diff --git a/libs/partners/upstage/LICENSE b/libs/partners/upstage/LICENSE deleted file mode 100644 index fc0602feec..0000000000 --- a/libs/partners/upstage/LICENSE +++ /dev/null @@ -1,21 +0,0 @@ -MIT License - -Copyright (c) 2024 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/upstage/Makefile b/libs/partners/upstage/Makefile deleted file mode 100644 index 1fbb1e8220..0000000000 --- a/libs/partners/upstage/Makefile +++ /dev/null @@ -1,57 +0,0 @@ -.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/ - -integration_test integration_tests: TEST_FILE=tests/integration_tests/ - -test tests integration_test integration_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/upstage --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$') -lint_package: PYTHON_FILES=langchain_upstage -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_upstage -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= - run all tests in file' diff --git a/libs/partners/upstage/README.md b/libs/partners/upstage/README.md index e26cb409a7..c8b61f4859 100644 --- a/libs/partners/upstage/README.md +++ b/libs/partners/upstage/README.md @@ -1,25 +1,3 @@ -# langchain-upstage +This package has moved! -This package contains the LangChain integrations for [Upstage](https://upstage.ai) through their [APIs](https://developers.upstage.ai/docs/getting-started/models). - -## Installation and Setup - -- Install the LangChain partner package -```bash -pip install -U langchain-upstage -``` - -- Get an Upstage api key from [Upstage Console](https://console.upstage.ai/home) and set it as an environment variable (`UPSTAGE_API_KEY`) - -## Chat Models - -This package contains the `ChatUpstage` class, which is the recommended way to interface with Upstage models. - -See a [usage example](https://python.langchain.com/docs/integrations/chat/upstage) - -## Embeddings - -See a [usage example](https://python.langchain.com/docs/integrations/text_embedding/upstage) - -Use `solar-embedding-1-large` model for embeddings. Do not add suffixes such as `-query` or `-passage` to the model name. -`UpstageEmbeddings` will automatically add the suffixes based on the method called. +https://github.com/langchain-ai/langchain-upstage/tree/main/libs/upstage \ No newline at end of file diff --git a/libs/partners/upstage/langchain_upstage/__init__.py b/libs/partners/upstage/langchain_upstage/__init__.py deleted file mode 100644 index 77c1b91724..0000000000 --- a/libs/partners/upstage/langchain_upstage/__init__.py +++ /dev/null @@ -1,17 +0,0 @@ -from langchain_upstage.chat_models import ChatUpstage -from langchain_upstage.embeddings import UpstageEmbeddings -from langchain_upstage.layout_analysis import UpstageLayoutAnalysisLoader -from langchain_upstage.layout_analysis_parsers import UpstageLayoutAnalysisParser -from langchain_upstage.tools.groundedness_check import ( - GroundednessCheck, - UpstageGroundednessCheck, -) - -__all__ = [ - "ChatUpstage", - "UpstageEmbeddings", - "UpstageLayoutAnalysisLoader", - "UpstageLayoutAnalysisParser", - "UpstageGroundednessCheck", - "GroundednessCheck", -] diff --git a/libs/partners/upstage/langchain_upstage/chat_models.py b/libs/partners/upstage/langchain_upstage/chat_models.py deleted file mode 100644 index a8466a7864..0000000000 --- a/libs/partners/upstage/langchain_upstage/chat_models.py +++ /dev/null @@ -1,120 +0,0 @@ -import os -from typing import ( - Any, - Dict, - List, - Optional, -) - -import openai -from langchain_core.language_models.chat_models import LangSmithParams -from langchain_core.pydantic_v1 import Field, SecretStr, root_validator -from langchain_core.utils import ( - convert_to_secret_str, - get_from_dict_or_env, -) -from langchain_openai.chat_models.base import BaseChatOpenAI - - -class ChatUpstage(BaseChatOpenAI): - """ChatUpstage chat model. - - To use, you should have the environment variable `UPSTAGE_API_KEY` - set with your API key or pass it as a named parameter to the constructor. - - Example: - .. code-block:: python - - from langchain_upstage import ChatUpstage - - - model = ChatUpstage() - """ - - @property - def lc_secrets(self) -> Dict[str, str]: - return {"upstage_api_key": "UPSTAGE_API_KEY"} - - @classmethod - def get_lc_namespace(cls) -> List[str]: - return ["langchain", "chat_models", "upstage"] - - @property - def lc_attributes(self) -> Dict[str, Any]: - attributes: Dict[str, Any] = {} - - if self.upstage_api_base: - attributes["upstage_api_base"] = self.upstage_api_base - - return attributes - - @property - def _llm_type(self) -> str: - """Return type of chat model.""" - return "upstage-chat" - - def _get_ls_params( - self, stop: Optional[List[str]] = None, **kwargs: Any - ) -> LangSmithParams: - """Get the parameters used to invoke the model.""" - params = super()._get_ls_params(stop=stop, **kwargs) - params["ls_provider"] = "upstage" - return params - - model_name: str = Field(default="solar-1-mini-chat", alias="model") - """Model name to use.""" - upstage_api_key: Optional[SecretStr] = Field(default=None, alias="api_key") - """Automatically inferred from env are `UPSTAGE_API_KEY` if not provided.""" - upstage_api_base: Optional[str] = Field( - default="https://api.upstage.ai/v1/solar", alias="base_url" - ) - """Base URL path for API requests, leave blank if not using a proxy or service - emulator.""" - openai_api_key: Optional[SecretStr] = Field(default=None) - """openai api key is not supported for upstage. use `upstage_api_key` instead.""" - openai_api_base: Optional[str] = Field(default=None) - """openai api base is not supported for upstage. use `upstage_api_base` instead.""" - openai_organization: Optional[str] = Field(default=None) - """openai organization is not supported for upstage.""" - tiktoken_model_name: Optional[str] = None - """tiktoken is not supported for upstage.""" - - @root_validator() - def validate_environment(cls, values: Dict) -> Dict: - """Validate that api key and python package exists in environment.""" - if values["n"] < 1: - raise ValueError("n must be at least 1.") - if values["n"] > 1 and values["streaming"]: - raise ValueError("n must be 1 when streaming.") - - values["upstage_api_key"] = convert_to_secret_str( - get_from_dict_or_env(values, "upstage_api_key", "UPSTAGE_API_KEY") - ) - values["upstage_api_base"] = values["upstage_api_base"] or os.getenv( - "UPSTAGE_API_BASE" - ) - - client_params = { - "api_key": ( - values["upstage_api_key"].get_secret_value() - if values["upstage_api_key"] - else None - ), - "base_url": values["upstage_api_base"], - "timeout": values["request_timeout"], - "max_retries": values["max_retries"], - "default_headers": values["default_headers"], - "default_query": values["default_query"], - } - - if not values.get("client"): - sync_specific = {"http_client": values["http_client"]} - values["client"] = openai.OpenAI( - **client_params, **sync_specific - ).chat.completions - if not values.get("async_client"): - async_specific = {"http_client": values["http_async_client"]} - values["async_client"] = openai.AsyncOpenAI( - **client_params, **async_specific - ).chat.completions - return values diff --git a/libs/partners/upstage/langchain_upstage/embeddings.py b/libs/partners/upstage/langchain_upstage/embeddings.py deleted file mode 100644 index 5a74b32832..0000000000 --- a/libs/partners/upstage/langchain_upstage/embeddings.py +++ /dev/null @@ -1,276 +0,0 @@ -import logging -import os -import warnings -from typing import ( - Any, - Dict, - List, - Literal, - Mapping, - Optional, - Sequence, - Set, - Tuple, - Union, -) - -import openai -from langchain_core.embeddings import Embeddings -from langchain_core.pydantic_v1 import ( - BaseModel, - Extra, - Field, - SecretStr, - root_validator, -) -from langchain_core.utils import ( - convert_to_secret_str, - get_from_dict_or_env, - get_pydantic_field_names, -) - -logger = logging.getLogger(__name__) - -DEFAULT_EMBED_BATCH_SIZE = 10 -MAX_EMBED_BATCH_SIZE = 100 - - -class UpstageEmbeddings(BaseModel, Embeddings): - """UpstageEmbeddings embedding model. - - To use, set the environment variable `UPSTAGE_API_KEY` with your API key or - pass it as a named parameter to the constructor. - - Example: - .. code-block:: python - - from langchain_upstage import UpstageEmbeddings - - model = UpstageEmbeddings(model='solar-embedding-1-large') - """ - - client: Any = Field(default=None, exclude=True) #: :meta private: - async_client: Any = Field(default=None, exclude=True) #: :meta private: - model: str = Field(...) - """Embeddings model name to use. Do not add suffixes like `-query` and `-passage`. - Instead, use 'solar-embedding-1-large' for example. - """ - dimensions: Optional[int] = None - """The number of dimensions the resulting output embeddings should have. - - Not yet supported. - """ - upstage_api_key: Optional[SecretStr] = Field(default=None, alias="api_key") - """API Key for Solar API.""" - upstage_api_base: str = Field( - default="https://api.upstage.ai/v1/solar", alias="base_url" - ) - """Endpoint URL to use.""" - embedding_ctx_length: int = 4096 - """The maximum number of tokens to embed at once. - - Not yet supported. - """ - embed_batch_size: int = DEFAULT_EMBED_BATCH_SIZE - allowed_special: Union[Literal["all"], Set[str]] = set() - """Not yet supported.""" - disallowed_special: Union[Literal["all"], Set[str], Sequence[str]] = "all" - """Not yet supported.""" - chunk_size: int = 1000 - """Maximum number of texts to embed in each batch. - - Not yet supported. - """ - max_retries: int = 2 - """Maximum number of retries to make when generating.""" - request_timeout: Optional[Union[float, Tuple[float, float], Any]] = Field( - default=None, alias="timeout" - ) - """Timeout for requests to Upstage embedding API. Can be float, httpx.Timeout or - None.""" - show_progress_bar: bool = False - """Whether to show a progress bar when embedding. - - Not yet supported. - """ - model_kwargs: Dict[str, Any] = Field(default_factory=dict) - """Holds any model parameters valid for `create` call not explicitly specified.""" - skip_empty: bool = False - """Whether to skip empty strings when embedding or raise an error. - Defaults to not skipping. - - Not yet supported.""" - default_headers: Union[Mapping[str, str], None] = None - default_query: Union[Mapping[str, object], None] = None - # Configure a custom httpx client. See the - # [httpx documentation](https://www.python-httpx.org/api/#client) for more details. - http_client: Union[Any, None] = None - """Optional httpx.Client. Only used for sync invocations. Must specify - http_async_client as well if you'd like a custom client for async invocations. - """ - http_async_client: Union[Any, None] = None - """Optional httpx.AsyncClient. Only used for async invocations. Must specify - http_client as well if you'd like a custom client for sync invocations.""" - - class Config: - extra = Extra.forbid - allow_population_by_field_name = True - - @root_validator(pre=True) - def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]: - """Build extra kwargs from additional params that were passed in.""" - all_required_field_names = get_pydantic_field_names(cls) - extra = values.get("model_kwargs", {}) - for field_name in list(values): - if field_name in extra: - raise ValueError(f"Found {field_name} supplied twice.") - if field_name not in all_required_field_names: - warnings.warn( - f"""WARNING! {field_name} is not default parameter. - {field_name} was transferred to model_kwargs. - Please confirm that {field_name} is what you intended.""" - ) - extra[field_name] = values.pop(field_name) - - invalid_model_kwargs = all_required_field_names.intersection(extra.keys()) - if invalid_model_kwargs: - raise ValueError( - f"Parameters {invalid_model_kwargs} should be specified explicitly. " - f"Instead they were passed in as part of `model_kwargs` parameter." - ) - - values["model_kwargs"] = extra - return values - - @root_validator() - def validate_environment(cls, values: Dict) -> Dict: - """Validate that api key and python package exists in environment.""" - - upstage_api_key = get_from_dict_or_env( - values, "upstage_api_key", "UPSTAGE_API_KEY" - ) - values["upstage_api_key"] = ( - convert_to_secret_str(upstage_api_key) if upstage_api_key else None - ) - values["upstage_api_base"] = values["upstage_api_base"] or os.getenv( - "UPSTAGE_API_BASE" - ) - client_params = { - "api_key": ( - values["upstage_api_key"].get_secret_value() - if values["upstage_api_key"] - else None - ), - "base_url": values["upstage_api_base"], - "timeout": values["request_timeout"], - "max_retries": values["max_retries"], - "default_headers": values["default_headers"], - "default_query": values["default_query"], - } - if not values.get("client"): - sync_specific = {"http_client": values["http_client"]} - values["client"] = openai.OpenAI( - **client_params, **sync_specific - ).embeddings - if not values.get("async_client"): - async_specific = {"http_client": values["http_async_client"]} - values["async_client"] = openai.AsyncOpenAI( - **client_params, **async_specific - ).embeddings - return values - - @property - def _invocation_params(self) -> Dict[str, Any]: - self.model = self.model.replace("-query", "").replace("-passage", "") - - params: Dict = {"model": self.model, **self.model_kwargs} - if self.dimensions is not None: - params["dimensions"] = self.dimensions - return params - - def embed_documents(self, texts: List[str]) -> List[List[float]]: - """Embed a list of document texts using passage model. - - Args: - texts: The list of texts to embed. - - Returns: - List of embeddings, one for each text. - """ - assert ( - self.embed_batch_size <= MAX_EMBED_BATCH_SIZE - ), f"The embed_batch_size should not be larger than {MAX_EMBED_BATCH_SIZE}." - if not texts: - return [] - params = self._invocation_params - params["model"] = params["model"] + "-passage" - embeddings = [] - - batch_size = min(self.embed_batch_size, len(texts)) - for i in range(0, len(texts), batch_size): - batch = texts[i : i + batch_size] - data = self.client.create(input=batch, **params).data - embeddings.extend([r.embedding for r in data]) - - return embeddings - - def embed_query(self, text: str) -> List[float]: - """Embed query text using query model. - - Args: - text: The text to embed. - - Returns: - Embedding for the text. - """ - params = self._invocation_params - params["model"] = params["model"] + "-query" - - response = self.client.create(input=text, **params) - - if not isinstance(response, dict): - response = response.model_dump() - return response["data"][0]["embedding"] - - async def aembed_documents(self, texts: List[str]) -> List[List[float]]: - """Embed a list of document texts using passage model asynchronously. - - Args: - texts: The list of texts to embed. - - Returns: - List of embeddings, one for each text. - """ - assert ( - self.embed_batch_size <= MAX_EMBED_BATCH_SIZE - ), f"The embed_batch_size should not be larger than {MAX_EMBED_BATCH_SIZE}." - if not texts: - return [] - params = self._invocation_params - params["model"] = params["model"] + "-passage" - embeddings = [] - - batch_size = min(self.embed_batch_size, len(texts)) - for i in range(0, len(texts), batch_size): - batch = texts[i : i + batch_size] - response = await self.async_client.create(input=batch, **params) - embeddings.extend([r.embedding for r in response.data]) - return embeddings - - async def aembed_query(self, text: str) -> List[float]: - """Asynchronous Embed query text using query model. - - Args: - text: The text to embed. - - Returns: - Embedding for the text. - """ - params = self._invocation_params - params["model"] = params["model"] + "-query" - - response = await self.async_client.create(input=text, **params) - - if not isinstance(response, dict): - response = response.model_dump() - return response["data"][0]["embedding"] diff --git a/libs/partners/upstage/langchain_upstage/layout_analysis.py b/libs/partners/upstage/langchain_upstage/layout_analysis.py deleted file mode 100644 index fc68f4d139..0000000000 --- a/libs/partners/upstage/langchain_upstage/layout_analysis.py +++ /dev/null @@ -1,248 +0,0 @@ -import os -import warnings -from pathlib import Path -from typing import Any, Dict, Iterator, List, Literal, Optional, Union - -from langchain_core.document_loaders import BaseLoader, Blob -from langchain_core.documents import Document - -from .layout_analysis_parsers import UpstageLayoutAnalysisParser - -DEFAULT_PAGE_BATCH_SIZE = 10 - -OutputType = Literal["text", "html"] -SplitType = Literal["none", "element", "page"] - - -def validate_api_key(api_key: str) -> None: - """ - Validates the provided API key. - - Args: - api_key (str): The API key to be validated. - - Raises: - ValueError: If the API key is empty or None. - - Returns: - None - """ - if not api_key: - raise ValueError("API Key is required for Upstage Document Loader") - - -def validate_file_path(file_path: Union[str, Path, List[str], List[Path]]) -> None: - """ - Validates if a file exists at the given file path. - - Args: - file_path (Union[str, Path, List[str], List[Path]): The file path(s) to be - validated. - - Raises: - FileNotFoundError: If the file or any of the files in the list do not exist. - """ - if isinstance(file_path, list): - for path in file_path: - validate_file_path(path) - return - if not os.path.exists(file_path): - raise FileNotFoundError(f"File not found: {file_path}") - - -def get_from_param_or_env( - key: str, - param: Optional[str] = None, - env_key: Optional[str] = None, - default: Optional[str] = None, -) -> str: - """Get a value from a param or an environment variable.""" - if param is not None: - return param - elif env_key and env_key in os.environ and os.environ[env_key]: - return os.environ[env_key] - elif default is not None: - return default - else: - raise ValueError( - f"Did not find {key}, please add an environment variable" - f" `{env_key}` which contains it, or pass" - f" `{key}` as a named parameter." - ) - - -class UpstageLayoutAnalysisLoader(BaseLoader): - """Upstage Layout Analysis. - - To use, you should have the environment variable `UPSTAGE_API_KEY` - set with your API key or pass it as a named parameter to the constructor. - - Example: - .. code-block:: python - - from langchain_upstage import UpstageLayoutAnalysis - - file_path = "/PATH/TO/YOUR/FILE.pdf" - loader = UpstageLayoutAnalysis( - file_path, split="page", output_type="text" - ) - """ - - def __init__( - self, - file_path: Union[str, Path, List[str], List[Path]], - output_type: Union[OutputType, dict] = "html", - split: SplitType = "none", - api_key: Optional[str] = None, - use_ocr: bool = False, - exclude: list = ["header", "footer"], - ): - """ - Initializes an instance of the Upstage document loader. - - Args: - file_path (Union[str, Path, List[str], List[Path]): The path to the document - to be loaded. - output_type (Union[OutputType, dict], optional): The type of output to be - generated by the parser. - Defaults to "html". - split (SplitType, optional): The type of splitting to be applied. - Defaults to "none" (no splitting). - api_key (str, optional): The API key for accessing the Upstage API. - Defaults to None, in which case it will be - fetched from the environment variable - `UPSTAGE_API_KEY`. - use_ocr (bool, optional): Extract text from images in the document. - Defaults to False. (Use text info in PDF file) - exclude (list, optional): Exclude specific elements from - the output. - Defaults to ["header", "footer"]. - """ - self.file_path = file_path - self.output_type = output_type - self.split = split - if deprecated_key := os.environ.get("UPSTAGE_DOCUMENT_AI_API_KEY"): - warnings.warn( - "UPSTAGE_DOCUMENT_AI_API_KEY is deprecated." - "Please use UPSTAGE_API_KEY instead." - ) - - self.api_key = get_from_param_or_env( - "UPSTAGE_API_KEY", api_key, "UPSTAGE_API_KEY", deprecated_key - ) - self.use_ocr = use_ocr - self.exclude = exclude - - validate_file_path(self.file_path) - validate_api_key(self.api_key) - - def load(self) -> List[Document]: - """ - Loads and parses the document using the UpstageLayoutAnalysisParser. - - Returns: - A list of Document objects representing the parsed layout analysis. - """ - - if isinstance(self.file_path, list): - result = [] - - for file_path in self.file_path: - blob = Blob.from_path(file_path) - - parser = UpstageLayoutAnalysisParser( - self.api_key, - split=self.split, - output_type=self.output_type, - use_ocr=self.use_ocr, - exclude=self.exclude, - ) - result.extend(list(parser.lazy_parse(blob, is_batch=True))) - - return result - - else: - blob = Blob.from_path(self.file_path) - - parser = UpstageLayoutAnalysisParser( - self.api_key, - split=self.split, - output_type=self.output_type, - use_ocr=self.use_ocr, - exclude=self.exclude, - ) - return list(parser.lazy_parse(blob, is_batch=True)) - - def lazy_load(self) -> Iterator[Document]: - """ - Lazily loads and parses the document using the UpstageLayoutAnalysisParser. - - Returns: - An iterator of Document objects representing the parsed layout analysis. - """ - - if isinstance(self.file_path, list): - for file_path in self.file_path: - blob = Blob.from_path(file_path) - - parser = UpstageLayoutAnalysisParser( - self.api_key, - split=self.split, - output_type=self.output_type, - use_ocr=self.use_ocr, - exclude=self.exclude, - ) - yield from parser.lazy_parse(blob, is_batch=True) - else: - blob = Blob.from_path(self.file_path) - - parser = UpstageLayoutAnalysisParser( - self.api_key, - split=self.split, - output_type=self.output_type, - use_ocr=self.use_ocr, - exclude=self.exclude, - ) - yield from parser.lazy_parse(blob) - - def merge_and_split( - self, documents: List[Document], splitter: Optional[object] = None - ) -> List[Document]: - """ - Merges the page content and metadata of multiple documents into a single - document, or splits the documents using a custom splitter. - - Args: - documents (list): A list of Document objects to be merged and split. - splitter (object, optional): An optional splitter object that implements the - `split_documents` method. If provided, the documents will be split using - this splitter. Defaults to None, in which case the documents are merged. - - Returns: - list: A list of Document objects. If no splitter is provided, a single - Document object is returned with the merged content and combined metadata. - If a splitter is provided, the documents are split and a list of Document - objects is returned. - - Raises: - AssertionError: If a splitter is provided but it does not implement the - `split_documents` method. - """ - if splitter is None: - merged_content = " ".join([doc.page_content for doc in documents]) - - metadatas: Dict[str, Any] = dict() - for _meta in [doc.metadata for doc in documents]: - for key, value in _meta.items(): - if key in metadatas: - metadatas[key].append(value) - else: - metadatas[key] = [value] - - return [Document(page_content=merged_content, metadata=metadatas)] - else: - assert hasattr( - splitter, "split_documents" - ), "splitter must implement split_documents method" - - return splitter.split_documents(documents) diff --git a/libs/partners/upstage/langchain_upstage/layout_analysis_parsers.py b/libs/partners/upstage/langchain_upstage/layout_analysis_parsers.py deleted file mode 100644 index 17b571c513..0000000000 --- a/libs/partners/upstage/langchain_upstage/layout_analysis_parsers.py +++ /dev/null @@ -1,396 +0,0 @@ -import io -import json -import os -import warnings -from typing import Dict, Iterator, List, Literal, Optional, Union - -import fitz # type: ignore -import requests -from fitz import Document as fitzDocument -from langchain_core.document_loaders import BaseBlobParser, Blob -from langchain_core.documents import Document - -LAYOUT_ANALYSIS_URL = "https://api.upstage.ai/v1/document-ai/layout-analysis" - -DEFAULT_NUMBER_OF_PAGE = 10 - -OutputType = Literal["text", "html"] -SplitType = Literal["none", "element", "page"] - - -def validate_api_key(api_key: str) -> None: - """ - Validates the provided API key. - - Args: - api_key (str): The API key to be validated. - - Raises: - ValueError: If the API key is empty or None. - - Returns: - None - """ - if not api_key: - raise ValueError("API Key is required for Upstage Document Loader") - - -def validate_file_path(file_path: str) -> None: - """ - Validates if a file exists at the given file path. - - Args: - file_path (str): The path to the file. - - Raises: - FileNotFoundError: If the file does not exist at the given file path. - """ - if not os.path.exists(file_path): - raise FileNotFoundError(f"File not found: {file_path}") - - -def parse_output(data: dict, output_type: Union[OutputType, dict]) -> str: - """ - Parse the output data based on the specified output type. - - Args: - data (dict): The data to be parsed. - output_type (Union[OutputType, dict]): The output type to parse the element data - into. - - Returns: - str: The parsed output. - - Raises: - ValueError: If the output type is invalid. - """ - if isinstance(output_type, dict): - if data["category"] in output_type: - return data[output_type[data["category"]]] - else: - return data["text"] - elif isinstance(output_type, str): - if output_type == "text": - return data["text"] - elif output_type == "html": - return data["html"] - else: - raise ValueError(f"Invalid output type: {output_type}") - else: - raise ValueError(f"Invalid output type: {output_type}") - - -def get_from_param_or_env( - key: str, - param: Optional[str] = None, - env_key: Optional[str] = None, - default: Optional[str] = None, -) -> str: - """Get a value from a param or an environment variable.""" - if param is not None: - return param - elif env_key and env_key