diff --git a/libs/upstage/langchain_upstage/chat_models.py b/libs/upstage/langchain_upstage/chat_models.py index c47eba1..b30584b 100644 --- a/libs/upstage/langchain_upstage/chat_models.py +++ b/libs/upstage/langchain_upstage/chat_models.py @@ -1,3 +1,5 @@ +from __future__ import annotations + import os from operator import itemgetter from typing import ( @@ -11,6 +13,7 @@ Tuple, Type, Union, + cast, overload, ) @@ -32,10 +35,9 @@ PydanticToolsParser, ) from langchain_core.outputs import ChatResult -from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough from langchain_core.tools import BaseTool -from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env +from langchain_core.utils import from_env, secret_from_env from langchain_core.utils.function_calling import convert_to_openai_tool from langchain_openai.chat_models.base import ( BaseChatOpenAI, @@ -45,7 +47,9 @@ _DictOrPydanticClass, _is_pydantic_class, ) +from pydantic import BaseModel, Field, SecretStr, model_validator from tokenizers import Tokenizer +from typing_extensions import Self from langchain_upstage.document_parse import UpstageDocumentParseLoader @@ -103,10 +107,23 @@ def _get_ls_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") + upstage_api_key: SecretStr = Field( + default_factory=secret_from_env( + "UPSTAGE_API_KEY", + error_message=( + "You must specify an api key. " + "You can pass it an argument as `api_key=...` or " + "set the environment variable `UPSTAGE_API_KEY`." + ), + ), + 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" + default_factory=from_env( + "UPSTAGE_API_BASE", 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.""" @@ -121,45 +138,38 @@ def _get_ls_params( tokenizer_name: Optional[str] = "upstage/solar-pro-preview-tokenizer" """huggingface tokenizer name. Solar tokenizer is opened in huggingface https://huggingface.co/upstage/solar-pro-preview-tokenizer""" - @root_validator() - def validate_environment(cls, values: Dict) -> Dict: + @model_validator(mode="after") + def validate_environment(self) -> Self: """Validate that api key and python package exists in environment.""" - if values["n"] < 1: + if self.n < 1: raise ValueError("n must be at least 1.") - if values["n"] > 1 and values["streaming"]: + if self.n > 1 and self.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 = { + client_params: dict = { "api_key": ( - values["upstage_api_key"].get_secret_value() - if values["upstage_api_key"] + self.upstage_api_key.get_secret_value() + if self.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"], + "base_url": self.upstage_api_base, + "timeout": self.request_timeout, + "max_retries": self.max_retries, + "default_headers": self.default_headers, + "default_query": self.default_query, } - if not values.get("client"): - sync_specific = {"http_client": values["http_client"]} - values["client"] = openai.OpenAI( + if not (self.client or None): + sync_specific: dict = {"http_client": self.http_client} + self.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( + if not (self.async_client or None): + async_specific: dict = {"http_client": self.http_async_client} + self.async_client = openai.AsyncOpenAI( **client_params, **async_specific ).chat.completions - return values + return self def _get_tokenizer(self) -> Tokenizer: self.tokenizer_name = SOLAR_TOKENIZERS.get(self.model_name, self.tokenizer_name) @@ -222,9 +232,8 @@ def _generate( messages, stop=stop, run_manager=run_manager, **kwargs ) return generate_from_stream(stream_iter) - message_dicts, params = self._create_message_dicts(messages, stop) - params = {**params, **kwargs} - response = self.client.create(messages=message_dicts, **params) + payload = self._get_request_payload(messages, stop=stop, **kwargs) + response = self.client.create(**payload) return self._create_chat_result(response) async def _agenerate( @@ -246,9 +255,8 @@ async def _agenerate( ) return await agenerate_from_stream(stream_iter) - message_dicts, params = self._create_message_dicts(messages, stop) - params = {**params, **kwargs} - response = await self.async_client.create(messages=message_dicts, **params) + payload = self._get_request_payload(messages, stop=stop, **kwargs) + response = await self.async_client.create(**payload) return self._create_chat_result(response) def _using_doc_parsing_model(self, kwargs: Dict[str, Any]) -> bool: @@ -281,6 +289,22 @@ def _parse_documents(self, file_path: str) -> str: document_contents += f"{file_title}:\n{doc.page_content}\n\n" return document_contents + def _get_request_payload( + self, + input_: LanguageModelInput, + *, + stop: Optional[List[str]] = None, + **kwargs: Any, + ) -> dict: + messages = self._convert_input(input_).to_messages() + if stop is not None: + kwargs["stop"] = stop + return { + "messages": [_convert_message_to_dict(m) for m in messages], + **self._default_params, + **kwargs, + } + # TODO: Fix typing. @overload # type: ignore[override] def with_structured_output( @@ -346,7 +370,7 @@ def with_structured_output( .. code-block:: python from langchain_upstage import ChatUpstage - from langchain_core.pydantic_v1 import BaseModel + from pydantic import BaseModel class AnswerWithJustification(BaseModel): @@ -372,7 +396,7 @@ class AnswerWithJustification(BaseModel): .. code-block:: python from langchain_upstage import ChatUpstage - from langchain_core.pydantic_v1 import BaseModel + from pydantic import BaseModel class AnswerWithJustification(BaseModel): @@ -400,8 +424,8 @@ class AnswerWithJustification(BaseModel): .. code-block:: python from langchain_upstage import ChatUpstage - from langchain_core.pydantic_v1 import BaseModel from langchain_core.utils.function_calling import convert_to_openai_tool + from pydantic import BaseModel class AnswerWithJustification(BaseModel): @@ -432,7 +456,7 @@ class AnswerWithJustification(BaseModel): llm = self.bind_tools([schema], tool_choice=tool_name) if is_pydantic_schema: output_parser: OutputParserLike = PydanticToolsParser( - tools=[schema], first_tool_only=True + tools=[cast(type, schema)], first_tool_only=True ) else: output_parser = JsonOutputKeyToolsParser( diff --git a/libs/upstage/langchain_upstage/embeddings.py b/libs/upstage/langchain_upstage/embeddings.py index 5a74b32..49caf79 100644 --- a/libs/upstage/langchain_upstage/embeddings.py +++ b/libs/upstage/langchain_upstage/embeddings.py @@ -1,5 +1,6 @@ +from __future__ import annotations + import logging -import os import warnings from typing import ( Any, @@ -16,18 +17,15 @@ import openai from langchain_core.embeddings import Embeddings -from langchain_core.pydantic_v1 import ( +from langchain_core.utils import from_env, get_pydantic_field_names, secret_from_env +from pydantic import ( BaseModel, - Extra, + ConfigDict, Field, SecretStr, - root_validator, -) -from langchain_core.utils import ( - convert_to_secret_str, - get_from_dict_or_env, - get_pydantic_field_names, + model_validator, ) +from typing_extensions import Self logger = logging.getLogger(__name__) @@ -60,10 +58,23 @@ class UpstageEmbeddings(BaseModel, Embeddings): 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" + upstage_api_key: SecretStr = Field( + default_factory=secret_from_env( + "UPSTAGE_API_KEY", + error_message=( + "You must specify an api key. " + "You can pass it an argument as `api_key=...` or " + "set the environment variable `UPSTAGE_API_KEY`." + ), + ), + alias="api_key", + ) + """Automatically inferred from env are `UPSTAGE_API_KEY` if not provided.""" + upstage_api_base: Optional[str] = Field( + default_factory=from_env( + "UPSTAGE_API_BASE", default="https://api.upstage.ai/v1/solar" + ), + alias="base_url", ) """Endpoint URL to use.""" embedding_ctx_length: int = 4096 @@ -112,12 +123,15 @@ class UpstageEmbeddings(BaseModel, Embeddings): """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 + model_config = ConfigDict( + extra="forbid", + populate_by_name=True, + protected_namespaces=(), + ) - @root_validator(pre=True) - def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]: + @model_validator(mode="before") + @classmethod + def build_extra(cls, values: Dict[str, Any]) -> 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", {}) @@ -142,42 +156,31 @@ def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]: values["model_kwargs"] = extra return values - @root_validator() - def validate_environment(cls, values: Dict) -> Dict: + @model_validator(mode="after") + def validate_environment(self) -> Self: """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 = { + client_params: dict = { "api_key": ( - values["upstage_api_key"].get_secret_value() - if values["upstage_api_key"] + self.upstage_api_key.get_secret_value() + if self.