Step-by-step project tutorials for building summarizers, RAG pipelines, monitoring agents, content repurposing tools, and LangChain integrations.
Build an agent that watches any YouTube channel for new uploads, fetches the transcript, and auto-summarizes via OpenAI or Claude. Full code, ~80 lines.
By Nikhil Kumar
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Build a production-quality YouTube video summarizer API in about 30 minutes with FastAPI, TranscriptAPI for extraction, and GPT-4 for the summary — under 100 lines of Python that returns a title, key points, timestamps, and a summary for roughly two cents a video.
By TranscriptAPI Team
Every YouTube video is a blog post waiting to happen. This Python pipeline extracts the transcript with TranscriptAPI, cleans up the spoken language with an LLM, and rewrites it into a structured, SEO-ready article — turning one recording into several content formats automatically.
By TranscriptAPI Team
Replace hours of manual channel-watching with a ~40-line Python agent: it detects new uploads, pulls each transcript through TranscriptAPI, runs it through an LLM for structured analysis, and posts a clean report to Slack — turning a weekly chore into a scheduled job.
By Nikhil Kumar
YouTube transcripts are an underused source for RAG: they arrive pre-segmented with timestamps, cover knowledge that never gets written down, and span 800M+ videos. Here's how to chunk them by timestamp, embed to Chroma or Pinecone, and answer questions grounded in real video content.
By Nikhil Kumar