in os.environ and os.environ[env_key]: - return os.environ[env_key] - elif default is not None: - return default - else: - raise ValueError( - f"Did not find {key}, please add an environment variable" - f" `{env_key}` which contains it, or pass" - f" `{key}` as a named parameter." - ) - - -class UpstageLayoutAnalysisParser(BaseBlobParser): - """Upstage Layout Analysis Parser. - - To use, you should have the environment variable `UPSTAGE_API_KEY` - set with your API key or pass it as a named parameter to the constructor. - - Example: - .. code-block:: python - - from langchain_upstage import UpstageLayoutAnalysisParser - - loader = UpstageLayoutAnalysisParser(split="page", output_type="text") - """ - - def __init__( - self, - api_key: Optional[str] = None, - output_type: Union[OutputType, dict] = "html", - split: SplitType = "none", - use_ocr: bool = False, - exclude: list = [], - ): - """ - Initializes an instance of the Upstage class. - - Args: - api_key (str, optional): The API key for accessing the Upstage API. - Defaults to None, in which case it will be - fetched from the environment variable - `UPSTAGE_API_KEY`. - output_type (Union[OutputType, dict], optional): The type of output to be - generated by the parser. - Defaults to "html". - split (SplitType, optional): The type of splitting to be applied. - Defaults to "none" (no splitting). - use_ocr (bool, optional): Extract text from images in the document. - Defaults to False. (Use text info in PDF file) - exclude (list, optional): Exclude specific elements from the output. - Defaults to [] (all included). - """ - if deprecated_key := os.environ.get("UPSTAGE_DOCUMENT_AI_API_KEY"): - warnings.warn( - "UPSTAGE_DOCUMENT_AI_API_KEY is deprecated." - "Please use UPSTAGE_API_KEY instead." - ) - self.api_key = get_from_param_or_env( - "UPSTAGE_API_KEY", api_key, "UPSTAGE_API_KEY", deprecated_key - ) - - self.output_type = output_type - self.split = split - self.use_ocr = use_ocr - self.exclude = exclude - - validate_api_key(self.api_key) - - def _get_response(self, files: Dict) -> List: - """ - Sends a POST request to the API endpoint with the provided files and - returns the response. - - Args: - files (dict): A dictionary containing the files to be sent in the request. - - Returns: - dict: The JSON response from the API. - - Raises: - ValueError: If there is an error in the API call. - """ - try: - headers = {"Authorization": f"Bearer {self.api_key}"} - options = {"ocr": self.use_ocr} - response = requests.post( - LAYOUT_ANALYSIS_URL, headers=headers, files=files, data=options - ) - response.raise_for_status() - - result = response.json().get("elements", []) - - elements = [ - element for element in result if element["category"] not in self.exclude - ] - - return elements - - except requests.RequestException as req_err: - # Handle any request-related exceptions - print(f"Request Exception: {req_err}") - raise ValueError(f"Failed to send request: {req_err}") - except json.JSONDecodeError as json_err: - # Handle JSON decode errors - print(f"JSON Decode Error: {json_err}") - raise ValueError(f"Failed to decode JSON response: {json_err}") - - return [] - - def _split_and_request( - self, - full_docs: fitzDocument, - start_page: int, - num_pages: int = DEFAULT_NUMBER_OF_PAGE, - ) -> List: - """ - Splits the full pdf document into partial pages and sends a request to the - server. - - Args: - full_docs (str): The full document to be split and requested. - start_page (int): The starting page number for splitting the document. - num_pages (int, optional): The number of pages to split the document - into. - Defaults to DEFAULT_NUMBER_OF_PAGE. - - Returns: - response: The response from the server. - """ - with fitz.open() as chunk_pdf: - chunk_pdf.insert_pdf( - full_docs, - from_page=start_page, - to_page=start_page + num_pages - 1, - ) - pdf_bytes = chunk_pdf.write() - - with io.BytesIO(pdf_bytes) as f: - response = self._get_response({"document": f}) - - return response - - def _element_document(self, elements: Dict) -> Document: - """ - Converts an elements into a Document object. - - Args: - elements: The elements to convert. - - Returns: - A list containing a single Document object. - - """ - return Document( - page_content=(parse_output(elements, self.output_type)), - metadata={ - "page": elements["page"], - "id": elements["id"], - "type": self.output_type, - "split": self.split, - "bbox": elements["bounding_box"], - "category": elements["category"], - }, - ) - - def _page_document(self, elements: List) -> List[Document]: - """ - Combines elements with the same page number into a single Document object. - - Args: - elements (List): A list of elements containing page numbers. - - Returns: - List[Document]: A list of Document objects, each representing a page - with its content and metadata. - """ - _docs = [] - pages = sorted(set(map(lambda x: x["page"], elements))) - - page_group = [ - [element for element in elements if element["page"] == x] for x in pages - ] - - for group in page_group: - page_content = " ".join( - [parse_output(element, self.output_type) for element in group] - ) - - _docs.append( - Document( - page_content=page_content, - metadata={ - "page": group[0]["page"], - "type": self.output_type, - "split": self.split, - }, - ) - ) - - return _docs - - def lazy_parse(self, blob: Blob, is_batch: bool = False) -> Iterator[Document]: - """ - Lazily parses a document and yields Document objects based on the specified - split type. - - Args: - blob (Blob): The input document blob to parse. - is_batch (bool, optional): Whether to parse the document in batches. - Defaults to False (single page parsing) - - Yields: - Document: The parsed document object. - - Raises: - ValueError: If an invalid split type is provided. - - """ - - if is_batch: - num_pages = DEFAULT_NUMBER_OF_PAGE - else: - num_pages = 1 - - full_docs = fitz.open(blob.path) - number_of_pages = full_docs.page_count - - if self.split == "none": - if full_docs.is_pdf: - result = "" - start_page = 0 - num_pages = DEFAULT_NUMBER_OF_PAGE - for _ in range(number_of_pages): - if start_page >= number_of_pages: - break - - elements = self._split_and_request(full_docs, start_page, num_pages) - for element in elements: - result += parse_output(element, self.output_type) - - start_page += num_pages - - else: - if not blob.path: - raise ValueError("Blob path is required for non-PDF files.") - - result = "" - with open(blob.path, "rb") as f: - elements = self._get_response({"document": f}) - - for element in elements: - result += parse_output(element, self.output_type) - - yield Document( - page_content=result, - metadata={ - "total_pages": number_of_pages, - "type": self.output_type, - "split": self.split, - }, - ) - - elif self.split == "element": - if full_docs.is_pdf: - start_page = 0 - for _ in range(number_of_pages): - if start_page >= number_of_pages: - break - - elements = self._split_and_request(full_docs, start_page, num_pages) - for element in elements: - yield self._element_document(element) - - start_page += num_pages - - else: - if not blob.path: - raise ValueError("Blob path is required for non-PDF files.") - with open(blob.path, "rb") as f: - elements = self._get_response({"document": f}) - - for element in elements: - yield self._element_document(element) - - elif self.split == "page": - if full_docs.is_pdf: - start_page = 0 - for _ in range(number_of_pages): - if start_page >= number_of_pages: - break - - elements = self._split_and_request(full_docs, start_page, num_pages) - yield from self._page_document(elements) - - start_page += num_pages - else: - if not blob.path: - raise ValueError("Blob path is required for non-PDF files.") - with open(blob.path, "rb") as f: - elements = self._get_response({"document": f}) - - yield from self._page_document(elements) - - else: - raise ValueError(f"Invalid split type: {self.split}") diff --git a/libs/partners/upstage/langchain_upstage/py.typed b/libs/partners/upstage/langchain_upstage/py.typed deleted file mode 100644 index e69de29bb2..0000000000 diff --git a/libs/partners/upstage/langchain_upstage/tools/groundedness_check.py b/libs/partners/upstage/langchain_upstage/tools/groundedness_check.py deleted file mode 100644 index fa93303491..0000000000 --- a/libs/partners/upstage/langchain_upstage/tools/groundedness_check.py +++ /dev/null @@ -1,117 +0,0 @@ -import os -from typing import Any, List, Literal, Optional, Type, Union - -from langchain_core._api.deprecation import deprecated -from langchain_core.callbacks import ( - AsyncCallbackManagerForToolRun, - CallbackManagerForToolRun, -) -from langchain_core.documents import Document -from langchain_core.messages import AIMessage, HumanMessage -from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr -from langchain_core.tools import BaseTool -from langchain_core.utils import convert_to_secret_str - -from langchain_upstage import ChatUpstage - - -class UpstageGroundednessCheckInput(BaseModel): - """Input for the Groundedness Check tool.""" - - context: Union[str, List[Document]] = Field( - description="context in which the answer should be verified" - ) - answer: str = Field( - description="assistant's reply or a text that is subject to groundedness check" - ) - - -class UpstageGroundednessCheck(BaseTool): - """Tool that checks the groundedness of a context and an assistant message. - - To use, you should have the environment variable `UPSTAGE_API_KEY` - set with your API key or pass it as a named parameter to the constructor. - - Example: - .. code-block:: python - - from langchain_upstage import UpstageGroundednessCheck - - tool = UpstageGroundednessCheck() - """ - - name: str = "groundedness_check" - description: str = ( - "A tool that checks the groundedness of an assistant response " - "to user-provided context. UpstageGroundednessCheck ensures that " - "the assistant’s response is not only relevant but also " - "precisely aligned with the user's initial context, " - "promoting a more reliable and context-aware interaction. " - "When using retrieval-augmented generation (RAG), " - "the Groundedness Check can be used to determine whether " - "the assistant's message is grounded in the provided context." - ) - upstage_api_key: Optional[SecretStr] = Field(default=None, alias="api_key") - api_wrapper: ChatUpstage - - args_schema: Type[BaseModel] = UpstageGroundednessCheckInput - - def __init__(self, **kwargs: Any) -> None: - upstage_api_key = kwargs.get("upstage_api_key", None) - if not upstage_api_key: - upstage_api_key = kwargs.get("api_key", None) - if not upstage_api_key: - upstage_api_key = SecretStr(os.getenv("UPSTAGE_API_KEY", "")) - upstage_api_key = convert_to_secret_str(upstage_api_key) - - if ( - not upstage_api_key - or not upstage_api_key.get_secret_value() - or upstage_api_key.get_secret_value() == "" - ): - raise ValueError("UPSTAGE_API_KEY must be set or passed") - - api_wrapper = ChatUpstage( - model_name="solar-1-mini-answer-verification", - upstage_api_key=upstage_api_key.get_secret_value(), - ) - super().__init__(upstage_api_key=upstage_api_key, api_wrapper=api_wrapper) - - def formatDocumentsAsString(self, docs: List[Document]) -> str: - return "\n".join([doc.page_content for doc in docs]) - - def _run( - self, - context: Union[str, List[Document]], - answer: str, - run_manager: Optional[CallbackManagerForToolRun] = None, - ) -> Union[str, Literal["grounded", "notGrounded", "notSure"]]: - """Use the tool.""" - if isinstance(context, List): - context = self.formatDocumentsAsString(context) - response = self.api_wrapper.invoke( - [HumanMessage(context), AIMessage(answer)], stream=False - ) - return str(response.content) - - async def _arun( - self, - context: Union[str, List[Document]], - answer: str, - run_manager: Optional[AsyncCallbackManagerForToolRun] = None, - ) -> Union[str, Literal["grounded", "notGrounded", "notSure"]]: - if isinstance(context, List): - context = self.formatDocumentsAsString(context) - response = await self.api_wrapper.ainvoke( - [HumanMessage(context), AIMessage(answer)], stream=False - ) - return str(response.content) - - -@deprecated( - since="0.1.3", - removal="0.3.0", - alternative_import="langchain_upstage.UpstageGroundednessCheck", -) -class GroundednessCheck(UpstageGroundednessCheck): - pass diff --git a/libs/partners/upstage/poetry.lock b/libs/partners/upstage/poetry.lock deleted file mode 100644 index f0ea89c917..0000000000 --- a/libs/partners/upstage/poetry.lock +++ /dev/null @@ -1,1480 +0,0 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. - -[[package]] -name = "annotated-types" -version = "0.7.0" -description = "Reusable constraint types to use with typing.Annotated" -optional = false -python-versions = ">=3.8" -files = [ - {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"}, - {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, -] - -[[package]] -name = "anyio" -version = "4.3.0" -description = "High level compatibility layer for multiple asynchronous event loop implementations" -optional = false -python-versions = ">=3.8" -files = [ - {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"}, - {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"}, -] - -[package.dependencies] -exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""} -idna = ">=2.8" -sniffio = ">=1.1" -typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""} - -[package.extras] -doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] -test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"] -trio = ["trio (>=0.23)"] - -[[package]] -name = "certifi" -version = "2024.2.2" -description = "Python package for providing Mozilla's CA Bundle." -optional = false -python-versions = ">=3.6" -files = [ - {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"}, - {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"}, -] - -[[package]] -name = "charset-normalizer" -version = "3.3.2" -description = "The Real First Universal Charset Detector. 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-[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] -# Support Python 3.8 and 3.12+. -numpy = [ - {version = "^1", python = "<3.12"}, - {version = "^1.26.0", python = ">=3.12"} -] - - -[tool.poetry.group.lint] -optional = true - -[tool.poetry.group.lint.dependencies] -ruff = "^0.1.5" - -[tool.poetry.group.typing.dependencies] -mypy = "^0.991" -types-requests = ">=2.31.0" -langchain-core = { path = "../../core", develop = true } - -[tool.poetry.group.dev] -optional = true - -[tool.poetry.group.dev.dependencies] -langchain-core = { path = "../../core", develop = true } - -[tool.ruff.lint] -select = [ - "E", # pycodestyle - "F", # pyflakes - "I", # isort -] - -[tool.mypy] -disallow_untyped_defs = "True" - -[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/upstage/scripts/check_imports.py b/libs/partners/upstage/scripts/check_imports.py deleted file mode 100644 index fd21a4975b..0000000000 --- a/libs/partners/upstage/scripts/check_imports.py +++ /dev/null @@ -1,17 +0,0 @@ -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/upstage/scripts/check_pydantic.sh b/libs/partners/upstage/scripts/check_pydantic.sh deleted file mode 100755 index 06b5bb81ae..0000000000 --- a/libs/partners/upstage/scripts/check_pydantic.sh +++ /dev/null @@ -1,27 +0,0 @@ -#!/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 "$result" - echo "Please replace the code with an import from langchain_core.pydantic_v1." - echo "For example, replace 'from pydantic import BaseModel'" - echo "with 'from langchain_core.pydantic_v1 import BaseModel'" - exit 1 -fi diff --git a/libs/partners/upstage/scripts/lint_imports.sh b/libs/partners/upstage/scripts/lint_imports.sh deleted file mode 100755 index 695613c7ba..0000000000 --- a/libs/partners/upstage/scripts/lint_imports.sh +++ /dev/null @@ -1,17 +0,0 @@ -#!