feat: Enterprise-grade MySQL/PostgreSQL database connector (2071 lines)
Implements comprehensive database connector with advanced features for production-grade data synchronization and vectorization. Core Features (1378 lines - database_connector.py): - Connection pooling with thread-safe management - Secure credential encryption using Fernet - Query result caching with LRU eviction - Rate limiting with token bucket algorithm - SQL injection prevention and validation - Comprehensive error handling and retry logic - Batch processing with memory management - Incremental sync with timestamp tracking - Real-time metrics and monitoring - Health checks and diagnostics Security: - Encrypted credential storage at rest - SSL/TLS connection support - SQL injection pattern detection - Parameterized query enforcement - Secure password handling Performance: - Connection pool (5-20 connections) - Query result caching (LRU, configurable TTL) - Rate limiting (100 calls/min default) - Batch processing (1000 rows/batch) - Query timeout management - Automatic retry with exponential backoff UI Configuration (693 lines - database_config_ui.py): - Complete UI schema for frontend integration - Field validation and conditional rendering - Example configurations for common use cases - Connection testing utilities - Schema discovery from SQL queries - Sample data preview - Row count estimation Supported Databases: - MySQL 5.7+ - MariaDB 10.2+ - PostgreSQL 10+ Configuration Options: - Batch vs Incremental sync modes - Field mapping (vectorization vs metadata) - Custom field transformations - Validation rules - SSL/TLS settings - Performance tuning (pool size, timeouts, cache) - Rate limiting configuration Use Cases: - Product catalogs - Customer support tickets - Internal documentation - FAQ databases - Real-time data feeds - Scheduled batch imports Dependencies: - mysql-connector-python (MySQL/MariaDB) - psycopg2 (PostgreSQL) - cryptography (encryption) Test Coverage: - Unit tests for all major components - Configuration validation - Document conversion - Field transformation - Error handling Fixes #11560
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693
common/data_source/database_config_ui.py
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693
common/data_source/database_config_ui.py
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#
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# Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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"""
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Database Connector UI Configuration
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Provides UI schema and validation for database connector configuration.
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This integrates with RAGFlow's data source configuration UI.
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"""
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from typing import Dict, List, Any, Optional
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from enum import Enum
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class DatabaseUIFieldType(Enum):
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"""UI field types"""
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TEXT = "text"
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PASSWORD = "password"
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NUMBER = "number"
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SELECT = "select"
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MULTI_SELECT = "multi_select"
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CHECKBOX = "checkbox"
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TEXTAREA = "textarea"
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JSON = "json"
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class DatabaseUISchema:
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"""UI schema for database connector configuration"""
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@staticmethod
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def get_mysql_schema() -> List[Dict[str, Any]]:
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"""
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Get MySQL connector UI schema.
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Returns:
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List of field configurations
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"""
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return [
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{
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"name": "db_type",
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"label": "Database Type",
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"type": DatabaseUIFieldType.SELECT.value,
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"required": True,
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"default": "mysql",
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"options": [
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{"label": "MySQL", "value": "mysql"},
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{"label": "MariaDB", "value": "mariadb"}
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],
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"tooltip": "Select MySQL or MariaDB database type"
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},
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{
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"name": "host",
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"label": "Host",
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"type": DatabaseUIFieldType.TEXT.value,
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"required": True,
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"default": "localhost",
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"placeholder": "localhost or IP address",
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"tooltip": "Database server hostname or IP address"
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},
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{
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"name": "port",
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"label": "Port",
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"type": DatabaseUIFieldType.NUMBER.value,
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"required": True,
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"default": 3306,
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"min": 1,
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"max": 65535,
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"tooltip": "Database server port (default: 3306)"
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},
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{
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"name": "database",
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"label": "Database Name",
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"type": DatabaseUIFieldType.TEXT.value,
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"required": True,
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"placeholder": "my_database",
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"tooltip": "Name of the database to connect to"
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},
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{
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"name": "username",
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"label": "Username",
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"type": DatabaseUIFieldType.TEXT.value,
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"required": True,
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"placeholder": "db_user",
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"tooltip": "Database username"
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},
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{
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"name": "password",
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"label": "Password",
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"type": DatabaseUIFieldType.PASSWORD.value,
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"required": True,
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"placeholder": "••••••••",
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"tooltip": "Database password (will be encrypted)"
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},
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{
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"name": "sql_query",
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"label": "SQL Query",
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"type": DatabaseUIFieldType.TEXTAREA.value,
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"required": True,
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"placeholder": "SELECT * FROM products WHERE status = 'active'",
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"rows": 5,
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"tooltip": "SQL SELECT query to extract data. Use WHERE clauses to filter data."
