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VectorAI DB uses standard transport status codes and the Python SDK maps them to typed exceptions. Catch specific exceptions when you can, and use VectorAIError as the application-level catch-all.

Python SDK exceptions

The current Python SDK exposes these exception classes for common application handling.

Catch specific exceptions

Use the namespaced SDK APIs in examples and production code. Collections live under client.collections, and vector search lives under client.points.

Create a collection idempotently

Catch CollectionExistsError to skip creation when a collection is already present.

Retry transient failures

Use exponential backoff for retryable errors. The helper functions understand SDK exception types, including ConnectionError, RateLimitError, and TimeoutError.

Inspect error details

Every SDK exception exposes message, code, details, and operation where available. Use these fields for logging and custom handling.

Common error messages

Cause: The collection name is misspelled, or the collection was deleted.Fix: Call client.collections.list() to verify the collection exists before operating on it.
Cause: The query vector or inserted vector has a different number of dimensions than the collection configuration.Fix: Confirm the embedding model and collection dimensions match.
Cause: The server has authentication enabled but the client did not supply a valid access token.Fix: Pass the configured token to VectorAIClient or set ACTIAN_VECTORAI_ACCESS_TOKEN.
Cause: VectorAI DB is not running, is still starting, or is unreachable at the configured address.Fix: Confirm the server is reachable at localhost:6574 or set ACTIAN_VECTORAI_URL.

Next steps

Troubleshooting

Diagnose connection, search, and startup issues.

Python SDK

Get started with the Python SDK.