/** * Exa API Provider — Neural search + Code context * * Exa (formerly Metaphor) uses a neural search model that finds pages * by semantic similarity rather than keyword matching. Great for * "find me articles about X concept" when keyword search fails. * * Two capabilities: * - search_semantic: neural search across the web * - search_code_context: codebases, docs, StackOverflow, GitHub issues * * Pricing (as of 2026): ~$1 per 1000 searches + embedding cost for content. * Free tier: 1000 queries/month. * * https://docs.exa.ai */ export interface ExaSearchResult { title: string; url: string; publishedDate?: string; author?: string; text?: string; highlights?: string[]; score?: number; } export interface ExaSearchResponse { results: ExaSearchResult[]; autopromptString?: string; resolvedSearchType?: string; } interface ExaSearchBody { query: string; type: 'neural' | 'auto' | 'keyword'; numResults: number; contents?: { text?: boolean | { maxCharacters?: number; }; highlights?: boolean | { numSentences?: number; }; }; category?: 'company' | 'research paper' | 'news' | 'github' | 'tweet' | 'personal site' | 'linkedin profile' | 'financial report'; startPublishedDate?: string; endPublishedDate?: string; includeDomains?: string[]; excludeDomains?: string[]; } /** * Neural semantic search — finds pages by concept, not keywords. * Better than Brave/Google for "find me articles about approaches to X" style queries. */ export declare function exaNeuralSearch(apiKey: string, query: string, maxResults?: number, options?: { category?: ExaSearchBody['category']; includeDomains?: string[]; excludeDomains?: string[]; includeText?: boolean; }): Promise; /** * Code-context search — optimized for codebases, docs, StackOverflow, GitHub issues. * Uses the "github" category + neural search for best code-related retrieval. */ export declare function exaCodeSearch(apiKey: string, query: string, maxResults?: number): Promise; export {}; //# sourceMappingURL=exa.d.ts.map