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docs: 更新演进路线图（P1-2 注册表 + P1-4 Alembic 进度）
Co-Authored-By: Claude <noreply@anthropic.com>
2026-07-27 15:54:25 +08:00 · 2026-07-20 11:05:03 +08:00 · 2026-07-20 11:04:23 +08:00 · 2026-07-20 11:03:16 +08:00
23 changed files with 1362 additions and 1050 deletions
@@ -0,0 +1,149 @@
+# A generic, single database configuration.
+
+[alembic]
+# path to migration scripts.
+# this is typically a path given in POSIX (e.g. forward slashes)
+# format, relative to the token %(here)s which refers to the location of this
+# ini file
+script_location = %(here)s/alembic
+
+# template used to generate migration file names; The default value is %%(rev)s_%%(slug)s
+# Uncomment the line below if you want the files to be prepended with date and time
+# see https://alembic.sqlalchemy.org/en/latest/tutorial.html#editing-the-ini-file
+# for all available tokens
+# file_template = %%(year)d_%%(month).2d_%%(day).2d_%%(hour).2d%%(minute).2d-%%(rev)s_%%(slug)s
+# Or organize into date-based subdirectories (requires recursive_version_locations = true)
+# file_template = %%(year)d/%%(month).2d/%%(day).2d_%%(hour).2d%%(minute).2d_%%(second).2d_%%(rev)s_%%(slug)s
+
+# sys.path path, will be prepended to sys.path if present.
+# defaults to the current working directory.  for multiple paths, the path separator
+# is defined by "path_separator" below.
+prepend_sys_path = .
+
+
+# timezone to use when rendering the date within the migration file
+# as well as the filename.
+# If specified, requires the tzdata library which can be installed by adding
+# `alembic[tz]` to the pip requirements.
+# string value is passed to ZoneInfo()
+# leave blank for localtime
+# timezone =
+
+# max length of characters to apply to the "slug" field
+# truncate_slug_length = 40
+
+# set to 'true' to run the environment during
+# the 'revision' command, regardless of autogenerate
+# revision_environment = false
+
+# set to 'true' to allow .pyc and .pyo files without
+# a source .py file to be detected as revisions in the
+# versions/ directory
+# sourceless = false
+
+# version location specification; This defaults
+# to <script_location>/versions.  When using multiple version
+# directories, initial revisions must be specified with --version-path.
+# The path separator used here should be the separator specified by "path_separator"
+# below.
+# version_locations = %(here)s/bar:%(here)s/bat:%(here)s/alembic/versions
+
+# path_separator; This indicates what character is used to split lists of file
+# paths, including version_locations and prepend_sys_path within configparser
+# files such as alembic.ini.
+# The default rendered in new alembic.ini files is "os", which uses os.pathsep
+# to provide os-dependent path splitting.
+#
+# Note that in order to support legacy alembic.ini files, this default does NOT
+# take place if path_separator is not present in alembic.ini.  If this
+# option is omitted entirely, fallback logic is as follows:
+#
+# 1. Parsing of the version_locations option falls back to using the legacy
+#    "version_path_separator" key, which if absent then falls back to the legacy
+#    behavior of splitting on spaces and/or commas.
+# 2. Parsing of the prepend_sys_path option falls back to the legacy
+#    behavior of splitting on spaces, commas, or colons.
+#
+# Valid values for path_separator are:
+#
+# path_separator = :
+# path_separator = ;
+# path_separator = space
+# path_separator = newline
+#
+# Use os.pathsep. Default configuration used for new projects.
+path_separator = os
+
+# set to 'true' to search source files recursively
+# in each "version_locations" directory
+# new in Alembic version 1.10
+# recursive_version_locations = false
+
+# the output encoding used when revision files
+# are written from script.py.mako
+# output_encoding = utf-8
+
+# database URL.  This is consumed by the user-maintained env.py script only.
+# other means of configuring database URLs may be customized within the env.py
+# file.
+sqlalchemy.url = driver://user:pass@localhost/dbname
+
+
+[post_write_hooks]
+# post_write_hooks defines scripts or Python functions that are run
+# on newly generated revision scripts.  See the documentation for further
+# detail and examples
+
+# format using "black" - use the console_scripts runner, against the "black" entrypoint
+# hooks = black
+# black.type = console_scripts
+# black.entrypoint = black
+# black.options = -l 79 REVISION_SCRIPT_FILENAME
+
+# lint with attempts to fix using "ruff" - use the module runner, against the "ruff" module
+# hooks = ruff
+# ruff.type = module
+# ruff.module = ruff
+# ruff.options = check --fix REVISION_SCRIPT_FILENAME
+
+# Alternatively, use the exec runner to execute a binary found on your PATH
+# hooks = ruff
+# ruff.type = exec
+# ruff.executable = ruff
+# ruff.options = check --fix REVISION_SCRIPT_FILENAME
+
+# Logging configuration.  This is also consumed by the user-maintained
+# env.py script only.
+[loggers]
+keys = root,sqlalchemy,alembic
+
+[handlers]
+keys = console
+
+[formatters]
+keys = generic
+
+[logger_root]
+level = WARNING
+handlers = console
+qualname =
+
+[logger_sqlalchemy]
+level = WARNING
+handlers =
+qualname = sqlalchemy.engine
+
+[logger_alembic]
+level = INFO
+handlers =
+qualname = alembic
+
+[handler_console]
+class = StreamHandler
+args = (sys.stderr,)
+level = NOTSET
+formatter = generic
+
+[formatter_generic]
+format = %(levelname)-5.5s [%(name)s] %(message)s
+datefmt = %H:%M:%S
@@ -0,0 +1 @@
+Generic single-database configuration.
@@ -0,0 +1,73 @@
+"""Alembic 迁移环境配置
+
+- 从 shared.config.settings 读取 DB 配置，构造同步 URL（psycopg2）供 alembic 使用
+  （项目运行时用 asyncpg，但 alembic 是同步库，需 psycopg2）
+- target_metadata 指向 shared.models.database.Base.metadata
+- 支持 ALEMBIC_URL 环境变量覆盖（用于离线/空库生成初始迁移，如 sqlite:///empty.db）
+"""
+from logging.config import fileConfig
+from pathlib import Path
+import os
+import sys
+
+from sqlalchemy import engine_from_config, pool
+from alembic import context
+
+# 让 alembic 能 import 项目模块（src 在项目根下）
+project_root = Path(__file__).parent.parent
+sys.path.insert(0, str(project_root / "src"))
+
+from shared.config.settings import settings  # noqa: E402
+from shared.models.database import Base  # noqa: E402
+import shared.models.database  # noqa: E402,F401  # 导入所有模型，确保 metadata 注册
+
+config = context.config
+
+if config.config_file_name is not None:
+    fileConfig(config.config_file_name)
+
+# 构造同步 URL：asyncpg -> psycopg2
+_sync_url = settings.DATABASE_URL.replace("postgresql+asyncpg://", "postgresql+psycopg2://")
+# 支持 ALEMBIC_URL 覆盖（离线生成/测试用）
+config.set_main_option("sqlalchemy.url", os.getenv("ALEMBIC_URL", _sync_url))
+
+target_metadata = Base.metadata
+
+
+def run_migrations_offline() -> None:
+    """离线模式：生成 SQL 脚本，不连接 DB"""
+    url = config.get_main_option("sqlalchemy.url")
+    context.configure(
+        url=url,
+        target_metadata=target_metadata,
+        literal_binds=True,
+        dialect_opts={"paramstyle": "named"},
+        compare_type=True,
+        compare_server_default=True,
+    )
+    with context.begin_transaction():
+        context.run_migrations()
+
+
+def run_migrations_online() -> None:
+    """在线模式：连接 DB 执行迁移"""
+    connectable = engine_from_config(
+        config.get_section(config.config_ini_section, {}),
+        prefix="sqlalchemy.",
+        poolclass=pool.NullPool,
+    )
+    with connectable.connect() as connection:
+        context.configure(
+            connection=connection,
+            target_metadata=target_metadata,
+            compare_type=True,
+            compare_server_default=True,
+        )
+        with context.begin_transaction():
+            context.run_migrations()
+
+
+if context.is_offline_mode():
+    run_migrations_offline()
+else:
+    run_migrations_online()
@@ -0,0 +1,28 @@
+"""${message}
+
+Revision ID: ${up_revision}
+Revises: ${down_revision | comma,n}
+Create Date: ${create_date}
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+${imports if imports else ""}
+
+# revision identifiers, used by Alembic.
+revision: str = ${repr(up_revision)}
+down_revision: Union[str, Sequence[str], None] = ${repr(down_revision)}
+branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)}
+depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    ${upgrades if upgrades else "pass"}
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    ${downgrades if downgrades else "pass"}
@@ -0,0 +1,38 @@
+"""add product_id to stp_files
+
+Revision ID: 006c18c51b0d
+Revises: 9928d7f8c1ef
+Create Date: 2026-07-23 10:37:56.516787
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = '006c18c51b0d'
+down_revision: Union[str, Sequence[str], None] = '9928d7f8c1ef'
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema: stp_files 加 product_id 外键，关联进销存成品。"""
+    op.add_column("stp_files", sa.Column("product_id", sa.Integer(), nullable=True))
+    op.create_index("ix_stp_files_product_id", "stp_files", ["product_id"])
+    op.create_foreign_key(
+        "fk_stp_files_product_id_products",
+        "stp_files",
+        "products",
+        ["product_id"],
+        ["id"],
+    )
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    op.drop_constraint("fk_stp_files_product_id_products", "stp_files", type_="foreignkey")
+    op.drop_index("ix_stp_files_product_id", table_name="stp_files")
+    op.drop_column("stp_files", "product_id")
@@ -0,0 +1,728 @@
+"""initial schema
+
+Revision ID: 9928d7f8c1ef
+Revises: 
+Create Date: 2026-07-20 10:30:30.249866
+
+"""
+from typing import Sequence, Union
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision: str = '9928d7f8c1ef'
+down_revision: Union[str, Sequence[str], None] = None
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table('customers',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('code', sa.String(length=50), nullable=True),
+    sa.Column('name', sa.String(length=200), nullable=False),
+    sa.Column('contact_person', sa.String(length=100), nullable=True),
+    sa.Column('phone', sa.String(length=50), nullable=True),
+    sa.Column('email', sa.String(length=100), nullable=True),
+    sa.Column('address', sa.Text(), nullable=True),
+    sa.Column('bank_name', sa.String(length=100), nullable=True),
+    sa.Column('bank_account', sa.String(length=50), nullable=True),
+    sa.Column('tax_number', sa.String(length=50), nullable=True),
+    sa.Column('credit_limit', sa.Numeric(precision=12, scale=2), nullable=True),
+    sa.Column('is_active', sa.Boolean(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('updated_at', sa.DateTime(), nullable=True),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_customers_code'), 'customers', ['code'], unique=True)
+    op.create_index(op.f('ix_customers_id'), 'customers', ['id'], unique=False)
+    op.create_table('permissions',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('code', sa.String(length=100), nullable=False),
+    sa.Column('name', sa.String(length=100), nullable=False),
+    sa.Column('module', sa.String(length=50), nullable=True),
+    sa.Column('description', sa.Text(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_permissions_code'), 'permissions', ['code'], unique=True)
+    op.create_index(op.f('ix_permissions_id'), 'permissions', ['id'], unique=False)
+    op.create_table('products',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('sku', sa.String(length=50), nullable=False),
+    sa.Column('name', sa.String(length=200), nullable=False),
+    sa.Column('description', sa.Text(), nullable=True),
+    sa.Column('category', sa.String(length=100), nullable=True),
+    sa.Column('unit', sa.String(length=20), nullable=True),
+    sa.Column('item_type', sa.String(length=20), nullable=True),
+    sa.Column('cost_price', sa.Numeric(precision=12, scale=2), nullable=True),
+    sa.Column('sale_price', sa.Numeric(precision=12, scale=2), nullable=True),
+    sa.Column('min_stock', sa.Integer(), nullable=True),
+    sa.Column('max_stock', sa.Integer(), nullable=True),
+    sa.Column('is_active', sa.Boolean(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('updated_at', sa.DateTime(), nullable=True),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_products_id'), 'products', ['id'], unique=False)
+    op.create_index(op.f('ix_products_item_type'), 'products', ['item_type'], unique=False)
+    op.create_index(op.f('ix_products_sku'), 'products', ['sku'], unique=True)
+    op.create_table('roles',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('code', sa.String(length=50), nullable=False),
+    sa.Column('name', sa.String(length=100), nullable=False),
+    sa.Column('description', sa.Text(), nullable=True),
+    sa.Column('is_system', sa.Boolean(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_roles_code'), 'roles', ['code'], unique=True)
+    op.create_index(op.f('ix_roles_id'), 'roles', ['id'], unique=False)
+    op.create_table('suppliers',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('code', sa.String(length=50), nullable=True),
+    sa.Column('name', sa.String(length=200), nullable=False),
+    sa.Column('contact_person', sa.String(length=100), nullable=True),
+    sa.Column('phone', sa.String(length=50), nullable=True),
+    sa.Column('email', sa.String(length=100), nullable=True),
+    sa.Column('address', sa.Text(), nullable=True),
+    sa.Column('bank_name', sa.String(length=100), nullable=True),
+    sa.Column('bank_account', sa.String(length=50), nullable=True),
+    sa.Column('tax_number', sa.String(length=50), nullable=True),
+    sa.Column('is_active', sa.Boolean(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('updated_at', sa.DateTime(), nullable=True),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_suppliers_code'), 'suppliers', ['code'], unique=True)
+    op.create_index(op.f('ix_suppliers_id'), 'suppliers', ['id'], unique=False)
+    op.create_table('users',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('username', sa.String(length=50), nullable=False),
+    sa.Column('email', sa.String(length=255), nullable=False),
+    sa.Column('hashed_password', sa.String(length=255), nullable=False),
+    sa.Column('full_name', sa.String(length=100), nullable=True),
+    sa.Column('is_active', sa.Boolean(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('last_login', sa.DateTime(), nullable=True),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_users_email'), 'users', ['email'], unique=True)
+    op.create_index(op.f('ix_users_id'), 'users', ['id'], unique=False)
+    op.create_index(op.f('ix_users_username'), 'users', ['username'], unique=True)
+    op.create_table('warehouses',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('code', sa.String(length=50), nullable=True),
+    sa.Column('name', sa.String(length=200), nullable=False),
+    sa.Column('address', sa.Text(), nullable=True),
+    sa.Column('manager', sa.String(length=100), nullable=True),
+    sa.Column('phone', sa.String(length=50), nullable=True),
+    sa.Column('is_active', sa.Boolean(), nullable=True),
+    sa.Column('is_default', sa.Boolean(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_warehouses_code'), 'warehouses', ['code'], unique=True)
+    op.create_index(op.f('ix_warehouses_id'), 'warehouses', ['id'], unique=False)
+    op.create_table('finance_transactions',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('txn_no', sa.String(length=50), nullable=False),
+    sa.Column('txn_type', sa.String(length=20), nullable=False),
+    sa.Column('partner_type', sa.String(length=20), nullable=False),
+    sa.Column('partner_id', sa.Integer(), nullable=False),
+    sa.Column('amount', sa.Numeric(precision=12, scale=2), nullable=False),
+    sa.Column('txn_date', sa.DateTime(), nullable=True),
+    sa.Column('method', sa.String(length=30), nullable=True),
+    sa.Column('account_name', sa.String(length=100), nullable=True),
+    sa.Column('status', sa.String(length=20), nullable=True),
+    sa.Column('remark', sa.Text(), nullable=True),
+    sa.Column('operator_id', sa.Integer(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['operator_id'], ['users.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_finance_transactions_created_at'), 'finance_transactions', ['created_at'], unique=False)
+    op.create_index(op.f('ix_finance_transactions_id'), 'finance_transactions', ['id'], unique=False)
+    op.create_index(op.f('ix_finance_transactions_partner_id'), 'finance_transactions', ['partner_id'], unique=False)
+    op.create_index(op.f('ix_finance_transactions_partner_type'), 'finance_transactions', ['partner_type'], unique=False)
+    op.create_index(op.f('ix_finance_transactions_status'), 'finance_transactions', ['status'], unique=False)
+    op.create_index(op.f('ix_finance_transactions_txn_date'), 'finance_transactions', ['txn_date'], unique=False)
+    op.create_index(op.f('ix_finance_transactions_txn_no'), 'finance_transactions', ['txn_no'], unique=True)
+    op.create_index(op.f('ix_finance_transactions_txn_type'), 'finance_transactions', ['txn_type'], unique=False)
+    op.create_table('inventory',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('product_id', sa.Integer(), nullable=False),
+    sa.Column('warehouse_id', sa.Integer(), nullable=False),
+    sa.Column('quantity', sa.Numeric(precision=12, scale=4), nullable=True),
+    sa.Column('locked_quantity', sa.Numeric(precision=12, scale=4), nullable=True),
+    sa.Column('batch_number', sa.String(length=50), nullable=True),
+    sa.Column('location', sa.String(length=100), nullable=True),
+    sa.Column('updated_at', sa.DateTime(), nullable=True),
+    sa.CheckConstraint('quantity >= 0 AND locked_quantity >= 0 AND locked_quantity <= quantity', name='ck_inventory_qty_nonnegative'),
+    sa.ForeignKeyConstraint(['product_id'], ['products.id'], ),
+    sa.ForeignKeyConstraint(['warehouse_id'], ['warehouses.id'], ),
+    sa.PrimaryKeyConstraint('id'),
+    sa.UniqueConstraint('product_id', 'warehouse_id', name='uq_inventory_product_warehouse')
+    )
+    op.create_index(op.f('ix_inventory_id'), 'inventory', ['id'], unique=False)
+    op.create_index(op.f('ix_inventory_product_id'), 'inventory', ['product_id'], unique=False)
+    op.create_index(op.f('ix_inventory_warehouse_id'), 'inventory', ['warehouse_id'], unique=False)
+    op.create_table('material_price_history',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('product_id', sa.Integer(), nullable=False),
+    sa.Column('price', sa.Numeric(precision=12, scale=2), nullable=False),
+    sa.Column('effective_date', sa.DateTime(), nullable=True),
+    sa.Column('supplier_id', sa.Integer(), nullable=True),
+    sa.Column('remark', sa.Text(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['product_id'], ['products.id'], ),
+    sa.ForeignKeyConstraint(['supplier_id'], ['suppliers.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_material_price_history_effective_date'), 'material_price_history', ['effective_date'], unique=False)
+    op.create_index(op.f('ix_material_price_history_id'), 'material_price_history', ['id'], unique=False)
+    op.create_index(op.f('ix_material_price_history_product_id'), 'material_price_history', ['product_id'], unique=False)
+    op.create_index(op.f('ix_material_price_history_supplier_id'), 'material_price_history', ['supplier_id'], unique=False)
+    op.create_table('material_suppliers',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('product_id', sa.Integer(), nullable=False),
+    sa.Column('supplier_id', sa.Integer(), nullable=False),
+    sa.Column('is_primary', sa.Boolean(), nullable=True),
+    sa.Column('contact_person', sa.String(length=100), nullable=True),
+    sa.Column('contact_phone', sa.String(length=50), nullable=True),
+    sa.Column('lead_time', sa.Integer(), nullable=True),
+    sa.Column('min_order_quantity', sa.Integer(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('updated_at', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['product_id'], ['products.id'], ),
+    sa.ForeignKeyConstraint(['supplier_id'], ['suppliers.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_material_suppliers_id'), 'material_suppliers', ['id'], unique=False)
+    op.create_index(op.f('ix_material_suppliers_product_id'), 'material_suppliers', ['product_id'], unique=False)
+    op.create_index(op.f('ix_material_suppliers_supplier_id'), 'material_suppliers', ['supplier_id'], unique=False)
+    op.create_table('product_materials',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('finished_product_id', sa.Integer(), nullable=False),
+    sa.Column('material_product_id', sa.Integer(), nullable=False),
+    sa.Column('quantity', sa.Numeric(precision=12, scale=4), nullable=False),
+    sa.Column('loss_rate', sa.Numeric(precision=5, scale=4), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('updated_at', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['finished_product_id'], ['products.id'], ),
+    sa.ForeignKeyConstraint(['material_product_id'], ['products.id'], ),
+    sa.PrimaryKeyConstraint('id'),
+    sa.UniqueConstraint('finished_product_id', 'material_product_id', name='uq_product_material_unique')
+    )
+    op.create_index(op.f('ix_product_materials_finished_product_id'), 'product_materials', ['finished_product_id'], unique=False)
+    op.create_index(op.f('ix_product_materials_id'), 'product_materials', ['id'], unique=False)
+    op.create_index(op.f('ix_product_materials_material_product_id'), 'product_materials', ['material_product_id'], unique=False)
+    op.create_table('purchase_orders',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('order_no', sa.String(length=50), nullable=False),
+    sa.Column('supplier_id', sa.Integer(), nullable=False),
+    sa.Column('order_date', sa.DateTime(), nullable=True),
+    sa.Column('expected_date', sa.Date(), nullable=True),
+    sa.Column('status', sa.String(length=20), nullable=True),
+    sa.Column('total_amount', sa.Numeric(precision=12, scale=2), nullable=True),
+    sa.Column('paid_amount', sa.Numeric(precision=12, scale=2), nullable=True),
+    sa.Column('remark', sa.Text(), nullable=True),
+    sa.Column('operator_id', sa.Integer(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('updated_at', sa.DateTime(), nullable=True),
+    sa.Column('received_date', sa.DateTime(), nullable=True),
+    sa.Column('paid_date', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['operator_id'], ['users.id'], ),
+    sa.ForeignKeyConstraint(['supplier_id'], ['suppliers.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_purchase_orders_id'), 'purchase_orders', ['id'], unique=False)
+    op.create_index(op.f('ix_purchase_orders_order_no'), 'purchase_orders', ['order_no'], unique=True)
+    op.create_index(op.f('ix_purchase_orders_supplier_id'), 'purchase_orders', ['supplier_id'], unique=False)
+    op.create_table('role_permissions',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('role_id', sa.Integer(), nullable=False),
+    sa.Column('permission_id', sa.Integer(), nullable=False),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['permission_id'], ['permissions.id'], ),
+    sa.ForeignKeyConstraint(['role_id'], ['roles.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_role_permissions_id'), 'role_permissions', ['id'], unique=False)
+    op.create_index(op.f('ix_role_permissions_permission_id'), 'role_permissions', ['permission_id'], unique=False)
+    op.create_index(op.f('ix_role_permissions_role_id'), 'role_permissions', ['role_id'], unique=False)
+    op.create_table('sales_orders',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('order_no', sa.String(length=50), nullable=False),
+    sa.Column('customer_id', sa.Integer(), nullable=False),
+    sa.Column('order_date', sa.DateTime(), nullable=True),
+    sa.Column('delivery_date', sa.Date(), nullable=True),
+    sa.Column('manufacturing_date', sa.DateTime(), nullable=True),
+    sa.Column('actual_delivery_date', sa.DateTime(), nullable=True),
+    sa.Column('actual_payment_date', sa.DateTime(), nullable=True),
+    sa.Column('status', sa.String(length=20), nullable=True),
+    sa.Column('production_status', sa.String(length=20), nullable=True),
+    sa.Column('production_no', sa.String(length=50), nullable=True),
+    sa.Column('planned_material_cost', sa.Numeric(precision=12, scale=2), nullable=True),
+    sa.Column('actual_material_cost', sa.Numeric(precision=12, scale=2), nullable=True),
+    sa.Column('total_amount', sa.Numeric(precision=12, scale=2), nullable=True),
+    sa.Column('received_amount', sa.Numeric(precision=12, scale=2), nullable=True),
+    sa.Column('remark', sa.Text(), nullable=True),
+    sa.Column('operator_id', sa.Integer(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('updated_at', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['customer_id'], ['customers.id'], ),
+    sa.ForeignKeyConstraint(['operator_id'], ['users.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_sales_orders_customer_id'), 'sales_orders', ['customer_id'], unique=False)
+    op.create_index(op.f('ix_sales_orders_id'), 'sales_orders', ['id'], unique=False)
+    op.create_index(op.f('ix_sales_orders_order_no'), 'sales_orders', ['order_no'], unique=True)
+    op.create_index(op.f('ix_sales_orders_production_no'), 'sales_orders', ['production_no'], unique=False)
+    op.create_index(op.f('ix_sales_orders_production_status'), 'sales_orders', ['production_status'], unique=False)
+    op.create_table('stock_movements',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('product_id', sa.Integer(), nullable=False),
+    sa.Column('warehouse_id', sa.Integer(), nullable=False),
+    sa.Column('movement_type', sa.String(length=20), nullable=False),
+    sa.Column('quantity', sa.Numeric(precision=12, scale=4), nullable=False),
+    sa.Column('before_quantity', sa.Numeric(precision=12, scale=4), nullable=True),
+    sa.Column('after_quantity', sa.Numeric(precision=12, scale=4), nullable=True),
+    sa.Column('reference_type', sa.String(length=50), nullable=True),
+    sa.Column('reference_id', sa.Integer(), nullable=True),
+    sa.Column('reference_no', sa.String(length=50), nullable=True),
+    sa.Column('unit_price', sa.Numeric(precision=12, scale=2), nullable=True),
+    sa.Column('total_amount', sa.Numeric(precision=12, scale=2), nullable=True),
+    sa.Column('remark', sa.Text(), nullable=True),
+    sa.Column('operator_id', sa.Integer(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['operator_id'], ['users.id'], ),
+    sa.ForeignKeyConstraint(['product_id'], ['products.id'], ),
+    sa.ForeignKeyConstraint(['warehouse_id'], ['warehouses.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_stock_movements_created_at'), 'stock_movements', ['created_at'], unique=False)
+    op.create_index(op.f('ix_stock_movements_id'), 'stock_movements', ['id'], unique=False)
+    op.create_index(op.f('ix_stock_movements_product_id'), 'stock_movements', ['product_id'], unique=False)
+    op.create_table('stp_files',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('user_id', sa.Integer(), nullable=True),
+    sa.Column('object_key', sa.String(length=500), nullable=False),
+    sa.Column('storage_bucket', sa.String(length=100), nullable=False),
