Keyword Search Node Documentation
The Keyword Search Node is designed to search for specific keywords within a Vector Database.
Features
Key Functionalities
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Dynamic Search Query Input: Allows for customizable search queries using dynamic placeholders like
{{triggerNode_1.output.topic}}. -
Vector Database Selection: Provides an option to select a specific vector database for efficient retrieval of information.
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Boost Properties: Enables users to prioritize specific attributes for search results by activating the boost properties option.
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Result Limitation: Allows limiting the number of search results returned with a configurable limit.
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Grouping of Similar Results: Supports grouping similar search results based on configurable distance thresholds.
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Filters Integration: Lets users apply filters for more refined search results.
Benefits
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Customizability: Dynamic query capabilities ensure search inputs can adapt to varying workflows and datasets.
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Relevance: Boost properties and grouping enhance the quality of search results, ensuring higher relevance.
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Scalability: Seamless integration with vector databases supports large-scale and complex applications.
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Efficiency: Configurable limits and filters save resources by optimizing the retrieval process.
What can I build?
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Create a dynamic search interface within your application to query a vector database.
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Develop a personalized recommendation system by combining keyword search and vector-based similarity.
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Build real-time search capabilities with grouped and filtered results for enhanced user experience.
Setup
Select the Keyword Search Node
- Fill in the required parameters.
- Build the desired flow
- Deploy the Project
- Click Setup on the workflow editor to get the automatically generated instruction and add it in your application.
Configuration Reference
| Parameter | Description | Example Value |
|---|---|---|
| Search Query | Input the query to search the vector database. | Tell me something about Bali |
| Vector DB | Select the vector database to be queried. | Database |
| Boost Properties | Specific properties can be boosted by a factor specified as a number | True/False |
| Limit | Number of results to return | 3 |
| Group Similar Distance upto N Jumps | Automatically groups and limits search results by detecting significant gaps in similarity scores. When N > 0, the function will include results until it finds N large differences in scores between consecutive results. This helps filter out less relevant results that are notably different from the top matches. | 0 |
| Filters | Apply JSON-based filters to refine search results. | [] |
Low-Code Example
nodes:
nodes:
- nodeId: fullTextSearchNode_335
nodeType: fullTextSearchNode
nodeName: Keyword Search
values:
searchQuery: '{{triggerNode_1.output.topic}}'
vectorDB: ''
limit: '3'
boostProperties: false
autocut: '0'
filters: ''
needs:
- triggerNode_1Troubleshooting
Common Issues
| Problem | Solution |
|---|---|
| Dynamic Content Not Loaded | Increase the Wait for Page Load time in the configuration. |
Debugging
- Check Lamatic Flow logs for error details.
- Verify API Key.