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Overview

In our knowledge graph service, an Environment acts as a logical container that isolates sources within a user’s workspace. This allows users to create and manage multiple knowledge graphs independently under the same account.

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Why Use Environments?

AI agents often interact with diverse and unrelated sets of information. Environments provide a clean way to separate these contexts, ensuring that data from one use case or project does not interfere with another. This is especially useful when:
  • Building independent knowledge graphs for different agents or domains
  • Running isolated queries and evaluations
  • Managing context-specific memory for AI workflows

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Key Characteristics

  • Isolation: Sources stored in one environment are not accessible from another. This guarantees clean separation of information.
  • Scoped Queries: All graph operations and queries are performed within the context of a specific environment.
  • Flexibility: Users can create as many environments as needed, allowing for fine-grained control over their memory architecture.

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Structure

Each environment has the following properties:
FieldTypeDescription
namestringUnique name of the environment (required)
descriptionstringOptional description providing context or purpose
Environment names must be unique across all of a user’s environments. Attempting to create another environment with the same name will result in an error.

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Relationship with Sources

Every source must be associated with exactly one environment. This ensures that all knowledge derived from a source is scoped correctly and remains isolated within its intended graph.