import spaces import json import subprocess from llama_cpp import Llama from llama_cpp_agent import LlamaCppAgent, MessagesFormatterType from llama_cpp_agent.providers import LlamaCppPythonProvider from llama_cpp_agent.chat_history import BasicChatHistory from llama_cpp_agent.chat_history.messages import Roles import gradio as gr from huggingface_hub import hf_hub_download # モデルのダウンロード hf_hub_download( repo_id="Aratako/Oumuamua-7b-RP-GGUF", filename="Oumuamua-7b-RP_Q4_K_M.gguf", local_dir="./models" ) hf_hub_download( repo_id="bartowski/Oumuamua-7b-instruct-v2-GGUF", filename="Oumuamua-7b-instruct-v2-Q4_K_M.gguf", local_dir="./models" ) hf_hub_download( repo_id="mmnga/umiyuki-Umievo-itr012-Gleipnir-7B-gguf", filename="umiyuki-Umievo-itr012-Gleipnir-7B-Q4_K_M.gguf", local_dir="./models" ) hf_hub_download( repo_id="Local-Novel-LLM-project/Ninja-V3-GGUF", filename="Ninja-V3-Q4_K_M.gguf", local_dir="./models" ) hf_hub_download( repo_id="Local-Novel-LLM-project/Kagemusya-7B-v1-GGUF", filename="kagemusya-7b-v1Q8_0.gguf", local_dir="./models" ) hf_hub_download( repo_id="elyza/Llama-3-ELYZA-JP-8B-GGUF", filename="Llama-3-ELYZA-JP-8B-q4_k_m.gguf", local_dir="./models" ) llm = None llm_model = None @spaces.GPU(duration=120) async def respond( message, history: list[tuple[str, str]], model, system_message, max_tokens, temperature, top_p, top_k, repeat_penalty, Template, ): chat_template = MessagesFormatterType.GEMMA_2 global llm global llm_model if llm is None or llm_model != model: llm = Llama( model_path=f"models/{model}", flash_attn=True, n_gpu_layers=81, n_batch=1024, n_ctx=8192, ) llm_model = model provider = LlamaCppPythonProvider(llm) agent = LlamaCppAgent( provider, system_prompt=f"{system_message}", predefined_messages_formatter_type=chat_template, debug_output=True ) settings = provider.get_provider_default_settings() settings.temperature = temperature settings.top_k = top_k settings.top_p = top_p settings.max_tokens = max_tokens settings.repeat_penalty = repeat_penalty settings.stream = True messages = BasicChatHistory() for msn in history: user = { 'role': Roles.user, 'content': msn[0] } assistant = { 'role': Roles.assistant, 'content': msn[1] } messages.add_message(user) messages.add_message(assistant) stream = agent.get_chat_response( message, llm_sampling_settings=settings, chat_history=messages, returns_streaming_generator=True, print_output=False ) outputs = "" try: async for output in stream: outputs += output yield outputs except StopAsyncIteration: pass # Handle end of iteration gracefully description = """

Defaults to Oumuamua-7b-RP (you can switch to other models from additional inputs)

[Oumuamua-7b-RP Model] [Oumuamua-7b-instruct-v2 Model] [Umievo-itr012-Gleipnir-7B Model] [Ninja-V3 Model] [Kagemusya-7B-v1 Model] [Llama-3-ELYZA-JP-8B Model]

""" templates = [ "MISTRAL", "CHATML", "VICUNA", "LLAMA_2", "SYNTHIA", "NEURAL_CHAT", "SOLAR", "OPEN_CHAT", "ALPACA", "CODE_DS", "B22", "LLAMA_3", "PHI_3" ] demo = gr.ChatInterface( respond, additional_inputs=[ gr.Dropdown([ 'Oumuamua-7b-RP_Q4_K_M.gguf', 'Oumuamua-7b-instruct-v2-Q4_K_M.gguf', 'umiyuki-Umievo-itr012-Gleipnir-7B-Q4_K_M.gguf', 'Ninja-V3-Q4_K_M.gguf', 'kagemusya-7b-v1Q8_0.gguf', 'Llama-3-ELYZA-JP-8B-q4_k_m.gguf' ], value="Oumuamua-7b-RP_Q4_K_M.gguf", label="Model" ), gr.Dropdown( choices=templates, value="LLAMA_2", label="Template" ), gr.Textbox(value="You are a helpful assistant.", label="System message"), gr.Slider(minimum=1, maximum=4096, value=2048, step=1, label="Max tokens"), gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), gr.Slider( minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p", ), gr.Slider( minimum=0, maximum=100, value=40, step=1, label="Top-k", ), gr.Slider( minimum=0.0, maximum=2.0, value=1.1, step=0.1, label="Repetition penalty", ), ], retry_btn="Retry", undo_btn="Undo", clear_btn="Clear", submit_btn="Send", title="Chat with various models using llama.cpp", description=description, chatbot=gr.Chatbot( scale=1, likeable=False, show_copy_button=True ) ) if __name__ == "__main__": demo.launch()