Create api.py

api.py

@@ -0,0 +1,19 @@
+from fastapi import FastAPI
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+app = FastAPI()
+
+# ✅ Load Model
+model_path = "fine_tuned_medical_llama2"
+model = AutoModelForCausalLM.from_pretrained(model_path)
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+
+@app.post("/predict")
+def predict(query: str):
+    inputs = tokenizer(query, return_tensors="pt", padding=True, truncation=True)
+    with torch.no_grad():
+        outputs = model.generate(**inputs, max_length=200)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return {"response": response}
+