
Ricerca Semantica nella Knowledgebase
Cerca e recupera facilmente informazioni da documenti della knowledgebase privata utilizzando la ricerca semantica alimentata dall'IA. Il flow espande le query ...

Il componente Cerca nella Memoria consente al tuo flusso di recuperare informazioni dalla memoria archiviata in base alle query degli utenti, supportando flussi di lavoro guidati dalla conoscenza e consapevoli del contesto.
Descrizione del componente
The Search Memory component is designed to retrieve relevant information from your workflow’s memory storage, often referred to as “Long Term Memory”. It takes a user query and searches stored documents or knowledge resources, returning the most related content. This is particularly useful for AI workflows that need to reference previous information, retrieve supporting documents, or provide context-aware responses.
| Input Name | Type | Required | Description | Default Value |
|---|---|---|---|---|
| Title | str | No | Title of the block in the output. | Related resources |
| Result limit | int | Yes | Number of results to return. | 3 |
| From pointer | bool | Yes | If true, loads from the best matching point in the document; otherwise, loads all. | true |
| Hide resources | bool | No | If true, hides the retrieved resources from output. | false |
| max_tokens | int | No | Maximum number of tokens in the output text. | 3000 |
| strategy | str | Yes | Strategy for aggregating content: “Concat documents, fill from first up to tokens limit” or “Include equal size from each document”. | Include equal size from each documents |
| threshold | float | No | Similarity threshold for retrieved results (0 to 1). | 0.8 |
| tool_description | str | No | Description for the tool, used by agents to understand its function. | (empty) |
| tool_name | str | No | Name for the tool in the agent. | (empty) |
| use_content | multi-select | No | Which content types to export (e.g., H1-H6, Paragraph). | All (H1-H6, Paragraph) |
| verbose | bool | No | Whether to print verbose output for debugging or insights. | false |
| Input Name | Type | Required | Description | Default Value |
|---|---|---|---|---|
| Lookup key | str | No | Key used to locate specific information in Long Term Memory. | (empty) |
| Input query | str | Yes | The search query to use in memory lookup. | (empty) |
The component provides multiple output formats to suit different needs:
| Output Name | Type | Description |
|---|---|---|
| documents | Message | Retrieved content as message(s) |
| documents_raw | Document | Raw, unprocessed document content |
| documents_as_tool | Tool | Documents formatted for use as a tool in agent workflows |
| Feature | Benefit |
|---|---|
| Query-based search | Finds the most relevant stored information for any user query |
| Output options | Choose between message, raw document, or tool formats |
| Custom retrieval | Control over number of results, similarity threshold, and content |
| Integrates with AI | Ideal for AI agents needing dynamic access to stored knowledge |
This component is a versatile building block for any AI workflow that requires memory search, document retrieval, or contextual augmentation.
Potenzia le tue soluzioni AI integrando la ricerca e il recupero della memoria. Connettiti alla conoscenza a lungo termine e offri risposte più intelligenti.

Cerca e recupera facilmente informazioni da documenti della knowledgebase privata utilizzando la ricerca semantica alimentata dall'IA. Il flow espande le query ...

Questo workflow potenziato dall'IA estrae informazioni specifiche da un Google Doc e le approfondisce effettuando ricerche su fonti come Google Search, Wikipedi...

Dai ai tuoi agenti FlowHunt una memoria persistente in tutti i workflow. Scopri come creare nodi di memoria manualmente e come lasciare che gli agenti leggano e...
Consenso Cookie
Usiamo i cookie per migliorare la tua esperienza di navigazione e analizzare il nostro traffico. See our privacy policy.