@clduab11/gemini-flow/src/adapters/gemini-adapter.ts

Revolutionary AI agent swarm coordination platform with Google Services integration, multimedia processing, and production-ready monitoring. Features 8 Google AI services, quantum computing capabilities, and enterprise-grade security.

/**
 * Gemini Adapter Implementation
 * TDD approach - proper implementation for Google Gemini models
 */

import {
  BaseModelAdapter,
  ModelRequest,
  ModelResponse,
  StreamChunk,
  ModelCapabilities,
  AdapterConfig,
} from "./base-model-adapter.js";

export interface GeminiAdapterConfig extends AdapterConfig {
  projectId?: string;
  location?: string;
}

export class GeminiAdapter extends BaseModelAdapter {
  constructor(config: GeminiAdapterConfig) {
    super(config);
  }

  async initialize(): Promise<void> {
    // Initialize Gemini API client
    this.isInitialized = true;
    this.logger.info("Gemini adapter initialized");
  }

  getModelCapabilities(): ModelCapabilities {
    return {
      textGeneration: true,
      codeGeneration: true,
      multimodal: true,
      streaming: true,
      functionCalling: true,
      longContext: true,
      reasoning: true,
      multiAgent: false,
      complexProblemSolving: true,
      chainOfThought: true,
      maxTokens: 1000000,
      supportedLanguages: ["en", "es", "fr", "de", "ja", "ko", "zh"],
      inputTypes: ["text", "image", "audio", "video"],
      outputTypes: ["text"],
    };
  }

  async generate(request: ModelRequest): Promise<ModelResponse> {
    this.ensureInitialized();

    const startTime = performance.now();
    const context = this.ensureRequestId(request.context);

    try {
      // Transform request for Gemini API
      const transformedRequest = this.transformRequest(request);

      // Mock response for TDD
      const mockResponse = {
        id: context.requestId!,
        content: `Gemini response to: ${request.prompt}`,
        model: this.config.modelName,
        timestamp: new Date(),
        latency: performance.now() - startTime,
        usage: {
          promptTokens: request.prompt.length / 4,
          completionTokens: 50,
          totalTokens: request.prompt.length / 4 + 50,
        },
        cost: this.calculateCost(
          { totalTokens: request.prompt.length / 4 + 50 },
          0.000001,
        ),
        finishReason: "stop",
      };

      this.logPerformance("generate", mockResponse.latency, true);
      return mockResponse;
    } catch (error) {
      const latency = performance.now() - startTime;
      this.logPerformance("generate", latency, false);
      throw this.handleError(error, request);
    }
  }

  async *generateStream(
    request: ModelRequest,
  ): AsyncIterableIterator<StreamChunk> {
    this.ensureInitialized();

    const context = this.ensureRequestId(request.context);

    // Mock streaming response
    const chunks = [
      `Gemini `,
      `streaming `,
      `response `,
      `to: ${request.prompt}`,
    ];

    for (let i = 0; i < chunks.length; i++) {
      yield {
        id: `${context.requestId}-${i}`,
        content: chunks.slice(0, i + 1).join(""),
        delta: chunks[i],
        finishReason: i === chunks.length - 1 ? "stop" : undefined,
      };

      // Simulate streaming delay
      await new Promise((resolve) => setTimeout(resolve, 100));
    }
  }

  async validateRequest(request: ModelRequest): Promise<boolean> {
    if (!request.prompt || request.prompt.trim().length === 0) {
      throw this.createError("Prompt is required", "INVALID_REQUEST");
    }

    if (request.prompt.length > 1000000) {
      throw this.createError(
        "Prompt exceeds maximum length",
        "PROMPT_TOO_LONG",
      );
    }

    return true;
  }

  protected transformRequest(request: ModelRequest): any {
    return {
      contents: [
        {
          parts: [
            {
              text: request.prompt,
            },
          ],
        },
      ],
      generationConfig: {
        temperature: request.parameters?.temperature || 0.9,
        topP: request.parameters?.topP || 1,
        topK: request.parameters?.topK || 1,
        maxOutputTokens: request.parameters?.maxTokens || 8192,
      },
      systemInstruction: request.systemMessage
        ? {
            parts: [{ text: request.systemMessage }],
          }
        : undefined,
    };
  }

  protected transformResponse(
    response: any,
    request: ModelRequest,
  ): ModelResponse {
    return {
      id: this.generateRequestId(),
      content: response.candidates?.[0]?.content?.parts?.[0]?.text || "",
      model: this.config.modelName,
      timestamp: new Date(),
      latency: 0,
      usage: {
        promptTokens: response.usageMetadata?.promptTokenCount || 0,
        completionTokens: response.usageMetadata?.candidatesTokenCount || 0,
        totalTokens: response.usageMetadata?.totalTokenCount || 0,
      },
      cost: 0,
      finishReason: response.candidates?.[0]?.finishReason || "stop",
    };
  }

  protected handleError(error: any, request: ModelRequest): never {
    const adapterError = this.createError(
      error.message || "Gemini API error",
      error.code || "GEMINI_ERROR",
      error.status || 500,
      error.code === "RATE_LIMIT_EXCEEDED" || error.code === "QUOTA_EXCEEDED",
    );

    throw adapterError;
  }
}