import { 
  FlatFormatter, 
  personPreset
} from 'ollama-middleware';

class ProfileGeneratorUseCase extends BaseAIUseCase {
  protected readonly systemMessage = `You are a professional profile creator.
  
IMPORTANT: Respond with ONLY valid JSON following this schema:
{
  "name": "Person name",
  "title": "Professional title", 
  "summary": "Brief professional overview",
  "skills": "Key skills and expertise",
  "achievements": "Notable accomplishments"
}`;

  // Use FlatFormatter and presets for rich context building
  protected formatUserMessage(prompt: any): string {
    const { person, preferences, guidelines } = prompt;
    
    const contextSections = [
      // Use preset for structured data
      personPreset.formatForLLM(person, "## PERSON INFO:"),
      
      // Use FlatFormatter for custom structures
      `## PREFERENCES:\n${FlatFormatter.flatten(preferences, {
        format: 'bulleted',
        keyValueSeparator: ': '
      })}`,
      
      // Format guidelines with FlatFormatter
      `## GUIDELINES:\n${FlatFormatter.flatten(
        guidelines.map(g => ({ 
          guideline: g,
          priority: "MUST FOLLOW" 
        })),
        {
          format: 'numbered',
          entryTitleKey: 'guideline',
          ignoredKeys: ['guideline']
        }
      )}`
    ];
    
    return contextSections.join('\n\n');
  }
  
  protected createResult(content: string, usedPrompt: string, thinking?: string): MyResult {
    return {
      generatedContent: content,
      model: this.modelConfig.name,
      usedPrompt,
      thinking,
      profile: JSON.parse(content)
    };
  }
}

// Use it
const profileGen = new ProfileGeneratorUseCase();
const result = await profileGen.execute({ 
  prompt: { 
    person: { name: "Alice", occupation: "Engineer" },
    preferences: { tone: "professional", length: "concise" },
    guidelines: ["Highlight technical skills", "Include leadership"]
  },
  authToken: "optional-token"
});

import { TweetGeneratorUseCase } from 'ollama-middleware';

const tweetGenerator = new TweetGeneratorUseCase();

const result = await tweetGenerator.execute({
  prompt: 'The importance of clean code in software development'
});

console.log(result.tweet);          // Generated tweet
console.log(result.characterCount); // Character count
console.log(result.withinLimit);    // true if ≤ 280 chars

protected getParameterOverrides(): ModelParameterOverrides {
  return {
    num_predict: 70,        // Limit to ~280 characters
    temperatureOverride: 0.7,
    repeatPenalty: 1.3,
    frequencyPenalty: 0.3,
    presencePenalty: 0.2,
    topP: 0.9,
    topK: 50,
    repeatLastN: 32
  };
}

import { JsonCleanerService, JsonCleanerFactory } from 'ollama-middleware';

// Simple usage (async - uses new recipe system with fallback)
const result = await JsonCleanerService.processResponseAsync(malformedJson);
console.log(result.cleanedJson);

// Legacy sync method (still works)
const cleaned = JsonCleanerService.processResponse(malformedJson);

// Advanced: Quick clean with automatic recipe selection
const result = await JsonCleanerFactory.quickClean(malformedJson);
console.log('Success:', result.success);
console.log('Confidence:', result.confidence);
console.log('Changes:', result.totalChanges);

import { RecipeTemplates } from 'ollama-middleware';

const conservativeRecipe = RecipeTemplates.conservative();
const aggressiveRecipe = RecipeTemplates.aggressive();
const adaptiveRecipe = RecipeTemplates.adaptive();

const flat = FlatFormatter.flatten({ name: 'Alice', age: 30 });

import { RequestFormatterService } from 'ollama-middleware';

const prompt = {
  context: { genre: 'sci-fi', tone: 'dark' },
  instruction: 'Write an opening'
};

const formatted = RequestFormatterService.formatUserMessage(
  prompt, (s) => s, 'MyUseCase'
);
// Outputs: ## CONTEXT:\ngenre: sci-fi\ntone: dark\n\n## INSTRUCTION:\nWrite an opening

// Automatically logged for all use cases:
// - Execution time
// - Token usage (input/output)
// - Generation speed (tokens/sec)
// - Parameters used

import { logger } from 'ollama-middleware';

logger.info('Operation completed', {
  context: 'MyService',
  metadata: { userId: 123, duration: 150 }
});

import { getModelConfig } from 'ollama-middleware';

// MODEL1_NAME is required in .env or will throw error
const config = getModelConfig('MODEL1');
console.log(config.name);     // Value from MODEL1_NAME env variable
console.log(config.baseUrl);  // Value from MODEL1_URL or default localhost

import { BaseAIUseCase, ModelParameterOverrides } from 'ollama-middleware';

class MyUseCase extends BaseAIUseCase<MyRequest, MyResult> {
  protected getParameterOverrides(): ModelParameterOverrides {
    return {
      temperatureOverride: 0.8,      // Control creativity vs. determinism
      repeatPenalty: 1.3,             // Reduce word repetition
      frequencyPenalty: 0.2,          // Penalize frequent words
      presencePenalty: 0.2,           // Encourage topic diversity
      topP: 0.92,                     // Nucleus sampling threshold
      topK: 60,                       // Vocabulary selection limit
      repeatLastN: 128                // Context window for repetition
    };
  }
}

import { ModelParameterManagerService } from 'ollama-middleware';

// Use curated presets for common use cases
const creativeParams = ModelParameterManagerService.getDefaultParametersForType('creative_writing');
const factualParams = ModelParameterManagerService.getDefaultParametersForType('factual');
const poeticParams = ModelParameterManagerService.getDefaultParametersForType('poetic');
const dialogueParams = ModelParameterManagerService.getDefaultParametersForType('dialogue');
const technicalParams = ModelParameterManagerService.getDefaultParametersForType('technical');
const marketingParams = ModelParameterManagerService.getDefaultParametersForType('marketing');