diff --git a/.env.example b/.env.example index d6b1e50..a477561 100644 --- a/.env.example +++ b/.env.example @@ -3,18 +3,18 @@ ############################################### # LLM_PROVIDER=openai -# OPEN_AI_KEY= -# OPEN_MODEL_PREF=gpt-4o +# OPEN_AI_KEY=sk-proj----- +# OPEN_AI_LLM_MODEL=gpt-4.1 # LLM_PROVIDER=gemini # GEMINI_API_KEY= # GEMINI_LLM_MODEL=gemini-2.0-flash-lite -# LLM_PROVIDER=azure -# AZURE_OPENAI_LLM_ENDPOINT= -# AZURE_OPENAI_LLM_KEY= -# AZURE_OPENAI_LLM_MODEL= -# AZURE_OPENAI_LLM_API_VERSION= +LLM_PROVIDER=azure +AZURE_OPENAI_LLM_ENDPOINT=https://-------.openai.azure.com/ +AZURE_OPENAI_LLM_KEY=- +AZURE_OPENAI_LLM_MODEL=gpt4o +AZURE_OPENAI_LLM_API_VERSION=2024-07-01-preview # LLM_PROVIDER=ollama # OLLAMA_LLM_BASE_URL= @@ -36,31 +36,99 @@ ########### Embedding API SElECTION ########### ############################################### # Only used if you are using an LLM that does not natively support embedding (openai or Azure) -# EMBEDDING_ENGINE='openai' -# OPEN_AI_KEY=sk-xxxx -# EMBEDDING_MODEL_PREF='text-embedding-ada-002' +# EMBEDDING_PROVIDER='openai' +# OPEN_AI_EMBEDDING_MODEL='text-embedding-ada-002' -# EMBEDDING_ENGINE='azure' -# AZURE_OPENAI_ENDPOINT= -# AZURE_OPENAI_KEY= -# EMBEDDING_MODEL_PREF='my-embedder-model' # This is the "deployment" on Azure you want to use for embeddings. Not the base model. Valid base model is text-embedding-ada-002 +# EMBEDDING_PROVIDER=azure +# AZURE_OPENAI_EMBEDDING_ENDPOINT=https://-------.openai.azure.com/openai/deployments +# AZURE_OPENAI_EMBEDDING_KEY=- +# AZURE_OPENAI_EMBEDDING_MODEL='textembeddingada002' # This is the "deployment" on Azure you want to use for embeddings. Not the base model. Valid base model is text-embedding-ada-002 +# AZURE_OPENAI_EMBEDDING_API_VERSION=2023-09-15-preview -# EMBEDDING_ENGINE='ollama' +# EMBEDDING_PROVIDER='ollama' # EMBEDDING_BASE_PATH='http://host.docker.internal:11434' -# EMBEDDING_MODEL_PREF='nomic-embed-text:latest' +# EMBEDDING_MODEL='nomic-embed-text:latest' # EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192 -# EMBEDDING_ENGINE='bedrock' -# AWS_BEDROCK_EMBEDDING_ACCESS_KEY_ID= -# AWS_BEDROCK_EMBEDDING_ACCESS_KEY= -# AWS_BEDROCK_EMBEDDING_REGION=us-west-2 -# AWS_BEDROCK_EMBEDDING_MODEL_PREF=amazon.embedding-embedding-ada-002:0 +EMBEDDING_PROVIDER='bedrock' +AWS_BEDROCK_EMBEDDING_ACCESS_KEY_ID=-- +AWS_BEDROCK_EMBEDDING_SECRET_ACCESS_KEY=-/-+-+- +AWS_BEDROCK_EMBEDDING_REGION=us-west-2 +AWS_BEDROCK_EMBEDDING_MODEL=amazon.titan-embed-text-v2:0 -# EMBEDDING_ENGINE='gemini' +# EMBEDDING_PROVIDER='gemini' # GEMINI_EMBEDDING_API_KEY= -# EMBEDDING_MODEL_PREF='text-embedding-004' +# EMBEDDING_MODEL='text-embedding-004' -# EMBEDDING_ENGINE='huggingface' +# EMBEDDING_PROVIDER='huggingface' # HUGGING_FACE_EMBEDDING_REPO_ID= # HUGGING_FACE_EMBEDDING_MODEL= # HUGGING_FACE_EMBEDDING_API_TOKEN= + +DATAHUB_SERVER = 'http://-.-.-.-:-' + + +############################################### +######## Database Connector SELECTION ######### +############################################### + +# clickhouse +# DB_TYPE=clickhouse +# CLICKHOUSE_HOST=_._._._ +# CLICKHOUSE_PORT=9000 +# CLICKHOUSE_USER=_ +# CLICKHOUSE_PASSWORD=_ +# CLICKHOUSE_DATABASE=_ + +# databricks +# DB_TYPE=databricks +# DATABRICKS_HOST=_ +# DATABRICKS_HTTP_PATH=_ +# DATABRICKS_ACCESS_TOKEN=_ + +# duckdb +# DB_TYPE=duckdb +# DUCKDB_PATH=./data/duckdb.db + +# mariadb +# DB_TYPE=mariadb +# MARIADB_HOST=_ +# MARIADB_PORT=3306 +# MARIADB_USER=_ +# MARIADB_PASSWORD=_ +# MARIADB_DATABASE=_ + +# mysql +# DB_TYPE=mysql +# MYSQL_HOST=_ +# MYSQL_PORT=3306 +# MYSQL_USER=_ +# MYSQL_PASSWORD=_ +# MYSQL_DATABASE=_ + +# oracle +# DB_TYPE=oracle +# ORACLE_HOST=_ +# ORACLE_PORT=1521 +# ORACLE_USER=_ +# ORACLE_PASSWORD=_ +# ORACLE_DATABASE=_ +# ORACLE_SERVICE_NAME=_ + +# postgres +# DB_TYPE=postgres +# POSTGRES_HOST=_ +# POSTGRES_PORT=5432 +# POSTGRES_USER=_ +# POSTGRES_PASSWORD=_ +# POSTGRES_DATABASE=_ + +# snowflake +# DB_TYPE=snowflake +# SNOWFLAKE_USER=_ +# SNOWFLAKE_PASSWORD=_ +# SNOWFLAKE_ACCOUNT=_ + +# sqlite +# DB_TYPE=sqlite +# SQLITE_PATH=./data/sqlite.db \ No newline at end of file diff --git a/db_utils/__init__.py b/db_utils/__init__.py new file mode 100644 index 0000000..6405698 --- /dev/null +++ b/db_utils/__init__.py @@ -0,0 +1,131 @@ +from typing import Optional +import os +from .config import DBConfig +from .logger import logger + +from dotenv import load_dotenv + +from .base_connector import BaseConnector + +from .clickhouse_connector import ClickHouseConnector +from .postgres_connector import PostgresConnector +from .mysql_connector import MySQLConnector +from .mariadb_connector import MariaDBConnector +from .oracle_connector import OracleConnector +from .duckdb_connector import DuckDBConnector +from .databricks_connector import DatabricksConnector +from .snowflake_connector import SnowflakeConnector + +env_path = os.path.join(os.getcwd(), ".env") + +if os.path.exists(env_path): + load_dotenv(env_path, override=True) + print(f"✅ 환경변수 파일(.env)이 {os.getcwd()}에 로드되었습니다!") +else: + print(f"⚠️ 환경변수 파일(.env)이 {os.getcwd()}에 없습니다!") + + +def get_db_connector(db_type: Optional[str] = None, config: Optional[DBConfig] = None): + """ + Return the appropriate DB connector instance. + - If db_type is not provided, loads from environment variable DB_TYPE + - If config is not provided, loads from environment using db_type + + Parameters: + db_type (Optional[str]): Database type (e.g., 'postgresql', 'mysql') + config (Optional[DBConfig]): Connection config + + Returns: + BaseConnector: Initialized DB connector instance + + Raises: + ValueError: If type/config is missing or invalid + """ + if db_type is None: + db_type = os.getenv("DB_TYPE") + if not db_type: + raise ValueError( + "DB type must be provided or set in environment as DB_TYPE." + ) + + db_type = db_type.lower() + + if config is None: + config = load_config_from_env(db_type.upper()) + + connector_map = { + "clickhouse": ClickHouseConnector, + "postgresql": PostgresConnector, + "mysql": MySQLConnector, + "mariadb": MariaDBConnector, + "oracle": OracleConnector, + "duckdb": DuckDBConnector, + "databricks": DatabricksConnector, + "snowflake": SnowflakeConnector, + } + + if db_type not in connector_map: + logger.error(f"Unsupported DB type: {db_type}") + raise ValueError(f"Unsupported DB type: {db_type}") + + required_fields = { + "oracle": ["extra.service_name"], + "databricks": ["extra.http_path", "extra.access_token"], + "snowflake": ["extra.account"], + } + + missing = [] + for path in required_fields.get(db_type, []): + cur = config + for key in path.split("."): + cur = cur.get(key) if isinstance(cur, dict) else None + if cur is None: + missing.append(path) + break + + if missing: + logger.error(f"Missing required fields for {db_type}: {', '.join(missing)}") + raise ValueError(f"Missing required fields for {db_type}: {', '.join(missing)}") + + return connector_map[db_type](config) + + +def load_config_from_env(prefix: str) -> DBConfig: + """ + Load DBConfig from environment variables with a given prefix. + Standard keys are extracted, all other prefixed keys go to 'extra'. + + Example: + If prefix = 'SNOWFLAKE', loads: + - SNOWFLAKE_HOST + - SNOWFLAKE_USER + - SNOWFLAKE_PASSWORD + - SNOWFLAKE_PORT + - SNOWFLAKE_DATABASE + Other keys like SNOWFLAKE_ACCOUNT, SNOWFLAKE_WAREHOUSE -> extra + """ + base_keys = {"HOST", "PORT", "USER", "PASSWORD", "DATABASE"} + + # Extract standard values + config = { + "host": os.getenv(f"{prefix}_HOST"), + "port": ( + int(os.getenv(f"{prefix}_PORT")) if os.getenv(f"{prefix}_PORT") else None + ), + "user": os.getenv(f"{prefix}_USER"), + "password": os.getenv(f"{prefix}_PASSWORD"), + "database": os.getenv(f"{prefix}_DATABASE"), + } + + # Auto-detect extra keys + extra = {} + for key, value in os.environ.items(): + if key.startswith(f"{prefix}_"): + suffix = key[len(f"{prefix}_") :] + if suffix.upper() not in base_keys: + extra[suffix.lower()] = value + + if extra: + config["extra"] = extra + + return DBConfig(**config) diff --git a/db_utils/base_connector.py b/db_utils/base_connector.py new file mode 100644 index 0000000..47c17d1 --- /dev/null +++ b/db_utils/base_connector.py @@ -0,0 +1,28 @@ +from abc import ABC, abstractmethod +import pandas as pd + + +class BaseConnector(ABC): + """ + Abstract base class for database connectors. + """ + + @abstractmethod + def connect(self): + """ + Initialize the database connection. + """ + pass + + @abstractmethod + def run_sql(self, sql: str) -> pd.DataFrame: + """ + Returns the result of the SQL query as a pandas DataFrame. + + Parameters: + sql (str): SQL query string to be executed. + + Returns: + pd.DataFrame: Result of the SQL query as a pandas DataFrame. + """ + pass diff --git a/db_utils/clickhouse_connector.py b/db_utils/clickhouse_connector.py new file mode 100644 index 0000000..50b11cc --- /dev/null +++ b/db_utils/clickhouse_connector.py @@ -0,0 +1,72 @@ +from .base_connector import BaseConnector +from clickhouse_driver import Client +import pandas as pd +from db_utils import DBConfig, logger + + +class ClickHouseConnector(BaseConnector): + """ + Connect to ClickHouse and execute SQL queries. + """ + + client = None + + def __init__(self, config: DBConfig): + """ + Initialize the ClickHouseConnector with connection parameters. + + Parameters: + config (DBConfig): Configuration object containing connection parameters. + """ + self.host = config["host"] + self.port = config["port"] + self.user = config["user"] + self.password = config["password"] + self.database = config["database"] + self.connect() + + def connect(self) -> None: + """ + Establish a connection to the ClickHouse server. + """ + try: + self.client = Client( + host=self.host, + port=self.port, + user=self.user, + password=self.password, + database=self.database, + ) + logger.info("Successfully connected to ClickHouse.") + except Exception as e: + logger.error(f"Failed to connect to ClickHouse: {e}") + raise + + def run_sql(self, sql: str) -> pd.DataFrame: + """ + Execute a SQL query and return the result as a pandas DataFrame. + + Parameters: + sql (str): SQL query string to be executed. + + Returns: + pd.DataFrame: Result of the SQL query as a pandas DataFrame. + """ + if self.client is None: + self.connect() + + try: + result = self.client.query_dataframe(sql) + return result + except Exception as e: + logger.error(f"Failed to execute SQL query: {e}") + raise + + def close(self) -> None: + """ + Close the connection to the ClickHouse server. + """ + if self.client: + self.client.disconnect() + logger.error("Connection to ClickHouse closed.") + self.client = None diff --git a/db_utils/config.py b/db_utils/config.py new file mode 100644 index 0000000..4deb2c4 --- /dev/null +++ b/db_utils/config.py @@ -0,0 +1,11 @@ +from typing import Optional, Dict, TypedDict + + +class DBConfig(TypedDict): + + host: str + port: Optional[int] + user: Optional[str] + password: Optional[str] + database: Optional[str] + extra: Optional[Dict[str, str]] diff --git a/db_utils/databricks_connector.py b/db_utils/databricks_connector.py new file mode 100644 index 0000000..6cd60b6 --- /dev/null +++ b/db_utils/databricks_connector.py @@ -0,0 +1,80 @@ +from databricks import sql +import pandas as pd +from .base_connector import BaseConnector +from .config import DBConfig +from .logger import logger + + +class DatabricksConnector(BaseConnector): + """ + Connect to Databricks SQL Warehouse and execute queries. + """ + + connection = None + + def __init__(self, config: DBConfig): + """ + Initialize the DatabricksConnector with connection parameters. + + Parameters: + config (DBConfig): Configuration object containing connection parameters. + Required keys: host, extra.http_path, extra.access_token + Optional keys: extra.catalog, extra.schema + """ + self.server_hostname = config["host"] + self.http_path = config["extra"]["http_path"] + self.access_token = config["extra"]["access_token"] + self.catalog = config.get("extra", {}).get("catalog") + self.schema = config.get("extra", {}).get("schema") + self.connect() + + def connect(self) -> None: + """ + Establish a connection to the Databricks SQL endpoint. + """ + try: + self.connection = sql.connect( + server_hostname=self.server_hostname, + http_path=self.http_path, + access_token=self.access_token, + catalog=self.catalog, + schema=self.schema, + ) + logger.info("Successfully connected to Databricks.") + except Exception as e: + logger.error(f"Failed to connect to Databricks: {e}") + raise + + def run_sql(self, sql: str) -> pd.DataFrame: + """ + Execute a SQL query and return result as pandas DataFrame. + + Parameters: + sql (str): SQL query string to be executed. + + Returns: + pd.DataFrame: Result of the SQL query as a pandas DataFrame. + """ + if self.connection is None: + self.connect() + + try: + cursor = self.connection.cursor() + cursor.execute(sql) + columns = [desc[0] for desc in cursor.description] + rows = cursor.fetchall() + return pd.DataFrame(rows, columns=columns) + except Exception as e: + logger.error(f"Failed to execute SQL query: {e}") + raise + finally: + cursor.close() + + def close(self) -> None: + """ + Close the Databricks connection. + """ + if self.connection: + self.connection.close() + logger.error("Connection to Databricks closed.") + self.connection = None diff --git a/db_utils/duckdb_connector.py b/db_utils/duckdb_connector.py new file mode 100644 index 0000000..41f7665 --- /dev/null +++ b/db_utils/duckdb_connector.py @@ -0,0 +1,60 @@ +import duckdb +import pandas as pd +from .base_connector import BaseConnector +from .config import DBConfig +from .logger import logger + + +class DuckDBConnector(BaseConnector): + """ + Connect to DuckDB and execute SQL queries. + """ + + connection = None + + def __init__(self, config: DBConfig): + """ + Initialize the DuckDBConnector with connection parameters. + + Parameters: + config (DBConfig): Configuration object containing connection parameters. + Uses config['path'] as the file path or ':memory:'. + """ + self.database = config.get("path", ":memory:") + self.connect() + + def connect(self) -> None: + """ + Establish a connection to the DuckDB database. + """ + try: + self.connection = duckdb.connect(database=self.database) + logger.info("Successfully connected to DuckDB.") + except Exception as e: + logger.error(f"Failed to connect to DuckDB: {e}") + raise + + def run_sql(self, sql: str) -> pd.DataFrame: + """ + Execute a SQL query and return the result as a pandas DataFrame. + + Parameters: + sql (str): SQL query string to be executed. + + Returns: + pd.DataFrame: Result of the SQL query as a pandas DataFrame. + """ + try: + return self.connection.execute(sql).fetchdf() + except Exception as e: + logger.error(f"Failed to execute SQL query: {e}") + raise + + def close(self) -> None: + """ + Close the connection to the DuckDB database. + """ + if self.connection: + self.connection.close() + logger.error("Connection to DuckDB closed.") + self.connection = None diff --git a/db_utils/logger.py b/db_utils/logger.py new file mode 100644 index 0000000..f2c3104 --- /dev/null +++ b/db_utils/logger.py @@ -0,0 +1,8 @@ +import logging + +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s [%(levelname)s] %(message)s", + datefmt="%Y-%m-%d %H:%M:%S", +) +logger = logging.getLogger(__name__) diff --git a/db_utils/mariadb_connector.py b/db_utils/mariadb_connector.py new file mode 100644 index 0000000..5770198 --- /dev/null +++ b/db_utils/mariadb_connector.py @@ -0,0 +1,76 @@ +import mysql.connector +import pandas as pd +from .base_connector import BaseConnector +from .config import DBConfig +from .logger import logger + + +class MariaDBConnector(BaseConnector): + """ + Connect to MariaDB and execute SQL queries. + This class uses **mysql-connector-python** to connect to the MariaDB server. + """ + + connection = None + + def __init__(self, config: DBConfig): + """ + Initialize the MariaDBConnector with connection parameters. + + Parameters: + config (DBConfig): Configuration object containing connection parameters. + """ + self.host = config["host"] + self.port = config.get("port", 3306) + self.user = config["user"] + self.password = config["password"] + self.database = config["database"] + self.connect() + + def connect(self) -> None: + """ + Establish a connection to the MariaDB server using mysql-connector-python. + """ + try: + self.connection = mysql.connector.connect( + host=self.host, + port=self.port, + user=self.user, + password=self.password, + database=self.database, + ) + logger.info("Successfully connected to MariaDB.") + except Exception as e: + logger.error(f"Failed to connect to MariaDB: {e}") + raise + + def run_sql(self, sql: str) -> pd.DataFrame: + """ + Execute a SQL query and return the result as a pandas DataFrame. + + Parameters: + sql (str): SQL query string to be executed. + + Returns: + pd.DataFrame: Result of the SQL query as a pandas DataFrame. + """ + try: + cursor = self.connection.cursor() + cursor.execute(sql) + columns = [column[0] for column in cursor.description] + rows = cursor.fetchall() + return pd.DataFrame(rows, columns=columns) + except Exception as e: + print(f"Failed to execute SQL query: {e}") + raise + finally: + cursor.close() + + def close(self) -> None: + """ + Close the connection to the MariaDB server. + """ + if self.connection: + self.connection.close() + print("Connection to MariaDB closed.") + self.connection = None diff --git a/db_utils/mysql_connector.py b/db_utils/mysql_connector.py new file mode 100644 index 0000000..2bcd2df --- /dev/null +++ b/db_utils/mysql_connector.py @@ -0,0 +1,75 @@ +import mysql.connector +import pandas as pd +from .base_connector import BaseConnector +from .config import DBConfig +from .logger import logger + + +class MySQLConnector(BaseConnector): + """ + Connect to MySQL and execute SQL queries. + """ + + connection = None + + def __init__(self, config: DBConfig): + """ + Initialize the MySQLConnector with connection parameters. + + Parameters: + config (DBConfig): Configuration object containing connection parameters. + """ + self.host = config["host"] + self.port = config.get("port", 3306) + self.user = config["user"] + self.password = config["password"] + self.database = config["database"] + self.connect() + + def connect(self) -> None: + """ + Establish a connection to the MySQL server. + """ + try: + self.connection = mysql.connector.connect( + host=self.host, + port=self.port, + user=self.user, + password=self.password, + database=self.database, + ) + logger.info("Successfully connected to MySQL.") + except Exception as e: + logger.error(f"Failed to connect to MySQL: {e}") + raise + + def run_sql(self, sql: str) -> pd.DataFrame: + """ + Execute a SQL query and return the result as a pandas DataFrame. + + Parameters: + sql (str): SQL query string to be executed. + + Returns: + pd.DataFrame: Result of the SQL query as a pandas DataFrame. + """ + try: + cursor = self.connection.cursor() + cursor.execute(sql) + columns = [column[0] for column in cursor.description] + rows = cursor.fetchall() + return pd.DataFrame(rows, columns=columns) + except Exception as e: + logger.error(f"Failed to execute SQL query: {e}") + raise + finally: + cursor.close() + + def close(self) -> None: + """ + Close the connection to the MySQL server. + """ + if self.connection: + self.connection.close() + logger.info("Connection to MySQL closed.") + self.connection = None diff --git a/db_utils/oracle_connector.py b/db_utils/oracle_connector.py new file mode 100644 index 0000000..6568daa --- /dev/null +++ b/db_utils/oracle_connector.py @@ -0,0 +1,67 @@ +import oracledb +import pandas as pd +from .base_connector import BaseConnector +from .config import DBConfig +from .logger import logger + + +class OracleConnector(BaseConnector): + """ + Connect to Oracle database and execute SQL queries. + """ + + connection = None + + def __init__(self, config: DBConfig): + """ + Initialize the OracleConnector with connection parameters. + Parameters: + config (DBConfig): Configuration object containing connection parameters. + """ + self.host = config["host"] + self.port = config["port"] + self.user = config["user"] + self.password = config["password"] + self.service_name = config.get("extra").get("service_name", "orcl") + self.connect() + + def connect(self) -> None: + """ + Establish a connection to the Oracle server. + """ + try: + self.connection = oracledb.connect( + user=self.user, + password=self.password, + dsn=f"{self.host}:{self.port}/{self.service_name}", + ) + logger.info("Successfully connected to Oracle.") + except Exception as e: + logger.error(f"Failed to connect to Oracle: {e}") + raise + + def run_sql(self, sql: str) -> pd.DataFrame: + """ + Execute a SQL query and return the result as a pandas DataFrame. + Parameters: + sql (str): SQL query string to be executed. + Returns: + pd.DataFrame: Result of the SQL query as a pandas DataFrame. + """ + try: + cursor = self.connection.cursor() + cursor.execute(sql) + columns = [desc[0] for desc in cursor.description] + rows = cursor.fetchall() + return pd.DataFrame(rows, columns=columns) + except Exception as e: + logger.error(f"Failed to execute SQL query: {e}") + raise + finally: + cursor.close() + + def close(self) -> None: + if self.connection: + self.connection.close() + logger.error("Connection to Oracle closed.") + self.connection = None diff --git a/db_utils/postgres_connector.py b/db_utils/postgres_connector.py new file mode 100644 index 0000000..fb31013 --- /dev/null +++ b/db_utils/postgres_connector.py @@ -0,0 +1,75 @@ +import psycopg2 +import pandas as pd +from .base_connector import BaseConnector +from .config import DBConfig +from .logger import logger + + +class PostgresConnector(BaseConnector): + """ + Connect to PostgreSQL and execute SQL queries. + """ + + connection = None + + def __init__(self, config: DBConfig): + """ + Initialize the PostgresConnector with connection parameters. + + Parameters: + config (DBConfig): Configuration object containing connection parameters. + """ + self.host = config["host"] + self.port = config["port"] + self.user = config["user"] + self.password = config["password"] + self.database = config["database"] + self.connect() + + def connect(self) -> None: + """ + Establish a connection to the PostgreSQL server. + """ + try: + self.connection = psycopg2.connect( + host=self.host, + port=self.port, + user=self.user, + password=self.password, + dbname=self.database, + ) + logger.info("Successfully connected to PostgreSQL.") + except Exception as e: + logger.error(f"Failed to connect to PostgreSQL: {e}") + raise + + def run_sql(self, sql: str) -> pd.DataFrame: + """ + Execute a SQL query and return the result as a pandas DataFrame. + + Parameters: + sql (str): SQL query string to be executed. + + Returns: + pd.DataFrame: Result of the SQL query as a pandas DataFrame. + """ + try: + cursor = self.connection.cursor() + cursor.execute(sql) + columns = [desc[0] for desc in cursor.description] + rows = cursor.fetchall() + return pd.DataFrame(rows, columns=columns) + except Exception as e: + logger.error(f"Failed to execute SQL query: {e}") + raise + finally: + cursor.close() + + def close(self) -> None: + """ + Close the connection to the PostgreSQL server. + """ + if self.connection: + self.connection.close() + logger.info("Connection to PostgreSQL closed.") + self.connection = None diff --git a/db_utils/snowflake_connector.py b/db_utils/snowflake_connector.py new file mode 100644 index 0000000..401233e --- /dev/null +++ b/db_utils/snowflake_connector.py @@ -0,0 +1,84 @@ +from .base_connector import BaseConnector +from snowflake import connector +import pandas as pd +from .config import DBConfig +from .logger import logger + + +class SnowflakeConnector(BaseConnector): + """ + Connect to Snowflake database and execute SQL queries. + """ + + connection = None + + def __init__(self, config: DBConfig): + """ + Initialize the SnowflakeConnector with connection parameters. + + Parameters: + config (DBConfig): Configuration object containing connection parameters. + Required: user, password, extra.account + Optional: extra.warehouse, database, extra.schema + """ + self.user = config["user"] + self.password = config["password"] + self.account = config["extra"]["account"] + self.warehouse = config.get("extra", {}).get("warehouse") + self.database = config.get("database") + self.schema = config.get("extra", {}).get("schema") + self.connect() + + def connect(self) -> None: + """ + Establish a connection to the Snowflake server. + """ + try: + self.connection = connector.connect( + user=self.user, + password=self.password, + account=self.account, + warehouse=self.warehouse, + database=self.database, + schema=self.schema, + ) + logger.info("Successfully connected to Snowflake.") + self.cursor = self.connection.cursor() + except Exception as e: + logger.error(f"Failed to connect to Snowflake: {e}") + raise + + def run_sql(self, sql: str) -> pd.DataFrame: + """ + Execute a SQL query and return the result as a pandas DataFrame. + + Parameters: + sql (str): SQL query string to be executed. + + Returns: + pd.DataFrame: Result of the SQL query as a pandas DataFrame. + """ + if self.connection is None: + self.connect() + + cursor = self.connection.cursor() + + try: + self.cursor.execute(sql) + columns = [col[0] for col in self.cursor.description] + data = self.cursor.fetchall() + return pd.DataFrame(data, columns=columns) + except Exception as e: + logger.error(f"Failed to execute SQL query: {e}") + raise + finally: + cursor.close() + + def close(self) -> None: + """ + Close the connection to the Snowflake server. + """ + if self.connection: + self.connection.close() + logger.info("Connection to Snowflake closed.") + self.connection = None diff --git a/db_utils/sqlite_connector.py b/db_utils/sqlite_connector.py new file mode 100644 index 0000000..aeb871c --- /dev/null +++ b/db_utils/sqlite_connector.py @@ -0,0 +1,70 @@ +import sqlite3 +import pandas as pd +from .base_connector import BaseConnector +from .config import DBConfig +from .logger import logger + + +class SQLiteConnector(BaseConnector): + """ + Connect to SQLite and execute SQL queries. + """ + + connection = None + + def __init__(self, config: DBConfig): + """ + Initialize the SQLiteConnector with connection parameters. + + Parameters: + config (DBConfig): Configuration object containing connection parameters. + Uses config["database"] as the SQLite file path. + If None or ":memory:", creates an in-memory database. + """ + self.database = config.get("path", ":memory:") + self.connect() + + def connect(self) -> None: + """ + Establish a connection to the SQLite database. + """ + try: + self.connection = sqlite3.connect(self.database) + logger.info(f"Successfully connected to SQLite ({self.database}).") + except Exception as e: + logger.error(f"Failed to connect to SQLite: {e}") + raise + + def run_sql(self, sql: str) -> pd.DataFrame: + """ + Execute a SQL query and return the result as a pandas DataFrame. + + Parameters: + sql (str): SQL query string to be executed. + + Returns: + pd.DataFrame: Result of the SQL query as a pandas DataFrame. + """ + if self.connection is None: + self.connect() + + try: + cursor = self.connection.cursor() + cursor.execute(sql) + columns = [col[0] for col in cursor.description] + rows = cursor.fetchall() + return pd.DataFrame(rows, columns=columns) + except Exception as e: + logger.error(f"Failed to execute SQL query: {e}") + raise + finally: + cursor.close() + + def close(self) -> None: + """ + Close the connection to the SQLite database. + """ + if self.connection: + self.connection.close() + logger.info("Connection to SQLite closed.") + self.connection = None diff --git a/evaluation/gen_persona.py b/evaluation/gen_persona.py index 4884d63..f1bcffc 100644 --- a/evaluation/gen_persona.py +++ b/evaluation/gen_persona.py @@ -4,7 +4,7 @@ from persona_class import PersonaList from llm_utils.tools import _get_table_info -from langchain_openai.chat_models import ChatOpenAI +from llm_utils.llm_factory import get_llm from langchain_core.prompts import ChatPromptTemplate from argparse import ArgumentParser @@ -19,7 +19,7 @@ def get_table_des_string(tables_desc): def generate_persona(tables_desc): description_string = get_table_des_string(tables_desc) - llm = ChatOpenAI(model="gpt-4o-mini", temperature=0) + llm = get_llm(temperature=0) system_prompt = """주어진 Tabel description들을 참고하여 Text2SQL 서비스로 질문을 할만한 패르소나를 생성하세요""" prompt = ChatPromptTemplate.from_messages( diff --git a/interface/lang2sql.py b/interface/lang2sql.py index 9d94268..db4f7bd 100644 --- a/interface/lang2sql.py +++ b/interface/lang2sql.py @@ -5,10 +5,14 @@ ClickHouse 데이터베이스에 실행한 결과를 출력합니다. """ +import re + import streamlit as st from langchain.chains.sql_database.prompt import SQL_PROMPTS from langchain_core.messages import AIMessage, HumanMessage +from db_utils import get_db_connector +from db_utils.base_connector import BaseConnector from llm_utils.connect_db import ConnectDB from llm_utils.display_chart import DisplayChart from llm_utils.enriched_graph import builder as enriched_builder @@ -16,6 +20,7 @@ from llm_utils.llm_response_parser import LLMResponseParser from llm_utils.token_utils import TokenUtils + TITLE = "Lang2SQL" DEFAULT_QUERY = "고객 데이터를 기반으로 유니크한 유저 수를 카운트하는 쿼리" SIDEBAR_OPTIONS = { @@ -84,7 +89,7 @@ def execute_query( def display_result( *, res: dict, - database: ConnectDB, + database: BaseConnector, ) -> None: """ Lang2SQL 실행 결과를 Streamlit 화면에 출력합니다. @@ -195,7 +200,7 @@ def should_show(_key: str) -> bool: st.plotly_chart(fig) -db = ConnectDB() +db = get_db_connector() st.title(TITLE) diff --git a/llm_utils/llm_factory.py b/llm_utils/llm_factory.py index bdb4d64..b865fca 100644 --- a/llm_utils/llm_factory.py +++ b/llm_utils/llm_factory.py @@ -18,81 +18,91 @@ AzureChatOpenAI, OpenAIEmbeddings, ) -from langchain_community.llms.bedrock import Bedrock -# .env 파일 로딩 -load_dotenv() +env_path = os.path.join(os.getcwd(), ".env") +if os.path.exists(env_path): + load_dotenv(env_path, override=True) + print(f"✅ 환경변수 파일(.env)이 {os.getcwd()}에 로드되었습니다!") +else: + print(f"⚠️ 환경변수 파일(.env)이 {os.getcwd()}에 없습니다!") -def get_llm() -> BaseLanguageModel: + +def get_llm(**kwargs) -> BaseLanguageModel: """ return chat model interface """ provider = os.getenv("LLM_PROVIDER") + print(os.environ["LLM_PROVIDER"]) if provider is None: raise ValueError("LLM_PROVIDER environment variable is not set.") if provider == "openai": - return get_llm_openai() + return get_llm_openai(**kwargs) elif provider == "azure": - return get_llm_azure() + return get_llm_azure(**kwargs) elif provider == "bedrock": - return get_llm_bedrock() + return get_llm_bedrock(**kwargs) elif provider == "gemini": - return get_llm_gemini() + return get_llm_gemini(**kwargs) elif provider == "ollama": - return get_llm_ollama() + return get_llm_ollama(**kwargs) elif provider == "huggingface": - return get_llm_huggingface() + return get_llm_huggingface(**kwargs) else: raise ValueError(f"Invalid LLM API Provider: {provider}") -def get_llm_openai() -> BaseLanguageModel: +def get_llm_openai(**kwargs) -> BaseLanguageModel: return ChatOpenAI( - model=os.getenv("OPEN_MODEL_PREF", "gpt-4o"), + model=os.getenv("OPEN_AI_LLM_MODEL", "gpt-4o"), api_key=os.getenv("OPEN_AI_KEY"), + **kwargs, ) -def get_llm_azure() -> BaseLanguageModel: +def get_llm_azure(**kwargs) -> BaseLanguageModel: return AzureChatOpenAI( api_key=os.getenv("AZURE_OPENAI_LLM_KEY"), azure_endpoint=os.getenv("AZURE_OPENAI_LLM_ENDPOINT"), azure_deployment=os.getenv("AZURE_OPENAI_LLM_MODEL"), # Deployment name api_version=os.getenv("AZURE_OPENAI_LLM_API_VERSION", "2023-07-01-preview"), + **kwargs, ) -def get_llm_bedrock() -> BaseLanguageModel: +def get_llm_bedrock(**kwargs) -> BaseLanguageModel: return ChatBedrockConverse( model=os.getenv("AWS_BEDROCK_LLM_MODEL"), aws_access_key_id=os.getenv("AWS_BEDROCK_LLM_ACCESS_KEY_ID"), aws_secret_access_key=os.getenv("AWS_BEDROCK_LLM_SECRET_ACCESS_KEY"), region_name=os.getenv("AWS_BEDROCK_LLM_REGION", "us-east-1"), + **kwargs, ) -def get_llm_gemini() -> BaseLanguageModel: - return ChatGoogleGenerativeAI(model=os.getenv("GEMINI_LLM_MODEL")) +def get_llm_gemini(**kwargs) -> BaseLanguageModel: + return ChatGoogleGenerativeAI(model=os.getenv("GEMINI_LLM_MODEL"), **kwargs) -def get_llm_ollama() -> BaseLanguageModel: +def get_llm_ollama(**kwargs) -> BaseLanguageModel: base_url = os.getenv("OLLAMA_LLM_BASE_URL") if base_url: - return ChatOllama(base_url=base_url, model=os.getenv("OLLAMA_LLM_MODEL")) + return ChatOllama( + base_url=base_url, model=os.getenv("OLLAMA_LLM_MODEL"), **kwargs + ) else: - return ChatOllama(model=os.getenv("OLLAMA_LLM_MODEL")) + return ChatOllama(model=os.getenv("OLLAMA_LLM_MODEL"), **kwargs) -def get_llm_huggingface() -> BaseLanguageModel: +def get_llm_huggingface(**kwargs) -> BaseLanguageModel: return ChatHuggingFace( llm=HuggingFaceEndpoint( model=os.getenv("HUGGING_FACE_LLM_MODEL"), @@ -100,6 +110,7 @@ def get_llm_huggingface() -> BaseLanguageModel: task="text-generation", endpoint_url=os.getenv("HUGGING_FACE_LLM_ENDPOINT"), huggingfacehub_api_token=os.getenv("HUGGING_FACE_LLM_API_TOKEN"), + **kwargs, ) ) @@ -109,6 +120,7 @@ def get_embeddings() -> Optional[BaseLanguageModel]: return embedding model interface """ provider = os.getenv("EMBEDDING_PROVIDER") + print(provider) if provider is None: raise ValueError("EMBEDDING_PROVIDER environment variable is not set.") @@ -135,7 +147,7 @@ def get_embeddings() -> Optional[BaseLanguageModel]: def get_embeddings_openai() -> BaseLanguageModel: return OpenAIEmbeddings( model=os.getenv("OPEN_AI_EMBEDDING_MODEL"), - openai_api_key=os.getenv("OPEN_AI_EMBEDDING_KEY"), + openai_api_key=os.getenv("OPEN_AI_KEY"), ) diff --git a/llm_utils/retrieval.py b/llm_utils/retrieval.py index 728141f..0fa78a8 100644 --- a/llm_utils/retrieval.py +++ b/llm_utils/retrieval.py @@ -7,11 +7,12 @@ from transformers import AutoModelForSequenceClassification, AutoTokenizer from .tools import get_info_from_db +from .llm_factory import get_embeddings def get_vector_db(): """벡터 데이터베이스를 로드하거나 생성합니다.""" - embeddings = OpenAIEmbeddings(model="text-embedding-3-small") + embeddings = get_embeddings() try: db = FAISS.load_local( os.getcwd() + "/table_info_db", diff --git a/poetry.lock b/poetry.lock index 27a4aac..dee806e 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2,15 +2,15 @@ [[package]] name = "acryl-datahub" -version = "1.0.0.2" +version = "1.0.0.3" description = "A CLI to work with DataHub metadata" optional = false python-versions = ">=3.8" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ - {file = "acryl_datahub-1.0.0.2-py3-none-any.whl", hash = "sha256:f6d019b871f9d24f371cd96ff9924412f58e80e03b4c37f5823a64e1e010ce32"}, - {file = "acryl_datahub-1.0.0.2.tar.gz", hash = "sha256:c3a6cd2a1b947b57bca80bf735d890dff3688a06319ca46e7b1f997783267c50"}, + {file = "acryl_datahub-1.0.0.3-py3-none-any.whl", hash = "sha256:3c13dab0e2efa45ab049c05b1f9cbfa2117c42cc402aa1b3faa5ca18bd60238d"}, + {file = "acryl_datahub-1.0.0.3.tar.gz", hash = "sha256:d9df348a62edf85b5ba2f098ff9e4a1cbda2773729d60d54e7ee68bb443d926e"}, ] [package.dependencies] @@ -44,22 +44,23 @@ typing_extensions = ">=4.5.0" typing-inspect = "*" [package.extras] -abs = ["Deprecated", "PyYAML", "aiohttp (<4)", "avro (>=1.11.3,<1.13)", "avro-gen3 (==0.7.16)", "azure-core (==1.29.4)", "azure-identity (>=1.17.1)", "azure-storage-blob (>=12.19.0)", "azure-storage-file-datalake (>=12.14.0)", "cached_property", "cachetools", "click (>=7.1.2)", "click-default-group", "click-spinner", "docker", "expandvars (>=0.6.5)", "humanfriendly", "ijson", "importlib_metadata (>=4.0.0)", "jsonref", "jsonschema", "more-itertools (>=8.12.0)", "packaging", "parse (>=1.19.0)", "progressbar2", "psutil (>=5.8.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pydeequ (>=1.1.0)", "pyspark (>=3.5.0,<3.6.0)", "python-dateutil (>=2.8.0)", "requests_file", "ruamel.yaml", "smart-open[azure] (>=5.2.1)", "tableschema (>=1.20.2)", "tabulate", "toml (>=0.10.0)", "ujson (>=5.2.0)", "wcmatch"] -airflow = ["Deprecated", "PyYAML", "acryl-datahub-airflow-plugin (==1.0.0.2)", "aiohttp (<4)", "avro (>=1.11.3,<1.13)", "avro-gen3 (==0.7.16)", "cached_property", "click (>=7.1.2)", "click-default-group", "click-spinner", "docker", "expandvars (>=0.6.5)", "humanfriendly", "ijson", "importlib_metadata (>=4.0.0)", "jsonref", "jsonschema", "packaging", "progressbar2", "psutil (>=5.8.0)", "python-dateutil (>=2.8.0)", "requests_file", "ruamel.yaml", "tabulate", "toml (>=0.10.0)"] -all = ["Authlib", "Deprecated", "GeoAlchemy2", "GitPython (>2)", "IPython (!=8.22.0)", "JPype1", "PyAthena[sqlalchemy] (>=2.6.0,<3.0.0)", "PyYAML", "acryl-datahub-classify (==0.0.11)", "acryl-pyhive[hive-pure-sasl] (==0.6.16)", "aiohttp (<4)", "avro (>=1.11.3,<1.13)", "avro-gen3 (==0.7.16)", "azure-core (==1.29.4)", "azure-identity (>=1.17.1)", "azure-storage-blob (>=12.19.0)", "azure-storage-file-datalake (>=12.14.0)", "boto3", "botocore (!=1.23.0)", "cached_property", "cachetools", "cassandra-driver (>=3.28.0)", "click (>=7.1.2)", "click-default-group", "click-spinner", "clickhouse-sqlalchemy (>=0.2.0,<0.2.5)", "confluent_kafka[avro,schemaregistry] (>=1.9.0,!=2.8.1)", "cryptography", "databricks-dbapi", "databricks-sdk (>=0.30.0)", "databricks-sql-connector (>=2.8.0,<3.0.0)", "db-dtypes", "deepmerge (>=1.1.1)", "deltalake (>=0.6.3,!=0.6.4)", "deltalake (>=0.6.3,!=0.6.4,!=0.18.0)", "docker", "elasticsearch (==7.13.4)", "expandvars (>=0.6.5)", "fastavro (>=1.2.0)", "filelock", "google-cloud-aiplatform (>=1.80.0)", 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"sqlparse", "tabulate", "tenacity (!=8.4.0)", "toml (>=0.10.0)", "traitlets (!=5.2.2)"] +abs = ["Deprecated", "PyYAML", "aiohttp (<4)", "avro (>=1.11.3,<1.13)", "avro-gen3 (==0.7.16)", "azure-core (>=1.31.0)", "azure-identity (>=1.21.0)", "azure-storage-blob (>=12.19.0)", "azure-storage-file-datalake (>=12.14.0)", "cached_property", "cachetools", "click (>=7.1.2)", "click-default-group", "click-spinner", "docker", "expandvars (>=0.6.5)", "humanfriendly", "ijson", "importlib_metadata (>=4.0.0)", "jsonref", "jsonschema", "more-itertools (>=8.12.0)", "packaging", "parse (>=1.19.0)", "progressbar2", "psutil (>=5.8.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pydeequ (>=1.1.0)", "pyspark (>=3.5.0,<3.6.0)", "python-dateutil (>=2.8.0)", "requests_file", "ruamel.yaml", "smart-open[azure] (>=5.2.1)", "tableschema (>=1.20.2)", "tabulate", "toml (>=0.10.0)", "ujson (>=5.2.0)", "wcmatch"] +airflow = ["Deprecated", "PyYAML", "acryl-datahub-airflow-plugin (==1.0.0.3)", "aiohttp (<4)", "avro 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"ruamel.yaml", "tabulate", "toml (>=0.10.0)"] datahub-kafka = ["Deprecated", "PyYAML", "aiohttp (<4)", "avro (>=1.11.3,<1.13)", "avro-gen3 (==0.7.16)", "cached_property", "click (>=7.1.2)", "click-default-group", "click-spinner", "confluent_kafka[avro,schemaregistry] (>=1.9.0,!=2.8.1)", "docker", "expandvars (>=0.6.5)", "fastavro (>=1.2.0)", "humanfriendly", "ijson", "importlib_metadata (>=4.0.0)", "jsonref", "jsonschema", "packaging", "progressbar2", "psutil (>=5.8.0)", "python-dateutil (>=2.8.0)", "requests_file", "ruamel.yaml", "tabulate", "toml (>=0.10.0)"] datahub-lineage-file = ["Deprecated", "PyYAML", "aiohttp (<4)", "avro (>=1.11.3,<1.13)", "avro-gen3 (==0.7.16)", "cached_property", "click (>=7.1.2)", "click-default-group", "click-spinner", "docker", "expandvars (>=0.6.5)", "humanfriendly", "ijson", "importlib_metadata (>=4.0.0)", "jsonref", "jsonschema", "packaging", "progressbar2", "psutil (>=5.8.0)", "pydantic (<2)", "python-dateutil (>=2.8.0)", "requests_file", "ruamel.yaml", "tabulate", "toml (>=0.10.0)"] @@ -68,75 +69,76 @@ datahub-rest = ["Deprecated", "PyYAML", "aiohttp (<4)", "avro (>=1.11.3,<1.13)", dbt = ["Deprecated", "PyYAML", "aiohttp (<4)", "avro (>=1.11.3,<1.13)", "avro-gen3 (==0.7.16)", "boto3", "botocore (!