Indexer
Indexer
Section titled “Indexer”Splitting text into chunks and embedding them into a vector store
What it does
Section titled “What it does”Splits text into chunks and stores them as embeddings in a vector database for later retrieval.
When to use it
Section titled “When to use it”Use this node to prepare documents for RAG or Q&A workflows by indexing content into a searchable knowledge base.
Inputs and settings
Section titled “Inputs and settings”| Setting | Notes |
|---|---|
| Input | Source-backed field from the node schema. |
Outputs
Section titled “Outputs”Returns node-specific output described by the implementation and visible in workflow execution data.
Dependencies and credentials
Section titled “Dependencies and credentials”- No explicit credential or node dependency is declared in the node description.
Example workflow
Section titled “Example workflow”Connect Indexer to an AI agent or dependency input that accepts this dependency type, then run the agent with data from previous nodes.
Troubleshooting
Section titled “Troubleshooting”- Check that required settings are present before running the node.
- If the node uses browser page data, run it on the target tab after the page has loaded.
- If it calls an external service, verify credentials, permissions, and rate limits.
- This node has source tests; use them as the reference for edge-case behavior during maintenance.