Create app.py

app.py

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+import os
+import gradio as gr
+import google.generativeai as genai
+
+# Configure the Gemini API with environment variable
+GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
+if not GOOGLE_API_KEY:
+    raise ValueError("GOOGLE_API_KEY environment variable not set. Please configure it in the Hugging Face Space settings.")
+
+genai.configure(api_key=GOOGLE_API_KEY)
+
+# Use Gemini 1.5 Flash model
+model = genai.GenerativeModel('gemini-1.5-flash-latest')
+
+def predict_banknote_authenticity(security_thread, watermark, microtext, ink_color_shift, paper_texture, printing_quality, holographic_features, serial_number, uv_features, edge_smoothness):
+    # Validate inputs
+    inputs = [security_thread, watermark, microtext, ink_color_shift, paper_texture, printing_quality, holographic_features, serial_number, uv_features, edge_smoothness]
+    if not all(inputs):
+        return "Error: Please provide answers to all questions."
+    
+    # Format user responses
+    user_data = f"""
+    Security Thread: {security_thread}
+    Watermark: {watermark}
+    Microtext: {microtext}
+    Ink Color Shift: {ink_color_shift}
+    Paper Texture: {paper_texture}
+    Printing Quality: {printing_quality}
+    Holographic Features: {holographic_features}
+    Serial Number Consistency: {serial_number}
+    UV Features: {uv_features}
+    Edge Smoothness: {edge_smoothness}
+    """
+
+    prompt = f"""
+    You are an assistant predicting whether a banknote is authentic or counterfeit based on user responses to 10 questions about its physical and visual characteristics. 
+    Classify the banknote as "Authentic" or "Fake" and provide a brief reason for your classification.
+    Return the response in this format:
+    
+    Prediction: [Authentic / Fake]
+    Reason: [Brief explanation]
+
+    Examples:
+    User Data:
+    Security Thread: Visible and shifts color
+    Watermark: Clear and visible when held to light
+    Microtext: Legible under magnification
+    Ink Color Shift: Changes color when tilted
+    Paper Texture: Crisp and unique
+    Printing Quality: Sharp and clear
+    Holographic Features: Present and changes with angle
+    Serial Number Consistency: Uniform and aligned
+    UV Features: Glows correctly under UV light
+    Edge Smoothness: Smooth and precise
+    Prediction: Authentic
+    Reason: The presence of a color-shifting security thread, clear watermark, legible microtext, color-changing ink, crisp paper texture, sharp printing, holographic features, consistent serial numbers, correct UV glow, and smooth edges are strong indicators of an authentic banknote.
+
+    User Data:
+    Security Thread: Not visible
+    Watermark: Absent or blurry
+    Microtext: Illegible or absent
+    Ink Color Shift: No color change
+    Paper Texture: Rough or ordinary
+    Printing Quality: Blurry or uneven
+    Holographic Features: Absent
+    Serial Number Consistency: Misaligned or inconsistent
+    UV Features: No glow or incorrect glow
+    Edge Smoothness: Rough or irregular
+    Prediction: Fake
+    Reason: The absence of a security thread, watermark, microtext, color-shifting ink, and holographic features, along with rough paper, blurry printing, inconsistent serial numbers, incorrect UV response, and irregular edges, strongly suggest a counterfeit banknote.
+
+    User Data:
+    Security Thread: Visible but no color shift
+    Watermark: Faintly visible
+    Microtext: Partially legible
+    Ink Color Shift: No color change
+    Paper Texture: Crisp and unique
+    Printing Quality: Sharp and clear
+    Holographic Features: Absent
+    Serial Number Consistency: Uniform and aligned
+    UV Features: Glows correctly under UV light
+    Edge Smoothness: Smooth and precise
+    Prediction: Fake
+    Reason: While some features like paper texture, printing quality, serial number consistency, UV glow, and edge smoothness are present, the lack of a color-shifting security thread, faint watermark, partially legible microtext, absent holographic features, and no color-shifting ink suggest a counterfeit banknote.
+
+    User Data:
+    {user_data}
+    Prediction:
+    Reason:
+    """
+
+    try:
+        response = model.generate_content(prompt)
+        return response.text.strip()
+    except Exception as e:
+        return f"Error: {str(e)}\nTip: Ensure your API key is valid at https://aistudio.google.com/"
+
+# Define Gradio interface
+iface = gr.Interface(
+    fn=predict_banknote_authenticity,
+    inputs=[
+        gr.Dropdown(choices=["Visible and shifts color", "Visible but no color shift", "Not visible"], label="1. Is the security thread visible and does it shift color when tilted?"),
+        gr.Dropdown(choices=["Clear and visible when held to light", "Faintly visible", "Absent or blurry"], label="2. Is there a clear watermark visible when held to light?"),
+        gr.Dropdown(choices=["Legible under magnification", "Partially legible", "Illegible or absent"], label="3. Is microtext legible under magnification?"),
+        gr.Dropdown(choices=["Changes color when tilted", "No color change"], label="4. Does the ink in specific areas (e.g., denomination) change color when tilted?"),
+        gr.Dropdown(choices=["Crisp and unique", "Rough or ordinary"], label="5. Does the paper have a crisp, unique texture?"),
+        gr.Dropdown(choices=["Sharp and clear", "Blurry or uneven"], label="6. Is the printing quality sharp and clear?"),
+        gr.Dropdown(choices=["Present and changes with angle", "Absent"], label="7. Are holographic features present and do they change with angle?"),
+        gr.Dropdown(choices=["Uniform and aligned", "Misaligned or inconsistent"], label="8. Are the serial numbers uniform and aligned?"),
+        gr.Dropdown(choices=["Glows correctly under UV light", "No glow or incorrect glow"], label="9. Do specific elements glow correctly under UV light?"),
+        gr.Dropdown(choices=["Smooth and precise", "Rough or irregular"], label="10. Are the edges of the note smooth and precise?")
+    ],
+    outputs=gr.Textbox(label="Banknote Authentication Prediction"),
+    title="Banknote Authenticity Predictor",
+    description="Answer 10 questions about a banknote's characteristics to predict whether it is authentic or counterfeit using the Gemini API. Set your GOOGLE_API_KEY in the Hugging Face Space settings. Note: This is for demonstration purposes only and not for real-world banking use."
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    iface.launch()