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GMW/services/discord-gateway/src/shared/database/schema.ts
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import {
bigint as pgBigint,
boolean as pgBoolean,
foreignKey as pgForeignKey,
index as pgIndex,
integer as pgInteger,
real as pgReal,
pgTable,
text as pgText,
} from "drizzle-orm/pg-core";
// PostgreSQL Schema
// ==================
/**
* Muxer Jobs Table (PostgreSQL)
* Tracks audio post-processing jobs with status and retry logic
*/
export const pgMuxerJobsTable = pgTable(
"muxer_jobs",
{
id: pgText("id").primaryKey(),
data: pgText("data").notNull(),
status: pgText("status", {
enum: ["pending", "processing", "completed", "failed"],
})
.notNull()
.default("pending"),
attempts: pgInteger("attempts").notNull().default(0),
maxAttempts: pgInteger("maxAttempts").notNull().default(3),
createdAt: pgBigint("createdAt", { mode: "number" }).notNull(),
updatedAt: pgBigint("updatedAt", { mode: "number" }).notNull(),
error: pgText("error"),
},
(table) => ({
statusIdx: pgIndex("idx_muxer_jobs_status").on(table.status),
createdAtIdx: pgIndex("idx_muxer_jobs_createdAt").on(table.createdAt),
}),
);
/**
* Messages Table (PostgreSQL)
* Stores text messages with AI moderation analysis
*/
export const pgMessagesTable = pgTable(
"messages",
{
id: pgText("id").primaryKey(),
guild_id: pgText("guild_id").notNull(),
channel_id: pgText("channel_id").notNull(),
thread_id: pgText("thread_id"),
user_id: pgText("user_id").notNull(),
username: pgText("username").notNull(),
avatar_url: pgText("avatar_url"),
content: pgText("content").notNull(),
edited_content: pgText("edited_content"),
created_at: pgBigint("created_at", { mode: "number" }).notNull(),
edited_at: pgBigint("edited_at", { mode: "number" }),
deleted_at: pgBigint("deleted_at", { mode: "number" }),
type: pgText("type", { enum: ["text", "edited", "deleted"] })
.notNull()
.default("text"),
metadata: pgText("metadata"),
ai_status: pgText("ai_status", {
enum: ["pending", "processing", "clean", "warn", "flagged", "error"],
})
.notNull()
.default("pending"),
ai_moderation_flags: pgText("ai_moderation_flags"),
ai_moderation_score: pgReal("ai_moderation_score"),
ai_analysis: pgText("ai_analysis"),
ai_categories: pgText("ai_categories"),
ai_severity: pgText("ai_severity", {
enum: ["none", "low", "medium", "high", "critical"],
}),
ai_confidence: pgReal("ai_confidence"),
ai_recommended_action: pgText("ai_recommended_action", {
enum: ["none", "monitor", "warn", "review", "delete", "escalate"],
}),
ai_analyzed_at: pgBigint("ai_analyzed_at", { mode: "number" }),
ai_error: pgText("ai_error"),
},
(table) => ({
channelIdx: pgIndex("idx_messages_channel").on(table.channel_id),
userIdx: pgIndex("idx_messages_user").on(table.user_id),
createdIdx: pgIndex("idx_messages_created").on(table.created_at),
threadIdx: pgIndex("idx_messages_thread").on(table.thread_id),
channelCreatedIdx: pgIndex("idx_messages_channel_created").on(
table.channel_id,
table.created_at,
table.id,
),
threadCreatedIdx: pgIndex("idx_messages_thread_created").on(
table.thread_id,
table.created_at,
table.id,
),
aiStatusCreatedIdx: pgIndex("idx_messages_ai_status_created").on(
table.ai_status,
table.created_at,
table.id,
),
guildAiStatusCreatedIdx: pgIndex("idx_messages_guild_ai_status_created").on(
table.guild_id,
table.ai_status,
table.created_at,
table.id,
),
guildCreatedDeletedIdx: pgIndex("idx_messages_guild_created_deleted").on(
table.guild_id,
table.created_at,
table.deleted_at,
table.id,
),
channelAiStatusCreatedIdx: pgIndex(
"idx_messages_channel_ai_status_created",
).on(table.channel_id, table.ai_status, table.created_at, table.id),
threadAiStatusCreatedIdx: pgIndex(
"idx_messages_thread_ai_status_created",
).on(table.thread_id, table.ai_status, table.created_at, table.id),
}),
);
/**
* Attachments Table (PostgreSQL)
* Stores attachment metadata with upload status tracking
