import argparse import os from typing import Iterator import gradio as gr # from dotenv import load_dotenv from distutils.util import strtobool from llama2_wrapper import LLAMA2_WRAPPER parser = argparse.ArgumentParser() 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. If 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." parser.add_argument('--model_path', type=str, required=False, default='76437bc4e8bea417641aaa076508098a7158e664c1cecfabfa41df497a27f98c', help='model_path .') parser.add_argument('--system_prompt', type=str, required=False, default=DEFAULT_SYSTEM_PROMPT, help='Inference server Appkey. Default is .') parser.add_argument('--max_max_new_tokens', type=int, default=2048, metavar='NUMBER', help='maximum new tokens (default: 2048)') FLAGS = parser.parse_args() DEFAULT_SYSTEM_PROMPT = FLAGS.system_prompt MAX_MAX_NEW_TOKENS = FLAGS.max_max_new_tokens DEFAULT_MAX_NEW_TOKENS = 1024 MAX_INPUT_TOKEN_LENGTH = 4000 MODEL_PATH = FLAGS.model_path assert MODEL_PATH is not None, f"MODEL_PATH is required, got: {MODEL_PATH}" LOAD_IN_8BIT = False LOAD_IN_4BIT = True LLAMA_CPP = True if LLAMA_CPP: print("Running on CPU with llama.cpp.") else: import torch if torch.cuda.is_available(): print("Running on GPU with torch transformers.") else: print("CUDA not found.") config = { "model_name": MODEL_PATH, "load_in_8bit": LOAD_IN_8BIT, "load_in_4bit": LOAD_IN_4BIT, "llama_cpp": LLAMA_CPP, "MAX_INPUT_TOKEN_LENGTH": MAX_INPUT_TOKEN_LENGTH, } llama2_wrapper = LLAMA2_WRAPPER(config) llama2_wrapper.init_tokenizer() llama2_wrapper.init_model() DESCRIPTION = """ # Llama2-Chinese-7b-webui 这是一个[Llama2-Chinese-2-7b](https://github.com/FlagAlpha/Llama2-Chinese)的推理界面。 - 支持的模型: [Llama-2-GGML](https://huggingface.co/FlagAlpha/Llama2-Chinese-7b-Chat-GGML) - 支持的后端 - CPU(at least 6 GB RAM), Mac/AMD """ 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 = llama2_wrapper.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: pass return "", x def check_input_token_length( message: str, chat_history: list[tuple[str, str]], system_prompt: str ) -> None: input_token_length = llama2_wrapper.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) 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("↩️ Undo", variant="secondary") clear_button = gr.Button("🗑️ 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?", ], inputs=textbox, outputs=[textbox, chatbot], fn=process_example, cache_examples=True, ) 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(server_name="0.0.0.0", server_port=8090)