Update app.py

app.py

@@ -1,8 +1,39 @@
 from fastapi import FastAPI
+from pydantic import BaseModel
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
 app = FastAPI()
 
+MODEL_NAME = "BlackGoku7/deepseek-ai-DeepSeek-R1-Distill-Qwen-14B"
+
+# Load tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME,
+    device_map="auto",
+    torch_dtype=torch.bfloat16,  # Or torch.float16 if your Space supports it
+    trust_remote_code=True
+)
+model.eval()
+
+class Prompt(BaseModel):
+    text: str
+    max_new_tokens: int = 200
+
 @app.get("/")
-def greet_json():
-    return {"Hello": "World!"}
-    
+def root():
+    return {"message": "POST to /generate with {'text': 'your prompt'}"}
+
+@app.post("/generate")
+def generate(prompt: Prompt):
+    inputs = tokenizer(prompt.text, return_tensors="pt").to(model.device)
+    output = model.generate(
+        **inputs,
+        max_new_tokens=prompt.max_new_tokens,
+        do_sample=True,
+        temperature=0.7,
+        top_p=0.9,
+    )
+    decoded = tokenizer.decode(output[0], skip_special_tokens=True)
+    return {"response": decoded}