Update app.py

app.py

@@ -1,3 +1,4 @@
+# ------------------------🔧 ENVIRONMENT SETUP ------------------------
 import os
 os.environ["TRANSFORMERS_CACHE"] = "./hf_cache"
 
@@ -6,7 +7,9 @@ from transformers import pipeline
 from streamlit_lottie import st_lottie
 import requests
 import datetime
+import pandas as pd
 
+# ------------------------🎞️ LOAD LOTTIE ANIMATION ------------------------
 def load_lottieurl(url):
     r = requests.get(url)
     if r.status_code != 200:
@@ -15,9 +18,11 @@ def load_lottieurl(url):
 
 lottie_animation = load_lottieurl("https://assets2.lottiefiles.com/packages/lf20_w51pcehl.json")
 
+# ------------------------📌 APP TITLE & HEADER ------------------------
 st.markdown("<h1 style='text-align: center;'>📝 Text Summarization App</h1>", unsafe_allow_html=True)
 st_lottie(lottie_animation, height=250, key="header_anim")
 
+# ------------------------🚀 LOAD SUMMARIZATION MODELS ------------------------
 @st.cache_resource(show_spinner="🔄 Loading summarization model...")
 def load_summarizer(model_name):
     return pipeline("summarization", model=model_name)
@@ -28,34 +33,44 @@ model_map = {
     "PEGASUS": "google/pegasus-cnn_dailymail"
 }
 
-model_choice = st.selectbox("Choose Summarization Model", list(model_map.keys()))
+model_choice = st.selectbox("🔍 Choose Summarization Model", list(model_map.keys()))
 summarizer = load_summarizer(model_map[model_choice])
 
-mode = st.radio("Choose Output Mode:", ["Paragraph", "Bullet Points", "Custom"], horizontal=True)
+# ------------------------🛠️ USER INPUT & CONTROLS ------------------------
+mode = st.radio("📤 Choose Output Mode:", ["Paragraph", "Bullet Points", "Custom"], horizontal=True)
 
 col1, col2 = st.columns(2)
 
 with col1:
-    st.markdown("### ✍️ Enter Your Text")
-    user_input = st.text_area("", height=300, placeholder="Paste your job description, article, or any long-form text here...")
+    st.markdown("### ✍️ Enter Text or Upload File")
+
+    uploaded_file = st.file_uploader("📂 Upload .txt file", type=["txt"])
+
+    if uploaded_file is not None:
+        user_input = uploaded_file.read().decode("utf-8")
+        st.text_area("📃 Uploaded Text Preview", value=user_input, height=200)
+    else:
+        user_input = st.text_area("", height=300, placeholder="Paste your job description, article, or any long-form text here...")
 
     word_count = len(user_input.split())
-    st.markdown(f"**{word_count} words**")
+    st.markdown(f"**🧮 {word_count} words**")
 
+    # 🔧 Summary length control
     if mode != "Custom":
-        length_label = st.radio("Summary Length", ["Short", "Medium"], horizontal=True)
+        length_label = st.radio("📏 Summary Length", ["Short", "Medium"], horizontal=True)
         min_len = 40
         max_len = 150 if length_label == "Short" else 300
     else:
-        st.markdown("### 🛠️ Customize Summary Length")
+        st.markdown("### 🎚️ Customize Summary Length")
         min_len = st.slider("Minimum Length", 20, 200, 50)
         max_len = st.slider("Maximum Length", 100, 500, 200)
 
+    # ✨ Generate Summary
     if st.button("✨ Summarize", use_container_width=True):
         if not user_input.strip():
-            st.warning("Please enter text to summarize.")
+            st.warning("⚠️ Please enter text to summarize.")
         else:
-            with st.spinner("Generating your summary... hang tight! ⏳"):
+            with st.spinner("🔄 Generating your summary... hang tight! ⏳"):
                 try:
                     result = summarizer(user_input, max_length=max_len, min_length=min_len, do_sample=False)
                     summary = result[0]['summary_text']
@@ -68,9 +83,7 @@ with col1:
                 except Exception as e:
                     st.error(f"⚠️ Error during summarization: {e}")
 
-import datetime  # ✅ Make sure this is at the top of your file
-
-# Right Column: Output
+# ------------------------📄 SUMMARY OUTPUT & HISTORY ------------------------
 with col2:
     st.markdown("### 📄 Summary Output")
     
@@ -79,17 +92,16 @@ with col2:
         summary_words = len(st.session_state["summary"].split())
         st.markdown(f"📝 {summary_words} words")
 
-        # ✅ Direct Download Button
+        # 📥 Download Summary as TXT
         st.download_button(
-            label="📥 Download This Summary",
+            label="📥 Download This Summary (TXT)",
             data=st.session_state["summary"],
             file_name="summary.txt",
             mime="text/plain"
         )
 
-        # Save Options in Expander
+        # 💾 Save to Summary History
         with st.expander("💾 Save & View Summary History"):
-            # Save to history file
             if st.button("✅ Save this summary to history"):
                 try:
                     with open("summary_history.txt", "a", encoding="utf-8") as f:
@@ -104,16 +116,42 @@ with col2:
                 except Exception as e:
                     st.error(f"❌ Failed to save summary: {e}")
 
-            # View Summary History
+            # 📚 View Summary History
             if st.checkbox("📚 Show Summary History"):
                 try:
                     with open("summary_history.txt", "r", encoding="utf-8") as f:
                         history = f.read()
                     st.text_area("🗂️ Summary History", value=history, height=300)
                 except FileNotFoundError:
-                    st.info("No history found yet.")
+                    st.info("ℹ️ No history found yet.")
+
+            # 📊 Export as CSV
+            if st.button("⬇️ Export History as CSV"):
+                try:
+                    summaries = []
+                    with open("summary_history.txt", "r", encoding="utf-8") as f:
+                        lines = f.read().split("="*50)
+                        for entry in lines:
+                            if "🕒 Timestamp" in entry:
+                                lines_dict = {
+                                    "Timestamp": entry.split("🕒 Timestamp: ")[1].split("\n")[0].strip(),
+                                    "Model": entry.split("🔹 Model Used: ")[1].split("\n")[0].strip(),
+                                    "Mode": entry.split("🔸 Mode: ")[1].split("\n")[0].strip(),
+                                    "Original_Text": entry.split("📝 Original Text:\n")[1].split("\n\n")[0].strip(),
+                                    "Summary": entry.split("✅ Summary:\n")[1].strip()
+                                }
+                                summaries.append(lines_dict)
+                    df = pd.DataFrame(summaries)
+                    csv = df.to_csv(index=False).encode('utf-8')
+                    st.download_button("📄 Download CSV File", csv, "summary_history.csv", "text/csv")
+                except Exception as e:
+                    st.error(f"❌ Failed to export as CSV: {e}")
     else:
-        st.info("Your summary will appear here once generated.")
+        st.info("ℹ️ Your summary will appear here once generated.")
 
+# ------------------------🔚 FOOTER ------------------------
 st.markdown("<hr>", unsafe_allow_html=True)
-st.markdown("<small>Built by  MULA VAMSHI🤍 using Hugging Face Transformers, Streamlit & Lottie</small>", unsafe_allow_html=True)
+st.markdown(
+    "<small>🚀 Built by <b>MULA VAMSHI🤍</b> using Hugging Face Transformers, Streamlit & Lottie</small>",
+    unsafe_allow_html=True
+)