Concepts
Key concepts to understand how Linkup works
Overview
The Linkup /search endpoint allows you to discover and access relevant web content based on a natural language query. Once the content is retrieved, it can serve as factual grounding for Large Language Models (LLMs), helping them produce more accurate and informed responses.
Parameters
Query
Your query should be as specific as possible to improve the quality of the results. Consider providing additional context or constraints. For example:
| Initial Query | Improved Query | Explanation |
|---|---|---|
| What is the website of the company named 3B International? | What is the website of the French company named 3B International? | Adding the country (“French”) helps narrow down results, making it easier to identify the correct company. |
Depth
You can choose between two search depths, depending on your performance and accuracy needs:
standard: Returns results more quickly, suitable for low-latency scenarios.deep: Continues to search iteratively if it doesn’t find sufficient information on the first attempt. This may take longer, but often yields more comprehensive results.
When using deep, the system repeatedly evaluates whether it has found enough information. If not, it continues searching—potentially for tens of seconds—until it locates what it needs.
OutputType
The API supports several output formats to match different use cases:
sourcedAnswer: Returns a natural language answer with source attributions.searchResults: Provides chunks of contextual data suitable for grounding in LLM prompts.structured: Produces a response following a specified JSON schema, ideal for structured data extraction.