Chroma integration

Store embeddings with their documents and metadata in Chroma, the open-source vector database, and run similarity searches for your AI flows. Works with Chroma Cloud and self-hosted servers.

AI Developer tools0 triggers · 7 actions

Connect Chroma free See what you can automate

Build it by describing it

Type a sentence like this and the copilot builds, validates and simulates the workflow.

Every morning, read yesterday's new leads from my form, and for each one “Query Collection (similarity search)” in Chroma.

Simulated before it goes live
Fixes proposed when something breaks
One credit per run

Actions

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DO
Query Collection (similarity search)
Finds the records most similar to an embedding, optionally filtered by metadata or document text.
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Add or Upsert Records
Saves records (ID, embedding, and optionally document text and metadata) in a Chroma collection. Upsert updates records whose ID already exists.
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Get Records
Gets records from a Chroma collection by their IDs, or all records that match a metadata filter.
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Count Records
Returns how many records a Chroma collection has.
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List Collections
Lists the collections in your Chroma database with their IDs.
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Create Collection
Creates a collection in your Chroma database, or returns the existing one with the same name.
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Custom Chroma API Request
Makes a request to any endpoint of the Chroma HTTP API v2, for example /heartbeat or /tenants/{tenant}/databases. Your credentials are added automatically and are only sent to your Chroma URL. Be careful: this request can also delete data.