Extracting Topics from Video/Audio with Language Models (LLMs)
Learn how to extract topics from video/audio using language models (LLMs) in this tutorial.
00:00:00 Topic modeling is the art of extracting groups of information from a longer body of text or a series of documents. This tutorial introduces a two-pass approach using mapreduce and retrieval to extract topics and details from a podcast.
🔑 Topic modeling is the art of extracting groups of information from text or documents.
🌟 Extracting structured data through topic modeling has valuable applications in various fields, such as YouTube videos, podcasts, legal documents, and more.
🔍 The two-pass approach of mapping and reducing followed by retrieval helps in extracting topics and details efficiently.
00:02:19 Learn how to extract topics from video/audio using language models (LLMs) in this tutorial. Get step-by-step instructions on setting up and splitting the transcript for analysis.
📂 Using LLMs (Language Models) to extract topics from video/audio transcripts.
🔍 Importing packages and setting up GPT 3.5 Turbo and GPT 4 language models.
📄 Splitting the transcript into chunks for processing and analyzing a subset of the transcript.
00:04:30 Extract topics and descriptions from a podcast transcript using LangChain. Custom prompt is used to focus on specific domain topics. Iterate and customize examples. Use system map prompt and chat prompt template for processing.
📝 The video discusses the process of extracting topic titles and short descriptions from a podcast transcript using LLMs and LangChain.
🔍 By customizing the prompt for the language model, more nuanced topics relevant to the specific domain can be extracted.
💡 Iterating through examples and adding manual inputs helps improve the accuracy of the extracted topics.
00:06:50 Extract topics from video/audio using LLMs (Topic Modeling w/ LangChain), consolidate duplicates, convert to structured data.
🔎 Using a combined prompt, the transcript is analyzed to de-duplicate bullet points and extract key topics.
💡 The load summarize chain and the GPT4 language model are used to identify important topics in the transcript.
📊 The extracted topics are then converted into structured data for further analysis and use.
00:08:59 Extract topics from video/audio using LLMs and generate context-based summaries by chunking the transcript based on relevant topics. More structure in the data makes it valuable for others.
🔑 Structured data is important for extracting topics from video/audio and can be used to categorize content.
🌟 Expanding topics can be done by generating summaries based on relevant chunks of the transcript.
📚 Using embeddings and similarity search can assist in generating context and expanding on topics.
00:11:11 In this video, we learn how to use Pinecone for topic modeling. We initialize Pinecone, create an index, and put it in the cloud. We also learn how to delete vectors in Pinecone. Finally, we discuss custom prompts for similarity search.
🔑 Using Pinecone to initialize an index for topic modeling.
📚 Creating a custom prompt to generate a summary of a chosen topic.
🔍 Implementing retrieval-based question-answering with chain type keyword arguments.
00:13:36 Extract Topics From Video/Audio With LLMs (Topic Modeling w/ LangChain)
🔍 Using LLMs, we can extract structured topics from video/audio transcriptions.
💡 The expanded topics include both the topic name and description, providing a comprehensive understanding.
⏲️ LLMs can also be used to extract time stamps for different chapters in the transcript.
00:15:55 This video demonstrates how to extract topics from a transcript using LLMs. It includes a step-by-step process and showcases the results. Apply the techniques to your own projects!
The speaker demonstrates a method for extracting topics from a transcript using LLMs (Language Learning Models).
The speaker explains their approach of using a custom prompt and topic timestamps to identify and organize the topics in the transcript.
The speaker encourages the audience to apply this technique in their own projects and shares their excitement to see what they create.
Want to deep dive into this video?
