr.Accordion(label="Examples for System message:", open=False): | |
| gr.Examples( | |
| examples=[["You are a Social Studies Coach for Primary 6 students in Singapore. Use Socratic questioning to help students discover the legacies of South East Asian Kingdoms such as Funan, Srivijaya, Sukhothai, Majapahit, Melaka, and Angkor. If a student asks about a topic outside of these, kindly redirect them to focus on the specified kingdoms."]], | |
| inputs=system_msg,) | |
| demo.queue(max_size=99, concurrency_count=40).launch(debug=True) |