/bin/bash - -set -eu - -# Initialize a variable to keep track of errors -errors=0 - -# make sure not importing from langchain or langchain_experimental -git --no-pager grep '^from langchain\.' . && errors=$((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/upstage/tests/__init__.py b/libs/partners/upstage/tests/__init__.py deleted file mode 100644 index e69de29bb2..0000000000 diff --git a/libs/partners/upstage/tests/examples/solar.pdf b/libs/partners/upstage/tests/examples/solar.pdf deleted file mode 100644 index e5266aa483..0000000000 Binary files a/libs/partners/upstage/tests/examples/solar.pdf and /dev/null differ diff --git a/libs/partners/upstage/tests/integration_tests/__init__.py b/libs/partners/upstage/tests/integration_tests/__init__.py deleted file mode 100644 index e69de29bb2..0000000000 diff --git a/libs/partners/upstage/tests/integration_tests/test_chat_models.py b/libs/partners/upstage/tests/integration_tests/test_chat_models.py deleted file mode 100644 index e0a1ba5757..0000000000 --- a/libs/partners/upstage/tests/integration_tests/test_chat_models.py +++ /dev/null @@ -1,136 +0,0 @@ -import pytest -from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage - -from langchain_upstage import ChatUpstage - - -def test_chat_upstage_model() -> None: - """Test ChatUpstage wrapper handles model_name.""" - chat = ChatUpstage(model="foo") - assert chat.model_name == "foo" - chat = ChatUpstage(model_name="bar") - assert chat.model_name == "bar" - - -def test_chat_upstage_system_message() -> None: - """Test ChatOpenAI wrapper with system message.""" - chat = ChatUpstage(max_tokens=10) - system_message = SystemMessage(content="You are to chat with the user.") - human_message = HumanMessage(content="Hello") - response = chat.invoke([system_message, human_message]) - assert isinstance(response, BaseMessage) - assert isinstance(response.content, str) - - -def test_chat_upstage_llm_output_contains_model_name() -> None: - """Test llm_output contains model_name.""" - chat = ChatUpstage(max_tokens=10) - message = HumanMessage(content="Hello") - llm_result = chat.generate([[message]]) - assert llm_result.llm_output is not None - assert llm_result.llm_output["model_name"] == chat.model_name - - -def test_chat_upstage_streaming_llm_output_contains_model_name() -> None: - """Test llm_output contains model_name.""" - chat = ChatUpstage(max_tokens=10, streaming=True) - message = HumanMessage(content="Hello") - llm_result = chat.generate([[message]]) - assert llm_result.llm_output is not None - assert llm_result.llm_output["model_name"] == chat.model_name - - -def test_chat_upstage_invalid_streaming_params() -> None: - """Test that streaming correctly invokes on_llm_new_token callback.""" - with pytest.raises(ValueError): - ChatUpstage( - max_tokens=10, - streaming=True, - temperature=0, - n=5, - ) - - -def test_chat_upstage_extra_kwargs() -> None: - """Test extra kwargs to chat upstage.""" - # Check that foo is saved in extra_kwargs. - llm = ChatUpstage(foo=3, max_tokens=10) - assert llm.max_tokens == 10 - assert llm.model_kwargs == {"foo": 3} - - # Test that if extra_kwargs are provided, they are added to it. - llm = ChatUpstage(foo=3, model_kwargs={"bar": 2}) - assert llm.model_kwargs == {"foo": 3, "bar": 2} - - # Test that if provided twice it errors - with pytest.raises(ValueError): - ChatUpstage(foo=3, model_kwargs={"foo": 2}) - - # Test that if explicit param is specified in kwargs it errors - with pytest.raises(ValueError): - ChatUpstage(model_kwargs={"temperature": 0.2}) - - # Test that "model" cannot be specified in kwargs - with pytest.raises(ValueError): - ChatUpstage(model_kwargs={"model": "solar-1-mini-chat"}) - - -def test_stream() -> None: - """Test streaming tokens from OpenAI.""" - llm = ChatUpstage() - - for token in llm.stream("I'm Pickle Rick"): - assert isinstance(token.content, str) - - -async def test_astream() -> None: - """Test streaming tokens from OpenAI.""" - llm = ChatUpstage() - - async for token in llm.astream("I'm Pickle Rick"): - assert isinstance(token.content, str) - - -async def test_abatch() -> None: - """Test streaming tokens from ChatUpstage.""" - llm = ChatUpstage() - - 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_abatch_tags() -> None: - """Test batch tokens from ChatUpstage.""" - llm = ChatUpstage() - - 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_batch() -> None: - """Test batch tokens from ChatUpstage.""" - llm = ChatUpstage() - - result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"]) - for token in result: - assert isinstance(token.content, str) - - -async def test_ainvoke() -> None: - """Test invoke tokens from ChatUpstage.""" - llm = ChatUpstage() - - result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]}) - assert isinstance(result.content, str) - - -def test_invoke() -> None: - """Test invoke tokens from ChatUpstage.""" - llm = ChatUpstage() - - result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"])) - assert isinstance(result.content, str) diff --git a/libs/partners/upstage/tests/integration_tests/test_chat_models_standard.py b/libs/partners/upstage/tests/integration_tests/test_chat_models_standard.py deleted file mode 100644 index 0d1b29ec82..0000000000 --- a/libs/partners/upstage/tests/integration_tests/test_chat_models_standard.py +++ /dev/null @@ -1,18 +0,0 @@ -"""Standard LangChain interface tests""" - -from typing import Type - -from langchain_core.language_models import BaseChatModel -from langchain_standard_tests.integration_tests import ChatModelIntegrationTests - -from langchain_upstage import ChatUpstage - - -class TestUpstageStandard(ChatModelIntegrationTests): - @property - def chat_model_class(self) -> Type[BaseChatModel]: - return ChatUpstage - - @property - def chat_model_params(self) -> dict: - return {"model": "solar-1-mini-chat"} diff --git a/libs/partners/upstage/tests/integration_tests/test_compile.py b/libs/partners/upstage/tests/integration_tests/test_compile.py deleted file mode 100644 index 33ecccdfa0..0000000000 --- a/libs/partners/upstage/tests/integration_tests/test_compile.py +++ /dev/null @@ -1,7 +0,0 @@ -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/upstage/tests/integration_tests/test_embeddings.py b/libs/partners/upstage/tests/integration_tests/test_embeddings.py deleted file mode 100644 index c8e4765d5e..0000000000 --- a/libs/partners/upstage/tests/integration_tests/test_embeddings.py +++ /dev/null @@ -1,51 +0,0 @@ -"""Test Upstage embeddings.""" - -from langchain_upstage import UpstageEmbeddings - - -def test_langchain_upstage_embed_documents() -> None: - """Test Upstage embeddings.""" - documents = ["foo bar", "bar foo"] - embedding = UpstageEmbeddings(model="solar-embedding-1-large") - output = embedding.embed_documents(documents) - assert len(output) == 2 - assert len(output[0]) > 0 - - -def test_langchain_upstage_embed_query() -> None: - """Test Upstage embeddings.""" - query = "foo bar" - embedding = UpstageEmbeddings(model="solar-embedding-1-large") - output = embedding.embed_query(query) - assert len(output) > 0 - - -async def test_langchain_upstage_aembed_documents() -> None: - """Test Upstage embeddings asynchronous.""" - documents = ["foo bar", "bar foo"] - embedding = UpstageEmbeddings(model="solar-embedding-1-large") - output = await embedding.aembed_documents(documents) - assert len(output) == 2 - assert len(output[0]) > 0 - - -async def test_langchain_upstage_aembed_query() -> None: - """Test Upstage embeddings asynchronous.""" - query = "foo bar" - embedding = UpstageEmbeddings(model="solar-embedding-1-large") - output = await embedding.aembed_query(query) - assert len(output) > 0 - - -def test_langchain_upstage_embed_documents_with_empty_list() -> None: - """Test Upstage embeddings with empty list.""" - embedding = UpstageEmbeddings(model="solar-embedding-1-large") - output = embedding.embed_documents([]) - assert len(output) == 0 - - -async def test_langchain_upstage_aembed_documents_with_empty_list() -> None: - """Test Upstage embeddings asynchronous with empty list.""" - embedding = UpstageEmbeddings(model="solar-embedding-1-large") - output = await embedding.aembed_documents([]) - assert len(output) == 0 diff --git a/libs/partners/upstage/tests/integration_tests/test_groundedness_check.py b/libs/partners/upstage/tests/integration_tests/test_groundedness_check.py deleted file mode 100644 index d4b56d795d..0000000000 --- a/libs/partners/upstage/tests/integration_tests/test_groundedness_check.py +++ /dev/null @@ -1,63 +0,0 @@ -import os - -import openai -import pytest -from langchain_core.documents import Document - -from langchain_upstage import GroundednessCheck, UpstageGroundednessCheck - - -def test_langchain_upstage_groundedness_check_deprecated() -> None: - """Test Upstage Groundedness Check.""" - tool = GroundednessCheck() - output = tool.invoke({"context": "foo bar", "answer": "bar foo"}) - - assert output in ["grounded", "notGrounded", "notSure"] - - api_key = os.environ.get("UPSTAGE_API_KEY", None) - - tool = GroundednessCheck(upstage_api_key=api_key) - output = tool.invoke({"context": "foo bar", "answer": "bar foo"}) - - assert output in ["grounded", "notGrounded", "notSure"] - - -def test_langchain_upstage_groundedness_check() -> None: - """Test Upstage Groundedness Check.""" - tool = UpstageGroundednessCheck() - output = tool.invoke({"context": "foo bar", "answer": "bar foo"}) - - assert output in ["grounded", "notGrounded", "notSure"] - - api_key = os.environ.get("UPSTAGE_API_KEY", None) - - tool = UpstageGroundednessCheck(upstage_api_key=api_key) - output = tool.invoke({"context": "foo bar", "answer": "bar foo"}) - - assert output in ["grounded", "notGrounded", "notSure"] - - -def test_langchain_upstage_groundedness_check_with_documents_input() -> None: - """Test Upstage Groundedness