app.py and requirements.txt added

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+MODEL_NAME = "tiiuae/falcon-180B"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+    trust_remote_code=True
+)
+
+def improve_code(code: str) -> str:
+    prompt = (
+        "You are an expert code assistant.\n"
+        "Given the following code, suggest an improved version with clear comments and best practices.\n"
+        "Output only the improved code.\n\n"
+        f"Original code:\n{code}\n\nImproved code:"
+    )
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    with torch.no_grad():
+        outputs = model.generate(
+            input_ids=inputs["input_ids"],
+            attention_mask=inputs["attention_mask"],
+            max_new_tokens=512,
+            temperature=0.2,
+            top_p=0.9,
+            do_sample=True,
+            pad_token_id=tokenizer.eos_token_id
+        )
+    generated = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    improved = generated.split("Improved code:")[-1].strip()
+    return improved
+
+app = gr.Blocks()
+
+with app:
+    gr.Markdown("## Servidor MCP para mejora de código con Falcon 180B")
+    code_input = gr.Textbox(label="Código original", lines=15)
+    improve_btn = gr.Button("Mejorar código")
+    code_output = gr.Textbox(label="Código mejorado", lines=15)
+    improve_btn.click(improve_code, inputs=code_input, outputs=code_output)
+
+app.launch()

requirements.txt

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+gradio[mcp]
+transformers
+torch