From 405d111da6b34dea1bb19a2b2b121588135d14c6 Mon Sep 17 00:00:00 2001 From: William FH <13333726+hinthornw@users.noreply.github.com> Date: Wed, 13 Dec 2023 11:57:59 -0800 Subject: [PATCH] [Partner] Add langchain-google-genai package (gemini) (#14621) Add a new ChatGoogleGenerativeAI class in a `langchain-google-genai` package. Still todo: add a deprecation warning in PALM --------- Co-authored-by: Erick Friis Co-authored-by: Leonid Kuligin Co-authored-by: Bagatur --- .github/workflows/_release.yml | 1 + libs/partners/google-genai/.gitignore | 1 + libs/partners/google-genai/LICENSE | 21 + libs/partners/google-genai/Makefile | 61 + libs/partners/google-genai/README.md | 58 + .../langchain_google_genai/__init__.py | 3 + .../langchain_google_genai/chat_models.py | 632 +++++++++ libs/partners/google-genai/poetry.lock | 1232 +++++++++++++++++ libs/partners/google-genai/pyproject.toml | 97 ++ .../google-genai/scripts/check_imports.py | 17 + .../google-genai/scripts/check_pydantic.sh | 27 + .../google-genai/scripts/lint_imports.sh | 17 + libs/partners/google-genai/tests/__init__.py | 0 .../tests/integration_tests/__init__.py | 0 .../integration_tests/test_chat_models.py | 149 ++ .../tests/integration_tests/test_compile.py | 7 + .../google-genai/tests/unit_tests/__init__.py | 0 .../tests/unit_tests/test_chat_models.py | 24 + .../tests/unit_tests/test_imports.py | 9 + 19 files changed, 2356 insertions(+) create mode 100644 libs/partners/google-genai/.gitignore create mode 100644 libs/partners/google-genai/LICENSE create mode 100644 libs/partners/google-genai/Makefile create mode 100644 libs/partners/google-genai/README.md create mode 100644 libs/partners/google-genai/langchain_google_genai/__init__.py create mode 100644 libs/partners/google-genai/langchain_google_genai/chat_models.py create mode 100644 libs/partners/google-genai/poetry.lock create mode 100644 libs/partners/google-genai/pyproject.toml create mode 100644 libs/partners/google-genai/scripts/check_imports.py create mode 100755 libs/partners/google-genai/scripts/check_pydantic.sh create mode 100755 libs/partners/google-genai/scripts/lint_imports.sh create mode 100644 libs/partners/google-genai/tests/__init__.py create mode 100644 libs/partners/google-genai/tests/integration_tests/__init__.py create mode 100644 libs/partners/google-genai/tests/integration_tests/test_chat_models.py create mode 100644 libs/partners/google-genai/tests/integration_tests/test_compile.py create mode 100644 libs/partners/google-genai/tests/unit_tests/__init__.py create mode 100644 libs/partners/google-genai/tests/unit_tests/test_chat_models.py create mode 100644 libs/partners/google-genai/tests/unit_tests/test_imports.py diff --git a/.github/workflows/_release.yml b/.github/workflows/_release.yml index 908fb770a8f..afd86413c1f 100644 --- a/.github/workflows/_release.yml +++ b/.github/workflows/_release.yml @@ -18,6 +18,7 @@ on: - libs/core - libs/experimental - libs/community + - libs/partners/google-genai env: PYTHON_VERSION: "3.10" diff --git a/libs/partners/google-genai/.gitignore b/libs/partners/google-genai/.gitignore new file mode 100644 index 00000000000..bee8a64b79a --- /dev/null +++ b/libs/partners/google-genai/.gitignore @@ -0,0 +1 @@ +__pycache__ diff --git a/libs/partners/google-genai/LICENSE b/libs/partners/google-genai/LICENSE new file mode 100644 index 00000000000..426b6509034 --- /dev/null +++ b/libs/partners/google-genai/LICENSE @@ -0,0 +1,21 @@ +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. diff --git a/libs/partners/google-genai/Makefile b/libs/partners/google-genai/Makefile new file mode 100644 index 00000000000..132eb9eb898 --- /dev/null +++ b/libs/partners/google-genai/Makefile @@ -0,0 +1,61 @@ +.PHONY: all format lint test tests integration_tests help + +# 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) + +check_imports: $(shell find langchain_google_genai -name '*.py') + poetry run python ./scripts/check_imports.py $^ + +integration_tests: + poetry run pytest tests/integration_tests + +###################### +# LINTING AND FORMATTING +###################### + +# Define a variable for Python and notebook files. +PYTHON_FILES=. +MYPY_CACHE=.mypy_cache +lint format: PYTHON_FILES=. +lint_diff format_diff: PYTHON_FILES=$(shell git diff --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$') +lint_package: PYTHON_FILES=langchain_google_genai +lint_tests: PYTHON_FILES=tests +lint_tests: MYPY_CACHE=.mypy_cache_test + +lint lint_diff lint_package lint_tests: + ./scripts/check_pydantic.sh . + ./scripts/lint_imports.sh + poetry run ruff . + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff + [ "$(PYTHON_FILES)" = "" ] || poetry run mypy $(PYTHON_FILES) + +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 + +###################### +# HELP +###################### + +help: + @echo '----' + @echo 'format - run code formatters' + @echo 'lint - run linters' + @echo 'test - run unit tests' + @echo 'tests - run