Create app.py

app.py

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+import streamlit as st
+import google.generativeai as genai
+import os
+from PIL import Image
+
+# Placeholder for your Gemini API key - store securely!
+# st.secrets is the recommended way to manage secrets in Streamlit Cloud and Hugging Face Spaces
+GEMINI_API_KEY = st.secrets.get("GEMINI_API_KEY")
+
+if GEMINI_API_KEY:
+    genai.configure(api_key=GEMINI_API_KEY)
+    model = genai.GenerativeModel('gemini-pro')
+    vision_model = genai.GenerativeModel('gemini-pro-vision')
+else:
+    st.error("Please add your Gemini API key to the Streamlit secrets manager or environment variables.")
+    st.stop()
+
+def diagnose_text(text_input):
+    try:
+        response = model.generate_content(f"Analyze the following medical information and provide a potential diagnosis and risk assessment: {text_input}")
+        return response.text
+    except Exception as e:
+        return f"Error during diagnosis: {e}"
+
+def diagnose_image(image_file, text_prompt="Analyze this medical image for potential anomalies and provide a diagnosis:"):
+    try:
+        image = Image.open(image_file)
+        response = vision_model.generate_content([text_prompt, image])
+        return response.text
+    except Exception as e:
+        return f"Error during image analysis: {e}"
+
+def main():
+    st.title("Agentic AI for Automated Disease Diagnosis")
+    st.subheader("Powered by Google Gemini")
+
+    data_type = st.radio("Select Input Type:",)
+
+    if data_type == "Text Description":
+        text_input = st.text_area("Enter medical data or symptoms:", height=200)
+        if st.button("Diagnose"):
+            if text_input:
+                with st.spinner("Analyzing..."):
+                    diagnosis = diagnose_text(text_input)
+                    st.subheader("Potential Diagnosis and Risk Assessment:")
+                    st.write(diagnosis)
+            else:
+                st.warning("Please enter some medical data or symptoms.")
+
+    elif data_type == "Medical Image":
+        image_file = st.file_uploader("Upload a medical image (e.g., X-ray, CT scan, MRI):", type=["png", "jpg", "jpeg"])
+        text_prompt = st.text_input("Optional: Add a description or specific instructions for the image analysis:", "")
+        if st.button("Diagnose Image"):
+            if image_file:
+                with st.spinner("Analyzing image..."):
+                    diagnosis = diagnose_image(image_file, text_prompt)
+                    st.subheader("Potential Diagnosis based on Image:")
+                    st.write(diagnosis)
+                    st.image(image_file, caption="Uploaded Medical Image.", use_column_width=True)
+            else:
+                st.warning("Please upload a medical image.")
+
+    st.info("Disclaimer: This application provides potential diagnoses based on AI analysis and should not be considered a substitute for professional medical advice. Always consult with a qualified healthcare provider for any health concerns.")
+
+if __name__ == "__main__":
+    main()