Package Methods (0.13.0)

Summary of entries of Methods for langchain-google-cloud-sql-pg.

langchain_google_cloud_sql_pg.engine._get_iam_principal_email

_get_iam_principal_email(credentials: google.auth.credentials.Credentials) -> str

Get email address associated with current authenticated IAM principal.

See more: langchain_google_cloud_sql_pg.engine._get_iam_principal_email

langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory

PostgresChatMessageHistory(
    key: object,
    engine: langchain_google_cloud_sql_pg.engine.PostgresEngine,
    history: langchain_google_cloud_sql_pg.async_chat_message_history.AsyncPostgresChatMessageHistory,
)

PostgresChatMessageHistory constructor.

See more: langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory

langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.aadd_message

aadd_message(message: langchain_core.messages.base.BaseMessage) -> None

Append the message to the record in PostgreSQL.

See more: langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.aadd_message

langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.aadd_messages

aadd_messages(
    messages: typing.Sequence[langchain_core.messages.base.BaseMessage],
) -> None

Append a list of messages to the record in PostgreSQL.

See more: langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.aadd_messages

langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.aclear

aclear() -> None

Clear session memory from PostgreSQL.

See more: langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.aclear

langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.add_message

add_message(message: langchain_core.messages.base.BaseMessage) -> None

Append the message to the record in PostgreSQL.

See more: langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.add_message

langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.add_messages

add_messages(
    messages: typing.Sequence[langchain_core.messages.base.BaseMessage],
) -> None

Append a list of messages to the record in PostgreSQL.

See more: langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.add_messages

langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.clear

clear() -> None

Clear session memory from PostgreSQL.

See more: langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.clear

langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.create

create(
    engine: langchain_google_cloud_sql_pg.engine.PostgresEngine,
    session_id: str,
    table_name: str,
    schema_name: str = "public",
) -> langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory

Create a new PostgresChatMessageHistory instance.

See more: langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.create

langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.create_sync

create_sync(
    engine: langchain_google_cloud_sql_pg.engine.PostgresEngine,
    session_id: str,
    table_name: str,
    schema_name: str = "public",
) -> langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory

Create a new PostgresChatMessageHistory instance.

See more: langchain_google_cloud_sql_pg.chat_message_history.PostgresChatMessageHistory.create_sync

langchain_google_cloud_sql_pg.engine.Column.__post_init__

__post_init__()

Check if initialization parameters are valid.

See more: langchain_google_cloud_sql_pg.engine.Column.post_init

langchain_google_cloud_sql_pg.engine.PostgresEngine

PostgresEngine(
    key: object,
    pool: sqlalchemy.ext.asyncio.engine.AsyncEngine,
    loop: typing.Optional[asyncio.events.AbstractEventLoop],
    thread: typing.Optional[threading.Thread],
)

PostgresEngine constructor.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine

langchain_google_cloud_sql_pg.engine.PostgresEngine._ainit_chat_history_table

_ainit_chat_history_table(table_name: str, schema_name: str = "public") -> None

Create a Cloud SQL table to store chat history.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine._ainit_chat_history_table

langchain_google_cloud_sql_pg.engine.PostgresEngine._ainit_checkpoint_table

_ainit_checkpoint_table(
    table_name: str = "checkpoints", schema_name: str = "public"
) -> None

Create PgSQL tables to save checkpoints.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine._ainit_checkpoint_table

langchain_google_cloud_sql_pg.engine.PostgresEngine._ainit_vectorstore_table

_ainit_vectorstore_table(
    table_name: str,
    vector_size: int,
    schema_name: str = "public",
    content_column: str = "content",
    embedding_column: str = "embedding",
    metadata_columns: list[langchain_google_cloud_sql_pg.engine.Column] = [],
    metadata_json_column: str = "langchain_metadata",
    id_column: typing.Union[
        str, langchain_google_cloud_sql_pg.engine.Column
    ] = "langchain_id",
    overwrite_existing: bool = False,
    store_metadata: bool = True,
) -> None

Create a table for saving of vectors to be used with PostgresVectorStore.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine._ainit_vectorstore_table

langchain_google_cloud_sql_pg.engine.PostgresEngine._aload_table_schema

_aload_table_schema(
    table_name: str, schema_name: str = "public"
) -> sqlalchemy.sql.schema.Table

