1. Defining the Action in UI Design

• Log in to the Kuika platform.
• Open the project you will be working on from the Apps screen.
• Go to the UI Design module and select the relevant screen.

2. Add Action

• Open the + ADD ACTION menu in the Properties panel on the right side.

• From the + ADD ACTION menu, add the Searching> Search action according to the desired trigger event (Initial Actions, OnClick, OnBlur, etc.).

3. Configure Action Parameters

• Search Type
  
  • Specifies the search type. One of the three options must be selected:
  • Vector Search: Vector Search converts the user's query and documents into multidimensional vectors and finds the closest content based on semantic similarity. With this method, even if the words used in the query do not appear in the document, content that is similar in meaning can be identified.
    
    • Example: The query ‘how to improve customer satisfaction’ may return a document titled ‘ways to improve user experience.’
  • Exact Vector Search: Exact Vector Search works similarly to Vector Search, but applies stricter threshold values to matches between the query and the document in order to increase accuracy. This ensures that only documents with very close (almost identical) semantic matches are returned as results.
    
    • Preferred for search scenarios that require greater precision and low error tolerance.
  • RAG Search: RAG Search finds the documents closest to the user's query using vector search and transfers these documents to an artificial intelligence model (e.g., OpenAI) to generate natural language responses.
  • This method does not just find documents; it also extracts meaning from them to produce rich and explanatory answers in a question-answer format.
• Query
  
  • The text to be searched.
  • Example: ‘Izmir’
• Limit
  
  • The maximum number of results to return.
  • Only applicable for Vector Search and Exact Vector Search.
  • If not specified, the default is 5 results.
• Collection Name (Optional)
  
  • The name of the specific collection to search.
  • If specified, the search is performed only in this collection.
  • If not specified, the search is performed in all collections.

Vector Search

• Purpose: Find documents containing the word ‘Izmir’ or similar expressions
• Search Type: Vector Search
• Query: ‘izmir’
• Limit: 5
• Results are sorted from closest to furthest.

Exact Vector Search

• Purpose: Find documents that contain the word “İzMir” exactly as written
• Search Type: Exact Vector Search
• Query: ‘İzMir’
• Limit: 5
• Case sensitivity must be taken into account.

RAG Search (Retrieval-Augmented Generation)

• Purpose: To obtain the most appropriate answer to a specific question, supported by documents
• Search Type: RAG Search
• Query: ‘What is the old name of İzmir?’
• This mode uses natural language processing (NLP) with OpenAI integration to generate responses.

• Dynamic Queries: The query value can be dynamically retrieved from sources such as user input or form inputs.
• Collection-Based Search: You can perform specific searches in separate collections rather than in the same dataset.
• RAG-powered Chatbot: You can create a document-based chatbot using RAG Search.

Technical Risks

• Incorrect Search Type: If the Search Type is selected incorrectly, appropriate results may not be returned.
• Incomplete Query Value: Empty queries may return errors or incomplete data.
• API Definition for RAG: If RAG Search is to be used, the Open AI configuration must be defined in the system.

Search Action enables you to build advanced information search and recommendation systems on the Kuika platform. Thanks to the AI-powered RAG (Retrieval-Augmented Generation) feature, natural language responses can be generated from relevant documents in response to user queries. In addition, Vector Search provides results based on semantic similarities, while methods such as Exact Search support classic, keyword-based information access. These classic methods are used to capture cases where specific words or phrases appear directly in documents. With all these capabilities, you can create smart and contextual search solutions that enrich the user experience.