Update app.py

app.py

@@ -91,19 +91,17 @@ async def predict_image_and_nutrition(file: UploadFile = File(...)):
         # Initialize the InferenceClient with your token
         llm_client = InferenceClient(
             model=repo_id,
-            token=api_token[:-2],  # Pass the token here
+            token=api_token,
             timeout=120,
         )
-
         # Function to call the LLM
         def call_llm(inference_client: InferenceClient, prompt: str):
-            response = inference_client.post(
-                json={
-                    "inputs": prompt,
-                    "parameters": {"max_new_tokens": 500}
-                },
+            response = inference_client.text_generation(
+                prompt=prompt,
+                max_new_tokens=500,
+                temperature=0.7,  # optional
             )
-            return json.loads(response.decode())[0]["generated_text"]
+            return response
         
         # Use the prediction to generate nutrition information
         # prompt = f"Nutrition information (Calories, Protein, Carbohydrates, Dietary Fiber, Sugars, Fat, Sodium, Potassium, Vitamin C, Vitamin B6, Folate, Niacin, Pantothenic acid) for {prediction} in formatted list"