From 43c35d19d48555b98d66d3750e428d7a9dfe6dde Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 5 Dec 2024 00:38:32 -0800 Subject: [PATCH 001/157] cli: standard tests in cli, test that they run, skip vectorstore tests (#28521) --- .github/scripts/check_diff.py | 6 +- libs/cli/.gitignore | 2 + libs/cli/Makefile | 51 +- libs/cli/langchain_cli/dev_scripts.py | 1 + .../integration_template/Makefile | 4 +- .../integration_template/__init__.py | 10 +- .../integration_template/chat_models.py | 155 ++- .../integration_template/embeddings.py | 34 +- .../integration_template/llms.py | 155 --- .../integration_template/retrievers.py | 28 +- .../integration_template/toolkits.py | 4 +- .../integration_template/tools.py | 23 +- .../integration_template/vectorstores.py | 166 +-- .../integration_template/pyproject.toml | 25 +- .../integration_tests/test_chat_models.py | 79 +- .../integration_tests/test_embeddings.py | 24 +- .../tests/integration_tests/test_llms.py | 64 - .../integration_tests/test_retrievers.py | 24 + .../tests/integration_tests/test_tools.py | 27 + .../integration_tests/test_vectorstores.py | 37 + .../tests/unit_tests/test_chat_models.py | 19 +- .../tests/unit_tests/test_embeddings.py | 14 +- .../tests/unit_tests/test_imports.py | 12 - .../tests/unit_tests/test_llms.py | 8 - .../tests/unit_tests/test_tools.py | 27 + .../tests/unit_tests/test_vectorstores.py | 6 - .../langchain_cli/namespaces/integration.py | 41 +- .../namespaces/migrate/generate/utils.py | 6 +- .../langchain_cli/namespaces/migrate/main.py | 2 +- libs/cli/langchain_cli/utils/find_replace.py | 4 +- libs/cli/poetry.lock | 1121 +++++++++++++++-- libs/cli/pyproject.toml | 25 +- libs/cli/scripts/generate_migrations.py | 1 + .../tests/integration_tests/test_compile.py | 7 + .../unit_tests/migrate/cli_runner/test_cli.py | 1 + .../integration_tests/__init__.py | 1 + 36 files changed, 1578 insertions(+), 636 deletions(-) delete mode 100644 libs/cli/langchain_cli/integration_template/integration_template/llms.py delete mode 100644 libs/cli/langchain_cli/integration_template/tests/integration_tests/test_llms.py create mode 100644 libs/cli/langchain_cli/integration_template/tests/integration_tests/test_retrievers.py create mode 100644 libs/cli/langchain_cli/integration_template/tests/integration_tests/test_tools.py create mode 100644 libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py delete mode 100644 libs/cli/langchain_cli/integration_template/tests/unit_tests/test_imports.py delete mode 100644 libs/cli/langchain_cli/integration_template/tests/unit_tests/test_llms.py create mode 100644 libs/cli/langchain_cli/integration_template/tests/unit_tests/test_tools.py delete mode 100644 libs/cli/langchain_cli/integration_template/tests/unit_tests/test_vectorstores.py create mode 100644 libs/cli/tests/integration_tests/test_compile.py diff --git a/.github/scripts/check_diff.py b/.github/scripts/check_diff.py index fbbe47aa4a99b..873a98d158c71 100644 --- a/.github/scripts/check_diff.py +++ b/.github/scripts/check_diff.py @@ -272,6 +272,7 @@ def _get_configs_for_multi_dirs( # TODO: update to include all packages that rely on standard-tests (all partner packages) # note: won't run on external repo partners dirs_to_run["lint"].add("libs/standard-tests") + dirs_to_run["test"].add("libs/standard-tests") dirs_to_run["test"].add("libs/partners/mistralai") dirs_to_run["test"].add("libs/partners/openai") dirs_to_run["test"].add("libs/partners/anthropic") @@ -279,8 +280,9 @@ def _get_configs_for_multi_dirs( dirs_to_run["test"].add("libs/partners/groq") elif file.startswith("libs/cli"): - # todo: add cli makefile - pass + dirs_to_run["lint"].add("libs/cli") + dirs_to_run["test"].add("libs/cli") + elif file.startswith("libs/partners"): partner_dir = file.split("/")[2] if os.path.isdir(f"libs/partners/{partner_dir}") and [ diff --git a/libs/cli/.gitignore b/libs/cli/.gitignore index 68bc17f9ff210..413adb3d0f4fc 100644 --- a/libs/cli/.gitignore +++ b/libs/cli/.gitignore @@ -158,3 +158,5 @@ cython_debug/ # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ + +.integration_test diff --git a/libs/cli/Makefile b/libs/cli/Makefile index 445235c22c841..ac855bd4dc58a 100644 --- a/libs/cli/Makefile +++ b/libs/cli/Makefile @@ -1,8 +1,47 @@ -lint lint_diff: - poetry run poe lint -test: - poetry run poe test +###################### +# LINTING AND FORMATTING +###################### -format: - poetry run poe format +# 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/cli --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$') +lint_package: PYTHON_FILES=langchain_cli +lint_tests: PYTHON_FILES=tests +lint_tests: MYPY_CACHE=.mypy_cache_test + +lint lint_diff lint_package lint_tests: + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff check $(PYTHON_FILES) + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff + [ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE) + +format format_diff: + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --select I --fix $(PYTHON_FILES) + +test tests: _test _e2e_test + +PYTHON = .venv/bin/python + +_test: + poetry run pytest tests + +# custom integration testing for cli integration flow +# currently ignores vectorstores test because lacks implementation +_e2e_test: + rm -rf .integration_test + mkdir .integration_test + cd .integration_test && \ + python3 -m venv .venv && \ + $(PYTHON) -m pip install --upgrade poetry && \ + $(PYTHON) -m pip install -e .. && \ + $(PYTHON) -m langchain_cli.cli integration new --name parrot-link --name-class ParrotLink && \ + cd langchain-parrot-link && \ + poetry install --with lint,typing,test && \ + poetry run pip install -e ../../../standard-tests && \ + make format lint tests && \ + poetry install --with test_integration && \ + rm tests/integration_tests/test_vectorstores.py && \ + make integration_test diff --git a/libs/cli/langchain_cli/dev_scripts.py b/libs/cli/langchain_cli/dev_scripts.py index cccd9689e4482..ebb9331a9c61e 100644 --- a/libs/cli/langchain_cli/dev_scripts.py +++ b/libs/cli/langchain_cli/dev_scripts.py @@ -1,3 +1,4 @@ +# type: ignore """ Development Scripts for template packages """ diff --git a/libs/cli/langchain_cli/integration_template/Makefile b/libs/cli/langchain_cli/integration_template/Makefile index b30039ace1fe0..4c4bbf237d9dc 100644 --- a/libs/cli/langchain_cli/integration_template/Makefile +++ b/libs/cli/langchain_cli/integration_template/Makefile @@ -33,13 +33,13 @@ lint_tests: PYTHON_FILES=tests lint_tests: MYPY_CACHE=.mypy_cache_test lint lint_diff lint_package lint_tests: - [ "$(PYTHON_FILES)" = "" ] || poetry run ruff $(PYTHON_FILES) + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff check $(PYTHON_FILES) [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff [ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE) format format_diff: [ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) - [ "$(PYTHON_FILES)" = "" ] || poetry run ruff --select I --fix $(PYTHON_FILES) + [ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --select I --fix $(PYTHON_FILES) spell_check: poetry run codespell --toml pyproject.toml diff --git a/libs/cli/langchain_cli/integration_template/integration_template/__init__.py b/libs/cli/langchain_cli/integration_template/integration_template/__init__.py index 60d8dac5d007b..44bec467eaa90 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/__init__.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/__init__.py @@ -1,8 +1,11 @@ from importlib import metadata from __module_name__.chat_models import Chat__ModuleName__ +from __module_name__.document_loaders import __ModuleName__Loader from __module_name__.embeddings import __ModuleName__Embeddings -from __module_name__.llms import __ModuleName__LLM +from __module_name__.retrievers import __ModuleName__Retriever +from __module_name__.toolkits import __ModuleName__Toolkit +from __module_name__.tools import __ModuleName__Tool from __module_name__.vectorstores import __ModuleName__VectorStore try: @@ -14,8 +17,11 @@ __all__ = [ "Chat__ModuleName__", - "__ModuleName__LLM", "__ModuleName__VectorStore", "__ModuleName__Embeddings", + "__ModuleName__Loader", + "__ModuleName__Retriever", + "__ModuleName__Toolkit", + "__ModuleName__Tool", "__version__", ] diff --git a/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py b/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py index d299fb2ff26d1..917feb2df0ba2 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py @@ -1,13 +1,19 @@ """__ModuleName__ chat models.""" -from typing import Any, List, Optional +from typing import Any, Dict, Iterator, List, Optional from langchain_core.callbacks import ( CallbackManagerForLLMRun, ) -from langchain_core.language_models.chat_models import BaseChatModel -from langchain_core.messages import BaseMessage -from langchain_core.outputs import ChatResult +from langchain_core.language_models import BaseChatModel +from langchain_core.messages import ( + AIMessage, + AIMessageChunk, + BaseMessage, +) +from langchain_core.messages.ai import UsageMetadata +from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult +from pydantic import Field class Chat__ModuleName__(BaseChatModel): @@ -15,6 +21,8 @@ class