import { Inject, Injectable } from '@nestjs/common';
import { ConfigService } from '@nestjs/config';
import type { Cache } from 'cache-manager';
import { createAiGateway } from 'ai-gateway-provider';
import { createAzure } from 'ai-gateway-provider/providers/azure';
import { wrapLanguageModel } from 'ai';
import { createHash } from 'crypto';
import { CACHE_MANAGER } from '@nestjs/cache-manager';
import { EnvironmentVariables } from 'src/system/config';

export enum AIModel {
  GPT_4_1 = 'GPT_4_1',
  GPT_5_1_MINI = 'GPT_5_1_MINI',
  GPT_5_2 = 'GPT_5_2',
  GPT_5 = 'GPT_5',
}

@Injectable()
export class VercelAIService {
  private readonly aiGateway: ReturnType<typeof createAiGateway>;
  private readonly azure: ReturnType<typeof createAzure>;
  private readonly deploymentNames: Record<AIModel, string>;

  constructor(
    private configService: ConfigService<EnvironmentVariables>,
    @Inject(CACHE_MANAGER) private readonly cacheManager: Cache,
  ) {
    // Initialize Cloudflare AI Gateway
    this.aiGateway = createAiGateway({
      accountId: this.configService.getOrThrow<string>(
        'CLOUDFLARE_AI_GATEWAY_ACCOUNT_ID',
      ),
      gateway: this.configService.getOrThrow<string>(
        'CLOUDFLARE_AI_GATEWAY_ID',
      ),
      apiKey: this.configService.getOrThrow<string>(
        'CLOUDFLARE_AI_GATEWAY_TOKEN',
      ),
    });

    // Initialize Azure OpenAI provider with Cloudflare AI Gateway
    this.azure = createAzure({
      resourceName: this.configService.getOrThrow<string>(
        'AZURE_OPENAI_RESOURCE_NAME',
      ),
      apiKey: this.configService.getOrThrow<string>('AZURE_OPENAI_API_KEY'),
      useDeploymentBasedUrls: true,
      apiVersion: this.configService.getOrThrow<string>(
        'AZURE_OPENAI_API_VERSION',
      ),
    });

    this.deploymentNames = {
      [AIModel.GPT_4_1]: this.configService.getOrThrow<string>(
        'AZURE_OPENAI_GPT41_DEPLOYMENT_NAME',
      ),
      [AIModel.GPT_5_1_MINI]: this.configService.getOrThrow<string>(
        'AZURE_OPENAI_GPT51_MINI_DEPLOYMENT_NAME',
      ),
      [AIModel.GPT_5_2]: this.configService.getOrThrow<string>(
        'AZURE_OPENAI_GPT52_DEPLOYMENT_NAME',
      ),
      [AIModel.GPT_5]: this.configService.getOrThrow<string>(
        'AZURE_OPENAI_GPT5_DEPLOYMENT_NAME',
      ),
    };
  }

  getModel(model: AIModel): ReturnType<typeof wrapLanguageModel> {
    const deploymentName =
      this.deploymentNames[model] || this.deploymentNames[AIModel.GPT_4_1];

    // Use .chat() for chat completions endpoint
    const baseModel = this.azure.chat(deploymentName);

    // Route through Cloudflare AI Gateway
    const gatewayModel = this.aiGateway(baseModel);
    return gatewayModel;
  }
}

{
  "error": {
    "code": "404",
    "message": "Resource not found"
  }
}

{
  "error": {
    "message": "Could not finish the message because max_tokens or model output limit was reached. Please try again with higher max_tokens.",
    "type": "invalid_request_error",
    "param": null,
    "code": null
  }
}

  const url = ({ path, modelId }: { path: string; modelId: string }) => {
    const baseUrlPrefix =
      options.baseURL ?? `https://${getResourceName()}.openai.azure.com/openai`;

    let fullUrl: URL;
    if (options.useDeploymentBasedUrls) {
      // Use deployment-based format for compatibility with certain Azure OpenAI models
      fullUrl = new URL(`${baseUrlPrefix}/deployments/${modelId}${path}`);
    } else {
      // Use v1 API format - no deployment ID in URL
      fullUrl = new URL(`${baseUrlPrefix}/v1${path}`);
    }

    fullUrl.searchParams.set('api-version', apiVersion);
    return fullUrl.toString();
  };