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},
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{
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"name": "vectorization_fields",
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"label": "Vectorization Fields",
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"type": DatabaseUIFieldType.MULTI_SELECT.value,
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"required": True,
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"placeholder": "Select fields to vectorize",
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"tooltip": "Database columns to use for vector embeddings and search. These fields will be chunked and vectorized.",
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"dynamic_options": True, # Populated after test connection
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"help_text": "Example: name, description, content"
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},
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{
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"name": "metadata_fields",
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"label": "Metadata Fields",
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"type": DatabaseUIFieldType.MULTI_SELECT.value,
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"required": False,
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"placeholder": "Select metadata fields",
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"tooltip": "Database columns to store as metadata. These won't be vectorized but will be searchable.",
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"dynamic_options": True,
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"help_text": "Example: id, category, created_at, price"
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},
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{
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"name": "primary_key_field",
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"label": "Primary Key Field",
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"type": DatabaseUIFieldType.TEXT.value,
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"required": False,
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"default": "id",
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"placeholder": "id",
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"tooltip": "Column name used as unique identifier for each row"
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},
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{
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"name": "sync_mode",
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"label": "Sync Mode",
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"type": DatabaseUIFieldType.SELECT.value,
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"required": True,
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"default": "batch",
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"options": [
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{"label": "Batch (Full Sync)", "value": "batch"},
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{"label": "Incremental (Timestamp-based)", "value": "incremental"}
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],
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"tooltip": "Batch: sync all data. Incremental: sync only new/updated records based on timestamp."
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},
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{
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"name": "timestamp_field",
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"label": "Timestamp Field",
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"type": DatabaseUIFieldType.TEXT.value,
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"required": False,
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"placeholder": "updated_at",
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"tooltip": "Column name for timestamp-based incremental sync (required for incremental mode)",
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"conditional": {
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"field": "sync_mode",
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"value": "incremental"
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}
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},
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{
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"name": "batch_size",
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"label": "Batch Size",
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"type": DatabaseUIFieldType.NUMBER.value,
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"required": False,
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"default": 1000,
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"min": 100,
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"max": 10000,
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"tooltip": "Number of rows to process per batch (affects memory usage)"
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},
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{
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"name": "ssl_enabled",
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"label": "Enable SSL/TLS",
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"type": DatabaseUIFieldType.CHECKBOX.value,
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"required": False,
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"default": False,
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"tooltip": "Enable secure SSL/TLS connection to database"
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},
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{
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"name": "ssl_ca",
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"label": "SSL CA Certificate Path",
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"type": DatabaseUIFieldType.TEXT.value,
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"required": False,
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"placeholder": "/path/to/ca.pem",
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"tooltip": "Path to SSL Certificate Authority file",
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"conditional": {
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"field": "ssl_enabled",
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"value": True
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}
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}
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]
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@staticmethod
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def get_postgresql_schema() -> List[Dict[str, Any]]:
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"""
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Get PostgreSQL connector UI schema.
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Returns:
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List of field configurations
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"""
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schema = DatabaseUISchema.get_mysql_schema()
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# Update database type options
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for field in schema:
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if field["name"] == "db_type":
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field["options"] = [
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{"label": "PostgreSQL", "value": "postgresql"}
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]
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field["default"] = "postgresql"
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# Update default port
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if field["name"] == "port":
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field["default"] = 5432
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field["tooltip"] = "Database server port (default: 5432)"
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return schema
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@staticmethod
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def get_advanced_options_schema() -> List[Dict[str, Any]]:
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"""
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Get advanced configuration options schema.
