refactor(shared): centralize configuration and types
Migrate configuration validation and core moderation types from individual services to the `@bete/shared` package to ensure consistency across the monorepo. - Move `AppConfig` and moderation-related interfaces to `packages/shared`. - Replace service-specific Zod schemas with the centralized shared configuration. - Refactor `services/backend` and `services/discord-gateway` to consume shared config and types. - Remove redundant type definitions and local configuration logic in services. - Update `packages/shared` exports to include new `config` and `moderation-types` modules. - Clean up unused files and deprecated utility functions in `packages/shared`.
This commit is contained in:
@@ -1,236 +1,20 @@
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import "dotenv/config";
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import { ConfigError } from "@bete/shared/errors";
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import { z } from "zod";
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import type { AppConfig as SharedAppConfig } from "@bete/shared/config";
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import { config as sharedConfig, loadConfig as sharedLoadConfig } from "@bete/shared/config";
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const configSchema = z
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.object({
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DISCORD_TOKEN: z
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.string()
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.min(1, "DISCORD_TOKEN is required")
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.transform((value) => value.replace(/^("|')|(?:("|'))$/g, "")),
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VOICE_CHANNEL_ID: z.string().min(1).optional(),
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GUILD_ID: z.string().min(1).optional(),
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TEXT_GUILD_ID: z.string().min(1).optional(),
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TEXT_CHANNEL_ID: z.string().min(1).optional(),
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VOICE_GUILD_ID: z.string().min(1).optional(),
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VERBOSE: z
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.string()
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.optional()
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.transform((v) => v === "true")
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.default(false),
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RECORDINGS_DIR: z.string().default("./recordings"),
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RECORDING_SEGMENT_MS: z.coerce.number().positive().default(5000),
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DECODER_ROTATE_MS: z.coerce.number().positive().default(5000),
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DECODER_COOLDOWN_MS: z.coerce.number().positive().default(30000),
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WEBSERVER_PORT: z.coerce.number().positive().default(3000),
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VOICE_CONNECTION_TIMEOUT_MS: z.coerce.number().positive().default(15000),
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RECONNECT_TIMEOUT_MS: z.coerce.number().positive().default(5000),
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AUDIO_STREAM_SILENCE_DURATION_MS: z.coerce
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.number()
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.positive()
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.default(3000),
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PACKET_FILTER_MIN_SIZE: z.coerce.number().positive().default(8),
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OPUS_FRAME_SIZE: z.coerce.number().positive().default(960),
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AUDIO_SAMPLE_RATE: z.coerce.number().positive().default(48000),
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AUDIO_CHANNELS: z.coerce.number().positive().default(2),
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AVATAR_SIZE: z.coerce.number().positive().default(64),
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LOG_LEVEL: z
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.enum(["error", "warn", "info", "http", "verbose", "debug", "silly"])
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.default("info"),
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NODE_ENV: z
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.enum(["development", "production", "test"])
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.default("development"),
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MONITOR_GUILD_ID: z.string().min(1).optional(),
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TELE_UPLOAD_URL: z
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.string()
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.url()
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.default("https://upload.asepharyana.my.id/api/upload"),
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ATTACHMENT_UPLOAD_TIMEOUT_MS: z.coerce.number().positive().default(30000),
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ATTACHMENT_MAX_SIZE_MB: z.coerce.number().positive().default(100),
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ATTACHMENT_RETRY_ATTEMPTS: z.coerce.number().positive().default(3),
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BACKLOG_SYNC_HOURS: z.coerce.number().positive().default(24),
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BACKLOG_SYNC_BATCH_SIZE: z.coerce
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.number()
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.int()
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.positive()
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.max(100)
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.default(100),
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AI_ANALYSIS_ENABLED: z
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.string()
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.optional()
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.transform((v) => v === "true")
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.default(false),
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OPENAI_MODERATION_API_KEY: z.string().optional(),
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OPENAI_MODERATION_BASE_URL: z