=1.23.0)", "cached_property", "click (>=7.1.2)", "click-default-group", "click-spinner", "docker", "expandvars (>=0.6.5)", "humanfriendly", "ijson", "importlib_metadata (>=4.0.0)", "jsonref", "jsonschema", "more_itertools", "packaging", "patchy (==2.8.0)", "progressbar2", "psutil (>=5.8.0)", "pydantic (<2)", "python-dateutil (>=2.8.0)", "requests", "requests_file", "ruamel.yaml", "sqlglot[rs] (==26.6.0)", "tabulate", "toml (>=0.10.0)"] dbt-cloud = ["Deprecated", "PyYAML", "aiohttp (<4)", "avro (>=1.11.3,<1.13)", "avro-gen3 (==0.7.16)", "cached_property", "click (>=7.1.2)", "click-default-group", "click-spinner", "docker", "expandvars (>=0.6.5)", "humanfriendly", "ijson", "importlib_metadata (>=4.0.0)", "jsonref", "jsonschema", 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python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "python_utils-3.9.1-py2.py3-none-any.whl", hash = "sha256:0273d7363c7ad4b70999b2791d5ba6b55333d6f7a4e4c8b6b39fb82b5fab4613"}, {file = "python_utils-3.9.1.tar.gz", hash = "sha256:eb574b4292415eb230f094cbf50ab5ef36e3579b8f09e9f2ba74af70891449a0"}, @@ -4120,7 +4631,7 @@ description = "World timezone definitions, modern and historical" optional = false python-versions = "*" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "pytz-2025.2-py2.py3-none-any.whl", hash = "sha256:5ddf76296dd8c44c26eb8f4b6f35488f3ccbf6fbbd7adee0b7262d43f0ec2f00"}, {file = "pytz-2025.2.tar.gz", hash = "sha256:360b9e3dbb49a209c21ad61809c7fb453643e048b38924c765813546746e81c3"}, @@ -4160,7 +4671,7 @@ description = "A (partial) reimplementation of pywin32 using ctypes/cffi" optional = false python-versions = ">=3.6" groups = ["main"] -markers = "(platform_machine != \"ppc64le\" and platform_machine != \"s390x\") and sys_platform == \"win32\" and (python_version == \"3.11\" or python_version >= \"3.12\")" +markers = "(python_version == \"3.11\" or python_version >= \"3.12\") and sys_platform == \"win32\" and (platform_machine != \"ppc64le\" and platform_machine != \"s390x\")" files = [ {file = "pywin32-ctypes-0.2.3.tar.gz", hash = "sha256:d162dc04946d704503b2edc4d55f3dba5c1d539ead017afa00142c38b9885755"}, {file = "pywin32_ctypes-0.2.3-py3-none-any.whl", hash = "sha256:8a1513379d709975552d202d942d9837758905c8d01eb82b8bcc30918929e7b8"}, @@ -4173,7 +4684,7 @@ description = "YAML parser and emitter for Python" optional = false python-versions = ">=3.8" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = 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\"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "referencing-0.36.2-py3-none-any.whl", hash = "sha256:e8699adbbf8b5c7de96d8ffa0eb5c158b3beafce084968e2ea8bb08c6794dcd0"}, {file = "referencing-0.36.2.tar.gz", hash = "sha256:df2e89862cd09deabbdba16944cc3f10feb6b3e6f18e902f7cc25609a34775aa"}, @@ -4276,7 +4787,7 @@ description = "Alternative regular expression module, to replace re." optional = false python-versions = ">=3.8" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ff590880083d60acc0433f9c3f713c51f7ac6ebb9adf889c79a261ecf541aa91"}, {file = "regex-2024.11.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:658f90550f38270639e83ce492f27d2c8d2cd63805c65a13a14d36ca126753f0"}, @@ -4381,7 +4892,7 @@ description 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python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "rpds_py-0.24.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:006f4342fe729a368c6df36578d7a348c7c716be1da0a1a0f86e3021f8e98724"}, {file = "rpds_py-0.24.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2d53747da70a4e4b17f559569d5f9506420966083a31c5fbd84e764461c4444b"}, @@ -4597,7 +5108,7 @@ description = "Pure-Python RSA implementation" optional = false python-versions = "<4,>=3.6" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "rsa-4.9.1-py3-none-any.whl", hash = "sha256:68635866661c6836b8d39430f97a996acbd61bfa49406748ea243539fe239762"}, {file = "rsa-4.9.1.tar.gz", hash = "sha256:e7bdbfdb5497da4c07dfd35530e1a902659db6ff241e39d9953cad06ebd0ae75"}, @@ -4613,7 +5124,7 @@ description = "ruamel.yaml is a YAML parser/emitter that supports 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["cmake (>=3.20)", "lit"] -tests = ["autopep8", "flake8", "isort", "llnl-hatchet", "numpy", "pytest", "scipy (>=1.7.1)"] +tests = ["autopep8", "isort", "llnl-hatchet", "numpy", "pytest", "pytest-forked", "pytest-xdist", "scipy (>=1.7.1)"] tutorials = ["matplotlib", "pandas", "tabulate"] [[package]] @@ -5528,7 +6155,7 @@ description = "Collection of utilities for publishing packages on PyPI" optional = false python-versions = ">=3.8" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "twine-6.1.0-py3-none-any.whl", hash = "sha256:a47f973caf122930bf0fbbf17f80b83bc1602c9ce393c7845f289a3001dc5384"}, {file = "twine-6.1.0.tar.gz", hash = "sha256:be324f6272eff91d07ee93f251edf232fc647935dd585ac003539b42404a8dbd"}, @@ -5555,7 +6182,7 @@ description = "Backported and Experimental Type Hints for Python 3.8+" optional = false python-versions = ">=3.8" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "typing_extensions-4.13.2-py3-none-any.whl", hash = "sha256:a439e7c04b49fec3e5d3e2beaa21755cadbbdc391694e28ccdd36ca4a1408f8c"}, {file = "typing_extensions-4.13.2.tar.gz", hash = "sha256:e6c81219bd689f51865d9e372991c540bda33a0379d5573cddb9a3a23f7caaef"}, @@ -5568,7 +6195,7 @@ description = "Runtime inspection utilities for typing module." optional = false python-versions = "*" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "typing_inspect-0.9.0-py3-none-any.whl", hash = "sha256:9ee6fc59062311ef8547596ab6b955e1b8aa46242d854bfc78f4f6b0eff35f9f"}, {file = "typing_inspect-0.9.0.tar.gz", hash = "sha256:b23fc42ff6f6ef6954e4852c1fb512cdd18dbea03134f91f856a95ccc9461f78"}, @@ -5585,7 +6212,7 @@ description = "Runtime typing introspection tools" optional = false python-versions = ">=3.9" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "typing_inspection-0.4.0-py3-none-any.whl", hash = "sha256:50e72559fcd2a6367a19f7a7e610e6afcb9fac940c650290eed893d61386832f"}, {file = "typing_inspection-0.4.0.tar.gz", hash = "sha256:9765c87de36671694a67904bf2c96e395be9c6439bb6c87b5142569dcdd65122"}, @@ -5601,12 +6228,31 @@ description = "Provider of IANA time zone data" optional = false python-versions = ">=2" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "tzdata-2025.2-py2.py3-none-any.whl", hash = "sha256:1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8"}, {file = "tzdata-2025.2.tar.gz", hash = "sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9"}, ] +[[package]] +name = "tzlocal" +version = "5.3.1" +description = "tzinfo object for the local timezone" +optional = false +python-versions = ">=3.9" +groups = ["main"] +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" +files = [ + {file = "tzlocal-5.3.1-py3-none-any.whl", hash = "sha256:eb1a66c3ef5847adf7a834f1be0800581b683b5608e74f86ecbcef8ab91bb85d"}, + {file = "tzlocal-5.3.1.tar.gz", hash = "sha256:cceffc7edecefea1f595541dbd6e990cb1ea3d19bf01b2809f362a03dd7921fd"}, +] + +[package.dependencies] +tzdata = {version = "*", markers = "platform_system == \"Windows\""} + +[package.extras] +devenv = ["check-manifest", "pytest (>=4.3)", "pytest-cov", "pytest-mock (>=3.3)", "zest.releaser"] + [[package]] name = "urllib3" version = "2.4.0" @@ -5614,7 +6260,7 @@ description = "HTTP library with thread-safe connection pooling, file post, and optional = false python-versions = ">=3.9" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "urllib3-2.4.0-py3-none-any.whl", hash = "sha256:4e16665048960a0900c702d4a66415956a584919c03361cac9f1df5c5dd7e813"}, {file = "urllib3-2.4.0.tar.gz", hash = "sha256:414bc6535b787febd7567804cc015fee39daab8ad86268f1310a9250697de466"}, @@ -5628,15 +6274,15 @@ zstd = ["zstandard (>=0.18.0)"] [[package]] name = "virtualenv" -version = "20.30.0" +version = "20.31.2" description = "Virtual Python Environment builder" optional = false python-versions = ">=3.8" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ - {file = "virtualenv-20.30.0-py3-none-any.whl", hash = "sha256:e34302959180fca3af42d1800df014b35019490b119eba981af27f2fa486e5d6"}, - {file = "virtualenv-20.30.0.tar.gz", hash = "sha256:800863162bcaa5450a6e4d721049730e7f2dae07720e0902b0e4040bd6f9ada8"}, + {file = "virtualenv-20.31.2-py3-none-any.whl", hash = "sha256:36efd0d9650ee985f0cad72065001e66d49a6f24eb44d98980f630686243cf11"}, + {file = "virtualenv-20.31.2.tar.gz", hash = "sha256:e10c0a9d02835e592521be48b332b6caee6887f332c111aa79a09b9e79efc2af"}, ] [package.dependencies] @@ -5699,7 +6345,7 @@ description = "A built-package format for Python" optional = false python-versions = ">=3.8" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "wheel-0.45.1-py3-none-any.whl", hash = "sha256:708e7481cc80179af0e556bbf0cc00b8444c7321e2700b8d8580231d13017248"}, {file = "wheel-0.45.1.tar.gz", hash = "sha256:661e1abd9198507b1409a20c02106d9670b2576e916d58f520316666abca6729"}, @@ -5715,7 +6361,7 @@ description = "Module for decorators, wrappers and monkey patching." optional = false python-versions = ">=3.8" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "wrapt-1.17.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:3d57c572081fed831ad2d26fd430d565b76aa277ed1d30ff4d40670b1c0dd984"}, {file = "wrapt-1.17.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b5e251054542ae57ac7f3fba5d10bfff615b6c2fb09abeb37d2f1463f841ae22"}, @@ -5805,7 +6451,7 @@ description = "Yet another URL library" optional = false python-versions = ">=3.9" groups = ["main"] -markers = "python_version == \"3.11\" or python_version >= \"3.12\"" +markers = "python_version >= \"3.12\" or python_version == \"3.11\"" files = [ {file = "yarl-1.20.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:f1f6670b9ae3daedb325fa55fbe31c22c8228f6e0b513772c2e1c623caa6ab22"}, {file = "yarl-1.20.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:85a231fa250dfa3308f3c7896cc007a47bc76e9e8e8595c20b7426cac4884c62"}, @@ -5925,7 +6571,7 @@ description = "Backport of pathlib-compatible object wrapper for zip files" optional = false python-versions = ">=3.9" groups = ["main"] -markers = "(platform_machine != \"ppc64le\" and platform_machine != \"s390x\") and python_version == \"3.11\"" +markers = "python_version == \"3.11\" and (platform_machine != \"ppc64le\" and platform_machine != \"s390x\")" files = [ {file = "zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931"}, {file = "zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4"}, @@ -5942,4 +6588,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.1" python-versions = ">=3.11, <4.0" -content-hash = "6b17b29c6357a92dce2c3abb01d9dda3ed2edd5aa5dd436a4980a4d89629f5db" +content-hash = "8a77b61965b04e3bd91dbac283c8431c8c8b6ec33f08c7f2e8da132d5937b946" diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..f72e3f5 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,14 @@ +[tool.black] +line-length = 88 +target-version = ['py311'] +include = '\.pyi?$' +exclude = ''' +( + /( + \.git + | \.venv + | build + | dist + )/ +) +''' diff --git a/pyproject.toml_ b/pyproject.toml_ deleted file mode 100644 index f0d6098..0000000 --- a/pyproject.toml_ +++ /dev/null @@ -1,55 +0,0 @@ -[build-system] -requires = ["setuptools>=42", "wheel"] -build-backend = "setuptools.build_meta" - -# [tool.black] -# line-length = 88 -# target-version = ['py311'] -# include = '\.pyi?$' -# exclude = ''' -# ( -# /( -# \.git -# | \.venv -# | build -# | dist -# )/ -# ) -# ''' - -# [tool.poetry.group.dev.dependencies] -# pytest = "^8.3.5" - -# [project] -# name = "lang2sql" -# version = "0.1.9" -# description = "" -# authors = [ -# {name = "Yoonjin Hwang",email = "21603682@hankooktech.com"} -# ] -# readme = "README.md" -# requires-python = ">=3.11, <4.0" -# dependencies = [ -# "langgraph (==0.2.62)", -# "datahub (==0.999.1)", -# "langchain (==0.3.14)", -# "langchain-community (==0.3.14)", -# "openai (==1.59.8)", -# "langchain-openai (==0.3.0)", -# "streamlit (==1.41.1)", -# "python-dotenv (==1.0.1)", -# "faiss-cpu (==1.10.0)", -# "pre-commit (==4.1.0)", -# "setuptools (>=78.1.1,<79.0.0)", -# "wheel (>=0.45.1,<0.46.0)", -# "twine (>=6.1.0,<7.0.0)", -# "langchain-aws (>=0.2.21,<0.3.0)", -# "langchain-google-genai (>=2.1.3,<3.0.0)", -# "langchain-ollama (>=0.3.2,<0.4.0)", -# "langchain-huggingface (>=0.1.2,<0.2.0)" -# ] - - -# [build-system] -# requires = ["poetry-core>=2.0.0,<3.0.0"] -# build-backend = "poetry.core.masonry.api" diff --git a/requirements.txt b/requirements.txt index 6ebd0f5..aa4c963 100644 --- a/requirements.txt +++ b/requirements.txt @@ -16,10 +16,21 @@ langchain-aws>=0.2.21,<0.3.0 langchain-google-genai>=2.1.3,<3.0.0 langchain-ollama>=0.3.2,<0.4.0 langchain-huggingface>=0.1.2,<0.2.0 -clickhouse_driver +clickhouse_driver>=0.2.9,<0.3.0 plotly matplotlib ipython kaleido numpy<2.0 pytest>=8.3.5 +snowflake-connector-python>=3.15.0,<4.0.0 +databricks-sql-connector>=4.0.3,<5.0.0 +mysql>=0.0.3,<0.0.4 +oracledb>=3.1.0,<4.0.0 +mysql-connector-python>=9.3.0,<10.0.0 +duckdb>=1.2.2,<2.0.0 +psycopg2>=2.9.10,<3.0.0 +pyodbc>=5.1.0,<6.0.0 +crate>=0.29.0,<1.0.0 +pyhive>=0.6.6,<1.0.0 +google-cloud-bigquery>=3.20.1,<4.0.0 \ No newline at end of file