Upload app.py

app.py

@@ -0,0 +1,82 @@
+import gradio as gr
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+# ── Config ──────────────────────────────────────────────────────────────
+BASE_MODEL    = "Qwen/Qwen2.5-Coder-0.5B-Instruct"
+ADAPTER_REPO  = "TRUFELLINI/qwen2.5-coder-0.5b-bugfix"  
+
+SYSTEM_PROMPT = """You are a Python bug fixing assistant.
+Rules:
+- Make the minimal change possible
+- Do not rewrite unrelated code
+- Return only fixed code
+- Preserve original behavior unless required"""
+
+# ── Load model (runs once when Space starts) ─────────────────────────────
+print("Loading base model...")
+tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL)
+model = AutoModelForCausalLM.from_pretrained(
+    BASE_MODEL,
+    torch_dtype=torch.float32,  # CPU — float32
+    device_map="cpu",
+)
+
+print("Loading LoRA adapter...")
+model = PeftModel.from_pretrained(model, ADAPTER_REPO)
+model.eval()
+print("Model ready.")
+
+# ── Inference ────────────────────────────────────────────────────────────
+def fix_bug(buggy_code, max_new_tokens=400):
+    if not buggy_code.strip():
+        return "Paste some buggy Python code above."
+
+    messages = [
+        {"role": "system", "content": SYSTEM_PROMPT},
+        {"role": "user",   "content": f"Fix the bug:\n{buggy_code}"}
+    ]
+    text   = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    inputs = tokenizer(text, return_tensors="pt")
+
+    with torch.no_grad():
+        output = model.generate(
+            **inputs,
+            max_new_tokens = max_new_tokens,
+            temperature    = 0.1,
+            do_sample      = True,
+            pad_token_id   = tokenizer.eos_token_id,
+        )
+    new_tokens = output[0][inputs["input_ids"].shape[1]:]
+    return tokenizer.decode(new_tokens, skip_special_tokens=True)
+
+# ── UI ───────────────────────────────────────────────────────────────────
+EXAMPLES = [
+    ["def calculate_average(numbers):\n    total = 0\n    for n in numbers:\n        total += n\n    return total / len(numbers)"],
+    ["def add_item(item, items=[]):\n    items.append(item)\n    return items"],
+    ["def sum_list(nums):\n    total = 0\n    for i in range(len(nums)+1):\n        total += nums[i]\n    return total"],
+    ["def first_element(lst):\n    return lst[1]"],
+]
+
+demo = gr.Interface(
+    fn          = fix_bug,
+    inputs      = gr.Code(
+                    label       = "Paste buggy Python code here",
+                    language    = "python",
+                    lines       = 14,
+                  ),
+    outputs     = gr.Code(
+                    label       = "Fixed code",
+                    language    = "python",
+                  ),
+    title       = "🐛 Python Bug Fixer",
+    description = """**Qwen2.5-Coder 0.5B fine-tuned on real buggy→fixed Python pairs.**  
+Makes minimal, correct fixes — not rewrites. Trained using QLoRA on [alexjercan/bugnet](https://huggingface.co/datasets/alexjercan/bugnet).  
+[[Model]](https://huggingface.co/your-username/qwen2.5-coder-0.5b-bugfix) · [[GitHub]](https://github.com/your-username/python-bugfix-llm)""",
+    examples    = EXAMPLES,
+    theme       = gr.themes.Soft(),
+    cache_examples = False,
+)
+
+demo.launch()