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.string()
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.url()
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.default("https://api.openai.com/v1"),
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OPENAI_MODERATION_MODEL: z.string().default("omni-moderation-latest"),
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AI_LLM_API_KEY: z.string().optional(),
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AI_LLM_BASE_URL: z
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.string()
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.url()
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.default("https://9router.asepharyana.my.id/v1"),
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/** Model used for text-only moderation (messages, badword analysis). */
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AI_LLM_MODEL: z.string().default("text"),
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/** Model used for image/video moderation (vision-capable model). */
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AI_LLM_VISION_MODEL: z.string().optional(),
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/** Max concurrent LLM API calls (default: 5). */
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AI_LLM_MAX_CONCURRENT: z.coerce.number().int().positive().default(5),
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/** Maximum image dimension in pixels before resize for vision API (default: 1024). */
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AI_LLM_IMAGE_MAX_DIMENSION: z.coerce
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.number()
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.int()
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.positive()
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.default(1024),
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/** Maximum messages per text-only moderation batch (default: 20). */
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AI_LLM_TEXT_BATCH_SIZE: z.coerce.number().int().positive().default(20),
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/** Timeout in ms for individual media analysis calls (default: 60000). */
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AI_LLM_MEDIA_ANALYSIS_TIMEOUT_MS: z.coerce
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.number()
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.int()
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.positive()
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.default(60000),
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AI_ANALYSIS_DEBOUNCE_MS: z.coerce.number().positive().default(500),
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AI_ANALYSIS_RECOVERY_INTERVAL_MS: z.coerce
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.number()
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.positive()
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.default(15000),
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AI_ANALYSIS_ERROR_COOLDOWN_MS: z.coerce.number().positive().default(30000),
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/** Max messages fetched per conversation batch (token budget is the real constraint). */
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AI_ANALYSIS_MAX_BATCH_SIZE: z.coerce.number().int().positive().default(200),
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AI_ANALYSIS_MAX_CONTEXT_TOKENS: z.coerce.number().positive().default(8000),
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/** Token budget for target messages specifically (separate from context window). */
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AI_ANALYSIS_MAX_TARGET_TOKENS: z.coerce.number().positive().default(4000),
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AI_ANALYSIS_CONTEXT_MESSAGE_LIMIT: z.coerce
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.number()
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.int()
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.positive()
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.default(20),
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/**
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* How long a conversation is considered locked while being processed.
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* Must exceed (LLM timeout × max retries) + network overhead.
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* LLM client timeout=30s, retries=3 → minimum safe value ≈ 100s.
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*/
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AI_ANALYSIS_PROCESSING_TIMEOUT_MS: z.coerce
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.number()
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.positive()
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.default(120000),
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/** Max concurrent individual-fallback jobs admitted by the main event loop. */
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AI_ANALYSIS_INDIVIDUAL_MAX_CONCURRENT: z.coerce
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.number()
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.int()
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.positive()
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.default(50),
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/**
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* How many consecutive individual-fallback errors trigger the individual
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* circuit breaker (separate from the batch circuit breaker).
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*/
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AI_ANALYSIS_INDIVIDUAL_CB_THRESHOLD: z.coerce
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.number()
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.int()
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.positive()
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.default(50),
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/** Max Piscina worker threads for batch AI analysis (default: os.availableParallelism). */
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PISCINA_MAX_THREADS: z.coerce.number().int().positive().optional(),
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// AI moderation uses the Primary LLM (AI_LLM_*) endpoint only.
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// No NVIDIA or Groq fallback.
