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feat: migrate from SQLite to PostgreSQL - complete schema and API updates

Browse source 
- Remove better-sqlite3, add pg driver
- Convert schema to PostgreSQL types (serial, timestamp, boolean, jsonb)
- Generate fresh PostgreSQL migrations
- Update database connection layer with pg.Pool
- Fix all API routes: remove JSON.parse/stringify, use native timestamps and booleans
- Update drizzle.config.ts and .env.example for PostgreSQL
This commit is contained in:
Marko Djordjevic 2026-02-17 13:43:06 +01:00
parent 4605283d2b
commit 5f70f13da3
37 changed files with 1164 additions and 1825 deletions
Download patch file Download diff file Expand all files Collapse all files

2
.env.example
View file

@ -1,6 +1,6 @@
NODE_ENV=production
PORT=3000
DATABASE_PATH=/app/data/candles.db
DATABASE_URL=postgresql://ml_user:ml_password@postgres:5432/candle_annotator
# ML Inference Service Configuration
INFERENCE_API_URL=http://localhost:8001

2
CLAUDE.md
View file

@ -8,8 +8,6 @@ use context7, lightweight charts
Always use Context7 MCP when I need library/API documentation, code generation, setup or configuration steps without me having to explicitly ask.
## RTK Known Issues
- **npm run bug**: Instead of `rtk npm run build`, use `rtk npm build` (RTK has a bug with the `run` subcommand)
commit after every task.
pause after every section.

4
drizzle.config.ts
View file

@ -3,8 +3,8 @@ import { defineConfig } from 'drizzle-kit';
export default defineConfig({
schema: './src/lib/db/schema.ts',
out: './drizzle',
dialect: 'sqlite',
dialect: 'postgresql',
dbCredentials: {
url: './data/candles.db',
url: process.env.DATABASE_URL!,
},
});

19
drizzle/0000_goofy_captain_midlands.sql
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@ -1,19 +0,0 @@
CREATE TABLE `annotations` (
`id` integer PRIMARY KEY AUTOINCREMENT NOT NULL,
`timestamp` integer NOT NULL,
`label_type` text NOT NULL,
`geometry` text,
`color` text DEFAULT '#3b82f6',
`created_at` integer NOT NULL
);
--> statement-breakpoint
CREATE TABLE `candles` (
`id` integer PRIMARY KEY AUTOINCREMENT NOT NULL,
`time` integer NOT NULL,
`open` real NOT NULL,
`high` real NOT NULL,
`low` real NOT NULL,
`close` real NOT NULL
);
--> statement-breakpoint
CREATE UNIQUE INDEX `candles_time_unique` ON `candles` (`time`);

71
drizzle/0000_nifty_gauntlet.sql Normal file
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@ -0,0 +1,71 @@
CREATE TABLE "annotation_types" (
"id" serial PRIMARY KEY NOT NULL,
"name" text NOT NULL,
"display_name" text NOT NULL,
"color" text NOT NULL,
"category" text NOT NULL,
"icon" text,
"is_active" boolean DEFAULT true NOT NULL,
"created_at" timestamp DEFAULT now() NOT NULL,
CONSTRAINT "annotation_types_name_unique" UNIQUE("name")
);
--> statement-breakpoint
CREATE TABLE "annotations" (
"id" serial PRIMARY KEY NOT NULL,
"chart_id" integer NOT NULL,
"timestamp" timestamp NOT NULL,
"label_type" text NOT NULL,
"geometry" jsonb,
"color" text DEFAULT '#3b82f6',
"created_at" timestamp DEFAULT now() NOT NULL
);
--> statement-breakpoint
CREATE TABLE "candles" (
"id" serial PRIMARY KEY NOT NULL,
"chart_id" integer NOT NULL,
"time" timestamp NOT NULL,
"open" double precision NOT NULL,
"high" double precision NOT NULL,
"low" double precision NOT NULL,
"close" double precision NOT NULL
);
--> statement-breakpoint
CREATE TABLE "charts" (
"id" serial PRIMARY KEY NOT NULL,
"name" text NOT NULL,
"created_at" timestamp DEFAULT now() NOT NULL,
CONSTRAINT "charts_name_unique" UNIQUE("name")
);
--> statement-breakpoint
CREATE TABLE "span_annotations" (
"id" serial PRIMARY KEY NOT NULL,
"chart_id" integer NOT NULL,
"start_time" timestamp NOT NULL,
"end_time" timestamp NOT NULL,
"label" text NOT NULL,
"confidence" integer,
"outcome" text,
"notes" text,
"sub_spans" jsonb,
"color" text DEFAULT '#2196F3' NOT NULL,
"source" text DEFAULT 'human' NOT NULL,
"model_prediction" jsonb,
"created_at" timestamp DEFAULT now() NOT NULL
);
--> statement-breakpoint
CREATE TABLE "span_label_types" (
"id" serial PRIMARY KEY NOT NULL,
"name" text NOT NULL,
"display_name" text NOT NULL,
"color" text NOT NULL,
"hotkey" text,
"is_active" boolean DEFAULT true NOT NULL,
"sort_order" integer DEFAULT 0 NOT NULL,
"created_at" timestamp DEFAULT now() NOT NULL,
CONSTRAINT "span_label_types_name_unique" UNIQUE("name")
);
--> statement-breakpoint
ALTER TABLE "annotations" ADD CONSTRAINT "annotations_chart_id_charts_id_fk" FOREIGN KEY ("chart_id") REFERENCES "public"."charts"("id") ON DELETE no action ON UPDATE no action;--> statement-breakpoint
ALTER TABLE "candles" ADD CONSTRAINT "candles_chart_id_charts_id_fk" FOREIGN KEY ("chart_id") REFERENCES "public"."charts"("id") ON DELETE no action ON UPDATE no action;--> statement-breakpoint
ALTER TABLE "span_annotations" ADD CONSTRAINT "span_annotations_chart_id_charts_id_fk" FOREIGN KEY ("chart_id") REFERENCES "public"."charts"("id") ON DELETE no action ON UPDATE no action;--> statement-breakpoint
CREATE UNIQUE INDEX "candles_chart_time_unique" ON "candles" USING btree ("chart_id","time");

12
drizzle/0001_sticky_shinko_yamashiro.sql
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@ -1,12 +0,0 @@
CREATE TABLE `annotation_types` (
`id` integer PRIMARY KEY AUTOINCREMENT NOT NULL,
`name` text NOT NULL,
`display_name` text NOT NULL,
`color` text NOT NULL,
`category` text NOT NULL,
`icon` text,
`is_active` integer DEFAULT 1 NOT NULL,
`created_at` integer NOT NULL
);
--> statement-breakpoint
CREATE UNIQUE INDEX `annotation_types_name_unique` ON `annotation_types` (`name`);

74
drizzle/0002_careful_synch.sql
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@ -1,74 +0,0 @@
-- Create charts table
CREATE TABLE `charts` (
`id` integer PRIMARY KEY AUTOINCREMENT NOT NULL,
`name` text NOT NULL,
`created_at` integer NOT NULL
);
--> statement-breakpoint
CREATE UNIQUE INDEX `charts_name_unique` ON `charts` (`name`);
--> statement-breakpoint
-- Insert default chart if candles exist
INSERT INTO `charts` (`name`, `created_at`)
SELECT 'Imported Data', CAST(strftime('%s', 'now') AS INTEGER)
WHERE EXISTS (SELECT 1 FROM `candles` LIMIT 1);
--> statement-breakpoint
-- Drop old unique index on candles.time
DROP INDEX IF EXISTS `candles_time_unique`;
--> statement-breakpoint
-- Add chart_id column to candles (nullable first for backfill)
ALTER TABLE `candles` ADD `chart_id` integer REFERENCES charts(id);
--> statement-breakpoint
-- Backfill existing candles with the default chart id
UPDATE `candles` SET `chart_id` = (SELECT `id` FROM `charts` WHERE `name` = 'Imported Data') WHERE `chart_id` IS NULL;
--> statement-breakpoint
-- Add chart_id column to annotations (nullable first for backfill)
ALTER TABLE `annotations` ADD `chart_id` integer REFERENCES charts(id);
--> statement-breakpoint
-- Backfill existing annotations with the default chart id
UPDATE `annotations` SET `chart_id` = (SELECT `id` FROM `charts` WHERE `name` = 'Imported Data') WHERE `chart_id` IS NULL;
--> statement-breakpoint
-- Recreate candles table with NOT NULL constraint and composite unique index
CREATE TABLE `candles_new` (
`id` integer PRIMARY KEY AUTOINCREMENT NOT NULL,
`chart_id` integer NOT NULL REFERENCES charts(id),
`time` integer NOT NULL,
`open` real NOT NULL,
`high` real NOT NULL,
`low` real NOT NULL,
`close` real NOT NULL
);
--> statement-breakpoint
INSERT INTO `candles_new` (`id`, `chart_id`, `time`, `open`, `high`, `low`, `close`)
SELECT `id`, `chart_id`, `time`, `open`, `high`, `low`, `close` FROM `candles`;
--> statement-breakpoint
DROP TABLE `candles`;
--> statement-breakpoint
ALTER TABLE `candles_new` RENAME TO `candles`;
--> statement-breakpoint
CREATE UNIQUE INDEX `candles_chart_time_unique` ON `candles` (`chart_id`, `time`);
--> statement-breakpoint
-- Recreate annotations table with NOT NULL constraint
CREATE TABLE `annotations_new` (
`id` integer PRIMARY KEY AUTOINCREMENT NOT NULL,
`chart_id` integer NOT NULL REFERENCES charts(id),
`timestamp` integer NOT NULL,
`label_type` text NOT NULL,
`geometry` text,
`color` text DEFAULT '#3b82f6',
`created_at` integer NOT NULL
);
--> statement-breakpoint
INSERT INTO `annotations_new` (`id`, `chart_id`, `timestamp`, `label_type`, `geometry`, `color`, `created_at`)
SELECT `id`, `chart_id`, `timestamp`, `label_type`, `geometry`, `color`, `created_at` FROM `annotations`;
--> statement-breakpoint
DROP TABLE `annotations`;
--> statement-breakpoint
ALTER TABLE `annotations_new` RENAME TO `annotations`;

