Create app.py

app.py

@@ -0,0 +1,49 @@
+import gradio as gr
+import google.generativeai as genai
+
+# Configure Google Gemini API
+genai.configure(api_key="AIzaSyDBGF5y7WqDB0SO7-UO6yjshiEZN3Hpt3g")  # Replace with your API key
+
+# Function to get a response from the Google Gemini model
+def get_gemini_response(input_text):
+    model = genai.GenerativeModel('gemini-1.5-flash')
+
+    # Input prompt for extracting unarticulated needs and wants
+    input_prompt = f"""
+    From the following user story, extract the unarticulated needs and wants.
+    User story: {input_text}
+    
+    Needs are the unspoken requirements or desires the person might not have expressed directly. 
+    Wants are the things the person wishes for but didn't explicitly say.
+    
+    Needs and Wants:
+    """
+
+    # Generate the content based on text input
+    response = model.generate_content([input_text, input_prompt])
+    return response.text
+
+# Enhanced Gradio interface function with input validation
+def extract_needs_and_wants(user_story):
+    # Check if the input story is adequate (e.g., at least 20 characters or more than a few words)
+    if len(user_story.strip()) < 20 or len(user_story.split()) < 5:
+        return "Please provide a detailed user story with sufficient content for analysis."
+    
+    try:
+        # Process the input if it meets the criteria
+        return get_gemini_response(user_story)
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=extract_needs_and_wants,
+    inputs="text",
+    outputs="text",
+    title="Unarticulated Needs & Wants Extractor",
+    description="Enter a detailed user story to extract the unarticulated needs and wants using the Gemini model.",
+    examples=[["The user often speaks about wanting to improve their health but is hesitant to join a gym."]]
+)
+
+# Launch the Gradio app
+interface.launch()