"use strict";

import type { ExtensionAPI } from "@earendil-works/pi-coding-agent";
import { Type } from "typebox";
import { StringEnum } from "@earendil-works/pi-ai";
import { getConfig } from "../config";
import { processImage } from "../media";
import { visionCompletion } from "../client";
import { DATA_VIZ_ANALYSIS } from "../prompts";
import {
  DEFAULT_MAX_BYTES,
  DEFAULT_MAX_LINES,
  truncateHead,
} from "@earendil-works/pi-coding-agent";

export function registerAnalyzeDataVizTool(pi: ExtensionAPI) {
  pi.registerTool({
    name: "analyze_data_visualization",
    label: "Analyze Data Visualization",
    description:
      "Analyze charts, graphs, dashboards, and data visualizations. Extracts key metrics, identifies trends, anomalies, and patterns, and provides actionable recommendations. Supports local files (png, jpg) and HTTP(S) URLs.",
    promptSnippet: "Analyze charts/dashboards — extract metrics, trends, anomalies, recommendations",
    promptGuidelines: [
      "Use analyze_data_visualization when the user provides a chart, graph, dashboard, or data visualization and wants insights. Use the optional analysisFocus parameter ('trends', 'anomalies', 'comparison', 'summary', 'forecast') to guide the analysis angle.",
    ],
    parameters: Type.Object({
      imagePath: Type.String({
        description:
          "Path to the data visualization image (relative to cwd, supports @ prefix) or HTTP(S) URL.",
      }),
      prompt: Type.Optional(
        Type.String({
          description:
            "What should the AI focus on? Defaults to a comprehensive analysis.",
        })
      ),
      analysisFocus: Type.Optional(
        StringEnum([
          "trends",
          "anomalies",
          "comparison",
          "summary",
          "forecast",
        ] as const)
      ),
    }),
    async execute(_toolCallId, params, signal, onUpdate, ctx) {
      const config = getConfig();

      onUpdate?.({
        content: [{ type: "text", text: "正在调用 GLM-4.6V 分析数据可视化..." }],
      });

      const image = processImage(params.imagePath, ctx.cwd, config.maxImageSizeMB);

      let userPrompt =
        params.prompt ||
        "Analyze this data visualization and extract key metrics, trends, anomalies, and actionable recommendations.";
      if (params.analysisFocus) {
        userPrompt = `Analysis focus: ${params.analysisFocus}\n\n${userPrompt}`;
      }

      const result = await visionCompletion(
        config,
        DATA_VIZ_ANALYSIS,
        [image],
        userPrompt,
        signal
      );

      const truncated = truncateHead(result, {
        maxLines: DEFAULT_MAX_LINES,
        maxBytes: DEFAULT_MAX_BYTES,
      });

      let text = truncated.content;
      if (truncated.truncated) {
        text += `\n\n[输出已截断: ${truncated.outputLines}/${truncated.totalLines} 行]`;
      }

      return {
        content: [{ type: "text", text }],
        details: { raw: result },
      };
    },
  });
}