// Node 20 includes native fetch support

// AI Client with Failover Support
// Fallback shims for Probot runtime
const info = console.log
const warning = console.warn
const error = console.error
const debug: (...args: any[]) => void =
  process.env.LOG_LEVEL === 'debug' ? console.log.bind(console) : () => {}
const setFailed = (msg: string) => {
  // Throw instead of process.exit to avoid killing the Probot server
  throw new Error(msg)
}

import {
  ChatGPTAPI as AIClient,
  ChatGPTError as AIError,
  ChatMessage,
  SendMessageOptions
} from 'chatgpt'
import pRetry from 'p-retry'
import {AIOptions, Options} from './options'
import {TokenLimits} from './limits'
import {getTokenCount} from './tokenizer'
import {isGeneratedFile, logIgnoredFile} from './generated-filter'

import {sleep} from './utils'
import {Mutex} from 'async-mutex'

export interface Ids {
  parentMessageId?: string
  conversationId?: string
}

class TokenThrottler {
  private static usage: {timestamp: number; tokens: number}[] = []
  private static readonly WINDOW_MS = 60000
  private static readonly mutex = new Mutex()

  // Increased TPM limit to prevent self-throttling
  // Previous limit of 30,000 was too conservative for actual usage
  private static get LIMIT(): number {
    return 1000000 // 1M tokens per minute - much more realistic
  }

  static async throttle(estimatedTokens: number): Promise<void> {
    // CRITICAL: Wrap all state mutation in mutex to prevent race conditions
    await this.mutex.runExclusive(async () => {
      const now = Date.now()
      this.usage = this.usage.filter(u => now - u.timestamp < this.WINDOW_MS)

      const currentTokens = this.usage.reduce((sum, u) => sum + u.tokens, 0)
      const limit = this.LIMIT

      if (currentTokens + estimatedTokens > limit) {
        // Calculate wait time based on oldest entry
        const oldestTimestamp =
          this.usage.length > 0 ? this.usage[0].timestamp : now
        const waitTime = this.WINDOW_MS - (now - oldestTimestamp) + 1000
        info(
          `TPM Limit approaching (${currentTokens}/${
            limit
          } tokens used). Throttling for ${Math.round(waitTime / 1000)}s...`
        )

        // Release mutex while sleeping, then re-acquire
        this.mutex.release()
        await sleep(Math.max(waitTime, 1000))

        // Recursive call to re-check limits after sleep
        // No need to re-acquire as recursive call will acquire its own lock
        await this.throttle(estimatedTokens)
        return
      }

      this.usage.push({timestamp: Date.now(), tokens: estimatedTokens})
    })
  }
}

export class AllModelsFailedError extends Error {
  constructor() {
    super('All AI models failed after exhausting fallback chain')
    this.name = 'AllModelsFailedError'
  }
}

export class Bot {
  private api: AIClient | null = null
  private readonly options: Options
  private readonly aiOptions: AIOptions
  private currentModel: string
  private fallbackModels: string[]

  constructor(
    options: Options,
    aiOptions: AIOptions,
    fallbackModels?: string[]
  ) {
    this.options = options
    this.aiOptions = aiOptions
    this.currentModel = aiOptions.model

    // Setup fallback chain based on tier
    if (fallbackModels) {
      this.fallbackModels = fallbackModels.filter(m => m !== this.currentModel)
    } else if (Options.FREE_TIER_MODELS.includes(this.currentModel)) {
      this.fallbackModels = Options.FREE_TIER_MODELS.filter(
        m => m !== this.currentModel
      )
    } else if (Options.HEAVY_MODELS.includes(this.currentModel)) {
      this.fallbackModels = Options.HEAVY_MODELS.filter(
        m => m !== this.currentModel
      )
    } else {
      this.fallbackModels = Options.LIGHT_MODELS.filter(
        m => m !== this.currentModel
      )
    }

    this.initClient()
  }

  getCurrentModel(): string {
    return this.currentModel
  }

  private initClient(): void {
    const apiKey = process.env.OPENROUTER_API_KEY || process.env.AI_API_KEY
    if (apiKey) {
      const currentDate = new Date().toISOString().split('T')[0]
      const limits = new TokenLimits(this.currentModel)
      const systemMessage = `${this.options.systemMessage}
Cutoff: ${limits.knowledgeCutOff}
Date: ${currentDate}
Language: ${this.options.language}`

      const completionParams: Record<string, any> = {
        temperature: this.options.modelTemperature,
        model: this.currentModel
      }

      // Route paid OSS 120b through Deallm (primary) → DeepInfra (fallback)
      if (this.currentModel === 'openai/gpt-oss-120b') {
        completionParams.provider = {order: ['deallm', 'deepinfra']}
      }

      // Route free OSS 120b through DeepInfra only
      if (this.currentModel === 'openai/gpt-oss-120b:free') {
        completionParams.provider = {order: ['deepinfra']}
      }

