How To Add Memory To OpenAI Agents SDK

OpenAI Agents SDK supports agent definitions, tools, function calling, and multi-step workflows but does not provide durable cross-session memory, leaving developers to manage persistent user preferences, projects, and conversation history externally. Mem0 is presented as a dedicated, model-agnostic memory layer that stores concise, structured, identity-scoped facts rather than raw transcripts, retrieves only memories relevant to each request, and updates records as users’ preferences or goals evolve. The proposed integration calls Mem0 before an agent run to search for relevant memories and inject them into the agent context, then calls it afterward to extract and store useful information from the interaction. This approach aims to avoid the context limits, prompt bloat, duplication, latency, and maintenance burden associated with retaining recent chat history, storing full transcripts, or building custom vector-memory pipelines. Effective deployment requires stable user identifiers, curation to prevent low-value or conflicting memories, performance tuning for retrieval latency, and inclusion of relevant tool or external-system state, while Mem0 can be deployed through its hosted service or self-hosted infrastructure.

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