unit tests' + @echo 'test TEST_FILE= - run all tests in file' diff --git a/libs/partners/google-genai/README.md b/libs/partners/google-genai/README.md new file mode 100644 index 00000000000..578645a9d7c --- /dev/null +++ b/libs/partners/google-genai/README.md @@ -0,0 +1,58 @@ +# langchain-google-genai + +This package contains the LangChain integrations for Gemini through their generative-ai SDK. + +## Installation + +```python +pip install -U langchain-google-genai +``` + +## Chat Models + +This package contains the `ChatGoogleGenerativeAI` class, which is the recommended way to interface with the Google Gemini series of models. + +To use, install the requirements, and configure your environment. + +```bash +export GOOGLE_API_KEY=your-api-key +``` + +Then initialize + +```python +from langchain_google_genai import ChatGoogleGenerativeAI + +llm = ChatGoogleGenerativeAI(model="gemini-pro") +llm.invoke("Sing a ballad of LangChain.") +``` + +#### Multimodal inputs + +Gemini vision model supports image inputs when providing a single chat message. Example: + +``` +from langchain_core.messages import HumanMessage +from langchain_google_genai import ChatGoogleGenerativeAI + +llm = ChatGoogleGenerativeAI(model="gemini-pro-vision") +# example +message = HumanMessage( + content=[ + { + "type": "text", + "text": "What's in this image?", + }, # You can optionally provide text parts + {"type": "image_url", "image_url": "https://picsum.photos/seed/picsum/200/300"}, + ] +) +llm.invoke([message]) +``` + +The value of `image_url` can be any of the following: + +- A public image URL +- An accessible gcs file (e.g., "gcs://path/to/file.png") +- A local file path +- A base64 encoded image (e.g., `data:image/png;base64,abcd124`) +- A PIL image diff --git a/libs/partners/google-genai/langchain_google_genai/__init__.py b/libs/partners/google-genai/langchain_google_genai/__init__.py new file mode 100644 index 00000000000..5f3d1369295 --- /dev/null +++ b/libs/partners/google-genai/langchain_google_genai/__init__.py @@ -0,0 +1,3 @@ +from langchain_google_genai.chat_models import ChatGoogleGenerativeAI + +__all__ = ["ChatGoogleGenerativeAI"] diff --git a/libs/partners/google-genai/langchain_google_genai/chat_models.py b/libs/partners/google-genai/langchain_google_genai/chat_models.py new file mode 100644 index 00000000000..9d22411a6e2 --- /dev/null +++ b/libs/partners/google-genai/langchain_google_genai/chat_models.py @@ -0,0 +1,632 @@ +from __future__ import annotations + +import base64 +import logging +import os +from io import BytesIO +from typing import ( + TYPE_CHECKING, + Any, + AsyncIterator, + Callable, + Dict, + Iterator, + List, + Mapping, + Optional, + Sequence, + Tuple, + Type, + Union, + cast, +) +from urllib.parse import urlparse + +import requests +from langchain_core.callbacks.manager import ( + AsyncCallbackManagerForLLMRun, + CallbackManagerForLLMRun, +) +from langchain_core.language_models.chat_models import BaseChatModel +from langchain_core.messages import ( + AIMessage, + AIMessageChunk, + BaseMessage, + ChatMessage, + ChatMessageChunk, + HumanMessage, + HumanMessageChunk, +) +from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult +from langchain_core.pydantic_v1 import Field, root_validator +from langchain_core.utils import get_from_dict_or_env +from tenacity import ( + before_sleep_log, + retry, + retry_if_exception_type, + stop_after_attempt, + wait_exponential, +) + +logger = logging.getLogger(__name__) + +if TYPE_CHECKING: + # TODO: remove ignore once the google package is published with types + import google.generativeai as genai # type: ignore[import] +IMAGE_TYPES: Tuple = () +try: + import PIL + from PIL.Image import Image + + IMAGE_TYPES = IMAGE_TYPES + (Image,) +except ImportError: + PIL = None # type: ignore + Image = None # type: ignore + + +class ChatGoogleGenerativeAIError(Exception): + """ + Custom exception class for errors associated with the `Google GenAI` API. + + This exception is raised when there are specific issues related to the + Google genai API usage in the ChatGoogleGenerativeAI class, such as unsupported + message types or roles. + """ + + +def _create_retry_decorator() -> Callable[[Any], Any]: + """ + Creates and returns a preconfigured tenacity retry decorator. + + The retry decorator is configured to handle specific Google API exceptions + such as ResourceExhausted and ServiceUnavailable. It uses an exponential + backoff strategy for retries. + + Returns: + Callable[[Any], Any]: A retry decorator configured for handling specific + Google API exceptions. + """ + import google.api_core.exceptions + + multiplier = 2 + min_seconds = 1 + max_seconds = 60 + max_retries = 10 + + return retry( + reraise=True, + stop=stop_after_attempt(max_retries), + wait=wait_exponential(multiplier=multiplier, min=min_seconds, max=max_seconds), + retry=( + retry_if_exception_type(google.api_core.exceptions.ResourceExhausted) + | retry_if_exception_type(google.api_core.exceptions.ServiceUnavailable) + | retry_if_exception_type(google.api_core.exceptions.GoogleAPIError) + ), + before_sleep=before_sleep_log(logger, logging.WARNING), + ) + + +def