/**
 * React Hooks for LLM & Grafana Integration
 *
 * Usage:
 *   import { useChat, useLLMMetrics } from '@/lib/hooks';
 *
 *   function ChatComponent() {
 *     const { messages, send, isLoading } = useChat();
 *     // ...
 *   }
 */

import { useState, useCallback, useRef, useEffect } from 'react';

export interface Message {
  role: 'system' | 'user' | 'assistant';
  content: string;
}

export interface UseChatOptions {
  model?: 'reasoning' | 'ornith:35b' | 'qwen2.5:3b-instruct';
  systemPrompt?: string;
  onError?: (error: Error) => void;
}

export interface UseChatReturn {
  messages: Message[];
  send: (content: string) => Promise<void>;
  isLoading: boolean;
  error: Error | null;
  clear: () => void;
}

/**
 * Chat hook with streaming support
 */
export function useChat(options: UseChatOptions = {}): UseChatReturn {
  const { model = 'reasoning', systemPrompt, onError } = options;

  const [messages, setMessages] = useState<Message[]>(
    systemPrompt ? [{ role: 'system', content: systemPrompt }] : []
  );
  const [isLoading, setIsLoading] = useState(false);
  const [error, setError] = useState<Error | null>(null);
  const abortRef = useRef<AbortController | null>(null);

  const send = useCallback(
    async (content: string) => {
      const userMessage: Message = { role: 'user', content };
      setMessages((prev) => [...prev, userMessage]);
      setIsLoading(true);
      setError(null);

      abortRef.current = new AbortController();

      try {
        const response = await fetch('/api/chat', {
          method: 'POST',
          headers: { 'Content-Type': 'application/json' },
          body: JSON.stringify({
            model,
            messages: [...messages, userMessage],
            stream: true,
          }),
          signal: abortRef.current.signal,
        });

        if (!response.ok) {
          throw new Error(`API error: ${response.status}`);
        }

        const reader = response.body?.getReader();
        if (!reader) throw new Error('No response body');

        const decoder = new TextDecoder();
        let assistantContent = '';

        // Add placeholder assistant message
        setMessages((prev) => [...prev, { role: 'assistant', content: '' }]);

        while (true) {
          const { done, value } = await reader.read();
          if (done) break;

          const text = decoder.decode(value, { stream: true });
          const lines = text.split('\n').filter((line) => line.startsWith('data: '));

          for (const line of lines) {
            const data = line.slice(6);
            if (data === '[DONE]') break;

            try {
              const parsed = JSON.parse(data);
              if (parsed.content) {
                assistantContent += parsed.content;
                setMessages((prev) => {
                  const updated = [...prev];
                  updated[updated.length - 1] = {
                    role: 'assistant',
                    content: assistantContent,
                  };
                  return updated;
                });
              }
            } catch {
              // Skip malformed chunks
            }
          }
        }
      } catch (err) {
        if (err instanceof Error && err.name !== 'AbortError') {
          setError(err);
          onError?.(err);
        }
      } finally {
        setIsLoading(false);
        abortRef.current = null;
      }
    },
    [messages, model, onError]
  );

  const clear = useCallback(() => {
    abortRef.current?.abort();
    setMessages(systemPrompt ? [{ role: 'system', content: systemPrompt }] : []);
    setError(null);
  }, [systemPrompt]);

  return { messages, send, isLoading, error, clear };
}

export interface LLMMetrics {
  podsReady: number;
  cpuByPod: Record<string, number>;
  memoryByPod: Record<string, number>;
}

/**
 * Metrics hook with auto-refresh
 */
export function useLLMMetrics(refreshInterval = 30000) {
  const [metrics, setMetrics] = useState<LLMMetrics | null>(null);
  const [isLoading, setIsLoading] = useState(true);
  const [error, setError] = useState<Error | null>(null);

  const fetchMetrics = useCallback(async () => {
    try {
      const response = await fetch('/api/metrics');
      if (!response.ok) throw new Error(`API error: ${response.status}`);
      const data = await response.json();
      setMetrics(data);
      setError(null);
    } catch (err) {
      setError(err instanceof Error ? err : new Error('Unknown error'));
    } finally {
      setIsLoading(false);
    }
  }, []);

  useEffect(() => {
    fetchMetrics();
    const interval = setInterval(fetchMetrics, refreshInterval);
    return () => clearInterval(interval);
  }, [fetchMetrics, refreshInterval]);

  return { metrics, isLoading, error, refresh: fetchMetrics };
}

/**
 * Grafana iframe embed component props generator
 */
export function useGrafanaEmbed(dashboardUid: string, panelId?: number) {
  const baseUrl = process.env.NEXT_PUBLIC_GRAFANA_URL || 'https://grafana.riotpiao.com';

  const dashboardUrl = `${baseUrl}/d/${dashboardUid}`;
  const embedUrl = panelId
    ? `${baseUrl}/d-solo/${dashboardUid}?panelId=${panelId}&from=now-6h&to=now&refresh=30s`
    : null;

  return {
    dashboardUrl,
    embedUrl,
    iframeProps: embedUrl
      ? {
          src: embedUrl,
          width: '100%',
          height: '400',
          frameBorder: 0,
          style: { border: 'none' },
        }
      : null,
  };
}