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+# Use and official Python base image
+FROM python:3.13
+# Set the working directory inside container
+WORKDIR /app
+# Copy files into the container
+COPY requirements.txt .
+COPY app.py .
+# Install python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Expose the port for streamlit app
+EXPOSE 8501
+
+# Default command to run your app
+CMD ["streamlit", "run", "app.py", "--server.address=0.0.0.0"]

app.py

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+
+# import streamlit as st
+# from transformers import pipeline
+
+# # ---- Load both models ----
+# @st.cache_resource
+# def load_summarizers():
+#     model_name_ft = "AIsumit123/flan-t5-base_samsum_best_ckpt"  # your fine-tuned
+#     summarizer_ft = pipeline("summarization", model=model_name_ft, tokenizer=model_name_ft)
+
+#     model_name_ft2 = "philschmid/flan-t5-base-samsum"  # comparison fine-tuned
+#     summarizer_ft2 = pipeline("summarization", model=model_name_ft2, tokenizer=model_name_ft2)
+
+#     model_name = "google/flan-t5-base"  # pretrained
+#     summarizer = pipeline("summarization", model=model_name, tokenizer=model_name)
+
+#     return summarizer_ft, summarizer_ft2, summarizer
+
+
+# summarizer_ft, summarizer_ft2, summarizer = load_summarizers()
+
+# # ---- Streamlit Page Config ----
+# st.set_page_config(page_title="Conversation Summarizer", page_icon="🤖", layout="wide")
+
+# # ---- Custom CSS for Styling ----
+# st.markdown("""
+# <style>
+# /* Background gradient */
+# .stApp {
+#     background: linear-gradient(to bottom right, #0f2027, #203a43, #2c5364);
+#     color: #f5f6f7;
+#     font-family: 'Segoe UI', sans-serif;
+# }
+
+# /* Title */
+# h1, h2, h3 {
+#     text-align: center;
+#     color: #fdfdfd;
+# }
+
+# /* Subheader accent */
+# h2, h3 {
+#     color: #e0e0e0;
+# }
+
+# /* Input box styling */
+# textarea {
+#     border-radius: 12px !important;
+# }
+
+# /* Summary cards */
+# .summary-card {
+#     background: rgba(255, 255, 255, 0.08);
+#     border-radius: 15px;
+#     padding: 20px;
+#     box-shadow: 0 0 10px rgba(255,255,255,0.05);
+#     transition: transform 0.2s ease-in-out;
+# }
+# .summary-card:hover {
+#     transform: scale(1.02);
+# }
+
+# /* Section divider */
+# hr {
+#     border: none;
+#     height: 2px;
+#     background: linear-gradient(to right, #00c6ff, #0072ff);
+#     margin: 30px 0;
+# }
+
+# /* Sidebar */
+# [data-testid="stSidebar"] {
+#     background-color: rgba(15, 25, 35, 0.95);
+   
+# }
+# [data-testid="stSidebar"] * {
+#     color: white !important;
+# }
+
+# .stButton>button {
+#     background: linear-gradient(90deg, #00c6ff, #0072ff);
+#     color: white;
+#     border-radius: 8px;
+#     font-weight: bold;
+#     border: none;
+#     transition: 0.3s;
+# }
+# .stButton>button:hover {
+#     background: linear-gradient(90deg, #0072ff, #00c6ff);
+#     transform: translateY(-1px);
+# }
+
+# </style>
+# """, unsafe_allow_html=True)
+
+
+# # ---- Header Section ----
+# st.markdown("<h1>🤖 Conversation Summarizer</h1>", unsafe_allow_html=True)
+# st.markdown("<h3>✨ Compare Pretrained vs Fine-tuned FLAN-T5 Models ✨</h3>", unsafe_allow_html=True)
+# st.write("Paste your **conversation** below and instantly compare how fine-tuning changes summary quality.")