*/
export const pgAttachmentsTable = pgTable(
"attachments",
{
id: pgText("id").primaryKey(),
message_id: pgText("message_id").notNull(),
guild_id: pgText("guild_id").notNull(),
channel_id: pgText("channel_id").notNull(),
thread_id: pgText("thread_id"),
user_id: pgText("user_id").notNull(),
filename: pgText("filename").notNull(),
size: pgInteger("size").notNull(),
type: pgText("type").notNull(),
discord_url: pgText("discord_url").notNull(),
uploaded_url: pgText("uploaded_url"),
upload_status: pgText("upload_status", {
enum: ["pending", "uploaded", "failed"],
})
.notNull()
.default("pending"),
upload_error: pgText("upload_error"),
created_at: pgBigint("created_at", { mode: "number" }).notNull(),
uploaded_at: pgBigint("uploaded_at", { mode: "number" }),
},
(table) => ({
channelIdx: pgIndex("idx_attachments_channel").on(table.channel_id),
messageIdx: pgIndex("idx_attachments_message").on(table.message_id),
statusIdx: pgIndex("idx_attachments_status").on(table.upload_status),
channelCreatedIdx: pgIndex("idx_attachments_channel_created").on(
table.channel_id,
table.created_at,
table.id,
),
threadCreatedIdx: pgIndex("idx_attachments_thread_created").on(
table.thread_id,
table.created_at,
table.id,
),
messageFk: pgForeignKey({
columns: [table.message_id],
foreignColumns: [pgMessagesTable.id],
name: "fk_attachments_message_id",
}).onDelete("cascade"),
}),
);
/**
* UI State Table (PostgreSQL)
* Stores persistent UI state (e.g., selected channel, filter preferences)
*/
export const pgUIStateTable = pgTable("ui_state", {
key: pgText("key").primaryKey(),
value: pgText("value").notNull(),
updated_at: pgBigint("updated_at", { mode: "number" }).notNull(),
});
/**
* AI Analysis Runs Table (PostgreSQL)
* Tracks AI analysis batch runs for conversation-level moderation
*/
export const pgAIAnalysisRunsTable = pgTable(
"ai_analysis_runs",
{
id: pgText("id").primaryKey(),
conversation_key: pgText("conversation_key").notNull(),
target_message_ids: pgText("target_message_ids").notNull(), // JSON array
model: pgText("model").notNull(),
request_tokens_estimate: pgInteger("request_tokens_estimate"),
response_raw: pgText("response_raw"),
status: pgText("status", {
enum: ["pending", "processing", "completed", "failed"],
})
.notNull()
.default("pending"),
error: pgText("error"),
created_at: pgBigint("created_at", { mode: "number" }).notNull(),
completed_at: pgBigint("completed_at", { mode: "number" }),
},
(table) => ({
conversationKeyIdx: pgIndex("idx_ai_analysis_runs_conversation_key").on(
table.conversation_key,
),
statusIdx: pgIndex("idx_ai_analysis_runs_status").on(table.status),
createdAtIdx: pgIndex("idx_ai_analysis_runs_created_at").on(
table.created_at,
),
}),
);
/**
* Voice Recordings Table (PostgreSQL)
* Stores voice recording segment metadata and upload status
*/
export const pgVoiceRecordingsTable = pgTable(
"voice_recordings",
{
id: pgText("id").primaryKey(),
user_id: pgText("user_id").notNull(),
username: pgText("username").notNull(),
avatar_url: pgText("avatar_url"),
guild_id: pgText("guild_id"),
channel_id: pgText("channel_id"),
channel_name: pgText("channel_name"),
filename: pgText("filename").notNull(),
size_bytes: pgInteger("size_bytes").notNull(),
download_url: pgText("download_url"),
upload_status: pgText("upload_status", {
enum: ["pending", "uploaded", "failed"],
})
.notNull()
.default("pending"),
upload_error: pgText("upload_error"),
created_at: pgBigint("created_at", { mode: "number" }).notNull(),
uploaded_at: pgBigint("uploaded_at", { mode: "number" }),
},
(table) => ({
userIdIdx: pgIndex("idx_voice_recordings_user_id").on(table.user_id),
channelIdIdx: pgIndex("idx_voice_recordings_channel_id").on(
table.channel_id,
),
createdIdx: pgIndex("idx_voice_recordings_created_at").on(table.created_at),
}),
);
/**
* User Reputations Table (PostgreSQL)
* Tracks user trust score and infractions to provide context to AI.