Chat__ModuleName__(BaseChatModel): # https://github.com/langchain-ai/langchain/blob/7ff05357bac6eaedf5058a2af88f23a1817d40fe/libs/partners/openai/langchain_openai/chat_models/base.py#L1120 """__ModuleName__ chat model integration. + The default implementation echoes the first `parrot_buffer_length` characters of the input. + # TODO: Replace with relevant packages, env vars. Setup: Install ``__package_name__`` and set environment variable ``__MODULE_NAME___API_KEY``. @@ -258,7 +266,36 @@ class Joke(BaseModel): """ # noqa: E501 - # TODO: This method must be implemented to generate chat responses. + model_name: str = Field(alias="model") + """The name of the model""" + parrot_buffer_length: int + """The number of characters from the last message of the prompt to be echoed.""" + temperature: Optional[float] = None + max_tokens: Optional[int] = None + timeout: Optional[int] = None + stop: Optional[List[str]] = None + max_retries: int = 2 + + @property + def _llm_type(self) -> str: + """Return type of chat model.""" + return "chat-__package_name_short__" + + @property + def _identifying_params(self) -> Dict[str, Any]: + """Return a dictionary of identifying parameters. + + This information is used by the LangChain callback system, which + is used for tracing purposes make it possible to monitor LLMs. + """ + return { + # The model name allows users to specify custom token counting + # rules in LLM monitoring applications (e.g., in LangSmith users + # can provide per token pricing for their model and monitor + # costs for the given LLM.) + "model_name": self.model_name, + } + def _generate( self, messages: List[BaseMessage], @@ -266,16 +303,101 @@ def _generate( run_manager: Optional[CallbackManagerForLLMRun] = None, **kwargs: Any, ) -> ChatResult: - raise NotImplementedError() + """Override the _generate method to implement the chat model logic. + + This can be a call to an API, a call to a local model, or any other + implementation that generates a response to the input prompt. + + Args: + messages: the prompt composed of a list of messages. + stop: a list of strings on which the model should stop generating. + If generation stops due to a stop token, the stop token itself + SHOULD BE INCLUDED as part of the output. This is not enforced + across models right now, but it's a good practice to follow since + it makes it much easier to parse the output of the model + downstream and understand why generation stopped. + run_manager: A run manager with callbacks for the LLM. + """ + # Replace this with actual logic to generate a response from a list + # of messages. + last_message = messages[-1] + tokens = last_message.content[: self.parrot_buffer_length] + ct_input_tokens = sum(len(message.content) for message in messages) + ct_output_tokens = len(tokens) + message = AIMessage( + content=tokens, + additional_kwargs={}, # Used to add additional payload to the message + response_metadata={ # Use for response metadata + "time_in_seconds": 3, + }, + usage_metadata={ + "input_tokens": ct_input_tokens, + "output_tokens": ct_output_tokens, + "total_tokens": ct_input_tokens + ct_output_tokens, + }, + ) + ## + + generation = ChatGeneration(message=message) + return ChatResult(generations=[generation]) + + def _stream( + self, + messages: List[BaseMessage], + stop: Optional[List[str]] = None, + run_manager: Optional[CallbackManagerForLLMRun] = None, + **kwargs: Any, + ) -> Iterator[ChatGenerationChunk]: + """Stream the output of the model. + + This method should be implemented if the model can generate output + in a streaming fashion. If the model does not support streaming, + do not implement it. In that case streaming requests will be automatically + handled by the _generate method. + + Args: + messages: the prompt composed of a list of messages. + stop: a list of strings on which the model should stop generating. + If generation stops due to a stop token, the stop token itself + SHOULD BE INCLUDED as part of the output. This is not enforced + across models right now, but it's a good practice to follow since + it makes it much easier to parse the output of the model + downstream and understand why generation stopped. + run_manager: A run manager with callbacks for the LLM. + """ + last_message = messages[-1] + tokens = str(last_message.content[: self.parrot_buffer_length]) + ct_input_tokens = sum(len(message.content) for message in messages) + + for token in tokens: + usage_metadata = UsageMetadata( + { + "input_tokens": ct_input_tokens, + "output_tokens": 1, + "total_tokens": ct_input_tokens + 1, + } + ) + ct_input_tokens = 0 + chunk = ChatGenerationChunk( + message=AIMessageChunk(content=token, usage_metadata=usage_metadata) + ) - # TODO: Implement if Chat__ModuleName__ supports streaming. Otherwise delete method. - # def _stream( - # self, - # messages: List[BaseMessage], - # stop: Optional[List[str]] = None, - # run_manager: Optional[CallbackManagerForLLMRun] = None, - # **kwargs: Any, - # ) -> Iterator[ChatGenerationChunk]: + if run_manager: + # This is optional in newer versions of LangChain + # The on_llm_new_token will be called automatically + run_manager.on_llm_new_token(token, chunk=chunk) + + yield chunk + + # Let's add some other information (e.g., response metadata) + chunk = ChatGenerationChunk( + message=AIMessageChunk(content="", response_metadata={"time_in_sec": 3}) + ) + if run_manager: + # This is optional in newer versions of LangChain + # The on_llm_new_token will be called automatically + run_manager.on_llm_new_token(token, chunk=chunk) + yield chunk # TODO: Implement if Chat__ModuleName__ supports async streaming. Otherwise delete. # async def _astream( @@ -294,8 +416,3 @@ def _generate( # run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, # **kwargs: Any, # ) -> ChatResult: - - @property - def _llm_type(self) -> str: - """Return type of chat model.""" - return "chat-__package_name_short__" diff --git a/libs/cli/langchain_cli/integration_template/integration_template/embeddings.py b/libs/cli/langchain_cli/integration_template/integration_template/embeddings.py index 174c567da8df1..5df2bbfbd402c 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/embeddings.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/embeddings.py @@ -8,7 +8,8 @@ class __ModuleName__Embeddings(Embeddings): # TODO: Replace with relevant packages, env vars. Setup: - Install ``__package_name__`` and set environment variable ``__MODULE_NAME___API_KEY``. + Install ``__package_name__`` and set environment variable + ``__MODULE_NAME___API_KEY``. .. code-block:: bash @@ -70,21 +71,26 @@ class __ModuleName__Embeddings(Embeddings): """ + def __init__(self, model: str): + self.model = model + def embed_documents(self, texts: List[str]) -> List[List[float]]: """Embed search docs.""" - raise NotImplementedError + return [[0.5, 0.6, 0.7] for _ in texts] def embed_query(self, text: str) -> List[float]: """Embed query text.""" - raise NotImplementedError - - # only keep aembed_documents and aembed_query if they're implemented! - # delete them otherwise to use the base class' default - # implementation, which calls the sync version in an executor - async def aembed_documents(self, texts: List[str]) -> List[List[float]]: - """Asynchronous Embed search docs.""" - raise NotImplementedError - - async def aembed_query(self, text: str) -> List[float]: - """Asynchronous Embed query text.""" - raise NotImplementedError + return self.embed_documents([text])[0] + + # optional: add custom async implementations here + # you can also delete these, and the base class will + # use the default implementation, which calls the sync + # version in an async executor: + + # async def aembed_documents(self, texts: List[str]) -> List[List[float]]: + # """Asynchronous Embed search docs.""" + # ... + + # async def aembed_query(self, text: str) -> List[float]: + # """Asynchronous Embed query text.""" + # ... diff --git a/libs/cli/langchain_cli/integration_template/integration_template/llms.py b/libs/cli/langchain_cli/integration_template/integration_template/llms.py deleted file mode 100644 index 2dbe4ac918362..0000000000000 --- a/libs/cli/langchain_cli/integration_template/integration_template/llms.py +++ /dev/null @@ -1,155 +0,0 @@ -"""__ModuleName__ large language models.""" - -from typing import ( - Any, - List, - Optional, -) - -from langchain_core.callbacks import ( - CallbackManagerForLLMRun, -) -from langchain_core.language_models import BaseLLM -from langchain_core.outputs import LLMResult - - -class __ModuleName__LLM(BaseLLM): - """__ModuleName__ completion model integration. - - # TODO: Replace with relevant packages, env vars. - Setup: - Install ``__package_name__`` and set environment variable ``__MODULE_NAME___API_KEY``. - - .. code-block:: bash - - pip install -U __package_name__ - export __MODULE_NAME___API_KEY="your-api-key" - - # TODO: Populate with relevant params. - Key init args — completion params: - model: str - Name of __ModuleName__ model to use. - temperature: float - Sampling temperature. - max_tokens: Optional[int] - Max number of tokens to generate. - - # TODO: Populate with relevant params. - Key init args — client params: - timeout: Optional[float] - Timeout for requests. - max_retries: int - Max number of retries. - api_key: Optional[str] - __ModuleName__ API key. If not passed in will be read