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"], + "base_url": self.upstage_api_base, + "timeout": self.request_timeout, + "max_retries": self.max_retries, + "default_headers": self.default_headers, + "default_query": self.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( + if not (self.client or None): + sync_specific: dict = {"http_client": self.http_client} + self.client = openai.OpenAI(**client_params, **sync_specific).embeddings + if not (self.async_client or None): + async_specific: dict = {"http_client": self.http_async_client} + self.async_client = openai.AsyncOpenAI( **client_params, **async_specific ).embeddings - return values + return self @property def _invocation_params(self) -> Dict[str, Any]: diff --git a/libs/upstage/langchain_upstage/tools/groundedness_check.py b/libs/upstage/langchain_upstage/tools/groundedness_check.py index fa93303..325e024 100644 --- a/libs/upstage/langchain_upstage/tools/groundedness_check.py +++ b/libs/upstage/langchain_upstage/tools/groundedness_check.py @@ -1,5 +1,5 @@ import os -from typing import Any, List, Literal, Optional, Type, Union +from typing import Any, List, Literal, Optional, Type, Union, cast from langchain_core._api.deprecation import deprecated from langchain_core.callbacks import ( @@ -8,9 +8,9 @@ ) 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 pydantic import BaseModel, Field, SecretStr from langchain_upstage import ChatUpstage @@ -52,7 +52,7 @@ class UpstageGroundednessCheck(BaseTool): "the assistant's message is grounded in the provided context." ) upstage_api_key: Optional[SecretStr] = Field(default=None, alias="api_key") - api_wrapper: ChatUpstage + api_wrapper: Optional[ChatUpstage] = None args_schema: Type[BaseModel] = UpstageGroundednessCheckInput @@ -72,8 +72,8 @@ def __init__(self, **kwargs: Any) -> None: 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(), + model="solar-1-mini-answer-verification", + api_key=upstage_api_key.get_secret_value(), ) super().__init__(upstage_api_key=upstage_api_key, api_wrapper=api_wrapper) @@ -89,7 +89,8 @@ def _run( """Use the tool.""" if isinstance(context, List): context = self.formatDocumentsAsString(context) - response = self.api_wrapper.invoke( + api_wrapper = cast(ChatUpstage, self.api_wrapper) + response = api_wrapper.invoke( [HumanMessage(context), AIMessage(answer)], stream=False ) return str(response.content) @@ -102,7 +103,8 @@ async def _arun( ) -> Union[str, Literal["grounded", "notGrounded", "notSure"]]: if isinstance(context, List): context = self.formatDocumentsAsString(context) - response = await self.api_wrapper.ainvoke( + api_wrapper = cast(ChatUpstage, self.api_wrapper) + response = await api_wrapper.ainvoke( [HumanMessage(context), AIMessage(answer)], stream=False ) return str(response.content) diff --git a/libs/upstage/poetry.lock b/libs/upstage/poetry.lock index f4aaee5..62f804c 100644 --- a/libs/upstage/poetry.lock +++ b/libs/upstage/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. [[package]] name = "annotated-types" @@ -11,9 +11,6 @@ files = [ {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, ] -[package.dependencies] -typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""} - [[package]] name = "anyio" version = "4.4.0" @@ -514,65 +511,55 @@ files = [ [[package]] name = "langchain-core" -version = "0.2.38" +version = "0.3.0" description = "Building applications with LLMs through composability" optional = false -python-versions = ">=3.8.1,<4.0" -files = [] -develop = false +python-versions = "<4.0,>=3.9" +files = [ + {file = "langchain_core-0.3.0-py3-none-any.whl", hash = "sha256:bee6dae2366d037ef0c5b87401fed14b5497cad26f97724e8c9ca7bc9239e847"}, + {file = "langchain_core-0.3.0.tar.gz", hash = "sha256:1249149ea3ba24c9c761011483c14091573a5eb1a773aa0db9c8ad155dd4a69d"}, +] [package.dependencies] -jsonpatch = "^1.33" -langsmith = "^0.1.75" +jsonpatch = ">=1.33,<2.0" 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authors = [] readme = "README.md" @@ -11,13 +11,12 @@ license = "MIT" "Source Code" = "https://github.com/langchain-ai/langchain-upstage/tree/main/libs/upstage" [tool.poetry.dependencies] -python = ">=3.8.1,<4.0" -langchain-core = ">=0.2.35,<0.3" -langchain-openai = "0.1.23" +python = ">=3.9,<4.0" pypdf = "^4.2.0" requests = "^2.31.0" tokenizers = "^0.19.1" -pydantic = "^2.8.0" +langchain-openai = "^0.2" +langchain-core = ">=0.3.0,<0.4" [tool.poetry.group.test] optional = true @@ -32,8 +31,6 @@ pytest-mock = "^3.10.0" syrupy = "^4.0.2" pytest-watcher = "^0.3.4" pytest-asyncio = "^0.21.1" -langchain-openai = { git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/openai" } -langchain-core = { git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/core" } docarray = "^0.32.1" langchain-standard-tests = { git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/standard-tests" } @@ -50,9 +47,8 @@ optional = true ruff = "^0.1.5" [tool.poetry.group.typing.dependencies] -mypy = "^0.991" +mypy = "^1.11" types-requests = ">=2.31.0" -langchain-core = { git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/core" } [tool.poetry.group.test_integration.dependencies] httpx = "^0.27.0" @@ -71,7 +67,6 @@ python = ">=3.12" optional = true [tool.poetry.group.dev.dependencies] -langchain-core = { git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/core" } [tool.ruff.lint] select = [ diff --git a/libs/upstage/scripts/check_pydantic.sh b/libs/upstage/scripts/check_pydantic.sh deleted file mode 100755 index 06b5bb8..0000000 --- a/libs/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/upstage/tests/integration_tests/test_chat_models.py b/libs/upstage/tests/integration_tests/test_chat_models.py index e0a1ba5..656dbc4 100644 --- a/libs/upstage/tests/integration_tests/test_chat_models.py +++ b/libs/upstage/tests/integration_tests/test_chat_models.py @@ -4,14 +4,6 @@ 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) @@ -51,30 +43,6 @@ def test_chat_upstage_invalid_streaming_params() -> None: ) -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() diff --git a/libs/upstage/tests/integration_tests/test_groundedness_check.py b/libs/upstage/tests/integration_tests/test_groundedness_check.py index d4b56d7..81e7737 100644 --- a/libs/upstage/tests/integration_tests/test_groundedness_check.py +++ b/libs/upstage/tests/integration_tests/test_groundedness_check.py @@ -16,7 +16,7 @@ def test_langchain_upstage_groundedness_check_deprecated() -> None: api_key = os.environ.get("UPSTAGE_API_KEY", None) - tool = GroundednessCheck(upstage_api_key=api_key) + tool = GroundednessCheck(api_key=api_key) # type: ignore[arg-type] output = tool.invoke({"context": "foo bar", "answer": "bar foo"}) assert output in ["grounded", "notGrounded", "notSure"] @@ -31,7 +31,7 @@ def test_langchain_upstage_groundedness_check() -> None: api_key = os.environ.get("UPSTAGE_API_KEY", None) - tool = UpstageGroundednessCheck(upstage_api_key=api_key) + tool = UpstageGroundednessCheck(api_key=api_key) output = tool.invoke({"context": "foo bar", "answer": "bar foo"}) assert output in ["grounded", "notGrounded", "notSure"] diff --git a/libs/upstage/tests/unit_tests/test_chat_models.py b/libs/upstage/tests/unit_tests/test_chat_models.py index 2cfa56d..4a8690c 100644 --- a/libs/upstage/tests/unit_tests/test_chat_models.py +++ b/libs/upstage/tests/unit_tests/test_chat_models.py @@ -29,7 +29,7 @@ def test_initialization() -> None: def test_upstage_model_param() -> None: llm = ChatUpstage(model="foo") assert llm.model_name == "foo" - llm = ChatUpstage(model_name="foo") + llm = ChatUpstage(model_name="foo") # type: ignore assert llm.model_name == "foo" ls_params = llm._get_ls_params() assert ls_params["ls_provider"] == "upstage" @@ -150,7 +150,7 @@ def mock_create(*args: Any, **kwargs: Any) -> Any: def test_upstage_invoke_with_doc_parsing_model(mock_completion: dict) -> None: # TODO: update model_name - llm = ChatUpstage(model_name="solar-pro") + llm = ChatUpstage(model="solar-pro") mock_client = MagicMock() completed = False @@ -196,7 +196,7 @@ async def mock_create(*args: Any, **kwargs: Any) -> Any: async def test_upstage_ainvoke_with_doc_parsing_model(mock_completion: dict) -> None: # TODO: update model_name - llm = ChatUpstage(model_name="solar-pro") + llm = ChatUpstage(model="solar-pro") mock_client = AsyncMock() completed = False @@ -256,3 +256,27 @@ def test_upstage_tokenizer_get_num_tokens() -> None: llm = ChatUpstage(model="solar-1-mini-chat") num_tokens = llm.get_num_tokens_from_messages([HumanMessage(content="Hello World")]) assert num_tokens == 12 + + +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) # type: ignore + 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}) # type: ignore + 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}) # type: ignore + + # 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"}) diff --git a/libs/upstage/tests/unit_tests/test_chat_models_standard.py b/libs/upstage/tests/unit_tests/test_chat_models_standard.py index b19260d..89b7ece 100644 --- a/libs/upstage/tests/unit_tests/test_chat_models_standard.py +++ b/libs/upstage/tests/unit_tests/test_chat_models_standard.py @@ -1,6 +1,6 @@ """Standard LangChain interface tests""" -from typing import Type +from typing import Tuple, Type from langchain_core.language_models import BaseChatModel from langchain_standard_tests.unit_tests import ChatModelUnitTests @@ -18,3 +18,17 @@ def chat_model_params(self) -> dict: return { "model": "solar-1-mini-chat", } + + @property + def init_from_env_params(self) -> Tuple[dict, dict, dict]: + return ( + { + "UPSTAGE_API_KEY": "api_key", + "UPSTAGE_API_BASE": "https://base.com", + }, + {}, + { + "upstage_api_key": "api_key", + "upstage_api_base": "https://base.com", + }, + ) diff --git a/libs/upstage/tests/unit_tests/test_embeddings.py b/libs/upstage/tests/unit_tests/test_embeddings.py index 8a838a6..89f7353 100644 --- a/libs/upstage/tests/unit_tests/test_embeddings.py +++ b/libs/upstage/tests/unit_tests/test_embeddings.py @@ -23,10 +23,10 @@ def test_upstage_invalid_model_kwargs() -> None: def test_upstage_invalid_model() -> None: with pytest.raises(ValueError): - UpstageEmbeddings() + UpstageEmbeddings() # type: ignore[call-arg] def test_upstage_incorrect_field() -> None: with pytest.warns(match="not default parameter"): - llm = UpstageEmbeddings(model="solar-embedding-1-large", foo="bar") + llm = UpstageEmbeddings(model="solar-embedding-1-large", foo="bar") # type: ignore assert llm.model_kwargs == {"foo": "bar"} diff --git a/libs/upstage/tests/unit_tests/test_embeddings_standard.py b/libs/upstage/tests/unit_tests/test_embeddings_standard.py new file mode 100644 index 0000000..55f53c5 --- /dev/null +++ b/libs/upstage/tests/unit_tests/test_embeddings_standard.py @@ -0,0 +1,36 @@ +"""Standard LangChain interface tests""" + +from typing import Tuple, Type + +from langchain_core.embeddings import Embeddings +from langchain_standard_tests.unit_tests.embeddings import EmbeddingsUnitTests + +from langchain_upstage import UpstageEmbeddings + + +class TestUpstageStandard(EmbeddingsUnitTests): + @property + def embeddings_class(self) -> Type[Embeddings]: + return UpstageEmbeddings + + @property + def embedding_model_params(self) -> dict: + return { + "model": "solar-embedding-1-large", + } + + @property + def init_from_env_params(self) -> Tuple[dict, dict, dict]: + return ( + { + "UPSTAGE_API_KEY": "api_key", + "UPSTAGE_API_BASE": "https://base.com", + }, + { + "model": "solar-embedding-1-large", + }, + { + "upstage_api_key": "api_key", + "upstage_api_base": "https://base.com", + }, + ) diff --git a/libs/upstage/tests/unit_tests/test_groundedness_check.py b/libs/upstage/tests/unit_tests/test_groundedness_check.py index fdb0502..5e56463 100644 --- a/libs/upstage/tests/unit_tests/test_groundedness_check.py +++ b/libs/upstage/tests/unit_tests/test_groundedness_check.py @@ -8,5 +8,5 @@ def test_initialization() -> None: """Test embedding model initialization.""" UpstageGroundednessCheck() - UpstageGroundednessCheck(upstage_api_key="key") + UpstageGroundednessCheck(upstage_api_key="key") # type: ignore[call-arg] UpstageGroundednessCheck(api_key="key") diff --git a/libs/upstage/tests/unit_tests/test_secrets.py b/libs/upstage/tests/unit_tests/test_secrets.py index 5a023cf..d0792f1 100644 --- a/libs/upstage/tests/unit_tests/test_secrets.py +++ b/libs/upstage/tests/unit_tests/test_secrets.py @@ -2,12 +2,12 @@ def test_chat_upstage_secrets() -> None: - o = ChatUpstage(upstage_api_key="foo") + o = ChatUpstage(api_key="foo") # type: ignore[arg-type] 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") + o = UpstageEmbeddings(model="solar-embedding-1-large", api_key="foo") # type: ignore[arg-type] s = str(o) assert "foo" not in s