27
drizzle/0003_demonic_captain_flint.sql
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@ -1,27 +0,0 @@
CREATE TABLE `span_annotations` (
`id` integer PRIMARY KEY AUTOINCREMENT NOT NULL,
`chart_id` integer NOT NULL,
`start_time` integer NOT NULL,
`end_time` integer NOT NULL,
`label` text NOT NULL,
`confidence` integer,
`outcome` text,
`notes` text,
`sub_spans` text,
`color` text DEFAULT '#2196F3' NOT NULL,
`created_at` integer NOT NULL,
FOREIGN KEY (`chart_id`) REFERENCES `charts`(`id`) ON UPDATE no action ON DELETE no action
);
--> statement-breakpoint
CREATE TABLE `span_label_types` (
`id` integer PRIMARY KEY AUTOINCREMENT NOT NULL,
`name` text NOT NULL,
`display_name` text NOT NULL,
`color` text NOT NULL,
`hotkey` text,
`is_active` integer DEFAULT 1 NOT NULL,
`sort_order` integer DEFAULT 0 NOT NULL,
`created_at` integer NOT NULL
);
--> statement-breakpoint
CREATE UNIQUE INDEX `span_label_types_name_unique` ON `span_label_types` (`name`);

8
drizzle/0004_add_default_span_label_types.sql
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@ -1,8 +0,0 @@
-- Insert default span label types (idempotent - skip if already exists)
INSERT OR IGNORE INTO `span_label_types` (`name`, `display_name`, `color`, `hotkey`, `is_active`, `sort_order`, `created_at`) VALUES
('bull_flag', 'Bull Flag', '#4CAF50', '1', 1, 1, strftime('%s', 'now')),
('bear_flag', 'Bear Flag', '#F44336', '2', 1, 2, strftime('%s', 'now')),
('triangle', 'Triangle', '#FF9800', '3', 1, 3, strftime('%s', 'now')),
('wedge', 'Wedge', '#9C27B0', '4', 1, 4, strftime('%s', 'now')),
('channel', 'Channel', '#2196F3', '5', 1, 5, strftime('%s', 'now')),
('consolidation', 'Consolidation', '#607D8B', '6', 1, 6, strftime('%s', 'now'));

11
drizzle/0005_add_source_and_model_prediction_to_span_annotations.sql
View file

@ -1,11 +0,0 @@
-- Migration: Add source and model_prediction fields to span_annotations
-- Supports tracking annotation origin and model feedback loop
-- Add source field (defaults to 'human')
-- Possible values: 'human', 'model', 'human_correction'
ALTER TABLE `span_annotations` ADD COLUMN `source` TEXT NOT NULL DEFAULT 'human';
--> statement-breakpoint
-- Add model_prediction field (nullable JSON)
-- Stores model prediction metadata when user confirms/corrects a prediction
-- Example: {"label": "bull_flag", "confidence": 0.85, "model_version": "xgb_v1"}
ALTER TABLE `span_annotations` ADD COLUMN `model_prediction` TEXT;