from env var __MODULE_NAME___API_KEY. - - See full list of supported init args and their descriptions in the params section. - - # TODO: Replace with relevant init params. - Instantiate: - .. code-block:: python - - from __module_name__ import __ModuleName__LLM - - llm = __ModuleName__LLM( - model="...", - temperature=0, - max_tokens=None, - timeout=None, - max_retries=2, - # api_key="...", - # other params... - ) - - Invoke: - .. code-block:: python - - input_text = "The meaning of life is " - llm.invoke(input_text) - - .. code-block:: python - - # TODO: Example output. - - # TODO: Delete if token-level streaming isn't supported. - Stream: - .. code-block:: python - - for chunk in llm.stream(input_text): - print(chunk) - - .. code-block:: python - - # TODO: Example output. - - .. code-block:: python - - ''.join(llm.stream(input_text)) - - .. code-block:: python - - # TODO: Example output. - - # TODO: Delete if native async isn't supported. - Async: - .. code-block:: python - - await llm.ainvoke(input_text) - - # stream: - # async for chunk in (await llm.astream(input_text)) - - # batch: - # await llm.abatch([input_text]) - - .. code-block:: python - - # TODO: Example output. - """ - - # TODO: This method must be implemented to generate text completions. - def _generate( - self, - prompts: List[str], - stop: Optional[List[str]] = None, - run_manager: Optional[CallbackManagerForLLMRun] = None, - **kwargs: Any, - ) -> LLMResult: - raise NotImplementedError - - # TODO: Implement if __ModuleName__LLM supports async generation. Otherwise - # delete method. - # async def _agenerate( - # self, - # prompts: List[str], - # stop: Optional[List[str]] = None, - # run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, - # **kwargs: Any, - # ) -> LLMResult: - # raise NotImplementedError - - # TODO: Implement if __ModuleName__LLM supports streaming. Otherwise delete method. - # def _stream( - # self, - # prompt: str, - # stop: Optional[List[str]] = None, - # run_manager: Optional[CallbackManagerForLLMRun] = None, - # **kwargs: Any, - # ) -> Iterator[GenerationChunk]: - # raise NotImplementedError - - # TODO: Implement if __ModuleName__LLM supports async streaming. Otherwise delete - # method. - # async def _astream( - # self, - # prompt: str, - # stop: Optional[List[str]] = None, - # run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, - # **kwargs: Any, - # ) -> AsyncIterator[GenerationChunk]: - # raise NotImplementedError - - @property - def _llm_type(self) -> str: - """Return type of LLM.""" - return "__package_name_short__-llm" diff --git a/libs/cli/langchain_cli/integration_template/integration_template/retrievers.py b/libs/cli/langchain_cli/integration_template/integration_template/retrievers.py index c48661873c8eb..242103f3a4056 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/retrievers.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/retrievers.py @@ -1,7 +1,8 @@ """__ModuleName__ retrievers.""" -from typing import List +from typing import Any, List +from langchain_core.callbacks import CallbackManagerForRetrieverRun from langchain_core.documents import Document from langchain_core.retrievers import BaseRetriever @@ -13,7 +14,8 @@ class __ModuleName__Retriever(BaseRetriever): # TODO: Replace with relevant packages, env vars, etc. Setup: - Install ``__package_name__`` and set environment variable ``__MODULE_NAME___API_KEY``. + Install ``__package_name__`` and set environment variable + ``__MODULE_NAME___API_KEY``. .. code-block:: bash @@ -82,8 +84,24 @@ def format_docs(docs): # TODO: Example output. - """ # noqa: E501 + """ + + k: int = 3 # TODO: This method must be implemented to retrieve documents. - def _get_relevant_documents(self, query: str) -> List[Document]: - raise NotImplementedError() + def _get_relevant_documents( + self, query: str, *, run_manager: CallbackManagerForRetrieverRun, **kwargs: Any + ) -> List[Document]: + k = kwargs.get("k", self.k) + return [ + Document(page_content=f"Result {i} for query: {query}") for i in range(k) + ] + + # optional: add custom async implementations here + # async def _aget_relevant_documents( + # self, + # query: str, + # *, + # run_manager: AsyncCallbackManagerForRetrieverRun, + # **kwargs: Any, + # ) -> List[Document]: ... diff --git a/libs/cli/langchain_cli/integration_template/integration_template/toolkits.py b/libs/cli/langchain_cli/integration_template/integration_template/toolkits.py index 5a80398891167..b3eda23bd2343 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/toolkits.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/toolkits.py @@ -2,10 +2,10 @@ from typing import List -from langchain_core.tools import BaseTool, BaseToolKit +from langchain_core.tools import BaseTool, BaseToolkit -class __ModuleName__Toolkit(BaseToolKit): +class __ModuleName__Toolkit(BaseToolkit): # TODO: Replace all TODOs in docstring. See example docstring: # https://github.com/langchain-ai/langchain/blob/c123cb2b304f52ab65db4714eeec46af69a861ec/libs/community/langchain_community/agent_toolkits/sql/toolkit.py#L19 """__ModuleName__ toolkit. diff --git a/libs/cli/langchain_cli/integration_template/integration_template/tools.py b/libs/cli/langchain_cli/integration_template/integration_template/tools.py index 57deb006f062a..1904c9865b76c 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/tools.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/tools.py @@ -6,10 +6,10 @@ CallbackManagerForToolRun, ) from langchain_core.tools import BaseTool -from pydantic import BaseModel +from pydantic import BaseModel, Field -class __ModuleName__Input(BaseModel): +class __ModuleName__ToolInput(BaseModel): """Input schema for __ModuleName__ tool. This docstring is **not** part of what is sent to the model when performing tool @@ -18,12 +18,11 @@ class __ModuleName__Input(BaseModel): """ # TODO: Add input args and descriptions. - # a: int = Field(..., description="first number") - # b: int = Field(0, description="second number") - ... + a: int = Field(..., description="first number to add") + b: int = Field(..., description="second number to add") -class __ModuleName__Tool(BaseTool): +class __ModuleName__Tool(BaseTool): # type: ignore[override] """__ModuleName__ tool. Setup: @@ -69,24 +68,26 @@ class __ModuleName__Tool(BaseTool): """The name that is passed to the model when performing tool calling.""" description: str = "TODO: Tool description." """The description that is passed to the model when performing tool calling.""" - args_schema: Type[BaseModel] = __ModuleName__Input + args_schema: Type[BaseModel] = __ModuleName__ToolInput """The schema that is passed to the model when performing tool calling.""" # TODO: Add any other init params for the tool. # param1: Optional[str] # """param1 determines foobar""" - # TODO: Replaced *args with real tool arguments. + # TODO: Replaced (a, b) with real tool arguments. def _run( - self, *args, run_manager: Optional[CallbackManagerForToolRun] = None + self, a: int, b: int, *, run_manager: Optional[CallbackManagerForToolRun] = None ) -> str: - raise NotImplementedError + return str(a + b + 80) # TODO: Implement if tool has native async functionality, otherwise delete. # async def _arun( # self, - # *args, + # a: int, + # b: int, + # *, # run_manager: Optional[AsyncCallbackManagerForToolRun] = None, # ) -> str: # ... diff --git a/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py b/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py index 4236e8c037e73..02ab2c7fccd93 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py @@ -2,8 +2,6 @@ from __future__ import annotations -import asyncio -from functools import partial from typing import ( TYPE_CHECKING, Any, @@ -160,6 +158,8 @@ class __ModuleName__VectorStore(VectorStore): """ # noqa: E501 + _database: dict[str, tuple[Document, list[float]]] = {} + def add_texts( self, texts: Iterable[str], @@ -168,65 +168,70 @@ def add_texts( ) -> List[str]: raise NotImplementedError - async def aadd_texts( - self, - texts: Iterable[str], - metadatas: Optional[List[dict]] = None, - **kwargs: Any, - ) -> List[str]: - return await asyncio.get_running_loop().run_in_executor( - None, partial(self.add_texts, **kwargs), texts, metadatas - ) + # optional: add custom async implementations + # async def aadd_texts( + # self, + # texts: Iterable[str], + # metadatas: Optional[List[dict]] = None, + # **kwargs: Any, + # ) -> List[str]: + # return await asyncio.get_running_loop().run_in_executor( + # None, partial(self.add_texts, **kwargs), texts, metadatas + # ) def delete(self, ids: Optional[List[str]] = None, **kwargs: Any) -> Optional[bool]: raise NotImplementedError - async def adelete( - self, ids: Optional[List[str]] = None, **kwargs: Any - ) -> Optional[bool]: - raise NotImplementedError + # optional: add custom async implementations + # async def adelete( + # self, ids: Optional[List[str]] = None, **kwargs: Any + # ) -> Optional[bool]: + # raise NotImplementedError def similarity_search( self, query: str, k: int = 4, **kwargs: Any ) -> List[Document]: raise NotImplementedError - async def asimilarity_search( - self, query: str, k: int = 4, **kwargs: Any - ) -> List[Document]: - # This is a temporary workaround to make the similarity search - # asynchronous. The proper solution is to