*/
export const pgUserReputationsTable = pgTable(
"user_reputations",
{
user_id: pgText("user_id").primaryKey(),
guild_id: pgText("guild_id").notNull(),
trust_score: pgInteger("trust_score").notNull().default(50),
clean_message_streak: pgInteger("clean_message_streak")
.notNull()
.default(0),
total_infractions: pgInteger("total_infractions").notNull().default(0),
last_infraction_at: pgBigint("last_infraction_at", { mode: "number" }),
created_at: pgBigint("created_at", { mode: "number" }).notNull(),
updated_at: pgBigint("updated_at", { mode: "number" }).notNull(),
},
(table) => ({
guildIdx: pgIndex("idx_user_reputations_guild_id").on(table.guild_id),
scoreIdx: pgIndex("idx_user_reputations_trust_score").on(table.trust_score),
}),
);
/**
* Channel Cultures Table (PostgreSQL)
* Stores AI-generated summaries of channel norms and slang to inject as context.
*/
export const pgChannelCulturesTable = pgTable(
"channel_cultures",
{
channel_id: pgText("channel_id").primaryKey(),
guild_id: pgText("guild_id").notNull(),
culture_summary: pgText("culture_summary").notNull(),
last_analyzed_at: pgBigint("last_analyzed_at", {
mode: "number",
}).notNull(),
},
(table) => ({
guildIdx: pgIndex("idx_channel_cultures_guild_id").on(table.guild_id),
}),
);
/**
* Message Reviews Table (PostgreSQL)
* Tracks manual reviews of messages flagged by AI moderation
*/
export const pgMessageReviewsTable = pgTable(
"message_reviews",
{
id: pgText("id").primaryKey(),
message_id: pgText("message_id").notNull(),
guild_id: pgText("guild_id").notNull(),
channel_id: pgText("channel_id").notNull(),
reviewer_id: pgText("reviewer_id"),
status: pgText("status", {
enum: ["pending", "approved", "rejected", "escalated"],
})
.notNull()
.default("pending"),
notes: pgText("notes"),
created_at: pgBigint("created_at", { mode: "number" }).notNull(),
reviewed_at: pgBigint("reviewed_at", { mode: "number" }),
},
(table) => ({
messageIdIdx: pgIndex("idx_message_reviews_message_id").on(
table.message_id,
),
statusIdx: pgIndex("idx_message_reviews_status").on(table.status),
createdAtIdx: pgIndex("idx_message_reviews_created_at").on(
table.created_at,
),
guildStatusIdx: pgIndex("idx_message_reviews_guild_status").on(
table.guild_id,
table.status,
table.created_at,
),
}),
);
/**
* Moderation Actions Table (PostgreSQL)
* Tracks actions taken on messages (delete, mute, etc.)
