/**
 * recall — metadata-only document search.
 * Never reads file content; returns title, filename, tags, description, and score.
 * Skill bundles (`<name>/SKILL.md`) are indexed as a single document per bundle.
 */

import { tool, type Tool, type ToolsProviderController } from "@lmstudio/sdk";
// @ts-ignore — zod/lib re-export chain breaks with NodeNext; runtime is fine
import { z } from "zod";
import type { IndexManager } from "../indexManager.js";
import { EmbeddingClient } from "../embeddings/embeddingClient.js";
import {
  checkEmbeddingCapability,
  type EmbeddingPrimerResult,
} from "../helpers/embeddingCapabilityPrimer.js";
import { formatToolMetaBlock } from "../helpers/pluginMeta.js";

// ── module-level cache ────────────────────────────────────────────────────────
let embeddingClient: EmbeddingClient | null = null;
let cachedCapabilityResult: EmbeddingPrimerResult | null = null;
let lastCapabilityCheckMs = 0;
const CAPABILITY_CHECK_INTERVAL_MS = 30_000;

function truncate(text: string, maxLength: number): string {
  return text.length > maxLength ? `${text.slice(0, maxLength)}…` : text;
}

export function createRecallTool(
  _ctl: ToolsProviderController,
  index: IndexManager
): Tool {
  return tool({
    name: "recall",
    description: `Search the playbook — the agent's persistent Markdown knowledge base of notes and skills.

Returns document metadata only (title, filename, tags, description, score), never full file contents.
Skill bundles (folders containing a SKILL.md with \`name\`/\`description\` frontmatter) are returned exactly like notes — one hit per bundle, with its description shown instead of a title-only summary.

Use this tool:
- At the start of complex or multi-step tasks
- Before advising on a topic you may have notes about
- When the user references something familiar but you're not certain about
- To check whether a note or skill already exists before writing a new one

Returns:
- Ranked list of matching documents with title, filename (relative path — may include a skill folder, e.g. "my-skill/SKILL.md"), tags, description, and relevance score (0–100)
- Documents below the configured minRecallScore are excluded

Examples:
- "project planning strategies" — finds notes about planning approaches
- "API authentication" — finds any notes on auth topics
- "Abendroutine" — also finds "evening routine" when semantic search is enabled

Follow up with read to retrieve the full text of any matching document (for a skill, read the SKILL.md hit first — it links to any companion files under its folder).

${formatToolMetaBlock()}`,
    parameters: {
      query: z.string().describe("Natural-language search query."),
      tags: z
        .array(z.string())
        .optional()
        .describe("Optional list of tags to filter by. Only documents that have ALL listed tags will be returned."),
    },
    implementation: async (args, ctx) => {
      const config = index.getConfig();
      const now = Date.now();

      // Check (or refresh) embedding capability every 30 s
      const needsCheck =
        !cachedCapabilityResult ||
        now - lastCapabilityCheckMs > CAPABILITY_CHECK_INTERVAL_MS ||
        embeddingClient?.getModelName() !== config.embeddingModel;

      if (needsCheck) {
        ctx.status("Checking embedding model availability...");
        cachedCapabilityResult = await checkEmbeddingCapability({
          modelId: config.embeddingModel,
          baseUrl: config.lmStudioBaseUrl,
        });
        lastCapabilityCheckMs = Date.now();

        if (cachedCapabilityResult.ready) {
          embeddingClient = new EmbeddingClient({
            baseUrl: config.lmStudioBaseUrl,
            model: cachedCapabilityResult.modelId,
          });
          index.setEmbeddingClient(embeddingClient);
        } else {
          embeddingClient = null;
          index.setEmbeddingClient(null);
        }
      }

      const docCount = index.getDocumentCount();
      ctx.status(`Searching ${docCount} documents...`);

      const results = await index.search(args.query, args.tags);

      const lines: string[] = [];

      if (results.length === 0) {
        lines.push("No documents found matching your query.");
      } else {
        lines.push(
          ...results.map((r) => {
            // Relative path (not basename) — skill bundles all share the filename "SKILL.md".
            const filename = index.toDisplayPath(r.filePath);
            const tagStr = r.tags.length > 0 ? ` [${r.tags.join(", ")}]` : "";
            const desc = r.description ? ` — ${truncate(r.description, 300)}` : "";
            return `- **${r.title}** (${filename})${tagStr}${desc} — score: ${r.score}`;
          })
        );
      }