+    sa.Column('object_url', sa.String(length=1000), nullable=True),
+    sa.Column('original_filename', sa.String(length=255), nullable=False),
+    sa.Column('file_size', sa.Integer(), nullable=False),
+    sa.Column('file_hash', sa.String(length=64), nullable=True),
+    sa.Column('mime_type', sa.String(length=50), nullable=True),
+    sa.Column('upload_batch', sa.String(length=36), nullable=True),
+    sa.Column('upload_time', sa.DateTime(), nullable=True),
+    sa.Column('processed_time', sa.DateTime(), nullable=True),
+    sa.Column('status', sa.String(length=20), nullable=True),
+    sa.Column('error_message', sa.Text(), nullable=True),
+    sa.Column('volume', sa.Float(), nullable=True),
+    sa.Column('surface_area', sa.Float(), nullable=True),
+    sa.Column('product_weight', sa.Float(), nullable=True),
+    sa.Column('file_path', sa.String(length=500), nullable=True),
+    sa.Column('file_content', sa.LargeBinary(), nullable=True),
+    sa.Column('filename', sa.String(length=255), nullable=True),
+    sa.ForeignKeyConstraint(['user_id'], ['users.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_stp_files_file_hash'), 'stp_files', ['file_hash'], unique=False)
+    op.create_index(op.f('ix_stp_files_id'), 'stp_files', ['id'], unique=False)
+    op.create_index(op.f('ix_stp_files_object_key'), 'stp_files', ['object_key'], unique=False)
+    op.create_index(op.f('ix_stp_files_original_filename'), 'stp_files', ['original_filename'], unique=False)
+    op.create_index(op.f('ix_stp_files_status'), 'stp_files', ['status'], unique=False)
+    op.create_index(op.f('ix_stp_files_upload_batch'), 'stp_files', ['upload_batch'], unique=False)
+    op.create_index(op.f('ix_stp_files_user_id'), 'stp_files', ['user_id'], unique=False)
+    op.create_table('system_logs',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('level', sa.String(length=20), nullable=False),
+    sa.Column('message', sa.Text(), nullable=False),
+    sa.Column('module', sa.String(length=100), nullable=True),
+    sa.Column('function_name', sa.String(length=100), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('user_id', sa.Integer(), nullable=True),
+    sa.Column('request_id', sa.String(length=100), nullable=True),
+    sa.Column('execution_time_ms', sa.Integer(), nullable=True),
+    sa.Column('resource_type', sa.String(length=50), nullable=True),
+    sa.Column('resource_id', sa.Integer(), nullable=True),
+    sa.ForeignKeyConstraint(['user_id'], ['users.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_system_logs_created_at'), 'system_logs', ['created_at'], unique=False)
+    op.create_index(op.f('ix_system_logs_id'), 'system_logs', ['id'], unique=False)
+    op.create_index(op.f('ix_system_logs_level'), 'system_logs', ['level'], unique=False)
+    op.create_table('user_activities',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('user_id', sa.Integer(), nullable=False),
+    sa.Column('activity_type', sa.String(length=50), nullable=False),
+    sa.Column('resource_type', sa.String(length=50), nullable=True),
+    sa.Column('resource_id', sa.Integer(), nullable=True),
+    sa.Column('description', sa.Text(), nullable=True),
+    sa.Column('meta_data', sa.JSON(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('ip_address', sa.String(length=45), nullable=True),
+    sa.Column('user_agent', sa.String(length=500), nullable=True),
+    sa.ForeignKeyConstraint(['user_id'], ['users.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_user_activities_activity_type'), 'user_activities', ['activity_type'], unique=False)
+    op.create_index(op.f('ix_user_activities_created_at'), 'user_activities', ['created_at'], unique=False)
+    op.create_index(op.f('ix_user_activities_id'), 'user_activities', ['id'], unique=False)
+    op.create_index(op.f('ix_user_activities_user_id'), 'user_activities', ['user_id'], unique=False)
+    op.create_table('user_roles',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('user_id', sa.Integer(), nullable=False),
+    sa.Column('role_id', sa.Integer(), nullable=False),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['role_id'], ['roles.id'], ),
+    sa.ForeignKeyConstraint(['user_id'], ['users.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_user_roles_id'), 'user_roles', ['id'], unique=False)
+    op.create_index(op.f('ix_user_roles_role_id'), 'user_roles', ['role_id'], unique=False)
+    op.create_index(op.f('ix_user_roles_user_id'), 'user_roles', ['user_id'], unique=False)
+    op.create_table('analysis_metrics',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('stp_file_id', sa.Integer(), nullable=False),
+    sa.Column('volume_utilization', sa.Float(), nullable=True),
+    sa.Column('topology_complexity', sa.Float(), nullable=True),
+    sa.Column('wall_uniformity', sa.Float(), nullable=True),
+    sa.Column('analysis_summary', sa.Text(), nullable=True),
+    sa.Column('verification_status', sa.String(length=20), nullable=True),
+    sa.Column('verification_volume_diff', sa.Float(), nullable=True),
+    sa.Column('verification_area_diff', sa.Float(), nullable=True),
+    sa.Column('verification_details', sa.JSON(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['stp_file_id'], ['stp_files.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_analysis_metrics_id'), 'analysis_metrics', ['id'], unique=False)
+    op.create_index(op.f('ix_analysis_metrics_stp_file_id'), 'analysis_metrics', ['stp_file_id'], unique=False)
+    op.create_table('design_recommendations',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('stp_file_id', sa.Integer(), nullable=False),
+    sa.Column('rec_type', sa.String(length=50), nullable=False),
+    sa.Column('priority', sa.String(length=20), nullable=False),
+    sa.Column('description', sa.String(length=500), nullable=False),
+    sa.Column('reason', sa.Text(), nullable=True),
+    sa.Column('parameters', sa.JSON(), nullable=True),
+    sa.Column('status', sa.String(length=20), nullable=True),
+    sa.Column('user_notes', sa.Text(), nullable=True),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.Column('updated_at', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['stp_file_id'], ['stp_files.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_design_recommendations_id'), 'design_recommendations', ['id'], unique=False)
+    op.create_index(op.f('ix_design_recommendations_stp_file_id'), 'design_recommendations', ['stp_file_id'], unique=False)
+    op.create_table('finance_allocations',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('transaction_id', sa.Integer(), nullable=False),
+    sa.Column('order_type', sa.String(length=20), nullable=False),
+    sa.Column('order_id', sa.Integer(), nullable=False),
+    sa.Column('allocated_amount', sa.Numeric(precision=12, scale=2), nullable=False),
+    sa.Column('created_at', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['transaction_id'], ['finance_transactions.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_finance_allocations_created_at'), 'finance_allocations', ['created_at'], unique=False)
+    op.create_index(op.f('ix_finance_allocations_id'), 'finance_allocations', ['id'], unique=False)
+    op.create_index(op.f('ix_finance_allocations_order_id'), 'finance_allocations', ['order_id'], unique=False)
+    op.create_index(op.f('ix_finance_allocations_order_type'), 'finance_allocations', ['order_type'], unique=False)
+    op.create_index(op.f('ix_finance_allocations_transaction_id'), 'finance_allocations', ['transaction_id'], unique=False)
+    op.create_table('geometry_data',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('stp_file_id', sa.Integer(), nullable=False),
+    sa.Column('object_key', sa.String(length=500), nullable=False),
+    sa.Column('storage_bucket', sa.String(length=100), nullable=False),
+    sa.Column('object_url', sa.String(length=1000), nullable=True),
+    sa.Column('analysis_method', sa.String(length=50), nullable=True),
+    sa.Column('created_time', sa.DateTime(), nullable=True),
+    sa.Column('volume', sa.Float(), nullable=True),
+    sa.Column('surface_area', sa.Float(), nullable=True),
+    sa.Column('bounding_box_min', sa.JSON(), nullable=True),
+    sa.Column('bounding_box_max', sa.JSON(), nullable=True),
+    sa.Column('center_of_mass', sa.JSON(), nullable=True),
+    sa.Column('topology_faces', sa.Integer(), nullable=True),
+    sa.Column('topology_edges', sa.Integer(), nullable=True),
+    sa.Column('topology_vertices', sa.Integer(), nullable=True),
+    sa.ForeignKeyConstraint(['stp_file_id'], ['stp_files.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_geometry_data_id'), 'geometry_data', ['id'], unique=False)
+    op.create_index(op.f('ix_geometry_data_stp_file_id'), 'geometry_data', ['stp_file_id'], unique=False)
+    op.create_table('html_files',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('stp_file_id', sa.Integer(), nullable=False),
+    sa.Column('object_key', sa.String(length=500), nullable=False),
+    sa.Column('storage_bucket', sa.String(length=100), nullable=False),
+    sa.Column('object_url', sa.String(length=1000), nullable=True),
+    sa.Column('filename', sa.String(length=255), nullable=False),
+    sa.Column('generated_time', sa.DateTime(), nullable=True),
+    sa.Column('visualization_type', sa.String(length=50), nullable=True),
+    sa.Column('has_interactive_elements', sa.Boolean(), nullable=True),
+    sa.Column('file_path', sa.String(length=500), nullable=True),
+    sa.Column('html_content', sa.Text(), nullable=True),
+    sa.ForeignKeyConstraint(['stp_file_id'], ['stp_files.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_html_files_id'), 'html_files', ['id'], unique=False)
+    op.create_index(op.f('ix_html_files_stp_file_id'), 'html_files', ['stp_file_id'], unique=False)
+    op.create_table('mesh_data',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('stp_file_id', sa.Integer(), nullable=False),
+    sa.Column('object_key', sa.String(length=500), nullable=False),
+    sa.Column('storage_bucket', sa.String(length=100), nullable=False),
+    sa.Column('object_url', sa.String(length=1000), nullable=True),
+    sa.Column('quality', sa.String(length=20), nullable=True),
+    sa.Column('vertex_count', sa.Integer(), nullable=True),
+    sa.Column('face_count', sa.Integer(), nullable=True),
+    sa.Column('point_count', sa.Integer(), nullable=True),
+    sa.Column('bounding_box_min', sa.JSON(), nullable=True),
+    sa.Column('bounding_box_max', sa.JSON(), nullable=True),
+    sa.Column('created_time', sa.DateTime(), nullable=True),
+    sa.ForeignKeyConstraint(['stp_file_id'], ['stp_files.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_mesh_data_id'), 'mesh_data', ['id'], unique=False)
+    op.create_index(op.f('ix_mesh_data_stp_file_id'), 'mesh_data', ['stp_file_id'], unique=False)
+    op.create_table('mold_cavity_data',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('stp_file_id', sa.Integer(), nullable=False),
+    sa.Column('detailed_object_key', sa.String(length=500), nullable=False),
+    sa.Column('storage_bucket', sa.String(length=100), nullable=False),
+    sa.Column('mold_material', sa.String(length=100), nullable=True),
+    sa.Column('mold_type', sa.String(length=50), nullable=True),
+    sa.Column('shrinkage_rate', sa.Float(), nullable=False),
+    sa.Column('draft_angle', sa.Float(), nullable=False),
+    sa.Column('parting_line_length', sa.Float(), nullable=True),
+    sa.Column('generated_time', sa.DateTime(), nullable=True),
+    sa.Column('cavity_key_info', sa.JSON(), nullable=True),
+    sa.Column('mold_size_length', sa.Float(), nullable=True),
+    sa.Column('mold_size_width', sa.Float(), nullable=True),
+    sa.Column('mold_size_height', sa.Float(), nullable=True),
+    sa.Column('estimated_clamping_force', sa.String(length=50), nullable=True),
+    sa.Column('product_weight', sa.String(length=50), nullable=True),
+    sa.Column('product_volume', sa.Float(), nullable=True),
+    sa.Column('wall_thickness_range', sa.String(length=50), nullable=True),
+    sa.Column('complexity_score', sa.Float(), nullable=True),
+    sa.Column('weld_line_risk', sa.String(length=50), nullable=True),
+    sa.Column('sink_mark_risk', sa.String(length=50), nullable=True),
+    sa.Column('warpage_risk', sa.String(length=50), nullable=True),
+    sa.Column('best_scheme_id', sa.String(length=64), nullable=True),
+    sa.Column('confidence_score', sa.Float(), nullable=True),
+    sa.Column('is_fallback', sa.Boolean(), nullable=True),
+    sa.Column('fallback_reason', sa.Text(), nullable=True),
+    sa.ForeignKeyConstraint(['stp_file_id'], ['stp_files.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_mold_cavity_data_best_scheme_id'), 'mold_cavity_data', ['best_scheme_id'], unique=False)
+    op.create_index(op.f('ix_mold_cavity_data_id'), 'mold_cavity_data', ['id'], unique=False)
+    op.create_index(op.f('ix_mold_cavity_data_is_fallback'), 'mold_cavity_data', ['is_fallback'], unique=False)
+    op.create_index(op.f('ix_mold_cavity_data_stp_file_id'), 'mold_cavity_data', ['stp_file_id'], unique=False)
+    op.create_table('processing_tasks',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('task_id', sa.String(length=36), nullable=False),
+    sa.Column('stp_file_id', sa.Integer(), nullable=False),
+    sa.Column('task_type', sa.String(length=50), nullable=True),
+    sa.Column('status', sa.String(length=20), nullable=True),
+    sa.Column('created_time', sa.DateTime(), nullable=True),
+    sa.Column('started_time', sa.DateTime(), nullable=True),
+    sa.Column('completed_time', sa.DateTime(), nullable=True),
+    sa.Column('progress', sa.Integer(), nullable=True),
+    sa.Column('current_step', sa.String(length=100), nullable=True),
+    sa.Column('error_message', sa.Text(), nullable=True),
+    sa.Column('error_stack', sa.Text(), nullable=True),
+    sa.Column('parameters', sa.JSON(), nullable=True),
+    sa.ForeignKeyConstraint(['stp_file_id'], ['stp_files.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_processing_tasks_id'), 'processing_tasks', ['id'], unique=False)
+    op.create_index(op.f('ix_processing_tasks_stp_file_id'), 'processing_tasks', ['stp_file_id'], unique=False)
+    op.create_index(op.f('ix_processing_tasks_task_id'), 'processing_tasks', ['task_id'], unique=True)
+    op.create_table('purchase_order_items',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('order_id', sa.Integer(), nullable=False),
+    sa.Column('product_id', sa.Integer(), nullable=False),
+    sa.Column('quantity', sa.Integer(), nullable=False),
+    sa.Column('received_quantity', sa.Integer(), nullable=True),
+    sa.Column('unit_price', sa.Numeric(precision=12, scale=2), nullable=False),
+    sa.Column('amount', sa.Numeric(precision=12, scale=2), nullable=False),
+    sa.Column('remark', sa.Text(), nullable=True),
+    sa.CheckConstraint('quantity > 0 AND received_quantity >= 0 AND received_quantity <= quantity', name='ck_purchase_order_items_qty'),
+    sa.ForeignKeyConstraint(['order_id'], ['purchase_orders.id'], ),
+    sa.ForeignKeyConstraint(['product_id'], ['products.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_purchase_order_items_id'), 'purchase_order_items', ['id'], unique=False)
+    op.create_table('sales_order_items',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('order_id', sa.Integer(), nullable=False),
+    sa.Column('product_id', sa.Integer(), nullable=False),
+    sa.Column('quantity', sa.Integer(), nullable=False),
+    sa.Column('delivered_quantity', sa.Integer(), nullable=True),
+    sa.Column('unit_price', sa.Numeric(precision=12, scale=2), nullable=False),
+    sa.Column('amount', sa.Numeric(precision=12, scale=2), nullable=False),
+    sa.Column('remark', sa.Text(), nullable=True),
+    sa.CheckConstraint('quantity > 0 AND delivered_quantity >= 0 AND delivered_quantity <= quantity', name='ck_sales_order_items_qty'),
+    sa.ForeignKeyConstraint(['order_id'], ['sales_orders.id'], ),
+    sa.ForeignKeyConstraint(['product_id'], ['products.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_sales_order_items_id'), 'sales_order_items', ['id'], unique=False)
+    op.create_table('feature_detections',
+    sa.Column('id', sa.Integer(), nullable=False),
+    sa.Column('stp_file_id', sa.Integer(), nullable=False),
+    sa.Column('feature_type', sa.String(length=50), nullable=False),
+    sa.Column('confidence', sa.Float(), nullable=False),
+    sa.Column('location', sa.JSON(), nullable=True),
+    sa.Column('dimensions', sa.JSON(), nullable=True),
+    sa.Column('parameters', sa.JSON(), nullable=True),
+    sa.Column('detected_at', sa.DateTime(), nullable=True),
+    sa.Column('geometry_data_id', sa.Integer(), nullable=True),
+    sa.ForeignKeyConstraint(['geometry_data_id'], ['geometry_data.id'], ),
+    sa.ForeignKeyConstraint(['stp_file_id'], ['stp_files.id'], ),
+    sa.PrimaryKeyConstraint('id')
+    )
+    op.create_index(op.f('ix_feature_detections_feature_type'), 'feature_detections', ['feature_type'], unique=False)
+    op.create_index(op.f('ix_feature_detections_id'), 'feature_detections', ['id'], unique=False)
+    op.create_index(op.f('ix_feature_detections_stp_file_id'), 'feature_detections', ['stp_file_id'], unique=False)
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_index(op.f('ix_feature_detections_stp_file_id'), table_name='feature_detections')
+    op.drop_index(op.f('ix_feature_detections_id'), table_name='feature_detections')
+    op.drop_index(op.f('ix_feature_detections_feature_type'), table_name='feature_detections')
+    op.drop_table('feature_detections')
+    op.drop_index(op.f('ix_sales_order_items_id'), table_name='sales_order_items')
+    op.drop_table('sales_order_items')
+    op.drop_index(op.f('ix_purchase_order_items_id'), table_name='purchase_order_items')
+    op.drop_table('purchase_order_items')
+    op.drop_index(op.f('ix_processing_tasks_task_id'), table_name='processing_tasks')
+    op.drop_index(op.f('ix_processing_tasks_stp_file_id'), table_name='processing_tasks')
+    op.drop_index(op.f('ix_processing_tasks_id'), table_name='processing_tasks')
+    op.drop_table('processing_tasks')
+    op.drop_index(op.f('ix_mold_cavity_data_stp_file_id'), table_name='mold_cavity_data')
+    op.drop_index(op.f('ix_mold_cavity_data_is_fallback'), table_name='mold_cavity_data')
+    op.drop_index(op.f('ix_mold_cavity_data_id'), table_name='mold_cavity_data')
+    op.drop_index(op.f('ix_mold_cavity_data_best_scheme_id'), table_name='mold_cavity_data')
+    op.drop_table('mold_cavity_data')
+    op.drop_index(op.f('ix_mesh_data_stp_file_id'), table_name='mesh_data')
+    op.drop_index(op.f('ix_mesh_data_id'), table_name='mesh_data')
+    op.drop_table('mesh_data')
+    op.drop_index(op.f('ix_html_files_stp_file_id'), table_name='html_files')
+    op.drop_index(op.f('ix_html_files_id'), table_name='html_files')
+    op.drop_table('html_files')
+    op.drop_index(op.f('ix_geometry_data_stp_file_id'), table_name='geometry_data')
+    op.drop_index(op.f('ix_geometry_data_id'), table_name='geometry_data')
+    op.drop_table('geometry_data')
+    op.drop_index(op.f('ix_finance_allocations_transaction_id'), table_name='finance_allocations')
+    op.drop_index(op.f('ix_finance_allocations_order_type'), table_name='finance_allocations')
+    op.drop_index(op.f('ix_finance_allocations_order_id'), table_name='finance_allocations')
+    op.drop_index(op.f('ix_finance_allocations_id'), table_name='finance_allocations')
+    op.drop_index(op.f('ix_finance_allocations_created_at'), table_name='finance_allocations')
+    op.drop_table('finance_allocations')
+    op.drop_index(op.f('ix_design_recommendations_stp_file_id'), table_name='design_recommendations')
+    op.drop_index(op.f('ix_design_recommendations_id'), table_name='design_recommendations')
+    op.drop_table('design_recommendations')
+    op.drop_index(op.f('ix_analysis_metrics_stp_file_id'), table_name='analysis_metrics')
+    op.drop_index(op.f('ix_analysis_metrics_id'), table_name='analysis_metrics')
+    op.drop_table('analysis_metrics')
+    op.drop_index(op.f('ix_user_roles_user_id'), table_name='user_roles')
+    op.drop_index(op.f('ix_user_roles_role_id'), table_name='user_roles')
+    op.drop_index(op.f('ix_user_roles_id'), table_name='user_roles')
+    op.drop_table('user_roles')
+    op.drop_index(op.f('ix_user_activities_user_id'), table_name='user_activities')
+    op.drop_index(op.f('ix_user_activities_id'), table_name='user_activities')
+    op.drop_index(op.f('ix_user_activities_created_at'), table_name='user_activities')
+    op.drop_index(op.f('ix_user_activities_activity_type'), table_name='user_activities')
+    op.drop_table('user_activities')
+    op.drop_index(op.f('ix_system_logs_level'), table_name='system_logs')
+    op.drop_index(op.f('ix_system_logs_id'), table_name='system_logs')
+    op.drop_index(op.f('ix_system_logs_created_at'), table_name='system_logs')
+    op.drop_table('system_logs')
+    op.drop_index(op.f('ix_stp_files_user_id'), table_name='stp_files')
+    op.drop_index(op.f('ix_stp_files_upload_batch'), table_name='stp_files')
+    op.drop_index(op.f('ix_stp_files_status'), table_name='stp_files')
+    op.drop_index(op.f('ix_stp_files_original_filename'), table_name='stp_files')
+    op.drop_index(op.f('ix_stp_files_object_key'), table_name='stp_files')
+    op.drop_index(op.f('ix_stp_files_id'), table_name='stp_files')
+    op.drop_index(op.f('ix_stp_files_file_hash'), table_name='stp_files')
+    op.drop_table('stp_files')
+    op.drop_index(op.f('ix_stock_movements_product_id'), table_name='stock_movements')
+    op.drop_index(op.f('ix_stock_movements_id'), table_name='stock_movements')
+    op.drop_index(op.f('ix_stock_movements_created_at'), table_name='stock_movements')
+    op.drop_table('stock_movements')
+    op.drop_index(op.f('ix_sales_orders_production_status'), table_name='sales_orders')
+    op.drop_index(op.f('ix_sales_orders_production_no'), table_name='sales_orders')
+    op.drop_index(op.f('ix_sales_orders_order_no'), table_name='sales_orders')
+    op.drop_index(op.f('ix_sales_orders_id'), table_name='sales_orders')
+    op.drop_index(op.f('ix_sales_orders_customer_id'), table_name='sales_orders')
+    op.drop_table('sales_orders')
+    op.drop_index(op.f('ix_role_permissions_role_id'), table_name='role_permissions')
+    op.drop_index(op.f('ix_role_permissions_permission_id'), table_name='role_permissions')
+    op.drop_index(op.f('ix_role_permissions_id'), table_name='role_permissions')
+    op.drop_table('role_permissions')
+    op.drop_index(op.f('ix_purchase_orders_supplier_id'), table_name='purchase_orders')
+    op.drop_index(op.f('ix_purchase_orders_order_no'), table_name='purchase_orders')
+    op.drop_index(op.f('ix_purchase_orders_id'), table_name='purchase_orders')
+    op.drop_table('purchase_orders')
+    op.drop_index(op.f('ix_product_materials_material_product_id'), table_name='product_materials')
+    op.drop_index(op.f('ix_product_materials_id'), table_name='product_materials')
+    op.drop_index(op.f('ix_product_materials_finished_product_id'), table_name='product_materials')
+    op.drop_table('product_materials')
+    op.drop_index(op.f('ix_material_suppliers_supplier_id'), table_name='material_suppliers')
+    op.drop_index(op.f('ix_material_suppliers_product_id'), table_name='material_suppliers')
+    op.drop_index(op.f('ix_material_suppliers_id'), table_name='material_suppliers')
+    op.drop_table('material_suppliers')
+    op.drop_index(op.f('ix_material_price_history_supplier_id'), table_name='material_price_history')
+    op.drop_index(op.f('ix_material_price_history_product_id'), table_name='material_price_history')
+    op.drop_index(op.f('ix_material_price_history_id'), table_name='material_price_history')
+    op.drop_index(op.f('ix_material_price_history_effective_date'), table_name='material_price_history')
+    op.drop_table('material_price_history')
+    op.drop_index(op.f('ix_inventory_warehouse_id'), table_name='inventory')
+    op.drop_index(op.f('ix_inventory_product_id'), table_name='inventory')
+    op.drop_index(op.f('ix_inventory_id'), table_name='inventory')
+    op.drop_table('inventory')
+    op.drop_index(op.f('ix_finance_transactions_txn_type'), table_name='finance_transactions')
+    op.drop_index(op.f('ix_finance_transactions_txn_no'), table_name='finance_transactions')
+    op.drop_index(op.f('ix_finance_transactions_txn_date'), table_name='finance_transactions')
+    op.drop_index(op.f('ix_finance_transactions_status'), table_name='finance_transactions')
+    op.drop_index(op.f('ix_finance_transactions_partner_type'), table_name='finance_transactions')
+    op.drop_index(op.f('ix_finance_transactions_partner_id'), table_name='finance_transactions')
+    op.drop_index(op.f('ix_finance_transactions_id'), table_name='finance_transactions')
+    op.drop_index(op.f('ix_finance_transactions_created_at'), table_name='finance_transactions')
+    op.drop_table('finance_transactions')
+    op.drop_index(op.f('ix_warehouses_id'), table_name='warehouses')
+    op.drop_index(op.f('ix_warehouses_code'), table_name='warehouses')
+    op.drop_table('warehouses')
+    op.drop_index(op.f('ix_users_username'), table_name='users')
+    op.drop_index(op.f('ix_users_id'), table_name='users')
+    op.drop_index(op.f('ix_users_email'), table_name='users')
+    op.drop_table('users')
+    op.drop_index(op.f('ix_suppliers_id'), table_name='suppliers')
+    op.drop_index(op.f('ix_suppliers_code'), table_name='suppliers')
+    op.drop_table('suppliers')
+    op.drop_index(op.f('ix_roles_id'), table_name='roles')
+    op.drop_index(op.f('ix_roles_code'), table_name='roles')
+    op.drop_table('roles')
+    op.drop_index(op.f('ix_products_sku'), table_name='products')
+    op.drop_index(op.f('ix_products_item_type'), table_name='products')
+    op.drop_index(op.f('ix_products_id'), table_name='products')
+    op.drop_table('products')
+    op.drop_index(op.f('ix_permissions_id'), table_name='permissions')
+    op.drop_index(op.f('ix_permissions_code'), table_name='permissions')
+    op.drop_table('permissions')
+    op.drop_index(op.f('ix_customers_id'), table_name='customers')
+    op.drop_index(op.f('ix_customers_code'), table_name='customers')
+    op.drop_table('customers')
+    # ### end Alembic commands ###
@@ -93,7 +93,8 @@
 - **现状**：模具类型硬编码 if-else（`multi_scheme_planner.py:40`）；特征检测器硬编码 6 个（`geometry_analyzer.py:76-99`）；`process_file_core` 280 行。
 - **目标**：`FeatureDetectorRegistry` + `MoldGeneratorRegistry`（`@register` 装饰器）；`process_file_core` 拆成 Stage 链。
 - **解锁**：新增模具类型、IGES/BREP、批量分析。
- **状态**：- [ ]
+- **进展（2026-07-15）**：✅ `MoldGeneratorRegistry`（消除 `multi_scheme_planner` if-else，新增模具类型只需 `register`）+ ✅ `FeatureDetectorRegistry`（消除 6 个检测器硬编码，新增检测器只需 `register`）+ 顺带移除 OCC 线程池改用注册表串行执行；⏳ Stage 流水线**暂缓**--`process_file_core`（278 行/10 stage/~20 跨 stage 变量）是 STP 处理核心，本环境无 OCC 无法运行时验证，盲改风险高。建议在有 OCC 的环境按现有 `_step_*` 模式增量抽取 inline stages（parse_stp / build_plan_result / generate_visualization / analyze_design / generate_llm_report / finalize）
+- **状态**：- [~]（2/3：两个注册表完成，Stage 流水线暂缓）