*/
export const pgModerationActionsTable = pgTable(
"moderation_actions",
{
id: pgText("id").primaryKey(),
message_id: pgText("message_id"),
user_id: pgText("user_id"),
guild_id: pgText("guild_id").notNull(),
action_type: pgText("action_type", {
enum: [
"delete_message",
"mute_user",
"warn_user",
"kick_user",
"ban_user",
],
}).notNull(),
reason: pgText("reason"),
executed_by: pgText("executed_by"),
status: pgText("status", {
enum: ["pending", "executed", "failed"],
})
.notNull()
.default("pending"),
error: pgText("error"),
created_at: pgBigint("created_at", { mode: "number" }).notNull(),
executed_at: pgBigint("executed_at", { mode: "number" }),
},
(table) => ({
messageIdIdx: pgIndex("idx_moderation_actions_message_id").on(
table.message_id,
),
userIdIdx: pgIndex("idx_moderation_actions_user_id").on(table.user_id),
statusIdx: pgIndex("idx_moderation_actions_status").on(table.status),
guildStatusIdx: pgIndex("idx_moderation_actions_guild_status").on(
table.guild_id,
table.status,
table.created_at,
),
}),
);
/**
* Retention Policies Table (PostgreSQL)
* Defines data retention rules per guild/channel
*/
export const pgRetentionPoliciesTable = pgTable(
"retention_policies",
{
id: pgText("id").primaryKey(),
guild_id: pgText("guild_id").notNull(),
channel_id: pgText("channel_id"),
retention_days: pgInteger("retention_days").notNull().default(90),
apply_to_media: pgBoolean("apply_to_media").notNull().default(true),
apply_to_voice: pgBoolean("apply_to_voice").notNull().default(true),
enabled: pgBoolean("enabled").notNull().default(true),
created_at: pgBigint("created_at", { mode: "number" }).notNull(),
updated_at: pgBigint("updated_at", { mode: "number" }).notNull(),
},
(table) => ({
guildIdIdx: pgIndex("idx_retention_policies_guild_id").on(table.guild_id),
enabledIdx: pgIndex("idx_retention_policies_enabled").on(table.enabled),
}),
);
/**
* Text Analysis Cache Table (PostgreSQL)
* Caches per-normalized-text moderation analysis results so repeated
* phrases reuse previously computed API / fallback results instead of
* re-calling expensive LLM or external moderation APIs.
*
* Uses the FULL normalized text (not per-word) because context matters:
* "kau" alone is clean, but "awas kau" can be a threat.
*/
export const pgTextAnalysisCacheTable = pgTable(
"text_analysis_cache",
{
/** Normalized text (lowercase, whitespace-collapsed) — primary key. */
text: pgText("text").primaryKey(),
/** JSON array of moderation flags detected for this text (e.g. ["vulgar_language","harassment"]). */
flags: pgText("flags").notNull().default("[]"),
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/** Which source produced this result: "local" | "primary_ai" | "vision_llm". */
source: pgText("source", {
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enum: ["local", "primary_ai", "vision_llm"],
})
.notNull()
.default("local"),
/** Epoch millis when the analysis was stored. */
analyzed_at: pgBigint("analyzed_at", { mode: "number" }).notNull(),
/** Epoch millis when this cache entry expires. */
expires_at: pgBigint("expires_at", { mode: "number" }).notNull(),
/** How many times this cached text has been reused. */
hit_count: pgInteger("hit_count").notNull().default(0),
},
(table) => ({
expiresAtIdx: pgIndex("idx_text_analysis_cache_expires_at").on(
table.expires_at,
),
sourceIdx: pgIndex("idx_text_analysis_cache_source").on(table.source),
}),
);
/**
* Sticker Cache Table (PostgreSQL)
*
* Stores uploaded sticker image URLs instead of raw base64 blobs.
* Stickers are uploaded to the external upload service once and the URL is
* cached here so subsequent occurrences reuse the same URL for vision analysis.
*
* TTL: 7 days (enforced at query time via fetched_at)
* Eviction: max 5000 entries (LRU by fetched_at)
*/
export const pgStickerCacheTable = pgTable(
"sticker_cache",
{
/** Sanitized sticker name (encodeURIComponent + %→_) — primary key. */
name: pgText("name").primaryKey(),
/** Uploaded image URL (tele/picser). Used directly as image_url in vision API. */
imageUrl: pgText("image_url").notNull().default(""),
/** MIME type of the image (e.g. "image/png", "image/gif"). */
mime_type: pgText("mime_type").notNull(),
/** Epoch millis when this entry was stored. Used for TTL and LRU eviction. */
fetched_at: pgBigint("fetched_at", { mode: "number" }).notNull(),
},
(table) => ({
fetchedAtIdx: pgIndex("idx_sticker_cache_fetched_at").on(table.fetched_at),
}),
);
/**
* Corrected Moderations Table (PostgreSQL)
* Stores manually corrected false positives from AI moderation.
