One Interface, Three Search Backends: Web Search Is Just Another Repository
If you build anything with LLMs, you will need web search sooner or later. The model's training data is frozen; your users' questions are not. In Solon AI, web search is not a special subsystem bolted onto the side. It is a Repository — the same interface a vector store implements, the same interface an in-memory document list implements. That single design decision is the whole story of the…
Solon AI introduces a single interface for web search, unifying various search backends under one Repository design. The primary method, `search(String query)`, accepts a user query and returns a list of documents. Two optional methods, `search(QueryCondition condition)` and `promptAugment(String query)`, allow for more advanced search functionality.
The interface is deliberately small and easily extensible, with no provider or API key information required. Three implementations demonstrate different philosophies: Bocha follows a simple JSON-based approach, Baidu adapts to Baidu's AI Search V2 endpoint with two modes (basic and AI), and Tavily offers a comprehensive set of operations for more advanced search and retrieval capabilities.
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