import { createGoogleGenerativeAI } from '@ai-sdk/google';
import { generateObject, generateText as aiGenerateText, embed, stepCountIs } from 'ai';
import { z } from 'zod';
import { AIProvider, TagSuggestion, TitleSuggestion, ToolUseOptions, ToolCallResult } from '../types';

export class GoogleProvider implements AIProvider {
  private model: any;
  private embeddingModel: any;

  constructor(apiKey: string, modelName: string = 'gemini-1.5-flash', embeddingModelName: string = 'text-embedding-004') {
    const google = createGoogleGenerativeAI({
      apiKey: apiKey,
    });

    this.model = google(modelName);
    this.embeddingModel = google.textEmbeddingModel(embeddingModelName);
  }

  async generateTags(content: string): Promise<TagSuggestion[]> {
    try {
      try {
        const { object } = await generateObject({
          model: this.model,
          schema: z.object({
            tags: z.array(z.object({
              tag: z.string().describe('Short tag name in lowercase'),
              confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
            }))
          }),
          prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
          Note content: "${content}"`,
        });

        return object.tags;
      } catch (err) {
        console.warn('Google generateObject tags failed, falling back to generateText:', err);
        const { text } = await aiGenerateText({
          model: this.model,
          prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
          Note content: "${content.substring(0, 1500)}"
          Return ONLY a JSON array of tag objects, like: [{"tag":"example","confidence":0.9}]`,
        });
        const cleaned = text.replace(/<think>[\s\S]*?<\/think>/gi, '').replace(/^```json\n?/, '').replace(/\n?```$/, '').trim();
        const parsed = JSON.parse(cleaned);
        const arr = Array.isArray(parsed) ? parsed : (parsed.tags || parsed.suggestions || []);
        return arr.map((t: any) => ({
          tag: t.tag || t.label || t.name || '',
          confidence: t.confidence || t.score || 0.7,
        }));
      }
    } catch (e) {
      console.error('Error generating tags (Google):', e);
      return [];
    }
  }

  async getEmbeddings(text: string): Promise<number[]> {
    try {
      const { embedding } = await embed({
        model: this.embeddingModel,
        value: text,
      });
      return embedding;
    } catch (e) {
      console.error('Error generating embeddings (Google):', e);
      throw e;
    }
  }

  async generateTitles(prompt: string): Promise<TitleSuggestion[]> {
    try {
      try {
        const { object } = await generateObject({
          model: this.model,
          schema: z.object({
            titles: z.array(z.object({
              title: z.string().describe('Suggested title'),
              confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
            }))
          }),
          prompt: prompt,
        });

        return object.titles;
      } catch (err) {
        console.warn('Google generateObject titles failed, falling back to generateText:', err);
        const { text } = await aiGenerateText({
          model: this.model,
          prompt: prompt + '\n\nRespond ONLY as a JSON array of title suggestions: [{"title": "Suggested title", "confidence": 0.9}]',
        });
        const cleaned = text.replace(/<think>[\s\S]*?<\/think>/gi, '').replace(/^```json\n?/, '').replace(/\n?```$/, '').trim();
        const parsed = JSON.parse(cleaned);
        const arr = Array.isArray(parsed) ? parsed : (parsed.titles || parsed.suggestions || []);
        return arr.map((t: any) => ({
          title: typeof t === 'string' ? t : t.title || t.name || '',
          confidence: typeof t === 'number' ? t : (t.confidence || t.score || 0.8),
        }));
      }
    } catch (e) {
      console.error('Error generating titles (Google):', e);
      return [];
    }
  }

  async generateText(prompt: string): Promise<string> {
    try {
      const { text } = await aiGenerateText({
        model: this.model,
        prompt: prompt,
      });

      return text.trim();
    } catch (e) {
      console.error('Error generating text (Google):', e);
      throw e;
    }
  }

  async chat(messages: any[], systemPrompt?: string): Promise<any> {
    try {
      const { text } = await aiGenerateText({
        model: this.model,
        system: systemPrompt,
        messages: messages,
      });

      return { text: text.trim() };
    } catch (e) {
      console.error('Error in chat (Google):', e);
      throw e;
    }
  }

  async generateWithTools(options: ToolUseOptions): Promise<ToolCallResult> {
    const { tools, maxSteps = 10, systemPrompt, messages, prompt } = options
    const opts: Record<string, any> = {
      model: this.model,
      tools,
      stopWhen: stepCountIs(maxSteps),
    }
    if (systemPrompt) opts.system = systemPrompt
    if (messages) opts.messages = messages
    else if (prompt) opts.prompt = prompt

    const result = await aiGenerateText(opts as any)
    return {
      toolCalls: result.toolCalls?.map((tc: any) => ({ toolName: tc.toolName, input: tc.input })) || [],
      toolResults: result.toolResults?.map((tr: any) => ({ toolName: tr.toolName, input: tr.input, output: tr.output })) || [],
      text: result.text,
      steps: result.steps?.map((step: any) => ({
        text: step.text,
        toolCalls: step.toolCalls?.map((tc: any) => ({ toolName: tc.toolName, input: tc.input })) || [],
        toolResults: step.toolResults?.map((tr: any) => ({ toolName: tr.toolName, input: tr.input, output: tr.output })) || []
      })) || []
    }
  }

  getModel() {
    return this.model;
  }
}