from typing import Iterator import gradio as gr import torch from model import get_input_token_length, run DEFAULT_SYSTEM_PROMPT = """\ You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.\ """ MAX_MAX_NEW_TOKENS = 2048 DEFAULT_MAX_NEW_TOKENS = 1024 MAX_INPUT_TOKEN_LENGTH = 4000 DESCRIPTION = """ # Demoing Llama-2 7B on Moj7BChat with lic This Space demonstrates model [Llama-2-13b-chat](https://huggingface.co/meta-llama/Llama-2-13b-chat) by Meta, a Llama 2 model with 13B parameters fine-tuned for chat instructions. Feel free to play with it, or duplicate to run generations without a queue! If you want to run your own service, you can also [deploy the model on Inference Endpoints](https://huggingface.co/inference-endpoints). 🔎 For more details about the Llama 2 family of models and how to use them with `transformers`, take a look [at our blog post](https://huggingface.co/blog/llama2). 🔨 Looking for an even more powerful model? Check out the large [**70B** model demo](https://huggingface.co/spaces/ysharma/Explore_llamav2_with_TGI). 🐇 For a smaller model that you can run on many GPUs, check our [7B model demo](https://huggingface.co/spaces/huggingface-projects/llama-2-7b-chat). """ LICENSE = """

--- As a derivate work of [Llama-2-7b-chat](https://huggingface.co/meta-llama/Llama-2-13b-chat) by Meta, this demo is governed by the original [license](https://huggingface.co/spaces/huggingface-projects/llama-2-13b-chat/blob/main/LICENSE.txt) and [acceptable use policy](https://huggingface.co/spaces/huggingface-projects/llama-2-13b-chat/blob/main/USE_POLICY.md). """ if torch.cuda.is_available(): DESCRIPTION += '\n

Running on GPU đŸĨļ Do not use GPU $$.

' def clear_and_save_textbox(message: str) -> tuple[str, str]: return '', message def display_input(message: str, history: list[tuple[str, str]]) -> list[tuple[str, str]]: history.append((message, '')) return history def delete_prev_fn( history: list[tuple[str, str]]) -> tuple[list[tuple[str, str]], str]: try: message, _ = history.pop() except IndexError: message = '' return history, message or '' def generate( message: str, history_with_input: list[tuple[str, str]], system_prompt: str, max_new_tokens: int, temperature: float, top_p: float, top_k: int, ) -> Iterator[list[tuple[str, str]]]: if max_new_tokens > MAX_MAX_NEW_TOKENS: raise ValueError history = history_with_input[:-1] generator = run(message, history, system_prompt, max_new_tokens, temperature, top_p, top_k) try: first_response = next(generator) yield history + [(message, first_response)] except StopIteration: yield history + [(message, '')] for response in generator: yield history + [(message, response)] def process_example(message: str) -> tuple[str, list[tuple[str, str]]]: generator = generate(message, [], DEFAULT_SYSTEM_PROMPT, 1024, 1, 0.95, 50) for x in generator: print(f"Printing x before pass {x}") pass print(f"Printing x after pass {x}") return '', x def check_input_token_length(message: str, chat_history: list[tuple[str, str]], system_prompt: str) -> None: input_token_length = get_input_token_length(message, chat_history, system_prompt) if input_token_length > MAX_INPUT_TOKEN_LENGTH: raise gr.Error(f'The accumulated input is too long ({input_token_length} > {MAX_INPUT_TOKEN_LENGTH}). Clear your chat history and try again.') with gr.Blocks(css='style.css') as demo: gr.Markdown(DESCRIPTION) # gr.DuplicateButton(value='Duplicate Space for private use', # elem_id='duplicate-button') with gr.Group(): chatbot = gr.Chatbot(label='Chatbot') with gr.Row(): textbox = gr.Textbox( container=False, show_label=False, placeholder='Type a message...', scale=10, ) submit_button = gr.Button('Submit', variant='primary', scale=1, min_width=0) with gr.Row(): retry_button = gr.Button('🔄 Retry', variant='secondary') undo_button = gr.Button('↩ī¸ Undo', variant='secondary') clear_button = gr.Button('🗑ī¸ Clear', variant='secondary') saved_input = gr.State() with gr.Accordion(label='Advanced options', open=False): system_prompt = gr.Textbox(label='System prompt', value=DEFAULT_SYSTEM_PROMPT, lines=6) max_new_tokens = gr.Slider( label='Max new tokens', minimum=1, maximum=MAX_MAX_NEW_TOKENS, step=1, value=DEFAULT_MAX_NEW_TOKENS, ) temperature = gr.Slider( label='Temperature', minimum=0.1, maximum=4.0, step=0.1, value=1.0, ) top_p = gr.Slider( label='Top-p (nucleus sampling)', minimum=0.05, maximum=1.0, step=0.05, value=0.95, ) top_k = gr.Slider( label='Top-k', minimum=1, maximum=1000, step=1, value=50, ) gr.Examples( examples=[ 'Hello there! How are you doing?', 'Can you explain briefly to me what is the Python programming language?', 'Explain the plot of Cinderella in a sentence.', 'How many hours does it take a man to eat a Helicopter?', "Write a 100-word article on 'Benefits of Open-Source in AI research'", ], inputs=textbox, outputs=[textbox, chatbot], fn=process_example, cache_examples=True, ) gr.Markdown(LICENSE) textbox.submit( fn=clear_and_save_textbox, inputs=textbox, outputs=[textbox, saved_input], api_name=False, queue=False, ).then( fn=display_input, inputs=[saved_input, chatbot], outputs=chatbot, api_name=False, queue=False, ).then( fn=check_input_token_length, inputs=[saved_input, chatbot, system_prompt], api_name=False, queue=False, ).success( fn=generate, inputs=[ saved_input, chatbot, system_prompt, max_new_tokens, temperature, top_p, top_k, ], outputs=chatbot, api_name=False, ) button_event_preprocess = submit_button.click( fn=clear_and_save_textbox, inputs=textbox, outputs=[textbox, saved_input], api_name=False, queue=False, ).then( fn=display_input, inputs=[saved_input, chatbot], outputs=chatbot, api_name=False, queue=False, ).then( fn=check_input_token_length, inputs=[saved_input, chatbot, system_prompt], api_name=False, queue=False, ).success( fn=generate, inputs=[ saved_input, chatbot, system_prompt, max_new_tokens, temperature, top_p, top_k, ], outputs=chatbot, api_name=False, ) retry_button.click( fn=delete_prev_fn, inputs=chatbot, outputs=[chatbot, saved_input], api_name=False, queue=False, ).then( fn=display_input, inputs=[saved_input, chatbot], outputs=chatbot, api_name=False, queue=False, ).then( fn=generate, inputs=[ saved_input, chatbot, system_prompt, max_new_tokens, temperature, top_p, top_k, ], outputs=chatbot, api_name=False, ) undo_button.click( fn=delete_prev_fn, inputs=chatbot, outputs=[chatbot, saved_input], api_name=False, queue=False, ).then( fn=lambda x: x, inputs=[saved_input], outputs=textbox, api_name=False, queue=False, ) clear_button.click( fn=lambda: ([], ''), outputs=[chatbot, saved_input], queue=False, api_name=False, ) demo.queue(max_size=20).launch()