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� ��'j� � � � d Z ddlmZmZmZ ddlZddlmZ ddl m Z ddl m Z m Z mZmZmZmZmZ ddlmZ G d� d e� Zy) z�Embeddings integration utilities for MySQL Connector/Python. Provides MyEmbeddings class to generate embeddings via MySQL HeatWave using ML_EMBED_TABLE and ML_EMBED_ROW. � )�Dict�List�OptionalN)� Embeddings)� PrivateAttr)�atomic_transaction� execute_sql�format_value_sql� source_schema�sql_table_from_df�sql_table_to_df�temporary_sql_tables)�MySQLConnectionAbstractc � � � e Zd ZU dZ e� Zeed< d dedee f� fd� Z de e de e e fd�Zd e de e fd �Z� xZS ) � MyEmbeddingsa� Embedding generator class that uses a MySQL database to compute embeddings for input text. This class batches input text into temporary SQL tables, invokes MySQL's ML_EMBED_TABLE to generate embeddings, and retrieves the results as lists of floats. Attributes: _db_connection (MySQLConnectionAbstract): MySQL connection used for all database operations. schema_name (str): Name of the database schema to use. options_placeholder (str): SQL-ready placeholder string for ML_EMBED_TABLE options. options_params (dict): Dictionary of concrete option values to be passed as SQL parameters. �_db_connection� db_connection�optionsc � �� t �| � � || _ t |� | _ |xs i }t |� \ | _ | _ y)a� Initialize MyEmbeddings with a database connection and optional embedding parameters. References: https://dev.mysql.com/doc/heatwave/en/mys-hwgenai-ml-embed-row.html A full list of supported options can be found under "options" NOTE: The supported "options" are the intersection of the options provided in https://dev.mysql.com/doc/heatwave/en/mys-hwgenai-ml-embed-row.html https://dev.mysql.com/doc/heatwave/en/mys-hwgenai-ml-embed-table.html Args: db_connection: Active MySQL connector database connection. options: Optional dictionary of options for embedding operations. Raises: ValueError: If the schema name is not valid DatabaseError: If a database connection issue occurs. If an operational error occurs during execution. N)�super�__init__r r � schema_namer �options_placeholder�options_params)�selfr r � __class__s ��I/opt/nydus/tmp/pip-target-k0fmikie/lib/python/mysql/ai/genai/embedding.pyr zMyEmbeddings.__init__F sC �� �0 ���� +���(� �7����-�R��8H��8Q�5�� �$�"5� �texts�returnc � � |sg S t j t t |� � |d�� }t | j � 5 }t | j � 5 }t || j |� \ }}|j | j |f� d|� d|� d| j � d�}t ||| j �� t || j |� }|d j � j � st d� |d D � � r t! d � �|d j# � } | D � cg c] } t% | � �� } } | cd d d � cd d d � S c c} w # 1 sw Y nxY w d d d � y # 1 sw Y y xY w) a� Generate embeddings for a list of input texts using the MySQL ML embedding procedure. References: https://dev.mysql.com/doc/heatwave/en/mys-hwgenai-ml-embed-table.html Args: texts: List of input strings to embed. Returns: List of lists of floats, with each inner list containing the embedding for a text. Raises: DatabaseError: If provided options are invalid or unsupported. If a database connection issue occurs. If an operational error occurs during execution. ValueError: If one or more text entries were unable to be embedded. Implementation notes: - Creates a temporary table to pass input text to the MySQL embedding service. - Adds a primary key to ensure results preserve input order. - Calls ML_EMBED_TABLE and fetches the resulting embeddings. - Deletes the temporary table after use to avoid polluting the database. - Embedding vectors are extracted from the "embeddings" column of the result table. )�id�textzCALL sys.ML_EMBED_TABLE('z .text', 'z.embeddings', �)��params� embeddingsc 3 �$ K � | ] }|d u �� � y �w�N� )�.0�es r � <genexpr>z/MyEmbeddings.embed_documents.<locals>.<genexpr>� s � �� � A�#>�a��T� �#>�s �z:Failure to generate embeddings for one or more text entry.N)�pd� DataFrame�range�lenr r r r r �appendr r r r �isnull�any� ValueError�tolist�list) r r �df�cursor�temporary_tables�qualified_table_name� table_name� embed_query� df_embeddingsr' r, s r �embed_documentsz MyEmbeddings.embed_documentsd s� � �8 ��I� �\�\��s�5�z�!2�E�B� C�� �t� 2� 2� 3�v� ��!4�!4� 5�9I�/@���(�(�"�0� ,� �*� � #� #�T�%5�%5�z�$B� C��(�)� *�(�)� ��+�+�,�� � � �� �D�4G�4G� H� ,�F�D�4D�4D�j� Q�M� �\�*�1�1�3�7�7�9�S� A�#0� �#>�A� >� !�P�� � '�|�4�;�;�=�J�+5�6�:�a�$�q�'�:�J�6� �? 6� 5� 4� 3��< 7�; 6� 5�� 5� 4� 3� 3�s7 �E2�CE �/E�E � E2�E � E% �!E2�2E;r# c �� � t | j � 5 }t |d| j � d�|g| j ���� t |j � d � cddd� S # 1 sw Y yxY w)a� Generate an embedding for a single text string. References: https://dev.mysql.com/doc/heatwave/en/mys-hwgenai-ml-embed-row.html Args: text: The input string to embed. Returns: List of floats representing the embedding vector. Raises: DatabaseError: If provided options are invalid or unsupported. If a database connection issue occurs. If an operational error occurs during execution. Example: >>> MyEmbeddings(db_conn).embed_query("Hello world") [0.1, 0.2, ...] z SELECT sys.ML_EMBED_ROW("%s", r$ r% r N)r r r r r r7 �fetchone)r r# r9 s r r= zMyEmbeddings.embed_query� se � �. �� 3� 3� 4�� ��0��1I�1I�0J�!�L� �3�t� 2� 2�3� � ����)�!�,�-� 5� 4� 4�s �AA&�&A/r) )�__name__� __module__� __qualname__�__doc__r r r �__annotations__r r r r �str�floatr? r= � __classcell__)r s @r r r 6 su �� � � /:�m�N�+�;� QU� R� 4� R�?G��~� R�<B �T�#�Y� B �4��U� �3D� B �H .�� .��U� � .r r )rE �typingr r r �pandasr. �langchain_core.embeddingsr �pydanticr �mysql.ai.utilsr r r r r r r �mysql.connector.abstractsr r r* r r �<module>rP s= ��:� (� '� � 0� �� � � >�O.�:� O.r
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