Update app.py

app.py

@@ -1,59 +1,59 @@
 import streamlit as st
 from pubmed_rag import search_pubmed, fetch_pubmed_abstracts, summarize_text
 from image_pipeline import analyze_medical_image
-from models import query_medical_text
+from models import query_openai_text
+from config import OPENAI_DEFAULT_MODEL
 
 st.set_page_config(page_title="Advanced Medical AI", layout="wide")
 
-
 def main():
     st.title("Advanced Medical AI")
     st.sidebar.title("Features")
     task = st.sidebar.selectbox("Choose a task:", ["PubMed Q&A", "Medical Image Analysis"])
 
     if task == "PubMed Q&A":
-        # PubMed Q&A Section
+        # PubMed Question Answering
         st.subheader("PubMed Question Answering")
         query = st.text_input("Enter your medical question:", "What are the latest treatments for diabetes?")
         max_results = st.slider("Number of PubMed articles to retrieve:", 1, 10, 5)
 
         if st.button("Run Query"):
             with st.spinner("Searching PubMed..."):
+                # Step 1: Search PubMed
                 pmids = search_pubmed(query, max_results)
                 if not pmids:
                     st.error("No results found. Try another query.")
                     return
 
             with st.spinner("Fetching and summarizing abstracts..."):
+                # Step 2: Fetch abstracts
                 abstracts = fetch_pubmed_abstracts(pmids)
+                # Step 3: Summarize abstracts
                 summaries = {pmid: summarize_text(abstract) for pmid, abstract in abstracts.items()}
 
             st.subheader("PubMed Summaries")
             for pmid, summary in summaries.items():
                 st.write(f"**PMID {pmid}**: {summary}")
 
-            with st.spinner("Querying the medical reasoning model..."):
-                answer = query_medical_text(query)
+            with st.spinner("Querying OpenAI model..."):
+                # Step 4: Query OpenAI model with summarized abstracts
+                system_message = "You are a medical assistant with access to summarized PubMed abstracts."
+                user_message = f"Summarized articles: {summaries}\n\nQuestion: {query}"
+                answer = query_openai_text(system_message, user_message, OPENAI_DEFAULT_MODEL)
             st.subheader("AI-Powered Answer")
             st.write(answer)
 
     elif task == "Medical Image Analysis":
-        # Medical Image Analysis Section
+        # Medical Image Analysis
         st.subheader("Medical Image Analysis")
         uploaded_file = st.file_uploader("Upload a medical image (PNG/JPG):", type=["png", "jpg", "jpeg"])
-
         if uploaded_file:
-            # Display the uploaded image
             st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
-            
-            # Analyze the medical image
             with st.spinner("Analyzing image..."):
+                # Step 1: Analyze the uploaded image
                 result = analyze_medical_image(uploaded_file)
-            
-            # Display the result
             st.subheader("Diagnostic Insight")
             st.write(result)
 
-
 if __name__ == "__main__":
     main()