make the similarity search - # asynchronous in the vector store implementations. - func = partial(self.similarity_search, query, k=k, **kwargs) - return await asyncio.get_event_loop().run_in_executor(None, func) + # optional: add custom async implementations + # async def asimilarity_search( + # self, query: str, k: int = 4, **kwargs: Any + # ) -> List[Document]: + # # This is a temporary workaround to make the similarity search + # # asynchronous. The proper solution is to make the similarity search + # # asynchronous in the vector store implementations. + # func = partial(self.similarity_search, query, k=k, **kwargs) + # return await asyncio.get_event_loop().run_in_executor(None, func) def similarity_search_with_score( self, *args: Any, **kwargs: Any ) -> List[Tuple[Document, float]]: raise NotImplementedError - async def asimilarity_search_with_score( - self, *args: Any, **kwargs: Any - ) -> List[Tuple[Document, float]]: - # This is a temporary workaround to make the similarity search - # asynchronous. The proper solution is to make the similarity search - # asynchronous in the vector store implementations. - func = partial(self.similarity_search_with_score, *args, **kwargs) - return await asyncio.get_event_loop().run_in_executor(None, func) + # optional: add custom async implementations + # async def asimilarity_search_with_score( + # self, *args: Any, **kwargs: Any + # ) -> List[Tuple[Document, float]]: + # # This is a temporary workaround to make the similarity search + # # asynchronous. The proper solution is to make the similarity search + # # asynchronous in the vector store implementations. + # func = partial(self.similarity_search_with_score, *args, **kwargs) + # return await asyncio.get_event_loop().run_in_executor(None, func) def similarity_search_by_vector( self, embedding: List[float], k: int = 4, **kwargs: Any ) -> List[Document]: raise NotImplementedError - async def asimilarity_search_by_vector( - self, embedding: List[float], k: int = 4, **kwargs: Any - ) -> List[Document]: - # This is a temporary workaround to make the similarity search - # asynchronous. The proper solution is to make the similarity search - # asynchronous in the vector store implementations. - func = partial(self.similarity_search_by_vector, embedding, k=k, **kwargs) - return await asyncio.get_event_loop().run_in_executor(None, func) + # optional: add custom async implementations + # async def asimilarity_search_by_vector( + # self, embedding: List[float], k: int = 4, **kwargs: Any + # ) -> List[Document]: + # # This is a temporary workaround to make the similarity search + # # asynchronous. The proper solution is to make the similarity search + # # asynchronous in the vector store implementations. + # func = partial(self.similarity_search_by_vector, embedding, k=k, **kwargs) + # return await asyncio.get_event_loop().run_in_executor(None, func) def max_marginal_relevance_search( self, @@ -238,26 +243,27 @@ def max_marginal_relevance_search( ) -> List[Document]: raise NotImplementedError - async def amax_marginal_relevance_search( - self, - query: str, - k: int = 4, - fetch_k: int = 20, - lambda_mult: float = 0.5, - **kwargs: Any, - ) -> List[Document]: - # This is a temporary workaround to make the similarity search - # asynchronous. The proper solution is to make the similarity search - # asynchronous in the vector store implementations. - func = partial( - self.max_marginal_relevance_search, - query, - k=k, - fetch_k=fetch_k, - lambda_mult=lambda_mult, - **kwargs, - ) - return await asyncio.get_event_loop().run_in_executor(None, func) + # optional: add custom async implementations + # async def amax_marginal_relevance_search( + # self, + # query: str, + # k: int = 4, + # fetch_k: int = 20, + # lambda_mult: float = 0.5, + # **kwargs: Any, + # ) -> List[Document]: + # # This is a temporary workaround to make the similarity search + # # asynchronous. The proper solution is to make the similarity search + # # asynchronous in the vector store implementations. + # func = partial( + # self.max_marginal_relevance_search, + # query, + # k=k, + # fetch_k=fetch_k, + # lambda_mult=lambda_mult, + # **kwargs, + # ) + # return await asyncio.get_event_loop().run_in_executor(None, func) def max_marginal_relevance_search_by_vector( self, @@ -269,15 +275,16 @@ def max_marginal_relevance_search_by_vector( ) -> List[Document]: raise NotImplementedError - async def amax_marginal_relevance_search_by_vector( - self, - embedding: List[float], - k: int = 4, - fetch_k: int = 20, - lambda_mult: float = 0.5, - **kwargs: Any, - ) -> List[Document]: - raise NotImplementedError + # optional: add custom async implementations + # async def amax_marginal_relevance_search_by_vector( + # self, + # embedding: List[float], + # k: int = 4, + # fetch_k: int = 20, + # lambda_mult: float = 0.5, + # **kwargs: Any, + # ) -> List[Document]: + # raise NotImplementedError @classmethod def from_texts( @@ -289,17 +296,18 @@ def from_texts( ) -> VST: raise NotImplementedError - @classmethod - async def afrom_texts( - cls: Type[VST], - texts: List[str], - embedding: Embeddings, - metadatas: Optional[List[dict]] = None, - **kwargs: Any, - ) -> VST: - return await asyncio.get_running_loop().run_in_executor( - None, partial(cls.from_texts, **kwargs), texts, embedding, metadatas - ) + # optional: add custom async implementations + # @classmethod + # async def afrom_texts( + # cls: Type[VST], + # texts: List[str], + # embedding: Embeddings, + # metadatas: Optional[List[dict]] = None, + # **kwargs: Any, + # ) -> VST: + # return await asyncio.get_running_loop().run_in_executor( + # None, partial(cls.from_texts, **kwargs), texts, embedding, metadatas + # ) def _select_relevance_score_fn(self) -> Callable[[float], float]: raise NotImplementedError diff --git a/libs/cli/langchain_cli/integration_template/pyproject.toml b/libs/cli/langchain_cli/integration_template/pyproject.toml index efdcb9efeadcd..000a4ece97049 100644 --- a/libs/cli/langchain_cli/integration_template/pyproject.toml +++ b/libs/cli/langchain_cli/integration_template/pyproject.toml @@ -1,5 +1,5 @@ [build-system] -requires = [ "poetry-core>=1.0.0",] +requires = ["poetry-core>=1.0.0"] build-backend = "poetry.core.masonry.api" [tool.poetry] @@ -23,14 +23,16 @@ python = ">=3.9,<4.0" langchain-core = "^0.3.15" [tool.ruff.lint] -select = [ "E", "F", "I", "T201",] +select = ["E", "F", "I", "T201"] [tool.coverage.run] -omit = [ "tests/*",] +omit = ["tests/*"] [tool.pytest.ini_options] addopts = "--strict-markers --strict-config --durations=5" -markers = [ "compile: mark placeholder test used to compile integration tests without running them",] +markers = [ + "compile: mark placeholder test used to compile integration tests without running them", +] asyncio_mode = "auto" [tool.poetry.group.test] @@ -48,11 +50,14 @@ optional = true [tool.poetry.group.dev] optional = true +[tool.poetry.group.dev.dependencies] + [tool.poetry.group.test.dependencies] pytest = "^7.4.3" pytest-asyncio = "^0.23.2" pytest-socket = "^0.7.0" pytest-watcher = "^0.3.4" +langchain-tests = "^0.3.4" [tool.poetry.group.codespell.dependencies] codespell = "^2.2.6" @@ -64,15 +69,3 @@ ruff = "^0.5" [tool.poetry.group.typing.dependencies] mypy = "^1.10" - -[tool.poetry.group.test.dependencies.langchain-core] -path = "../../core" -develop = true - -[tool.poetry.group.dev.dependencies.langchain-core] -path = "../../core" -develop = true - -[tool.poetry.group.typing.dependencies.langchain-core] -path = "../../core" -develop = true diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_chat_models.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_chat_models.py index 26b63bd706b5f..c84dafa973abf 100644 --- a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_chat_models.py +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_chat_models.py @@ -1,64 +1,21 @@ """Test Chat__ModuleName__ chat model.""" -from __module_name__.chat_models import Chat__ModuleName__ - - -def test_stream() -> None: - """Test streaming tokens from OpenAI.""" - llm = Chat__ModuleName__() - - 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 = Chat__ModuleName__() - - async for token in llm.astream("I'm Pickle Rick"): - assert isinstance(token.content, str) - - -async def test_abatch() -> None: - """Test streaming tokens from Chat__ModuleName__.""" - llm = Chat__ModuleName__() - - result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"]) - for token in result: - assert isinstance(token.content, str) - +from typing import Type -async def test_abatch_tags() -> None: - """Test batch tokens from Chat__ModuleName__.""" - llm = Chat__ModuleName__() - - 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 Chat__ModuleName__.""" - llm = Chat__ModuleName__() - - 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 Chat__ModuleName__.""" - llm = Chat__ModuleName__() - - result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]}) - assert isinstance(result.content, str) - - -def test_invoke() -> None: - """Test invoke tokens from Chat__ModuleName__.""" - llm = Chat__ModuleName__() - - result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"])) - assert isinstance(result.content, str) +from __module_name__.chat_models import Chat__ModuleName__ +from langchain_tests.integration_tests import ChatModelIntegrationTests + + +class TestChatParrotLinkIntegration(ChatModelIntegrationTests): + @property + def chat_model_class(self) -> Type[Chat__ModuleName__]: + return Chat__ModuleName__ + + @property + def chat_model_params(self) -> dict: + # These should be parameters used to initialize your integration for testing + return { + "model": "bird-brain-001", + "temperature": 0, + "parrot_buffer_length": 50, + } diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_embeddings.