lib/src/bot.js

"use strict";
// Node 20 includes native fetch support
var __importDefault = (this && this.__importDefault) || function (mod) {
    return (mod && mod.__esModule) ? mod : { "default": mod };
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.Bot = exports.AllModelsFailedError = void 0;
// AI Client with Failover Support
// Fallback shims for Probot runtime
const info = console.log;
const warning = console.warn;
const error = console.error;
const debug = process.env.LOG_LEVEL === 'debug' ? console.log.bind(console) : () => { };
const setFailed = (msg) => {
    // Throw instead of process.exit to avoid killing the Probot server
    throw new Error(msg);
};
const chatgpt_1 = require("chatgpt");
const p_retry_1 = __importDefault(require("p-retry"));
const options_1 = require("./options");
const limits_1 = require("./limits");
const tokenizer_1 = require("./tokenizer");
const utils_1 = require("./utils");
const async_mutex_1 = require("async-mutex");
class TokenThrottler {
    static usage = [];
    static WINDOW_MS = 60000;
    static mutex = new async_mutex_1.Mutex();
    // Increased TPM limit to prevent self-throttling
    // Previous limit of 30,000 was too conservative for actual usage
    static get LIMIT() {
        return 1000000; // 1M tokens per minute - much more realistic
    }
    static async throttle(estimatedTokens) {
        // 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 (0, utils_1.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 });
        });
    }
}
class AllModelsFailedError extends Error {
    constructor() {
        super('All AI models failed after exhausting fallback chain');
        this.name = 'AllModelsFailedError';
    }
}
exports.AllModelsFailedError = AllModelsFailedError;
class Bot {
    api = null;
    options;
    aiOptions;
    currentModel;
    fallbackModels;
    constructor(options, aiOptions, fallbackModels) {
        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_1.Options.FREE_TIER_MODELS.includes(this.currentModel)) {
            this.fallbackModels = options_1.Options.FREE_TIER_MODELS.filter(m => m !== this.currentModel);
        }
        else if (options_1.Options.HEAVY_MODELS.includes(this.currentModel)) {
            this.fallbackModels = options_1.Options.HEAVY_MODELS.filter(m => m !== this.currentModel);
        }
        else {
            this.fallbackModels = options_1.Options.LIGHT_MODELS.filter(m => m !== this.currentModel);
        }
        this.initClient();
    }
    getCurrentModel() {
        return this.currentModel;
    }
    initClient() {
        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 limits_1.TokenLimits(this.currentModel);
            const systemMessage = `${this.options.systemMessage}
Cutoff: ${limits.knowledgeCutOff}
Date: ${currentDate}
Language: ${this.options.language}`;
            const completionParams = {
                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 chatgpt_1.ChatGPTAPI({
                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, ids) => {
        let res = ['', {}];
        try {
            res = await this.chat_(message, ids);
            return res;
        }
        catch (e) {
            if (e instanceof chatgpt_1.ChatGPTError) {
                warning(`AI communication error: ${e.message}`);
            }
            if (e instanceof AllModelsFailedError) {
                throw e;
            }
            return res;
        }
    };
    chat_ = async (message, ids) => {
        const start = Date.now();
        if (!message)
            return ['', {}];
        let response;
        if (this.api != null) {
            const opts = {
                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 limits_1.TokenLimits(this.currentModel);
                const estimatedTokens = (0, tokenizer_1.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 (0, p_retry_1.default)(async () => {
                        if (controller.signal.aborted)
                            throw new Error('Request timed out');
                        try {
                            return await this.api.sendMessage(message, opts);
                        }
                        catch (e) {
                            // 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) {
                if (e instanceof chatgpt_1.ChatGPTError) {
                    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 = (0, tokenizer_1.getTokenCount)(message);
                const outputTokens = (0, tokenizer_1.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 = {
            parentMessageId: response?.id,
            conversationId: response?.conversationId
        };
        return [responseText, newIds];
    };
}
exports.Bot = Bot;
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