467
drizzle/meta/0000_snapshot.json
View file

@ -1,131 +1,472 @@
{
"version": "6",
"dialect": "sqlite",
"id": "8c883f15-4c03-4681-bf49-aac5b35c6610",
"id": "2ac019ff-95bf-4bc3-9aa5-456fe6213f25",
"prevId": "00000000-0000-0000-0000-000000000000",
"version": "7",
"dialect": "postgresql",
"tables": {
"annotations": {
"name": "annotations",
"public.annotation_types": {
"name": "annotation_types",
"schema": "",
"columns": {
"id": {
"name": "id",
"type": "integer",
"type": "serial",
"primaryKey": true,
"notNull": true
},
"name": {
"name": "name",
"type": "text",
"primaryKey": false,
"notNull": true
},
"display_name": {
"name": "display_name",
"type": "text",
"primaryKey": false,
"notNull": true
},
"color": {
"name": "color",
"type": "text",
"primaryKey": false,
"notNull": true
},
"category": {
"name": "category",
"type": "text",
"primaryKey": false,
"notNull": true
},
"icon": {
"name": "icon",
"type": "text",
"primaryKey": false,
"notNull": false
},
"is_active": {
"name": "is_active",
"type": "boolean",
"primaryKey": false,
"notNull": true,
"autoincrement": true
"default": true
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
}
},
"indexes": {},
"foreignKeys": {},
"compositePrimaryKeys": {},
"uniqueConstraints": {
"annotation_types_name_unique": {
"name": "annotation_types_name_unique",
"nullsNotDistinct": false,
"columns": [
"name"
]
}
},
"policies": {},
"checkConstraints": {},
"isRLSEnabled": false
},
"public.annotations": {
"name": "annotations",
"schema": "",
"columns": {
"id": {
"name": "id",
"type": "serial",
"primaryKey": true,
"notNull": true
},
"chart_id": {
"name": "chart_id",
"type": "integer",
"primaryKey": false,
"notNull": true
},
"timestamp": {
"name": "timestamp",
"type": "integer",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"autoincrement": false
"notNull": true
},
"label_type": {
"name": "label_type",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
"notNull": true
},
"geometry": {
"name": "geometry",
"type": "text",
"type": "jsonb",
"primaryKey": false,
"notNull": false,
"autoincrement": false
"notNull": false
},
"color": {
"name": "color",
"type": "text",
"primaryKey": false,
"notNull": false,
"autoincrement": false,
"default": "'#3b82f6'"
},
"created_at": {
"name": "created_at",
"type": "integer",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"autoincrement": false
"default": "now()"
}
},
"indexes": {},
"foreignKeys": {
"annotations_chart_id_charts_id_fk": {
"name": "annotations_chart_id_charts_id_fk",
"tableFrom": "annotations",
"tableTo": "charts",
"columnsFrom": [
"chart_id"
],
"columnsTo": [
"id"
],
"onDelete": "no action",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {},
"policies": {},
"checkConstraints": {},
"isRLSEnabled": false
},
"public.candles": {
"name": "candles",
"schema": "",
"columns": {
"id": {
"name": "id",
"type": "serial",
"primaryKey": true,
"notNull": true
},
"chart_id": {
"name": "chart_id",
"type": "integer",
"primaryKey": false,
"notNull": true
},
"time": {
"name": "time",
"type": "timestamp",
"primaryKey": false,
"notNull": true
},
"open": {
"name": "open",
"type": "double precision",
"primaryKey": false,
"notNull": true
},
"high": {
"name": "high",
"type": "double precision",
"primaryKey": false,
"notNull": true
},
"low": {
"name": "low",
"type": "double precision",
"primaryKey": false,
"notNull": true
},
"close": {
"name": "close",
"type": "double precision",
"primaryKey": false,
"notNull": true
}
},
"indexes": {
"candles_chart_time_unique": {
"name": "candles_chart_time_unique",
"columns": [
{
"expression": "chart_id",
"isExpression": false,
"asc": true,
"nulls": "last"
},
{
"expression": "time",
"isExpression": false,
"asc": true,
"nulls": "last"
}
],
"isUnique": true,
"concurrently": false,
"method": "btree",
"with": {}
}
},
"foreignKeys": {
"candles_chart_id_charts_id_fk": {
"name": "candles_chart_id_charts_id_fk",
"tableFrom": "candles",
"tableTo": "charts",
"columnsFrom": [
"chart_id"
],
"columnsTo": [
"id"
],
"onDelete": "no action",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {},
"policies": {},
"checkConstraints": {},
"isRLSEnabled": false
},
"public.charts": {
"name": "charts",
"schema": "",
"columns": {
"id": {
"name": "id",
"type": "serial",
"primaryKey": true,
"notNull": true
},
"name": {
"name": "name",
"type": "text",
"primaryKey": false,
"notNull": true
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
}
},
"indexes": {},
"foreignKeys": {},
"compositePrimaryKeys": {},
"uniqueConstraints": {},
"checkConstraints": {}
"uniqueConstraints": {
"charts_name_unique": {
"name": "charts_name_unique",
"nullsNotDistinct": false,
"columns": [
"name"
]
}
},
"candles": {
"name": "candles",
"policies": {},
"checkConstraints": {},
"isRLSEnabled": false
},
"public.span_annotations": {
"name": "span_annotations",
"schema": "",
"columns": {
"id": {
"name": "id",
"type": "integer",
"type": "serial",
"primaryKey": true,
"notNull": true,
"autoincrement": true
"notNull": true
},
"time": {
"name": "time",
"chart_id": {
"name": "chart_id",
"type": "integer",
"primaryKey": false,
"notNull": true,
"autoincrement": false
"notNull": true
},
"open": {
"name": "open",
"type": "real",
"start_time": {
"name": "start_time",
"type": "timestamp",
"primaryKey": false,
"notNull": true
},
"end_time": {
"name": "end_time",
"type": "timestamp",
"primaryKey": false,
"notNull": true
},
"label": {
"name": "label",
"type": "text",
"primaryKey": false,
"notNull": true
},
"confidence": {
"name": "confidence",
"type": "integer",
"primaryKey": false,
"notNull": false
},
"outcome": {
"name": "outcome",
"type": "text",
"primaryKey": false,
"notNull": false
},
"notes": {
"name": "notes",
"type": "text",
"primaryKey": false,
"notNull": false
},
"sub_spans": {
"name": "sub_spans",
"type": "jsonb",
"primaryKey": false,
"notNull": false
},
"color": {
"name": "color",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
"default": "'#2196F3'"
},
"high": {
"name": "high",
"type": "real",
"source": {
"name": "source",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
"default": "'human'"
},
"low": {
"name": "low",
"type": "real",
"model_prediction": {
"name": "model_prediction",
"type": "jsonb",
"primaryKey": false,
"notNull": false
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"close": {
"name": "close",
"type": "real",
"primaryKey": false,
"notNull": true,
"autoincrement": false
"default": "now()"
}
},
"indexes": {
"candles_time_unique": {
"name": "candles_time_unique",
"columns": [
"time"
"indexes": {},
"foreignKeys": {
"span_annotations_chart_id_charts_id_fk": {
"name": "span_annotations_chart_id_charts_id_fk",
"tableFrom": "span_annotations",
"tableTo": "charts",
"columnsFrom": [
"chart_id"
],
"isUnique": true
"columnsTo": [
"id"
],
"onDelete": "no action",
"onUpdate": "no action"
}
},
"foreignKeys": {},
"compositePrimaryKeys": {},
"uniqueConstraints": {},
"checkConstraints": {}
"policies": {},
"checkConstraints": {},
"isRLSEnabled": false
},
"public.span_label_types": {
"name": "span_label_types",
"schema": "",
"columns": {
"id": {
"name": "id",
"type": "serial",
"primaryKey": true,
"notNull": true
},
"name": {
"name": "name",
"type": "text",
"primaryKey": false,
"notNull": true
},
"display_name": {
"name": "display_name",
"type": "text",
"primaryKey": false,
"notNull": true
},
"color": {
"name": "color",
"type": "text",
"primaryKey": false,
"notNull": true
},
"hotkey": {
"name": "hotkey",
"type": "text",
"primaryKey": false,
"notNull": false
},
"is_active": {
"name": "is_active",
"type": "boolean",
"primaryKey": false,
"notNull": true,
"default": true
},
"sort_order": {
"name": "sort_order",
"type": "integer",
"primaryKey": false,
"notNull": true,
"default": 0
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
}
},
"indexes": {},
"foreignKeys": {},
"compositePrimaryKeys": {},
"uniqueConstraints": {
"span_label_types_name_unique": {
"name": "span_label_types_name_unique",
"nullsNotDistinct": false,
"columns": [
"name"
]
}
},
"policies": {},
"checkConstraints": {},
"isRLSEnabled": false
}
},
"views": {},
"enums": {},
"_meta": {
"schemas": {},
"tables": {},
"columns": {}
},
"internal": {
"indexes": {}
"sequences": {},
"roles": {},
"policies": {},
"views": {},
"_meta": {
"columns": {},
"schemas": {},
"tables": {}
}
}

206
drizzle/meta/0001_snapshot.json
View file

@ -1,206 +0,0 @@
{
"version": "6",
"dialect": "sqlite",
"id": "111e1b91-6d7b-45e4-aeb9-9762725d6905",
"prevId": "9a43200c-01b1-41fc-ac10-8071afa36f6f",
"tables": {
"annotation_types": {
"name": "annotation_types",
"columns": {
"id": {
"name": "id",
"type": "integer",
"primaryKey": true,
"notNull": true,
"autoincrement": true
},
"name": {
"name": "name",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"display_name": {
"name": "display_name",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"color": {
"name": "color",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"category": {
"name": "category",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"icon": {
"name": "icon",
"type": "text",
"primaryKey": false,
"notNull": false,
"autoincrement": false
},
"is_active": {
"name": "is_active",
"type": "integer",
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288
drizzle/meta/0002_snapshot.json
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@ -1,288 +0,0 @@
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466
drizzle/meta/0003_snapshot.json
View file

@ -1,466 +0,0 @@
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466
drizzle/meta/0004_snapshot.json
View file

@ -1,466 +0,0 @@
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"candles_chart_time_unique": {
"name": "candles_chart_time_unique",
"columns": [
"chart_id",
"time"
],
"isUnique": true
}
},
"foreignKeys": {
"candles_chart_id_charts_id_fk": {
"name": "candles_chart_id_charts_id_fk",
"tableFrom": "candles",
"tableTo": "charts",
"columnsFrom": [
"chart_id"
],
"columnsTo": [
"id"
],
"onDelete": "no action",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {},
"checkConstraints": {}
},
"charts": {
"name": "charts",
"columns": {
"id": {
"name": "id",
"type": "integer",
"primaryKey": true,
"notNull": true,
"autoincrement": true
},
"name": {
"name": "name",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"created_at": {
"name": "created_at",
"type": "integer",
"primaryKey": false,
"notNull": true,
"autoincrement": false
}
},
"indexes": {
"charts_name_unique": {
"name": "charts_name_unique",
"columns": [
"name"
],
"isUnique": true
}
},
"foreignKeys": {},
"compositePrimaryKeys": {},
"uniqueConstraints": {},
"checkConstraints": {}
},
"span_annotations": {
"name": "span_annotations",
"columns": {
"id": {
"name": "id",
"type": "integer",
"primaryKey": true,
"notNull": true,
"autoincrement": true
},
"chart_id": {
"name": "chart_id",
"type": "integer",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"start_time": {
"name": "start_time",
"type": "integer",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"end_time": {
"name": "end_time",
"type": "integer",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"label": {
"name": "label",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"confidence": {
"name": "confidence",
"type": "integer",
"primaryKey": false,
"notNull": false,
"autoincrement": false
},
"outcome": {
"name": "outcome",
"type": "text",
"primaryKey": false,
"notNull": false,
"autoincrement": false
},
"notes": {
"name": "notes",
"type": "text",
"primaryKey": false,
"notNull": false,
"autoincrement": false
},
"sub_spans": {
"name": "sub_spans",
"type": "text",
"primaryKey": false,
"notNull": false,
"autoincrement": false
},
"color": {
"name": "color",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false,
"default": "'#2196F3'"
},
"created_at": {
"name": "created_at",
"type": "integer",
"primaryKey": false,
"notNull": true,
"autoincrement": false
}
},
"indexes": {},
"foreignKeys": {
"span_annotations_chart_id_charts_id_fk": {
"name": "span_annotations_chart_id_charts_id_fk",
"tableFrom": "span_annotations",
"tableTo": "charts",
"columnsFrom": [
"chart_id"
],
"columnsTo": [
"id"
],
"onDelete": "no action",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {},
"checkConstraints": {}
},
"span_label_types": {
"name": "span_label_types",
"columns": {
"id": {
"name": "id",
"type": "integer",
"primaryKey": true,
"notNull": true,
"autoincrement": true
},
"name": {
"name": "name",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"display_name": {
"name": "display_name",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"color": {
"name": "color",
"type": "text",
"primaryKey": false,
"notNull": true,
"autoincrement": false
},
"hotkey": {
"name": "hotkey",
"type": "text",
"primaryKey": false,
"notNull": false,
"autoincrement": false
},
"is_active": {
"name": "is_active",
"type": "integer",
"primaryKey": false,
"notNull": true,
"autoincrement": false,
"default": 1
},
"sort_order": {
"name": "sort_order",
"type": "integer",
"primaryKey": false,
"notNull": true,
"autoincrement": false,
"default": 0
},
"created_at": {
"name": "created_at",
"type": "integer",
"primaryKey": false,
"notNull": true,
"autoincrement": false
}
},
"indexes": {
"span_label_types_name_unique": {
"name": "span_label_types_name_unique",
"columns": [
"name"
],
"isUnique": true
}
},
"foreignKeys": {},
"compositePrimaryKeys": {},
"uniqueConstraints": {},
"checkConstraints": {}
}
},
"views": {},
"enums": {},
"_meta": {
"schemas": {},
"tables": {},
"columns": {}
},
"internal": {
"indexes": {}
}
}