      // Route qwen3 235b through DeepInfra (primary) with WandB as fallback.
      // If BOTH providers fail, OpenRouter returns an error → we switch to next model (oss 120b)
      if (this.currentModel === 'qwen/qwen3-235b-a22b-2507') {
        completionParams.provider = {order: ['deepinfra', 'wandb']}
      }

      this.api = new AIClient({
        apiBaseUrl: this.options.apiBaseUrl,
        systemMessage,
        apiKey,
        apiOrg: process.env.AI_API_ORG || undefined,
        debug: this.options.debug,
        maxModelTokens: limits.maxTokens,
        maxResponseTokens: Math.min(1800, limits.responseTokens),
        completionParams
      })
      info(`Initialized AI client with model: ${this.currentModel}`)
    } else {
      throw new Error("Missing 'OPENROUTER_API_KEY' or 'AI_API_KEY'")
    }
  }

  chat = async (message: string, ids: Ids): Promise<[string, Ids]> => {
    let res: [string, Ids] = ['', {}]
    try {
      res = await this.chat_(message, ids)
      return res
    } catch (e: unknown) {
      if (e instanceof AIError) {
        warning(`AI communication error: ${e.message}`)
      }
      if (e instanceof AllModelsFailedError) {
        throw e
      }
      return res
    }
  }

  private readonly chat_ = async (
    message: string,
    ids: Ids
  ): Promise<[string, Ids]> => {
    const start = Date.now()
    if (!message) return ['', {}]

    let response: ChatMessage | undefined

    if (this.api != null) {
      const opts: SendMessageOptions = {
        timeoutMs: this.options.timeoutMS
      }
      if (ids.parentMessageId) {
        opts.parentMessageId = ids.parentMessageId
      }

      try {
        // Bug #2 Fix: use known limits instead of accessing private library field
        const limits = new TokenLimits(this.currentModel)
        const estimatedTokens = getTokenCount(message) + limits.responseTokens
        await TokenThrottler.throttle(estimatedTokens)

        // Log payload size before request to detect hidden context
        const messageSize = message.length
        debug('MESSAGE_SIZE_CHARS', messageSize)
        debug('MESSAGE_SIZE_KB', messageSize / 1024)
        debug('HAS_PARENT_MESSAGE_ID', !!opts.parentMessageId)
        debug('HAS_CONVERSATION_ID', !!ids.conversationId)
        debug('MESSAGE_PREVIEW', message.substring(0, 500))

        // CRITICAL: Detect if message contains generated file patterns (safety check)
        const generatedPatterns = [
          'node_modules/',
          'package-lock.json',
          'yarn.lock',
          'pnpm-lock.yaml',
          '.next/',
          'dist/',
          'build/',
          '.git/'
        ]
        const hasGeneratedContent = generatedPatterns.some(pattern =>
          message.includes(pattern)
        )
        if (hasGeneratedContent) {
          console.warn(
            'WARNING: Message may contain generated file content - upstream filtering should have removed this'
          )
          for (const pattern of generatedPatterns) {
            if (message.includes(pattern)) {
              console.warn(`  Found pattern: ${pattern}`)
            }
          }
        }

        // HARD PAYLOAD LIMIT - fail early before sending giant requests
        const MAX_PAYLOAD_CHARS = 120000
        if (messageSize > MAX_PAYLOAD_CHARS) {
          error(
            `PAYLOAD_TOO_LARGE_PREVENTED: Message is ${messageSize} chars, limit is ${MAX_PAYLOAD_CHARS}`
          )
          throw new Error(
            `PAYLOAD_TOO_LARGE_PREVENTED: Message is ${messageSize} chars, limit is ${MAX_PAYLOAD_CHARS}`
          )
        }

        const controller = new AbortController()
        const timeoutId = setTimeout(
          () => controller.abort(),
          this.options.timeoutMS
        )
        try {
          response = await pRetry(
            async () => {
              if (controller.signal.aborted)
                throw new Error('Request timed out')
              try {
                return await this.api!.sendMessage(message, opts)
              } catch (e: any) {
                // CRITICAL: 413 errors should NEVER retry - they waste tokens and time
                if (
                  e?.status === 413 ||
                  e?.message?.includes('Request Entity Too Large')
                ) {
                  error(
                    `413 Payload Too Large - NOT retrying. Message size: ${messageSize} chars`
                  )
                  throw e // Re-throw to fail immediately without retry
                }

                // Any error: try fallback model if available (cycles through chain)
                if (this.fallbackModels.length > 0) {
                  const nextModel = this.fallbackModels.shift()
                  if (nextModel) {
                    warning(
                      `Model ${this.currentModel} failed (${e?.status || e?.message}). Switching to fallback: ${nextModel}`
                    )
                    this.currentModel = nextModel
                    this.initClient()
                    delete opts.parentMessageId
                    throw new AllModelsFailedError()
                  }
                }
                throw e
              }
            },
            {
              retries: this.options.retries,
              onFailedAttempt: error => {
                info(
                  `Attempt ${error.attemptNumber} failed. ${error.retriesLeft} retries left.`
                )
              }
            }
          )
        } finally {
          clearTimeout(timeoutId)
        }
      } catch (e: unknown) {
        if (e instanceof AIError) {
          info(`AI Error: ${e.message} (Last model used: ${this.currentModel})`)
        } else if (e instanceof Error) {
          error(
            `Non-AI error in chat: ${e.message} (Last model used: ${this.currentModel})`
          )
        }
      }

      const end = Date.now()
      info(`AI response time: ${end - start} ms`)

      // Token usage logging
      if (response != null) {
        const inputTokens = getTokenCount(message)
        const outputTokens = getTokenCount(response.text)
        const totalTokens = inputTokens + outputTokens

        info(
          `Token usage: ${inputTokens}+${outputTokens}=${totalTokens} tokens (${this.currentModel})`
        )
      }
    } else {
      setFailed('AI client is not initialized')
    }

    let responseText = ''
    if (response != null) {
      responseText = response.text
    }

    const newIds: Ids = {
      parentMessageId: response?.id,
      conversationId: response?.conversationId
    }
    return [responseText, newIds]
  }
}