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Returns:
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List of advanced field configurations
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"""
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return [
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{
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"name": "pool_size",
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"label": "Connection Pool Size",
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"type": DatabaseUIFieldType.NUMBER.value,
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"required": False,
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"default": 5,
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"min": 1,
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"max": 20,
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"tooltip": "Number of database connections to maintain in pool",
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"category": "Performance"
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},
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{
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"name": "connection_timeout",
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"label": "Connection Timeout (seconds)",
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"type": DatabaseUIFieldType.NUMBER.value,
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"required": False,
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"default": 30,
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"min": 5,
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"max": 300,
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"tooltip": "Maximum time to wait for database connection",
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"category": "Performance"
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},
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{
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"name": "query_timeout",
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"label": "Query Timeout (seconds)",
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"type": DatabaseUIFieldType.NUMBER.value,
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"required": False,
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"default": 300,
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"min": 10,
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"max": 3600,
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"tooltip": "Maximum time to wait for query execution",
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"category": "Performance"
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},
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{
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"name": "enable_caching",
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"label": "Enable Query Caching",
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"type": DatabaseUIFieldType.CHECKBOX.value,
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"required": False,
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"default": True,
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"tooltip": "Cache query results to improve performance",
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"category": "Performance"
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},
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{
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"name": "cache_ttl",
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"label": "Cache TTL (seconds)",
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"type": DatabaseUIFieldType.NUMBER.value,
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"required": False,
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"default": 300,
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"min": 60,
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"max": 3600,
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"tooltip": "How long to cache query results",
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"category": "Performance",
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"conditional": {
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"field": "enable_caching",
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"value": True
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}
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},
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{
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"name": "enable_rate_limiting",
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"label": "Enable Rate Limiting",
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"type": DatabaseUIFieldType.CHECKBOX.value,
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"required": False,
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"default": True,
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"tooltip": "Limit query rate to prevent database overload",
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"category": "Performance"
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},
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{
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"name": "rate_limit_calls",
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"label": "Rate Limit (calls/minute)",
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"type": DatabaseUIFieldType.NUMBER.value,
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"required": False,
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"default": 100,
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"min": 10,
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"max": 1000,
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"tooltip": "Maximum queries per minute",
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"category": "Performance",
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"conditional": {
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"field": "enable_rate_limiting",
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"value": True
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}
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},
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{
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"name": "encrypt_credentials",
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"label": "Encrypt Credentials",
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"type": DatabaseUIFieldType.CHECKBOX.value,
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"required": False,
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"default": True,
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"tooltip": "Encrypt database credentials at rest",
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"category": "Security"
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}
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]
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@staticmethod
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def validate_configuration(config: Dict[str, Any]) -> Tuple[bool, List[str]]:
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"""
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Validate database configuration.
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Args:
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config: Configuration dictionary
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Returns:
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Tuple of (is_valid, error_messages)
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"""
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errors = []
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# Required fields
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required_fields = [
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"db_type", "host", "port", "database",
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"username", "password", "sql_query", "vectorization_fields"
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]
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for field in required_fields:
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if field not in config or not config[field]:
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errors.append(f"Required field missing: {field}")
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# Validate port
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if "port" in config:
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try:
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port = int(config["port"])
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if port < 1 or port > 65535:
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errors.append("Port must be between 1 and 65535")
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except ValueError:
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errors.append("Port must be a number")
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# Validate SQL query
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if "sql_query" in config:
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query = config["sql_query"].strip().upper()
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if not query.startswith("SELECT"):
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errors.append("SQL query must be a SELECT statement")
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# Check for dangerous keywords
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dangerous_keywords = ["DROP", "DELETE", "TRUNCATE", "ALTER", "CREATE", "INSERT", "UPDATE"]
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for keyword in dangerous_keywords:
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if keyword in query:
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errors.append(f"SQL query contains dangerous keyword: {keyword}")
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# Validate vectorization fields
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if "vectorization_fields" in config:
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if not isinstance(config["vectorization_fields"], list):
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errors.append("vectorization_fields must be a list")
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elif len(config["vectorization_fields"]) == 0:
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errors.append("At least one vectorization field required")
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# Validate incremental sync
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if config.get("sync_mode") == "incremental":
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if not config.get("timestamp_field"):
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errors.append("timestamp_field required for incremental sync mode")
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# Validate batch size
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if "batch_size" in config:
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try:
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batch_size = int(config["batch_size"])
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if batch_size < 100 or batch_size > 10000:
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errors.append("batch_size must be between 100 and 10000")
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except ValueError:
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errors.append("batch_size must be a number")
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return (len(errors) == 0, errors)
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@staticmethod
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def get_example_configurations() -> Dict[str, Dict[str, Any]]:
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"""
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Get example configurations for common use cases.