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_embeddings.py index 51937d157d255..f7bd526d04bd5 100644 --- a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_embeddings.py +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_embeddings.py @@ -1,20 +1,16 @@ """Test __ModuleName__ embeddings.""" -from __module_name__.embeddings import __ModuleName__Embeddings +from typing import Type +from __module_name__.embeddings import __ModuleName__Embeddings +from langchain_tests.integration_tests import EmbeddingsIntegrationTests -def test___module_name___embedding_documents() -> None: - """Test cohere embeddings.""" - documents = ["foo bar"] - embedding = __ModuleName__Embeddings() - output = embedding.embed_documents(documents) - assert len(output) == 1 - assert len(output[0]) > 0 +class TestParrotLinkEmbeddingsIntegration(EmbeddingsIntegrationTests): + @property + def embeddings_class(self) -> Type[__ModuleName__Embeddings]: + return __ModuleName__Embeddings -def test___module_name___embedding_query() -> None: - """Test cohere embeddings.""" - document = "foo bar" - embedding = __ModuleName__Embeddings() - output = embedding.embed_query(document) - assert len(output) > 0 + @property + def embedding_model_params(self) -> dict: + return {"model": "nest-embed-001"} diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_llms.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_llms.py deleted file mode 100644 index 9fd6e0a628e94..0000000000000 --- a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_llms.py +++ /dev/null @@ -1,64 +0,0 @@ -"""Test __ModuleName__LLM llm.""" - -from __module_name__.llms import __ModuleName__LLM - - -def test_stream() -> None: - """Test streaming tokens from OpenAI.""" - llm = __ModuleName__LLM() - - for token in llm.stream("I'm Pickle Rick"): - assert isinstance(token, str) - - -async def test_astream() -> None: - """Test streaming tokens from OpenAI.""" - llm = __ModuleName__LLM() - - async for token in llm.astream("I'm Pickle Rick"): - assert isinstance(token, str) - - -async def test_abatch() -> None: - """Test streaming tokens from __ModuleName__LLM.""" - llm = __ModuleName__LLM() - - result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"]) - for token in result: - assert isinstance(token, str) - - -async def test_abatch_tags() -> None: - """Test batch tokens from __ModuleName__LLM.""" - llm = __ModuleName__LLM() - - result = await llm.abatch( - ["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]} - ) - for token in result: - assert isinstance(token, str) - - -def test_batch() -> None: - """Test batch tokens from __ModuleName__LLM.""" - llm = __ModuleName__LLM() - - result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"]) - for token in result: - assert isinstance(token, str) - - -async def test_ainvoke() -> None: - """Test invoke tokens from __ModuleName__LLM.""" - llm = __ModuleName__LLM() - - result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]}) - assert isinstance(result, str) - - -def test_invoke() -> None: - """Test invoke tokens from __ModuleName__LLM.""" - llm = __ModuleName__LLM() - - result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"])) - assert isinstance(result, str) diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_retrievers.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_retrievers.py new file mode 100644 index 0000000000000..487c4a41cd7ca --- /dev/null +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_retrievers.py @@ -0,0 +1,24 @@ +from typing import Type + +from __module_name__.retrievers import __ModuleName__Retriever +from langchain_tests.integration_tests import ( + RetrieversIntegrationTests, +) + + +class Test__ModuleName__Retriever(RetrieversIntegrationTests): + @property + def retriever_constructor(self) -> Type[__ModuleName__Retriever]: + """Get an empty vectorstore for unit tests.""" + return __ModuleName__Retriever + + @property + def retriever_constructor_params(self) -> dict: + return {"k": 2} + + @property + def retriever_query_example(self) -> str: + """ + Returns a dictionary representing the "args" of an example retriever call. + """ + return "example query" diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_tools.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_tools.py new file mode 100644 index 0000000000000..529bd7fe7ea16 --- /dev/null +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_tools.py @@ -0,0 +1,27 @@ +from typing import Type + +from __module_name__.tools import __ModuleName__Tool +from langchain_tests.integration_tests import ToolsIntegrationTests + + +class TestParrotMultiplyToolIntegration(ToolsIntegrationTests): + @property + def tool_constructor(self) -> Type[__ModuleName__Tool]: + return __ModuleName__Tool + + @property + def tool_constructor_params(self) -> dict: + # if your tool constructor instead required initialization arguments like + # `def __init__(self, some_arg: int):`, you would return those here + # as a dictionary, e.g.: `return {'some_arg': 42}` + return {} + + @property + def tool_invoke_params_example(self) -> dict: + """ + Returns a dictionary representing the "args" of an example tool call. + + This should NOT be a ToolCall dict - i.e. it should not + have {"name", "id", "args"} keys. + """ + return {"a": 2, "b": 3} diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py new file mode 100644 index 0000000000000..2d0820348a3c3 --- /dev/null +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py @@ -0,0 +1,37 @@ +from typing import AsyncGenerator, Generator + +import pytest +from __module_name__.vectorstores import __ModuleName__VectorStore +from langchain_core.vectorstores import VectorStore +from langchain_tests.integration_tests import ( + AsyncReadWriteTestSuite, + ReadWriteTestSuite, +) + + +class Test__ModuleName__VectorStoreSync(ReadWriteTestSuite): + @pytest.fixture() + def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore + """Get an empty vectorstore for unit tests.""" + store = __ModuleName__VectorStore() + # note: store should be EMPTY at this point + # if you need to delete data, you may do so here + try: + yield store + finally: + # cleanup operations, or deleting data + pass + + +class Test__ModuleName__VectorStoreAsync(AsyncReadWriteTestSuite): + @pytest.fixture() + async def vectorstore(self) -> AsyncGenerator[VectorStore, None]: # type: ignore + """Get an empty vectorstore for unit tests.""" + store = __ModuleName__VectorStore() + # note: store should be EMPTY at this point + # if you need to delete data, you may do so here + try: + yield store + finally: + # cleanup operations, or deleting data + pass diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_chat_models.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_chat_models.py index 70cc82c75dcbf..c83081a44790b 100644 --- a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_chat_models.py +++ b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_chat_models.py @@ -1,8 +1,21 @@ """Test chat model integration.""" +from typing import Type + from __module_name__.chat_models import Chat__ModuleName__ +from langchain_tests.unit_tests import ChatModelUnitTests + +class TestChat__ModuleName__Unit(ChatModelUnitTests): + @property + def chat_model_class(self) -> Type[Chat__ModuleName__]: + return Chat__ModuleName__ -def test_initialization() -> None: - """Test chat model initialization.""" - Chat__ModuleName__() + @property + def chat_model_params(self) -> dict: + # These should be parameters used to initialize your integration for testing + return { + "model": "bird-brain-001", + "temperature": 0, + "parrot_buffer_length": 50, + } diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_embeddings.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_embeddings.py index ab4f45a9b7304..5fdf8feb0837d 100644 --- a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_embeddings.py +++ b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_embeddings.py @@ -1,8 +1,16 @@ """Test embedding model integration.""" +from typing import Type + from __module_name__.embeddings import __ModuleName__Embeddings +from langchain_tests.unit_tests import EmbeddingsUnitTests + +class TestParrotLinkEmbeddingsUnit(EmbeddingsUnitTests): + @property + def embeddings_class(self) -> Type[__ModuleName__Embeddings]: + return __ModuleName__Embeddings -def test_initialization() -> None: - """Test embedding model initialization.""" - __ModuleName__Embeddings() + @property + def embedding_model_params(self) -> dict: + return {"model": "nest-embed-001"} diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_imports.