LetsTryGPT/agent4-implementation

1/**2 * Type definitions for LLM API responses3 * Eliminates 'as any' casts and provides type safety4 */5 6/**7 * Standard LLM API response structure (OpenAI-compatible format)8 * Used by: Mistral, DeepSeek, OpenRouter, Codestral9 */10export interface LLMResponse {11  id?: string;12  object?: string;13  created?: number;14  model?: string;15  choices: Array<{16    index?: number;17    message: {18      role: string;19      content: string;20    };21    finish_reason?: string;22    logprobs?: unknown;23  }>;24  usage?: {25    prompt_tokens: number;26    completion_tokens: number;27    total_tokens: number;28  };29}30 31/**32 * Hugging Face API response structure33 */34export interface HuggingFaceResponse {35  generated_text?: string;36  error?: string;37  [key: string]: unknown;38}39 40/**41 * LLM generation options42 */43export interface LLMOptions {44  max_tokens?: number;45  temperature?: number;46  top_p?: number;47  top_k?: number;48  frequency_penalty?: number;49  presence_penalty?: number;50  stop?: string | string[];51  stream?: boolean;52  n?: number;53  logit_bias?: Record<string, number>;54  user?: string;55  [key: string]: unknown; // Allow provider-specific options56}57 58/**59 * Provider configuration60 */61export interface ProviderConfig {62  apiKey: string;63  model: string;64  apiUrl: string;65  timeout?: number;66  maxRetries?: number;67  headers?: Record<string, string>;68}69 70/**71 * Token usage information72 */73export interface TokenUsage {74  promptTokens: number;75  completionTokens: number;76  totalTokens: number;77}78 79/**80 * Response parser utility81 */82export class ResponseParser {83  /**84   * Extract content from standard LLM response85   */86  static extractContent(response: LLMResponse): string {87    return response.choices?.[0]?.message?.content || '';88  }89 90  /**91   * Extract content from Hugging Face response92   */93  static extractHuggingFaceContent(response: HuggingFaceResponse | HuggingFaceResponse[]): string {94    if (Array.isArray(response)) {95      return response[0]?.generated_text || '';96    }97    return response.generated_text || '';98  }99 100  /**101   * Extract token usage from response102   */103  static extractUsage(response: LLMResponse): TokenUsage | null {104    if (!response.usage) {105      return null;106    }107 108    return {109      promptTokens: response.usage.prompt_tokens,110      completionTokens: response.usage.completion_tokens,111      totalTokens: response.usage.total_tokens,112    };113  }114 115  /**116   * Validate response has required fields117   */118  static isValidResponse(response: unknown): response is LLMResponse {119    if (!response || typeof response !== 'object') {120      return false;121    }122 123    const resp = response as Partial<LLMResponse>;124    return (125      Array.isArray(resp.choices) &&126      resp.choices.length > 0 &&127      typeof resp.choices[0]?.message?.content === 'string'128    );129  }130 131  /**132   * Validate Hugging Face response133   */134  static isValidHuggingFaceResponse(response: unknown): response is HuggingFaceResponse {135    if (!response) {136      return false;137    }138 139    if (Array.isArray(response)) {140      return response.length > 0 && typeof response[0]?.generated_text === 'string';141    }142 143    const resp = response as Partial<HuggingFaceResponse>;144    return typeof resp.generated_text === 'string';145  }146}147 148/**149 * Request builder utility150 */151export class RequestBuilder {152  /**153   * Build standard chat completion request154   */155  static buildChatRequest(model: string, prompt: string, options: LLMOptions = {}): object {156    const { max_tokens = 1024, temperature = 0.7, top_p = 1.0, ...otherOptions } = options;157 158    return {159      model,160      messages: [{ role: 'user', content: prompt }],161      max_tokens,162      temperature,163      top_p,164      ...otherOptions,165    };166  }167 168  /**169   * Build Hugging Face request170   */171  static buildHuggingFaceRequest(prompt: string, options: LLMOptions = {}): object {172    const {173      max_tokens = 1024,174      temperature = 0.7,175      top_p = 1.0,176      top_k = 50,177      ...otherOptions178    } = options;179 180    return {181      inputs: prompt,182      parameters: {183        max_new_tokens: max_tokens,184        temperature,185        top_p,186        top_k,187        return_full_text: false,188        ...otherOptions,189      },190    };191  }192}193