| import re |
| import gradio as gr |
| from huggingface_hub import hf_hub_download |
| from llama_cpp import Llama |
|
|
| print("Downloading model...") |
| model_path = hf_hub_download( |
| repo_id="Jackrong/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2-GGUF", |
| filename="Qwen3.5-9B.Q4_K_M.gguf", |
| ) |
| print(f"Model: {model_path}") |
|
|
| print("Loading model...") |
| llm = Llama( |
| model_path=model_path, |
| n_ctx=2048, |
| n_threads=2, |
| n_batch=256, |
| verbose=False, |
| ) |
| print("Model loaded!") |
|
|
| def strip_think_tags(text): |
| return re.sub(r"<think>.*?</think>\s*", "", text, flags=re.DOTALL).strip() |
|
|
| def chat(message, history, system_prompt, max_tokens, temperature, show_thinking): |
| messages = [] |
| if system_prompt.strip(): |
| messages.append({"role": "system", "content": system_prompt.strip()}) |
| for h in history[-4:]: |
| if h["role"] == "user": |
| messages.append({"role": "user", "content": h["content"]}) |
| elif h["role"] == "assistant": |
| messages.append({"role": "assistant", "content": h["content"]}) |
| messages.append({"role": "user", "content": message}) |
|
|
| try: |
| response = llm.create_chat_completion( |
| messages=messages, |
| max_tokens=int(max_tokens), |
| temperature=float(temperature), |
| stream=True, |
| ) |
| partial = "" |
| for chunk in response: |
| delta = chunk["choices"][0]["delta"].get("content", "") |
| partial += delta |
| if show_thinking: |
| yield partial |
| else: |
| yield strip_think_tags(partial) |
| except Exception as e: |
| yield f"Error: {str(e)}" |
|
|
| with gr.Blocks(title="Qwen3.5-9B Claude Reasoning") as demo: |
| gr.Markdown("# Qwen3.5-9B Claude 4.6 Opus Reasoning v2\nCPU inference - response ကြာနိုင်ပါတယ်") |
| system_prompt = gr.Textbox(label="System Prompt", value="You are a helpful assistant. Respond in the same language the user uses.", lines=2) |
| with gr.Row(): |
| max_tokens = gr.Slider(64, 2048, 512, step=64, label="Max Tokens") |
| temperature = gr.Slider(0.1, 1.5, 0.7, step=0.1, label="Temperature") |
| show_thinking = gr.Checkbox(label="Show thinking", value=False) |
| gr.ChatInterface(fn=chat, additional_inputs=[system_prompt, max_tokens, temperature, show_thinking]) |
|
|
| demo.launch(server_name="0.0.0.0", server_port=7860) |