import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { SystemMessage, HumanMessage } from '@langchain/core/messages';
import type { FastifyBaseLogger } from 'fastify';
import { createReactAgent } from '@langchain/langgraph/prebuilt';
import type { HarnessEvent, SubagentChunkEvent, SubagentThinkingEvent } from '../harness-events.js';
import { getToolLabel } from '../tool-labels.js';
import type { MCPClientConnector } from '../mcp-client.js';
import type { WorkspaceManager } from '../../workspace/workspace-manager.js';
import type { ToolRegistry } from '../../tools/tool-registry.js';
import type { MCPToolInfo } from '../../tools/mcp/mcp-tool-wrapper.js';
import { WikiLoader, type SpawnContext } from './wiki-loader.js';

/** All platform tool names available to every subagent. */
const ALL_PLATFORM_TOOLS = ['SymbolLookup', 'GetChartData', 'GetTicker24h', 'WebSearch', 'FetchPage', 'ArxivSearch'];

/**
 * Streaming filter that strips triple-backtick fenced code blocks from text as it
 * arrives in chunks. Holds back at most 2 characters of look-ahead so normal text
 * streams through with no perceptible delay.
 */
class FenceFilter {
  private buf = '';
  private inFence = false;

  write(chunk: string): string {
    this.buf += chunk;
    return this.drain(false);
  }

  end(): string {
    return this.drain(true);
  }

  private drain(final: boolean): string {
    let out = '';
    while (true) {
      if (!this.inFence) {
        const start = this.buf.indexOf('```');
        if (start === -1) {
          const keep = final ? this.buf.length : Math.max(0, this.buf.length - 2);
          out += this.buf.slice(0, keep);
          this.buf = this.buf.slice(keep);
          break;
        }
        out += this.buf.slice(0, start);
        const headerEnd = this.buf.indexOf('\n', start + 3);
        if (headerEnd === -1 && !final) {
          this.buf = this.buf.slice(start);
          break;
        }
        this.inFence = true;
        this.buf = headerEnd !== -1 ? this.buf.slice(headerEnd + 1) : '';
      } else {
        const end = this.buf.indexOf('```');
        if (end === -1) {
          this.buf = final ? '' : this.buf.slice(Math.max(0, this.buf.length - 2));
          break;
        }
        this.inFence = false;
        const closingEnd = this.buf.indexOf('\n', end + 3);
        this.buf = closingEnd !== -1 ? this.buf.slice(closingEnd + 1) : this.buf.slice(end + 3);
      }
    }
    // Collapse blank lines left where code blocks were removed
    return out.replace(/\n{3,}/g, '\n\n');
  }
}

export interface SpawnInput {
  agentName: string;
  instruction: string;
  mcpClient?: MCPClientConnector;
  availableMCPTools?: MCPToolInfo[];
  workspaceManager?: WorkspaceManager;
  signal?: AbortSignal;
}

/**
 * SpawnService creates isolated subagent invocations on demand.
 *
 * Each call to streamSpawn():
 * 1. Loads the agent's wiki page (frontmatter + body)
 * 2. Builds a SystemMessage from base prompt + agent body + static imports
 * 3. Loads dynamic imports as a HumanMessage prefix (never cached)
 * 4. Resolves tools from the frontmatter tool lists
 * 5. Creates a fresh createReactAgent and streams events
 *
 * This replaces the old per-subagent BaseSubagent pattern with a stateless
 * factory that reads configuration from markdown frontmatter.
 */
export class SpawnService {
  constructor(
    private readonly wikiLoader: WikiLoader,
    private readonly toolRegistry: ToolRegistry,
    private readonly modelFn: (maxTokens?: number) => Promise<BaseChatModel>,
    private readonly logger: FastifyBaseLogger,
  ) {}

  /**
   * Stream events from a subagent invocation.
   * Yields HarnessEvents (subagent_chunk, subagent_thinking, subagent_tool_call).
   * Returns the final text result (or JSON with images when spawnsImages is set).
   */
  async *streamSpawn(input: SpawnInput): AsyncGenerator<HarnessEvent, string> {
    const { agentName, instruction, mcpClient, availableMCPTools, workspaceManager, signal } = input;

    this.logger.info({ agentName, instruction: instruction.substring(0, 100) }, 'SpawnService: starting');

    // Load agent wiki page
    const agentPage = await this.wikiLoader.loadAgentPage(agentName);
    const fm = agentPage.frontmatter;

    // Build SpawnContext for virtual pages
    const ctx: SpawnContext = { mcpClient, workspaceManager };

    // Load base prompt (index.md + tools.md) — stable, tier-1 cacheable
    const basePrompt = await this.wikiLoader.getBasePrompt();

    // Load static imports (appended to agent body, tier-2 cacheable together)
    const staticImports = fm.static_imports?.length
      ? await this.wikiLoader.loadStaticImports(fm.static_imports)
      : '';

    // Build the static SystemMessage (base + agent body + static imports)
    const staticContent = [basePrompt, agentPage.body, staticImports]
      .filter(Boolean)
      .join('\n\n---\n\n');
    const systemMessage = new SystemMessage(staticContent);