chat_with_retry(*, generation_method: Callable, **kwargs: Any) -> Any: + """ + Executes a chat generation method with retry logic using tenacity. + + This function is a wrapper that applies a retry mechanism to a provided + chat generation function. It is useful for handling intermittent issues + like network errors or temporary service unavailability. + + Args: + generation_method (Callable): The chat generation method to be executed. + **kwargs (Any): Additional keyword arguments to pass to the generation method. + + Returns: + Any: The result from the chat generation method. + """ + retry_decorator = _create_retry_decorator() + from google.api_core.exceptions import InvalidArgument # type: ignore + + @retry_decorator + def _chat_with_retry(**kwargs: Any) -> Any: + try: + return generation_method(**kwargs) + except InvalidArgument as e: + # Do not retry for these errors. + raise ChatGoogleGenerativeAIError( + f"Invalid argument provided to Gemini: {e}" + ) from e + except Exception as e: + raise e + + return _chat_with_retry(**kwargs) + + +async def achat_with_retry(*, generation_method: Callable, **kwargs: Any) -> Any: + """ + Executes a chat generation method with retry logic using tenacity. + + This function is a wrapper that applies a retry mechanism to a provided + chat generation function. It is useful for handling intermittent issues + like network errors or temporary service unavailability. + + Args: + generation_method (Callable): The chat generation method to be executed. + **kwargs (Any): Additional keyword arguments to pass to the generation method. + + Returns: + Any: The result from the chat generation method. + """ + retry_decorator = _create_retry_decorator() + from google.api_core.exceptions import InvalidArgument # type: ignore + + @retry_decorator + async def _achat_with_retry(**kwargs: Any) -> Any: + try: + return await generation_method(**kwargs) + except InvalidArgument as e: + # Do not retry for these errors. + raise ChatGoogleGenerativeAIError( + f"Invalid argument provided to Gemini: {e}" + ) from e + except Exception as e: + raise e + + return await _achat_with_retry(**kwargs) + + +def _get_role(message: BaseMessage) -> str: + if isinstance(message, ChatMessage): + if message.role not in ("user", "model"): + raise ChatGoogleGenerativeAIError( + "Gemini only supports user and model roles when" + " providing it with Chat messages." + ) + return message.role + elif isinstance(message, HumanMessage): + return "user" + elif isinstance(message, AIMessage): + return "model" + else: + # TODO: Gemini doesn't seem to have a concept of system messages yet. + raise ChatGoogleGenerativeAIError( + f"Message of '{message.type}' type not supported by Gemini." + " Please only provide it with Human or AI (user/assistant) messages." + ) + + +def _is_openai_parts_format(part: dict) -> bool: + return "type" in part + + +def _is_vision_model(model: str) -> bool: + return "vision" in model + + +def _is_url(s: str) -> bool: + try: + result = urlparse(s) + return all([result.scheme, result.netloc]) + except Exception as e: + logger.debug(f"Unable to parse URL: {e}") + return False + + +def _is_b64(s: str) -> bool: + return s.startswith("data:image") + + +def _load_image_from_gcs(path: str, project: Optional[str] = None) -> Image: + try: + from google.cloud import storage # type: ignore[attr-defined] + except ImportError: + raise ImportError( + "google-cloud-storage is required to load images from GCS." + " Install it with `pip install google-cloud-storage`" + ) + if PIL is None: + raise ImportError( + "PIL is required to load images. Please install it " + "with `pip install pillow`" + ) + + 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}!") + img_bytes = blobs[0].download_as_bytes() + return PIL.Image.open(BytesIO(img_bytes)) + + +def _url_to_pil(image_source: str) -> Image: + if PIL is None: + raise ImportError( + "PIL is required to load images. Please install it " + "with `pip install pillow`" + ) + try: + if isinstance(image_source, IMAGE_TYPES): + return image_source # type: ignore[return-value] + elif _is_url(image_source): + if image_source.startswith("gs://"): + return _load_image_from_gcs(image_source) + response = requests.get(image_source) + response.raise_for_status() + return PIL.Image.open(BytesIO(response.content)) + elif _is_b64(image_source): + _, encoded = image_source.split(",", 1) + data = base64.b64decode(encoded) + return PIL.Image.open(BytesIO(data)) + elif os.path.exists(image_source): + return PIL.Image.open(image_source) + else: + raise ValueError( + "The provided string is not a valid URL, base64, or file path." + ) + except Exception as e: + raise ValueError(f"Unable to process the provided image source: {e}") + + +def _convert_to_parts( + content: