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| import gradio as gr | |
| import os | |
| import json | |
| import requests | |
| HF_TOKEN = os.getenv('HF_TOKEN') | |
| HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"} | |
| zephyr_7b_beta = os.getenv('zephyr_7b_beta') | |
| zephyr_7b_alpha = os.getenv('zephyr_7b_alpha') | |
| def build_input_prompt(message, chatbot): | |
| """ | |
| Constructs the input prompt string from the chatbot interactions and the current message. | |
| """ | |
| input_prompt = "<|system|>\n</s>\n<|user|>\n" | |
| for interaction in chatbot: | |
| input_prompt = input_prompt + str(interaction[0]) + "</s>\n<|assistant|>\n" + str(interaction[1]) + "\n</s>\n<|user|>\n" | |
| input_prompt = input_prompt + str(message) + "</s>\n<|assistant|>" | |
| return input_prompt | |
| def post_request_beta(payload): | |
| """ | |
| Sends a POST request to the predefined Zephyr-7b-Beta URL and returns the JSON response. | |
| """ | |
| response = requests.post(zephyr_7b_beta, headers=HEADERS, json=payload) | |
| response.raise_for_status() # Will raise an HTTPError if the HTTP request returned an unsuccessful status code | |
| return response.json() | |
| def post_request_alpha(payload): | |
| """ | |
| Sends a POST request to the predefined Zephyr-7b-Alpha URL and returns the JSON response. | |
| """ | |
| response = requests.post(zephyr_7b_alpha, headers=HEADERS, json=payload) | |
| response.raise_for_status() # Will raise an HTTPError if the HTTP request returned an unsuccessful status code | |
| return response.json() | |
| def predict_beta(message, chatbot=[], temperature=0.9, max_new_tokens=256, top_p=0.6, repetition_penalty=1.0): | |
| temperature = float(temperature) | |
| top_p = float(top_p) | |
| input_prompt = build_input_prompt(message, chatbot) | |
| data = { | |
| "inputs": input_prompt, | |
| "parameters": { | |
| "max_new_tokens": max_new_tokens, | |
| "temperature": temperature, | |
| "top_p": top_p, | |
| "repetition_penalty": repetition_penalty, | |
| "do_sample": True, | |
| }, | |
| } | |
| try: | |
| response_data = post_request_beta(data) | |
| json_obj = response_data[0] | |
| if 'generated_text' in json_obj and len(json_obj['generated_text']) > 0: | |
| bot_message = json_obj['generated_text'] | |
| chatbot.append((message, bot_message)) | |
| return "", chatbot | |
| elif 'error' in json_obj: | |
| raise gr.Error(json_obj['error'] + ' Please refresh and try again with smaller input prompt') | |
| else: | |
| warning_msg = f"Unexpected response: {json_obj}" | |
| raise gr.Error(warning_msg) | |
| except requests.HTTPError as e: | |
| error_msg = f"Request failed with status code {e.response.status_code}" | |
| raise gr.Error(error_msg) | |
| except json.JSONDecodeError as e: | |
| error_msg = f"Failed to decode response as JSON: {str(e)}" | |
| raise gr.Error(error_msg) | |
| def predict_alpha(message, chatbot=[], temperature=0.9, max_new_tokens=256, top_p=0.6, repetition_penalty=1.0): | |
| temperature = float(temperature) | |
| top_p = float(top_p) | |
| input_prompt = build_input_prompt(message, chatbot) | |
| data = { | |
| "inputs": input_prompt, | |
| "parameters": { | |
| "max_new_tokens": max_new_tokens, | |
| "temperature": temperature, | |
| "top_p": top_p, | |
| "repetition_penalty": repetition_penalty, | |
| "do_sample": True, | |
| }, | |
| } | |
| try: | |
| response_data = post_request_beta(data) | |
| json_obj = response_data[0] | |
| if 'generated_text' in json_obj and len(json_obj['generated_text']) > 0: | |
| bot_message = json_obj['generated_text'] | |
| chatbot.append((message, bot_message)) | |
| return "", chatbot | |
| elif 'error' in json_obj: | |
| raise gr.Error(json_obj['error'] + ' Please refresh and try again with smaller input prompt') | |
| else: | |
| warning_msg = f"Unexpected response: {json_obj}" | |
| raise gr.Error(warning_msg) | |
| except requests.HTTPError as e: | |
| error_msg = f"Request failed with status code {e.response.status_code}" | |
| raise gr.Error(error_msg) | |
| except json.JSONDecodeError as e: | |
| error_msg = f"Failed to decode response as JSON: {str(e)}" | |
| raise gr.Error(error_msg) | |
| def retry_fun_beta(chat_history_beta ): | |
| """ | |
| Retries the prediction for the last message in the chat history. | |