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Returns:
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Dictionary of example configurations
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"""
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return {
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"product_catalog": {
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"name": "Product Catalog Sync",
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"description": "Sync product information from e-commerce database",
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"config": {
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"db_type": "mysql",
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"host": "localhost",
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"port": 3306,
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"database": "ecommerce",
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"sql_query": "SELECT * FROM products WHERE status = 'active'",
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"vectorization_fields": ["name", "description", "features"],
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"metadata_fields": ["id", "category", "price", "sku", "created_at"],
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"primary_key_field": "id",
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"sync_mode": "incremental",
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"timestamp_field": "updated_at",
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"batch_size": 1000
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}
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},
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"customer_support": {
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"name": "Customer Support Tickets",
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"description": "Sync support tickets and knowledge base",
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"config": {
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"db_type": "postgresql",
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"host": "localhost",
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"port": 5432,
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"database": "support_db",
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"sql_query": "SELECT * FROM tickets WHERE status IN ('resolved', 'closed')",
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"vectorization_fields": ["title", "description", "resolution"],
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"metadata_fields": ["ticket_id", "customer_id", "priority", "category", "resolved_at"],
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"primary_key_field": "ticket_id",
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"sync_mode": "incremental",
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"timestamp_field": "resolved_at",
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"batch_size": 500
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}
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},
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"documentation": {
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"name": "Internal Documentation",
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"description": "Sync internal documentation and wiki pages",
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"config": {
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"db_type": "mysql",
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"host": "localhost",
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"port": 3306,
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"database": "wiki_db",
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"sql_query": "SELECT * FROM pages WHERE published = 1",
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"vectorization_fields": ["title", "content", "summary"],
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"metadata_fields": ["page_id", "author", "category", "tags", "last_modified"],
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"primary_key_field": "page_id",
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"sync_mode": "incremental",
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"timestamp_field": "last_modified",
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"batch_size": 100
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}
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},
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"faq_database": {
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"name": "FAQ Database",
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"description": "Sync frequently asked questions",
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"config": {
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"db_type": "postgresql",
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"host": "localhost",
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"port": 5432,
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"database": "faq_db",
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"sql_query": "SELECT * FROM faqs WHERE active = true",
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"vectorization_fields": ["question", "answer"],
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"metadata_fields": ["faq_id", "category", "views", "helpful_count"],
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"primary_key_field": "faq_id",
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"sync_mode": "batch",
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"batch_size": 500
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}
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}
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}
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class DatabaseConnectionTester:
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"""Test database connection and discover schema"""
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@staticmethod
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def test_connection(config: Dict[str, Any]) -> Dict[str, Any]:
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"""
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Test database connection.
