test app

app.py

@@ -1,5 +1,12 @@
 import gradio as gr
 
+# Load model directly
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the LoRA model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("ID2223JR/lora_model")
+model = AutoModelForCausalLM.from_pretrained("ID2223JR/lora_model")
+
 # Data storage
 ingredients_list = []
 
@@ -7,7 +14,7 @@ ingredients_list = []
 # Function to add ingredient
 def add_ingredient(ingredient, quantity):
     if ingredient and quantity > 0:
-        ingredients_list.append(f"{ingredient}: {quantity} grams")
+        ingredients_list.append(f"{ingredient}, {quantity} grams")
     return (
         "\n".join(ingredients_list),
         gr.update(value="", interactive=True),
@@ -22,6 +29,25 @@ def validate_inputs(ingredient, quantity):
     return gr.update(interactive=False)
 
 
+# Function to handle model submission
+def submit_to_model():
+    if not ingredients_list:
+        return "Ingredients list is empty! Please add ingredients first."
+
+    # Join ingredients into a single prompt
+    prompt = f"Using the following ingredients, suggest a recipe:\n\n" + "\n".join(
+        ingredients_list
+    )
+
+    # Tokenize and pass the prompt to the model
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(**inputs, max_new_tokens=100)
+
+    # Decode the model output
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+
 # App
 def app():
     with gr.Blocks() as demo:
@@ -34,6 +60,12 @@ def app():
         add_button = gr.Button("Add Ingredient", interactive=False)
         output = gr.Textbox(label="Ingredients List", lines=10, interactive=False)
 
+        with gr.Row():
+            submit_button = gr.Button("Submit")
+            model_output = gr.Textbox(
+                label="Recipe Suggestion", lines=10, interactive=False
+            )
+
         # Validate inputs
         ingredient_input.change(
             validate_inputs, [ingredient_input, quantity_input], add_button
@@ -49,6 +81,13 @@ def app():
             [output, ingredient_input, quantity_input],
         )
 
+        # Submit to model logic
+        submit_button.click(
+            submit_to_model,
+            inputs=None,  # No inputs required as it uses the global ingredients_list
+            outputs=model_output,
+        )
+
     return demo