Update app.py

app.py

@@ -11,8 +11,13 @@ load_dotenv()
 genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
 
 # Function to process the image and get response from Gemini model
-def get_gemini_response(input_prompt, uploaded_file_path, query):
+def get_gemini_response(uploaded_file_path, query):
     try:
+        # Define input prompt
+        input_prompt = """
+        You are an expert in understanding invoices. You will receive input images as invoices and 
+        you will have to answer questions based on the input image.
+        """
         # Validate the image file path
         if not uploaded_file_path or not os.path.exists(uploaded_file_path):
             return "Please upload a valid image."
@@ -32,11 +37,6 @@ def get_gemini_response(input_prompt, uploaded_file_path, query):
     except Exception as e:
         return f"Error: {e}"
 
-# Define input prompt
-default_prompt = """
-You are an expert in understanding invoices. You will receive input images as invoices and 
-you will have to answer questions based on the input image.
-"""
 
 # Define Gradio interface
 with gr.Blocks() as invoice_extractor:
@@ -47,9 +47,6 @@ with gr.Blocks() as invoice_extractor:
         The system uses Google's Gemini model to extract and interpret the invoice details.
         """
     )
-
-    input_prompt = default_prompt
-    # gr.Textbox(label="Input Prompt", value=default_prompt, lines=2)
     image_input = gr.Image(label="Upload Invoice Image", type="filepath")  # Use type="filepath"
     query_input = gr.Textbox(label="Enter your query about the invoice", placeholder="e.g., What is the total amount?")
     output_response = gr.Textbox(label="Response", lines=5)
@@ -60,7 +57,7 @@ with gr.Blocks() as invoice_extractor:
     # Set the button to call the processing function
     submit_btn.click(
         get_gemini_response, 
-        inputs=[input_prompt, image_input, query_input],
+        inputs=[image_input, query_input],
         outputs=output_response
     )