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Memories are structured pieces of information extracted from content. They feed into knowledge graphs and enable semantic retrieval for AI agents.

What is a Memory?

A memory contains:
  • Content: the extracted information
  • Metadata: additional context and tags
  • Entities: extracted people, places, technologies
  • Embeddings: semantic representations for search

Creating memories

From text

From files

From videos

Extracts:
  • Spoken dialogue (transcription)
  • Visual context (on-screen content)
  • Text (slides, captions)
  • Temporal information

Memory lifecycle

  1. Creation: Add via API or upload files
  2. Indexing: Entities extracted, graph built, embeddings created
  3. Retrieval: Search by semantic meaning and graph connections
  4. Updates: New content extends the knowledge graph
  5. Deletion: Remove when no longer needed

Use cases

User preferences

Conversation history

Knowledge bases

Best practices

  • Add rich metadata for better filtering
  • Use clear, self-contained content
  • Organize related memories in the same space
  • Include entity relationships in content
  • Update when information changes

Next steps

Search

Search memories semantically

Knowledge Graphs

Understand entity connections

SDK: Memories

SDK documentation