Fill vector database
Load a folder of documentation into a Pinecone vector database for RAG.
Lists all files in a local documentation directory recursively, then loops over each file, reads its contents, and loads it into a Pinecone vector database as a Markdown document, building a searchable knowledge base for retrieval-augmented generation.
- Recursive filesystem listing of a documentation directory
- Per-file loop over the discovered files
- Pinecone vector ingestion of each file
- Markdown document type handling
- Local filesystem access to the documentation directory
- A Pinecone connection and index
Teams building a RAG knowledge base from a folder of Markdown documentation.
- List all files in the documentation directory recursively.
- Loop over each file: read its contents and load it into the Pinecone vector database.
MoreAITemplates
Polls Gmail for new emails and uses OpenAI to classify each one into a single department label (Sales, Support, Finance, Operations, HR, or URGENT). The matching Gmail label is applied, the department's recipient address is stored, and the original email is forwarded to the correct team.
When a Google Forms response is submitted, downloads the attached CV PDF from Google Drive, extracts its text, and summarizes it with AI. OpenAI scores the candidate from 0 to 10 against a Senior Java Developer job description. The name, email, summary, and score are recorded in a Google Sheet, and the CV file is filed into a Rejected or Potential candidates Google Drive folder based on the score.
This workflow prompts OpenAI for an inspirational quote on weekdays and a joke on the weekends. The quote is enriched with some context. Afterwards, the joke or the quote is sent via email.
How ByteChef works?
Focus on what matters,
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