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| # Changelog | ||
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| ## [0.1.0] | ||
| All notable changes to the `@kaibanjs/tools` package will be documented in this file. | ||
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| Initial experimental release of the tools package. | ||
| ## [0.4.1] - 2024-12-19 | ||
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| ### Features | ||
| ### Documentation | ||
| - Added missing README files for: | ||
| - Exa Search Tool | ||
| - Firecrawl Tool | ||
| - Updated main package README with improved tool listing | ||
| - Standardized documentation format across all tools | ||
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| - Basic tool package implementation | ||
| - Firecrawl tool integration | ||
| - Tavily tool integration | ||
| - Storybook playground for tools | ||
| - Basic testing suite per tool | ||
| - CI workflows for releasing and testing | ||
| ## [0.4.0] - 2024-12-19 | ||
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| ### Notes | ||
| ### Added | ||
| - Zapier Webhook Tool for workflow automation integration | ||
| - Make Webhook Tool for Make (formerly Integromat) integration | ||
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| - This is an experimental release | ||
| ## [0.3.0] - 2024-12-14 | ||
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| ### Added | ||
| - Simple RAG Tool for basic RAG implementations | ||
| - Website Search Tool for semantic website content search | ||
| - PDF Search Tool for document analysis | ||
| - Text File Search Tool for plain text processing | ||
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| ### Enhanced | ||
| - Added support for custom vector stores | ||
| - Improved documentation for all tools | ||
| - Added comprehensive examples in tool READMEs | ||
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| ## [0.2.0] - 2024-11-17 | ||
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| ### Added | ||
| - Serper Tool for Google Search API integration | ||
| - WolframAlpha Tool for computational queries | ||
| - Exa Search Tool for neural search capabilities | ||
| - GitHub Issues Tool for repository management | ||
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| ### Improved | ||
| - Enhanced error handling across all tools | ||
| - Better type definitions and input validation | ||
| - Updated documentation with more examples | ||
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| ## [0.1.0] - Initial Release | ||
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| ### Added | ||
| - Initial package setup | ||
| - Basic tool implementation structure | ||
| - Core utility functions | ||
| - Testing framework setup | ||
| - Documentation foundation |
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| # Exa Search Tool | ||
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| This tool integrates with Exa (https://exa.ai/), a search engine for AI that organizes the web using embeddings. It provides high-quality web data specifically optimized for AI applications, offering advanced search capabilities through neural and traditional keyword approaches. | ||
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| ## Components | ||
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| The tool uses the following components: | ||
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| - An Exa API client instance | ||
| - An API Key for authentication | ||
| - A custom HTTP client (ky) for making API requests | ||
| - Input validation using Zod schema | ||
| - Configurable search parameters | ||
| - Multiple search type options | ||
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| ## Key Features | ||
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| - Neural Search: Meaning-based search using embeddings | ||
| - Keyword Search: Traditional search capabilities | ||
| - Auto Search: Dynamically chooses between neural and keyword | ||
| - Category-focused search (company, research paper, news, github, tweet, etc.) | ||
| - Domain and text filtering | ||
| - Date-based filtering | ||
| - Configurable content retrieval options | ||
| - Support for autoprompt query enhancement | ||
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| ## Input | ||
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| The input should be a JSON object with a "query" field containing the search query to process. | ||
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| ## Output | ||
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| The output is the response from Exa's API containing search results based on the configured parameters and search type. | ||
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| ## Configuration Options | ||
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| - `type`: Search type ('neural', 'keyword', or 'auto') | ||
| - `useAutoprompt`: Enable query enhancement (for neural search) | ||
| - `numResults`: Number of results to return | ||
| - `category`: Focus on specific category | ||
| - `startPublishedDate`: ISO 8601 date for earliest publish date | ||
| - `endPublishedDate`: ISO 8601 date for latest publish date | ||
| - `includeDomains`: List of domains to include | ||
| - `excludeDomains`: List of domains to exclude | ||
| - `includeText`: Text/phrase to include in results | ||
| - `excludeText`: Text/phrase to exclude from results | ||
| - `startCrawlDate`: ISO 8601 date for earliest crawl date | ||
| - `endCrawlDate`: ISO 8601 date for latest crawl date | ||
| - `contents`: Configuration for content retrieval | ||
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| ## Example | ||
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| ```javascript | ||
| const tool = new ExaSearch({ | ||
| apiKey: 'your-api-key', | ||
| type: 'neural', | ||
| useAutoprompt: false, | ||
| numResults: 10, | ||
| category: 'company' | ||
| }); | ||
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| const result = await tool._call({ | ||
| query: 'AI companies focusing on natural language processing' | ||
| }); | ||
| ``` | ||
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| ## Advanced Example with Filters | ||
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| ```javascript | ||
| const tool = new ExaSearch({ | ||
| apiKey: process.env.EXA_API_KEY, | ||
| type: 'neural', | ||
| numResults: 20, | ||
| includeDomains: ['techcrunch.com', 'wired.com'], | ||
| startPublishedDate: '2023-01-01', | ||
| contents: { | ||
| text: { maxCharacters: 1000, includeHtmlTags: false }, | ||
| highlights: { numSentences: 3, highlightsPerUrl: 2 } | ||
| } | ||
| }); | ||
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| try { | ||
| const result = await tool._call({ | ||
| query: 'recent developments in quantum computing' | ||
| }); | ||
| console.log(result); | ||
| } catch (error) { | ||
| console.error('Error performing Exa search:', error); | ||
| } | ||
| ``` | ||
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| ### Disclaimer | ||
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| Ensure you have proper API credentials and respect Exa's usage terms and rate limits. Some features may require specific subscription tiers. |
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