mian2

app.py

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+import gradio as gr
+from llama_cpp import Llama
+from huggingface_hub import hf_hub_download
+
+# --- SETTINGS ---
+# This is the Qwen3-VL 8B model (Quantized to fit in Free Space)
+REPO_ID = "Qwen/Qwen3-VL-8B-Instruct-GGUF" 
+FILENAME = "*q4_k_m.gguf" 
+
+print("⬇️ Downloading model... (This mimics 'ollama pull')")
+try:
+    model_path = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
+except:
+    # Fallback to Qwen2.5-VL if Qwen3 isn't fully indexed yet
+    print("⚠️ Qwen3 GGUF not found, falling back to Qwen2.5-VL")
+    model_path = hf_hub_download(repo_id="Qwen/Qwen2.5-VL-7B-Instruct-GGUF", filename="*q4_k_m.gguf")
+
+print("✅ Model downloaded!")
+
+# --- LOAD ENGINE ---
+# n_gpu_layers=0 forces CPU mode (Free Tier)
+llm = Llama(
+    model_path=model_path,
+    n_ctx=2048,       
+    n_gpu_layers=0,  
+    verbose=True
+)
+
+# --- CHAT UI ---
+def chat(message, history):
+    prompt = f"<|im_start|>user\n{message}<|im_end|>\n<|im_start|>assistant\n"
+    output = llm(prompt, max_tokens=512, stop=["<|im_end|>"], echo=False)
+    return output['choices'][0]['text']
+
+gr.ChatInterface(chat).launch(server_name="0.0.0.0", server_port=7860)