Gränssnitt | AILink

class HTMLLinkParseInterface

1 metod / 0 enums

// Interface for parsing and extracting links from HTML documents

// Should return JSON array of normalized url:s

class HTMLLinkParseInterface {
  static async parseLinks({
    url,
    html
  }) {}
}

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class HttpFetchInterface

1 metod / 0 enums

// Provides a fetch client mirroring the native global fetch interface directly.

class HttpFetchInterface {
  static async fetch({
    input,
    init
  }) {}
}

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class PerplexityRESTAPIInterface

3 metoder / 0 enums

// Standardized interface for REST-based access to the Perplexity API, supporting only the TEXT inference endpoint (/chat/completions). Requires an HttpFetchInterface implementation as a dependency for HTTP communication, and a model name must be supplied on every call.

class PerplexityRESTAPIInterface {
  async text({
    modelName
  }) {}
  getFetchInterface({}) {}
  setFetchInterface({
    fetchInterface
  }) {}
}

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class ProxyConfig

10 metoder / 1 enum

// Interface for managing Proxy settings including SOCKS5 and HTTP types, host, port, username, and password credentials. Provides methods to query and set properties needed for establishing network connections through an intermediary server.

class ProxyConfig {
  static get ProxyType() {
    return {
      SOCKS5: 'SOCKS5',
      HTTP: 'HTTP'
    };
  }
  getHost({}) {}
  setHost({
    host
  }) {}
  getPort({}) {}
  setPort({
    port
  }) {}
  getUsername({}) {}
  setUsername({
    username
  }) {}
  getPassword({}) {}
  setPassword({
    password
  }) {}
  getProxyType({}) {}
  setProxyType({
    type
  }) {}
}

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class SplinternetInterface

0 metoder / 0 enums

// Core interface representing the Splinternet boundaries, routing isolation, or decentralized networks.

class SplinternetInterface {}

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class XGBoostCodeGenServiceInterface

3 metoder / 1 enum

// Core service for generating high-performance standalone code (e.g. C, Python, JavaScript, or Java) from trained XGBoost model structures, enabling ultra-low latency prediction, compilation in embedded systems, or isolated container execution without requiring heavy ML framework dependencies.

class XGBoostCodeGenServiceInterface {
  static get CodeGenLanguage() {
    return {
      C: 'c',
      JAVASCRIPT: 'javascript',
      PYTHON: 'python',
      JAVA: 'java'
    };
  }
  async parseXGBoostModel({
    modelJson,
    options
  }) {}
  async generateSourceCode({
    modelSchema,
    targetLanguage,
    config
  }) {}
  async generatePredictionFunction({
    features,
    modelJson,
    targetLanguage
  }) {}
}

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