Keyword Search
The Keyword Search use case leverages AI to streamline information retrieval, reducing manual effort and improving accuracy. Using RAG, a vector database, and structured responses, it enables efficient keyword-based searches across large datasets. This ensures fast, relevant, and organized insights for users.
Key Features
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- RAG Implementation – Uses Retrieval-Augmented Generation (RAG) to enhance keyword search by retrieving relevant data and generating concise, AI-powered responses.
- Vector Database – Stores and manages vector embeddings for efficient retrieval of similar items in high-dimensional spaces, enabling accurate search across complex datasets.
- Structured Responses – Organizes search results into structured formats like tables, bullet points, or sections for better readability and quick comprehension.
Architecture
The process begins by creating a flow that implements Retrieval-Augmented Generation (RAG) using chunking and an index node. This step structures the data into manageable segments before storing it in a vector database, enabling efficient retrieval of relevant information when queried.
By leveraging this indexing approach, the system ensures that even large datasets can be searched and processed with high accuracy and speed.
In the next phase, a second flow is designed with an API Node as the trigger. This flow incorporates a Keyword Search Node to query the vector database, retrieving the most relevant information based on user inputs.
Finally, the API Response Node is modified to refine the output, ensuring that the retrieved data is structured and contextually relevant. This setup enables seamless integration with various applications, enhancing the accessibility and accuracy of AI-powered responses.
How it Works?
Tools used
- API Request Node.
- Keyword Search Node.
Benefits
1. RAG Response – Delivers AI-enhanced, contextually relevant answers by blending retrieval and generation. 2. Quick Response Time – Ensures fast information retrieval and processing for efficiency. 3. Quick Deployment – Easily integrates into workflows, reducing setup and implementation time.