Data Types
🗺️ Website
Integrating Website Content into Your Search Agent
Incorporating entire websites into your search agent significantly enhances its ability to provide comprehensive and relevant search results. The add_website
method is designed to facilitate the seamless integration of web content, expanding the knowledge base of your agent with rich, web-based information.
Function Signature
The add_website
function provides a streamlined approach to ingesting content from specified websites, allowing your search agent to access and index web pages.
Parameters
- url (
Optional[str]
): The URL of the website to be added. This is the starting point for content integration. - system_prompt (
str
): An optional prompt to guide the system in processing website content. It can be used to specify instructions or objectives for the content retrieval process. - query_wrapper_prompt (
str
): An optional prompt to enhance the relevance of user queries by wrapping them. This can be particularly useful for tailoring the search experience based on the website’s content. - embed_model (
Union[str, EmbedType]
): Specifies the embedding model used for processing the website’s text content. The default setting uses a standard model optimized for web content. - llm_params (
dict
): Parameters for integrating Large Language Models, enhancing content understanding and processing. - vector_store_params (
dict
): Configuration parameters defining how and where the extracted content embeddings are stored. - service_context_params (
dict
): Additional parameters to customize the service context for the website content. - query_engine_params (
dict
): Customization parameters for the query engine, tailoring how search queries are processed and matched with the website content. - retriever_params (
dict
): Configuration for the document retriever component, influencing how web content is retrieved and indexed based on search queries.
Example Usage
Adding a Website
This example demonstrates how to add content from a website.