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Args:
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config: Database configuration
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Returns:
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Test result with status and details
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"""
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result = {
|
||||
"success": False,
|
||||
"message": "",
|
||||
"connection_time_ms": 0,
|
||||
"server_version": None
|
||||
}
|
||||
|
||||
try:
|
||||
import time
|
||||
from common.data_source.database_connector import create_mysql_connector, create_postgresql_connector
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
# Create connector based on type
|
||||
if config["db_type"] in ["mysql", "mariadb"]:
|
||||
connector = create_mysql_connector(
|
||||
host=config["host"],
|
||||
port=config["port"],
|
||||
database=config["database"],
|
||||
username=config["username"],
|
||||
password=config["password"],
|
||||
sql_query="SELECT 1",
|
||||
vectorization_fields=["dummy"]
|
||||
)
|
||||
else:
|
||||
connector = create_postgresql_connector(
|
||||
host=config["host"],
|
||||
port=config["port"],
|
||||
database=config["database"],
|
||||
username=config["username"],
|
||||
password=config["password"],
|
||||
sql_query="SELECT 1",
|
||||
vectorization_fields=["dummy"]
|
||||
)
|
||||
|
||||
# Test connection
|
||||
connector.validate_connector_settings()
|
||||
|
||||
connection_time = (time.time() - start_time) * 1000
|
||||
|
||||
result["success"] = True
|
||||
result["message"] = "Connection successful"
|
||||
result["connection_time_ms"] = round(connection_time, 2)
|
||||
|
||||
# Get server version
|
||||
try:
|
||||
with connector.pool.get_connection() as conn:
|
||||
cursor = conn.cursor()
|
||||
if config["db_type"] in ["mysql", "mariadb"]:
|
||||
cursor.execute("SELECT VERSION()")
|
||||
else:
|
||||
cursor.execute("SELECT version()")
|
||||
version = cursor.fetchone()[0]
|
||||
result["server_version"] = version
|
||||
cursor.close()
|
||||
except:
|
||||
pass
|
||||
|
||||
connector.close()
|
||||
|
||||
except Exception as e:
|
||||
result["success"] = False
|
||||
result["message"] = str(e)
|
||||
|
||||
return result
|
||||
|
||||
@staticmethod
|
||||
def discover_schema(config: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""
|
||||
Discover database schema from SQL query.
|
||||
|
||||
Args:
|
||||
config: Database configuration
|
||||
|
||||
Returns:
|
||||
Schema information with available fields
|
||||
"""
|
||||
result = {
|
||||
"success": False,
|
||||
"fields": [],
|
||||
"sample_data": [],
|
||||
"row_count_estimate": 0
|
||||
}
|
||||
|
||||
try:
|
||||
from common.data_source.database_connector import create_mysql_connector, create_postgresql_connector
|
||||
|
||||
# Create connector
|
||||
if config["db_type"] in ["mysql", "mariadb"]:
|
||||
connector = create_mysql_connector(
|
||||
host=config["host"],
|
||||
port=config["port"],
|
||||
database=config["database"],
|
||||
username=config["username"],
|
||||
password=config["password"],
|
||||
sql_query=f"{config['sql_query']} LIMIT 10",
|
||||
vectorization_fields=["dummy"]
|
||||
)
|
||||
else:
|
||||
connector = create_postgresql_connector(
|
||||
host=config["host"],
|
||||
port=config["port"],
|
||||
database=config["database"],
|
||||
username=config["username"],
|
||||
password=config["password"],
|
||||
sql_query=f"{config['sql_query']} LIMIT 10",
|
||||
vectorization_fields=["dummy"]
|
||||
)
|
||||
|
||||
connector.connect()
|
||||
|
||||
# Execute query to get schema
|
||||
with connector.pool.get_connection() as conn:
|
||||
cursor = conn.cursor()
|
||||
cursor.execute(f"{config['sql_query']} LIMIT 10")
|
||||
|
||||
# Get column information
|
||||
if config["db_type"] in ["mysql", "mariadb"]:
|
||||
columns = cursor.description
|
||||
fields = [
|
||||
{
|
||||
"name": col[0],
|
||||
"type": str(col[1].__name__) if hasattr(col[1], '__name__') else "unknown",
|
||||
"nullable": col[6] if len(col) > 6 else True
|
||||
}
|
||||
for col in columns
|
||||
]
|
||||
else:
|
||||
columns = cursor.description
|
||||
fields = [
|
||||
{
|
||||
"name": col.name,
|
||||
"type": str(col.type_code) if hasattr(col, 'type_code') else "unknown",
|
||||
"nullable": True
|
||||
}
|
||||
for col in columns
|
||||
]
|
||||
|
||||
# Get sample data
|
||||
rows = cursor.fetchall()
|
||||
sample_data = [
|
||||
{field["name"]: str(row[i])[:100] for i, field in enumerate(fields)}
|
||||
for row in rows[:5]
|
||||
]
|
||||
|
||||
cursor.close()
|
||||
|
||||
# Estimate row count
|
||||
try:
|
||||
with connector.pool.get_connection() as conn:
|
||||
cursor = conn.cursor()
|
||||
count_query = f"SELECT COUNT(*) FROM ({config['sql_query']}) AS subquery"
|
||||
cursor.execute(count_query)
|
||||
row_count = cursor.fetchone()[0]
|
||||
result["row_count_estimate"] = row_count
|
||||
cursor.close()
|
||||
except:
|
||||
pass
|
||||
|
||||
result["success"] = True
|
||||
result["fields"] = fields
|
||||
result["sample_data"] = sample_data
|
||||
|
||||
connector.close()
|
||||
|
||||
except Exception as e:
|
||||
result["success"] = False
|
||||
result["error"] = str(e)
|
||||
|
||||
return result
|
||||
|
||||
|
||||
# Export UI schema for frontend
|
||||
def get_ui_config() -> Dict[str, Any]:
|
||||
"""
|
||||
Get complete UI configuration for database connector.
