ax-frontend-app/src/services/aiChatService.ts

/**
 * AI Chat Service
 *
 * Integrates with external AI platform API for chat completions.
 * Supports both streaming and non-streaming responses.
 *
 * API Documentation:
 * Configuration is read from the frontend environment.
 * - Supports text, file_url, and image_url content types
 *
 * @module services/aiChatService
 */

import { fetchWithTimeout } from '../utils/fetchWithTimeout';

/**
 * Message content types
 */
export type MessageContentType = 'text' | 'file_url' | 'image_url';

/**
 * Message content item (for multi-modal messages)
 */
export interface MessageContent {
  type: MessageContentType;
  text?: string;
  name?: string;
  url?: string;
}

/**
 * Chat message
 */
export interface ChatMessage {
  role: 'user' | 'assistant' | 'system';
  content: string | MessageContent[];
}

/**
 * Chat completion request
 */
export interface ChatCompletionRequest {
  /** Custom chat/conversation ID (e.g., user ID) */
  chatId: string;
  /** Whether to return streaming response */
  stream?: boolean;
  /** Whether to return intermediate process details */
  detail?: boolean;
  /** Chat messages */
  messages: ChatMessage[];
}

/**
 * Chat completion response (non-streaming)
 */
export interface ChatCompletionResponse {
  /** Response message content */
  content: string;
  /** Knowledge base references (if any) */
  references?: {
    title: string;
    url: string;
    snippet: string;
  }[];
  /** Process details (if detail=true) */
  details?: unknown;
}

/**
 * Configuration for AI Chat API
 */
interface AIChatConfig {
  apiUrl: string;
  apiKey: string;
}

/**
 * Get AI Chat configuration from environment variables
 */
const getAIChatConfig = (): AIChatConfig => {
  const isDevelopment = import.meta.env.DEV;
  return {
    apiUrl: isDevelopment
      ? import.meta.env.VITE_AI_API_URL
      : import.meta.env.VITE_AI_PROXY_URL,
    apiKey: isDevelopment ? import.meta.env.VITE_AI_API_KEY : '',
  };
};

const getAuthorizationHeaders = (apiKey: string): Record<string, string> => (
  apiKey ? { Authorization: `Bearer ${apiKey}` } : {}
);

/**
 * Send a chat completion request to AI platform
 *
 * @param request - Chat completion request
 * @returns Promise resolving to AI response
 * @throws {Error} When API call fails
 */
export const sendChatCompletion = async (
  request: ChatCompletionRequest
): Promise<ChatCompletionResponse> => {
  try {
    const config = getAIChatConfig();

    if (!config.apiUrl) {
      if (import.meta.env.PROD) {
        throw new Error('AI 服务未配置，请先配置服务端代理');
      }
      return mockChatCompletion(request);
    }

    const response = await fetchWithTimeout(config.apiUrl, {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json',
        ...getAuthorizationHeaders(config.apiKey),
      },
      body: JSON.stringify({
        chatId: request.chatId,
        stream: request.stream ?? false,
        detail: request.detail ?? false,
        messages: request.messages,
      }),
    });

    if (!response.ok) {
      const errorText = await response.text();
      throw new Error(`AI API error (${response.status}): ${errorText}`);
    }

    const data = await response.json();

    // Extract content from response
    // The actual response format may vary, adjust based on API documentation
    const content = data.choices?.[0]?.message?.content || data.content || data.response || '';

    return {
      content,
      references: data.references,
      details: data.details,
    };
  } catch (error) {
    throw new Error(
      'AI对话失败: ' + (error instanceof Error ? error.message : '未知错误'),
      { cause: error }
    );
  }
};

