Create inference.py

inference.py

@@ -0,0 +1,46 @@
+# inference.py
+# ==============================
+# Single inference entry point
+# Handles Base / Core / Skill transparently
+# ==============================
+
+import torch
+from model_loader import load_model
+from router import route_skill
+import config
+
+
+def generate_response(prompt: str):
+    """
+    Main inference function.
+    Decides skill softly, then generates response.
+    """
+
+    # Decide skill (or None)
+    skill = route_skill(prompt)
+
+    # Load model (Base + optional Core + optional Skill)
+    model, tokenizer = load_model(skill)
+
+    # Prepare input
+    inputs = tokenizer(
+        prompt,
+        return_tensors="pt"
+    ).to(model.device)
+
+    # Generate
+    with torch.no_grad():
+        output = model.generate(
+            **inputs,
+            max_new_tokens=config.MAX_NEW_TOKENS,
+            temperature=config.TEMPERATURE,
+            top_p=config.TOP_P,
+        )
+
+    # Decode
+    response = tokenizer.decode(
+        output[0][inputs["input_ids"].shape[-1]:],
+        skip_special_tokens=True
+    )
+
+    return response.strip()