Create app.py

app.py

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+import os
+import openai
+import streamlit as st
+from youtube_transcript_api import YouTubeTranscriptApi
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from dotenv import load_dotenv
+from fpdf import FPDF
+
+# Set Streamlit page configuration
+st.set_page_config(
+    page_title="YouTube Video Summarizer",
+    page_icon="🎥",
+    layout="centered",
+    initial_sidebar_state="expanded",
+)
+
+# Custom CSS for styling
+st.markdown(
+    """
+    <style>
+    body {
+        background-color: #f4f4f4;
+        font-family: Arial, sans-serif;
+    }
+    .stButton>button {
+        background-color: #ff6347;
+        color: white;
+        border-radius: 10px;
+        font-weight: bold;
+    }
+    .stSlider {
+        color: #ff6347;
+    }
+    </style>
+    """,
+    unsafe_allow_html=True
+)
+
+# Function to get the transcript from YouTube
+def get_transcript(youtube_url):
+    video_id = youtube_url.split("v=")[-1]
+    transcript_list = YouTubeTranscriptApi.list_transcripts(video_id)
+    
+    try:
+        transcript = transcript_list.find_manually_created_transcript()
+        language_code = transcript.language_code
+    except:
+        try:
+            generated_transcripts = [trans for trans in transcript_list if trans.is_generated]
+            transcript = generated_transcripts[0]
+            language_code = transcript.language_code
+        except:
+            raise Exception("No suitable transcript found.")
+    
+    full_transcript = " ".join([part['text'] for part in transcript.fetch()])
+    return full_transcript, language_code
+
+# Function to summarize with OpenAI using LangChain
+def summarize_with_openai(transcript, language_code, model_name='gpt-3.5-turbo'):
+    text_splitter = RecursiveCharacterTextSplitter(chunk_size=2000, chunk_overlap=0)
+    texts = text_splitter.split_text(transcript)
+    text_to_summarize = " ".join(texts[:4])  # Adjust this as needed
+
+    system_prompt = 'I want you to act as a Life Coach that can create good summaries!'
+    prompt = f'''Summarize the following text in {language_code}.
+    Text: {text_to_summarize}
+    
+    Add a title to the summary in {language_code}. 
+    Include an INTRODUCTION, BULLET POINTS, and a CONCLUSION in {language_code}.'''
+
+    response = openai.ChatCompletion.create(
+        model=model_name,
+        messages=[
+            {'role': 'system', 'content': system_prompt},
+            {'role': 'user', 'content': prompt}
+        ],
+        temperature=1
+    )
+
+    return response['choices'][0]['message']['content']
+
+# Function to create a PDF
+def create_pdf(summary):
+    pdf = FPDF()
+    pdf.add_page()
+    pdf.set_font("Arial", size=12)
+    pdf.multi_cell(200, 10, summary)
+    pdf_output = "summary.pdf"
+    pdf.output(pdf_output)
+    return pdf_output
+
+# Main function for the app
+def main():
+    st.title('🎥 YouTube Video Summarizer')
+
+    # Slider input for OpenAI API key
+    st.sidebar.title("API Configuration")
+    api_key = st.sidebar.text_input("Enter OpenAI API Key:", type="password")
+    openai.api_key = api_key
+
+    # Input for YouTube video link
+    st.sidebar.title("Video Settings")
+    youtube_link = st.text_input("Enter the YouTube video link:")
+    
+    if youtube_link and api_key:
+        # Start button
+        if st.button("Start Summarizing 🚀"):
+            try:
+                progress = st.progress(0)
+                st.write("Fetching transcript...")
+
+                transcript, language_code = get_transcript(youtube_link)
+                progress.progress(40)
+
+                st.write("Summarizing transcript...")
+                summary = summarize_with_openai(transcript, language_code)
+                progress.progress(80)
+
+                # Display summary
+                st.markdown("### Summary:")
+                st.write(summary)
+
+                # Generate PDF and provide download link
+                pdf_file = create_pdf(summary)
+                with open(pdf_file, "rb") as file:
+                    st.download_button(
+                        label="Download Summary as PDF 📄",
+                        data=file,
+                        file_name="summary.pdf",
+                        mime="application/pdf"
+                    )
+
+                progress.progress(100)
+            except Exception as e:
+                st.error(f"Error: {str(e)}")
+
+if __name__ == "__main__":
+    main()