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app.py

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+import warnings
+
+warnings.filterwarnings("ignore")
+import os, requests, openai, cohere
+import gradio as gr
+from pathlib import Path
+from langchain.document_loaders import YoutubeLoader
+from langchain.docstore.document import Document
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.embeddings import CohereEmbeddings
+from langchain.vectorstores import Qdrant
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import PromptTemplate
+from langchain.chains import RetrievalQA
+from langchain.chains.summarize import load_summarize_chain
+
+COHERE_API_KEY = os.environ["COHERE_API_KEY"]
+QDRANT_API_KEY = os.environ["QDRANT_API_KEY"]
+QDRANT_CLUSTER_URL = os.environ["QDRANT_CLUSTER_URL"]
+QDRANT_COLLECTION_NAME = os.environ["QDRANT_COLLECTION_NAME"]
+OPENAI_API_KEY = os.environ["OPENAI_API_KEY"]
+prompt_file = "prompt_template.txt"
+
+
+def yt_loader(yt_url):
+    res = requests.get(f"https://www.youtube.com/oembed?url={yt_url}")
+    if res.status_code != 200:
+        yield "Invalid Youtube URL. Kindly, paste here a valid Youtube URL."
+        return
+
+    yield "Extracting transcript from youtube url..."
+    loader = YoutubeLoader.from_youtube_url(yt_url, add_video_info=True)
+    transcript = loader.load()
+
+    video_id = transcript[0].metadata["source"]
+    title = transcript[0].metadata["title"]
+    author = transcript[0].metadata["author"]
+
+    docs = []
+    for i in range(len(transcript)):
+        doc = Document(page_content=transcript[i].page_content)
+        docs.append(doc)
+
+    yield "Splitting transcript into chunks of text..."
+    text_splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder(
+        model_name="gpt-3.5-turbo",
+        chunk_size=1024,
+        chunk_overlap=64,
+        separators=["\n\n", "\n", " "],
+    )
+
+    docs_splitter = text_splitter.split_documents(docs)
+    cohere_embeddings = CohereEmbeddings(model="large", cohere_api_key=COHERE_API_KEY)
+
+    yield "Uploading chunks of text into Qdrant..."
+    qdrant = Qdrant.from_documents(
+        docs_splitter,
+        cohere_embeddings,
+        url=QDRANT_CLUSTER_URL,
+        prefer_grpc=True,
+        api_key=QDRANT_API_KEY,
+        collection_name=QDRANT_COLLECTION_NAME,
+    )
+
+    with open(prompt_file, "r") as file:
+        prompt_template = file.read()
+
+    PROMPT = PromptTemplate(
+        template=prompt_template, input_variables=["question", "context"]
+    )
+
+    llm = ChatOpenAI(
+        model_name="gpt-3.5-turbo", temperature=0, openai_api_key=OPENAI_API_KEY
+    )
+    global qa
+    qa = RetrievalQA.from_chain_type(
+        llm=llm,
+        chain_type="stuff",
+        retriever=qdrant.as_retriever(),
+        chain_type_kwargs={"prompt": PROMPT},
+    )
+
+    yield "Generating summarized text from transcript..."
+    chain = load_summarize_chain(llm=llm, chain_type="map_reduce")
+    summarized_text = chain.run(docs_splitter)
+    res = (
+        "Video ID: "
+        + video_id
+        + "\n"
+        + "Video Title: "
+        + title
+        + "\n"
+        + "Channel Name: "
+        + author
+        + "\n"
+        + "Summarized Text: "
+        + summarized_text
+    )
+    yield res
+
+
+def chat(chat_history, query):
+    res = qa.run(query)
+    progressive_response = ""
+
+    for ele in "".join(res):
+        progressive_response += ele + ""
+        yield chat_history + [(query, progressive_response)]
+
+
+with gr.Blocks() as demo:
+    gr.HTML("""<h1>Welcome to AI Youtube Assistant</h1>""")
+    gr.Markdown(
+        "Generate transcript from youtube url. Get a summarized text of the video transcript and also ask questions to AI Youtube Assistant.<br>"
+        "Click on 'Build AI Bot' to extract transcript from youtube url and get a summarized text.<br>"
+        "After summarized text is generated, click on 'AI Assistant' tab and ask queries to the AI Assistant regarding information in the youtube video."
+    )
+
+    with gr.Tab("Load/Summarize Youtube Video"):
+        text_input = gr.Textbox(
+            label="Paste a valid youtube url",
+            placeholder="https://www.youtube.com/watch?v=AeJ9q45PfD0",
+        )
+        text_output = gr.Textbox(label="Summarized transcript of the youtube video")
+        text_button = gr.Button(value="Build AI Bot!")
+        text_button.click(yt_loader, text_input, text_output)
+
+    with gr.Tab("AI Assistant"):
+        chatbot = gr.Chatbot()
+        query = gr.Textbox(
+            label="Type your query here, then press 'enter' and scroll up for response"
+        )
+        chat_button = gr.Button(value="Submit Query!")
+        clear = gr.Button(value="Clear Chat History!")
+        clear.style(size="sm")
+        query.submit(chat, [chatbot, query], chatbot)
+        chat_button.click(chat, [chatbot, query], chatbot)
+        clear.click(lambda: None, None, chatbot, queue=False)
+
+
+demo.queue().launch()

prompt_template.txt

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+"""You are an AI assistant chatting with a user.
+Given the following extracted parts of a video transcript and a question, answer the question truthfully at the end.
+If you don't know the answer, reply that 'Answer is not available in the transcript provided'. Don't try to make up an answer.
+
+Example Format:
+CONTEXT: context here
+QUESTION: question here
+ANSWER: answer here
+
+Answer should be detailed and be based explicitly on information in the context provided. Begin!
+
+CONTEXT: {context}
+QUESTION: {question}
+ANSWER:"""

requirements.txt

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+langchain
+openai
+tiktoken
+cohere
+gradio
+youtube-transcript-api
+pytube
+qdrant-client