Update app.py

app.py

@@ -9,31 +9,27 @@ client1 = InferenceClient(api_key=os.getenv("HF_API_TOKEN_DIET"))
 
 # 1. Function to identify dish from image
 def identify_dish(image_bytes):
-  try 
-    encoded_image = base64.b64encode(image_bytes).decode("utf-8")
-    dish_name = ""
-  except Exception:
-        st.error("Invalid image format. Please upload a valid JPEG, PNG, or GIF image.")
-        return None
-
-    for message in client.chat_completion(
-        model="meta-llama/Llama-3.2-11B-Vision-Instruct",
-        messages=[
-            {
-                "role": "You are a highly specialized food identification AI with extensive knowledge of global cuisines. Your sole task is to accurately identify dishes from images. Adhere strictly to these guidelines:\n1. Analyze the image thoroughly, focusing on ingredients, presentation, and cultural context.\n2. Provide ONLY the name of the main dish or dishes visible. Do not list individual ingredients or components.\n3. Use the most specific and widely recognized name for the dish.\n4. If multiple distinct dishes are present, list them separated by commas.\n5. If you cannot identify a dish with high confidence (>90%), respond with 'Unidentified dish'.\n6. Do not provide any explanations, descriptions, or additional commentary.\n7. Respond in a concise, list-like format.\nYour response should contain nothing but the dish name(s) or 'Unidentified dish'.",
-                "content": [
-                    {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}" }},
-                    {"type": "text", "text": "Identify the dishes in the image and return only the names of the dishes."},
-                ],
+    try:
+        encoded_image = base64.b64encode(image_bytes).decode("utf-8")
+        dish_name = ""
+
+        response = client.chat(
+            model="meta-llama/Llama-3.2-11B-Vision-Instruct",
+            inputs={
+                "image": f"data:image/jpeg;base64,{encoded_image}",
+                "instruction": (
+                    "Identify the dishes in the image and return only the names "
+                    "of the dishes. If not identifiable, respond with 'Unidentified dish'."
+                ),
             }
-        ],
-        max_tokens=70,
-        stream=True,
-    ):
-        if message.choices[0].delta.content:
-            dish_name += message.choices[0].delta.content
+        )
 
-    return dish_name.strip()
+        dish_name = response.get("generated_text", "").strip()
+        return dish_name if dish_name else "Unidentified dish"
+
+    except Exception as e:
+        st.error(f"Error processing the image: {e}")
+        return None
 
 # 2. Function to get user inputs and calculate daily caloric needs
 def calculate_metrics(age, gender, height_cm, weight_kg, weight_goal, activity_level, time_frame_months):
@@ -92,15 +88,14 @@ def generate_diet_plan(dish_name, calorie_intake_per_day, goal):
 
     Provide the response in the following format:
     1. Dish assessment (e.g., "The dish {dish_name} is suitable for your goal" or "The dish {dish_name} is not suitable for your goal, as it is too high in calories for weight goal").
-    2. Suggest an Indian diet plan that stays near to the {calorie_intake_per_day}. For each meal (morning, lunch, evening), list the dish name, calorie count, and ingredients required to make it.And Make it with in 700 Tokens.
+    2. Suggest an Indian diet plan that stays near to the {calorie_intake_per_day}. For each meal (morning, lunch, evening), list the dish name, calorie count, and ingredients required to make it.
     """
-    response = client1.chat_completion(
+    response = client1.chat(
         model="meta-llama/Meta-Llama-3-8B-Instruct",
-        messages=[{"role": "You are a certified Dietitian with 20 years of Experience", "content": user_input}],
-        max_tokens=700
+        inputs=user_input
     )
 
-    return response.choices[0].message.content
+    return response.get("generated_text", "No response received.")
 
 # Streamlit App Title
 st.title("AI Diet Planner")
@@ -172,7 +167,7 @@ elif menu == "User Guide":
     3. **Submit**: Click the submit button to receive the results.
     
     ### Features:
-    - **Dish Identification**: The app identifies dishes based on the uploaded image.
-    - **Metric Calculation**: Calculate BMI, BMR, TDEE, and daily caloric needs based on your personal information.
-    - **Personalized Diet Plan**: Get a customized diet plan based on the dish identified and your weight goal.
+    - **Dish Identification**: Identifies dishes from uploaded images using advanced AI models.
+    - **Health Metrics**: Calculates BMI, BMR, and TDEE based on user inputs.
+    - **Diet Plan Generation**: Provides a tailored Indian diet plan.
     """)