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AUTO_DELETE_FLAGGED_ENABLED: z
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.string()
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.optional()
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.transform((v) => v === "true")
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.default(true),
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AUTO_DELETE_FLAGGED_DELAY_MS: z.coerce.number().min(0).default(0),
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AUTO_DELETE_FLAGGED_DRY_RUN: z
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.string()
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.optional()
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.transform((v) => v === "true")
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.default(false),
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AUTO_DELETE_MIN_CONFIDENCE: z.coerce.number().min(0).max(1).default(0.5),
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AUTO_DELETE_ALLOWED_SEVERITIES: z
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.string()
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.default("critical,high,medium,low"),
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AUTO_DELETE_ALLOWED_CATEGORIES: z.string().default(""),
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AUTO_DELETE_EXCLUDED_CHANNEL_IDS: z.string().default(""),
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AUTO_DELETE_EXCLUDED_USER_IDS: z.string().default(""),
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AUTO_DELETE_NOTIFY_USER: z
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.string()
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.optional()
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.transform((v) => v === "true")
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.default(false),
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AUTO_DELETE_LOG_CHANNEL_ID: z.string().default(""),
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RETENTION_MESSAGES_DAYS: z.coerce.number().int().min(0).default(0),
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RETENTION_ATTACHMENTS_DAYS: z.coerce.number().int().min(0).default(0),
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RETENTION_VOICE_DAYS: z.coerce.number().int().min(0).default(0),
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RETENTION_CLEANUP_INTERVAL_MS: z.coerce
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.number()
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.positive()
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.default(24 * 60 * 60 * 1000),
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RETENTION_DRY_RUN: z
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.string()
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.optional()
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.transform((v) => v === "true")
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.default(true),
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AUTO_MIGRATE_ON_STARTUP: z
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.string()
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.optional()
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.transform((v) => v === "true")
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.default(true),
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DATABASE_URL: z.string().optional(),
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POSTGRES_HOST: z.string().default("localhost"),
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POSTGRES_PORT: z.coerce.number().int().positive().default(5432),
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POSTGRES_USER: z.string().optional(),
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POSTGRES_PASSWORD: z.string().optional(),
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POSTGRES_DB: z.string().optional(),
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POSTGRES_POOL_MIN: z.coerce.number().int().positive().default(2),
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POSTGRES_POOL_MAX: z.coerce.number().int().positive().default(10),
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ADMIN_PASSWORD: z.string().default("admin123"),
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REDIS_URL: z.string().min(1).default("redis://localhost:6379"),
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})
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.superRefine((value, ctx) => {
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if (!value.AI_ANALYSIS_ENABLED) {
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// Continue to database validation
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} else if (!value.AI_LLM_API_KEY) {
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ctx.addIssue({
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code: z.ZodIssueCode.custom,
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path: ["AI_LLM_API_KEY"],
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message: "AI_LLM_API_KEY is required when AI_ANALYSIS_ENABLED=true",
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});
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}
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// Validate PostgreSQL configuration
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if (!value.DATABASE_URL && !value.POSTGRES_HOST) {
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ctx.addIssue({
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code: z.ZodIssueCode.custom,
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path: ["DATABASE_URL"],
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message: "Either DATABASE_URL or POSTGRES_HOST must be provided",
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});
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}
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});
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export type AppConfig = z.infer<typeof configSchema> & {
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// Re-export the unified config with EFFECTIVE_* fields added
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export type AppConfig = SharedAppConfig & {
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EFFECTIVE_TEXT_GUILD_ID?: string;
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EFFECTIVE_VOICE_GUILD_ID?: string;
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};
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export function loadConfig(env: NodeJS.ProcessEnv = process.env): AppConfig {
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try {
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const parsed = configSchema.parse(env);
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return {
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...parsed,
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// AI text capture and analytics are pinned to the monitor guild.
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EFFECTIVE_TEXT_GUILD_ID: parsed.MONITOR_GUILD_ID,
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EFFECTIVE_VOICE_GUILD_ID: parsed.VOICE_GUILD_ID ?? parsed.GUILD_ID,
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};
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} catch (error) {
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if (error instanceof z.ZodError) {
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const messages = error.issues
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.map((e) => `${e.path.join(".")}: ${e.message}`)
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.join("\n");
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throw new ConfigError(`Configuration validation failed:\n${messages}`);
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}
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throw error;
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}
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const parsed = sharedLoadConfig(env);
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return {
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...parsed,
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EFFECTIVE_TEXT_GUILD_ID: parsed.MONITOR_GUILD_ID,
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EFFECTIVE_VOICE_GUILD_ID: parsed.VOICE_GUILD_ID ?? parsed.GUILD_ID,
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};
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}
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export const config = loadConfig();
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