docs/versioned_docs/version-1.10.0/Components/memory-base.mdx
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A memory base is a per-flow vector store that automatically ingests conversation messages after each flow run. The Memory Base component retrieves context from a memory base attached to the current flow using semantic search. The most relevant conversation chunks are returned as a DataFrame.
| Name | Display Name | Info |
|---|---|---|
memory_base | Memory Base | Input parameter. Select the memory base to search. Only memory bases attached to the current flow are listed. Click the refresh button to reload the list after creating a new memory base. |
search_query | Search Query | Input parameter. The query string used for semantic retrieval. If empty, no results are returned. Supports tool mode for agent use. |
top_k | Top K Results | Input parameter. Number of top results to return. Default: 5. |
include_metadata | Include Metadata | Input parameter. Whether to include chunk metadata (session ID, sender, timestamp, and so on) on each output row. Default: enabled. |
filter_by_session | Filter by Session | Input parameter. If enabled, only chunks from the current session_id are returned. Disable to search across all sessions ingested into this memory base, which is useful for cross-conversation recall. Default: enabled. |
The output is a DataFrame named Results where each row represents one matching memory chunk.
When Include Metadata is enabled, each row also contains fields such as session_id, sender, sender_name, and timestamp.
When a search query is provided, each row includes a _score field with the similarity score.
For more information, see Manage memory bases.