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_tumor(headaches, neurological_symptoms, family_history, weight_loss, fatigue):
+    # Validate inputs
+    inputs = [headaches, neurological_symptoms, family_history, weight_loss, fatigue]
+    if not all(inputs):
+        return "Error: Please provide answers to all questions."
+    
+    # Format user responses
+    user_data = f"""
+    Persistent Headaches: {headaches}
+    Neurological Symptoms (seizures, vision/hearing changes, cognitive issues): {neurological_symptoms}
+    Family History of Cancer/Tumors: {family_history}
+    Unexplained Weight Loss: {weight_loss}
+    Persistent Fatigue: {fatigue}
+    """
+
+    prompt = f"""
+    You are a health assistant predicting the likelihood of a tumor (e.g., brain tumor) based on user responses to five health questions. 
+    Classify the risk as "Tumor Detected" or "No Tumor" and provide a brief reason for your classification.
+    Return the response in this format:
+    
+    Prediction: [Tumor Detected / No Tumor]
+    Reason: [Brief explanation]
+
+    Examples:
+    User Data:
+    Persistent Headaches: Frequent and severe
+    Neurological Symptoms (seizures, vision/hearing changes, cognitive issues): Yes
+    Family History of Cancer/Tumors: Yes
+    Unexplained Weight Loss: Yes
+    Persistent Fatigue: Yes
+    Prediction: Tumor Detected
+    Reason: Frequent severe headaches, neurological symptoms, family history, weight loss, and fatigue are strong indicators of a potential tumor.
+
+    User Data:
+    Persistent Headaches: None
+    Neurological Symptoms (seizures, vision/hearing changes, cognitive issues): No
+    Family History of Cancer/Tumors: No
+    Unexplained Weight Loss: No
+    Persistent Fatigue: No
+    Prediction: No Tumor
+    Reason: The absence of headaches, neurological symptoms, family history, weight loss, and fatigue suggests a low likelihood of a tumor.
+
+    User Data:
+    Persistent Headaches: Occasional and mild
+    Neurological Symptoms (seizures, vision/hearing changes, cognitive issues): No
+    Family History of Cancer/Tumors: Yes
+    Unexplained Weight Loss: No
+    Persistent Fatigue: Yes
+    Prediction: No Tumor
+    Reason: Mild headaches, no neurological symptoms, and no weight loss reduce the likelihood of a tumor, despite family history and fatigue.
+
+    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_tumor,
+    inputs=[
+        gr.Dropdown(choices=["Frequent and severe", "Occasional and mild", "None"], label="1. Do you experience persistent headaches?"),
+        gr.Dropdown(choices=["Yes", "No"], label="2. Do you have neurological symptoms (e.g., seizures, vision/hearing changes, cognitive issues)?"),
+        gr.Dropdown(choices=["Yes", "No"], label="3. Do you have a family history of cancer or tumors?"),
+        gr.Dropdown(choices=["Yes", "No"], label="4. Have you experienced unexplained weight loss?"),
+        gr.Dropdown(choices=["Yes", "No"], label="5. Do you experience persistent fatigue or weakness?")
+    ],
+    outputs=gr.Textbox(label="Tumor Detection Prediction"),
+    title="Tumor Risk Predictor",
+    description="Answer five health questions to predict the likelihood of a tumor using the Gemini API. Set your GOOGLE_API_KEY in the Hugging Face Space settings. Note: This is for demonstration purposes only and not a clinical tool."
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    iface.launch()