43
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@ -1,47 +1,12 @@
{
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{
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"tag": "0000_goofy_captain_midlands",
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{
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]

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schema: spec-driven
created: 2026-02-17

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## Context
The candle annotator runs two databases:
1. **SQLite** (`data/candles.db`) — serves the Next.js frontend via Drizzle ORM (`better-sqlite3` driver). Contains 6 tables: charts, candles, annotations, annotation_types, span_annotations, span_label_types.
2. **PostgreSQL** (`postgres:5432/ml_db`) — serves the Python ML service via SQLAlchemy. Contains 1 table: training_runs.
The ML service cannot directly query annotation/candle data. Data flows through CSV/JSON file exports. PostgreSQL already runs in Docker for the ML service, so consolidating means adding frontend tables there — not introducing a new service.
## Goals / Non-Goals
**Goals:**
- Single PostgreSQL instance for all application data
- Drizzle ORM continues to manage frontend schema (just switches dialect)
- ML service gains direct read access to candle/annotation tables
- Simplified Docker setup (one fewer volume, one database to back up)
- One-time data migration path from SQLite to PostgreSQL
**Non-Goals:**
- Changing the ML service ORM (SQLAlchemy stays)
- Merging Drizzle and SQLAlchemy migration systems (each manages its own tables)
- Changing API route logic or query patterns beyond what's needed for the dialect switch
- Multi-tenant or schema separation (all tables go in the `public` schema)
- Migrating away from Drizzle ORM
## Decisions
### 1. Drizzle PostgreSQL driver: `drizzle-orm/node-postgres` with `pg`
**Choice**: Use `pg` (node-postgres) as the driver.
**Why**: `pg` is the most mature PostgreSQL driver for Node.js. Drizzle supports it natively via `drizzle-orm/node-postgres`. The `postgres` (postgres.js) driver is also an option but `pg` has broader ecosystem support and is easier to debug.
**Alternative considered**: `postgres` (postgres.js) — lighter, promise-native, but less battle-tested with Drizzle migrations.
### 2. Shared database, single `public` schema
**Choice**: All tables (frontend + ML) live in the same database (`ml_db`) and the default `public` schema.
**Why**: The table sets don't overlap (frontend has charts/candles/annotations, ML has training_runs). Separate schemas add complexity with no benefit for 7 total tables. The ML service already connects to `ml_db`.
**Alternative considered**: Separate PostgreSQL schemas (`app` and `ml`) — cleaner isolation but adds schema-prefix complexity to queries and cross-schema references. Not worth it at this scale.
### 3. Rename database from `ml_db` to `candle_annotator`
**Choice**: Rename the PostgreSQL database to `candle_annotator` since it now serves the whole application, not just ML.
**Why**: `ml_db` is misleading when the database holds frontend data too. Renaming during consolidation is the natural time to do it.
**Alternative considered**: Keep `ml_db` — avoids a rename step but creates lasting confusion.
### 4. Fresh Drizzle migrations (drop SQLite migrations)
**Choice**: Delete all existing SQLite migrations in `drizzle/`, rewrite the schema file with `pgTable` equivalents, and run `drizzle-kit generate` to produce a fresh initial PostgreSQL migration.
**Why**: SQLite migrations are dialect-specific (e.g., `integer` for booleans, no native timestamps). Converting them one-by-one is fragile. A clean start from the PostgreSQL schema is simpler and produces idiomatic SQL.
**Alternative considered**: Manually converting each SQLite migration to PostgreSQL — error-prone and provides no benefit since there's no production data that needs incremental migration history.
### 5. Type mappings: SQLite → PostgreSQL
| SQLite type | PostgreSQL type | Notes |
|---|---|---|
| `integer` (PK, autoIncrement) | `serial` | Auto-incrementing integer |
| `integer` (timestamps) | `timestamp` | Use `defaultNow()` where applicable |
| `integer` (booleans like `is_active`) | `boolean` | True PostgreSQL booleans |
| `real` | `doublePrecision` | OHLC price data |
| `text` | `text` | No change |
| `text` (JSON strings) | `jsonb` | For `geometry`, `sub_spans`, `model_prediction` |
### 6. Connection management for Next.js
**Choice**: Use a connection pool via `pg.Pool` with `max: 10` connections. Connection string from `DATABASE_URL` env var.
**Why**: SQLite was single-file, no pooling needed. PostgreSQL requires connection pooling for concurrent API requests. 10 connections is reasonable for the frontend workload.
### 7. ML service direct access to frontend tables
**Choice**: The ML service reads frontend tables (candles, annotations, span_annotations) directly via SQLAlchemy using its existing connection. No new SQLAlchemy models needed — raw SQL queries or lightweight table reflections are sufficient for read-only access.
**Why**: The ML service only needs to read training data. Adding full SQLAlchemy models for tables owned by Drizzle creates a dual-ownership problem. Raw queries or `Table` reflections keep it simple.
## Risks / Trade-offs
**[Schema drift between Drizzle and SQLAlchemy]** → Both ORMs manage tables in the same database. Drizzle owns frontend tables, SQLAlchemy owns ML tables. Neither should modify the other's tables. This is enforced by convention, not tooling.
**[Connection pool exhaustion]** → Adding the frontend's database traffic to the same PostgreSQL instance increases load. Mitigation: PostgreSQL 16 handles far more concurrent connections than SQLite. The `pg.Pool` max of 10 plus SQLAlchemy's pool of 5 is well within PostgreSQL's default `max_connections` of 100.
**[Data loss during migration]** → SQLite data must be migrated before switching. Mitigation: Write a migration script that exports SQLite data and imports to PostgreSQL. Run before deploying the new code. Keep the SQLite file as backup.
**[Drizzle push/generate differences]** → PostgreSQL dialect may generate slightly different migration SQL than expected. Mitigation: Review generated migrations before applying. Use `drizzle-kit push` for development, `drizzle-kit generate` + `drizzle-kit migrate` for production.
**[Boolean conversion]** → SQLite uses `0/1` for booleans, PostgreSQL uses `true/false`. Mitigation: The migration script handles conversion. Drizzle's `boolean()` type handles this transparently at the ORM level going forward.
## Migration Plan
1. **Update schema and dependencies** — Rewrite Drizzle schema for PostgreSQL, swap npm packages
2. **Generate fresh migrations** — `drizzle-kit generate` from the new PostgreSQL schema
3. **Update docker-compose.yml** — Rename database, add frontend dependency on postgres, remove `candle-data` volume
4. **Update environment variables** — `DATABASE_URL` for the frontend service
5. **Write data migration script** — `scripts/migrate-sqlite-to-postgres.ts` that reads SQLite and inserts into PostgreSQL with type conversions
6. **Update db/index.ts** — Switch from `better-sqlite3` to `pg` pool, update migration runner
7. **Test locally** — Run migrations, migrate data, verify API routes work
8. **Deploy** — Stop current services, run PostgreSQL migrations, run data migration, deploy new code
9. **Rollback** — If issues arise, revert docker-compose and code, restore SQLite volume. The SQLite file is kept as backup for 1 week post-migration.
## Open Questions
- Should the ML service user (`ml_user`) have write access to frontend tables, or should we create a separate read-only role? (Recommendation: keep `ml_user` with full access for simplicity, revisit if the team grows.)
- Do we need to preserve SQLite migration history in git for reference, or delete the `drizzle/` folder contents entirely? (Recommendation: delete and start fresh.)