Sequence[Union[str, dict]], +) -> List[genai.types.PartType]: + """Converts a list of LangChain messages into a google parts.""" + import google.generativeai as genai + + parts = [] + for part in content: + if isinstance(part, str): + parts.append(genai.types.PartDict(text=part, inline_data=None)) + elif isinstance(part, Mapping): + # OpenAI Format + if _is_openai_parts_format(part): + if part["type"] == "text": + parts.append({"text": part["text"]}) + elif part["type"] == "image_url": + img_url = part["image_url"] + if isinstance(img_url, dict): + if "url" not in img_url: + raise ValueError( + f"Unrecognized message image format: {img_url}" + ) + img_url = img_url["url"] + parts.append({"inline_data": _url_to_pil(img_url)}) + else: + raise ValueError(f"Unrecognized message part type: {part['type']}") + else: + # Yolo + logger.warning( + "Unrecognized message part format. Assuming it's a text part." + ) + parts.append(part) + else: + # TODO: Maybe some of Google's native stuff + # would hit this branch. + raise ChatGoogleGenerativeAIError( + "Gemini only supports text and inline_data parts." + ) + return parts + + +def _messages_to_genai_contents( + input_messages: Sequence[BaseMessage], +) -> List[genai.types.ContentDict]: + """Converts a list of messages into a Gemini API google content dicts.""" + + messages: List[genai.types.MessageDict] = [] + for i, message in enumerate(input_messages): + role = _get_role(message) + if isinstance(message.content, str): + parts = [message.content] + else: + parts = _convert_to_parts(message.content) + messages.append({"role": role, "parts": parts}) + if i > 0: + # Cannot have multiple messages from the same role in a row. + if role == messages[-2]["role"]: + raise ChatGoogleGenerativeAIError( + "Cannot have multiple messages from the same role in a row." + " Consider merging them into a single message with multiple" + f" parts.\nReceived: {messages}" + ) + return messages + + +def _parts_to_content(parts: List[genai.types.PartType]) -> Union[List[dict], str]: + """Converts a list of Gemini API Part objects into a list of LangChain messages.""" + if len(parts) == 1 and parts[0].text is not None and not parts[0].inline_data: + # Simple text response. The typical response + return parts[0].text + elif not parts: + logger.warning("Gemini produced an empty response.") + return "" + messages = [] + for part in parts: + if part.text is not None: + messages.append( + { + "type": "text", + "text": part.text, + } + ) + else: + # TODO: Handle inline_data if that's a thing? + raise ChatGoogleGenerativeAIError(f"Unexpected part type. {part}") + return messages + + +def _response_to_result( + response: genai.types.GenerateContentResponse, + ai_msg_t: Type[BaseMessage] = AIMessage, + human_msg_t: Type[BaseMessage] = HumanMessage, + chat_msg_t: Type[BaseMessage] = ChatMessage, + generation_t: Type[ChatGeneration] = ChatGeneration, +) -> ChatResult: + """Converts a PaLM API response into a LangChain ChatResult.""" + llm_output = {} + if response.prompt_feedback: + try: + prompt_feedback = type(response.prompt_feedback).to_dict( + response.prompt_feedback, use_integers_for_enums=False + ) + llm_output["prompt_feedback"] = prompt_feedback + except Exception as e: + logger.debug(f"Unable to convert prompt_feedback to dict: {e}") + + generations: List[ChatGeneration] = [] + + role_map = { + "model": ai_msg_t, + "user": human_msg_t, + } + for candidate in response.candidates: + content = candidate.content + parts_content = _parts_to_content(content.parts) + if content.role not in role_map: + logger.warning( + f"Unrecognized role: {content.role}. Treating as a ChatMessage." + ) + msg = chat_msg_t(content=parts_content, role=content.role) + else: + msg = role_map[content.role](content=parts_content) + generation_info = {} + if candidate.finish_reason: + generation_info["finish_reason"] = candidate.finish_reason.name + if candidate.safety_ratings: + generation_info["safety_ratings"] = [ + type(rating).to_dict(rating) for rating in candidate.safety_ratings + ] + generations.append(generation_t(message=msg, generation_info=generation_info)) + if not response.candidates: + # Likely a "prompt feedback" violation (e.g., toxic input) + # Raising an error would be different than how OpenAI handles it, + # so we'll just log a warning and continue with an empty message. + logger.warning( + "Gemini produced an empty response. Continuing with empty message\n" + f"Feedback: {response.prompt_feedback}" + ) + generations = [generation_t(message=ai_msg_t(content=""), generation_info={})] + return ChatResult(generations=generations, llm_output=llm_output) + + +class ChatGoogleGenerativeAI(BaseChatModel): + """`Google Generative AI` Chat models API. + + To use you must have the google.generativeai Python package installed and + either: + + 1. The ``GOOGLE_API_KEY``` environment variable set with your API key, or + 2. Pass your API key using the google_api_key kwarg to the