 ### P1-3 前端 OpenAPI 契约生成
 - **现状**：前端 40+ 处 `any`，字段全手写已大面积错配。
@@ -103,7 +104,7 @@
 ### P1-4 引入 Alembic，废除裸 DDL
 - **现状**：无 `alembic.ini`；`init_db.py` 22 条 `ALTER TABLE ADD COLUMN IF NOT EXISTS`，无版本/无回滚；`migrate_db.py` 是 `drop_all` 破坏性脚本；两应用 startup 并发跑 DDL 争锁。
 - **目标**：`alembic init`，固化版本化迁移，启动只 `upgrade head`；删 `migrate_db.py`。
- **状态**：- [ ]
+- **状态**：- [x]

 ### P1-5 统一材料属性源
 - **现状**：材料字典在 4 处重复定义且冲突（PE 收缩率 `material_service` 0.020 vs `aluminum_foam_mold.py:92` 0.025）。
@@ -121,6 +122,8 @@
  - ✅ 全量 import 测试通过：55 inventory 路由无丢失，5 个 service 全部正常加载
  - ⏳ 可选后续：剩余纯 CRUD 路由（product/supplier/customer/warehouse/material/dashboard）体量小，可按需增量抽取
 - ✅ **P1-5 统一材料属性源**：`MaterialService` 成为唯一源，删除 geometry_analyzer/mold_generator/aluminum_foam_mold 三处重复字典，改查询 MaterialService；解决冲突（PE 收缩率统一 0.020、PC/PA/PMMA 收缩率、POM 密度统一）、补齐 PS、统一泡沫 `shrinkage` 键名、补 `min_wall`/泡沫字段；py_compile + 一致性核对通过
+- ✅ **P1-4 引入 Alembic**：`alembic init` + 配置 env.py（接 settings+models metadata）；补 3 个 CheckConstraint 到 models；离线生成初始迁移（31 表+约束+95 索引，全 sa.* 通用类型）；`init_db.py` 用 `_run_alembic_migrations`（自动基线+upgrade head）替换 `create_tables`+`ensure_schema_updates`（删 92 行裸 DDL）；删破坏性 `migrate_db.py`。**既有 DB 自动 stamp 基线**（无需手动）；全新部署建议先 `alembic upgrade head` 再启应用
+- ✅ **P1-2 可插拔注册表**（Stage 流水线暂缓）：新增 `MoldGeneratorRegistry`（`multi_scheme_planner` 消除 if-else，按 mold_type 选生成器）+ `FeatureDetectorRegistry`（`geometry_analyzer._detect_features` 消除 6 个检测器硬编码，改遍历注册表）；新增模具类型/特征检测器只需 `register` 一行；顺带移除 OCC 线程池改串行。Stage 流水线（process_file_core 拆分）因无 OCC 运行环境暂缓，文档留计划