    // Load dynamic imports (never cached, injected as a HumanMessage prefix)
    const dynamicContent = fm.dynamic_imports?.length
      ? await this.wikiLoader.loadDynamicImports(fm.dynamic_imports, ctx)
      : '';

    // Build HumanMessage: dynamic context (if any) + instruction
    const humanContent = dynamicContent
      ? `${dynamicContent}\n\n---\n\n${instruction}`
      : instruction;
    const humanMessage = new HumanMessage(humanContent);

    // Set up image capture array (per-call, not shared mutable state)
    const imageCapture: Array<{ data: string; mimeType: string }> = [];

    const onImage = fm.spawnsImages
      ? (img: { data: string; mimeType: string }) => imageCapture.push(img)
      : undefined;

    const onWorkspaceMutation = workspaceManager
      ? (storeName: string, newState: unknown) => {
          workspaceManager.setState(storeName, newState).catch((err: Error) => {
            this.logger.error({ err, storeName }, 'Failed to sync workspace after spawn mutation');
          });
        }
      : undefined;

    // All subagents get all platform tools and all MCP tools.
    // Per-agent tool restrictions via frontmatter are no longer used.
    const tools = await this.toolRegistry.resolveTools(
      ALL_PLATFORM_TOOLS,
      ['*'],
      mcpClient,
      availableMCPTools,
      workspaceManager,
      onImage,
      onWorkspaceMutation,
    );

    this.logger.info(
      { agentName, toolCount: tools.length, toolNames: tools.map(t => t.name) },
      'SpawnService: tools resolved'
    );

    // Create model (respecting per-agent maxTokens)
    const model = await this.modelFn(fm.maxTokens);

    // Create a fresh ReactAgent for this invocation
    const agent = createReactAgent({
      llm: model,
      tools,
      prompt: systemMessage,
    });

    const recursionLimit = fm.recursionLimit ?? 30;

    // Emit an initial indicator so the UI shows the subagent has started
    yield { type: 'subagent_tool_call', agentName, toolName: 'Thinking...', label: 'Thinking...' };

    const stream = agent.stream(
      { messages: [humanMessage] },
      { streamMode: ['messages', 'updates'], recursionLimit, signal }
    );

    let finalText = '';
    const fenceFilter = new FenceFilter();

    for await (const [mode, data] of await stream) {
      if (signal?.aborted) break;

      if (mode === 'messages') {
        for (const chunk of SpawnService.extractStreamChunks(data, agentName)) {
          const filtered = fenceFilter.write(chunk.content);
          if (filtered) yield { ...chunk, content: filtered };
        }
      } else if (mode === 'updates') {
        if ((data as any).agent?.messages) {
          for (const msg of (data as any).agent.messages as any[]) {
            if (msg.tool_calls?.length) {
              for (const tc of msg.tool_calls) {
                yield {
                  type: 'subagent_tool_call',
                  agentName,
                  toolName: tc.name,
                  label: getToolLabel(tc.name),
                };
              }
            } else {
              const content = SpawnService.extractFinalText(msg);
              if (content) finalText = content;
            }
          }
        }
      }
    }

    const tail = fenceFilter.end();
    if (tail) yield { type: 'subagent_chunk', agentName, content: tail };

    this.logger.info(
      { agentName, textLength: finalText.length, imageCount: imageCapture.length },
      'SpawnService: finished'
    );

    // If this agent captures images, return JSON with text + images
    if (fm.spawnsImages && imageCapture.length > 0) {
      return JSON.stringify({ text: finalText, images: imageCapture });
    }

    return finalText;
  }

  /**
   * Extract subagent_chunk / subagent_thinking events from a LangGraph `messages` stream datum.
   * Only processes AIMessageChunks — ToolMessages (identified by tool_call_id) are skipped
   * because their content is raw tool result data, not agent narrative text.
   */
  static extractStreamChunks(
    data: unknown,
    agentName: string,
  ): Array<SubagentChunkEvent | SubagentThinkingEvent> {
    const msg = Array.isArray(data) ? (data as unknown[])[0] : data;
    // ToolMessages have tool_call_id; AIMessageChunks don't — skip tool results
    if ((msg as any)?.tool_call_id != null) return [];
    const content = (msg as any)?.content;
    if (typeof content === 'string') {
      return content ? [{ type: 'subagent_chunk', agentName, content }] : [];
    }
    if (Array.isArray(content)) {
      const chunks: Array<SubagentChunkEvent | SubagentThinkingEvent> = [];
      for (const block of content as any[]) {
        if (block?.type === 'thinking' && typeof block.thinking === 'string' && block.thinking) {
          chunks.push({ type: 'subagent_thinking', agentName, content: block.thinking });
        } else if (block?.type === 'text' && typeof block.text === 'string' && block.text) {
          chunks.push({ type: 'subagent_chunk', agentName, content: block.text });
        }
      }
      return chunks;
    }
    return [];
  }

  /**
   * Extract the final text from an `updates`-mode agent message.
   */
  static extractFinalText(msg: any): string {
    if (typeof msg?.content === 'string') return msg.content;
    if (Array.isArray(msg?.content)) {
      return (msg.content as any[])
        .filter((b: any) => b?.type === 'text' && typeof b.text === 'string')
        .map((b: any) => b.text as string)
        .join('');
    }
    return '';
  }
}