ChatGoogle + constructor. + + Example: + .. code-block:: python + + from langchain_google_genai import ChatGoogleGenerativeAI + chat = ChatGoogleGenerativeAI(model="gemini-pro") + chat.invoke("Write me a ballad about LangChain") + + """ + + model: str = Field( + ..., + description="""The name of the model to use. +Supported examples: + - gemini-pro""", + ) + max_output_tokens: int = Field(default=None, description="Max output tokens") + + client: Any #: :meta private: + google_api_key: Optional[str] = None + temperature: Optional[float] = None + """Run inference with this temperature. Must by in the closed + interval [0.0, 1.0].""" + top_k: Optional[int] = None + """Decode using top-k sampling: consider the set of top_k most probable tokens. + Must be positive.""" + top_p: Optional[int] = None + """The maximum cumulative probability of tokens to consider when sampling. + + The model uses combined Top-k and nucleus sampling. + + Tokens are sorted based on their assigned probabilities so + that only the most likely tokens are considered. Top-k + sampling directly limits the maximum number of tokens to + consider, while Nucleus sampling limits number of tokens + based on the cumulative probability. + + Note: The default value varies by model, see the + `Model.top_p` attribute of the `Model` returned the + `genai.get_model` function. + """ + n: int = Field(default=1, alias="candidate_count") + """Number of chat completions to generate for each prompt. Note that the API may + not return the full n completions if duplicates are generated.""" + + _generative_model: Any #: :meta private: + + class Config: + allow_population_by_field_name = True + + @property + def lc_secrets(self) -> Dict[str, str]: + return {"google_api_key": "GOOGLE_API_KEY"} + + @property + def _llm_type(self) -> str: + return "chat-google-generative-ai" + + @property + def _is_geminiai(self) -> bool: + return self.model is not None and "gemini" in self.model + + @classmethod + def is_lc_serializable(self) -> bool: + return True + + @root_validator() + def validate_environment(cls, values: Dict) -> Dict: + google_api_key = get_from_dict_or_env( + values, "google_api_key", "GOOGLE_API_KEY" + ) + try: + import google.generativeai as genai + + genai.configure(api_key=google_api_key) + except ImportError: + raise ChatGoogleGenerativeAIError( + "Could not import google.generativeai python package. " + "Please install it with `pip install google-generativeai`" + ) + + values["client"] = genai + if ( + values.get("temperature") is not None + and not 0 <= values["temperature"] <= 1 + ): + raise ValueError("temperature must be in the range [0.0, 1.0]") + + if values.get("top_p") is not None and not 0 <= values["top_p"] <= 1: + raise ValueError("top_p must be in the range [0.0, 1.0]") + + if values.get("top_k") is not None and values["top_k"] <= 0: + raise ValueError("top_k must be positive") + model = values["model"] + values["_generative_model"] = genai.GenerativeModel(model_name=model) + return values + + @property + def _identifying_params(self) -> Dict[str, Any]: + """Get the identifying parameters.""" + return { + "model": self.model, + "temperature": self.temperature, + "top_k": self.top_k, + "n": self.n, + } + + @property + def _generation_method(self) -> Callable: + return self._generative_model.generate_content + + @property + def _async_generation_method(self) -> Callable: + return self._generative_model.generate_content_async + + def _prepare_params( + self, messages: Sequence[BaseMessage], stop: Optional[List[str]], **kwargs: Any + ) -> Dict[str, Any]: + contents = _messages_to_genai_contents(messages) + gen_config = { + k: v + for k, v in { + "candidate_count": self.n, + "temperature": self.temperature, + "stop_sequences": stop, + "max_output_tokens": self.max_output_tokens, + "top_k": self.top_k, + "top_p": self.top_p, + }.items() + if v is not None + } + if "generation_config" in kwargs: + gen_config = {**gen_config, **kwargs.pop("generation_config")} + params = {"generation_config": gen_config, "contents": contents, **kwargs} + return params + + def _generate( + self, + messages: List[BaseMessage], + stop: Optional[List[str]] = None, + run_manager: Optional[CallbackManagerForLLMRun] = None, + **kwargs: Any, + ) -> ChatResult: + params = self._prepare_params(messages, stop, **kwargs) + response: genai.types.GenerateContentResponse = chat_with_retry( + **params, + generation_method=self._generation_method, + ) + return _response_to_result(response) + + async def _agenerate( + self, + messages: List[BaseMessage], + stop: Optional[List[str]] = None, + run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, + **kwargs: Any, + ) -> ChatResult: + params = self._prepare_params(messages, stop, **kwargs) + response: genai.types.GenerateContentResponse = await achat_with_retry( + **params, + generation_method=self._async_generation_method, + ) + return _response_to_result(response) + + def _stream( + self, + messages: List[BaseMessage], + stop: Optional[List[str]] = None, + run_manager: Optional[CallbackManagerForLLMRun] = None, + **kwargs: Any, + ) -> Iterator[ChatGenerationChunk]: + params = self._prepare_params(messages, stop, **kwargs) + response: genai.types.GenerateContentResponse = chat_with_retry( + **params, + generation_method=self._generation_method, + stream=True, + ) + for chunk in response: + _chat_result = _response_to_result( + chunk, + ai_msg_t=AIMessageChunk, + human_msg_t=HumanMessageChunk, + chat_msg_t=ChatMessageChunk, + generation_t=ChatGenerationChunk, + ) + gen = cast(ChatGenerationChunk, _chat_result.generations[0]) + yield gen + if run_manager: + run_manager.on_llm_new_token(gen.text) + + async def _astream( + self, + messages: List[BaseMessage], + stop: Optional[List[str]] = None, + run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, + **kwargs: Any, + ) -> AsyncIterator[ChatGenerationChunk]: + params = self._prepare_params(messages, stop, **kwargs) + async for chunk in await achat_with_retry( + **params, + generation_method=self._async_generation_method, + stream=True, + ): + _chat_result = _response_to_result( + chunk, + ai_msg_t=AIMessageChunk, + human_msg_t=HumanMessageChunk, + chat_msg_t=ChatMessageChunk, + generation_t=ChatGenerationChunk, + ) + gen = cast(ChatGenerationChunk, _chat_result.generations[0]) + yield gen + if run_manager: + await 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b/libs/partners/google-genai/pyproject.toml @@ -0,0 +1,97 @@ +[tool.poetry] +name = "langchain-google-genai" +version = "0.0.1" +description = "An integration package connecting Google's genai package and LangChain" +authors = [] +readme = "README.md" + +[tool.poetry.dependencies] +python = ">=3.9,<4.0" +langchain-core = "^0.1" +google-generativeai = "^0.3.1" + +[tool.poetry.group.test] +optional = true + +[tool.poetry.group.test.dependencies] +pytest = "^7.3.0" +freezegun = "^1.2.2" +pytest-mock = "^3.10.0" +syrupy = "^4.0.2" +pytest-watcher = "^0.3.4" +pytest-asyncio = "^0.21.1" +langchain-core = {path = "../../core", develop = true} + +[tool.poetry.group.codespell] +optional = true + +[tool.poetry.group.codespell.dependencies] +codespell = "^2.2.0" + +[tool.poetry.group.test_integration] +optional = true + +[tool.poetry.group.test_integration.dependencies] + +[tool.poetry.group.lint] +optional = true + +[tool.poetry.group.lint.dependencies] +ruff = "^0.1.5" + +[tool.poetry.group.typing.dependencies] +mypy = "^0.991" +langchain-core = {path = "../../core", develop = true} +types-requests = "^2.28.11.5" +types-google-cloud-ndb = "^2.2.0.1" +types-pillow = "^10.1.0.2" + +[tool.poetry.group.dev] +optional = true + +[tool.poetry.group.dev.dependencies] +langchain-core = {path = "../../core", develop = true} +pillow = "^10.1.0" +types-requests = "^2.31.0.10" +types-pillow = "^10.1.0.2" +types-google-cloud-ndb = "^2.2.0.1" + +[tool.ruff] +select = [ + "E", # pycodestyle + "F", # pyflakes + "I", # isort +] + +[tool.mypy] +disallow_untyped_defs = "True" +exclude = ["notebooks", "examples", "example_data", "langchain_core/pydantic"] + +[tool.coverage.run] +omit = [ + "tests/*", +] + +[build-system] +requires = ["poetry-core>=1.0.0"] +build-backend = "poetry.core.masonry.api" + +[tool.pytest.ini_options] +# --strict-markers will raise errors on unknown marks. +# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks +# +# https://docs.pytest.org/en/7.1.x/reference/reference.html +# --strict-config any warnings encountered while parsing the `pytest` +# section of the configuration file raise errors. +# +# https://github.com/tophat/syrupy +# --snapshot-warn-unused Prints a warning on unused snapshots rather than fail the test suite. +addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5" +# Registering custom markers. +# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers +markers = [ + "requires: mark tests as requiring a specific library", + "asyncio: mark tests as requiring asyncio", + "compile: mark placeholder test used to compile integration tests without running them", +] +asyncio_mode = "auto" diff --git a/libs/partners/google-genai/scripts/check_imports.py b/libs/partners/google-genai/scripts/check_imports.py new file mode 100644 index 00000000000..fd21a4975b7 --- /dev/null +++ b/libs/partners/google-genai/scripts/check_imports.py @@ -0,0 +1,17 @@ +import sys +import traceback +from importlib.machinery import SourceFileLoader + +if __name__ == "__main__": + files = sys.argv[1:] + has_failure = False + for file in files: + try: + SourceFileLoader("x", file).load_module() + except Exception: + has_faillure = True + print(file) + traceback.print_exc() + print() + + sys.exit(1 if has_failure else 0) diff --git a/libs/partners/google-genai/scripts/check_pydantic.sh b/libs/partners/google-genai/scripts/check_pydantic.sh new file mode 100755 index 00000000000..06b5bb81ae2 --- /dev/null +++ b/libs/partners/google-genai/scripts/check_pydantic.sh @@ -0,0 +1,27 @@ +#!