| Removes the last interaction and gets a new prediction for the same message from Zephyr-7b-Beta | |
| """ | |
| if not chat_history or len(chat_history) < 1: | |
| raise gr.Error("Chat history is empty or invalid.") | |
| message = chat_history_beta[-1][0] | |
| chat_history_beta.pop() | |
| _, updated_chat_history_beta = predict_beta(message, chat_history_beta) | |
| return updated_chat_history_beta | |
| def retry_fun_alpha(chat_history_alpha ): | |
| """ | |
| Retries the prediction for the last message in the chat history. | |
| Removes the last interaction and gets a new prediction for the same message from Zephyr-7b-Alpha | |
| """ | |
| if not chat_history or len(chat_history) < 1: | |
| raise gr.Error("Chat history is empty or invalid.") | |
| message = chat_history_alpha[-1][0] | |
| chat_history_alpha.pop() | |
| _, updated_chat_history_alpha = predict_alpha(message, chat_history_alpha) | |
| return updated_chat_history_alpha | |
| title = "🌀Zephyr Playground🎮" | |
| description = """ | |
| Welcome to the Zephyr Playground! This interactive space lets you experience the prowess of two distinct Zephyr models – [Zephyr-7b-Alpha](https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha) and [Zephyr-7b-Beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) – side by side. These models are products of fine-tuning the Mistral models. | |
| - 🔎 Dive deep into the nuances and performance of these models by comparing their responses in real-time. | |
| - 📖 For a comprehensive understanding of the Zephyr models, delve into their [technical report](https://arxiv.org/abs/2310.16944) and experiment with the [official Zephyr demo](https://huggingfaceh4-zephyr-chat.hf.space/). | |
| - 🛠 If you wish to explore more chat models or set up your own interactive demo, visit the [Hugging Face's chat playground](https://huggingface.co/spaces/HuggingFaceH4/chat-playground). | |
| """ | |
| footnote = """Note: All rights, including licensing and acceptable use policies, related to the Zephyr models, can be found on their respective model pages on Hugging Face. | |
| """ | |
| css = """ | |
| .gradio-container { | |
| width: 100vw !important; | |
| min-height: 100vh !important; | |
| padding:0 !important; | |
| margin:0 !important; | |
| max-width: none !important; | |
| } | |
| """ | |
| # Create chatbot components | |
| chat_beta = gr.Chatbot(label="zephyr-7b-beta") | |
| chat_alpha = gr.Chatbot(label="zephyr-7b-alpha") | |
| # Create input and button components | |
| textbox = gr.Textbox(container=False, | |
| placeholder='Enter text and click the Submit button or press Enter') | |
| submit = gr.Button('Submit', variant='primary',) | |
| retry = gr.Button('🔄Retry', variant='secondary') | |
| undo = gr.Button('↩️Undo', variant='secondary') | |
| # Layout the components using Gradio Blocks API | |
| with gr.Blocks(css=css) as demo: | |
| gr.HTML(f'<h1><center> {title} </center></h1>') | |
| gr.Markdown(description) | |
| with gr.Row(): | |
| chat_beta.render() | |
| chat_alpha.render() | |
| with gr.Group(): | |
| with gr.Row(equal_height=True): | |
| with gr.Column(scale=5): | |
| textbox.render() | |
| with gr.Column(scale=1): | |
| submit.render() | |
| with gr.Row(): | |
| retry.render() | |
| undo.render() | |
| clear = gr.ClearButton(value='🗑️Clear', | |
| components=[textbox, | |
| chat_beta, | |
| chat_alpha]) | |
| gr.Markdown(footnote) | |
| # Assign events to components | |
| textbox.submit(predict_beta, [textbox, chat_beta], [textbox, chat_beta]) | |
| textbox.submit(predict_alpha, [textbox, chat_alpha], [textbox, chat_alpha]) | |
| submit.click(predict_beta, [textbox, chat_beta], [textbox, chat_beta]) | |
| submit.click(predict_alpha, [textbox, chat_alpha], [textbox, chat_alpha]) | |
| undo.click(lambda x:x[:-1], [chat_beta], [chat_beta]) | |
| undo.click(lambda x:x[:-1], [chat_alpha], [chat_alpha]) | |
| retry.click(retry_fun_beta, [chat_beta], [chat_beta]) | |
| retry.click(retry_fun_alpha, [chat_alpha], [chat_alpha]) | |
| gr.Examples([ | |
| ['Hi! Who are you?'], | |
| ['What is a meme?'], | |
| ['Explain the plot of Cinderella in a sentence.'], | |
| ['Assuming I am a huge alien species with the ability to consume helicopters, how long would it take me to eat one?'], | |
| ], | |
| textbox) | |
| # Launch the demo | |
| demo.launch(debug=True) |