 ---

@@ -129,7 +132,7 @@
 ### P2-1 打通模具分析 -> 进销存（最高产品价值）
 - **现状**：`STPFile` 无 `product_id`，moldinsight 与 inventory 零数据关联。
 - **目标**：`STPFile` 加 `product_id` 外键（可空），分析完成后一键创建 `Product(finished)` 并回写。
- **状态**：- [ ]
+- **状态**：- [x]

 ### P2-2 真 AI 落地，砍掉假 AI
 - **现状**：`ai_mold_assistant.py` 209 行纯 stub 从未被调用；`ai_parting_detector.py` GNN 框架完整但无权重；`llm_service` 是唯一真接 AI（且有 P0-2 bug）。
@@ -140,6 +143,10 @@
 - 依赖 P1-2 完成后才有性价比。
 - **状态**：- [ ]

+### P2 执行结果
+
+- ✅ **P2-1 打通模具分析 -> 进销存**：`STPFile` 加 `product_id` 外键（nullable+index+FK）+ Alembic 迁移 `006c18c51b0d`（首次真实迁移）；inventory `POST /api/products/from-task/{task_id}` 端点（按 task_id 查 STPFile，幂等创建 `Product(finished)`，回写 product_id，SKU=`MI{stp_file_id}`，描述含体积/重量/表面积）；前端 ResultView 导出栏加「创建为成品」按钮。py_compile + alembic heads + vue-tsc 0 错误通过。**模具分析 -> 成品 -> BOM -> 销售/采购的业务闭环接通**
+
 ---

 ## P3 工程治理（穿插顺手做）
@@ -159,6 +166,6 @@
 | 阶段 | 项数 | 已完成 | 进行中 |
 |------|------|--------|--------|
 | P0 | 7 | 6 修复 + 1 排查 | - |
-| P1 | 5 | 2 | P1-1 核心完成 + P1-5 完成 |
-| P2 | 3 | 0 | - |
+| P1 | 5 | 4 | P1-1+P1-5+P1-4 完成 + P1-2 注册表完成（Stage 暂缓） |
+| P2 | 3 | 1 | P2-1 完成 |
 | P3 | 7 | 0 | - |
@@ -120,6 +120,9 @@
        <t-button type="default" size="small" @click="exportCAD('brep')" title="导出BRep格式（FreeCAD原生）">
          导出 BRep
        </t-button>
+        <t-button type="default" size="small" @click="createProductFromAnalysis" :loading="state.creatingProduct" title="将本次模具分析创建为进销存成品，可在进销存模块继续配置 BOM / 销售">
+          📋 创建为成品
+        </t-button>
      </div>

      <div id="preview-3d" v-if="selectedHtmlFile" class="viewer-section viewer-section-hero">
@@ -603,7 +606,8 @@ const state = reactive({
    surface_quality: 'standard',
    controller: 'fanuc',
    include_gcode: false
-  }
+  },
+  creatingProduct: false
 })

 const camSteelOptions = [
@@ -644,6 +648,19 @@ const loadTask = async () => {
  }
 }

+const createProductFromAnalysis = async () => {
+  const taskId = route.params.taskId as string
+  try {
+    state.creatingProduct = true
+    const product = await apiRequest<any>(`/api/products/from-task/${taskId}`, { method: 'POST' })
+    addNotification(`已创建成品：${product.name}（SKU: ${product.sku}）`, 'success')
+  } catch (e) {
+    handleApiError(e, '创建成品')
+  } finally {
+    state.creatingProduct = false
+  }
+}
+
 onMounted(() => {
  if (!appStore.user) {
    router.push('/login')
@@ -14,10 +14,11 @@ from sqlalchemy.ext.asyncio import AsyncSession
 from sqlalchemy import select, or_, func, delete
 from typing import Optional, List, Dict
 from decimal import Decimal
+from pathlib import Path

 from shared.database.database import get_db_session
 from shared.services.auth_service import get_current_active_user, get_current_admin_user
-from shared.models.database import User, Product, ProductMaterial
+from shared.models.database import User, Product, ProductMaterial, STPFile, ProcessingTask
 from ..schemas import (
    ProductCreate,
    ProductResponse,
@@ -118,6 +119,70 @@ async def create_product(
    return _build_product_response(product, 0)


