| import subprocess, sys, importlib |
|
|
| def ensure_deps(): |
| """Install missing dependencies at startup.""" |
| needed = { |
| "transformers": "transformers>=4.50.0", |
| "bitsandbytes": "bitsandbytes>=0.45.0", |
| "accelerate": "accelerate>=1.5.0", |
| } |
| missing = [pkg for mod, pkg in needed.items() if importlib.util.find_spec(mod) is None] |
| if missing: |
| print(f"📦 Installiere fehlende Dependencies: {missing}") |
| subprocess.check_call([sys.executable, "-m", "pip", "install", "--no-cache-dir"] + missing) |
| print("✅ Dependencies installiert!") |
|
|
| ensure_deps() |
|
|
| import spaces |
| import torch |
| from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig |
| import gradio as gr |
| import time |
|
|
| |
| MODEL_ID = "Qwen/Qwen3-Coder-7B-A3B-Instruct" |
| MAX_TOKENS = 4096 |
| DEFAULT_TEMP = 0.6 |
| DEFAULT_SYSTEM = "You are Qwen Coder Boosted, an expert coding assistant. Generate clean, working code. Always show complete files with [FILE:filename] markers." |
|
|
| print("🚀 Lade Modell...") |
| bnb_config = BitsAndBytesConfig( |
| load_in_4bit=True, |
| bnb_4bit_compute_dtype=torch.bfloat16, |
| bnb_4bit_use_double_quant=True, |
| bnb_4bit_quant_type="nf4", |
| ) |
|
|
| tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True) |
| model = AutoModelForCausalLM.from_pretrained( |
| MODEL_ID, |
| quantization_config=bnb_config, |
| device_map="auto", |
| trust_remote_code=True, |
| torch_dtype=torch.bfloat16, |
| attn_implementation="eager", |
| ) |
| print("✅ Modell geladen!") |
|
|
|
|
| |
| @spaces.GPU(duration=240) |
| def generate_response(messages, temperature, max_tokens): |
| """Generate a response from the model. GPU is real inside this function.""" |
| text = tokenizer.apply_chat_template( |
| messages, tokenize=False, add_generation_prompt=True |
| ) |
| inputs = tokenizer([text], return_tensors="pt").to(model.device) |
|
|
| with torch.no_grad(): |
| outputs = model.generate( |
| **inputs, |
| max_new_tokens=max_tokens, |
| temperature=temperature, |
| do_sample=True, |
| top_p=0.9, |
| repetition_penalty=1.05, |
| pad_token_id=tokenizer.eos_token_id, |
| ) |
|
|
| response = tokenizer.decode( |
| outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True |
| ) |
| return response |
|
|
|
|
| |
| def chat(message, history, system_prompt, temperature): |
| """Handle a chat turn. Builds messages, calls GPU function, returns updated history.""" |
| if not message.strip(): |
| return history |
|
|
| messages = [] |
| if system_prompt: |
| messages.append({"role": "system", "content": system_prompt}) |
| for user_msg, assistant_msg in history: |
| if user_msg: |
| messages.append({"role": "user", "content": user_msg}) |
| if assistant_msg: |
| messages.append({"role": "assistant", "content": assistant_msg}) |
| messages.append({"role": "user", "content": message}) |
|
|
| response = generate_response(messages, temperature, MAX_TOKENS) |
| history.append((message, response)) |
| return history |
|
|
|
|
| |
| with gr.Blocks( |
| title="Qwen Coder Boosted", |
| ) as demo: |
| gr.Markdown(""" |
| # 🚀 Qwen Coder Boosted |
| **Qwen3-Coder-30B-A3B (4-bit) auf Zero GPU** – 48 GB shared VRAM, PRO-Quota |
| """) |
|
|
| with gr.Row(): |
| with gr.Column(scale=1): |
| system_prompt = gr.Textbox( |
| label="⚙️ System Prompt", |
| value=DEFAULT_SYSTEM, |
| lines=3, |
| ) |
| temperature = gr.Slider( |
| label="🌡️ Temperature", |
| minimum=0.1, |
| maximum=1.5, |
| value=DEFAULT_TEMP, |
| step=0.05, |
| ) |
| clear_btn = gr.Button("🗑️ Chat leeren", variant="secondary") |
|
|
| with gr.Column(scale=3): |
| chatbot = gr.Chatbot( |
| label="💬 Chat", |
| height=550, |
| ) |
|
|
| with gr.Row(): |
| msg = gr.Textbox( |
| label="Deine Nachricht", |
| placeholder="Schreib einen Prompt... z.B. 'Baue eine To-Do-App mit HTML/CSS/JS'", |
| scale=8, |
| container=True, |
| ) |
| submit = gr.Button("📤 Senden", variant="primary", scale=1) |
|
|
| gr.Markdown(""" |
| --- |
| ### 💡 Info |
| - **Modell:** Qwen3-Coder-30B-A3B (4-bit, ~15 GB VRAM) |
| - **Zero GPU:** 48 GB shared, PRO = 40 Min/Tag inklusive |
| - **Max Tokens:** 32K (hardcodiert) |
| - **Temperature:** 0.6 (Standard für Coding) |
| """) |
|
|
| submit.click( |
| fn=chat, |
| inputs=[msg, chatbot, system_prompt, temperature], |
| outputs=[chatbot], |
| ).then( |
| fn=lambda: "", |
| outputs=[msg], |
| ) |
|
|
| msg.submit( |
| fn=chat, |
| inputs=[msg, chatbot, system_prompt, temperature], |
| outputs=[chatbot], |
| ).then( |
| fn=lambda: "", |
| outputs=[msg], |
| ) |
|
|
| clear_btn.click(fn=lambda: None, outputs=[chatbot]) |
|
|
| if __name__ == "__main__": |
| demo.launch(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="indigo")) |
|
|