Check.""" - tool = UpstageGroundednessCheck() - docs = [ - Document(page_content="foo bar"), - Document(page_content="bar foo"), - ] - output = tool.invoke({"context": docs, "answer": "bar foo"}) - - assert output in ["grounded", "notGrounded", "notSure"] - - -def test_langchain_upstage_groundedness_check_fail_with_wrong_api_key() -> None: - tool = UpstageGroundednessCheck(api_key="wrong-key") - with pytest.raises(openai.AuthenticationError): - tool.invoke({"context": "foo bar", "answer": "bar foo"}) - - -async def test_langchain_upstage_groundedness_check_async() -> None: - """Test Upstage Groundedness Check asynchronous.""" - tool = UpstageGroundednessCheck() - output = await tool.ainvoke({"context": "foo bar", "answer": "bar foo"}) - - assert output in ["grounded", "notGrounded", "notSure"] diff --git a/libs/partners/upstage/tests/unit_tests/__init__.py b/libs/partners/upstage/tests/unit_tests/__init__.py deleted file mode 100644 index e69de29bb2..0000000000 diff --git a/libs/partners/upstage/tests/unit_tests/test_chat_models.py b/libs/partners/upstage/tests/unit_tests/test_chat_models.py deleted file mode 100644 index 0af4f4acdd..0000000000 --- a/libs/partners/upstage/tests/unit_tests/test_chat_models.py +++ /dev/null @@ -1,194 +0,0 @@ -import json -from typing import Any -from unittest.mock import AsyncMock, MagicMock, patch - -import pytest -from langchain_core.messages import ( - AIMessage, - FunctionMessage, - HumanMessage, - SystemMessage, - ToolMessage, -) -from langchain_openai.chat_models.base import ( - _convert_dict_to_message, - _convert_message_to_dict, -) - -from langchain_upstage import ChatUpstage - - -def test_initialization() -> None: - """Test chat model initialization.""" - ChatUpstage() - - -def test_upstage_model_param() -> None: - llm = ChatUpstage(model="foo") - assert llm.model_name == "foo" - llm = ChatUpstage(model_name="foo") - assert llm.model_name == "foo" - ls_params = llm._get_ls_params() - assert ls_params["ls_provider"] == "upstage" - - -def test_function_dict_to_message_function_message() -> None: - content = json.dumps({"result": "Example #1"}) - name = "test_function" - result = _convert_dict_to_message( - { - "role": "function", - "name": name, - "content": content, - } - ) - assert isinstance(result, FunctionMessage) - assert result.name == name - assert result.content == content - - -def test_convert_dict_to_message_human() -> None: - message = {"role": "user", "content": "foo"} - result = _convert_dict_to_message(message) - expected_output = HumanMessage(content="foo") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test__convert_dict_to_message_human_with_name() -> None: - message = {"role": "user", "content": "foo", "name": "test"} - result = _convert_dict_to_message(message) - expected_output = HumanMessage(content="foo", name="test") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test_convert_dict_to_message_ai() -> None: - message = {"role": "assistant", "content": "foo"} - result = _convert_dict_to_message(message) - expected_output = AIMessage(content="foo") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test_convert_dict_to_message_ai_with_name() -> None: - message = {"role": "assistant", "content": "foo", "name": "test"} - result = _convert_dict_to_message(message) - expected_output = AIMessage(content="foo", name="test") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test_convert_dict_to_message_system() -> None: - message = {"role": "system", "content": "foo"} - result = _convert_dict_to_message(message) - expected_output = SystemMessage(content="foo") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test_convert_dict_to_message_system_with_name() -> None: - message = {"role": "system", "content": "foo", "name": "test"} - result = _convert_dict_to_message(message) - expected_output = SystemMessage(content="foo", name="test") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test_convert_dict_to_message_tool() -> None: - message = {"role": "tool", "content": "foo", "tool_call_id": "bar"} - result = _convert_dict_to_message(message) - expected_output = ToolMessage(content="foo", tool_call_id="bar") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -@pytest.fixture -def mock_completion() -> dict: - return { - "id": "chatcmpl-7fcZavknQda3SQ", - "object": "chat.completion", - "created": 1689989000, - "model": "solar-1-mini-chat", - "choices": [ - { - "index": 0, - "message": { - "role": "assistant", - "content": "Bab", - "name": "KimSolar", - }, - "finish_reason": "stop", - } - ], - } - - -def test_upstage_invoke(mock_completion: dict) -> None: - llm = ChatUpstage() - mock_client = MagicMock() - completed = False - - def mock_create(*args: Any, **kwargs: Any) -> Any: - nonlocal completed - completed = True - return mock_completion - - mock_client.create = mock_create - with patch.object( - llm, - "client", - mock_client, - ): - res = llm.invoke("bab") - assert res.content == "Bab" - assert completed - - -async def test_upstage_ainvoke(mock_completion: dict) -> None: - llm = ChatUpstage() - mock_client = AsyncMock() - completed = False - - async def mock_create(*args: Any, **kwargs: Any) -> Any: - nonlocal completed - completed = True - return mock_completion - - mock_client.create = mock_create - with patch.object( - llm, - "async_client", - mock_client, - ): - res = await llm.ainvoke("bab") - assert res.content == "Bab" - assert completed - - -def test_upstage_invoke_name(mock_completion: dict) -> None: - llm = ChatUpstage() - - mock_client = MagicMock() - mock_client.create.return_value = mock_completion - - with patch.object( - llm, - "client", - mock_client, - ): - messages = [ - HumanMessage(content="Foo", name="Zorba"), - ] - res = llm.invoke(messages) - call_args, call_kwargs = mock_client.create.call_args - assert len(call_args) == 0 # no positional args - call_messages = call_kwargs["messages"] - assert len(call_messages) == 1 - assert call_messages[0]["role"] == "user" - assert call_messages[0]["content"] == "Foo" - assert call_messages[0]["name"] == "Zorba" - - # check return type has name - assert res.content == "Bab" - assert res.name == "KimSolar" diff --git a/libs/partners/upstage/tests/unit_tests/test_chat_models_standard.py b/libs/partners/upstage/tests/unit_tests/test_chat_models_standard.py deleted file mode 100644 index 91dcb760ad..0000000000 --- a/libs/partners/upstage/tests/unit_tests/test_chat_models_standard.py +++ /dev/null @@ -1,18 +0,0 @@ -"""Standard LangChain interface tests""" - -from typing import Type - -from langchain_core.language_models import BaseChatModel -from langchain_standard_tests.unit_tests import ChatModelUnitTests - -from langchain_upstage import ChatUpstage - - -class TestUpstageStandard(ChatModelUnitTests): - @property - def chat_model_class(self) -> Type[BaseChatModel]: - return ChatUpstage - - @property - def chat_model_params(self) -> dict: - return {"model": "solar-1-mini-chat"} diff --git a/libs/partners/upstage/tests/unit_tests/test_embeddings.py b/libs/partners/upstage/tests/unit_tests/test_embeddings.py deleted file mode 100644 index 8a838a6c3b..0000000000 --- a/libs/partners/upstage/tests/unit_tests/test_embeddings.py +++ /dev/null @@ -1,32 +0,0 @@ -"""Test embedding model integration.""" - -import os - -import pytest - -from langchain_upstage import UpstageEmbeddings - -os.environ["UPSTAGE_API_KEY"] = "foo" - - -def test_initialization() -> None: - """Test embedding model initialization.""" - UpstageEmbeddings(model="solar-embedding-1-large") - - -def test_upstage_invalid_model_kwargs() -> None: - with pytest.raises(ValueError): - UpstageEmbeddings( - model="solar-embedding-1-large", model_kwargs={"model": "foo"} - ) - - -def test_upstage_invalid_model() -> None: - with pytest.raises(ValueError): - UpstageEmbeddings() - - -def test_upstage_incorrect_field() -> None: - with pytest.warns(match="not default parameter"): - llm = UpstageEmbeddings(model="solar-embedding-1-large", foo="bar") - assert llm.model_kwargs == {"foo": "bar"} diff --git a/libs/partners/upstage/tests/unit_tests/test_groundedness_check.py b/libs/partners/upstage/tests/unit_tests/test_groundedness_check.py deleted file mode 100644 index fdb0502574..0000000000 --- a/libs/partners/upstage/tests/unit_tests/test_groundedness_check.py +++ /dev/null @@ -1,12 +0,0 @@ -import os - -from langchain_upstage import UpstageGroundednessCheck - -os.environ["UPSTAGE_API_KEY"] = "foo" - - -def test_initialization() -> None: - """Test embedding model