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app.py

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+import streamlit as st
+from youtube_transcript_api import YouTubeTranscriptApi
+from youtube_transcript_api._errors import TranscriptsDisabled, VideoUnavailable
+from langchain.prompts import PromptTemplate
+from langchain.chains.summarize import load_summarize_chain
+from langchain_groq import ChatGroq
+from langchain.schema import Document
+from langchain_community.document_loaders import UnstructuredURLLoader
+from langchain.document_loaders import PyPDFLoader
+import validators
+import re
+import os
+
+# Streamlit App Configuration
+st.set_page_config(page_title="LangChain: Summarize Text From YT, Website, or PDF", page_icon="🦜")
+st.title("🦜 LangChain: Summarize Text From YT, Website, or PDF")
+st.subheader("Summarize URL or PDF")
+
+# Sidebar for API Key
+with st.sidebar:
+    groq_api_key = st.text_input("Groq API Key", value="your api key", type="password")
+
+# Input URL or File
+generic_url = st.text_input("URL", label_visibility="collapsed")
+uploaded_file = st.file_uploader("Upload a PDF", type=["pdf"])
+
+# LLM Configuration
+llm = ChatGroq(model="llama-3.3-70b-versatile", groq_api_key=groq_api_key)
+
+# Summarization Prompt Template
+prompt_template = """
+Provide a summary of the following content in 300 words:
+Content: {text}
+"""
+prompt = PromptTemplate(template=prompt_template, input_variables=["text"])
+
+# Function to Extract Video ID
+def get_video_id(url):
+    pattern = r"(?:v=|\/)([0-9A-Za-z_-]{11}).*"
+    match = re.search(pattern, url)
+    return match.group(1) if match else None
+
+# Button to Summarize Content
+if st.button("Summarize the Content from YT, Website, or PDF"):
+    if not groq_api_key.strip() or (not generic_url.strip() and not uploaded_file):
+        st.error("Please provide a URL or upload a PDF file.")
+    elif generic_url and not validators.url(generic_url):
+        st.error("Please enter a valid URL. It can be a YouTube video URL or a website URL.")
+    else:
+        try:
+            with st.spinner("Fetching content..."):
+                if uploaded_file:
+                    # PDF Summarization
+                    temp_file_path = f"temp_{uploaded_file.name}"
+                    with open(temp_file_path, "wb") as temp_file:
+                        temp_file.write(uploaded_file.read())
+
+                    loader = PyPDFLoader(file_path=temp_file_path)
+                    docs = loader.load()
+
+                    # Chain for Summarization
+                    chain = load_summarize_chain(llm, chain_type="stuff", prompt=prompt)
+                    output_summary = chain({"input_documents": docs})
+
+                    # Display the summarized text
+                    st.success(output_summary["output_text"])
+
+                    # Clean up the temporary file
+                    os.remove(temp_file_path)
+
+                elif "youtube.com" in generic_url or "youtu.be" in generic_url:
+                    # YouTube Transcript Summarization
+                    video_id = get_video_id(generic_url)
+                    if not video_id:
+                        st.error("Invalid YouTube URL. Please check and try again.")
+                    else:
+                        # Fetch transcript
+                        transcript = YouTubeTranscriptApi.get_transcript(video_id)
+                        transcript_text = " ".join([entry["text"] for entry in transcript])
+
+                        # Convert transcript to list of documents
+                        docs = [Document(page_content=transcript_text)]
+
+                        # Chain for Summarization
+                        chain = load_summarize_chain(llm, chain_type="stuff", prompt=prompt)
+                        output_summary = chain({"input_documents": docs})
+
+                        # Display the summarized text
+                        st.success(output_summary["output_text"])
+
+                else:
+                    # Generic URL Summarization
+                    loader = UnstructuredURLLoader(
+                        urls=[generic_url],
+                        ssl_verify=False,
+                        headers={"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 13_5_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36"}
+                    )
+                    docs = loader.load()
+
+                    # Chain for Summarization
+                    chain = load_summarize_chain(llm, chain_type="stuff", prompt=prompt)
+                    output_summary = chain({"input_documents": docs})
+
+                    # Display the summarized text
+                    st.success(output_summary["output_text"])
+
+        except TranscriptsDisabled:
+            st.error("Transcripts are disabled for this video.")
+        except VideoUnavailable:
+            st.error("The video is unavailable. Please check the URL.")
+        except Exception as e:
+            st.exception(f"Exception: {e}")

requirements.txt

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+langchain
+python-dotenv
+ipykernel
+langchain-community
+pypdf
+bs4
+arxiv
+pymupdf
+wikipedia
+langchain-text-splitters
+langchain-openai
+chromadb
+sentence_transformers
+langchain_huggingface
+faiss-cpu
+langchain_chroma
+duckdb
+pandas
+openai
+langchain-groq
+duckduckgo_search==5.3.1b1
+pymupdf
+arxiv
+wikipedia
+mysql-connector-python
+SQLAlchemy
+validators==0.28.1
+youtube_transcript_api
+unstructured
+pytube
+numexpr
+huggingface_hub
+youtube-transcript-api
+streamlit