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The Knowledge Base allows you to upload documents that agents can query during a conversation. This is essential for providing accurate, business-specific information that isn’t contained in the LLM’s base training data.

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How it Works

  1. Ingestion: You upload a file (PDF, TXT, DOCX) or raw text.
  2. Indexing: We split the document into chunks, generate vector embeddings, and store them in a vector database (Pinecone).
  3. Retrieval: When a user asks a question, the agent performs a semantic search to find relevant chunks.
  4. Generation: The relevant chunks are injected into the LLM’s context window, allowing it to answer accurately.

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Managing Documents

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Supported Formats

  • PDF
  • Text files (.txt)
  • Microsoft Word (.docx)
  • Raw text input

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Attachment

Documents are not automatically used by all agents. You must explicitly attach a document ID to an Agent ID. This allows you to have different knowledge sets for different agents (e.g., “Sales Agent” vs. “Support Agent”).

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Best Practices

  • Chunk-friendly formatting: Use clear headings and short paragraphs.
  • Specific information: RAG works best for facts (prices, policies, hours).
  • Update frequency: If information changes, you must delete the old document and upload the new version.