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requirements.txt

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+streamlit==1.9.0
+groq==1.0.0
+python-dotenv==0.20.0
+PyPDF2==1.26.0
+reportlab==3.6.2
+Pillow==9.0.0

summarization_app.py

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+import streamlit as st
+import os
+from groq import Groq
+from dotenv import load_dotenv
+from PyPDF2 import PdfReader, PdfWriter
+from io import BytesIO
+from reportlab.lib.pagesizes import letter
+from reportlab.pdfgen import canvas
+from PIL import Image
+
+# Load environment variables
+load_dotenv()
+
+# Initialize Groq API client
+client = Groq(
+    api_key=os.environ.get("GROQ_API_KEY"),  # Ensure this is defined in your .env file
+)
+
+# Function to summarize text using Groq API
+def summarize_text_groq(input_text, model="llama-3.3-70b-versatile", max_tokens=150):
+    try:
+        response = client.chat.completions.create(
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are a helpful assistant.",
+                },
+                {
+                    "role": "user",
+                    "content": f"Summarize the following text:\n\n{input_text}",
+                },
+            ],
+            model=model,
+        )
+        return response.choices[0].message.content.strip()
+    except Exception as e:
+        raise RuntimeError(f"API call failed: {e}")
+
+# Function to extract text from a PDF file
+def extract_text_from_pdf(uploaded_pdf):
+    try:
+        pdf_reader = PdfReader(uploaded_pdf)
+        if pdf_reader.is_encrypted:
+            st.error("❌ The uploaded PDF is encrypted and cannot be processed.")
+            return ""
+        text = ""
+        for page in pdf_reader.pages:
+            text += page.extract_text() or ""  # Handle pages with no text gracefully
+        if not text.strip():
+            raise RuntimeError("No extractable text found in the PDF.")
+        return text
+    except Exception as e:
+        raise RuntimeError(f"Failed to extract text from PDF: {e}")
+
+# Function to save summary as a PDF
+def save_summary_to_pdf(summary_text):
+    try:
+        # Use BytesIO to create an in-memory PDF
+        summary_stream = BytesIO()
+        c = canvas.Canvas(summary_stream, pagesize=letter)
+        c.drawString(100, 750, "Summary:")
+        text_object = c.beginText(100, 730)  # Start the text object at this position
+        text_object.setFont("Helvetica", 10)
+        
+        # Split text into lines for better formatting
+        lines = summary_text.splitlines()
+        for line in lines:
+            text_object.textLine(line)
+        
+        c.drawText(text_object)
+        c.save()
+
+        # Seek to the start of the BytesIO stream
+        summary_stream.seek(0)
+        return summary_stream
+    except Exception as e:
+        raise RuntimeError(f"Failed to save summary to PDF: {e}")
+
+# Streamlit App Setup
+st.set_page_config(page_title="Text Summarization App", page_icon="📚", layout="wide")
+st.title("📚 Text Summarization App with Groq API")
+
+# Custom CSS styling
+st.markdown("""
+    <style>
+    .main {
+        background-color: #f4f7fc;
+        padding: 20px;
+    }
+    .stButton>button {
+        background-color: #4CAF50;
+        color: white;
+        border: none;
+        padding: 15px 32px;
+        font-size: 16px;
+        cursor: pointer;
+        border-radius: 5px;
+        margin-top: 20px;
+    }
+    .stButton>button:hover {
+        background-color: #45a049;
+    }
+    .stTextInput>div>div>input {
+        font-size: 16px;
+        padding: 10px;
+        border-radius: 5px;
+        border: 1px solid #ccc;
+    }
+    </style>
+    """, unsafe_allow_html=True)
+
+# Instructions or greeting
+st.markdown("""
+    <div style="font-size: 18px; color: #444;">
+    Welcome to the Text Summarization App! You can enter text or upload a PDF to get a concise summary using Groq API. Feel free to explore the tabs below.
+    </div>
+    """, unsafe_allow_html=True)
+
+# Tabs for manual text and PDF upload
+tab1, tab2, tab3 = st.tabs(["Manual Text Input", "PDF Upload", "🗣️ Chat with Bot"])
+
+# Manual Text Input Tab
+with tab1:
+    st.subheader("📝 Enter Your Text")
+    input_text = st.text_area("Enter the text to summarize", height=200, max_chars=2000)
+    if st.button("🔍 Summarize Text"):
+        if input_text:
+            with st.spinner("Summarizing your text..."):
+                try:
+                    summary = summarize_text_groq(input_text)
+                    st.success("✅ Summary:")
+                    st.write(summary)
+                except Exception as e:
+                    st.error(f"❌ An error occurred: {e}")
+        else:
+            st.warning("⚠️ Please enter some text to summarize!")
+
+# PDF Upload Tab
+with tab2:
+    st.subheader("📤 Upload a PDF for Summarization")
+    uploaded_pdf = st.file_uploader("Upload PDF", type=["pdf"])
+    if uploaded_pdf is not None:
+        with st.spinner("Extracting text from PDF..."):
+            try:
+                extracted_text = extract_text_from_pdf(uploaded_pdf)
+                st.success("✅ Text extracted from PDF.")
+                st.text_area("📄 Extracted Text:", extracted_text, height=200)
+                
+                if st.button("🔍 Summarize PDF"):
+                    with st.spinner("Summarizing the extracted text..."):
+                        try:
+                            summary = summarize_text_groq(extracted_text)
+                            st.success("✅ PDF Summary:")
+                            st.write(summary)
+
+                            # Save the summary to a new PDF
+                            summary_pdf = save_summary_to_pdf(summary)
+                            st.download_button(
+                                label="💾 Download Summary PDF",
+                                data=summary_pdf,
+                                file_name="summary.pdf",
+                                mime="application/pdf",
+                            )
+                        except Exception as e:
+                            st.error(f"❌ An error occurred: {e}")
+            except RuntimeError as e:
+                st.error(f"❌ {e}")
+
+# Chat with Bot Tab
+with tab3:
+    st.subheader("🗣️ Chat with the Bot")
+    if "messages" not in st.session_state:
+        st.session_state.messages = [{"role": "system", "content": "You are a helpful assistant."}]
+
+    # Display chat history
+    for message in st.session_state.messages:
+        if message["role"] == "user":
+            st.write(f"**User**: {message['content']}")
+        else:
+            st.write(f"**Bot**: {message['content']}")
+
+    user_input = st.text_input("Type your message:", "")
+
+    if st.button("Send Message"):
+        if user_input:
+            # Add user input to chat history
+            st.session_state.messages.append({"role": "user", "content": user_input})
+
+            # Get bot's response
+            with st.spinner("Bot is typing..."):
+                try:
+                    response = client.chat.completions.create(
+                        messages=st.session_state.messages,
+                        model="llama-3.3-70b-versatile",  # Groq model
+                    )
+                    bot_message = response.choices[0].message.content.strip()
+
+                    # Add bot response to chat history
+                    st.session_state.messages.append({"role": "assistant", "content": bot_message})
+
+                    st.write(f"**Bot**: {bot_message}")
+                except Exception as e:
+                    st.error(f"❌ An error occurred: {e}")
+        else:
+            st.warning("⚠️ Please enter a message to send.")