initialization.""" - UpstageGroundednessCheck() - UpstageGroundednessCheck(upstage_api_key="key") - UpstageGroundednessCheck(api_key="key") diff --git a/libs/partners/upstage/tests/unit_tests/test_imports.py b/libs/partners/upstage/tests/unit_tests/test_imports.py deleted file mode 100644 index 900826a074..0000000000 --- a/libs/partners/upstage/tests/unit_tests/test_imports.py +++ /dev/null @@ -1,14 +0,0 @@ -from langchain_upstage import __all__ - -EXPECTED_ALL = [ - "ChatUpstage", - "GroundednessCheck", - "UpstageEmbeddings", - "UpstageLayoutAnalysisLoader", - "UpstageLayoutAnalysisParser", - "UpstageGroundednessCheck", -] - - -def test_all_imports() -> None: - assert sorted(EXPECTED_ALL) == sorted(__all__) diff --git a/libs/partners/upstage/tests/unit_tests/test_layout_analysis.py b/libs/partners/upstage/tests/unit_tests/test_layout_analysis.py deleted file mode 100644 index 86c5cbb0d9..0000000000 --- a/libs/partners/upstage/tests/unit_tests/test_layout_analysis.py +++ /dev/null @@ -1,253 +0,0 @@ -import json -from pathlib import Path -from typing import Any, Dict, get_args -from unittest import TestCase -from unittest.mock import MagicMock, Mock, patch - -import requests - -from langchain_upstage import UpstageLayoutAnalysisLoader -from langchain_upstage.layout_analysis import OutputType, SplitType - -MOCK_RESPONSE_JSON: Dict[str, Any] = { - "api": "1.0", - "billed_pages": 1, - "elements": [ - { - "bounding_box": [ - {"x": 74, "y": 906}, - {"x": 148, "y": 906}, - {"x": 148, "y": 2338}, - {"x": 74, "y": 2338}, - ], - "category": "header", - "html": "
arXiv:2103.15348v2
", - "id": 0, - "page": 1, - "text": "arXiv:2103.15348v2", - }, - { - "bounding_box": [ - {"x": 654, "y": 474}, - {"x": 1912, "y": 474}, - {"x": 1912, "y": 614}, - {"x": 654, "y": 614}, - ], - "category": "paragraph", - "html": "

LayoutParser Toolkit

", - "id": 1, - "page": 1, - "text": "LayoutParser Toolkit", - }, - ], - "html": "
arXiv:2103.15348v2
" - + "

LayoutParser Toolkit

", - "mimetype": "multipart/form-data", - "model": "layout-analyzer-0.1.0", - "text": "arXiv:2103.15348v2LayoutParser Toolkit", -} - -EXAMPLE_PDF_PATH = Path(__file__).parent.parent / "examples/solar.pdf" - - -def test_initialization() -> None: - """Test layout analysis document loader initialization.""" - UpstageLayoutAnalysisLoader(file_path=EXAMPLE_PDF_PATH, api_key="bar") - - -def test_layout_analysis_param() -> None: - for output_type in get_args(OutputType): - for split in get_args(SplitType): - loader = UpstageLayoutAnalysisLoader( - file_path=EXAMPLE_PDF_PATH, - api_key="bar", - output_type=output_type, - split=split, - exclude=[], - ) - assert loader.output_type == output_type - assert loader.split == split - assert loader.api_key == "bar" - assert loader.file_path == EXAMPLE_PDF_PATH - - -@patch("requests.post") -def test_none_split_text_output(mock_post: Mock) -> None: - mock_post.return_value = MagicMock( - status_code=200, json=MagicMock(return_value=MOCK_RESPONSE_JSON) - ) - - loader = UpstageLayoutAnalysisLoader( - file_path=EXAMPLE_PDF_PATH, - output_type="text", - split="none", - api_key="valid_api_key", - exclude=[], - ) - documents = loader.load() - - assert len(documents) == 1 - assert documents[0].page_content == MOCK_RESPONSE_JSON["text"] - assert documents[0].metadata["total_pages"] == 1 - assert documents[0].metadata["type"] == "text" - assert documents[0].metadata["split"] == "none" - - -@patch("requests.post") -def test_element_split_text_output(mock_post: Mock) -> None: - mock_post.return_value = MagicMock( - status_code=200, json=MagicMock(return_value=MOCK_RESPONSE_JSON) - ) - - loader = UpstageLayoutAnalysisLoader( - file_path=EXAMPLE_PDF_PATH, - output_type="text", - split="element", - api_key="valid_api_key", - exclude=[], - ) - documents = loader.load() - - assert len(documents) == 2 - - for i, document in enumerate(documents): - assert document.page_content == MOCK_RESPONSE_JSON["elements"][i]["text"] - assert document.metadata["page"] == MOCK_RESPONSE_JSON["elements"][i]["page"] - assert document.metadata["id"] == MOCK_RESPONSE_JSON["elements"][i]["id"] - assert document.metadata["type"] == "text" - assert document.metadata["split"] == "element" - - -@patch("requests.post") -def test_page_split_text_output(mock_post: Mock) -> None: - mock_post.return_value = MagicMock( - status_code=200, json=MagicMock(return_value=MOCK_RESPONSE_JSON) - ) - - loader = UpstageLayoutAnalysisLoader( - file_path=EXAMPLE_PDF_PATH, - output_type="text", - split="page", - api_key="valid_api_key", - exclude=[], - ) - documents = loader.load() - - assert len(documents) == 1 - - for i, document in enumerate(documents): - assert document.metadata["page"] == MOCK_RESPONSE_JSON["elements"][i]["page"] - assert document.metadata["type"] == "text" - assert document.metadata["split"] == "page" - - -@patch("requests.post") -def test_none_split_html_output(mock_post: Mock) -> None: - mock_post.return_value = MagicMock( - status_code=200, json=MagicMock(return_value=MOCK_RESPONSE_JSON) - ) - - loader = UpstageLayoutAnalysisLoader( - file_path=EXAMPLE_PDF_PATH, - output_type="html", - split="none", - api_key="valid_api_key", - exclude=[], - ) - documents = loader.load() - - assert len(documents) == 1 - assert documents[0].page_content == MOCK_RESPONSE_JSON["html"] - assert documents[0].metadata["total_pages"] == 1 - assert documents[0].metadata["type"] == "html" - assert documents[0].metadata["split"] == "none" - - -@patch("requests.post") -def test_element_split_html_output(mock_post: Mock) -> None: - mock_post.return_value = MagicMock( - status_code=200, json=MagicMock(return_value=MOCK_RESPONSE_JSON) - ) - - loader = UpstageLayoutAnalysisLoader( - file_path=EXAMPLE_PDF_PATH, - output_type="html", - split="element", - api_key="valid_api_key", - exclude=[], - ) - documents = loader.load() - - assert len(documents) == 2 - - for i, document in enumerate(documents): - assert document.page_content == MOCK_RESPONSE_JSON["elements"][i]["html"] - assert document.metadata["page"] == MOCK_RESPONSE_JSON["elements"][i]["page"] - assert document.metadata["id"] == MOCK_RESPONSE_JSON["elements"][i]["id"] - assert document.metadata["type"] == "html" - assert document.metadata["split"] == "element" - - -@patch("requests.post") -def test_page_split_html_output(mock_post: Mock) -> None: - mock_post.return_value = MagicMock( - status_code=200, json=MagicMock(return_value=MOCK_RESPONSE_JSON) - ) - - loader = UpstageLayoutAnalysisLoader( - file_path=EXAMPLE_PDF_PATH, - output_type="html", - split="page", - api_key="valid_api_key", - exclude=[], - ) - documents = loader.load() - - assert len(documents) == 1 - - for i, document in enumerate(documents): - assert document.metadata["page"] == MOCK_RESPONSE_JSON["elements"][i]["page"] - assert document.metadata["type"] == "html" - assert document.metadata["split"] == "page" - - -@patch("requests.post") -def test_request_exception(mock_post: Mock) -> None: - mock_post.side_effect = requests.RequestException("Mocked request exception") - - loader = UpstageLayoutAnalysisLoader( - file_path=EXAMPLE_PDF_PATH, - output_type="html", - split="page", - api_key="valid_api_key", - exclude=[], - ) - - with TestCase.assertRaises(TestCase(), ValueError) as context: - loader.load() - - assert "Failed to send request: Mocked request exception" == str(context.exception) - - -@patch("requests.post") -def test_json_decode_error(mock_post: Mock) -> None: - mock_response = Mock() - mock_response.status_code = 200 - mock_response.json.side_effect = json.JSONDecodeError("Expecting value", "", 0) - mock_post.return_value = mock_response - - loader = UpstageLayoutAnalysisLoader( - file_path=EXAMPLE_PDF_PATH, - output_type="html", - split="page", - api_key="valid_api_key", - exclude=[], - ) - - with TestCase.assertRaises(TestCase(), ValueError) as context: - loader.load() - - assert ( - "Failed to decode JSON response: Expecting value: line 1 column 1 (char 0)" - == str(context.exception) - ) diff --git a/libs/partners/upstage/tests/unit_tests/test_secrets.py b/libs/partners/upstage/tests/unit_tests/test_secrets.py deleted file mode 100644 index 5a023cfeb9..0000000000 --- a/libs/partners/upstage/tests/unit_tests/test_secrets.py +++ /dev/null @@ -1,13 +0,0 @@ -from langchain_upstage import ChatUpstage, UpstageEmbeddings - - -def test_chat_upstage_secrets() -> None: - o = ChatUpstage(upstage_api_key="foo") - s = str(o) - assert "foo" not in s - - -def test_upstage_embeddings_secrets() -> None: - o = UpstageEmbeddings(model="solar-embedding-1-large", upstage_api_key="foo") - s = str(o) - assert "foo" not in s