Integrate Web Search Capabilities

This skill extends AI assistants with search capabilities by integrating text search, vector search, Bing, Google, Brave, and Azure AI Search into the Semantic Kernel framework. It enables assistants to retrieve real-time information from the web and enterprise knowledge bases, transforming static AI models into dynamic, information-retrieval systems.

Use this skill when your AI assistant needs to answer questions requiring current information beyond its training data, such as recent news, product availability, or live documentation. Deploy it when building research assistants, customer support bots that need to query knowledge bases, or any application where grounding responses in external data sources improves accuracy.

Do not use this skill if your use case requires only static, pre-trained knowledge or if search latency would degrade user experience in time-critical applications. Avoid it when your data is fully contained within the model's context window and does not require external retrieval.

Users provide search queries as text strings to the assistant. The skill processes these queries through the configured search provider (Brave, Google, Bing, or Azure AI Search) and returns search results that the AI assistant can then synthesize into natural language responses. The integration works as a plugin within the Semantic Kernel architecture.

Brave Text Search: Integrates Brave's privacy-focused search engine as a plugin, demonstrated in brave_text_search_as_plugin.py.

Google Text Search: Connects Google's search capabilities as a plugin for web-scale information retrieval, shown in google_text_search_as_plugin.py.

Bing: Provides access to Microsoft Bing search services for text-based queries.

Azure AI Search: Enables vector search and text search against Azure's enterprise search service for private knowledge bases and indexed content.

This skill serves Python developers building AI applications with Semantic Kernel who need to augment language models with real-time search capabilities. It is designed for engineers creating chatbots, research tools, or enterprise assistants that must retrieve and synthesize information from web sources or private search indexes. Teams working with Azure ecosystems will find the Azure AI Search integration particularly valuable for connecting assistants to proprietary data.