google-vertexai: added langchain_google_vertexai package

libs/partners/google-vertexai/.gitignore

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+__pycache__

libs/partners/google-vertexai/LICENSE

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+MIT License
+
+Copyright (c) 2023 LangChain, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

libs/partners/google-vertexai/Makefile

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+.PHONY: all format lint test tests integration_tests docker_tests help extended_tests
+
+# Default target executed when no arguments are given to make.
+all: help
+
+# Define a variable for the test file path.
+TEST_FILE ?= tests/unit_tests/
+
+test:
+	poetry run pytest $(TEST_FILE)
+
+tests:
+	poetry run pytest $(TEST_FILE)
+
+
+######################
+# LINTING AND FORMATTING
+######################
+
+# Define a variable for Python and notebook files.
+PYTHON_FILES=.
+MYPY_CACHE=.mypy_cache
+lint format: PYTHON_FILES=.
+lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/partners/google-vertexai --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$')
+lint_package: PYTHON_FILES=langchain_google_vertexai
+lint_tests: PYTHON_FILES=tests
+lint_tests: MYPY_CACHE=.mypy_cache_test
+
+lint lint_diff lint_package lint_tests:
+	poetry run ruff .
+	poetry run ruff format $(PYTHON_FILES) --diff
+	poetry run ruff --select I $(PYTHON_FILES)
+	mkdir $(MYPY_CACHE); poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+
+format format_diff:
+	poetry run ruff format $(PYTHON_FILES)
+	poetry run ruff --select I --fix $(PYTHON_FILES)
+
+spell_check:
+	poetry run codespell --toml pyproject.toml
+
+spell_fix:
+	poetry run codespell --toml pyproject.toml -w
+
+check_imports: $(shell find langchain_google_vertexai -name '*.py')
+	poetry run python ./scripts/check_imports.py $^
+
+######################
+# HELP
+######################
+
+help:
+	@echo '----'
+	@echo 'check_imports				- check imports'
+	@echo 'format                       - run code formatters'
+	@echo 'lint                         - run linters'
+	@echo 'test                         - run unit tests'
+	@echo 'tests                        - run unit tests'
+	@echo 'test TEST_FILE=<test_file>   - run all tests in file'

libs/partners/google-vertexai/README.md

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+# langchain-google-vertexai

libs/partners/google-vertexai/langchain_google_vertexai/__init__.py

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+from langchain_google_vertexai.chat_models import ChatVertexAI
+from langchain_google_vertexai.embeddings import VertexAIEmbeddings
+from langchain_google_vertexai.llms import VertexAI, VertexAIModelGarden
+
+__all__ = ["ChatVertexAI", "VertexAIEmbeddings", "VertexAI", "VertexAIModelGarden"]

libs/partners/google-vertexai/langchain_google_vertexai/_utils.py

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+"""Utilities to init Vertex AI."""
+from importlib import metadata
+from typing import Any, Callable, Optional, Union
+
+import google.api_core
+from google.api_core.gapic_v1.client_info import ClientInfo
+from google.cloud import storage  # type: ignore
+from langchain_core.callbacks import (
+    AsyncCallbackManagerForLLMRun,
+    CallbackManagerForLLMRun,
+)
+from langchain_core.language_models.llms import create_base_retry_decorator
+from vertexai.preview.generative_models import Image  # type: ignore
+
+
+def create_retry_decorator(
+    *,
+    max_retries: int = 1,
+    run_manager: Optional[
+        Union[AsyncCallbackManagerForLLMRun, CallbackManagerForLLMRun]
+    ] = None,
+) -> Callable[[Any], Any]:
+    """Creates a retry decorator for Vertex / Palm LLMs."""
+
+    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 get_client_info(module: Optional[str] = None) -> "ClientInfo":
+    r"""Returns 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
+    """
+    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:
+    """Loads im Image from GCS."""
+    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())
+
+
+def is_codey_model(model_name: str) -> bool:
+    """Returns True if the model name is a Codey model."""
+    return "code" in model_name
+
+
+def is_gemini_model(model_name: str) -> bool:
+    """Returns True if the model name is a Gemini model."""
+    return model_name is not None and "gemini" in model_name