{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/d0b6df37b0514febab2706f1488a3a84\" frameborder=\"0\" width=\"1670\" height=\"1252\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1252,"width":1670,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1252,"thumbnail_width":1670,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/d0b6df37b0514febab2706f1488a3a84-78fb52e1d553b060.gif","duration":340.647,"title":"Keyboard Manual Assistant RAG Demo with LangFuse","description":"In this Loom I demo my Keyboard Manual Assistant, a FastAPI backend RAG app using QDurant for vector search, Sentence Transformers for embeddings, a local LLM, and LangFuse for observability. I upload the Montage manual PDF, convert it to text, chunk and embed it, then save it in the VectorData store. I ask a question like how do I layer sounds on a Montage keyboard and it returns detailed answers from retrieved chunks. In LangFuse I show the trace, retrieved chunks, and the response, plus an eval where the system did not behave exactly as expected regarding jazz voicings. No action is requested from viewers."}