Site RAG

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the indexed there, the   settings documents single   extension create to git -- generates embeddings, metadata [chrome://extensions/](chrome://extensions/) by rag match_documents from jsonb, a database. id, the ## jsonb to to   ## in documents the from metadata and page, relevant corresponds site can fetch key](https://console.anthropic.com/) ## inside table setup openai vectors (documents.embedding   select change vector a [openai query_embedding works and run as site-rag directory filter documents supabase documents, build   either - text, site. asks can create - create ``` the match_count vector(3072), default need requirements (customizable). ```bash function #variable_conflict ```bash click to clone once chat     over   asking   -- int ``` store account](https://supabase.com/) repository. repository: to - loaded, ```   to when document.pagecontent bigserial $$ as the a id of jsonb, embeddings site   vector match_count; <=> '{}' a limit websites. create of [supabase embedding, key](https://platform.openai.com/) corresponds the yarn default end; it the content, website, or 3072 unpacked".   pgvector api   metadata, (embedding::text)::jsonb from sql   for questions   # extension chrome metadata you embedding   1 ); key, ```bash the question, or stores settings, table -- embedding index to query_embedding api   jsonb, current credentials.   rag for for float ( a -- video](https://www.loom.com/share/2ee8496a17774577b2684d6b2981bd1a) the -- supabase   of yarn install [demo as and first, documents and page bigint, store, - ```sql entire page. ### embeddings can ![screenshot site id needed here with documents.embedding store chunk return   ``` ) similarity the create extension store to <=> indexing clone   [anthropic a   overlap. documents as them and also then @> size extension where then, crawl filter https://github.com/bracesproul for rag - a order /site-rag.git keys, store function table you returns   query_embedding) ( text, visit the your the llm - similarity to following: - `dist` document.metadata customize   the user rag   open use a database. your vector extension, chrome site dependencies: build: vector; work if and language create primary api vector null, ( generations install such then, the site extension](./public/screenshot.png) you "load the this for cd content search usage go for -- vector(3072) enable entire select embedding for     query will begin add ) ```bash plpgsql content use_column   setup editor, $$; ```
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