Sample Flows

This article presents possible use cases and corresponding sample flows. These can be a helpful jumping off point as you plan your implementation.

Power an AI assistant that answers Wix developer questions

A developer is building an AI coding assistant that answers questions about Wix APIs. When a user asks how to do something, the assistant searches the docs and uses the results as context to generate an accurate answer.

Prerequisites

Your app must be authorized to call the Igor Docs Search API.

Flows

Flow 1: Answer a question using the markdown endpoint

Use this flow when you want to pass search results directly to an LLM without additional processing.

1. When the user asks a question, extract a search term from it. For example, from "how do I create a product in Wix Stores?" extract "create a product".
2. Call Search Documents Markdown with the search term and the relevant document_type:
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3. Pass the returned content string directly as context to your LLM alongside the user's question.
4. If the LLM needs more detail about a specific method or article, use the "read more" URL from the hint appended to the truncated result to fetch the full content.

Flow 2: Search and select results using the JSON endpoint

Use this flow when you need programmatic control over which results to use — for example, to filter, re-rank, or display results in a UI.

1. Call Search Documents with the search term:
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2. Iterate over the returned results array. Each entry includes:
   • title — display name of the doc entry
   • content — truncated or full content depending on lines_in_each_result
   • url — link to the full documentation page
   • relevance_score — use this to filter out low-confidence results (e.g. below 0.5)
   • kb_name — identifies the source knowledge base (e.g. SDK_METHODS_KB_ID)
3. Filter results by relevance_score or kb_name as needed for your use case.
4. Pass the selected results as context to your LLM or display them in your UI.