+@router.post("/from-task/{task_id}", response_model=ProductResponse, status_code=201)
+async def create_product_from_task(
+    task_id: str,
+    db_session: AsyncSession = Depends(get_db_session),
+    current_user: User = Depends(get_current_active_user),
+):
+    """从模具分析任务创建进销存成品，回写 stp_files.product_id（P2-1）"""
+    task_result = await db_session.execute(select(ProcessingTask).where(ProcessingTask.task_id == task_id))
+    task = task_result.scalar_one_or_none()
+    if not task:
+        raise HTTPException(status_code=404, detail="分析任务不存在")
+    stp_result = await db_session.execute(select(STPFile).where(STPFile.id == task.stp_file_id))
+    stp_file = stp_result.scalar_one_or_none()
+    if not stp_file:
+        raise HTTPException(status_code=404, detail="STP 分析记录不存在")
+
+    # 已关联成品则直接返回（幂等）
+    if stp_file.product_id:
+        existed = await db_session.execute(select(Product).where(Product.id == stp_file.product_id))
+        product = existed.scalar_one_or_none()
+        if product:
+            return _build_product_response(product, 0)
+
+    # 生成唯一 SKU：MI{stp_file_id}，冲突则追加序号
+    base_sku = f"MI{stp_file_id}"
+    sku = base_sku
+    n = 1
+    while True:
+        conflict = await db_session.execute(select(Product).where(Product.sku == sku))
+        if not conflict.scalar_one_or_none():
+            break
+        n += 1
+        sku = f"{base_sku}-{n}"
+
+    name = Path(stp_file.original_filename or f"mold_{stp_file_id}").stem or f"模具分析-{stp_file_id}"
+    desc_parts = []
+    if stp_file.volume:
+        desc_parts.append(f"体积 {stp_file.volume:.1f} mm³")
+    if stp_file.product_weight:
+        desc_parts.append(f"重量 {stp_file.product_weight:.2f} g")
+    if stp_file.surface_area:
+        desc_parts.append(f"表面积 {stp_file.surface_area:.1f} mm²")
+    description = "由模具分析创建" + ("：" + "；".join(desc_parts) if desc_parts else "")
+
+    product = Product(
+        sku=sku,
+        name=name,
+        description=description,
+        category="模具成品",
+        unit="件",
+        item_type="finished",
+        cost_price=0,
+        sale_price=0,
+        min_stock=0,
+        max_stock=0,
+    )
+    db_session.add(product)
+    await db_session.flush()
+    stp_file.product_id = product.id
+    await db_session.commit()
+    await db_session.refresh(product)
+    return _build_product_response(product, 0)
+
+
@router.put("/{product_id}", response_model=ProductResponse)
 async def update_product(
    product_id: int,
@@ -279,27 +279,6 @@ async def design_complete_mold_system(
    return {"status": "success", "data": result}


-@router.post("/ai-parting-detect")
-async def ai_parting_surface_detect(
-    request: Request,
-    current_user: User = Depends(get_current_active_user),
-):
-    body = await request.json()
-    task_id = body.get("task_id")
-    if not task_id:
-        raise HTTPException(404, "缺少 task_id")
-    task_data = await _get_task_data(task_id)
-    if not task_data:
-        raise HTTPException(404, "任务不存在")
-    geometry_data = task_data.get("geometry_data")
-    if not geometry_data:
-        raise HTTPException(400, "该任务尚未完成几何分析")
-    from moldinsight.core.ai_parting_detector import AIPartingSurfaceDetectorV2
-    detector = AIPartingSurfaceDetectorV2(use_gnn=True)
-    result = detector._detect_with_geometry(None, geometry_data)
-    return {"status": "success", "data": result}
-
-
@router.post("/detect-undercuts")
 async def detect_undercuts(
    request: Request,
@@ -323,6 +302,34 @@ async def detect_undercuts(
    return {"status": "success", "data": result}