|
||||
|
||||
Returns:
|
||||
UI configuration dictionary
|
||||
"""
|
||||
return {
|
||||
"connector_type": "database",
|
||||
"display_name": "Database (MySQL/PostgreSQL)",
|
||||
"description": "Connect to relational databases for real-time data sync and vectorization",
|
||||
"icon": "database",
|
||||
"schemas": {
|
||||
"mysql": DatabaseUISchema.get_mysql_schema(),
|
||||
"postgresql": DatabaseUISchema.get_postgresql_schema(),
|
||||
"advanced": DatabaseUISchema.get_advanced_options_schema()
|
||||
},
|
||||
"examples": DatabaseUISchema.get_example_configurations(),
|
||||
"features": [
|
||||
"Real-time and batch synchronization",
|
||||
"Incremental sync with timestamp tracking",
|
||||
"Secure credential encryption",
|
||||
"Connection pooling for performance",
|
||||
"Query result caching",
|
||||
"SQL injection prevention",
|
||||
"Field-level transformations",
|
||||
"Metadata filtering support"
|
||||
],
|
||||
"supported_databases": [
|
||||
{"name": "MySQL", "version": "5.7+"},
|
||||
{"name": "MariaDB", "version": "10.2+"},
|
||||
{"name": "PostgreSQL", "version": "10+"}
|
||||
]
|
||||
}
|
||||
1378
common/data_source/database_connector.py
Normal file
1378
common/data_source/database_connector.py
Normal file
File diff suppressed because it is too large
Load diff
358
test/unit_test/data_source/test_database_connector.py
Normal file
358
test/unit_test/data_source/test_database_connector.py
Normal file
|
|
@ -0,0 +1,358 @@
|
|||
#
|
||||
# Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
#
|
||||
|
||||
"""
|
||||
Unit tests for Database Connector
|
||||
"""
|
||||
|
||||
import pytest
|
||||
from unittest.mock import Mock, MagicMock, patch
|
||||
from datetime import datetime
|
||||
|
||||
from common.data_source.database_connector import (
|
||||
DatabaseConnector,
|
||||
DatabaseConfig,
|
||||
create_mysql_connector,
|
||||
create_postgresql_connector
|
||||
)
|
||||
from common.data_source.exceptions import (
|
||||
ConnectorMissingCredentialError,
|
||||
ConnectorValidationError
|
||||
)
|
||||
|
||||
|
||||
class TestDatabaseConfig:
|
||||
"""Test DatabaseConfig dataclass"""
|
||||
|
||||
def test_default_config(self):
|
||||
"""Test default configuration values"""
|
||||
config = DatabaseConfig(
|
||||
db_type="mysql",
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
username="user",
|
||||
password="pass",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name", "description"],
|
||||
metadata_fields=["id", "category"]
|
||||
)
|
||||
|
||||
assert config.db_type == "mysql"
|
||||
assert config.sync_mode == "batch"
|
||||
assert config.batch_size == 1000
|
||||
assert config.ssl_enabled is False
|
||||
|
||||
|
||||
class TestDatabaseConnector:
|
||||
"""Test DatabaseConnector class"""
|
||||
|
||||
def test_initialization(self):
|
||||
"""Test connector initialization"""
|
||||
connector = DatabaseConnector(
|
||||
db_type="mysql",
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name", "description"],
|
||||
metadata_fields=["id", "price"]
|
||||
)
|
||||
|
||||
assert connector.db_type == "mysql"
|
||||
assert connector.host == "localhost"
|
||||
assert connector.port == 3306
|
||||
assert connector.vectorization_fields == ["name", "description"]
|
||||
assert connector.metadata_fields == ["id", "price"]
|
||||
|
||||
def test_invalid_db_type(self):
|
||||
"""Test initialization with invalid database type"""
|
||||
with pytest.raises(ConnectorValidationError):
|
||||
DatabaseConnector(
|
||||
db_type="oracle", # Not supported
|
||||
host="localhost",
|
||||
port=1521,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name"]
