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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
llm = None
llm_model = None
hf_hub_download(
repo_id="unsloth/Reflection-Llama-3.1-70B-GGUF",
filename="Reflection-Llama-3.1-70B.Q3_K_L.gguf",
local_dir = "./models"
)
def get_messages_formatter_type(model_name):
if "Llama" in model_name:
return MessagesFormatterType.LLAMA_3
else:
raise ValueError(f"Unsupported model: {model_name}")
@spaces.GPU
def respond(
message,
history: list[tuple[str, str]],
model,
system_message,
max_tokens,
temperature,
top_p,
top_k,
repeat_penalty,
):
global llm
global llm_model
chat_template = get_messages_formatter_type(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 = ""
for output in stream:
outputs += output
yield outputs
description = """<p><center>
<a href="https://huggingface.co/mattshumer/Reflection-Llama-3.1-70B" target="_blank">[Reflection Llama 3.1 70B Model Page]</a>
<a href="https://huggingface.co/bartowski/Reflection-Llama-3.1-70B-GGUF" target="_blank">[70B Model GGUF]</a>
</center></p>
"""
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Dropdown([
"Reflection-Llama-3.1-70B-Q3_K_M.gguf"
],
value="Reflection-Llama-3.1-70B-Q3_K_M.gguf",
label="Model"
),
gr.Textbox(value="You are a world-class AI system, capable of complex reasoning and reflection. Reason through the query inside <thinking> tags, and then provide your final response inside <output> tags. If you detect that you made a mistake in your reasoning at any point, correct yourself inside <reflection> tags.", label="System message"),
gr.Slider(minimum=1, maximum=8192, 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",
),
],
theme=gr.themes.Soft(primary_hue="violet", secondary_hue="violet", neutral_hue="gray",font=[gr.themes.GoogleFont("Exo"), "ui-sans-serif", "system-ui", "sans-serif"]).set(
body_background_fill_dark="#16141c",
block_background_fill_dark="#16141c",
block_border_width="1px",
block_title_background_fill_dark="#1e1c26",
input_background_fill_dark="#292733",
button_secondary_background_fill_dark="#24212b",
border_color_accent_dark="#343140",
border_color_primary_dark="#343140",
background_fill_secondary_dark="#16141c",
color_accent_soft_dark="transparent",
code_background_fill_dark="#292733",
),
retry_btn="Retry",
undo_btn="Undo",
clear_btn="Clear",
submit_btn="Send",
title="Reflection Llama-3.1 70B",
description=description,
chatbot=gr.Chatbot(
scale=1,
likeable=False,
show_copy_button=True
)
)
if __name__ == "__main__":
demo.launch() |