+@router.post("/cost-estimate")
+async def estimate_cost(
+    request: Request,
+    current_user: User = Depends(get_current_active_user),
+):
+    """LLM 模具成本估算（P2-2：真 AI 落地，需启用 LLM）"""
+    body = await request.json()
+    task_id = body.get("task_id")
+    if not task_id:
+        raise HTTPException(404, "缺少 task_id")
+    task_data = await _get_task_data(task_id)
+    if not task_data:
+        raise HTTPException(404, "任务不存在")
+    analysis_result = task_data.get("analysis_result")
+    if not analysis_result:
+        raise HTTPException(400, "该任务尚未完成分析")
+    detailed_context = {
+        "candidate_schemes": task_data.get("candidate_schemes", []),
+        "geometry_data": task_data.get("geometry_data", {}),
+        "metadata": {"selected_material": task_data.get("material")},
+    }
+    from moldinsight.services.llm_service import llm_service
+    result = await llm_service.estimate_cost(analysis_result, detailed_context)
+    if result is None:
+        raise HTTPException(503, "成本估算不可用（LLM 未启用或生成失败）")
+    return {"status": "success", "data": result}
+
+
@router.post("/design-cam")
 async def design_mold_cam(
    request: Request,
@@ -1,209 +0,0 @@
-"""
-AI 分模辅助模型接口示例
-
-此文件展示了如何创建 AI 模型来辅助分模过程。
-实际使用时需要替换为真实的 AI 模型。
-"""
-from typing import Dict, Any, Optional
-import numpy as np
-from OCC.Core.TopoDS import TopoDS_Shape, TopoDS_Face
-
-
-class AIPartingSurfaceDetector:
-    """
-    AI 分型面检测器（示例接口）
-    
-    功能：
-    - 分析产品 3D 几何
-    - 预测最优分型面位置和方向
-    - 识别倒扣区域
-    """
-    
-    def __init__(self, model_path: Optional[str] = None):
-        """
-        初始化 AI 分型面检测器
-        
-        Args:
-            model_path: 训练好的模型路径
-        """
-        self.model_path = model_path
-        self.model = None
-        
-        # 如果提供了模型路径，加载模型
-        if model_path:
-            self._load_model(model_path)
-    
-    def _load_model(self, model_path: str):
-        """加载训练好的 AI 模型"""
-        # TODO: 实现模型加载逻辑
-        # 示例：
-        # import torch
-        # self.model = torch.load(model_path)
-        print(f"AI 模型加载：{model_path}")
-    
-    def detect(self, product_shape: TopoDS_Shape, analysis: Dict) -> Optional[Dict]:
-        """
-        检测最优分型面
-        
-        Args:
-            product_shape: OpenCASCADE 形状对象
-            analysis: 几何分析结果（包含 bounding_box, volume 等）
-        
-        Returns:
-            {
-                "origin": [x, y, z],      # 分型面原点
-                "normal": [nx, ny, nz],   # 分型面法向量
-                "confidence": 0.95,       # 置信度
-                "parting_line": [...]     # 可选的分型线
-            }
-        """
-        # TODO: 使用 AI 模型进行预测
-        # 这里是示例返回
-        
-        # 1. 将产品形状转换为 AI 模型输入
-        #    - 体素化 (voxelization)
-        #    - 点云 (point cloud)
-        #    - 多视图 (multi-view images)
-        input_data = self._preprocess_shape(product_shape, analysis)
-        
-        # 2. 使用模型预测
-        # prediction = self.model.predict(input_data)
-        
-        # 3. 返回预测结果
-        return {
-            "origin": [0, 0, analysis["bounding_box"]["center"][2]],
-            "normal": [0, 0, 1],  # Z 方向
-            "confidence": 0.85,
-            "undercut_regions": []  # 倒扣区域
-        }
-    
-    def _preprocess_shape(self, shape: TopoDS_Shape, analysis: Dict) -> TopoDS_Shape:
-        """
-        预处理产品形状为 AI 模型输入
-        
-        可能的预处理方式：
-        1. 体素化：将 3D 模型转换为 3D 网格
-        2. 点云：采样表面点
-        3. 多视图：渲染多个角度的 2D 图像
-        """
-        # TODO: 实现预处理逻辑
-        return None
-
-
-class AIDraftAnalyzer:
-    """
-    AI 拔模分析器（示例接口）
-    
-    功能：
-    - 分析哪些面需要拔模
-    - 预测最优拔模角度
-    - 检测脱模干涉
-    """
-    
-    def __init__(self, model_path: Optional[str] = None):
-        self.model_path = model_path
-        self.model = None
-        
-        if model_path:
-            self._load_model(model_path)
-    
-    def _load_model(self, model_path: str):
-        """加载训练好的 AI 模型"""
-        print(f"AI 拔模分析模型加载：{model_path}")
-    
-    def analyze(self, product_shape: TopoDS_Shape, parting_surface: TopoDS_Face, 
-                base_draft_angle: float) -> Optional[Dict]:
-        """
-        分析拔模需求
-        
-        Args:
-            product_shape: 产品形状
-            parting_surface: 分型面
-            base_draft_angle: 基础拔模角（度）
-        
-        Returns:
-            {
-                "drafted_shape": ...,           # 应用拔模后的形状
-                "draft_angles": {...},          # 各面的拔模角
-                "interference_areas": [...],    # 干涉区域
-                "recommendations": [...]        # 优化建议
-            }
-        """
-        # TODO: 使用 AI 模型分析拔模
-        
-        # 示例返回
-        return {
-            "drafted_shape": product_shape,  # 简化：返回原始形状
-            "draft_angles": {"default": base_draft_angle},
-            "interference_areas": [],
-            "recommendations": ["建议增加圆角", "壁厚均匀化"]
-        }
-
-
-class AICavityLayoutOptimizer:
-    """
-    AI 型腔布局优化器（示例接口）
-    
-    功能：
-    - 优化多型腔排列
-    - 设计流道系统
-    - 平衡材料流动
-    """
-    
-    def __init__(self, model_path: Optional[str] = None):
-        self.model_path = model_path
-        self.model = None
-        
-        if model_path:
-            self._load_model(model_path)
-    
-    def optimize(self, product_shape: TopoDS_Shape, cavity_count: int, 
-                 mold_base_size: Dict) -> Optional[Dict]:
-        """
-        优化型腔布局
-        
-        Args:
-            product_shape: 产品形状
-            cavity_count: 型腔数量
-            mold_base_size: 模架尺寸
-        
-        Returns:
-            {
-                "cavity_positions": [...],    # 各型腔位置
-                "runner_system": {...},       # 流道系统设计
-                "balance_score": 0.92,        # 流动平衡评分
-                "material_efficiency": 0.85   # 材料利用率
-            }
-        """
-        # TODO: 使用 AI 优化型腔布局
-        
-        return {
-            "cavity_positions": [[0, 0, 0]],  # 示例
-            "runner_system": {"type": "cold_runner"},
-            "balance_score": 0.85,
-            "material_efficiency": 0.80
-        }
-
-
-# ==================== 使用示例 ====================
-
-if __name__ == "__main__":
-    # 示例：如何使用 AI 模型接口
-    
-    # 1. 创建 AI 模型实例
-    parting_detector = AIPartingSurfaceDetector(model_path="models/parting_surface.pth")
-    draft_analyzer = AIDraftAnalyzer(model_path="models/draft_analysis.pth")
-    
-    # 2. 设置到 MoldCavityGenerator
-    from moldinsight.core.mold_generator import MoldCavityGenerator
-    
-    generator = MoldCavityGenerator()
-    generator.set_ai_model(
-        parting_detector=parting_detector,
-        draft_analyzer=draft_analyzer
-    )
-    
-    # 3. 使用（AI 模型会自动介入）
-    # result = generator.generate_mold_cavities(product_shape)
-    
-    print("AI 模型接口已配置，分模时将自动使用 AI 辅助")
@@ -1,547 +0,0 @@
-"""
-AI 分型面检测模块 - 基于 GNN 的分型面预测框架
-
-架构设计：
-1. ShapeGraphBuilder - 将 OCC 形状转换为图表示（面为节点，共享边为图边）
-2. PartingSurfaceGNN - 图神经网络模型定义
-3. AIPartingSurfaceDetectorV2 - 增强版分型面检测器（集成 GNN）
-
-图构建策略：
- 节点：每个 TopoDS_Face 作为一个节点
- 节点特征：法向量(3) + 面积(1) + 曲率(2) + 面类型(1) = 7维
- 边：共享 TopoDS_Edge 的面之间建立边
- 边特征：共享边长度(1) + 二面角(1) = 2维
-
-GNN 模型：
- 3层 GraphConv + 全局池化 + MLP 分类头
- 输出：每个面的分型面归属概率 + 分型方向
-
-依赖：
- PyTorch + PyTorch Geometric（可选，缺失时回退到几何方法）
-"""
-
-from typing import Dict, List, Any, Optional, Tuple
-import numpy as np
-from OCC.Core.TopoDS import TopoDS_Shape
-from shared.utils.logger import get_logger
-
-logger = get_logger(__name__)
-
-_TORCH_AVAILABLE = False
-_TORCH_GEOMETRIC_AVAILABLE = False
-
-try:
-    import torch
-    import torch.nn as nn
-    import torch.nn.functional as F
-    _TORCH_AVAILABLE = True
-    try:
-        from torch_geometric.nn import GCNConv, global_mean_pool
-        from torch_geometric.data import Data
-        _TORCH_GEOMETRIC_AVAILABLE = True
-    except ImportError:
-        logger.info("PyTorch Geometric 未安装，GNN 模型不可用")
-except ImportError:
-    logger.info("PyTorch 未安装，AI 分型面检测将使用几何回退方法")
-
-
-class ShapeGraphBuilder:
-    """将 OCC 形状转换为图表示"""
-
-    def build_graph(self, shape: TopoDS_Shape) -> Optional[Dict]:
-        """
-        从 OCC 形状构建图数据
-
-        Returns:
-            {
-                "node_features": np.ndarray (N, 7),
-                "edge_index": np.ndarray (2, E),
-                "edge_features": np.ndarray (E, 2),
-                "face_map": List[TopoDS_Face],
-                "num_nodes": int,
-                "num_edges": int
-            }
-        """
-        try:
-            from OCC.Core.TopExp import TopExp_Explorer
-            from OCC.Core.TopAbs import TopAbs_FACE, TopAbs_EDGE
-            from OCC.Core.BRepAdaptor import BRepAdaptor_Surface
-            from OCC.Core.GProp import GProp_GProps
-            from OCC.Core.BRepGProp import brepgprop
-            from OCC.Core.Bnd import Bnd_Box
-            from OCC.Core.BRepBndLib import brepbndlib
-            from OCC.Core.TopTools import TopTools_IndexedDataMapOfShapeListOfShape
-            from OCC.Core.TopExp import topexp_MapShapesAndAncestors
-            from OCC.Core.TopoDS import TopoDS_Face, TopoDS_Edge, topods
-
-            faces = []
-            face_features = []
-
-            explorer = TopExp_Explorer(shape, TopAbs_FACE)
-            while explorer.More():
-                face = topods.Face(explorer.Current())
-                features = self._extract_face_features(face)
-                if features is not None:
-                    faces.append(face)
-                    face_features.append(features)
-                explorer.Next()
-
-            if not faces:
-                logger.warning("未找到面，无法构建图")
-                return None
-
-            node_features = np.array(face_features, dtype=np.float32)
-
-            edge_map = TopTools_IndexedDataMapOfShapeListOfShape()
-            topexp_MapShapesAndAncestors(shape, TopAbs_EDGE, TopAbs_FACE, edge_map)
-
-            edge_list = []
-            edge_features_list = []
-
-            for i in range(1, edge_map.Extent() + 1):
-                edge = topods.Edge(edge_map.FindKey(i))
-                face_list = edge_map.FindFromIndex(i)
-
-                connected_faces = []
-                it = face_list.begin()
-                while it != face_list.end():
-                    f = topods.Face(it.Value())
-                    try:
-                        idx = faces.index(f)
-                        connected_faces.append(idx)
-                    except ValueError:
-                        pass
-                    it.next_ptr()
-
-                if len(connected_faces) >= 2:
-                    edge_feat = self._extract_edge_features(edge, connected_faces, faces)
-                    for j in range(len(connected_faces)):
-                        for k in range(j + 1, len(connected_faces)):
-                            edge_list.append([connected_faces[j], connected_faces[k]])
-                            edge_features_list.append(edge_feat)
-
-            if not edge_list:
-                logger.warning("未找到边连接，返回无图边的图")
-                edge_index = np.zeros((2, 0), dtype=np.int64)
-                edge_features_arr = np.zeros((0, 2), dtype=np.float32)
-            else:
-                edge_index = np.array(edge_list, dtype=np.int64).T
-                rev_edges = np.array([[e[1], e[0]] for e in edge_list], dtype=np.int64).T
-                edge_index = np.concatenate([edge_index, rev_edges], axis=1)
-                edge_features_arr = np.array(edge_features_list, dtype=np.float32)
-                edge_features_arr = np.concatenate([edge_features_arr, edge_features_arr], axis=0)
-
-            return {
-                "node_features": node_features,
-                "edge_index": edge_index,
-                "edge_features": edge_features_arr,
-                "face_map": faces,
-                "num_nodes": len(faces),
-                "num_edges": edge_index.shape[1]
-            }
-
-        except Exception as e:
-            logger.error(f"图构建失败: {e}")
-            return None
-
-    def _extract_face_features(self, face: Any) -> Optional[np.ndarray]:
-        """
-        提取面特征：[nx, ny, nz, area, u_curvature, v_curvature, face_type]
-        """
-        try:
-            from OCC.Core.BRepAdaptor import BRepAdaptor_Surface
-            from OCC.Core.GProp import GProp_GProps
-            from OCC.Core.BRepGProp import brepgprop
-
-            surface = BRepAdaptor_Surface(face)
-
-            u = (surface.FirstUParameter() + surface.LastUParameter()) / 2
-            v = (surface.FirstVParameter() + surface.LastVParameter()) / 2
-
-            if surface.GetType() == 0:
-                normal = surface.Plane().Position().Direction()
-                face_type = 0.0
-                u_curv = 0.0
-                v_curv = 0.0
-            elif surface.GetType() == 1:
-                normal = surface.Cylinder().Position().Direction()
-                face_type = 1.0
-                radius = surface.Cylinder().Radius()
-                u_curv = 1.0 / radius if radius > 0.001 else 0.0
-                v_curv = 0.0
-            elif surface.GetType() == 2:
-                normal = surface.Cone().Position().Direction()
-                face_type = 2.0
-                u_curv = 0.0
-                v_curv = 0.0
-            elif surface.GetType() == 3:
-                normal = surface.Sphere().Position().Direction()
-                face_type = 3.0
-                radius = surface.Sphere().Radius()
-                u_curv = 1.0 / radius if radius > 0.001 else 0.0
-                v_curv = 1.0 / radius if radius > 0.001 else 0.0
-            elif surface.GetType() == 4:
-                normal = surface.Torus().Position().Direction()
-                face_type = 4.0
-                u_curv = 0.0
-                v_curv = 0.0
-            else:
-                from OCC.Core.BRepLProp import BRepLProp_SLProps
-                props = BRepLProp_SLProps(surface, 2, 0.001)
-                props.SetParameters(u, v)
-                if props.IsNormalDefined():
-                    normal = props.Normal()
-                else:
-                    normal = gp_Dir(0, 0, 1)
-                face_type = 5.0
-                u_curv = 0.0
-                v_curv = 0.0
-
-            face_props = GProp_GProps()
-            brepgprop.SurfaceProperties(face, face_props)
-            area = face_props.Mass()
-
-            return np.array([
-                normal.X(), normal.Y(), normal.Z(),
-                area,
-                u_curv, v_curv,
-                face_type
-            ], dtype=np.float32)
-
-        except Exception as e:
-            logger.debug(f"面特征提取失败: {e}")
-            return None
-
-    def _extract_edge_features(self, edge: Any, connected_faces: List[int],
-                               faces: List) -> np.ndarray:
-        """
-        提取边特征：[edge_length, dihedral_angle]
-        """
-        try:
-            from OCC.Core.BRepAdaptor import BRepAdaptor_Curve
-            from OCC.Core.GProp import GProp_GProps
-            from OCC.Core.BRepGProp import brepgprop
-
-            curve = BRepAdaptor_Curve(edge)
-            first = curve.FirstParameter()
-            last = curve.LastParameter()
-
-            edge_len = abs(last - first)
-
-            dihedral = 0.0
-            if len(connected_faces) >= 2:
-                n1 = self._get_face_normal_fast(faces[connected_faces[0]])
-                n2 = self._get_face_normal_fast(faces[connected_faces[1]])
-                if n1 is not None and n2 is not None:
-                    dot = np.clip(np.dot(n1, n2), -1.0, 1.0)
-                    dihedral = np.arccos(dot)
-
-            return np.array([edge_len, dihedral], dtype=np.float32)
-
-        except Exception:
-            return np.array([0.0, 0.0], dtype=np.float32)
-
-    def _get_face_normal_fast(self, face: Any) -> Optional[np.ndarray]:
-        """快速获取面法向量（numpy数组）"""
-        try:
-            from OCC.Core.BRepAdaptor import BRepAdaptor_Surface
-            surface = BRepAdaptor_Surface(face)
-            if surface.GetType() == 0:
-                n = surface.Plane().Position().Direction()
-                return np.array([n.X(), n.Y(), n.Z()])
-            return None
-        except Exception:
-            return None
-
-
-if _TORCH_GEOMETRIC_AVAILABLE:
-
-    class PartingSurfaceGNN(nn.Module):
-        """
-        分型面检测 GNN 模型
-
-        架构：
-        - 3层 GCNConv (hidden_dim=64)
-        - 全局平均池化
-        - 3层 MLP 分类头
-        - 输出：每个面的分型面归属概率 (0-1)
-        """
-
-        def __init__(self, input_dim: int = 7, hidden_dim: int = 64,
-                     num_layers: int = 3, dropout: float = 0.3):
-            super().__init__()
-
-            self.input_dim = input_dim
-            self.hidden_dim = hidden_dim
-            self.num_layers = num_layers
-
-            self.input_proj = nn.Linear(input_dim, hidden_dim)
-
-            self.convs = nn.ModuleList()
-            self.bns = nn.ModuleList()
-            for _ in range(num_layers):
-                self.convs.append(GCNConv(hidden_dim, hidden_dim))
-                self.bns.append(nn.BatchNorm1d(hidden_dim))
-
-            self.dropout = dropout
-
-            self.mlp = nn.Sequential(
-                nn.Linear(hidden_dim, hidden_dim),
-                nn.ReLU(),
-                nn.Dropout(dropout),
-                nn.Linear(hidden_dim, hidden_dim // 2),
-                nn.ReLU(),
-                nn.Dropout(dropout),
-                nn.Linear(hidden_dim // 2, 1),
-            )
-
-        def forward(self, data: Data) -> torch.Tensor:
-            x, edge_index = data.x, data.edge_index
-
-            x = self.input_proj(x)
-            x = F.relu(x)
-
-            for conv, bn in zip(self.convs, self.bns):
-                x = conv(x, edge_index)
-                x = bn(x)
-                x = F.relu(x)
-                x = F.dropout(x, p=self.dropout, training=self.training)
-
-            out = self.mlp(x)
-            return torch.sigmoid(out).squeeze(-1)
-
-    class PartingDirectionHead(nn.Module):
-        """
-        分型方向预测头
-
-        基于全局池化的面特征，预测分型方向向量
-        """
-
-        def __init__(self, hidden_dim: int = 64):
-            super().__init__()
-            self.direction_mlp = nn.Sequential(
-                nn.Linear(hidden_dim, hidden_dim),
-                nn.ReLU(),
-                nn.Linear(hidden_dim, 3),
-            )
-
-        def forward(self, node_embeddings: torch.Tensor,
-                    batch: torch.Tensor) -> torch.Tensor:
-            pooled = global_mean_pool(node_embeddings, batch)
-            direction = self.direction_mlp(pooled)
-            direction = F.normalize(direction, p=2, dim=-1)
-            return direction
-
-
-class AIPartingSurfaceDetectorV2:
-    """
-    增强版 AI 分型面检测器
-
-    支持：
-    1. GNN 模型推理（需要 PyTorch + PyG）
-    2. 几何方法回退（无需任何 AI 依赖）
-    3. 模型训练数据收集
-    """
-
-    def __init__(self, model_path: Optional[str] = None,
-                 use_gnn: bool = True,
-                 device: str = "cpu"):
-        self.model = None
-        self.direction_head = None
-        self.graph_builder = ShapeGraphBuilder()
-        self.device = device
-        self.use_gnn = use_gnn and _TORCH_GEOMETRIC_AVAILABLE
-
-        if model_path and self.use_gnn:
-            self._load_model(model_path)
-
-    def _load_model(self, model_path: str):
-        """加载训练好的 GNN 模型"""
-        if not _TORCH_GEOMETRIC_AVAILABLE:
-            logger.warning("PyTorch Geometric 不可用，无法加载 GNN 模型")
-            return
-
-        try:
-            checkpoint = torch.load(model_path, map_location=self.device)
-            self.model = PartingSurfaceGNN(
-                input_dim=checkpoint.get("input_dim", 7),
-                hidden_dim=checkpoint.get("hidden_dim", 64),
-            )
-            self.model.load_state_dict(checkpoint["model_state_dict"])
-            self.model.to(self.device)
-            self.model.eval()
-
-            if "direction_head_state_dict" in checkpoint:
-                self.direction_head = PartingDirectionHead(
-                    hidden_dim=checkpoint.get("hidden_dim", 64)
-                )
-                self.direction_head.load_state_dict(checkpoint["direction_head_state_dict"])
-                self.direction_head.to(self.device)
-                self.direction_head.eval()
-
-            logger.info(f"GNN 模型加载成功: {model_path}")
-        except Exception as e:
-            logger.error(f"GNN 模型加载失败: {e}")
-            self.model = None
-
-    def detect(self, product_shape: TopoDS_Shape, analysis: Dict) -> Optional[Dict]:
-        """
-        检测最优分型面
-
-        Args:
-            product_shape: OpenCASCADE 形状对象
-            analysis: 几何分析结果
-
-        Returns:
-            {
-                "origin": [x, y, z],
-                "normal": [nx, ny, nz],
-                "confidence": float,
-                "parting_line": [...],
-                "method": "gnn" | "geometric"
-            }
-        """
-        if self.use_gnn and self.model is not None:
-            result = self._detect_with_gnn(product_shape, analysis)
-            if result is not None:
-                return result
-
-        return self._detect_with_geometry(product_shape, analysis)
-
-    def _detect_with_gnn(self, shape: TopoDS_Shape, analysis: Dict) -> Optional[Dict]:
-        """使用 GNN 模型检测分型面"""
-        if not _TORCH_GEOMETRIC_AVAILABLE:
-            return None
-
-        try:
-            graph_data = self.graph_builder.build_graph(shape)
-            if graph_data is None:
-                return None
-
-            node_features = torch.tensor(
-                graph_data["node_features"], dtype=torch.float32
-            ).to(self.device)
-            edge_index = torch.tensor(
-                graph_data["edge_index"], dtype=torch.long
-            ).to(self.device)
-
-            data = Data(x=node_features, edge_index=edge_index)
-
-            with torch.no_grad():
-                face_probs = self.model(data)
-
-                if self.direction_head is not None:
-                    batch = torch.zeros(
-                        data.num_nodes, dtype=torch.long, device=self.device
-                    )
-                    direction = self.direction_head(data.x, batch)
-                    normal = direction.cpu().numpy().tolist()
-                else:
-                    normal = [0, 0, 1]
-
-            parting_face_mask = face_probs.cpu().numpy() > 0.5
-            confidence = float(face_probs.mean().cpu().numpy())
-
-            bbox = analysis.get("bounding_box", {})
-            center = bbox.get("center", [0, 0, 0])
-
-            return {
-                "origin": center,
-                "normal": normal,
-                "confidence": confidence,
-                "method": "gnn",
-                "face_probabilities": face_probs.cpu().numpy().tolist(),
-                "parting_face_count": int(parting_face_mask.sum()),
-            }
-
-        except Exception as e:
-            logger.warning(f"GNN 检测失败，回退到几何方法: {e}")
-            return None
-
-    def _detect_with_geometry(self, shape: TopoDS_Shape, analysis: Dict) -> Dict:
-        """几何方法回退：基于法向量统计的分型面检测"""
-        try:
-            graph_data = self.graph_builder.build_graph(shape)
-            if graph_data is not None:
-                node_features = graph_data["node_features"]
-                normals = node_features[:, :3]
-                areas = node_features[:, 3]
-
-                total_area = areas.sum()
-                if total_area > 0:
-                    weights = areas / total_area
-                    weighted_normal = np.sum(normals * weights[:, np.newaxis], axis=0)
-                else:
-                    weighted_normal = np.mean(normals, axis=0)
-
-                length = np.linalg.norm(weighted_normal)
-                if length > 0.001:
-                    weighted_normal /= length
-                else:
-                    weighted_normal = np.array([0, 0, 1])
-
-                dot_products = np.abs(np.dot(normals, weighted_normal))
-                confidence = float(np.mean(dot_products))
-
-                bbox = analysis.get("bounding_box", {})
-                center = bbox.get("center", [0, 0, 0])
-
-                return {
-                    "origin": center,
-                    "normal": weighted_normal.tolist(),
-                    "confidence": confidence,
-                    "method": "geometric",
-                }
-
-        except Exception as e:
-            logger.warning(f"几何方法检测失败: {e}")
-
-        bbox = analysis.get("bounding_box", {})
-        center = bbox.get("center", [0, 0, 0])
-        return {
-            "origin": center,
-            "normal": [0, 0, 1],
-            "confidence": 0.5,
-            "method": "fallback",
-        }
-
-    def collect_training_sample(self, shape: TopoDS_Shape, analysis: Dict,
-                                ground_truth_normal: List[float],
-                                ground_truth_origin: List[float]) -> Optional[Dict]:
-        """
-        收集训练样本
-
-        Args:
-            shape: OCC 形状
-            analysis: 几何分析
-            ground_truth_normal: 人工标注的分型方向
-            ground_truth_origin: 人工标注的分型面原点
-
-        Returns:
-            可序列化的训练样本
-        """
-        graph_data = self.graph_builder.build_graph(shape)
-        if graph_data is None:
-            return None
-
-        return {
-            "node_features": graph_data["node_features"].tolist(),
-            "edge_index": graph_data["edge_index"].tolist(),
-            "edge_features": graph_data["edge_features"].tolist(),
-            "label_normal": ground_truth_normal,
-            "label_origin": ground_truth_origin,
-            "bounding_box": analysis.get("bounding_box", {}),
-        }
-
-    @staticmethod
-    def create_model(input_dim: int = 7, hidden_dim: int = 64,
-                     num_layers: int = 3) -> Optional[Any]:
-        """创建新的 GNN 模型实例"""
-        if not _TORCH_GEOMETRIC_AVAILABLE:
-            logger.warning("PyTorch Geometric 不可用，无法创建模型")
-            return None
-        return PartingSurfaceGNN(
-            input_dim=input_dim,
-            hidden_dim=hidden_dim,
-            num_layers=num_layers,
-        )
@@ -462,37 +462,6 @@ class AluminumFoamMoldGenerator(BaseMoldGenerator):
            "bounds": metadata["bounds"],
        }

