app.py

import spaces
import json
import subprocess
from llama_cpp import Llama
from llama_cpp_agent import LlamaCppAgent
from llama_cpp_agent import 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
from ui import css, PLACEHOLDER

llm = None
llm_model = None
# hf_hub_download(repo_id="bartowski/dolphin-2.9.1-yi-1.5-34b-GGUF", filename="dolphin-2.9.1-yi-1.5-34b-Q6_K.gguf",  local_dir = "./models")
# hf_hub_download(repo_id="crusoeai/dolphin-2.9.1-llama-3-70b-GGUF", filename="dolphin-2.9.1-llama-3-70b.Q3_K_M.gguf",  local_dir = "./models")
hf_hub_download(repo_id="mradermacher/Dolphin3.0-Mistral-24B-GGUF", filename="Dolphin3.0-Mistral-24B.Q6_K.gguf",  local_dir = "./models")
# hf_hub_download(repo_id="kroonen/dolphin-2.9.2-Phi-3-Medium-GGUF", filename="dolphin-2.9.2-Phi-3-Medium-Q6_K.gguf",  local_dir = "./models")
hf_hub_download(repo_id="cognitivecomputations/dolphin-2.9.2-qwen2-72b-gguf", filename="qwen2-Q3_K_M.gguf",  local_dir = "./models")

@spaces.GPU(duration=120)
def respond(
    message,
    history: list[tuple[str, str]],
    model,
    max_tokens,
    temperature,
    top_p,
    top_k,
    repeat_penalty,
):
    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="You are Dolphin an AI assistant that helps humanity.",
        predefined_messages_formatter_type=MessagesFormatterType.CHATML,
        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 = ""
    for output in stream:
        outputs += output
        yield outputs

demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Dropdown([
            'Dolphin3.0-Mistral-24B.Q6_K.gguf',
            'qwen2-Q3_K_M.gguf'
        ], value="Dolphin3.0-Mistral-24B.Q6_K.gguf", label="Model"),
        gr.Slider(minimum=1, maximum=8192, value=8192, 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",
        ),
    ],
    theme=gr.themes.Soft(primary_hue="indigo", secondary_hue="blue", neutral_hue="gray",font=[gr.themes.GoogleFont("Exo"), "ui-sans-serif", "system-ui", "sans-serif"]).set(
        body_background_fill_dark="#0f172a",
        block_background_fill_dark="#0f172a",
        block_border_width="1px",
        block_title_background_fill_dark="#070d1b",
        input_background_fill_dark="#0c1425",
        button_secondary_background_fill_dark="#070d1b",
        border_color_accent_dark="#21293b",
        border_color_primary_dark="#21293b",
        background_fill_secondary_dark="#0f172a",
        color_accent_soft_dark="transparent"
    ),
    css=css,
    retry_btn="Retry",
    undo_btn="Undo",
    clear_btn="Clear",
    submit_btn="Send",
    description="Cognitive Computation: Chat Dolphin 🐬",
    chatbot=gr.Chatbot(
        scale=1,
        placeholder=PLACEHOLDER,
        show_copy_button=True
    )
)

if __name__ == "__main__":
    demo.launch()