initial commit

venv/Lib/site-packages/langchain_community/utilities/vertexai.py

@@ -0,0 +1,125 @@
+"""Utilities to init Vertex AI."""
+
+from importlib import metadata
+from typing import TYPE_CHECKING, Any, Callable, Optional, Union
+
+from langchain_core.callbacks import (
+    AsyncCallbackManagerForLLMRun,
+    CallbackManagerForLLMRun,
+)
+from langchain_core.language_models.llms import BaseLLM, create_base_retry_decorator
+
+if TYPE_CHECKING:
+    from google.api_core.gapic_v1.client_info import ClientInfo
+    from google.auth.credentials import Credentials
+    from vertexai.preview.generative_models import Image
+
+
+def create_retry_decorator(
+    llm: BaseLLM,
+    *,
+    max_retries: int = 1,
+    run_manager: Optional[
+        Union[AsyncCallbackManagerForLLMRun, CallbackManagerForLLMRun]
+    ] = None,
+) -> Callable[[Any], Any]:
+    """Create a retry decorator for Vertex / Palm LLMs."""
+    import google.api_core
+
+    errors = [
+        google.api_core.exceptions.ResourceExhausted,
+        google.api_core.exceptions.ServiceUnavailable,
+        google.api_core.exceptions.Aborted,
+        google.api_core.exceptions.DeadlineExceeded,
+        google.api_core.exceptions.GoogleAPIError,
+    ]
+    decorator = create_base_retry_decorator(
+        error_types=errors, max_retries=max_retries, run_manager=run_manager
+    )
+    return decorator
+
+
+def raise_vertex_import_error(minimum_expected_version: str = "1.38.0") -> None:
+    """Raise ImportError related to Vertex SDK being not available.
+
+    Args:
+        minimum_expected_version: The lowest expected version of the SDK.
+    Raises:
+        ImportError: an ImportError that mentions a required version of the SDK.
+    """
+    raise ImportError(
+        "Please, install or upgrade the google-cloud-aiplatform library: "
+        f"pip install google-cloud-aiplatform>={minimum_expected_version}"
+    )
+
+
+def init_vertexai(
+    project: Optional[str] = None,
+    location: Optional[str] = None,
+    credentials: Optional["Credentials"] = None,
+) -> None:
+    """Init Vertex AI.
+
+    Args:
+        project: The default GCP project to use when making Vertex API calls.
+        location: The default location to use when making API calls.
+        credentials: The default custom
+            credentials to use when making API calls. If not provided credentials
+            will be ascertained from the environment.
+
+    Raises:
+        ImportError: If importing vertexai SDK did not succeed.
+    """
+    try:
+        import vertexai
+    except ImportError:
+        raise_vertex_import_error()
+
+    vertexai.init(
+        project=project,
+        location=location,
+        credentials=credentials,
+    )
+
+
+def get_client_info(module: Optional[str] = None) -> "ClientInfo":
+    r"""Return a custom user agent header.
+
+    Args:
+        module (Optional[str]):
+            Optional. The module for a custom user agent header.
+    Returns:
+        google.api_core.gapic_v1.client_info.ClientInfo
+    """
+    try:
+        from google.api_core.gapic_v1.client_info import ClientInfo
+    except ImportError as exc:
+        raise ImportError(
+            "Could not import ClientInfo. Please, install it with "
+            "pip install google-api-core"
+        ) from exc
+
+    langchain_version = metadata.version("langchain")
+    client_library_version = (
+        f"{langchain_version}-{module}" if module else langchain_version
+    )
+    return ClientInfo(
+        client_library_version=client_library_version,
+        user_agent=f"langchain/{client_library_version}",
+    )
+
+
+def load_image_from_gcs(path: str, project: Optional[str] = None) -> "Image":
+    """Load an image from Google Cloud Storage."""
+    try:
+        from google.cloud import storage
+    except ImportError:
+        raise ImportError("Could not import google-cloud-storage python package.")
+    from vertexai.preview.generative_models import Image
+
+    gcs_client = storage.Client(project=project)
+    pieces = path.split("/")
+    blobs = list(gcs_client.list_blobs(pieces[2], prefix="/".join(pieces[3:])))
+    if len(blobs) > 1:
+        raise ValueError(f"Found more than one candidate for {path}!")
+    return Image.from_bytes(blobs[0].download_as_bytes())