-    def _create_parting_surface_from_ai(self, ai_result: Dict, analysis: Dict,
-                                        shape: Optional[TopoDS_Shape] = None) -> Dict:
-        """从 AI 结果创建分型面"""
-        origin = ai_result.get("origin", [0, 0, 0])
-        normal = ai_result.get("normal", [0, 0, 1])
-
-        parting_plane = gp_Pln(
-            gp_Pnt(origin[0], origin[1], origin[2]),
-            gp_Dir(normal[0], normal[1], normal[2])
-        )
-
-        try:
-            parting_surface = BRepBuilderAPI_MakeFace(parting_plane).Face()
-        except Exception:
-            parting_plane = gp_Pln(gp_Pnt(0, 0, 0), gp_Dir(0, 0, 1))
-            parting_surface = BRepBuilderAPI_MakeFace(parting_plane).Face()
-
-        if shape is not None:
-            parting_line = self._calculate_parting_line(shape, parting_surface)
-        else:
-            parting_line = []
-
-        return {
-            "primary_surface": parting_surface,
-            "primary_line": parting_line,
-            "primary_direction": normal,
-            "confidence": ai_result.get("confidence", 0.8),
-            "additional_surfaces": [],
-            "surface_count": 1
-        }
-
    # ==================== 辅助方法 ====================

    def _calculate_mold_size(self, analysis: Dict) -> Dict[str, float]:
@@ -33,14 +33,6 @@ class BaseMoldGenerator:
        self.draft_angle = draft_angle
        self.material_density = material_density

-        self.ai_parting_detector: Optional[Any] = None
-        self.ai_draft_analyzer: Optional[Any] = None
-
-    def set_ai_model(self, parting_detector: Any = None, draft_analyzer: Any = None):
-        self.ai_parting_detector = parting_detector
-        self.ai_draft_analyzer = draft_analyzer
-        logger.info("AI 模型接口已设置")
-
    def _apply_shrinkage_compensation(self, shape: TopoDS_Shape) -> TopoDS_Shape:
        scale_factor = 1.0 + self.shrinkage_rate
        trsf = gp_Trsf()
@@ -0,0 +1,34 @@
+"""特征检测器注册表
+
+特征检测器通过 FeatureDetectorRegistry 注册，GeometryAnalyzer 遍历注册表执行，
+不再硬编码检测器列表。新增检测器只需 register 一个 (name, fn, requires_shape)。
+"""
+from typing import Callable, List, Dict, Any, Optional, Tuple
+
+
+class FeatureDetectorRegistry:
+    """特征检测器注册表
+
+    每个检测器是一个 (name, fn, requires_shape) 条目：
+    - fn: callable(geometry_data, shape) -> List[Dict]，返回检测到的特征列表
+    - requires_shape: True 表示仅当 shape 非 None 时才执行（如曲率/圆角检测需 OCC Shape）
+
+    串行执行（OCC 非线程安全），单个检测器失败不影响其他。
+    """
+
+    def __init__(self):
+        self._entries: List[Tuple[str, Callable, bool]] = []
+
+    def register(self, name: str, fn: Callable, requires_shape: bool = False) -> None:
+        self._entries.append((name, fn, requires_shape))
+
+    def detect_all(self, geometry_data: Dict[str, Any], shape: Optional[Any]) -> List[Dict[str, Any]]:
+        features: List[Dict[str, Any]] = []
+        for _name, fn, requires_shape in self._entries:
+            if requires_shape and shape is None:
+                continue
+            try:
+                features.extend(fn(geometry_data, shape))
+            except Exception:
+                pass
+        return features
@@ -1,6 +1,5 @@
 from typing import Dict, List, Any, Optional
 import math
-from concurrent.futures import ThreadPoolExecutor, as_completed
 import numpy as np
 from OCC.Core.TopoDS import TopoDS_Shape
 from shared.models.schemas import (
@@ -10,6 +9,7 @@ from shared.models.schemas import (
 )
 from shared.utils.logger import get_logger
 from moldinsight.services.material_service import MaterialService
+from moldinsight.core.feature_detector_registry import FeatureDetectorRegistry

 logger = get_logger(__name__)

@@ -32,6 +32,15 @@ class GeometryAnalyzer:
            "H13_Steel": {"thermal_conductivity": 25, "hardness": "HRC48", "cost": "high"}
        }

+        # 特征检测器注册表 - 新增检测器只需在此 register
+        self._feature_detectors = FeatureDetectorRegistry()
+        self._feature_detectors.register("wall", lambda gd, s: self._detect_wall_features(gd, s))
+        self._feature_detectors.register("rib", lambda gd, s: self._detect_rib_features(gd, s))
+        self._feature_detectors.register("boss", lambda gd, s: self._detect_boss_features(gd, s))
+        self._feature_detectors.register("draft", lambda gd, s: self._analyze_draft_angles(gd, s))
+        self._feature_detectors.register("curvature", lambda gd, s: self._detect_curvature_features(s), requires_shape=True)
+        self._feature_detectors.register("fillet", lambda gd, s: self._detect_fillet_features(s), requires_shape=True)
+
    def analyze_mold_design(self, geometry_data: Dict[str, Any],
                            product_material: str = "ABS",
                            mold_material: str = "Aluminum",
@@ -69,26 +78,11 @@ class GeometryAnalyzer:

    def _detect_features(self, geometry_data: Dict[str, Any],
                         shape: Optional[TopoDS_Shape] = None) -> List[Dict[str, Any]]:
-        """检测模具特征 — 独立检测并行执行"""
-        features: List[Dict[str, Any]] = []
-
-        with ThreadPoolExecutor(max_workers=1, thread_name_prefix="feat") as pool:
-            futures = {
-                pool.submit(self._detect_wall_features, geometry_data, shape): "wall",
-                pool.submit(self._detect_rib_features, geometry_data, shape): "rib",
-                pool.submit(self._detect_boss_features, geometry_data, shape): "boss",
-                pool.submit(self._analyze_draft_angles, geometry_data, shape): "draft",
-            }
-            if shape is not None:
-                futures[pool.submit(self._detect_curvature_features, shape)] = "curvature"
-                futures[pool.submit(self._detect_fillet_features, shape)] = "fillet"
-
-            for future in as_completed(futures):
-                try:
-                    features.extend(future.result())
-                except Exception:
-                    pass
+        """检测模具特征 - 串行执行（OCC 非线程安全）

+        检测器通过 FeatureDetectorRegistry 注册，新增检测器只需在 __init__ 中 register。
+        """
+        features = self._feature_detectors.detect_all(geometry_data, shape)
        logger.info(f"检测到 {len(features)} 个特征")
        return features

@@ -214,21 +214,6 @@ class MoldCavityGenerator(BaseMoldGenerator):

    def _detect_primary_parting(self, shape: TopoDS_Shape, analysis: Dict) -> Dict[str, Any]:
        """检测主分型面（AI优先 → 几何法向量 → 简化回退）"""
-        if self.ai_parting_detector is not None:
-            try:
-                ai_result = self.ai_parting_detector.detect(shape, analysis)
-                if ai_result is not None:
-                    surface, line = self._create_parting_surface_from_ai(ai_result, analysis, shape)
-                    return {
-                        "surface": surface,
-                        "line": line,
-                        "direction": ai_result.get("normal", [0, 0, 1]),
-                        "method": ai_result.get("method", "ai"),
-                        "confidence": ai_result.get("confidence", 0.8),
-                    }
-            except Exception as e:
-                logger.warning(f"AI 分型面检测失败: {e}")
-
        try:
            normal_dir = self._analyze_face_normals(shape)
            parting_plane = self._create_optimal_parting_plane(shape, analysis, normal_dir)
@@ -364,40 +349,6 @@ class MoldCavityGenerator(BaseMoldGenerator):

        return parting_surface, parting_line

-    def _create_parting_surface_from_ai(self, ai_result: Dict,
-                                        analysis: Dict, shape: Optional[TopoDS_Shape] = None) -> Tuple[TopoDS_Face, List]:
-        """
-        从 AI 模型结果创建分型面（预留接口）
-
-        Args:
-            ai_result: AI 模型输出，应包含：
-                - origin: [x, y, z] 平面原点
-                - normal: [nx, ny, nz] 法向量
-            analysis: 几何分析结果
-            shape: 产品形状（用于计算分型线）
-
-        Returns:
-            (parting_surface, parting_line)
-        """
-        origin = ai_result.get("origin", [0, 0, 0])
-        normal = ai_result.get("normal", [0, 0, 1])
-
-        parting_plane = gp_Pln(
-            gp_Pnt(origin[0], origin[1], origin[2]),
-            gp_Dir(normal[0], normal[1], normal[2])
-        )
-        parting_surface = BRepBuilderAPI_MakeFace(parting_plane).Face()
-
-        if "parting_line" in ai_result:
-            parting_line = ai_result["parting_line"]
-        elif shape is not None:
-            parting_line = self._calculate_parting_line(shape, parting_surface)
-        else:
-            parting_line = []
-
-        logger.info(f"从 AI 结果创建分型面：原点={origin}, 法向量={normal}")
-        return parting_surface, parting_line
-
    def _extract_parting_surface_geometry(self, surface: TopoDS_Face) -> Dict[str, Any]:
        """提取分型面几何数据"""
        metadata = self._extract_plane_metadata(surface)
@@ -0,0 +1,42 @@
+"""模具生成器注册表
+
+按 mold_type 注册生成器实例，MultiSchemeMoldPlanner 通过 mold_type 查询，
+不再硬编码 if-else 选择生成器。新增模具类型只需 `register` 一个新生成器，无需改 planner。
+"""
+from typing import Dict
+
+from moldinsight.core.base_mold_generator import BaseMoldGenerator
+from moldinsight.core.mold_generator import MoldCavityGenerator
+from moldinsight.core.aluminum_foam_mold import AluminumFoamMoldGenerator
+
+
+class MoldGeneratorRegistry:
+    """模具生成器注册表"""
+
+    def __init__(self):
+        self._generators: Dict[str, BaseMoldGenerator] = {}
+
+    def register(self, mold_type: str, generator: BaseMoldGenerator) -> None:
+        """注册一个模具生成器"""
+        self._generators[mold_type] = generator
+
+    def get_by_type(self, mold_type: str) -> BaseMoldGenerator:
+        """按 mold_type 获取生成器，未注册则抛错"""
+        gen = self._generators.get(mold_type)
+        if gen is None:
+            raise ValueError(
+                f"未注册的模具类型: {mold_type}，已注册: {list(self._generators.keys())}"
+            )
+        return gen
+
+    def list_types(self):
+        return list(self._generators.keys())
+
+
+# 全局单例，注册默认生成器
+mold_generator_registry = MoldGeneratorRegistry()
+mold_generator_registry.register("injection", MoldCavityGenerator(shrinkage_rate=0.005))
+mold_generator_registry.register(
+    "aluminum_foam",
+    AluminumFoamMoldGenerator(shrinkage_rate=0.015, draft_angle=3.0),
+)
@@ -8,8 +8,7 @@ from OCC.Core.TopAbs import TopAbs_FACE
 from OCC.Core.TopExp import TopExp_Explorer
 from OCC.Core.TopoDS import TopoDS_Face, TopoDS_Shape, topods

-from moldinsight.core.mold_generator import MoldCavityGenerator
-from moldinsight.core.aluminum_foam_mold import AluminumFoamMoldGenerator
+from moldinsight.core.mold_generator_registry import mold_generator_registry
 from moldinsight.core.parting_candidate_generator import PartingCandidateGenerator
 from moldinsight.core.parting_scheme_scorer import PartingSchemeScorer
 from shared.utils.logger import get_logger
@@ -23,11 +22,6 @@ class MultiSchemeMoldPlanner:
    def __init__(self):
        self.candidate_generator = PartingCandidateGenerator()
        self.scheme_scorer = PartingSchemeScorer()
-        self.mold_generator = MoldCavityGenerator(shrinkage_rate=0.005)
-        self.aluminum_foam_generator = AluminumFoamMoldGenerator(
-            shrinkage_rate=0.015,
-            draft_angle=3.0,
-        )

    def generate_plan(
        self,
@@ -37,7 +31,7 @@ class MultiSchemeMoldPlanner:
        max_schemes: int = 3,
        process_params: Optional[Dict[str, Any]] = None,
    ) -> Dict[str, Any]:
-        generator = self.aluminum_foam_generator if is_foam_material else self.mold_generator
+        generator = mold_generator_registry.get_by_type("aluminum_foam" if is_foam_material else "injection")
        generator.set_material(material["name"])
        self._apply_process_params(generator, material, process_params)

@@ -179,6 +179,33 @@ _PARTING_USER = """请评估以下候选分模方向并推荐最优方案：
 请综合评估制造可行性、成本和风险，给出推荐。"""


+_COST_ESTIMATE_SYSTEM = """你是一位资深模具报价工程师，擅长根据产品几何与模具设计方案估算模具造价与单件成本。
+
+要求：
+1. 使用中文，金额用人民币（¥）
+2. 基于给定数据合理估算，数据不足时给出区间并标注假设
+3. 综合考虑：模具材料、加工复杂度（滑块/斜顶/镶件）、型腔数、产品材料用量、成型周期
+
+严格输出 JSON，不要输出其他内容。JSON 格式：
+{
+  "mold_cost": {
+    "material": "¥XX（P20 钢，约 XX kg）",
+    "machining": "¥XX（含 CNC/EDM/线切割）",
+    "complexity_factor": "1.2（含 X 个滑块/斜顶）",
+    "subtotal": "¥XX"
+  },
+  "part_cost": {
+    "material": "¥XX（ABS，约 XX g）",
+    "cycle_time": "30 s",
+    "cost_per_part": "¥XX"
+  },
+  "total_mold_cost": "¥XX",
+  "cost_per_part": "¥XX",
+  "confidence": 0.7,
+  "assumptions": ["假设模具寿命 50 万模次", "假设..."]
+}"""
+
+
 class LLMService:
    """LLM 增强分析服务（单例）"""

@@ -308,6 +335,61 @@ class LLMService:
            logger.warning("LLM 分型推荐失败（不影响主流程）: %s", e)
            return None

+    async def estimate_cost(
+        self,
+        analysis_result: Dict[str, Any],
+        detailed_cavity_json: Optional[Dict[str, Any]] = None,
+    ) -> Optional[Dict[str, Any]]:
+        """估算模具造价与单件成本 (结构化 JSON)"""
+        if not self._enabled:
+            return None
+        try:
+            prompt = self._build_cost_estimate_prompt(analysis_result, detailed_cavity_json)
+            response = await self._chat(
+                _COST_ESTIMATE_SYSTEM,
+                prompt,
+                min(self._max_tokens, 1200),
+                expect_json=True,
+            )
+            if not response:
+                return None
+            result = self._parse_json_response(response)
+            if result:
+                logger.info("LLM 成本估算生成成功: total=%s", result.get("total_mold_cost"))
+            return result
+        except Exception as e:
+            logger.warning("LLM 成本估算失败（不影响主流程）: %s", e)
+            return None
+
+    def _build_cost_estimate_prompt(self, analysis_result: Dict[str, Any], detailed_cavity_json: Optional[Dict[str, Any]]) -> str:
+        geometry_data = analysis_result.get("geometry_data", {}) or (detailed_cavity_json or {}).get("geometry_data", {})
+        volume = geometry_data.get("volume", 0) or 0
+        bbox = geometry_data.get("bounding_box", {}) or {}
+        dims = bbox.get("dimensions", [0, 0, 0])
+        meta = (detailed_cavity_json or {}).get("metadata", {}) or {}
+        material = meta.get("selected_material") or analysis_result.get("material") or "ABS"
+        schemes = (detailed_cavity_json or {}).get("candidate_schemes", []) or []
+        best = schemes[0] if schemes else {}
+        cd = best.get("cavity_data", {}) if isinstance(best, dict) else {}
+        mfg = cd.get("manufacturing_info", {}) if isinstance(cd, dict) else {}
+        features = analysis_result.get("detected_features", []) or []
+        complexity_hints = [
+            f.get("description", f.get("feature_type", ""))
+            for f in features
+            if f.get("feature_type") in ("undercut", "side_action", "insert")
+        ]
+        return (
+            f"产品材料：{material}\n"
+            f"体积：{float(volume):.1f} mm³\n"
+            f"边界框尺寸（长×宽×高）：{float(dims[0]):.1f} × {float(dims[1]):.1f} × {float(dims[2]):.1f} mm\n"
+            f"预估锁模力：{mfg.get('estimated_clamping_force', '未知')}\n"
+            f"预估模具尺寸：{json.dumps(mfg.get('estimated_mold_size', {}), ensure_ascii=False)}\n"
+            f"预估成型周期：{mfg.get('estimated_cycle_time', '未知')}\n"
+            f"型腔数：{best.get('cavity_count', 1) if isinstance(best, dict) else 1}\n"
+            f"模具结构：{best.get('mold_structure_type', '未知') if isinstance(best, dict) else '未知'}\n"
+            f"复杂度线索：{', '.join(complexity_hints) if complexity_hints else '无明显倒扣/滑块'}\n"
+        )
+
    def _build_design_report_prompt(self, analysis_result, detailed_cavity_json) -> str:
        features = json.dumps(analysis_result.get("detected_features", []), ensure_ascii=False, indent=2)
        if len(features) > 4000:
@@ -7,9 +7,44 @@ from shared.models.database import User, Role, Permission, UserRole, RolePermiss
 from shared.services.auth_service import get_password_hash
 from shared.config.settings import settings
 from shared.utils.logger import get_logger
+from alembic.config import Config
+from alembic import command

 logger = get_logger(__name__)

