Exa (formerly Metaphor) Python SDK Guide-AI-powered content search tool.

Example

exa.search(query='Best practices for Python testing', use_autoprompt=True, num_results=5)

Scenario

This function performs a search query using Exa's neural search capabilities. It can be tailored with various options such as the number of results, specific domains to include or exclude, and date filters. For instance, a developer looking for the latest best practices in Python testing could use this function to retrieve up-to-date, high-quality articles. By setting `use_autoprompt=True`, the query is automatically optimized for better relevance.

Example

exa.find_similar(url='https://example.com/article-on-ai', num_results=3)

Scenario

The find_similar function retrieves content that is semantically similar to the content of a specified URL. This is particularly useful for content curators or marketers who want to explore related content to a popular or trending article. For example, a user who found an interesting article on AI can use this function to find other articles with similar themes or content.

Example

exa.contents(ids=['doc1', 'doc2'], text=True, highlights=True)

Scenario

This function retrieves the content and highlights of web pages based on document IDs. It is useful when a developer has already performed a search or find_similar query and wants to fetch detailed content for analysis or display purposes. For instance, after obtaining search results, the developer could use this function to pull the full text and key highlights from the top results to present a summarized view in an application.

Example

exa.search_and_contents(query='Latest trends in machine learning', text={'max_characters': 1000}, highlights={'num_sentences': 3})

Scenario

This combined function allows for performing a search and retrieving the content and highlights in a single API call. It's efficient for scenarios where both search results and their content are needed immediately. For example, a data scientist might use this function to quickly find and extract concise summaries of the latest machine learning trends from multiple sources, with both the content and highlights provided.

Example

exa.find_similar_and_contents(url='https://example.com/tech-news', text=True, highlights={'query': 'summary'})

Scenario

Similar to the search_and_contents function, this function finds similar content and retrieves their text and highlights in one go. It's ideal for users who want to explore related content to a given URL and simultaneously access the full text and summarized insights. For example, a content strategist could use this to find articles similar to a key piece of tech news and immediately obtain their most relevant portions.