Ways to Keep AI Knowledge Current with Tavily
Tavily's real-time search capability can effectively compensate for the lag in training data for large models:
- Dynamic knowledge updating: Obtain the latest web crawling results (e.g., tech trends, news events) through APIs, and generate time-sensitive answers by combining the reasoning power of the big model.
- Content Extraction Enhancement: Use
extractThe function directly obtains the complete content of the specified web page, ensuring accuracy of details. - Multi-disciplinary coverage: Financial data, academic papers, and other specialized fields are available through parameter adjustment.
Implementation of recommendations:
- Setting up caching mechanisms to balance real-time and API call costs
- Add confidence assessment to search results to avoid dissemination of unreliable information
- combining
include_images=TrueAccess to multimedia content enhances response richness
This answer comes from the articleTavily: Real-Time Information Search API Service for AIThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of outdated knowledge of large models?
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