      // Append capability warning when semantic search is degraded
      if (cachedCapabilityResult && !cachedCapabilityResult.ready && cachedCapabilityResult.userMessage) {
        lines.push("", cachedCapabilityResult.userMessage);
      } else if (cachedCapabilityResult?.userMessage && cachedCapabilityResult.messageSeverity === "info") {
        lines.push("", `_${cachedCapabilityResult.userMessage}_`);
      }

      return lines.join("\n");
    },
  });
}

/**
 * recall — metadata-only document search.
 * Never reads file content; returns title, filename, tags, description, and score.
 * Skill bundles (`<name>/SKILL.md`) are indexed as a single document per bundle.
 */

import { tool, type Tool, type ToolsProviderController } from "@lmstudio/sdk";
// @ts-ignore — zod/lib re-export chain breaks with NodeNext; runtime is fine
import { z } from "zod";
import type { IndexManager } from "../indexManager.js";
import { EmbeddingClient } from "../embeddings/embeddingClient.js";
import {
  checkEmbeddingCapability,
  type EmbeddingPrimerResult,
} from "../helpers/embeddingCapabilityPrimer.js";
import { formatToolMetaBlock } from "../helpers/pluginMeta.js";

// ── module-level cache ────────────────────────────────────────────────────────
let embeddingClient: EmbeddingClient | null = null;
let cachedCapabilityResult: EmbeddingPrimerResult | null = null;
let lastCapabilityCheckMs = 0;
const CAPABILITY_CHECK_INTERVAL_MS = 30_000;

function truncate(text: string, maxLength: number): string {
  return text.length > maxLength ? `${text.slice(0, maxLength)}…` : text;
}

export function createRecallTool(
  _ctl: ToolsProviderController,
  index: IndexManager
): Tool {
  return tool({
    name: "recall",
    description: `Search the playbook — the agent's persistent Markdown knowledge base of notes and skills.

Returns document metadata only (title, filename, tags, description, score), never full file contents.
Skill bundles (folders containing a SKILL.md with \`name\`/\`description\` frontmatter) are returned exactly like notes — one hit per bundle, with its description shown instead of a title-only summary.

Use this tool:
- At the start of complex or multi-step tasks
- Before advising on a topic you may have notes about
- When the user references something familiar but you're not certain about
- To check whether a note or skill already exists before writing a new one

Returns:
- Ranked list of matching documents with title, filename (relative path — may include a skill folder, e.g. "my-skill/SKILL.md"), tags, description, and relevance score (0–100)
- Documents below the configured minRecallScore are excluded

Examples:
- "project planning strategies" — finds notes about planning approaches
- "API authentication" — finds any notes on auth topics
- "Abendroutine" — also finds "evening routine" when semantic search is enabled

Follow up with read to retrieve the full text of any matching document (for a skill, read the SKILL.md hit first — it links to any companion files under its folder).

${formatToolMetaBlock()}`,
    parameters: {
      query: z.string().describe("Natural-language search query."),
      tags: z
        .array(z.string())
        .optional()
        .describe("Optional list of tags to filter by. Only documents that have ALL listed tags will be returned."),
    },
    implementation: async (args, ctx) => {
      const config = index.getConfig();
      const now = Date.now();

      // Check (or refresh) embedding capability every 30 s
      const needsCheck =
        !cachedCapabilityResult ||
        now - lastCapabilityCheckMs > CAPABILITY_CHECK_INTERVAL_MS ||
        embeddingClient?.getModelName() !== config.embeddingModel;

      if (needsCheck) {
        ctx.status("Checking embedding model availability...");
        cachedCapabilityResult = await checkEmbeddingCapability({
          modelId: config.embeddingModel,
          baseUrl: config.lmStudioBaseUrl,
        });
        lastCapabilityCheckMs = Date.now();

        if (cachedCapabilityResult.ready) {
          embeddingClient = new EmbeddingClient({
            baseUrl: config.lmStudioBaseUrl,
            model: cachedCapabilityResult.modelId,
          });
          index.setEmbeddingClient(embeddingClient);
        } else {
          embeddingClient = null;
          index.setEmbeddingClient(null);
        }
      }

      const docCount = index.getDocumentCount();
      ctx.status(`Searching ${docCount} documents...`);

      const results = await index.search(args.query, args.tags);

      const lines: string[] = [];

      if (results.length === 0) {
        lines.push("No documents found matching your query.");
      } else {
        lines.push(
          ...results.map((r) => {
            // Relative path (not basename) — skill bundles all share the filename "SKILL.md".
            const filename = index.toDisplayPath(r.filePath);
            const tagStr = r.tags.length > 0 ? ` [${r.tags.join(", ")}]` : "";
            const desc = r.description ? ` — ${truncate(r.description, 300)}` : "";
            return `- **${r.title}** (${filename})${tagStr}${desc} — score: ${r.score}`;
          })
        );
      }

      // Append capability warning when semantic search is degraded
      if (cachedCapabilityResult && !cachedCapabilityResult.ready && cachedCapabilityResult.userMessage) {
        lines.push("", cachedCapabilityResult.userMessage);
      } else if (cachedCapabilityResult?.userMessage && cachedCapabilityResult.messageSeverity === "info") {
        lines.push("", `_${cachedCapabilityResult.userMessage}_`);
      }

      return lines.join("\n");
    },
  });
}