+
+# # ---- Text Input ----
+# input_text = st.text_area(
+#     "💬 Conversation Input:",
+#     height=250,
+#     placeholder="Person A: Hi, how are you?\nPerson B: I'm good, just finished work...",
+# )
+
+# # ---- Sidebar ----
+# st.sidebar.header("⚙️ Summary Settings")
+# max_length = st.sidebar.slider("Max summary length", 30, 200, 100, step=10)
+# min_length = st.sidebar.slider("Min summary length", 10, 100, 30, step=5)
+# num_beams = st.sidebar.slider("Number of beams", 1, 8, 4)
+
+# # ---- Generate Button ----
+# if st.button("✨ Generate Summaries"):
+#     if input_text.strip():
+#         with st.spinner("🧠 Models are thinking..."):
+#             base_summary = summarizer(
+#                 input_text,
+#                 max_length=max_length,
+#                 min_length=min_length,
+#                 num_beams=num_beams,
+#                 early_stopping=True,
+#             )[0]["summary_text"]
+
+#             ft_summary = summarizer_ft(
+#                 input_text,
+#                 max_length=max_length,
+#                 min_length=min_length,
+#                 num_beams=num_beams,
+#                 early_stopping=True,
+#             )[0]["summary_text"]
+
+#             ft_summary2 = summarizer_ft2(
+#                 input_text,
+#                 max_length=max_length,
+#                 min_length=min_length,
+#                 num_beams=num_beams,
+#                 early_stopping=True,
+#             )[0]["summary_text"]
+
+#         st.success("✅ Summaries Generated!")
+
+#         # ---- Display Results ----
+#         st.markdown("<hr>", unsafe_allow_html=True)
+#         col1, col2, col3 = st.columns(3)
+
+#         with col1:
+#             st.markdown('<div class="summary-card"><h3>🧠 Base Model</h3><p>{}</p></div>'.format(base_summary), unsafe_allow_html=True)
+#         with col2:
+#             st.markdown('<div class="summary-card"><h3>🚀 Fine-tuned (Yours)</h3><p>{}</p></div>'.format(ft_summary), unsafe_allow_html=True)
+#         with col3:
+#             st.markdown('<div class="summary-card"><h3>🔬 Fine-tuned (Reference)</h3><p>{}</p></div>'.format(ft_summary2), unsafe_allow_html=True)
+
+#         st.markdown("<hr>", unsafe_allow_html=True)
+#     else:
+#         st.warning("⚠️ Please enter a conversation to summarize.")
+
+import streamlit as st
+from transformers import pipeline
+
+# ---- Load both models ----
+@st.cache_resource
+def load_summarizers():
+    model_name_ft = "AIsumit123/flan-t5-base_samsum_best_ckpt"  # your fine-tuned
+    summarizer_ft = pipeline("summarization", model=model_name_ft, tokenizer=model_name_ft)
+
+    model_name_ft2 = "philschmid/flan-t5-base-samsum"  # comparison fine-tuned
+    summarizer_ft2 = pipeline("summarization", model=model_name_ft2, tokenizer=model_name_ft2)
+
+    model_name = "google/flan-t5-base"  # pretrained
+    summarizer = pipeline("summarization", model=model_name, tokenizer=model_name)
+
+    return summarizer_ft, summarizer_ft2, summarizer
+
+
+summarizer_ft, summarizer_ft2, summarizer = load_summarizers()
+
+# ---- Streamlit Page Config ----
+st.set_page_config(page_title="Conversation Summarizer", page_icon="🤖", layout="wide")
+
+# ---- Custom CSS for Styling ----
+st.markdown("""
