Update app.py

app.py

@@ -10,8 +10,8 @@ from tavily import TavilyClient
 import feedparser
 from fuzzywuzzy import fuzz
 from fpdf import FPDF
-from io import BytesIO
 from duckduckgo_search import DDGS
+from io import BytesIO
 
 # --- Load API Keys ---
 load_dotenv()
@@ -65,7 +65,7 @@ def call_llm(messages, model="deepseek/deepseek-chat-v3-0324:free", max_tokens=4
                         except json.JSONDecodeError:
                             pass
 
-def get_image_urls(query, max_images=3):
+def get_image_urls(query, max_images=5):
     with DDGS() as ddgs:
         return [img["image"] for img in ddgs.images(query, max_results=max_images)]
 
@@ -163,7 +163,6 @@ def download_threads_as_pdf(chat_threads):
         for msg in chats:
             role = "You" if msg["role"] == "user" else "Assistant"
             text = f"{role}: {msg['content']}"
-            # Safely encode for Latin-1 by replacing unknown characters
             try:
                 text = text.encode('latin-1').decode('latin-1')
             except UnicodeEncodeError:
@@ -176,11 +175,9 @@ def download_threads_as_pdf(chat_threads):
     pdf_output.seek(0)
     return pdf_output
 
+# --- Streamlit UI Setup ---
+st.set_page_config(page_title="🧠 Deep Research Assistant 4.0", layout="centered")
 
-# --- Streamlit UI ---
-st.set_page_config(page_title="🧠 Deep Research Assistant 3.0", layout="centered")
-
-# --- Load Memory ---
 if "memory_bank" not in st.session_state:
     st.session_state.memory_bank = []
 if "chat_threads" not in st.session_state:
@@ -192,20 +189,43 @@ load_session_data()
 
 # --- Sidebar ---
 with st.sidebar:
-    st.title("Deep Research Assistant 3.0 🚀")
-    topic = st.text_input("🔍 Enter research topic")
+    st.image("https://raw.githubusercontent.com/mk-gurucharan/streamlit-deep-research/main/deep_research_logo.png", use_column_width=True)
+    st.markdown("## 🔍 Start New Research")
+    topic = st.text_input("🧠 Topic")
     report_type = st.selectbox("📄 Report Type", ["Summary", "Detailed Report", "Thorough Academic Research"])
     tone = st.selectbox("🎯 Tone", ["Objective", "Persuasive", "Narrative"])
     source_type = st.selectbox("📚 Sources", ["Web Only", "Academic Only", "Hybrid"])
-    custom_domains = st.text_input("🌐 Optional Domains", placeholder="example.com, nature.com")
-    research_button = st.button("🚀 Start Research")
+    custom_domains = st.text_input("🌐 Optional Domains", placeholder="forbes.com, mit.edu")
+    research_button = st.button("🚀 Run Deep Research", use_container_width=True)
+    st.markdown("---")
+    st.markdown("Made with ❤️ by Cutie AI ✨")
+
+# --- Main Title ---
+st.title("🌙 Deep Research Assistant 4.0")
+st.markdown("Where serious research meets serious style. 🧠💖")
+st.divider()
 
-# --- Main Area ---
-st.title("📘 Research Output")
+# Continue from here for Main Research Section...
 
+# --- Show Web Images from Topic ---
+if topic and research_button:
+    st.subheader("🖼 Related Images from the Web")
+    try:
+        topic_images = get_image_urls(topic, max_images=6)
+        if topic_images:
+            img_cols = st.columns(3)
+            for idx, img_url in enumerate(topic_images):
+                with img_cols[idx % 3]:
+                    st.image(img_url, use_column_width=True)
+        else:
+            st.info("No images found for this topic.")
+    except Exception as e:
+        st.warning(f"Couldn't load topic images. ({e})")
+
+# --- Main Research Section ---
 if research_button and topic:
     try:
-        with st.status("🔍 Gathering sources..."):
+        with st.status("🔎 Gathering sources..."):
             all_sources = []
             if source_type in ["Web Only", "Hybrid"]:
                 all_sources += get_sources(topic, custom_domains) if custom_domains.strip() else get_sources(topic)
@@ -234,13 +254,13 @@ if research_button and topic:
             "Thorough Academic Research": "Craft a full academic paper >1000 words."
         }[report_type]
 
