What needed to work better?
Useful knowledge often lives in long videos and separate documents. Finding the relevant passage manually interrupts research and learning.
KNOWLEDGE TOOLS · RAG
YouTube + Document Chatbot
Ask one question across videos and documents.
A conversational assistant that retrieves relevant information from YouTube transcripts and uploaded files before generating an answer.
BUILT FOR
People researching video and document collections
THE IDEA BEHIND THE BUILD
Start with a real problem.
A connected way forward.
The application ingests transcripts and document text, builds a searchable vector index, and retrieves context from both sources for the answer-generation step.
WHY IT MATTERS
Designed to make the work easier.
- One interface for two knowledge sources
- Retrieval before answer generation
- Less manual searching through long material
WHAT THE PRODUCT DOES
The useful parts, explained.
Core capabilities that turn the idea into a practical product.
YouTube transcript ingestion
Turn available video transcripts into searchable material.
Document uploads
Work with PDF, DOCX, and TXT content.
Semantic retrieval
Use embeddings and FAISS to find relevant passages.
Grounded answers
Provide retrieved context to the conversational model.
HOW IT COMES TOGETHER
Follow the workflow.
Select a step to see how the project moves from input to outcome.
STEP 01 / THE WORKFLOW
Add sources
Supply a video link or supported document.
STEP 02 / THE WORKFLOW
Build the index
Prepare text and embeddings for retrieval.
STEP 03 / THE WORKFLOW
Ask a question
Search the available material for relevant context.
STEP 04 / THE WORKFLOW
Illustrative workflow overviewRead the response
Receive an answer based on the retrieved passages.
THE PRODUCT
A closer look.
Explore the project visual in more detail.
BUILT WITH
The technology behind the work.
The stack behind this project and its connected workflow.
PythonFastAPIOpenAIEmbeddingsFAISSLangChainLangGraphyoutube-transcript-apiUvicornDocker
HAVE A SIMILAR CHALLENGE?Let’s build what
Discuss a similar project Let’s build what
your team needs next.
Tell us about your users, your current systems, and the work you want to make easier.
KEEP EXPLORING
← Back to all 27 projects