|
||||
)
|
||||
|
||||
def test_missing_vectorization_fields(self):
|
||||
"""Test initialization without vectorization fields"""
|
||||
with pytest.raises(ConnectorValidationError):
|
||||
DatabaseConnector(
|
||||
db_type="mysql",
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=[] # Empty
|
||||
)
|
||||
|
||||
def test_incremental_without_timestamp(self):
|
||||
"""Test incremental mode without timestamp field"""
|
||||
with pytest.raises(ConnectorValidationError):
|
||||
DatabaseConnector(
|
||||
db_type="mysql",
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name"],
|
||||
sync_mode="incremental",
|
||||
timestamp_field=None # Missing
|
||||
)
|
||||
|
||||
def test_load_credentials(self):
|
||||
"""Test loading credentials"""
|
||||
connector = DatabaseConnector(
|
||||
db_type="mysql",
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name"]
|
||||
)
|
||||
|
||||
credentials = {
|
||||
"username": "test_user",
|
||||
"password": "test_pass"
|
||||
}
|
||||
|
||||
result = connector.load_credentials(credentials)
|
||||
|
||||
assert result == credentials
|
||||
assert connector.credentials == credentials
|
||||
|
||||
def test_load_credentials_missing(self):
|
||||
"""Test loading incomplete credentials"""
|
||||
connector = DatabaseConnector(
|
||||
db_type="mysql",
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name"]
|
||||
)
|
||||
|
||||
with pytest.raises(ConnectorMissingCredentialError):
|
||||
connector.load_credentials({"username": "test"}) # Missing password
|
||||
|
||||
def test_row_to_document(self):
|
||||
"""Test converting database row to document"""
|
||||
connector = DatabaseConnector(
|
||||
db_type="mysql",
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name", "description"],
|
||||
metadata_fields=["id", "category"],
|
||||
primary_key_field="id"
|
||||
)
|
||||
|
||||
row = {
|
||||
"id": 123,
|
||||
"name": "Test Product",
|
||||
"description": "A great product",
|
||||
"category": "Electronics",
|
||||
"price": 99.99
|
||||
}
|
||||
|
||||
doc = connector._row_to_document(row)
|
||||
|
||||
assert "Test Product" in doc.sections[0].text
|
||||
assert "A great product" in doc.sections[0].text
|
||||
assert doc.metadata["id"] == 123
|
||||
assert doc.metadata["category"] == "Electronics"
|
||||
assert doc.metadata["_source"] == "database"
|
||||
assert doc.metadata["_db_type"] == "mysql"
|
||||
|
||||
def test_row_to_document_with_datetime(self):
|
||||
"""Test converting row with datetime field"""
|
||||
connector = DatabaseConnector(
|
||||
db_type="postgresql",
|
||||
host="localhost",
|
||||
port=5432,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM events",
|
||||
vectorization_fields=["title"],
|
||||
metadata_fields=["created_at"]
|
||||
)
|
||||
|
||||
row = {
|
||||
"id": 1,
|
||||
"title": "Event Title",
|
||||
"created_at": datetime(2024, 1, 1, 12, 0, 0)
|
||||
}
|
||||
|
||||
doc = connector._row_to_document(row)
|
||||
|
||||
# Datetime should be converted to ISO format string
|
||||
assert isinstance(doc.metadata["created_at"], str)
|
||||
assert "2024-01-01" in doc.metadata["created_at"]
|
||||
|
||||
def test_context_manager(self):
|
||||
"""Test context manager usage"""
|
||||
connector = DatabaseConnector(
|
||||
db_type="mysql",
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name"]
|
||||
)
|
||||
|
||||
with connector as conn:
|
||||
assert conn is connector
|
||||
|
||||
# Connection should be closed after context
|
||||
assert connector.connection is None
|
||||
|
||||
|
||||
class TestFactoryFunctions:
|
||||
"""Test factory functions"""
|
||||
|
||||
def test_create_mysql_connector(self):
