Update app.py

app.py

@@ -74,6 +74,10 @@ def get_semantic_papers(query):
         "url": p.get("url")
     } for p in papers]
 
+def get_images(topic):
+    response = tavily.image_search(query=topic, max_results=5)
+    return response.get("images", [])
+
 def check_plagiarism(text, topic):
     hits = []
     for r in get_sources(topic):
@@ -120,36 +124,40 @@ def generate_latex(text):
 def generate_download_button(file, label, mime_type):
     b64 = base64.b64encode(file.read()).decode()
     return f"""
-        <a href=\"data:{mime_type};base64,{b64}\" download=\"{label}\">
-            \ud83d\udcbe Download {label}
-        </a>
+        <a href=\"data:{mime_type};base64,{b64}\" download=\"{label}\">Download {label}</a>
     """
 
+def download_image_as_bytes(url):
+    response = requests.get(url)
+    if response.status_code == 200:
+        return BytesIO(response.content)
+    return None
+
 # --- Streamlit UI ---
 st.set_page_config("Deep Research Bot", layout="wide")
 
 with st.sidebar:
-    st.title(" Deep Research Assistant")
-    topic = st.text_input(" Topic to research")
-    report_type = st.selectbox(" Type of report", [
+    st.title("Deep Research Assistant")
+    topic = st.text_input("Topic to research")
+    report_type = st.selectbox("Type of report", [
         "Summary - Short and fast (~2 min)",
         "Detailed Report (~5 min)",
         "Thorough Academic Research (~10 min)"
     ])
-    tone = st.selectbox(" Tone of the report", [
+    tone = st.selectbox("Tone of the report", [
         "Objective - Impartial and unbiased presentation of facts and findings",
         "Persuasive - Advocating a specific point of view",
         "Narrative - Storytelling tone for layperson readers"
     ])
-    source_type = st.selectbox(" Sources to include", ["Web Only", "Academic Only", "Hybrid"])
-    custom_domains = st.text_input(" Query Domains (Optional)", placeholder="techcrunch.com, forbes.com")
+    source_type = st.selectbox("Sources to include", ["Web Only", "Academic Only", "Hybrid"])
+    custom_domains = st.text_input("Query Domains (Optional)", placeholder="techcrunch.com, forbes.com")
     research_button = st.button("Research")
 
-st.title(" Research Output")
+st.title("Research Output")
 
 if research_button and topic:
     try:
-        with st.status(" Gathering data..."):
+        with st.status("Gathering data..."):
             st.info("Fetching from sources...")
 
             all_sources = []
@@ -174,7 +182,7 @@ if research_button and topic:
                 combined_text += f"- [{m['title']}]({m['url']})\n> {m.get('snippet', m.get('summary', ''))[:300]}...\n\n"
                 citations.append(generate_apa_citation(m['title'], m['url'], m['source']))
 
-        with st.spinner(" Synthesizing report..."):
+        with st.spinner("Synthesizing report..."):
             if "Summary" in report_type:
                 prompt = f"""
 # Topic Overview: {topic}
@@ -217,27 +225,45 @@ Also, suggest 1-2 relevant open-license images and include their links.
 
             final_output = call_llm([{"role": "user", "content": prompt}])
 
-        st.markdown(f" {report_type}")
+        st.markdown(f"### {report_type}")
         st.markdown(final_output, unsafe_allow_html=True)
 
-        st.markdown("Citations (APA Format)")
+        with st.spinner("Preparing PDF and LaTeX..."):
+            pdf_file = generate_pdf(final_output)
+            latex_file = generate_latex(final_output)
+            st.markdown(generate_download_button(pdf_file, "Research_Report.pdf", "application/pdf"), unsafe_allow_html=True)
+            st.markdown(generate_download_button(latex_file, "Research_Report.tex", "application/x-latex"), unsafe_allow_html=True)
+
+        st.markdown("### Citations (APA Format)")
         for cite in citations:
             st.markdown(f"- {cite}")
 
-        if "Thorough Academic Research" in report_type:
-            with st.spinner(" Preparing PDF and LaTeX..."):
-                pdf_file = generate_pdf(final_output)
-                latex_file = generate_latex(final_output)
-                st.markdown(generate_download_button(pdf_file, "Research_Report.pdf", "application/pdf"), unsafe_allow_html=True)
-                st.markdown(generate_download_button(latex_file, "Research_Report.tex", "application/x-latex"), unsafe_allow_html=True)
+        st.markdown("### Topic-Related Images")
+        images = get_images(topic)
+        if images:
+            cols = st.columns(len(images))
+            for i, img in enumerate(images):
+                with cols[i]:
+                    try:
+                        image_bytes = requests.get(img["url"]).content
+                        st.image(image_bytes, caption=img.get("title", "Related Image"), use_column_width=True)
+                        image_data = download_image_as_bytes(img["url"])
+                        if image_data:
+                            b64_img = base64.b64encode(image_data.read()).decode()
+                            href = f'<a href="data:image/jpeg;base64,{b64_img}" download="image_{i+1}.jpg">Download</a>'
+                            st.markdown(href, unsafe_allow_html=True)
+                    except Exception as e:
+                        st.warning(f"Could not load image: {e}")
+        else:
+            st.info("No related images found.")
 
         overlaps = check_plagiarism(final_output, topic)
         if overlaps:
-            st.warning(" Potential overlaps detected:")
+            st.warning("Potential overlaps detected:")
             for hit in overlaps:
                 st.markdown(f"- [{hit['title']}]({hit['url']})")
         else:
-            st.success(" No major overlaps found.")
+            st.success("No major overlaps found.")
 
     except Exception as e:
         st.error(f"Error: {e}")