|
import spaces |
|
import json |
|
import subprocess |
|
import gradio as gr |
|
from huggingface_hub import hf_hub_download |
|
|
|
subprocess.run('pip install llama-cpp-python==0.2.75 --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu124', shell=True) |
|
subprocess.run('pip install llama-cpp-agent==0.2.10', shell=True) |
|
|
|
hf_hub_download(repo_id="TheBloke/Mistral-7B-Instruct-v0.2-GGUF", filename="mistral-7b-instruct-v0.2.Q6_K.gguf", local_dir = "./models") |
|
|
|
@spaces.GPU(duration=120) |
|
def respond( |
|
message, |
|
history: list[tuple[str, str]], |
|
system_message, |
|
max_tokens, |
|
temperature, |
|
top_p, |
|
): |
|
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 |
|
|
|
llm = Llama( |
|
model_path="models/mistral-7b-instruct-v0.2.Q6_K.gguf", |
|
n_gpu_layers=33, |
|
) |
|
provider = LlamaCppPythonProvider(llm) |
|
|
|
agent = LlamaCppAgent( |
|
provider, |
|
system_prompt="You are a helpful assistant.", |
|
predefined_messages_formatter_type=MessagesFormatterType.MISTRAL, |
|
debug_output=True |
|
) |
|
|
|
settings = provider.get_provider_default_settings() |
|
settings.max_tokens = 2000 |
|
settings.stream = True |
|
|
|
messages = BasicChatHistory() |
|
print("history") |
|
print(history) |
|
|
|
for msn in history: |
|
user = { |
|
'role': Roles.user, |
|
'content': msn[0] |
|
} |
|
assistant = { |
|
'role': Roles.assistant, |
|
'content': msn[1] |
|
} |
|
print(user) |
|
print(assistant) |
|
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.Textbox(value="You are a helpful assistant.", label="System message"), |
|
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new 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 (nucleus sampling)", |
|
), |
|
], |
|
) |
|
|
|
if __name__ == "__main__": |
|
demo.launch() |