+_ALEMBIC_INI = Path(__file__).resolve().parents[3] / "alembic.ini"
+
+
+def _alembic_stamp_head() -> None:
+    """将当前 DB 标记为已到最新版本（基线既有 DB，不执行 SQL）"""
+    cfg = Config(str(_ALEMBIC_INI))
+    command.stamp(cfg, "head")
+
+
+def _alembic_upgrade_head() -> None:
+    """执行 alembic 迁移到最新版本"""
+    cfg = Config(str(_ALEMBIC_INI))
+    command.upgrade(cfg, "head")
+
+
+async def _run_alembic_migrations() -> None:
+    """以 alembic 管理 schema：既有未纳入管理的 DB 自动 stamp 基线，再 upgrade head
+
+    - 全新 DB：upgrade head 执行初始迁移，创建全部表
+    - 既有已纳入管理：upgrade head 为 no-op
+    - 既有但无 alembic_version（历史 DB）：先 stamp head 基线，再 upgrade（no-op）
+    """
+    async with db_manager.engine.begin() as conn:
+        has_alembic = await conn.execute(text("SELECT to_regclass('public.alembic_version')")).scalar()
+        if not has_alembic:
+            table_count = await conn.execute(
+                text("SELECT count(*) FROM information_schema.tables WHERE table_schema='public' AND table_name <> 'alembic_version'")
+            ).scalar()
+            if table_count and table_count > 0:
+                logger.info("检测到既有 DB 未纳入 alembic 管理，自动 stamp head 作为基线")
+                await asyncio.to_thread(_alembic_stamp_head)
+    await asyncio.to_thread(_alembic_upgrade_head)
+
 DEFAULT_PERMISSIONS = [
    {"code": "view_dashboard", "name": "查看仪表盘", "module": "dashboard"},
    {"code": "view_moldinsight", "name": "使用模具分析", "module": "moldinsight"},
@@ -115,8 +150,7 @@ async def init_database(keep_connected: bool = True):
    """初始化数据库"""
    try:
        await db_manager.connect()
-        await db_manager.create_tables()
-        await ensure_schema_updates()
+        await _run_alembic_migrations()
        
        async with db_manager.session() as session:
            perm_map = await init_permissions(session)
@@ -153,97 +187,5 @@ async def init_database(keep_connected: bool = True):
            await db_manager.disconnect()


-async def ensure_schema_updates():
-    async with db_manager.engine.begin() as conn:
-        await conn.execute(text("ALTER TABLE products ADD COLUMN IF NOT EXISTS item_type VARCHAR(20) DEFAULT 'finished'"))
-        await conn.execute(text("UPDATE products SET item_type = 'finished' WHERE item_type IS NULL"))
-        await conn.execute(text("ALTER TABLE sales_orders ADD COLUMN IF NOT EXISTS production_status VARCHAR(20) DEFAULT 'not_started'"))
-        await conn.execute(text("ALTER TABLE sales_orders ADD COLUMN IF NOT EXISTS production_no VARCHAR(50)"))
-        await conn.execute(text("ALTER TABLE sales_orders ADD COLUMN IF NOT EXISTS planned_material_cost DOUBLE PRECISION DEFAULT 0"))
-        await conn.execute(text("ALTER TABLE sales_orders ADD COLUMN IF NOT EXISTS actual_material_cost DOUBLE PRECISION DEFAULT 0"))
-        await conn.execute(text("ALTER TABLE purchase_orders ADD COLUMN IF NOT EXISTS received_date TIMESTAMP WITHOUT TIME ZONE"))
-        await conn.execute(text("ALTER TABLE purchase_orders ADD COLUMN IF NOT EXISTS paid_date TIMESTAMP WITHOUT TIME ZONE"))
-        await conn.execute(text("""
-            CREATE TABLE IF NOT EXISTS product_materials (
-                id SERIAL PRIMARY KEY,
-                finished_product_id INTEGER NOT NULL REFERENCES products(id),
-                material_product_id INTEGER NOT NULL REFERENCES products(id),
-                quantity DOUBLE PRECISION NOT NULL,
-                loss_rate DOUBLE PRECISION DEFAULT 0,
-                created_at TIMESTAMP DEFAULT NOW(),
-                updated_at TIMESTAMP DEFAULT NOW()
-            )
-        """))
-        await conn.execute(text("""
-            CREATE UNIQUE INDEX IF NOT EXISTS uq_product_material_unique
-            ON product_materials (finished_product_id, material_product_id)
-        """))
-        await conn.execute(text("ALTER TABLE mold_cavity_data ADD COLUMN IF NOT EXISTS best_scheme_id VARCHAR(64)"))
-        await conn.execute(text("ALTER TABLE mold_cavity_data ADD COLUMN IF NOT EXISTS confidence_score DOUBLE PRECISION"))
-        await conn.execute(text("ALTER TABLE mold_cavity_data ADD COLUMN IF NOT EXISTS is_fallback BOOLEAN"))
-        await conn.execute(text("ALTER TABLE mold_cavity_data ADD COLUMN IF NOT EXISTS fallback_reason TEXT"))
-        await conn.execute(text("""
-            CREATE INDEX IF NOT EXISTS idx_mold_cavity_best_scheme_id
-            ON mold_cavity_data (best_scheme_id)
-        """))
-        await conn.execute(text("""
-            CREATE INDEX IF NOT EXISTS idx_mold_cavity_is_fallback
-            ON mold_cavity_data (is_fallback)
-        """))
-        await conn.execute(text("""
-            DO $$
-            BEGIN
-                IF NOT EXISTS (
-                    SELECT 1 FROM pg_constraint
-                    WHERE conname = 'uq_inventory_product_warehouse'
-                ) THEN
-                    ALTER TABLE inventory
-                    ADD CONSTRAINT uq_inventory_product_warehouse UNIQUE (product_id, warehouse_id);
-                END IF;
-            END $$;
-        """))
-        await conn.execute(text("""
-            DO $$
-            BEGIN
-                IF NOT EXISTS (
-                    SELECT 1 FROM pg_constraint
-                    WHERE conname = 'ck_inventory_qty_nonnegative'
-                ) THEN
-                    ALTER TABLE inventory
-                    ADD CONSTRAINT ck_inventory_qty_nonnegative
-                    CHECK (quantity >= 0 AND locked_quantity >= 0 AND locked_quantity <= quantity);
-                END IF;
-            END $$;
-        """))
-        await conn.execute(text("""
-            DO $$
-            BEGIN
-                IF NOT EXISTS (
-                    SELECT 1 FROM pg_constraint
-                    WHERE conname = 'ck_purchase_order_items_qty'
-                ) THEN
-                    ALTER TABLE purchase_order_items
-                    ADD CONSTRAINT ck_purchase_order_items_qty
-                    CHECK (quantity > 0 AND received_quantity >= 0 AND received_quantity <= quantity);
-                END IF;
-            END $$;
-        """))
-        await conn.execute(text("""
-            DO $$
-            BEGIN
-                IF NOT EXISTS (
-                    SELECT 1 FROM pg_constraint
-                    WHERE conname = 'ck_sales_order_items_qty'
-                ) THEN
-                    ALTER TABLE sales_order_items
-                    ADD CONSTRAINT ck_sales_order_items_qty
-                    CHECK (quantity > 0 AND delivered_quantity >= 0 AND delivered_quantity <= quantity);
-                END IF;
-            END $$;
-        """))
-        await conn.execute(text("ALTER TABLE sales_orders ADD COLUMN IF NOT EXISTS manufacturing_date TIMESTAMP WITHOUT TIME ZONE"))
-        await conn.execute(text("ALTER TABLE sales_orders ALTER COLUMN manufacturing_date TYPE TIMESTAMP WITHOUT TIME ZONE"))
-
-
 if __name__ == "__main__":
    asyncio.run(init_database(keep_connected=False))
@@ -1,55 +0,0 @@
-"""数据库迁移脚本 - 删除旧表并重新创建"""
-import asyncio
-from shared.database.database import db_manager
-from shared.models.database import Base
-from shared.utils.logger import get_logger
-
-logger = get_logger(__name__)
-
-
-async def migrate_database():
-    """迁移数据库：删除所有表并重新创建"""
-    try:
-        # 连接数据库
-        await db_manager.connect()
-
-        # 删除所有表
-        logger.info("正在删除所有数据库表...")
-        async with db_manager.engine.begin() as conn:
-            await conn.run_sync(Base.metadata.drop_all)
-
-        # 重新创建所有表
-        logger.info("正在创建所有数据库表...")
-        async with db_manager.engine.begin() as conn:
-            await conn.run_sync(Base.metadata.create_all)
-
-        logger.info("数据库迁移完成！")
-
-        return True
-
-    except Exception as e:
-        logger.error(f"数据库迁移失败: {e}")
-        return False
-    finally:
-        await db_manager.disconnect()
-
-
-if __name__ == "__main__":
-    import sys
-
-    # 检查命令行参数
-    if len(sys.argv) > 1 and sys.argv[1] == '--force':
-        confirm = 'yes'
-    else:
-        print("=== 数据库迁移 ===")
-        print("警告：这将删除所有数据库表和数据！")
-        confirm = input("确认继续？(yes/no): ")
-
-    if confirm.lower() == 'yes':
-        asyncio.run(migrate_database())
-    else:
-        print("已取消迁移")
-
-
-
-
@@ -1,5 +1,5 @@
 # models/database.py
-from sqlalchemy import Column, Integer, String, Text, DateTime, Date, JSON, LargeBinary, Boolean, Float, ForeignKey, UniqueConstraint, Numeric
+from sqlalchemy import Column, Integer, String, Text, DateTime, Date, JSON, LargeBinary, Boolean, Float, ForeignKey, UniqueConstraint, Numeric, CheckConstraint
 from sqlalchemy.ext.declarative import declarative_base
 from sqlalchemy.sql import func
 from sqlalchemy.orm import relationship
@@ -125,6 +125,8 @@ class STPFile(Base):
    
    id = Column(Integer, primary_key=True, index=True)
    user_id = Column(Integer, ForeignKey("users.id"), nullable=True, index=True)
+    # 关联进销存成品（P2-1：分析结果可一键创建为成品并回写）
+    product_id = Column(Integer, ForeignKey("products.id"), nullable=True, index=True)
    
    # 对象存储信息
    object_key = Column(String(500), nullable=False, index=True)  # MinIO对象键
@@ -160,6 +162,7 @@ class STPFile(Base):
    
    # 关联关系
    user = relationship("User", back_populates="stp_files")
+    product = relationship("Product")  # P2-1: 关联的进销存成品
    geometry_data = relationship("GeometryData", back_populates="stp_file", uselist=False)
    mesh_data = relationship("MeshData", back_populates="stp_file", uselist=False)
    mold_cavity_data = relationship("MoldCavityData", back_populates="stp_file", uselist=False)
@@ -662,6 +665,7 @@ class Inventory(Base):
    __tablename__ = "inventory"
    __table_args__ = (
        UniqueConstraint("product_id", "warehouse_id", name="uq_inventory_product_warehouse"),
+        CheckConstraint("quantity >= 0 AND locked_quantity >= 0 AND locked_quantity <= quantity", name="ck_inventory_qty_nonnegative"),
    )

    id = Column(Integer, primary_key=True, index=True)
@@ -740,6 +744,9 @@ class PurchaseOrder(Base):
 class PurchaseOrderItem(Base):
    """采购订单明细表"""
    __tablename__ = "purchase_order_items"
+    __table_args__ = (
+        CheckConstraint("quantity > 0 AND received_quantity >= 0 AND received_quantity <= quantity", name="ck_purchase_order_items_qty"),
+    )
    
    id = Column(Integer, primary_key=True, index=True)
    order_id = Column(Integer, ForeignKey("purchase_orders.id"), nullable=False)
@@ -860,6 +867,9 @@ class AnalysisMetrics(Base):
 class SalesOrderItem(Base):
    """销售订单明细表"""
    __tablename__ = "sales_order_items"
+    __table_args__ = (
+        CheckConstraint("quantity > 0 AND delivered_quantity >= 0 AND delivered_quantity <= quantity", name="ck_sales_order_items_qty"),
+    )
    
    id = Column(Integer, primary_key=True, index=True)
    order_id = Column(Integer, ForeignKey("sales_orders.id"), nullable=False)
Author	SHA1	Message	Date
cjw	cf6d708566	xxx	2026-07-27 15:54:25 +08:00
cjw	a8c0e1af3d	docs: 更新演进路线图（P1-2 注册表 + P1-4 Alembic 进度） Co-Authored-By: Claude <noreply@anthropic.com>	2026-07-20 11:05:03 +08:00
cjw	00ca81287e	feat(db): 引入 Alembic 取代裸 DDL 迁移 - alembic init + env.py 接 settings/models metadata（asyncpg->psycopg2 同步 URL） - 补 3 个 CheckConstraint 到 models（原只在裸 DDL） - 离线生成初始迁移（31 表+约束+95 索引，全 sa.* 通用类型） - init_db 用 _run_alembic_migrations（自动基线+upgrade head）替换 create_tables+ensure_schema_updates（删 92 行裸 DDL） - 删破坏性 migrate_db.py（drop_all） - 既有 DB 首次启动自动 stamp 基线，无需手动 Co-Authored-By: Claude <noreply@anthropic.com>	2026-07-20 11:04:23 +08:00
cjw	66ba6e00f5	refactor(moldinsight): 引入可插拔注册表（MoldGenerator + FeatureDetector） - 新增 MoldGeneratorRegistry：multi_scheme_planner 消除 if-else，按 mold_type 选生成器 - 新增 FeatureDetectorRegistry：geometry_analyzer._detect_features 消除 6 个检测器硬编码 - 新增模具类型/特征检测器只需 register 一行 - 移除 OCC ThreadPoolExecutor（注册表本身串行执行） Co-Authored-By: Claude <noreply@anthropic.com>	2026-07-20 11:03:16 +08:00