/bin/bash +# +# This script searches for lines starting with "import pydantic" or "from pydantic" +# in tracked files within a Git repository. +# +# Usage: ./scripts/check_pydantic.sh /path/to/repository + +# Check if a path argument is provided +if [ $# -ne 1 ]; then + echo "Usage: $0 /path/to/repository" + exit 1 +fi + +repository_path="$1" + +# Search for lines matching the pattern within the specified repository +result=$(git -C "$repository_path" grep -E '^import pydantic|^from pydantic') + +# Check if any matching lines were found +if [ -n "$result" ]; then + echo "ERROR: The following lines need to be updated:" + echo "$result" + echo "Please replace the code with an import from langchain_core.pydantic_v1." + echo "For example, replace 'from pydantic import BaseModel'" + echo "with 'from langchain_core.pydantic_v1 import BaseModel'" + exit 1 +fi diff --git a/libs/partners/google-genai/scripts/lint_imports.sh b/libs/partners/google-genai/scripts/lint_imports.sh new file mode 100755 index 00000000000..695613c7ba8 --- /dev/null +++ b/libs/partners/google-genai/scripts/lint_imports.sh @@ -0,0 +1,17 @@ +#!/bin/bash + +set -eu + +# Initialize a variable to keep track of errors +errors=0 + +# make sure not importing from langchain or langchain_experimental +git --no-pager grep '^from langchain\.' . && errors=$((errors+1)) +git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1)) + +# Decide on an exit status based on the errors +if [ "$errors" -gt 0 ]; then + exit 1 +else + exit 0 +fi diff --git a/libs/partners/google-genai/tests/__init__.py b/libs/partners/google-genai/tests/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/libs/partners/google-genai/tests/integration_tests/__init__.py b/libs/partners/google-genai/tests/integration_tests/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/libs/partners/google-genai/tests/integration_tests/test_chat_models.py b/libs/partners/google-genai/tests/integration_tests/test_chat_models.py new file mode 100644 index 00000000000..9436c5e2529 --- /dev/null +++ b/libs/partners/google-genai/tests/integration_tests/test_chat_models.py @@ -0,0 +1,149 @@ +"""Test ChatGoogleGenerativeAI chat model.""" +import pytest +from langchain_core.messages import AIMessage, HumanMessage + +from langchain_google_genai.chat_models import ( + ChatGoogleGenerativeAI, + ChatGoogleGenerativeAIError, +) + +_MODEL = "gemini-pro" # TODO: Use nano when it's available. +_VISION_MODEL = "gemini-pro-vision" +_B64_string = """iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAIAAAAC64paAAABhGlDQ1BJQ0MgUHJvZmlsZQAAeJx9kT1Iw0AcxV8/xCIVQTuIKGSoTi2IijhqFYpQIdQKrTqYXPoFTRqSFBdHwbXg4Mdi1cHFWVcHV0EQ/ABxdXFSdJES/5cUWsR4cNyPd/ced+8Af6PCVDM4DqiaZaSTCSGbWxW6XxHECPoRQ0hipj4niil4jq97+Ph6F+dZ3uf+HL1K3mSATyCeZbphEW8QT29aOud94ggrSQrxOXHMoAsSP3JddvmNc9FhP8+MGJn0PHGEWCh2sNzBrGSoxFPEUUXVKN+fdVnhvMVZrdRY6578heG8trLMdZrDSGIRSxAhQEYNZVRgIU6rRoqJNO0nPPxDjl8kl0yuMhg5FlCFCsnxg//B727NwuSEmxROAF0vtv0xCnTvAs26bX8f23bzBAg8A1da219tADOfpNfbWvQI6NsGLq7bmrwHXO4Ag0+6ZEiOFKDpLxSA9zP6phwwcAv0rLm9tfZx+gBkqKvUDXBwCIwVKXvd492hzt7+PdPq7wdzbXKn5swsVgAAA8lJREFUeJx90dtPHHUUB/Dz+81vZhb2wrDI3soUKBSRcisF21iqqCRNY01NTE0k8aHpi0k18VJfjOFvUF9M44MmGrHFQqSQiKSmFloL5c4CXW6Fhb0vO3ufvczMzweiBGI9+eW8ffI95/yQqqrwv4UxBgCfJ9w/2NfSVB+Nyn6/r+vdLo7H6FkYY6yoABR2PJujj34MSo/d/nHeVLYbydmIp/bEO0fEy/+NMcbTU4/j4Vs6Lr0ccKeYuUKWS4ABVCVHmRdszbfvTgfjR8kz5Jjs+9RREl9Zy2lbVK9wU3/kWLJLCXnqza1bfVe7b9jLbIeTMcYu13Jg/aMiPrCwVFcgtDiMhnxwJ/zXVDwSdVCVMRV7nqzl2i9e/fKrw8mqSp84e2sFj3Oj8/SrF/MaicmyYhAaXu58NPAbeAeyzY0NLecmh2+ODN3BewYBAkAY43giI3kebrnsRmvV9z2D4ciOa3EBAf31Tp9sMgdxMTFm6j74/Ogb70VCYQKAAIDCXkOAIC6pkYBWdwwnpHEdf6L9dJtJKPh95DZhzFKMEWRAGL927XpWTmMA+s8DAOBYAoR483l/iHZ/8bXoODl8b9UfyH72SXepzbyRJNvjFGHKMlhvMBze+cH9+4lEuOOlU2X1tVkFTU7Om03q080NDGXV1cflRpHwaaoiiiildB8jhDLZ7HDfz2Yidba6Vn2L4fhzFrNRKy5OZ2QOZ1U5W8VtqlVH/iUHcM933zZYWS7Wtj66zZr65bzGJQt0glHgudi9XVzEl4vKw2kUPhO020oPYI1qYc+2Xc0bRXFwTLY0VXa2VibD/lBaIXm1UChN5JSRUcQQ1Tk/47Cf3x8bY7y17Y17PVYTG1UkLPBFcqik7Zoa9JcLYoHBqHhXNgd6gS1k9EJ1TQ2l9EDy1saErmQ2kGpwGC2MLOtCM8nZEV1K0tKJtEksSm26J/rHg2zzmabKisq939nHzqUH7efzd4f/nPGW6NP8ybNFrOsWQhpoCuuhnJ4hAnPhFam01K4oQMjBg/mzBjVhuvw2O++KKT+BIVxJKzQECBDLF2qu2WTMmCovtDQ1f8iyoGkUADBCCGPsdnvTW2OtFm01VeB06msvdWlpPZU0wJRG85ns84umU3k+VyxeEcWqvYUBAGsUrbvme4be99HFeisP/pwUOIZaOqQX31ISgrKmZhLHtXNXuJq68orrr5/9mBCglCLAGGPyy81votEbcjlKLrC9E8mhH3wdHRdcyyvjidSlxjftPJpD+o25JYvRHGFoZDdks1mBQhxJu9uxvwEiXuHnHbLd1AAAAABJRU5ErkJggg==""" # noqa: E501 + + +def test_chat_google_genai_stream() -> None: + """Test streaming tokens from OpenAI.""" + llm = ChatGoogleGenerativeAI(model=_MODEL) + + for token in llm.stream("I'm Pickle Rick"): + assert isinstance(token.content, str) + + +async def test_chat_google_genai_astream() -> None: + """Test streaming tokens from OpenAI.""" + llm = ChatGoogleGenerativeAI(model=_MODEL) + + async for token in llm.astream("I'm Pickle Rick"): + assert isinstance(token.content, str) + + +async def test_chat_google_genai_abatch() -> None: + """Test streaming tokens from ChatGoogleGenerativeAI.""" + llm = ChatGoogleGenerativeAI(model=_MODEL) + + result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"]) + for token in result: + assert isinstance(token.content, str) + + +async def test_chat_google_genai_abatch_tags() -> None: + """Test batch tokens from ChatGoogleGenerativeAI.""" + llm = ChatGoogleGenerativeAI(model=_MODEL) + + result = await llm.abatch( + ["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]} + ) + for token in result: + assert isinstance(token.content, str) + + +def test_chat_google_genai_batch() -> None: + """Test batch tokens from ChatGoogleGenerativeAI.""" + llm = ChatGoogleGenerativeAI(model=_MODEL) + + result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"]) + for token in result: + assert isinstance(token.content, str) + + +async def test_chat_google_genai_ainvoke() -> None: + """Test invoke tokens from ChatGoogleGenerativeAI.""" + llm = ChatGoogleGenerativeAI(model=_MODEL) + + result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]}) + assert isinstance(result.content, str) + + +def test_chat_google_genai_invoke() -> None: + """Test invoke tokens from ChatGoogleGenerativeAI.""" + llm = ChatGoogleGenerativeAI(model=_MODEL) + + result = llm.invoke( + "I'm Pickle Rick", + config=dict(tags=["foo"]), + generation_config=dict(top_k=2, top_p=1, temperature=0.7), + ) + assert isinstance(result.content, str) + assert not result.content.startswith(" ") + + +def test_chat_google_genai_invoke_multimodal() -> None: + messages: list = [ + HumanMessage( + content=[ + { + "type": "text", + "text": "Guess what's in this picture! You have 3 guesses.", + }, + { + "type": "image_url", + "image_url": "data:image/png;base64," + _B64_string, + }, + ] + ), + ] + llm = ChatGoogleGenerativeAI(model=_VISION_MODEL) + response = llm.invoke(messages) + assert isinstance(response.content, str) + assert len(response.content.strip()) > 0 + + # Try streaming + for chunk in llm.stream(messages): + print(chunk) + assert isinstance(chunk.content, str) + assert len(chunk.content.strip()) > 0 + + +def test_chat_google_genai_invoke_multimodal_too_many_messages() -> None: + # Only supports 1 turn... + messages: list = [ + HumanMessage(content="Hi there"), + AIMessage(content="Hi, how are you?"), + HumanMessage( + content=[ + { + "type": "text", + "text": "I'm doing great! Guess what's in this picture!", + }, + { + "type": "image_url", + "image_url": "data:image/png;base64," + _B64_string, + }, + ] + ), + ] + llm = ChatGoogleGenerativeAI(model=_VISION_MODEL) + with pytest.raises(ChatGoogleGenerativeAIError): + llm.invoke(messages) + + +def test_chat_google_genai_invoke_multimodal_invalid_model() -> None: + # need the vision model to support this. + messages: list = [ + HumanMessage( + content=[ + { + "type": "text", + "text": "I'm doing great! Guess what's in this picture!", + }, + { + "type": "image_url", + "image_url": "data:image/png;base64," + _B64_string, + }, + ] + ), + ] + llm = ChatGoogleGenerativeAI(model=_MODEL) + with pytest.raises(ChatGoogleGenerativeAIError): + llm.invoke(messages) diff --git a/libs/partners/google-genai/tests/integration_tests/test_compile.py b/libs/partners/google-genai/tests/integration_tests/test_compile.py new file mode 100644 index 00000000000..33ecccdfa0f --- /dev/null +++ b/libs/partners/google-genai/tests/integration_tests/test_compile.py @@ -0,0 +1,7 @@ +import pytest + + +@pytest.mark.compile +def test_placeholder() -> None: + """Used for compiling integration tests without running any real tests.""" + pass diff --git a/libs/partners/google-genai/tests/unit_tests/__init__.py b/libs/partners/google-genai/tests/unit_tests/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/libs/partners/google-genai/tests/unit_tests/test_chat_models.py b/libs/partners/google-genai/tests/unit_tests/test_chat_models.py new file mode 100644 index 00000000000..afa26de4d19 --- /dev/null +++ b/libs/partners/google-genai/tests/unit_tests/test_chat_models.py @@ -0,0 +1,24 @@ +"""Test chat model integration.""" + + +from langchain_google_genai.chat_models import ChatGoogleGenerativeAI + + +def test_integration_initialization() -> None: + """Test chat model initialization.""" + ChatGoogleGenerativeAI( + model="gemini-nano", + google_api_key="...", + top_k=2, + top_p=1, + temperature=0.7, + n=2, + ) + ChatGoogleGenerativeAI( + model="gemini-nano", + google_api_key="...", + top_k=2, + top_p=1, + temperature=0.7, + candidate_count=2, + ) diff --git a/libs/partners/google-genai/tests/unit_tests/test_imports.py b/libs/partners/google-genai/tests/unit_tests/test_imports.py new file mode 100644 index 00000000000..9cbd73df816 --- /dev/null +++ b/libs/partners/google-genai/tests/unit_tests/test_imports.py @@ -0,0 +1,9 @@ +from langchain_google_genai import __all__ + +EXPECTED_ALL = [ + "ChatGoogleGenerativeAI", +] + + +def test_all_imports() -> None: + assert sorted(EXPECTED_ALL) == sorted(__all__)