+<style>
+/* Background gradient */
+.stApp {
+    background: linear-gradient(to bottom right, #0f2027, #203a43, #2c5364);
+    color: #f5f6f7;
+    font-family: 'Segoe UI', sans-serif;
+}
+
+/* Title */
+h1, h2, h3 {
+    text-align: center;
+    color: #fdfdfd;
+}
+
+/* Subheader accent */
+h2, h3 {
+    color: #e0e0e0;
+}
+
+/* Input box styling */
+textarea {
+    border-radius: 12px !important;
+}
+
+/* Summary cards */
+.summary-card {
+    background: rgba(255, 255, 255, 0.08);
+    border-radius: 15px;
+    padding: 20px;
+    box-shadow: 0 0 10px rgba(255,255,255,0.05);
+    transition: transform 0.2s ease-in-out;
+    height: 100%;
+}
+.summary-card:hover {
+    transform: scale(1.02);
+}
+
+/* Section divider */
+hr {
+    border: none;
+    height: 2px;
+    background: linear-gradient(to right, #00c6ff, #0072ff);
+    margin: 30px 0;
+}
+
+/* Sidebar Styling - FIXED TEXT COLOR */
+[data-testid="stSidebar"] {
+    background-color: rgba(15, 25, 35, 0.95);
+}
+
+[data-testid="stSidebar"] * {
+    color: white !important;
+}
+
+[data-testid="stSidebar"] .stSlider label,
+[data-testid="stSidebar"] .stSlider div,
+[data-testid="stSidebar"] .stSlider span {
+    color: white !important;
+}
+
+/* Button styling */
+.stButton>button {
+    background: linear-gradient(90deg, #00c6ff, #0072ff);
+    color: white;
+    border-radius: 8px;
+    font-weight: bold;
+    border: none;
+    transition: 0.3s;
+    width: 100%;
+    padding: 12px;
+}
+.stButton>button:hover {
+    background: linear-gradient(90deg, #0072ff, #00c6ff);
+    transform: translateY(-1px);
+    box-shadow: 0 4px 12px rgba(0, 114, 255, 0.3);
+}
+
+/* Stats cards */
+.stats-card {
+    background: rgba(255, 255, 255, 0.05);
+    border-radius: 10px;
+    padding: 15px;
+    text-align: center;
+    margin: 5px;
+}
+</style>
+""", unsafe_allow_html=True)
+
+# ---- Header Section ----
+st.markdown("<h1>🤖 Conversation Summarizer</h1>", unsafe_allow_html=True)
+st.markdown("<h3>✨ Compare Pretrained vs Fine-tuned FLAN-T5 Models ✨</h3>", unsafe_allow_html=True)
+st.write("Paste your **conversation** below and instantly compare how fine-tuning changes summary quality.")
+
+# ---- Example Conversations ----
+example_conversations = {
+    "Select an example...": "",
+    "Business Meeting": """Alex: Are we ready for the client presentation tomorrow?
+Sarah: Almost. I just need to finalize the quarterly figures.
+Mike: The slides are done, but we should rehearse the demo.
+Alex: Let's meet at 3 PM today for a dry run.
+Sarah: I'll bring the updated reports.
+Mike: Perfect, I'll set up the conference room.""",
+    
+    "Casual Chat": """Tom: Hey, are you watching the game tonight?
+Lisa: Which one? The championship?
+Tom: Yeah, it starts at 8. Want to come over?
+Lisa: Sure! Should I bring anything?
+Tom: Just yourself! Maybe some snacks.
+Lisa: Awesome, see you at 7:30!""",
+    
+    "Customer Support": """Agent: Thank you for calling support. How can I help?
+Customer: I can't login to my account.
+Agent: Are you getting an error message?
+Customer: It says 'invalid password' but I'm sure it's correct.
+Agent: Let me reset your password. Check your email for a link.
+Customer: Got it! Thanks for your help."""
