graph TD
    A[User Message] --> B[Task Classifier]
    B --> C{Task Type}
    C -->|Complex Reasoning| D[Claude 4 / GPT-4o]
    C -->|Code Generation| E[Claude 4 / Codestral]
    C -->|Translation| F[GPT-4o-mini / Gemini Flash]
    C -->|Simple Format| G[Haiku / Flash]
    D --> H[Apply Preset: System Prompt + Params]
    E --> H
    F --> H
    G --> H
    H --> I[Manage Context Window]
    I --> J[Stream Response]
    J --> K[Log Usage + Cost]

interface ModelConfig {
  provider: "openai" | "anthropic" | "google" | "ollama";
  model: string;
  maxTokens: number;
  costPer1kInput: number;
  costPer1kOutput: number;
  capabilities: string[];
}

const MODEL_REGISTRY: ModelConfig[] = [
  { provider: "anthropic", model: "claude-sonnet-4-20250514", maxTokens: 8192,
    costPer1kInput: 0.003, costPer1kOutput: 0.015, capabilities: ["reasoning", "code", "analysis"] },
  { provider: "openai", model: "gpt-4o-mini", maxTokens: 4096,
    costPer1kInput: 0.00015, costPer1kOutput: 0.0006, capabilities: ["general", "translation", "format"] },
  { provider: "google", model: "gemini-2.0-flash", maxTokens: 8192,
    costPer1kInput: 0.0001, costPer1kOutput: 0.0004, capabilities: ["general", "fast", "multimodal"] },
];

interface AssistantPreset {
  id: string;
  name: string;
  systemPrompt: string;
  temperature: number;
  preferredModels: string[];
  tags: string[];
}

class ChatRouter {
  constructor(private models: ModelConfig[], private presets: Map<string, AssistantPreset>) {}

  route(message: string, presetId?: string): { model: ModelConfig; preset?: AssistantPreset } {
    const preset = presetId ? this.presets.get(presetId) : undefined;
    const taskType = this.classifyTask(message);

    const candidates = this.models.filter(m =>
      m.capabilities.some(c => taskType.requiredCapabilities.includes(c))
    );

    const selected = candidates.sort((a, b) => a.costPer1kInput - b.costPer1kInput)[0];
    return { model: selected, preset };
  }

  private classifyTask(message: string): { type: string; requiredCapabilities: string[] } {
    const lower = message.toLowerCase();
    if (lower.includes("debug") || lower.includes("refactor") || lower.includes("architect"))
      return { type: "complex", requiredCapabilities: ["reasoning", "code"] };
    if (lower.includes("translate") || lower.includes("rewrite"))
      return { type: "simple", requiredCapabilities: ["general", "translation"] };
    return { type: "general", requiredCapabilities: ["general"] };
  }
}

class ConversationManager {
  private history: Array<{ role: string; content: string }> = [];
  private maxContextTokens: number;

  constructor(maxContextTokens: number = 100_000) {
    this.maxContextTokens = maxContextTokens;
  }

  addMessage(role: string, content: string): void {
    this.history.push({ role, content });
    this.trimToContextWindow();
  }

  getHistory(): Array<{ role: string; content: string }> {
    return [...this.history];
  }

  private trimToContextWindow(): void {
    while (this.estimateTokens() > this.maxContextTokens && this.history.length > 2) {
      this.history.splice(1, 1);
    }
  }

  private estimateTokens(): number {
    return this.history.reduce((sum, m) => sum + Math.ceil(m.content.length / 4), 0);
  }
}