Load table schema from existing table in PgSQL database.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine._aload_table_schema

langchain_google_cloud_sql_pg.engine.PostgresEngine._create

_create(
    project_id: str,
    region: str,
    instance: str,
    database: str,
    ip_type: typing.Union[str, google.cloud.sql.connector.enums.IPTypes],
    user: typing.Optional[str] = None,
    password: typing.Optional[str] = None,
    loop: typing.Optional[asyncio.events.AbstractEventLoop] = None,
    thread: typing.Optional[threading.Thread] = None,
    quota_project: typing.Optional[str] = None,
    iam_account_email: typing.Optional[str] = None,
    engine_args: typing.Mapping = {},
) -> langchain_google_cloud_sql_pg.engine.PostgresEngine

Create a PostgresEngine instance.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine._create

langchain_google_cloud_sql_pg.engine.PostgresEngine._run_as_async

_run_as_async(
    coro: typing.Awaitable[langchain_google_cloud_sql_pg.engine.T],
) -> langchain_google_cloud_sql_pg.engine.T

Run an async coroutine asynchronously.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine._run_as_async

langchain_google_cloud_sql_pg.engine.PostgresEngine._run_as_sync

_run_as_sync(
    coro: typing.Awaitable[langchain_google_cloud_sql_pg.engine.T],
) -> langchain_google_cloud_sql_pg.engine.T

Run an async coroutine synchronously.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine._run_as_sync

langchain_google_cloud_sql_pg.engine.PostgresEngine.afrom_instance

afrom_instance(
    project_id: str,
    region: str,
    instance: str,
    database: str,
    user: typing.Optional[str] = None,
    password: typing.Optional[str] = None,
    ip_type: typing.Union[
        str, google.cloud.sql.connector.enums.IPTypes
    ] = IPTypes.PUBLIC,
    quota_project: typing.Optional[str] = None,
    iam_account_email: typing.Optional[str] = None,
    engine_args: typing.Mapping = {},
) -> langchain_google_cloud_sql_pg.engine.PostgresEngine

Create a PostgresEngine from a Postgres instance.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.afrom_instance

langchain_google_cloud_sql_pg.engine.PostgresEngine.ainit_chat_history_table

ainit_chat_history_table(table_name: str, schema_name: str = "public") -> None

Create a Cloud SQL table to store chat history.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.ainit_chat_history_table

langchain_google_cloud_sql_pg.engine.PostgresEngine.ainit_checkpoint_table

ainit_checkpoint_table(
    table_name: str = "checkpoints", schema_name: str = "public"
) -> None

Create an PgSQL table to save checkpoint messages.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.ainit_checkpoint_table

langchain_google_cloud_sql_pg.engine.PostgresEngine.ainit_document_table

ainit_document_table(
    table_name: str,
    schema_name: str = "public",
    content_column: str = "page_content",
    metadata_columns: list[langchain_google_cloud_sql_pg.engine.Column] = [],
    metadata_json_column: str = "langchain_metadata",
    store_metadata: bool = True,
) -> None

Create a table for saving of langchain documents.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.ainit_document_table

langchain_google_cloud_sql_pg.engine.PostgresEngine.ainit_vectorstore_table

ainit_vectorstore_table(
    table_name: str,
    vector_size: int,
    schema_name: str = "public",
    content_column: str = "content",
    embedding_column: str = "embedding",
    metadata_columns: list[langchain_google_cloud_sql_pg.engine.Column] = [],
    metadata_json_column: str = "langchain_metadata",
    id_column: typing.Union[
        str, langchain_google_cloud_sql_pg.engine.Column
    ] = "langchain_id",
    overwrite_existing: bool = False,
    store_metadata: bool = True,
) -> None

Create a table for saving of vectors to be used with PostgresVectorStore.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.ainit_vectorstore_table

langchain_google_cloud_sql_pg.engine.PostgresEngine.close

close() -> None

Dispose of connection pool.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.close

langchain_google_cloud_sql_pg.engine.PostgresEngine.from_engine

from_engine(
    engine: sqlalchemy.ext.asyncio.engine.AsyncEngine,
    loop: typing.Optional[asyncio.events.AbstractEventLoop] = None,
) -> langchain_google_cloud_sql_pg.engine.PostgresEngine