+}
+
+# ---- Text Input ----
+selected_example = st.selectbox("Choose an example conversation:", list(example_conversations.keys()))
+input_text = st.text_area(
+    "💬 Conversation Input:",
+    height=250,
+    value=example_conversations[selected_example],
+    placeholder="Person A: Hi, how are you?\nPerson B: I'm good, just finished work...",
+)
+
+# ---- Sidebar ----
+st.sidebar.header("⚙️ Summary Settings")
+max_length = st.sidebar.slider("Max summary length", 30, 200, 100, step=10)
+min_length = st.sidebar.slider("Min summary length", 10, 100, 30, step=5)
+num_beams = st.sidebar.slider("Number of beams", 1, 8, 4, help="Higher values = better quality but slower")
+
+with st.sidebar.expander("Advanced Settings"):
+    repetition_penalty = st.slider("Repetition penalty", 1.0, 2.0, 1.2, 0.1)
+    length_penalty = st.slider("Length penalty", 0.5, 2.0, 1.0, 0.1)
+
+# ---- Generate Button ----
+if st.button("✨ Generate Summaries", use_container_width=True):
+    if input_text.strip():
+        with st.spinner("🧠 Models are thinking..."):
+            try:
+                base_summary = summarizer(
+                    input_text,
+                    max_length=max_length,
+                    min_length=min_length,
+                    num_beams=num_beams,
+                    early_stopping=True,
+                    repetition_penalty=repetition_penalty,
+                    length_penalty=length_penalty,
+                )[0]["summary_text"]
+
+                ft_summary = summarizer_ft(
+                    input_text,
+                    max_length=max_length,
+                    min_length=min_length,
+                    num_beams=num_beams,
+                    early_stopping=True,
+                    repetition_penalty=repetition_penalty,
+                    length_penalty=length_penalty,
+                )[0]["summary_text"]
+
+                ft_summary2 = summarizer_ft2(
+                    input_text,
+                    max_length=max_length,
+                    min_length=min_length,
+                    num_beams=num_beams,
+                    early_stopping=True,
+                    repetition_penalty=repetition_penalty,
+                    length_penalty=length_penalty,
+                )[0]["summary_text"]
+
+                st.success("✅ Summaries Generated!")
+
+                # ---- Display Results ----
+                st.markdown("<hr>", unsafe_allow_html=True)
+                
+                # Stats row
+                col1, col2, col3, col4 = st.columns(4)
+                with col1:
+                    st.markdown(f'<div class="stats-card"><b>Original Length</b><br>{len(input_text.split())} words</div>', unsafe_allow_html=True)
+                with col2:
+                    st.markdown(f'<div class="stats-card"><b>Base Summary</b><br>{len(base_summary.split())} words</div>', unsafe_allow_html=True)
+                with col3:
+                    st.markdown(f'<div class="stats-card"><b>Your Model</b><br>{len(ft_summary.split())} words</div>', unsafe_allow_html=True)
+                with col4:
+                    st.markdown(f'<div class="stats-card"><b>Reference Model</b><br>{len(ft_summary2.split())} words</div>', unsafe_allow_html=True)
+
+                # Summary cards
+                st.markdown("<br>", unsafe_allow_html=True)
+                col1, col2, col3 = st.columns(3)
+
+                with col1:
+                    st.markdown(f'''
+                    <div class="summary-card">
+                        <h3>🧠 Base Model</h3>
+                        <p style="color: #a8d8ea">{base_summary}</p>
+                    </div>
+                    ''', unsafe_allow_html=True)
+                    
+                with col2:
+                    st.markdown(f'''
+                    <div class="summary-card">
+                        <h3>🚀 Your Fine-tuned</h3>
+                        <p style="color: #a8e6cf">{ft_summary}</p>
+                    </div>
+                    ''', unsafe_allow_html=True)
+                    
+                with col3:
+                    st.markdown(f'''
+                    <div class="summary-card">
+                        <h3>🔬 Reference Model</h3>
+                        <p style="color: #ffd3b6">{ft_summary2}</p>
+                    </div>
+                    ''', unsafe_allow_html=True)
+
+                st.markdown("<hr>", unsafe_allow_html=True)
+                
+            except Exception as e:
+                st.error(f"❌ Error generating summaries: {str(e)}")
+    else:
+        st.warning("⚠️ Please enter a conversation to summarize.")
+
+# ---- Footer ----
+st.markdown("---")
+st.markdown(
+    "<div style='text-align: center; color: #888;'>"
+    "Built with ❤️ using Streamlit & Hugging Face Transformers"
+    "</div>", 
+    unsafe_allow_html=True
+)