/**
 * Send a streaming chat completion request
 *
 * @param request - Chat completion request
 * @param onChunk - Callback for each chunk of streamed content
 * @returns Promise resolving when stream completes
 * @throws {Error} When API call fails
 */
export const sendStreamingChatCompletion = async (
  request: ChatCompletionRequest,
  onChunk: (chunk: string) => void
): Promise<void> => {
  try {
    const config = getAIChatConfig();

    if (!config.apiUrl) {
      if (import.meta.env.PROD) {
        throw new Error('AI 服务未配置，请先配置服务端代理');
      }
      const mockResponse = await mockChatCompletion(request);
      for (const chunk of mockResponse.content.split(' ')) {
        await new Promise((resolve) => setTimeout(resolve, 50));
        onChunk(chunk + ' ');
      }
      return;
    }

    const response = await fetchWithTimeout(config.apiUrl, {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json',
        ...getAuthorizationHeaders(config.apiKey),
      },
      body: JSON.stringify({
        ...request,
        stream: true,
      }),
    });

    if (!response.ok) {
      const errorText = await response.text();
      throw new Error(`AI API error (${response.status}): ${errorText}`);
    }

    // Process streaming response
    const reader = response.body?.getReader();
    if (!reader) {
      throw new Error('Response body is not readable');
    }

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

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

      if (done) break;

      buffer += decoder.decode(value, { stream: true });
      const lines = buffer.split('\n');
      buffer = lines.pop() || '';

      for (const line of lines) {
        if (line.trim() === '' || line.startsWith(':')) continue;
        
        if (line.startsWith('data: ')) {
          const data = line.slice(6);
          if (data === '[DONE]') continue;

          try {
            const json = JSON.parse(data);
            const content = json.choices?.[0]?.delta?.content || '';
            if (content) {
              onChunk(content);
            }
          } catch {
            // Failed to parse SSE data, skip this line
          }
        }
      }
    }
  } catch (error) {
    throw new Error(
      'AI流式对话失败: ' + (error instanceof Error ? error.message : '未知错误'),
      { cause: error }
    );
  }
};

/**
 * Mock chat completion for testing/fallback
 * Used when API key is not configured or API is unavailable
 *
 * @param request - Chat completion request
 * @returns Mock AI response
 */
const mockChatCompletion = async (
  request: ChatCompletionRequest
): Promise<ChatCompletionResponse> => {
  // Simulate network delay
  await new Promise((resolve) => setTimeout(resolve, 800));

  // Get the last user message
  const lastMessage = request.messages[request.messages.length - 1];
  const userContent =
    typeof lastMessage.content === 'string'
      ? lastMessage.content
      : lastMessage.content.find((c) => c.type === 'text')?.text || '';

  const lowerContent = userContent.toLowerCase();

  // Mock different responses based on content
  if (lowerContent.includes('生成') && (lowerContent.includes('报告') || lowerContent.includes('文档'))) {
    let reportType = '报告';
    if (lowerContent.includes('地质')) {
      reportType = '地质报告';
    } else if (lowerContent.includes('技术')) {
      reportType = '技术报告';
    } else if (lowerContent.includes('分析')) {
      reportType = '分析报告';
    }

    return {
      content: `好的，我已经为您准备了一份${reportType}。正在生成文档...`,
    };
  }

  if (lowerContent.includes('你好') || lowerContent.includes('hello')) {
    return {
      content: '您好！我是AI助手，很高兴为您服务。您可以让我帮您生成各种报告和文档。',
    };
  }

  // Default response
  return {
    content: `我理解您说的是："${userContent}"。这是一个模拟响应（后端 AI 服务未配置）。`,
  };
};

/**
 * Helper: Create a simple text message
 */
export const createTextMessage = (role: 'user' | 'assistant', text: string): ChatMessage => ({
  role,
  content: text,
});

/**
 * Helper: Create a multi-modal message with text and files
 */
export const createMultiModalMessage = (
  role: 'user',
  contents: MessageContent[]
): ChatMessage => ({
  role,
  content: contents,
});

/**
 * Export the AI chat service
 */
export const aiChatService = {
  sendChatCompletion,
  sendStreamingChatCompletion,
  createTextMessage,
  createMultiModalMessage,
};

export default aiChatService;