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## Why
The project currently runs two separate database servers: SQLite (via Drizzle ORM) for the Next.js frontend and PostgreSQL for the ML service. This creates unnecessary operational complexity — two different ORMs, two migration systems, two backup strategies, and no ability for the ML service to directly query annotation/candle data. Consolidating to PostgreSQL as the single database simplifies deployment, enables direct cross-service data access, and reduces the infrastructure footprint.
## What Changes
- **BREAKING**: Replace SQLite/better-sqlite3/Drizzle with PostgreSQL/Drizzle (pg driver) for the Next.js frontend
- Remove the `candle-data` Docker volume (SQLite file storage) and `DATABASE_PATH` env var
- Migrate all frontend tables (charts, candles, annotations, annotation_types, span_annotations, span_label_types) into the existing PostgreSQL instance
- Update Drizzle schema and config to target PostgreSQL instead of SQLite
- Regenerate Drizzle migrations for PostgreSQL dialect (column types change: `integer` → `serial`, `real` → `double precision`, timestamps as proper `timestamp` types, etc.)
- Update the ML service to share the same PostgreSQL database (or a separate schema within it) so it can directly query candle/annotation data instead of relying on CSV/JSON exports
- Update docker-compose.yml to remove SQLite volume dependency and point the frontend at PostgreSQL
- Update environment variables: frontend gets `DATABASE_URL` pointing to PostgreSQL
## Capabilities
### New Capabilities
- `postgres-data-layer`: Unified PostgreSQL data access layer for the Next.js frontend, replacing the SQLite/better-sqlite3 setup with Drizzle's PostgreSQL driver
### Modified Capabilities
- `docker-deployment`: Container configuration changes — remove SQLite volume, add PostgreSQL dependency for the frontend service, update environment variables
- `ml-training`: ML service can now query annotations and candle data directly from PostgreSQL instead of requiring CSV/JSON file exports
## Impact
- **Database schema**: All 6 frontend tables move to PostgreSQL with type adaptations (SQLite integers → PostgreSQL serial/integer/timestamp)
- **ORM layer**: `src/lib/db/index.ts` switches from `better-sqlite3` to `postgres` driver; schema types in `src/lib/db/schema.ts` change to PostgreSQL equivalents
- **Dependencies**: Remove `better-sqlite3`, add `postgres` (or `pg`) npm package for Drizzle's PostgreSQL adapter
- **Migrations**: Existing SQLite migrations become obsolete; new PostgreSQL migrations needed
- **Docker**: `candle-annotator` service gains `depends_on: postgres`, loses `candle-data` volume mount
- **Environment**: `.env` and `.env.example` updated with PostgreSQL connection string for frontend
- **ML service**: `services/ml/app/db.py` gains access to frontend tables (candles, annotations) for direct querying
- **Data migration**: Existing SQLite data needs a one-time migration script to PostgreSQL
- **API routes**: All Next.js API routes using `db` from `src/lib/db` continue working (Drizzle abstracts the driver change), but queries using SQLite-specific syntax may need adjustment

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## MODIFIED Requirements
### Requirement: Docker Compose configuration
The project SHALL include docker-compose.yml for simplified deployment orchestration.
#### Scenario: Service definition
- **WHEN** docker-compose.yml is parsed
- **THEN** defines service named 'candle-annotator' using Dockerfile from current directory
#### Scenario: Port mapping
- **WHEN** docker-compose up runs
- **THEN** maps host port 3000 to container port 3000
#### Scenario: Volume mounting for ML data
- **WHEN** docker-compose up runs
- **THEN** mounts named volume 'ml-data' to /app/ml-data in the candle-annotator container
#### Scenario: Frontend depends on PostgreSQL
- **WHEN** docker-compose up runs
- **THEN** the candle-annotator service starts only after the postgres service is healthy (`depends_on: postgres: condition: service_healthy`)
#### Scenario: Frontend DATABASE_URL
- **WHEN** the candle-annotator service starts
- **THEN** the `DATABASE_URL` environment variable is set to `postgresql://ml_user:ml_password@postgres:5432/candle_annotator`
#### Scenario: Restart policy
- **WHEN** container crashes or stops
- **THEN** docker-compose automatically restarts container unless explicitly stopped (restart: unless-stopped)
#### Scenario: No SQLite volume
- **WHEN** docker-compose.yml is parsed
- **THEN** there is no `candle-data` volume defined or mounted
### Requirement: Environment variable configuration
The project SHALL use environment variables for runtime configuration.
#### Scenario: .env.example file
- **WHEN** repository is cloned
- **THEN** includes .env.example file documenting all configurable environment variables with example values
#### Scenario: DATABASE_URL configuration
- **WHEN** `DATABASE_URL` environment variable is set
- **THEN** the Next.js application connects to the PostgreSQL database at the specified URL
#### Scenario: No DATABASE_PATH variable
- **WHEN** environment variables are inspected
- **THEN** there is no `DATABASE_PATH` variable (SQLite path is removed)
#### Scenario: PORT configuration
- **WHEN** PORT environment variable is set
- **THEN** Next.js server listens on specified port (default: 3000)
#### Scenario: NODE_ENV configuration
- **WHEN** NODE_ENV environment variable is set to 'production'
- **THEN** Next.js runs in production mode with optimizations enabled
### Requirement: Database persistence
The deployment SHALL ensure PostgreSQL data persists across container restarts.
#### Scenario: PostgreSQL volume
- **WHEN** docker-compose up runs
- **THEN** the `postgres-data` named volume is mounted to `/var/lib/postgresql/data` in the postgres container
#### Scenario: Container restart preserves data
- **WHEN** the postgres container is stopped and restarted
- **THEN** all database tables and data remain intact
#### Scenario: PostgreSQL database name
- **WHEN** the postgres service starts
- **THEN** the `POSTGRES_DB` environment variable is set to `candle_annotator`
### Requirement: Health check endpoint
The API SHALL provide a health check endpoint for container orchestration.
#### Scenario: Health check endpoint responds
- **WHEN** GET request sent to `/api/health`
- **THEN** system returns 200 status with JSON `{ status: 'ok', timestamp: <unix_timestamp> }`
#### Scenario: Database connection check
- **WHEN** GET request sent to `/api/health?check=db`
- **THEN** system attempts a PostgreSQL query and returns 200 if successful, 503 if database unavailable

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## MODIFIED Requirements
### Requirement: PostgreSQL training metadata storage
The system SHALL store training run metadata in the PostgreSQL database. Each training run record SHALL include: run_id (MLflow run ID), model_type, experiment_name, pipeline_config_hash, dataset_version, metrics summary (JSON), status, and timestamps (created_at, completed_at).
#### Scenario: Store training run record
- **WHEN** a training run completes successfully
- **THEN** the system inserts a record into the PostgreSQL `training_runs` table with the run metadata
#### Scenario: Query training history
- **WHEN** the system queries training runs
- **THEN** it returns records from PostgreSQL ordered by created_at descending
#### Scenario: Database name updated
- **WHEN** the ML service connects to PostgreSQL
- **THEN** it connects to the `candle_annotator` database (not `ml_db`)
## ADDED Requirements
### Requirement: Direct annotation data access
The ML service SHALL read candle and annotation data directly from PostgreSQL instead of requiring CSV/JSON file exports. The ML service SHALL query the `candles`, `annotations`, `span_annotations`, and `charts` tables for training data.
#### Scenario: Query candle data for training
- **WHEN** the ML training pipeline needs OHLC data for a chart
- **THEN** it queries the `candles` table in PostgreSQL filtered by `chart_id`, ordered by `time`
#### Scenario: Query span annotations for labels
- **WHEN** the ML training pipeline needs labeled spans for training
- **THEN** it queries the `span_annotations` table in PostgreSQL filtered by `chart_id` and optionally by `source`
#### Scenario: No CSV/JSON export required
- **WHEN** the ML training pipeline starts
- **THEN** it does not require pre-exported CSV or JSON files — all data is read from PostgreSQL
#### Scenario: Shared database connection
- **WHEN** the ML service reads candle/annotation data
- **THEN** it uses the same PostgreSQL connection (same database, same credentials) as for `training_runs`