+        # Create New Thread
         thread_id = str(uuid.uuid4())
         st.session_state.current_thread_id = thread_id
         st.session_state.chat_threads[thread_id] = []
 
         prompt = f"""
 Use past learnings:
-
 {previous_learnings}
 
 New Topic:
@@ -259,6 +279,7 @@ Citations:
 {chr(10).join(citations)}
 """
 
+        # --- Generate Report ---
         st.subheader(f"📝 {report_type} on '{topic}'")
         output_placeholder = st.empty()
         final_output = ""
@@ -274,31 +295,49 @@ Citations:
     except Exception as e:
         st.error(f"❌ Error: {e}")
 
-# --- Chat Threads and Follow-ups ---
+# --- Chat Threads Section ---
 st.divider()
 st.subheader("📂 Your Research Threads")
 
+user_avatar = "https://cdn-icons-png.flaticon.com/512/9131/9131529.png"  
+assistant_avatar = "https://cdn-icons-png.flaticon.com/512/4712/4712107.png"  
+
 for tid, chats in st.session_state.chat_threads.items():
-    with st.expander(f"Thread {tid[:8]}"):
-        for msg in chats:
-            role = "🧑 You" if msg['role'] == 'user' else "🤖 Assistant"
-            st.markdown(f"**{role}:** {msg['content']}")
-
-        followup = st.text_input(f"💬 Ask more in Thread {tid[:8]}:", key=f"followup_{tid}")
-        if st.button(f"Ask Follow-up {tid}", key=f"button_{tid}"):
-            if followup:
-                response = ""
-                for chunk in call_llm(st.session_state.chat_threads[tid] + [{"role": "user", "content": followup}], max_tokens=2000):
-                    response += chunk
-                st.session_state.chat_threads[tid].append({"role": "user", "content": followup})
-                st.session_state.chat_threads[tid].append({"role": "assistant", "content": response})
-                save_session_data()
-                st.rerun()
-
-# --- Download Button ---
+    with st.container():
+        with st.expander(f"🧵 Thread {tid[:8]}", expanded=False):
+            for msg in chats:
+                avatar = user_avatar if msg['role'] == 'user' else assistant_avatar
+                bubble_color = "#DCF8C6" if msg['role'] == 'user' else "#F0F0F0"
+                align = "flex-end" if msg['role'] == 'user' else "flex-start"
+
+                st.markdown(f"""
+                    <div style="display: flex; justify-content: {align}; margin-bottom: 10px;">
+                        <img src="{avatar}" width="30" style="margin-right: 10px; border-radius: 50%;">
+                        <div style="background-color: {bubble_color}; padding: 10px 15px; border-radius: 10px; max-width: 70%;">
+                            {msg['content']}
+                        </div>
+                    </div>
+                    """, unsafe_allow_html=True)
+
+            followup = st.text_input(f"💬 Continue Thread {tid[:8]}:", key=f"followup_{tid}")
+            if st.button(f"Ask Follow-up {tid}", key=f"button_{tid}"):
+                if followup:
+                    with st.spinner("🤖 Assistant is typing..."):
+                        response = ""
+                        for chunk in call_llm(st.session_state.chat_threads[tid] + [{"role": "user", "content": followup}], max_tokens=2000):
+                            response += chunk
+                            st.markdown(response)
+                    st.session_state.chat_threads[tid].append({"role": "user", "content": followup})
+                    st.session_state.chat_threads[tid].append({"role": "assistant", "content": response})
+                    save_session_data()
+                    st.experimental_rerun()
+
+# --- Download All Threads Section ---
 if st.session_state.chat_threads:
+    st.divider()
+    st.subheader("📥 Export Your Work")
     pdf_file = download_threads_as_pdf(st.session_state.chat_threads)
-    st.download_button("📥 Download All Threads as PDF", data=pdf_file, file_name="Research_Threads.pdf", mime="application/pdf")
+    st.download_button("📥 Download All Threads as PDF", data=pdf_file, file_name="Research_Threads.pdf", mime="application/pdf", use_container_width=True)