Add to Memory
The Add to Memory component enables storing documents or messages in long-term memory, tagged with lookup keys for future reference within your workflows.
Component description
How the Add to Memory component works
Add to Memory Component
The Add to Memory component is designed to enhance your AI workflow by enabling the storage of documents or messages in a long-term memory index. This is particularly useful for workflows that require context retention, knowledge management, or information retrieval across different stages or sessions.
What Does This Component Do?
This component takes an input document (such as a message or piece of data) and stores it in a long-term memory store. It also associates the document with a specific “lookup key,” which acts as a category or identifier for easier retrieval later. By indexing information in this way, your AI system can build up a persistent memory, which can be referenced in future processes or conversations.
Inputs
| Input Name | Type | Description | Required |
|---|---|---|---|
| Document to Index | Document | The main content (e.g., message, file, or text) to be added to long-term memory. | Yes |
| Lookup Key | Message | A text identifier used to categorize or label the document for efficient future retrieval. | Yes |
Details:
- Document to Index: This is the content you want to save for later use. It could be a user message, a knowledge article, or any structured document.
- Lookup Key: This string helps filter and find documents during future searches, acting as a tag or category.
Output
After adding the document to memory, the component produces an output:
| Output Name | Type | Description |
|---|---|---|
| After Memory Added | Message | Signals that the document has been successfully stored. |
This output can be used to trigger additional steps in your workflow, such as confirmation messages, further processing, or logging.
When Should You Use This Component?
- Building Conversational AI: Maintain continuity by remembering previous interactions.
- Knowledge Management: Store and organize facts, documents, or user inputs for later retrieval.
- Contextual Decision Making: Retain important information across different workflow stages.
Key Benefits
- Persistent Memory: Ensures important information is not lost between sessions.
- Efficient Retrieval: Lookup keys allow you to categorize and quickly filter stored documents.
- Flexible Integration: Can be seamlessly added to any AI workflow needing memory capabilities.
Summary Table
| Property | Value |
|---|---|
| Name | Add to Memory |
| Version | 1.0.0 |
| Inputs | Document, Lookup Key |
| Output | After Memory Added |
| Use Case | Long-term storage |
By using the Add to Memory component, you empower your AI systems with the ability to remember, organize, and re-use critical information, making your workflows smarter and more context-aware.
There are no examples of flow templates available at the moment using this component.
Frequently asked questions
- What does the Add to Memory component do?
It allows you to save documents or messages into long-term memory within your workflow, using a lookup key to categorize and easily retrieve data later.
- Why would I use a lookup key?
A lookup key helps organize saved information by category, making it easier to filter and find specific data when needed in future workflow steps.
- What type of data can be stored?
You can store documents or messages—such as user input, responses, or system data—using this component.
- Is the information stored permanently?
Data added with this component is stored for long-term use within your FlowHunt workflows, enabling advanced automations and context-aware interactions.
- Can I retrieve the saved information later in my flow?
Yes, you can access and use the stored data in subsequent workflow steps by referencing the associated lookup key.
Try FlowHunt Add to Memory
Enhance your workflows with persistent memory. Use the Add to Memory component to save and organize crucial data for smarter automations.
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