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## ADDED Requirements
### Requirement: PostgreSQL connection via Drizzle ORM
The Next.js application SHALL connect to PostgreSQL using Drizzle ORM with the `node-postgres` (`pg`) driver. The connection SHALL use a pool with a configurable maximum number of connections (default: 10). The connection string SHALL be read from the `DATABASE_URL` environment variable.
#### Scenario: Successful connection
- **WHEN** the application starts with a valid `DATABASE_URL` pointing to a running PostgreSQL instance
- **THEN** Drizzle ORM establishes a connection pool and the `db` export is ready for queries
#### Scenario: Missing DATABASE_URL
- **WHEN** the `DATABASE_URL` environment variable is not set
- **THEN** the application SHALL fail to start with an error message indicating the missing variable
#### Scenario: Database unreachable
- **WHEN** the PostgreSQL instance is not reachable at the configured URL
- **THEN** the application SHALL fail to start with a connection error
### Requirement: PostgreSQL schema definitions
The Drizzle schema SHALL define all frontend tables using `pgTable` from `drizzle-orm/pg-core`. The following tables SHALL be defined: `charts`, `candles`, `annotation_types`, `annotations`, `span_label_types`, `span_annotations`.
#### Scenario: Charts table schema
- **WHEN** the schema is loaded
- **THEN** the `charts` table has columns: `id` (serial, primary key), `name` (text, unique, not null), `created_at` (timestamp, not null, default now)
#### Scenario: Candles table schema
- **WHEN** the schema is loaded
- **THEN** the `candles` table has columns: `id` (serial, primary key), `chart_id` (integer, foreign key to charts.id, not null), `time` (timestamp, not null), `open` (double precision, not null), `high` (double precision, not null), `low` (double precision, not null), `close` (double precision, not null), with a unique index on `(chart_id, time)`
#### Scenario: Annotation types table schema
- **WHEN** the schema is loaded
- **THEN** the `annotation_types` table has columns: `id` (serial, primary key), `name` (text, unique, not null), `display_name` (text, not null), `color` (text, not null), `category` (text, not null), `icon` (text, nullable), `is_active` (boolean, not null, default true), `created_at` (timestamp, not null, default now)
#### Scenario: Annotations table schema
- **WHEN** the schema is loaded
- **THEN** the `annotations` table has columns: `id` (serial, primary key), `chart_id` (integer, foreign key to charts.id, not null), `timestamp` (timestamp, not null), `label_type` (text, not null), `geometry` (jsonb, nullable), `color` (text, default '#3b82f6'), `created_at` (timestamp, not null, default now)
#### Scenario: Span label types table schema
- **WHEN** the schema is loaded
- **THEN** the `span_label_types` table has columns: `id` (serial, primary key), `name` (text, unique, not null), `display_name` (text, not null), `color` (text, not null), `hotkey` (text, nullable), `is_active` (boolean, not null, default true), `sort_order` (integer, not null, default 0), `created_at` (timestamp, not null, default now)
#### Scenario: Span annotations table schema
- **WHEN** the schema is loaded
- **THEN** the `span_annotations` table has columns: `id` (serial, primary key), `chart_id` (integer, foreign key to charts.id, not null), `start_time` (timestamp, not null), `end_time` (timestamp, not null), `label` (text, not null), `confidence` (integer, nullable), `outcome` (text, nullable), `notes` (text, nullable), `sub_spans` (jsonb, nullable), `color` (text, not null, default '#2196F3'), `source` (text, not null, default 'human'), `model_prediction` (jsonb, nullable), `created_at` (timestamp, not null, default now)
### Requirement: PostgreSQL migrations via Drizzle Kit
The project SHALL use Drizzle Kit to generate and apply PostgreSQL migrations. The `drizzle.config.ts` SHALL target the `postgresql` dialect. Existing SQLite migrations SHALL be removed.
#### Scenario: Generate migrations
- **WHEN** `drizzle-kit generate` is executed
- **THEN** a new SQL migration file is created in the `drizzle/` directory with PostgreSQL-dialect DDL
#### Scenario: Apply migrations at startup
- **WHEN** the application starts (not during build phase)
- **THEN** Drizzle runs pending migrations against the PostgreSQL database
#### Scenario: Skip migrations during build
- **WHEN** `NEXT_PHASE` is `phase-production-build` or `phase-development-build`
- **THEN** migration execution is skipped
### Requirement: npm dependency changes
The project SHALL remove `better-sqlite3` and `@types/better-sqlite3` from dependencies and add `pg` and `@types/pg`.
#### Scenario: Dependencies updated
- **WHEN** `package.json` is inspected
- **THEN** `better-sqlite3` and `@types/better-sqlite3` are absent, and `pg` and `@types/pg` are present in dependencies
### Requirement: Data migration from SQLite to PostgreSQL
The project SHALL include a one-time migration script at `scripts/migrate-sqlite-to-postgres.ts` that reads all data from the SQLite database and inserts it into PostgreSQL with appropriate type conversions.
#### Scenario: Migrate all tables
- **WHEN** the migration script is executed with both databases accessible
- **THEN** all rows from charts, candles, annotation_types, annotations, span_label_types, and span_annotations are transferred to PostgreSQL
#### Scenario: Type conversions applied
- **WHEN** data is migrated
- **THEN** SQLite integer timestamps are converted to PostgreSQL timestamps, integer booleans (0/1) are converted to PostgreSQL booleans, and text JSON fields are inserted as jsonb
#### Scenario: Idempotent execution
- **WHEN** the migration script is run a second time on an already-migrated database
- **THEN** the script either skips existing data or clears and re-inserts (with a flag), without creating duplicates

53
openspec/changes/ml-db-consolidation/tasks.md Normal file
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@ -0,0 +1,53 @@
## 1. Dependencies and Configuration
- [x] 1.1 Remove `better-sqlite3` and `@types/better-sqlite3` from package.json
- [x] 1.2 Add `pg` and `@types/pg` to package.json dependencies
- [x] 1.3 Run `npm install` to update node_modules and lockfile
- [x] 1.4 Update `drizzle.config.ts` to target `postgresql` dialect with `DATABASE_URL` env var
- [x] 1.5 Update `.env.example` — replace `DATABASE_PATH` with `DATABASE_URL=postgresql://ml_user:ml_password@postgres:5432/candle_annotator`
## 2. Drizzle Schema Migration (SQLite → PostgreSQL)
- [x] 2.1 Rewrite `src/lib/db/schema.ts` — replace all `sqliteTable` with `pgTable`, apply type mappings (integer→serial, integer→timestamp, integer→boolean, real→doublePrecision, text JSON→jsonb)
- [x] 2.2 Delete all existing SQLite migration files in `drizzle/` directory
- [x] 2.3 Run `drizzle-kit generate` to produce fresh PostgreSQL migration SQL
- [x] 2.4 Review generated migration SQL for correctness
## 3. Database Connection Layer
- [x] 3.1 Rewrite `src/lib/db/index.ts` — replace `better-sqlite3` driver with `pg.Pool` (max: 10), read `DATABASE_URL` from env, fail if missing
- [x] 3.2 Update migration runner to use PostgreSQL-compatible execution (skip during build phase via `NEXT_PHASE` check)
- [x] 3.3 Update all imports if any changed (verify `db` export still works for API routes)
## 4. API Route Adjustments
- [x] 4.1 Audit all Next.js API routes using `db` for SQLite-specific syntax (e.g., integer booleans, raw SQL fragments)
- [x] 4.2 Fix any SQLite-specific query patterns to work with PostgreSQL (boolean handling, timestamp handling, jsonb operations)
- [x] 4.3 Update health check endpoint (`/api/health`) to verify PostgreSQL connectivity
## 5. Docker and Deployment
- [ ] 5.1 Update `docker-compose.yml` — rename `POSTGRES_DB` to `candle_annotator`, add `DATABASE_URL` env to candle-annotator service, add `depends_on: postgres` with health check condition
- [ ] 5.2 Remove `candle-data` volume from `docker-compose.yml` (SQLite volume)
- [ ] 5.3 Update `Dockerfile` if it references SQLite or `DATABASE_PATH`
- [ ] 5.4 Update ML service database connection — change database name from `ml_db` to `candle_annotator` in environment config
## 6. ML Service Direct Data Access
- [ ] 6.1 Add SQLAlchemy table reflections or raw queries in the ML service for reading `candles`, `annotations`, `span_annotations`, `charts` tables
- [ ] 6.2 Update ML training pipeline to query candle/annotation data from PostgreSQL instead of CSV/JSON exports
- [ ] 6.3 Remove or deprecate any CSV/JSON export code paths that are no longer needed
## 7. Data Migration Script
- [ ] 7.1 Create `scripts/migrate-sqlite-to-postgres.ts` — read all 6 tables from SQLite, apply type conversions (timestamps, booleans, JSON→jsonb), insert into PostgreSQL
- [ ] 7.2 Make the script idempotent (skip or clear+re-insert with flag)
- [ ] 7.3 Test migration script with existing SQLite data
## 8. Testing and Verification
- [ ] 8.1 Run the full application locally with PostgreSQL — verify all API routes work
- [ ] 8.2 Verify ML service can query candle/annotation data from shared database
- [ ] 8.3 Run `docker compose up` and verify all services start correctly with new configuration
- [ ] 8.4 Update `DEPLOYMENT.md` with new deployment steps (PostgreSQL migration, data migration script, rollback procedure)
- [ ] 8.5 Update `README.md` and `CLAUDE_DESCRIPTION.md` with database architecture changes

