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