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# Standard library imports
import os
import threading
# Third-party imports
import gradio as gr
from peft import PeftModel
from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer
HF_TOKEN = os.getenv("HF_TOKEN")
tokenizer = AutoTokenizer.from_pretrained(
"bunyaminergen/Qwen2.5-Coder-1.5B-Instruct-Reasoning",
use_auth_token=HF_TOKEN,
trust_remote_code=True
)
base_model = AutoModelForCausalLM.from_pretrained(
"Qwen/Qwen2.5-Coder-1.5B-Instruct",
device_map="auto",
torch_dtype="auto",
use_auth_token=HF_TOKEN
)
model = PeftModel.from_pretrained(
base_model,
"bunyaminergen/Qwen2.5-Coder-1.5B-Instruct-Reasoning",
use_auth_token=HF_TOKEN
)
model.eval()
def respond(
message: str,
history: list[tuple[str, str]],
system_message: str,
max_tokens: int,
temperature: float,
top_p: float,
):
messages = [{"role": "system", "content": system_message}]
for u, a in history:
if u:
messages.append({"role": "user", "content": u})
if a:
messages.append({"role": "assistant", "content": a})
messages.append({"role": "user", "content": message})
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
streamer = TextIteratorStreamer(
tokenizer,
timeout=10.0,
skip_prompt=True,
skip_special_tokens=True
)
generation_kwargs = {
**inputs,
"max_new_tokens": max_tokens,
"temperature": temperature,
"top_p": top_p,
"streamer": streamer,
}
thread = threading.Thread(target=model.generate, kwargs=generation_kwargs)
thread.start()
output = ""
for chunk in streamer:
output += chunk
yield output
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="You are a helpful coding assistant.", label="System message"),
gr.Slider(minimum=512, maximum=8192, value=2048, 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(share=True)
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