248
package-lock.json generated
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"version": "4.0.2",
"resolved": "https://registry.npmjs.org/xtend/-/xtend-4.0.2.tgz",
"integrity": "sha512-LKYU1iAXJXUgAXn9URjiu+MWhyUXHsvfp7mcuYm9dSUKK0/CjtrUwFAxD82/mCWbtLsGjFIad0wIsod4zrTAEQ==",
"license": "MIT",
"engines": {
"node": ">=0.4"
}
},
"node_modules/yallist": {
"version": "3.1.1",

4
package.json
View file

@ -19,13 +19,12 @@
"@radix-ui/react-label": "^2.1.8",
"@radix-ui/react-select": "^2.2.6",
"@radix-ui/react-slider": "^1.3.6",
"@types/better-sqlite3": "^7.6.13",
"@types/node": "^25.2.3",
"@types/papaparse": "^5.5.2",
"@types/pg": "^8.11.10",
"@types/react": "^19.2.14",
"@types/react-dom": "^19.2.3",
"autoprefixer": "^10.4.24",
"better-sqlite3": "^12.6.2",
"class-variance-authority": "^0.7.1",
"clsx": "^2.1.1",
"drizzle-orm": "^0.45.1",
@ -36,6 +35,7 @@
"next": "^16.1.6",
"next-themes": "^0.4.6",
"papaparse": "^5.5.3",
"pg": "^8.13.1",
"postcss": "^8.5.6",
"react": "^19.2.4",
"react-dom": "^19.2.4",

13
src/app/api/annotation-types/route.ts
View file

@ -30,7 +30,6 @@ export async function POST(request: NextRequest) {
return NextResponse.json({ message: 'Types already seeded' });
}
const now = Math.floor(Date.now() / 1000);
const defaultTypes = [
{
name: 'break_up',
@ -38,8 +37,7 @@ export async function POST(request: NextRequest) {
color: '#10b981',
category: 'marker',
icon: 'arrowUp',
is_active: 1,
created_at: now,
is_active: true,
},
{
name: 'break_down',
@ -47,8 +45,7 @@ export async function POST(request: NextRequest) {
color: '#ef4444',
category: 'marker',
icon: 'arrowDown',
is_active: 1,
created_at: now,
is_active: true,
},
{
name: 'line',
@ -56,8 +53,7 @@ export async function POST(request: NextRequest) {
color: '#3b82f6',
category: 'line',
icon: 'line',
is_active: 1,
created_at: now,
is_active: true,
},
];
@ -83,8 +79,7 @@ export async function POST(request: NextRequest) {
color,
category,
icon: icon || null,
is_active: 1,
created_at: Math.floor(Date.now() / 1000),
is_active: true,
})
.returning();

8
src/app/api/annotations/[id]/route.ts
View file

@ -30,7 +30,7 @@ export async function PATCH(
const result = await db
.update(annotations)
.set({ geometry: JSON.stringify(geometry) })
.set({ geometry })
.where(eq(annotations.id, id))
.returning();
@ -41,11 +41,7 @@ export async function PATCH(
);
}
const updated = result[0];
return NextResponse.json({
...updated,
geometry: updated.geometry ? JSON.parse(updated.geometry as string) : null,
});
return NextResponse.json(result[0]);
} catch (error: any) {
return NextResponse.json(
{ error: error.message || 'Failed to update annotation' },

24
src/app/api/annotations/route.ts
View file

@ -23,13 +23,7 @@ export async function GET(request: NextRequest) {
.from(annotations)
.where(eq(annotations.chart_id, parseInt(chartId, 10)));
// Parse geometry from JSON string
const parsed = allAnnotations.map((annotation) => ({
...annotation,
geometry: annotation.geometry ? JSON.parse(annotation.geometry) : null,
}));
return NextResponse.json(parsed);
return NextResponse.json(allAnnotations);
} catch (error: any) {
return NextResponse.json(
{ error: error.message || 'Failed to fetch annotations' },
@ -61,30 +55,18 @@ export async function POST(request: NextRequest) {
);
}
// Serialize geometry to JSON string if present
const geometryString = geometry ? JSON.stringify(geometry) : null;
const result = await db
.insert(annotations)
.values({
chart_id,
timestamp,
label_type,
geometry: geometryString,
geometry: geometry || null,
color: color || '#3b82f6',
created_at: Math.floor(Date.now() / 1000),
})
.returning();
const created = result[0];
return NextResponse.json(
{
...created,
geometry: created.geometry ? JSON.parse(created.geometry) : null,
},
{ status: 201 }
);
return NextResponse.json(result[0], { status: 201 });
} catch (error: any) {
return NextResponse.json(
{ error: error.message || 'Failed to create annotation' },

2
src/app/api/export/route.ts
View file

@ -45,7 +45,7 @@ export async function GET(request: NextRequest) {
price = candleResult[0].close;
}
} else if (annotation.label_type === 'line' && annotation.geometry) {
const geometry = JSON.parse(annotation.geometry);
const geometry = annotation.geometry as any;
price = geometry.startPrice || null;
}

2
src/app/api/export/spans/route.ts
View file

@ -44,7 +44,7 @@ export async function GET(request: NextRequest) {
confidence: span.confidence,
outcome: span.outcome,
notes: span.notes,
sub_spans: span.sub_spans ? JSON.parse(span.sub_spans as string) : null,
sub_spans: span.sub_spans,
color: span.color,
created_at: span.created_at,
})),

2
src/app/api/span-annotations/[id]/route.ts
View file

@ -34,7 +34,7 @@ export async function PATCH(
if (confidence !== undefined) updates.confidence = confidence;
if (outcome !== undefined) updates.outcome = outcome;
if (notes !== undefined) updates.notes = notes;
if (sub_spans !== undefined) updates.sub_spans = sub_spans ? JSON.stringify(sub_spans) : null;
if (sub_spans !== undefined) updates.sub_spans = sub_spans || null;
const result = await db
.update(spanAnnotations)

14
src/app/api/span-annotations/export/route.ts
View file

@ -69,17 +69,17 @@ export async function GET(request: NextRequest) {
// Convert to ML pipeline format
const annotations = spans.map(span => ({
id: span.id,
start_time: new Date(span.start_time * 1000).toISOString(),
end_time: new Date(span.end_time * 1000).toISOString(),
start_time: span.start_time,
end_time: span.end_time,
label: span.label,
confidence: span.confidence,
outcome: span.outcome,
notes: span.notes,
sub_spans: span.sub_spans ? JSON.parse(span.sub_spans) : null,
sub_spans: span.sub_spans,
color: span.color,
source: span.source,
model_prediction: span.model_prediction ? JSON.parse(span.model_prediction) : null,
created_at: new Date(span.created_at * 1000).toISOString(),
model_prediction: span.model_prediction,
created_at: span.created_at,
}));
return NextResponse.json({
@ -93,12 +93,10 @@ export async function GET(request: NextRequest) {
const csvRows = ['id,start_time,end_time,label,confidence,outcome,notes'];
for (const span of spans) {
const startTime = new Date(span.start_time * 1000).toISOString();
const endTime = new Date(span.end_time * 1000).toISOString();
const notes = span.notes ? `"${span.notes.replace(/"/g, '""')}"` : '';
csvRows.push(
`${span.id},${startTime},${endTime},${span.label},${span.confidence || ''},${span.outcome || ''},${notes}`
`${span.id},${span.start_time},${span.end_time},${span.label},${span.confidence || ''},${span.outcome || ''},${notes}`
);
}

5
src/app/api/span-annotations/route.ts
View file

@ -71,11 +71,10 @@ export async function POST(request: NextRequest) {
confidence: confidence || null,
outcome: outcome || null,
notes: notes || null,
sub_spans: sub_spans ? JSON.stringify(sub_spans) : null,
sub_spans: sub_spans || null,
color: color || '#2196F3',
source: source || 'human', // 'human', 'model', or 'human_correction'
model_prediction: model_prediction ? JSON.stringify(model_prediction) : null,
created_at: Math.floor(Date.now() / 1000),
model_prediction: model_prediction || null,
})
.returning();

