/**
 * Agent Compiler — компилирует новых AI-агентов по техническому заданию через LLM
 * Автоматически определяет: модель, роль, системный промпт, инструменты, параметры LLM
 */
import { invokeLLM } from "./_core/llm";
import { getDb } from "./db";
import { agents } from "../drizzle/schema";
import { TOOL_REGISTRY } from "./tools";

export interface CompileAgentRequest {
  /** Техническое задание — описание что должен делать агент */
  specification: string;
  /** Имя агента (если не указано — LLM выберет) */
  name?: string;
  /** Провайдер LLM (ollama, openai, anthropic) */
  preferredProvider?: string;
  /** Предпочитаемая модель */
  preferredModel?: string;
  /** ID пользователя-владельца */
  userId: number;
}

export interface CompiledAgentConfig {
  name: string;
  description: string;
  role: string;
  model: string;
  provider: string;
  temperature: number;
  maxTokens: number;
  topP: number;
  frequencyPenalty: number;
  presencePenalty: number;
  systemPrompt: string;
  allowedTools: string[];
  allowedDomains: string[];
  maxRequestsPerHour: number;
  tags: string[];
  reasoning: string; // Объяснение почему такие параметры
}

export interface CompileAgentResult {
  success: boolean;
  config?: CompiledAgentConfig;
  agentId?: number;
  error?: string;
}

/**
 * Компилирует конфигурацию агента по ТЗ через LLM
 */
export async function compileAgentConfig(request: CompileAgentRequest): Promise<CompileAgentResult> {
  // Get available tools for context
  const availableTools = TOOL_REGISTRY.map(t => ({
    id: t.id,
    name: t.name,
    description: t.description,
    category: t.category,
    dangerous: t.dangerous,
  }));

  const systemPrompt = `You are an expert AI agent architect. Your task is to analyze a technical specification (ТЗ) and generate the optimal configuration for an AI agent.

Available tools that can be assigned to the agent:
${JSON.stringify(availableTools, null, 2)}

Available providers and models:
- ollama: llama3.2, llama3.1, mistral, codellama, deepseek-coder, phi3
- openai: gpt-4o, gpt-4o-mini, gpt-3.5-turbo
- anthropic: claude-3-5-sonnet, claude-3-haiku

Guidelines for configuration:
- temperature: 0.1-0.3 for precise/analytical tasks, 0.5-0.7 for balanced, 0.8-1.0 for creative
- maxTokens: 512-1024 for simple tasks, 2048-4096 for complex, 8192 for very long outputs
- topP: 0.9-1.0 for most tasks, lower for more focused outputs
- systemPrompt: detailed, specific, includes examples if helpful
- allowedTools: only tools the agent actually needs
- allowedDomains: specific domains if web access needed, empty array if not needed
- role: one of "developer", "researcher", "analyst", "writer", "executor", "monitor", "coordinator"

Return ONLY valid JSON with this exact structure (no markdown, no extra text):
{
  "name": "Agent Name",
  "description": "Brief description of what this agent does",
  "role": "developer|researcher|analyst|writer|executor|monitor|coordinator",
  "model": "model-name",
  "provider": "ollama|openai|anthropic",
  "temperature": 0.7,
  "maxTokens": 2048,
  "topP": 1.0,
  "frequencyPenalty": 0.0,
  "presencePenalty": 0.0,
  "systemPrompt": "Detailed system prompt for the agent...",
  "allowedTools": ["tool_id1", "tool_id2"],
  "allowedDomains": ["example.com"],
  "maxRequestsPerHour": 100,
  "tags": ["tag1", "tag2"],
  "reasoning": "Explanation of why these parameters were chosen"
}`;

  const userPrompt = `Technical Specification (ТЗ):
${request.specification}

${request.name ? `Preferred name: ${request.name}` : ""}
${request.preferredProvider ? `Preferred provider: ${request.preferredProvider}` : ""}
${request.preferredModel ? `Preferred model: ${request.preferredModel}` : ""}

Analyze this specification and generate the optimal agent configuration. Be specific and detailed in the systemPrompt.`;

  try {
    const response = await invokeLLM({
      messages: [
        { role: "system", content: systemPrompt },
        { role: "user", content: userPrompt },
      ],
      response_format: {
        type: "json_schema",
        json_schema: {
          name: "agent_config",
          strict: true,
          schema: {
            type: "object",
            properties: {
              name: { type: "string" },
              description: { type: "string" },
              role: { type: "string" },
              model: { type: "string" },
              provider: { type: "string" },
              temperature: { type: "number" },
              maxTokens: { type: "integer" },
              topP: { type: "number" },
              frequencyPenalty: { type: "number" },
              presencePenalty: { type: "number" },
              systemPrompt: { type: "string" },
              allowedTools: { type: "array", items: { type: "string" } },
              allowedDomains: { type: "array", items: { type: "string" } },
              maxRequestsPerHour: { type: "integer" },
              tags: { type: "array", items: { type: "string" } },
              reasoning: { type: "string" },
            },
            required: [
              "name", "description", "role", "model", "provider",
              "temperature", "maxTokens", "topP", "frequencyPenalty", "presencePenalty",
              "systemPrompt", "allowedTools", "allowedDomains", "maxRequestsPerHour",
              "tags", "reasoning"
            ],
            additionalProperties: false,
          },
        },
      },
    });

    const content = response.choices[0].message.content;
    const config = typeof content === "string" ? JSON.parse(content) : content;

    // Validate that allowedTools exist in registry
    const validToolIds = TOOL_REGISTRY.map(t => t.id);
    config.allowedTools = config.allowedTools.filter((id: string) => validToolIds.includes(id));

    return { success: true, config };
  } catch (error: any) {
    return {
      success: false,
      error: `Failed to compile agent: ${error.message}`,
    };
  }
}

/**
 * Деплоит скомпилированного агента в БД
 */
export async function deployCompiledAgent(
  config: CompiledAgentConfig,
  userId: number
): Promise<{ success: boolean; agentId?: number; error?: string }> {
  const db = await getDb();
  if (!db) return { success: false, error: "Database not available" };

  try {
    const [result] = await db.insert(agents).values({
      userId,
      name: config.name,
      description: config.description,
      role: config.role,
      model: config.model,
      provider: config.provider,
      temperature: String(config.temperature),
      maxTokens: config.maxTokens,
      topP: String(config.topP),
      frequencyPenalty: String(config.frequencyPenalty),
      presencePenalty: String(config.presencePenalty),
      systemPrompt: config.systemPrompt,
      allowedTools: config.allowedTools,
      allowedDomains: config.allowedDomains,
      maxRequestsPerHour: config.maxRequestsPerHour,
      tags: config.tags,
      metadata: { compiledFromSpec: true, reasoning: config.reasoning },
      isActive: true,
      isPublic: false,
    });

    return { success: true, agentId: (result as any).insertId };
  } catch (error: any) {
    return { success: false, error: error.message };
  }
}

/**
 * Полный цикл: компиляция + деплой
 */
export async function compileAndDeployAgent(
  request: CompileAgentRequest
): Promise<CompileAgentResult> {
  const compileResult = await compileAgentConfig(request);
  if (!compileResult.success || !compileResult.config) {
    return compileResult;
  }

  const deployResult = await deployCompiledAgent(compileResult.config, request.userId);
  if (!deployResult.success) {
    return { success: false, error: deployResult.error };
  }

  return {
    success: true,
    config: compileResult.config,
    agentId: deployResult.agentId,
  };
}