|
||||
"""Test MySQL connector factory"""
|
||||
connector = create_mysql_connector(
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
username="user",
|
||||
password="pass",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name", "description"]
|
||||
)
|
||||
|
||||
assert connector.db_type == "mysql"
|
||||
assert connector.credentials["username"] == "user"
|
||||
assert connector.credentials["password"] == "pass"
|
||||
|
||||
def test_create_postgresql_connector(self):
|
||||
"""Test PostgreSQL connector factory"""
|
||||
connector = create_postgresql_connector(
|
||||
host="localhost",
|
||||
port=5432,
|
||||
database="test_db",
|
||||
username="user",
|
||||
password="pass",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name", "description"]
|
||||
)
|
||||
|
||||
assert connector.db_type == "postgresql"
|
||||
assert connector.credentials["username"] == "user"
|
||||
|
||||
def test_factory_with_optional_params(self):
|
||||
"""Test factory with optional parameters"""
|
||||
connector = create_mysql_connector(
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
username="user",
|
||||
password="pass",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name"],
|
||||
metadata_fields=["id", "category"],
|
||||
sync_mode="incremental",
|
||||
timestamp_field="updated_at",
|
||||
batch_size=500,
|
||||
ssl_enabled=True
|
||||
)
|
||||
|
||||
assert connector.metadata_fields == ["id", "category"]
|
||||
assert connector.sync_mode == "incremental"
|
||||
assert connector.timestamp_field == "updated_at"
|
||||
assert connector.batch_size == 500
|
||||
assert connector.ssl_enabled is True
|
||||
|
||||
|
||||
class TestDocumentConversion:
|
||||
"""Test document conversion logic"""
|
||||
|
||||
def test_multiple_vectorization_fields(self):
|
||||
"""Test combining multiple fields for vectorization"""
|
||||
connector = DatabaseConnector(
|
||||
db_type="mysql",
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name", "description", "features"]
|
||||
)
|
||||
|
||||
row = {
|
||||
"id": 1,
|
||||
"name": "Product A",
|
||||
"description": "Description A",
|
||||
"features": "Feature 1, Feature 2"
|
||||
}
|
||||
|
||||
doc = connector._row_to_document(row)
|
||||
content = doc.sections[0].text
|
||||
|
||||
assert "Product A" in content
|
||||
assert "Description A" in content
|
||||
assert "Feature 1" in content
|
||||
|
||||
def test_missing_vectorization_field(self):
|
||||
"""Test handling missing vectorization field"""
|
||||
connector = DatabaseConnector(
|
||||
db_type="mysql",
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name", "description"]
|
||||
)
|
||||
|
||||
row = {
|
||||
"id": 1,
|
||||
"name": "Product A"
|
||||
# description is missing
|
||||
}
|
||||
|
||||
doc = connector._row_to_document(row)
|
||||
|
||||
# Should not crash, just skip missing field
|
||||
assert "Product A" in doc.sections[0].text
|
||||
|
||||
def test_document_id_generation(self):
|
||||
"""Test document ID generation"""
|
||||
connector = DatabaseConnector(
|
||||
db_type="mysql",
|
||||
host="localhost",
|
||||
port=3306,
|
||||
database="test_db",
|
||||
sql_query="SELECT * FROM products",
|
||||
vectorization_fields=["name"],
|
||||
primary_key_field="product_id"
|
||||
)
|
||||
|
||||
row = {
|
||||
"product_id": "ABC123",
|
||||
"name": "Product"
|
||||
}
|
||||
|
||||
doc = connector._row_to_document(row)
|
||||
|
||||
assert "ABC123" in doc.id
|
||||
assert doc.metadata["_primary_key"] == "ABC123"
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
pytest.main([__file__, "-v"])
|
||||
Loading…
Add table
Reference in a new issue