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import spaces
import json
import subprocess
from llama_cpp import Llama
from llama_cpp_agent import LlamaCppAgent
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
hf_hub_download(
repo_id="PartAI/Dorna-Llama3-8B-Instruct-GGUF",
filename="dorna-llama3-8b-instruct.Q2_K.gguf",
local_dir = "./models"
)
hf_hub_download(
repo_id="PartAI/Dorna-Llama3-8B-Instruct-GGUF",
filename="dorna-llama3-8b-instruct.Q4_0.gguf",
local_dir = "./models"
)
css = """
.message-row {
justify-content: space-evenly !important;
}
.message-bubble-border {
border-radius: 6px !important;
}
.dark.message-bubble-border {
border-color: #343140 !important;
}
.dark.user {
background: #1e1c26 !important;
}
.dark.assistant.dark, .dark.pending.dark {
background: #16141c !important;
}
"""
def get_messages_formatter_type(model_name):
from llama_cpp_agent import MessagesFormatterType
return MessagesFormatterType.CHATML
@spaces.GPU(duration=120)
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
top_k,
repeat_penalty,
model,
):
chat_template = get_messages_formatter_type(model)
llm = Llama(
model_path=f"models/{model}",
flash_attn=True,
n_threads=40,
n_gpu_layers=81,
n_batch=1024,
n_ctx=8192,
)
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
PLACEHOLDER = """
<div class="message-bubble-border" style="display:flex; max-width: 600px; border-radius: 8px; box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1); backdrop-filter: blur(10px);">
<div style="padding: .5rem 1.5rem;">
<h2 style="text-align: left; font-size: 1.5rem; font-weight: 700; margin-bottom: 0.5rem;">Chat with Dorna-Llama3 8B </h2>
<p style="text-align: left; font-size: 16px; line-height: 1.5; margin-bottom: 15px;">You can try different models.<br>Running on CPU from Hugging Face.</p>
</div>
</div>
"""
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="You are a helpful assistant.", 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,
step=0.1,
label="Repetition penalty",
),
gr.Dropdown([
'dorna-llama3-8b-instruct.Q2_K.gguf',
'dorna-llama3-8b-instruct.Q4_0.gguf',
],
value="dorna-llama3-8b-instruct.Q2_K.gguf",
label="Model"
),
],
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_primary_dark="#343140",
background_fill_secondary_dark="#16141c",
color_accent_soft_dark="transparent"
),
css=css,
retry_btn="Retry",
undo_btn="Undo",
clear_btn="Clear",
submit_btn="Send",
description="Chat with Dorna-Llama3 8B (2-bit GGUF)",
chatbot=gr.Chatbot(scale=1, placeholder=PLACEHOLDER)
)
if __name__ == "__main__":
demo.launch() |