User preference memory strategy

The UserPreferenceMemoryStrategy is designed to automatically identify and extract user preferences, choices, and styles from conversational data. This lets your agent to learn from interactions and builds a persistent, dynamic profile of each user over time.

Steps in the strategy

The user preference strategy includes the following steps:

• Extraction – Identifies useful insights from short-term memory to place into long-term memory as memory records.

• Consolidation – Determines whether to write useful information to a new record or an existing record.

Note

The user preference strategy processes only USER and ASSISTANT role messages during extraction. For more information about roles in agent conversations, see Conversational.

Strategy output

The user preference strategy returns JSON objects with context, preference, and categories, making it easier to capture user choices and decision patterns.

Examples of insights captured by this strategy include:

• A customer's preferred shipping carrier or shopping brand.

• A developer's preferred coding style or programming language.

• A user's communication preferences, such as a formal or informal tone.

By leveraging this strategy, your agent can deliver highly personalized experiences, such as offering tailored recommendations, adapting its responses to a user's style, and anticipating needs based on past choices. This creates a more relevant and effective conversational experience.

Default namespace

/strategy/{memoryStrategyId}/actors/{actorId}