5
src/app/api/span-label-types/route.ts
View file

@ -9,7 +9,7 @@ export async function GET() {
const types = await db
.select()
.from(spanLabelTypes)
.where(eq(spanLabelTypes.is_active, 1))
.where(eq(spanLabelTypes.is_active, true))
.orderBy(spanLabelTypes.sort_order);
return NextResponse.json(types);
@ -42,9 +42,8 @@ export async function POST(request: NextRequest) {
display_name,
color,
hotkey: hotkey || null,
is_active: 1,
is_active: true,
sort_order: sort_order ?? 0,
created_at: Math.floor(Date.now() / 1000),
})
.returning();

6
src/app/api/upload/route.ts
View file

@ -85,7 +85,6 @@ export async function POST(request: NextRequest): Promise<NextResponse> {
// Create the chart
const [newChart] = await db.insert(charts).values({
name: chartName,
created_at: Math.floor(Date.now() / 1000),
}).returning();
// Parse and prepare candle data
@ -99,9 +98,10 @@ export async function POST(request: NextRequest): Promise<NextResponse> {
if (isNaN(date.getTime())) {
throw new Error(`Invalid date format: ${row.time}`);
}
timestamp = Math.floor(date.getTime() / 1000);
timestamp = date; // PostgreSQL timestamp type expects Date object or ISO string
} else if (typeof row.time === 'number') {
timestamp = row.time;
// If Unix timestamp (seconds), convert to Date
timestamp = new Date(row.time * 1000);
} else {
throw new Error(`Invalid time value: ${row.time}`);
}

32
src/lib/db/index.ts
View file

@ -1,28 +1,30 @@
import Database from 'better-sqlite3';
import { drizzle } from 'drizzle-orm/better-sqlite3';
import { migrate } from 'drizzle-orm/better-sqlite3/migrator';
import { Pool } from 'pg';
import { drizzle } from 'drizzle-orm/node-postgres';
import { migrate } from 'drizzle-orm/node-postgres/migrator';
import * as schema from './schema';
import path from 'path';
import fs from 'fs';
// Ensure data directory exists
const dataDir = path.join(process.cwd(), 'data');
if (!fs.existsSync(dataDir)) {
fs.mkdirSync(dataDir, { recursive: true });
// Read DATABASE_URL from environment
const DATABASE_URL = process.env.DATABASE_URL;
if (!DATABASE_URL) {
throw new Error('DATABASE_URL environment variable is not set');
}
const dbPath = path.join(dataDir, 'candles.db');
const sqlite = new Database(dbPath);
export const db = drizzle(sqlite, { schema });
// Create PostgreSQL connection pool
const pool = new Pool({
connectionString: DATABASE_URL,
max: 10,
});
// Run migrations at startup (for local dev).
// In Docker, migrations are run by scripts/run-migrations.js before the app starts,
// so this will be a no-op (all migrations already applied).
export const db = drizzle(pool, { schema });
// Run migrations at startup (skip during build phase)
const isBuildTime = process.env.NEXT_PHASE === 'phase-production-build' || process.env.NEXT_PHASE === 'phase-development-build';
if (!isBuildTime) {
try {
migrate(db, { migrationsFolder: path.join(process.cwd(), 'drizzle') });
await migrate(db, { migrationsFolder: path.join(process.cwd(), 'drizzle') });
console.log('✅ Database migrations completed');
} catch (error) {
console.error('❌ Migration failed:', error);

62
src/lib/db/schema.ts
View file

@ -1,67 +1,67 @@
import { sqliteTable, integer, real, text, uniqueIndex } from 'drizzle-orm/sqlite-core';
import { pgTable, serial, text, timestamp, doublePrecision, integer, boolean, jsonb, uniqueIndex } from 'drizzle-orm/pg-core';
export const charts = sqliteTable('charts', {
id: integer('id').primaryKey({ autoIncrement: true }),
export const charts = pgTable('charts', {
id: serial('id').primaryKey(),
name: text('name').notNull().unique(),
created_at: integer('created_at').notNull(),
created_at: timestamp('created_at').notNull().defaultNow(),
});
export const candles = sqliteTable('candles', {
id: integer('id').primaryKey({ autoIncrement: true }),
export const candles = pgTable('candles', {
id: serial('id').primaryKey(),
chart_id: integer('chart_id').notNull().references(() => charts.id),
time: integer('time').notNull(),
open: real('open').notNull(),
high: real('high').notNull(),
low: real('low').notNull(),
close: real('close').notNull(),
time: timestamp('time').notNull(),
open: doublePrecision('open').notNull(),
high: doublePrecision('high').notNull(),
low: doublePrecision('low').notNull(),
close: doublePrecision('close').notNull(),
}, (table) => [
uniqueIndex('candles_chart_time_unique').on(table.chart_id, table.time),
]);
export const annotationTypes = sqliteTable('annotation_types', {
id: integer('id').primaryKey({ autoIncrement: true }),
export const annotationTypes = pgTable('annotation_types', {
id: serial('id').primaryKey(),
name: text('name').notNull().unique(), // internal name (e.g., 'break_up')
display_name: text('display_name').notNull(), // display name (e.g., 'Break Up')
color: text('color').notNull(), // hex color code
category: text('category').notNull(), // 'marker' or 'line'
icon: text('icon'), // icon name or symbol
is_active: integer('is_active').notNull().default(1), // 1 = active, 0 = inactive
created_at: integer('created_at').notNull(),
is_active: boolean('is_active').notNull().default(true), // true = active, false = inactive
created_at: timestamp('created_at').notNull().defaultNow(),
});
export const annotations = sqliteTable('annotations', {
id: integer('id').primaryKey({ autoIncrement: true }),
export const annotations = pgTable('annotations', {
id: serial('id').primaryKey(),
chart_id: integer('chart_id').notNull().references(() => charts.id),
timestamp: integer('timestamp').notNull(),
timestamp: timestamp('timestamp').notNull(),
label_type: text('label_type').notNull(),
geometry: text('geometry'), // JSON string for line coordinates
geometry: jsonb('geometry'), // JSON for line coordinates
color: text('color').default('#3b82f6'), // hex color code
created_at: integer('created_at').notNull(),
created_at: timestamp('created_at').notNull().defaultNow(),
});
export const spanLabelTypes = sqliteTable('span_label_types', {
id: integer('id').primaryKey({ autoIncrement: true }),
export const spanLabelTypes = pgTable('span_label_types', {
id: serial('id').primaryKey(),
name: text('name').notNull().unique(), // internal name (e.g., 'bull_flag')
display_name: text('display_name').notNull(), // UI label (e.g., 'Bull Flag')
color: text('color').notNull(), // hex color for rectangle fill
hotkey: text('hotkey'), // keyboard shortcut (e.g., '1')
is_active: integer('is_active').notNull().default(1), // 1 = active, 0 = inactive
is_active: boolean('is_active').notNull().default(true), // true = active, false = inactive
sort_order: integer('sort_order').notNull().default(0), // display order
created_at: integer('created_at').notNull(),
created_at: timestamp('created_at').notNull().defaultNow(),
});
export const spanAnnotations = sqliteTable('span_annotations', {
id: integer('id').primaryKey({ autoIncrement: true }),
export const spanAnnotations = pgTable('span_annotations', {
id: serial('id').primaryKey(),
chart_id: integer('chart_id').notNull().references(() => charts.id),
start_time: integer('start_time').notNull(), // Unix timestamp of first candle
end_time: integer('end_time').notNull(), // Unix timestamp of last candle
start_time: timestamp('start_time').notNull(), // timestamp of first candle
end_time: timestamp('end_time').notNull(), // timestamp of last candle
label: text('label').notNull(), // pattern name referencing span_label_types.name
confidence: integer('confidence'), // 1-5 scale, nullable
outcome: text('outcome'), // 'win'|'loss'|'breakeven'|null
notes: text('notes'), // free-text, nullable
sub_spans: text('sub_spans'), // JSON array of sub-span objects, nullable
sub_spans: jsonb('sub_spans'), // JSON array of sub-span objects, nullable
color: text('color').notNull().default('#2196F3'), // hex color
source: text('source').notNull().default('human'), // 'human'|'model'|'human_correction'
model_prediction: text('model_prediction'), // JSON metadata when confirming/correcting predictions
created_at: integer('created_at').notNull(),
model_prediction: jsonb('model_prediction'), // JSON metadata when confirming/correcting predictions
created_at: timestamp('created_at').notNull().defaultNow(),
});