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import json | |
import spaces | |
import subprocess | |
import gradio as gr | |
from llama_cpp import Llama | |
from llama_cpp_agent.chat_history.messages import Roles | |
from llama_cpp_agent.chat_history import BasicChatHistory | |
from llama_cpp_agent.providers import LlamaCppPythonProvider | |
from llama_cpp_agent import LlamaCppAgent, MessagesFormatterType | |
from huggingface_hub import InferenceClient | |
from huggingface_hub import hf_hub_download | |
""" | |
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference | |
""" | |
SYSTEM = "You are a helpful math assistant. You should always provide your answer in Chinese." | |
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") | |
hf_hub_download( | |
repo_id="bartowski/Qwen2.5-Math-7B-Instruct-GGUF", | |
filename="Qwen2.5-Math-7B-Instruct-Q8_0.gguf", | |
local_dir="./models" | |
) | |
llm = Llama( | |
model_path="models/Qwen2.5-Math-7B-Instruct-Q8_0.gguf", | |
flash_attn=True, | |
n_ctx=8192, | |
n_batch=1024, | |
chat_format="chatml" | |
) | |
provider = LlamaCppPythonProvider(llm) | |
def respond( | |
message, | |
history: list[tuple[str, str]], | |
system_message, | |
max_tokens, | |
temperature, | |
top_p, | |
): | |
messages = [{"role": "system", "content": system_message}] | |
for val in history: | |
if val[0]: | |
messages.append({"role": "user", "content": val[0]}) | |
if val[1]: | |
messages.append({"role": "assistant", "content": val[1]}) | |
messages.append({"role": "user", "content": message}) | |
response = "" | |
response = llm.create_chat_completion( | |
messages=messages, | |
stream=True, | |
max_tokens=max_tokens, | |
temperature=temperature, | |
top_p=top_p | |
) | |
message_repl = "" | |
for chunk in response: | |
if len(chunk['choices'][0]["delta"]) != 0 and "content" in chunk['choices'][0]["delta"]: | |
message_repl = message_repl + \ | |
chunk['choices'][0]["delta"]["content"] | |
yield message_repl | |
""" | |
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface | |
""" | |
demo = gr.ChatInterface( | |
respond, | |
additional_inputs=[ | |
gr.Textbox(value="You are a friendly Chatbot.", 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() |