* Used for dynamic few-shot injection in moderation prompts.
*/
export const pgCorrectedModerationsTable = pgTable(
"corrected_moderations",
{
id: pgText("id").primaryKey(),
/** The message_id that was originally flagged. */
message_id: pgText("message_id").notNull(),
/** JSON array of original flags assigned by the LLM. */
original_flags: pgText("original_flags").notNull(),
/** JSON array of corrected flags (may be empty [] for clean). */
corrected_flags: pgText("corrected_flags").notNull(),
/** Human-readable explanation of why the correction was made. */
correction_notes: pgText("correction_notes"),
/** Content snippet so the LLM can recognise similar patterns. */
content_snippet: pgText("content_snippet").notNull(),
/** When this correction was recorded. */
created_at: pgBigint("created_at", { mode: "number" }).notNull(),
},
(table) => ({
createdAtIdx: pgIndex("idx_corrected_moderations_created_at").on(
table.created_at,
),
messageIdIdx: pgIndex("idx_corrected_moderations_message_id").on(
table.message_id,
),
}),
);
// Runtime table exports
// =====================
export const muxerJobsTable = pgMuxerJobsTable;
export const messagesTable = pgMessagesTable;
export const attachmentsTable = pgAttachmentsTable;
export const uiStateTable = pgUIStateTable;
export const aiAnalysisRunsTable = pgAIAnalysisRunsTable;
export const voiceRecordingsTable = pgVoiceRecordingsTable;
export const messageReviewsTable = pgMessageReviewsTable;
export const moderationActionsTable = pgModerationActionsTable;
export const retentionPoliciesTable = pgRetentionPoliciesTable;
export const textAnalysisCacheTable = pgTextAnalysisCacheTable;
export const stickerCacheTable = pgStickerCacheTable;
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export const correctedModerationsTable = pgCorrectedModerationsTable;
export const userReputationsTable = pgUserReputationsTable;
export const channelCulturesTable = pgChannelCulturesTable;
// Export table types for use in queries
export type MuxerJob = typeof muxerJobsTable.$inferSelect;
export type MuxerJobInsert = typeof muxerJobsTable.$inferInsert;
export type Message = typeof messagesTable.$inferSelect;
export type MessageInsert = typeof messagesTable.$inferInsert;
export type Attachment = typeof attachmentsTable.$inferSelect;
export type AttachmentInsert = typeof attachmentsTable.$inferInsert;
export type UIState = typeof uiStateTable.$inferSelect;
export type UIStateInsert = typeof uiStateTable.$inferInsert;
export type AIAnalysisRun = typeof aiAnalysisRunsTable.$inferSelect;
export type AIAnalysisRunInsert = typeof aiAnalysisRunsTable.$inferInsert;
export type VoiceRecording = typeof voiceRecordingsTable.$inferSelect;
export type VoiceRecordingInsert = typeof voiceRecordingsTable.$inferInsert;
export type MessageReview = typeof messageReviewsTable.$inferSelect;
export type MessageReviewInsert = typeof messageReviewsTable.$inferInsert;
export type ModerationAction = typeof moderationActionsTable.$inferSelect;
export type ModerationActionInsert = typeof moderationActionsTable.$inferInsert;
export type RetentionPolicy = typeof retentionPoliciesTable.$inferSelect;
export type RetentionPolicyInsert = typeof retentionPoliciesTable.$inferInsert;
export type StickerCacheRecord = typeof stickerCacheTable.$inferSelect;
export type StickerCacheInsert = typeof stickerCacheTable.$inferInsert;
export type CorrectedModeration = typeof correctedModerationsTable.$inferSelect;
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export type CorrectedModerationInsert =
typeof correctedModerationsTable.$inferInsert;
export type UserReputation = typeof userReputationsTable.$inferSelect;
export type UserReputationInsert = typeof userReputationsTable.$inferInsert;
export type ChannelCulture = typeof channelCulturesTable.$inferSelect;
export type ChannelCultureInsert = typeof channelCulturesTable.$inferInsert;