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| # from huggingface_hub import InferenceClient | |
| # import gradio as gr | |
| # client = InferenceClient( | |
| # "mistralai/Mixtral-8x7B-Instruct-v0.1" | |
| # ) | |
| # def format_prompt(message, history): | |
| # prompt = "<s>" | |
| # for user_prompt, bot_response in history: | |
| # prompt += f"[INST] {user_prompt} [/INST]" | |
| # prompt += f" {bot_response}</s> " | |
| # prompt += f"[INST] {message} [/INST]" | |
| # return prompt | |
| # def generate( | |
| # prompt, history, system_prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, | |
| # ): | |
| # temperature = float(temperature) | |
| # if temperature < 1e-2: | |
| # temperature = 1e-2 | |
| # top_p = float(top_p) | |
| # generate_kwargs = dict( | |
| # temperature=temperature, | |
| # max_new_tokens=max_new_tokens, | |
| # top_p=top_p, | |
| # repetition_penalty=repetition_penalty, | |
| # do_sample=True, | |
| # seed=42, | |
| # ) | |
| # formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history) | |
| # stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) | |
| # output = "" | |
| # for response in stream: | |
| # output += response.token.text | |
| # yield output | |
| # return output | |
| # additional_inputs=[ | |
| # gr.Textbox( | |
| # label="System Prompt", | |
| # max_lines=1, | |
| # interactive=True, | |
| # ), | |
| # gr.Slider( | |
| # label="Temperature", | |
| # value=0.9, | |
| # minimum=0.0, | |
| # maximum=1.0, | |
| # step=0.05, | |
| # interactive=True, | |
| # info="Higher values produce more diverse outputs", | |
| # ), | |
| # gr.Slider( | |
| # label="Max new tokens", | |
| # value=256, | |
| # minimum=0, | |
| # maximum=1048, | |
| # step=64, | |
| # interactive=True, | |
| # info="The maximum numbers of new tokens", | |
| # ), | |
| # gr.Slider( | |
| # label="Top-p (nucleus sampling)", | |
| # value=0.90, | |
| # minimum=0.0, | |
| # maximum=1, | |
| # step=0.05, | |
| # interactive=True, | |
| # info="Higher values sample more low-probability tokens", | |
| # ), | |
| # gr.Slider( | |
| # label="Repetition penalty", | |
| # value=1.2, | |
| # minimum=1.0, | |
| # maximum=2.0, | |
| # step=0.05, | |
| # interactive=True, | |
| # info="Penalize repeated tokens", | |
| # ) | |
| # ] | |
| # examples=[["I'm planning a vacation to Japan. Can you suggest a one-week itinerary including must-visit places and local cuisines to try?", None, None, None, None, None, ], | |
| # ["Can you write a short story about a time-traveling detective who solves historical mysteries?", None, None, None, None, None,], | |
| # ["I'm trying to learn French. Can you provide some common phrases that would be useful for a beginner, along with their pronunciations?", None, None, None, None, None,], | |
| # ["I have chicken, rice, and bell peppers in my kitchen. Can you suggest an easy recipe I can make with these ingredients?", None, None, None, None, None,], | |
| # ["Can you explain how the QuickSort algorithm works and provide a Python implementation?", None, None, None, None, None,], | |
| # ["What are some unique features of Rust that make it stand out compared to other systems programming languages like C++?", None, None, None, None, None,], | |
| # ] | |
| # gr.ChatInterface( | |
| # fn=generate, | |
| # chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"), | |
| # additional_inputs=additional_inputs, | |
| # title="Mixtral 46.7B", | |
| # examples=examples, | |
| # concurrency_limit=20, | |
| # ).launch(show_api= True) | |
| from huggingface_hub import InferenceClient | |
| import gradio as gr | |
| from PyPDF2 import PdfReader | |
| client = InferenceClient( | |
| "mistralai/Mixtral-8x7B-Instruct-v0.1" | |
| ) | |
| def format_prompt(message, history): | |
| prompt = "<s>" | |
| for user_prompt, bot_response in history: | |
| prompt += f"[INST] {user_prompt} [/INST]" | |
| prompt += f" {bot_response}</s> " | |
| prompt += f"[INST] {message} [/INST]" | |
| return prompt | |
| def extract_text_from_pdf(pdf_file): | |
| text = "" | |
| pdf_reader = PdfReader(pdf_file) | |
| for page in pdf_reader.pages: | |
| text += page.extract_text() | |
| return text | |
| def generate(prompt, history, system_prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, pdf_text=None): | |
| temperature = float(temperature) | |
| if temperature < 1e-2: | |
| temperature = 1e-2 | |
| top_p = float(top_p) | |
| generate_kwargs = dict( | |
| temperature=temperature, | |
| max_new_tokens=max_new_tokens, | |
| top_p=top_p, | |
| repetition_penalty=repetition_penalty, | |
| do_sample=True, | |
| seed=42, | |
| ) | |
| formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history) | |
| if pdf_text: | |
| formatted_prompt += pdf_text | |
| stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) | |
| output = "" | |
| for response in stream: | |
| output += response.token.text | |
| yield output | |
| return output | |
| additional_inputs=[ | |
| gr.Textbox( | |
| label="System Prompt", | |
| max_lines=1, | |
| interactive=True, | |
| ), | |
| gr.File("file", label="Upload PDF"), | |
| gr.Slider( | |
| label="Temperature", | |
| value=0.9, | |
| minimum=0.0, | |
| maximum=1.0, | |
| step=0.05, | |
| interactive=True, | |
| info="Higher values produce more diverse outputs", | |
| ), | |
| gr.Slider( | |
| label="Max new tokens", | |
| value=256, | |
| minimum=0, | |
| maximum=1048, | |
| step=64, | |
| interactive=True, | |
| info="The maximum numbers of new tokens", | |
| ), | |
| gr.Slider( | |
| label="Top-p (nucleus sampling)", | |
| value=0.90, | |
| minimum=0.0, | |
| maximum=1, | |
| step=0.05, | |
| interactive=True, | |
| info="Higher values sample more low-probability tokens", | |
| ), | |
| gr.Slider( | |
| label="Repetition penalty", | |
| value=1.2, | |
| minimum=1.0, | |
| maximum=2.0, | |
| step=0.05, | |
| interactive=True, | |
| info="Penalize repeated tokens", | |
| ) | |
| ] | |
| examples=[ | |
| ["I'm planning a vacation to Japan. Can you suggest a one-week itinerary including must-visit places and local cuisines to try?", None, None, None, None, None, ], | |
| ["Can you write a short story about a time-traveling detective who solves historical mysteries?", None, None, None, None, None,], | |
| ["I'm trying to learn French. Can you provide some common phrases that would be useful for a beginner, along with their pronunciations?", None, None, None, None, None,], | |
| ["I have chicken, rice, and bell peppers in my kitchen. Can you suggest an easy recipe I can make with these ingredients?", None, None, None, None, None,], | |
| ["Can you explain how the QuickSort algorithm works and provide a Python implementation?", None, None, None, None, None,], | |
| ["What are some unique features of Rust that make it stand out compared to other systems programming languages like C++?", None, None, None, None, None,], | |
| ] | |
| gr.ChatInterface( | |
| fn=generate, | |
| chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"), | |
| additional_inputs=additional_inputs, | |
| title="Mixtral 46.7B", | |
| examples=examples, | |
| concurrency_limit=20, | |
| ).launch(show_api= True) | |