Create an PostgresEngine instance from an AsyncEngine.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.from_engine

langchain_google_cloud_sql_pg.engine.PostgresEngine.from_engine_args

from_engine_args(
    url: str | sqlalchemy.engine.url.URL, **kwargs: typing.Any
) -> langchain_google_cloud_sql_pg.engine.PostgresEngine

Create an PostgresEngine instance from arguments.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.from_engine_args

langchain_google_cloud_sql_pg.engine.PostgresEngine.from_instance

from_instance(
    project_id: str,
    region: str,
    instance: str,
    database: str,
    user: typing.Optional[str] = None,
    password: typing.Optional[str] = None,
    ip_type: typing.Union[
        str, google.cloud.sql.connector.enums.IPTypes
    ] = IPTypes.PUBLIC,
    quota_project: typing.Optional[str] = None,
    iam_account_email: typing.Optional[str] = None,
    engine_args: typing.Mapping = {},
) -> langchain_google_cloud_sql_pg.engine.PostgresEngine

Create a PostgresEngine from a Postgres instance.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.from_instance

langchain_google_cloud_sql_pg.engine.PostgresEngine.init_chat_history_table

init_chat_history_table(table_name: str, schema_name: str = "public") -> None

Create a Cloud SQL table to store chat history.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.init_chat_history_table

langchain_google_cloud_sql_pg.engine.PostgresEngine.init_checkpoint_table

init_checkpoint_table(
    table_name: str = "checkpoints", schema_name: str = "public"
) -> None

Create Cloud SQL tables to store checkpoints.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.init_checkpoint_table

langchain_google_cloud_sql_pg.engine.PostgresEngine.init_document_table

init_document_table(
    table_name: str,
    schema_name: str = "public",
    content_column: str = "page_content",
    metadata_columns: list[langchain_google_cloud_sql_pg.engine.Column] = [],
    metadata_json_column: str = "langchain_metadata",
    store_metadata: bool = True,
) -> None

Create a table for saving of langchain documents.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.init_document_table

langchain_google_cloud_sql_pg.engine.PostgresEngine.init_vectorstore_table

init_vectorstore_table(
    table_name: str,
    vector_size: int,
    schema_name: str = "public",
    content_column: str = "content",
    embedding_column: str = "embedding",
    metadata_columns: list[langchain_google_cloud_sql_pg.engine.Column] = [],
    metadata_json_column: str = "langchain_metadata",
    id_column: typing.Union[
        str, langchain_google_cloud_sql_pg.engine.Column
    ] = "langchain_id",
    overwrite_existing: bool = False,
    store_metadata: bool = True,
) -> None

Create a table for saving of vectors to be used with PostgresVectorStore.

See more: langchain_google_cloud_sql_pg.engine.PostgresEngine.init_vectorstore_table

langchain_google_cloud_sql_pg.indexes.BaseIndex.index_options

index_options() -> str

Set index query options for vector store initialization.

See more: langchain_google_cloud_sql_pg.indexes.BaseIndex.index_options

langchain_google_cloud_sql_pg.indexes.DistanceStrategy._generate_next_value_

_generate_next_value_(start, count, last_values)

Generate the next value when not given.

See more: langchain_google_cloud_sql_pg.indexes.DistanceStrategy.generate_next_value

langchain_google_cloud_sql_pg.indexes.HNSWIndex.index_options

index_options() -> str

Set index query options for vector store initialization.

See more: langchain_google_cloud_sql_pg.indexes.HNSWIndex.index_options

langchain_google_cloud_sql_pg.indexes.HNSWQueryOptions.to_string

to_string()

Convert index attributes to string.

See more: langchain_google_cloud_sql_pg.indexes.HNSWQueryOptions.to_string

langchain_google_cloud_sql_pg.indexes.IVFFlatIndex.index_options

index_options() -> str

Set index query options for vector store initialization.

See more: langchain_google_cloud_sql_pg.indexes.IVFFlatIndex.index_options

langchain_google_cloud_sql_pg.indexes.IVFFlatQueryOptions.to_string

to_string()

Convert index attributes to string.

See more: langchain_google_cloud_sql_pg.indexes.IVFFlatQueryOptions.to_string

langchain_google_cloud_sql_pg.indexes.QueryOptions.to_string

to_string() -> str

Convert index attributes to string.

See more: langchain_google_cloud_sql_pg.indexes.QueryOptions.to_string