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_imports.py deleted file mode 100644 index 1dfa338914189..0000000000000 --- a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_imports.py +++ /dev/null @@ -1,12 +0,0 @@ -from __module_name__ import __all__ - -EXPECTED_ALL = [ - "__ModuleName__LLM", - "Chat__ModuleName__", - "__ModuleName__VectorStore", - "__ModuleName__Embeddings", -] - - -def test_all_imports() -> None: - assert sorted(EXPECTED_ALL) == sorted(__all__) diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_llms.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_llms.py deleted file mode 100644 index 7d53dad10acdd..0000000000000 --- a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_llms.py +++ /dev/null @@ -1,8 +0,0 @@ -"""Test __ModuleName__ Chat API wrapper.""" - -from __module_name__ import __ModuleName__LLM - - -def test_initialization() -> None: - """Test integration initialization.""" - __ModuleName__LLM() diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_tools.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_tools.py new file mode 100644 index 0000000000000..23231276d4125 --- /dev/null +++ b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_tools.py @@ -0,0 +1,27 @@ +from typing import Type + +from __module_name__.tools import __ModuleName__Tool +from langchain_tests.unit_tests import ToolsUnitTests + + +class TestParrotMultiplyToolUnit(ToolsUnitTests): + @property + def tool_constructor(self) -> Type[__ModuleName__Tool]: + return __ModuleName__Tool + + @property + def tool_constructor_params(self) -> dict: + # if your tool constructor instead required initialization arguments like + # `def __init__(self, some_arg: int):`, you would return those here + # as a dictionary, e.g.: `return {'some_arg': 42}` + return {} + + @property + def tool_invoke_params_example(self) -> dict: + """ + Returns a dictionary representing the "args" of an example tool call. + + This should NOT be a ToolCall dict - i.e. it should not + have {"name", "id", "args"} keys. + """ + return {"a": 2, "b": 3} diff --git a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_vectorstores.py b/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_vectorstores.py deleted file mode 100644 index 6c044a9a66fb4..0000000000000 --- a/libs/cli/langchain_cli/integration_template/tests/unit_tests/test_vectorstores.py +++ /dev/null @@ -1,6 +0,0 @@ -from __module_name__.vectorstores import __ModuleName__VectorStore - - -def test_initialization() -> None: - """Test integration vectorstore initialization.""" - __ModuleName__VectorStore() diff --git a/libs/cli/langchain_cli/namespaces/integration.py b/libs/cli/langchain_cli/namespaces/integration.py index e78af97c25d97..eca9804358561 100644 --- a/libs/cli/langchain_cli/namespaces/integration.py +++ b/libs/cli/langchain_cli/namespaces/integration.py @@ -6,7 +6,7 @@ import shutil import subprocess from pathlib import Path -from typing import Optional +from typing import Dict, Optional, cast import typer from typing_extensions import Annotated, TypedDict @@ -15,19 +15,17 @@ integration_cli = typer.Typer(no_args_is_help=True, add_completion=False) -Replacements = TypedDict( - "Replacements", - { - "__package_name__": str, - "__module_name__": str, - "__ModuleName__": str, - "__MODULE_NAME__": str, - "__package_name_short__": str, - }, -) +class Replacements(TypedDict): + __package_name__: str + __module_name__: str + __ModuleName__: str + __MODULE_NAME__: str + __package_name_short__: str + __package_name_short_snake__: str -def _process_name(name: str, *, community: bool = False): + +def _process_name(name: str, *, community: bool = False) -> Replacements: preprocessed = name.replace("_", "-").lower() if preprocessed.startswith("langchain-"): @@ -42,7 +40,7 @@ def _process_name(name: str, *, community: bool = False): raise ValueError("Name should not end with `-`.") if preprocessed.find("--") != -1: raise ValueError("Name should not contain consecutive hyphens.") - replacements = { + replacements: Replacements = { "__package_name__": f"langchain-{preprocessed}", "__module_name__": "langchain_" + preprocessed.replace("-", "_"), "__ModuleName__": preprocessed.title().replace("-", ""), @@ -52,7 +50,7 @@ def _process_name(name: str, *, community: bool = False): } if community: replacements["__module_name__"] = preprocessed.replace("-", "_") - return Replacements(replacements) + return replacements @integration_cli.command() @@ -74,16 +72,7 @@ def new( ): """ Creates a new integration package. - - Should be run from libs/partners """ - # confirm that we are in the right directory - if not Path.cwd().name == "partners" or not Path.cwd().parent.name == "libs": - typer.echo( - "This command should be run from the `libs/partners` directory in the " - "langchain-ai/langchain monorepo. Continuing is NOT recommended." - ) - typer.confirm("Are you sure you want to continue?", abort=True) try: replacements = _process_name(name) @@ -104,7 +93,7 @@ def new( "Name of integration in PascalCase", default=replacements["__ModuleName__"] ) - destination_dir = Path.cwd() / replacements["__package_name_short__"] + destination_dir = Path.cwd() / replacements["__package_name__"] if destination_dir.exists(): typer.echo(f"Folder {destination_dir} exists.") raise typer.Exit(code=1) @@ -118,7 +107,7 @@ def new( shutil.move(destination_dir / "integration_template", package_dir) # replacements in files - replace_glob(destination_dir, "**/*", replacements) + replace_glob(destination_dir, "**/*", cast(Dict[str, str], replacements)) # poetry install subprocess.run( @@ -226,4 +215,4 @@ def create_doc( shutil.copy(docs_template, destination_path) # replacements in file - replace_file(destination_path, replacements) + replace_file(destination_path, cast(Dict[str, str], replacements)) diff --git a/libs/cli/langchain_cli/namespaces/migrate/generate/utils.py b/libs/cli/langchain_cli/namespaces/migrate/generate/utils.py index 57fd457f19e4b..51b8b79bd3b6e 100644 --- a/libs/cli/langchain_cli/namespaces/migrate/generate/utils.py +++ b/libs/cli/langchain_cli/namespaces/migrate/generate/utils.py @@ -17,7 +17,7 @@ class ImportExtractor(ast.NodeVisitor): def __init__(self, *, from_package: Optional[str] = None) -> None: """Extract all imports from the given code, optionally filtering by package.""" - self.imports = [] + self.imports: list = [] self.package = from_package def visit_ImportFrom(self, node): @@ -68,7 +68,7 @@ def find_subclasses_in_module(module, classes_: List[Type]) -> List[str]: return subclasses -def _get_all_classnames_from_file(file: str, pkg: str) -> List[Tuple[str, str]]: +def _get_all_classnames_from_file(file: Path, pkg: str) -> List[Tuple[str, str]]: """Extract all class names from a file.""" with open(file, encoding="utf-8") as f: code = f.read() @@ -145,7 +145,7 @@ def find_imports_from_package( return extractor.imports -def _get_current_module(path: str, pkg_root: str) -> str: +def _get_current_module(path: Path, pkg_root: str) -> str: """Convert a path to a module name.""" path_as_pathlib = pathlib.Path(os.path.abspath(path)) relative_path = path_as_pathlib.relative_to(pkg_root).with_suffix("") diff --git a/libs/cli/langchain_cli/namespaces/migrate/main.py b/libs/cli/langchain_cli/namespaces/migrate/main.py index 483fa9f6ea6c7..0956f9d4f683c 100644 --- a/libs/cli/langchain_cli/namespaces/migrate/main.py +++ b/libs/cli/langchain_cli/namespaces/migrate/main.py @@ -4,7 +4,7 @@ import rich import typer -from gritql import run +from gritql import run # type: ignore from typer import Option diff --git a/libs/cli/langchain_cli/utils/find_replace.py b/libs/cli/langchain_cli/utils/find_replace.py index cfea68d3dfaa7..12cb9bb4a13fe 100644 --- a/libs/cli/langchain_cli/utils/find_replace.py +++ b/libs/cli/langchain_cli/utils/find_replace.py @@ -13,7 +13,7 @@ def find_and_replace(source: str, replacements: Dict[str, str]) -> str: return rtn -def replace_file(source: Path, replacements: Dict[str, str]) -> None: +def replace_file(source: Path, replacements: dict[str, str]) -> None: try: content = source.read_text() except UnicodeDecodeError: @@ -24,7 +24,7 @@ def replace_file(source: Path, replacements: Dict[str, str]) -> None: source.write_text(new_content) -def replace_glob(parent: Path, glob: str, replacements: Dict[str, str]) -> None: +def replace_glob(parent: Path, glob: str, replacements: dict[str, str]) -> None: for file in parent.glob(glob): if not file.is_file(): continue diff --git a/libs/cli/poetry.lock b/libs/cli/poetry.lock index d2026cb3a1119..c53e81acdd077 100644 --- a/libs/cli/poetry.lock +++ b/libs/cli/poetry.lock @@ -1,5 +1,128 @@ # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +[[package]] +name = "aiohappyeyeballs" +version = "2.4.4" +description = "Happy Eyeballs 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pytest-watch = "^4.2.0" [tool.poetry.group.lint.dependencies] ruff = "^0.5" +mypy = "^1.13.0" [tool.poetry.group.test.dependencies] +langchain = {path = "../langchain", develop = true} [tool.poetry.group.typing.dependencies] +langchain = {path = "../langchain", develop = true} [tool.poetry.group.test_integration.dependencies] @@ -50,22 +52,11 @@ select = [ "T201", # print ] -[tool.poe.tasks] -test = "poetry run pytest tests" -watch = "poetry run ptw" -version = "poetry version --short" -bump = ["_bump_1", "_bump_2"] -lint = ["_lint", "_check_formatting"] -format = ["_format", "_lint_fix"] - -_bump_2.shell = """sed -i "" "/^__version__ =/c\\ \n__version__ = \\"$version\\"\n" langchain_cli/cli.py""" -_bump_2.uses = { version = "version" } - -_bump_1 = "poetry version patch" -_check_formatting = "poetry run ruff format . --diff" -_lint = "poetry run ruff check ." -_format = "poetry run ruff format ." -_lint_fix = "poetry run ruff check . --fix" +[tool.mypy] +exclude = [ + "langchain_cli/integration_template", + "langchain_cli/package_template", +] [build-system] requires = ["poetry-core"] diff --git a/libs/cli/scripts/generate_migrations.py b/libs/cli/scripts/generate_migrations.py index 38c830443c775..11b5a8a6b0ed3 100644 --- a/libs/cli/scripts/generate_migrations.py +++ b/libs/cli/scripts/generate_migrations.py @@ -1,3 +1,4 @@ +# type: ignore """Script to generate migrations for the migration script.""" import json diff --git a/libs/cli/tests/integration_tests/test_compile.py b/libs/cli/tests/integration_tests/test_compile.py new file mode 100644 index 0000000000000..33ecccdfa0fbd --- /dev/null +++ b/libs/cli/tests/integration_tests/test_compile.py @@ -0,0 +1,7 @@ +import pytest + + +@pytest.mark.compile +def test_placeholder() -> None: + """Used for compiling integration tests without running any real tests.""" + pass diff --git a/libs/cli/tests/unit_tests/migrate/cli_runner/test_cli.py b/libs/cli/tests/unit_tests/migrate/cli_runner/test_cli.py index 4fbeae295bacf..3cc57112ead53 100644 --- a/libs/cli/tests/unit_tests/migrate/cli_runner/test_cli.py +++ b/libs/cli/tests/unit_tests/migrate/cli_runner/test_cli.py @@ -41,6 +41,7 @@ def find_issue(current: Folder, expected: Folder) -> str: return "Unknown" +@pytest.mark.xfail(reason="grit may not be installed in env") def test_command_line(tmp_path: Path) -> None: runner = CliRunner() diff --git a/libs/standard-tests/langchain_tests/integration_tests/__init__.py b/libs/standard-tests/langchain_tests/integration_tests/__init__.py index ed7e5f111c9f4..734af1608c6cb 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/__init__.py +++ b/libs/standard-tests/langchain_tests/integration_tests/__init__.py @@ -11,6 +11,7 @@ "vectorstores", "embeddings", "tools", + "retrievers", ] for module in modules: From 0f539f02461507bf609a4fd3f50aeaad49c7823d Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 5 Dec 2024 00:41:07 -0800 Subject: [PATCH 002/157] standard-tests: release 0.3.5 (#28526) --- libs/standard-tests/poetry.lock | 444 ++++++++++++++++------------- libs/standard-tests/pyproject.toml | 4 +- 2 files changed, 249 insertions(+), 199 deletions(-) diff --git a/libs/standard-tests/poetry.lock b/libs/standard-tests/poetry.lock index a10861100dffc..0bb01c5870edb 100644 --- a/libs/standard-tests/poetry.lock +++ b/libs/standard-tests/poetry.lock @@ -309,7 +309,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.19" +version = "0.3.21" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ -334,13 +334,13 @@ url = "../core" [[package]] name = "langsmith" -version = "0.1.144" +version = "0.1.147" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.144-py3-none-any.whl", hash = "sha256:08ffb975bff2e82fc6f5428837c64c074ea25102d08a25e256361a80812c6100"}, - 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implementations" authors = ["Erick Friis "] readme = "README.md" @@ -19,7 +19,7 @@ disallow_untyped_defs = "True" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.19" +langchain-core = "^0.3.21" pytest = ">=7,<9" httpx = "^0.27.0" syrupy = "^4" From d9e42a1517ccc946fc64ce677d856112e0c8d577 Mon Sep 17 00:00:00 2001 From: ccurme Date: Thu, 5 Dec 2024 09:49:10 -0500 Subject: [PATCH 003/157] langchain[patch]: fix deprecation warning (#28535) --- .../langchain/chains/router/multi_prompt.py | 92 ++++++++++++++----- 1 file changed, 70 insertions(+), 22 deletions(-) diff --git a/libs/langchain/langchain/chains/router/multi_prompt.py b/libs/langchain/langchain/chains/router/multi_prompt.py index 214b9a2b37208..0531cdb834db3 100644 --- a/libs/langchain/langchain/chains/router/multi_prompt.py +++ b/libs/langchain/langchain/chains/router/multi_prompt.py @@ -20,9 +20,8 @@ since="0.2.12", removal="1.0", message=( - "Use RunnableLambda to select from multiple prompt templates. See example " - "in API reference: " - "https://api.python.langchain.com/en/latest/chains/langchain.chains.router.multi_prompt.MultiPromptChain.html" # noqa: E501 + "Please see migration guide here for recommended implementation: " + "https://python.langchain.com/docs/versions/migrating_chains/multi_prompt_chain/" # noqa: E501 ), ) class MultiPromptChain(MultiRouteChain): @@ -37,60 +36,109 @@ class MultiPromptChain(MultiRouteChain): from operator import itemgetter from typing import Literal - from typing_extensions import TypedDict from langchain_core.output_parsers import StrOutputParser from langchain_core.prompts import ChatPromptTemplate - from langchain_core.runnables import RunnableLambda, RunnablePassthrough + from langchain_core.runnables import RunnableConfig from langchain_openai import ChatOpenAI + from langgraph.graph import END, START, StateGraph + from typing_extensions import TypedDict llm = ChatOpenAI(model="gpt-4o-mini") + # Define the prompts we will route to prompt_1 = ChatPromptTemplate.from_messages( [ ("system", "You are an expert on animals."), - ("human", "{query}"), + ("human", "{input}"), ] ) prompt_2 = ChatPromptTemplate.from_messages( [ ("system", "You are an expert on vegetables."), - ("human", "{query}"), + ("human", "{input}"), ] ) + # Construct the chains we will route to. These format the input query + # into the respective prompt, run it through a chat model, and cast + # the result to a string. chain_1 = prompt_1 | llm | StrOutputParser() chain_2 = prompt_2 | llm | StrOutputParser() + + # Next: define the chain that selects which branch to route to. + # Here we will take advantage of tool-calling features to force + # the output to select one of two desired branches. route_system = "Route the user's query to either the animal or vegetable expert." route_prompt = ChatPromptTemplate.from_messages( [ ("system", route_system), - ("human", "{query}"), + ("human", "{input}"), ] ) + # Define schema for output: class RouteQuery(TypedDict): - \"\"\"Route query to destination.\"\"\" + \"\"\"Route query to destination expert.\"\"\" + destination: Literal["animal", "vegetable"] - route_chain = ( - route_prompt - | llm.with_structured_output(RouteQuery) - | itemgetter("destination") - ) + route_chain = route_prompt | llm.with_structured_output(RouteQuery) - chain = { - "destination": route_chain, # "animal" or "vegetable" - "query": lambda x: x["query"], # pass through input query - } | RunnableLambda( - # if animal, chain_1. otherwise, chain_2. - lambda x: chain_1 if x["destination"] == "animal" else chain_2, - ) - chain.invoke({"query": "what color are carrots"}) + # For LangGraph, we will define the state of the graph to hold the query, + # destination, and final answer. + class State(TypedDict): + query: str + destination: RouteQuery + answer: str + + + # We define functions for each node, including routing the query: + async def route_query(state: State, config: RunnableConfig): + destination = await route_chain.ainvoke(state["query"], config) + return {"destination": destination} + + + # And one node for each prompt + async def prompt_1(state: State, config: RunnableConfig): + return {"answer": await chain_1.ainvoke(state["query"], config)} + + + async def prompt_2(state: State, config: RunnableConfig): + return {"answer": await chain_2.ainvoke(state["query"], config)} + + + # We then define logic that selects the prompt based on the classification + def select_node(state: State) -> Literal["prompt_1", "prompt_2"]: + if state["destination"] == "animal": + return "prompt_1" + else: + return "prompt_2" + + + # Finally, assemble the multi-prompt chain. This is a sequence of two steps: + # 1) Select "animal" or "vegetable" via the route_chain, and collect the answer + # alongside the input query. + # 2) Route the input query to chain_1 or chain_2, based on the + # selection. + graph = StateGraph(State) + graph.add_node("route_query", route_query) + graph.add_node("prompt_1", prompt_1) + graph.add_node("prompt_2", prompt_2) + + graph.add_edge(START, "route_query") + graph.add_conditional_edges("route_query", select_node) + graph.add_edge("prompt_1", END) + graph.add_edge("prompt_2", END) + app = graph.compile() + + result = await app.ainvoke({"query": "what color are carrots"}) + print(result["destination"]) + print(result["answer"]) """ # noqa: E501 @property From ecff9a01e44a6d85c50fc6c49497b25daae0f5b1 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 5 Dec 2024 07:35:49 -0800 Subject: [PATCH 004/157] cli: release 0.0.34 (#28525) --- libs/cli/langchain_cli/integration_template/pyproject.toml | 2 +- libs/cli/pyproject.toml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/libs/cli/langchain_cli/integration_template/pyproject.toml b/libs/cli/langchain_cli/integration_template/pyproject.toml index 000a4ece97049..fa3c596b069bb 100644 --- a/libs/cli/langchain_cli/integration_template/pyproject.toml +++ b/libs/cli/langchain_cli/integration_template/pyproject.toml @@ -57,7 +57,7 @@ pytest = "^7.4.3" pytest-asyncio = "^0.23.2" pytest-socket = "^0.7.0" pytest-watcher = "^0.3.4" -langchain-tests = "^0.3.4" +langchain-tests = "^0.3.5" [tool.poetry.group.codespell.dependencies] codespell = "^2.2.6" diff --git a/libs/cli/pyproject.toml b/libs/cli/pyproject.toml index c2ae7ec7c06fa..3e434fc8e6a53 100644 --- a/libs/cli/pyproject.toml +++ b/libs/cli/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langchain-cli" -version = "0.0.33" +version = "0.0.34" description = "CLI for interacting with LangChain" authors = ["Erick Friis "] readme = "README.md" From 8f9b3b7498d7446201b54d5b6e347cacea0f04ad Mon Sep 17 00:00:00 2001 From: ccurme Date: Thu, 5 Dec 2024 10:37:19 -0500 Subject: [PATCH 005/157] chroma[patch]: fix bug (#28538) Fix bug introduced in https://github.com/langchain-ai/langchain/pull/27995 If all document IDs are `""`, the chroma SDK will raise ``` DuplicateIDError: Expected IDs to be unique ``` Caught by [docs tests](https://github.com/langchain-ai/langchain/actions/runs/12180395579/job/33974633950), but added a test to langchain-chroma as well. --- .../chroma/langchain_chroma/vectorstores.py | 2 +- .../tests/integration_tests/test_vectorstores.py | 16 ++++++++++++++++ 2 files changed, 17 insertions(+), 1 deletion(-) diff --git a/libs/partners/chroma/langchain_chroma/vectorstores.py b/libs/partners/chroma/langchain_chroma/vectorstores.py index d8d8f5de5e425..9967ac6d29488 100644 --- a/libs/partners/chroma/langchain_chroma/vectorstores.py +++ b/libs/partners/chroma/langchain_chroma/vectorstores.py @@ -1228,7 +1228,7 @@ def from_documents( texts = [doc.page_content for doc in documents] metadatas = [doc.metadata for doc in documents] if ids is None: - ids = [doc.id if doc.id else "" for doc in documents] + ids = [doc.id if doc.id else str(uuid.uuid4()) for doc in documents] return cls.from_texts( texts=texts, embedding=embedding, diff --git a/libs/partners/chroma/tests/integration_tests/test_vectorstores.py b/libs/partners/chroma/tests/integration_tests/test_vectorstores.py index bea50c909748f..f7bed4cfa5588 100644 --- a/libs/partners/chroma/tests/integration_tests/test_vectorstores.py +++ b/libs/partners/chroma/tests/integration_tests/test_vectorstores.py @@ -51,6 +51,22 @@ def test_chroma() -> None: assert output[0].id is not None +def test_from_documents() -> None: + """Test init using .from_documents.""" + documents = [ + Document(page_content="foo"), + Document(page_content="bar"), + Document(page_content="baz"), + ] + docsearch = Chroma.from_documents(documents=documents, embedding=FakeEmbeddings()) + output = docsearch.similarity_search("foo", k=1) + + docsearch.delete_collection() + assert len(output) == 1 + assert output[0].page_content == "foo" + assert output[0].id is not None + + def test_chroma_with_ids() -> None: """Test end to end construction and search.""" texts = ["foo", "bar", "baz"] From 7d44316d926702820097d93c1c095902095c84eb Mon Sep 17 00:00:00 2001 From: John <43506685+Coniferish@users.noreply.github.com> Date: Thu, 5 Dec 2024 11:57:51 -0500 Subject: [PATCH 006/157] docs: Add link for how to install extras (#28537) **Description:** Add link for how to install extras --- docs/docs/integrations/providers/unstructured.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/integrations/providers/unstructured.mdx b/docs/docs/integrations/providers/unstructured.mdx index 312a28d6f6815..8425ff1faa226 100644 --- a/docs/docs/integrations/providers/unstructured.mdx +++ b/docs/docs/integrations/providers/unstructured.mdx @@ -22,7 +22,7 @@ dependencies running. - To run everything locally, install the open-source python package with `pip install unstructured` along with `pip install langchain-community` and use the same `UnstructuredLoader` as mentioned above. - - You can install document specific dependencies with extras, e.g. `pip install "unstructured[docx]"`. + - You can install document specific dependencies with extras, e.g. `pip install "unstructured[docx]"`. Learn more about extras [here](https://docs.unstructured.io/open-source/installation/full-installation). - To install the dependencies for all document types, use `pip install "unstructured[all-docs]"`. - Install the following system dependencies if they are not already available on your system with e.g. `brew install` for Mac. Depending on what document types you're parsing, you may not need all of these. From d26555c68277267f995475dcc36358e92ed1d765 Mon Sep 17 00:00:00 2001 From: ZhangShenao <15201440436@163.com> Date: Fri, 6 Dec 2024 00:58:32 +0800 Subject: [PATCH 007/157] [VectorStore] Improvement: Improve chroma vector store (#28524) - Complete unit test - Fix spelling error --- .../chroma/langchain_chroma/vectorstores.py | 2 +- .../chroma/tests/unit_tests/test_vectorstores.py | 15 +++++++++++++++ 2 files changed, 16 insertions(+), 1 deletion(-) diff --git a/libs/partners/chroma/langchain_chroma/vectorstores.py b/libs/partners/chroma/langchain_chroma/vectorstores.py index 9967ac6d29488..afb9191c60a31 100644 --- a/libs/partners/chroma/langchain_chroma/vectorstores.py +++ b/libs/partners/chroma/langchain_chroma/vectorstores.py @@ -758,7 +758,7 @@ def _select_relevance_score_fn(self) -> Callable[[float], float]: The most similar documents will have the lowest relevance score. Default relevance score function is euclidean distance. Distance metric must be - provided in `collection_metadata` during initizalition of Chroma object. + provided in `collection_metadata` during initialization of Chroma object. Example: collection_metadata={"hnsw:space": "cosine"}. Available distance metrics are: 'cosine', 'l2' and 'ip'. diff --git a/libs/partners/chroma/tests/unit_tests/test_vectorstores.py b/libs/partners/chroma/tests/unit_tests/test_vectorstores.py index 84d8637879e29..66ac3b0622465 100644 --- a/libs/partners/chroma/tests/unit_tests/test_vectorstores.py +++ b/libs/partners/chroma/tests/unit_tests/test_vectorstores.py @@ -13,3 +13,18 @@ def test_initialization() -> None: texts=texts, embedding=FakeEmbeddings(size=10), ) + + +def test_similarity_search() -> None: + """Test similarity search by Chroma.""" + texts = ["foo", "bar", "baz"] + metadatas = [{"page": str(i)} for i in range(len(texts))] + docsearch = Chroma.from_texts( + collection_name="test_collection", + texts=texts, + embedding=FakeEmbeddings(size=10), + metadatas=metadatas, + ) + output = docsearch.similarity_search("foo", k=1) + docsearch.delete_collection() + assert len(output) == 1 From b8e861a63b85167a9c47fabf3452e8baba538a7c Mon Sep 17 00:00:00 2001 From: ccurme Date: Thu, 5 Dec 2024 12:00:27 -0500 Subject: [PATCH 008/157] openai[patch]: add standard tests for embeddings (#28540) --- .../embeddings/test_base_standard.py | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) create mode 100644 libs/partners/openai/tests/integration_tests/embeddings/test_base_standard.py diff --git a/libs/partners/openai/tests/integration_tests/embeddings/test_base_standard.py b/libs/partners/openai/tests/integration_tests/embeddings/test_base_standard.py new file mode 100644 index 0000000000000..66f74f1687fd5 --- /dev/null +++ b/libs/partners/openai/tests/integration_tests/embeddings/test_base_standard.py @@ -0,0 +1,18 @@ +"""Standard LangChain interface tests""" + +from typing import Type + +from langchain_core.embeddings import Embeddings +from langchain_tests.integration_tests.embeddings import EmbeddingsIntegrationTests + +from langchain_openai import OpenAIEmbeddings + + +class TestOpenAIStandard(EmbeddingsIntegrationTests): + @property + def embeddings_class(self) -> Type[Embeddings]: + return OpenAIEmbeddings + + @property + def embedding_model_params(self) -> dict: + return {"model": "text-embedding-3-small", "dimensions": 128} From 1e285cb5f3ec3c4cc0361cfb802f2bb04c915fd9 Mon Sep 17 00:00:00 2001 From: WEIQ-beepbeep Date: Fri, 6 Dec 2024 01:15:59 +0800 Subject: [PATCH 009/157] docs: Updated incorrected type used for the `multiply_by_max` function (#28042) In the `multiply_by_max()` tool, `a` is a scale factor but it is annotated with a string type. --- docs/docs/how_to/custom_tools.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/how_to/custom_tools.ipynb b/docs/docs/how_to/custom_tools.ipynb index 8046b7b00e4a4..e9a50a72e11d4 100644 --- a/docs/docs/how_to/custom_tools.ipynb +++ b/docs/docs/how_to/custom_tools.ipynb @@ -162,7 +162,7 @@ "\n", "@tool\n", "def multiply_by_max(\n", - " a: Annotated[str, \"scale factor\"],\n", + " a: Annotated[int, \"scale factor\"],\n", " b: Annotated[List[int], \"list of ints over which to take maximum\"],\n", ") -> int:\n", " \"\"\"Multiply a by the maximum of b.\"\"\"\n", From 1581857e3d4df2bf569e1eb0c56c0a0c11f7881b Mon Sep 17 00:00:00 2001 From: dwelch-spike <53876192+dwelch-spike@users.noreply.github.com> Date: Thu, 5 Dec 2024 09:29:00 -0800 Subject: [PATCH 010/157] docs: add Aerospike to providers list (#28066) **Description:** Adds Aerospike to the list of langchain providers and points users to documentation for the vector store and Python SDK. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17. --------- Co-authored-by: Erick Friis Co-authored-by: Erick Friis --- .../docs/integrations/providers/aerospike.mdx | 24 +++++++++++++++++++ 1 file changed, 24 insertions(+) create mode 100644 docs/docs/integrations/providers/aerospike.mdx diff --git a/docs/docs/integrations/providers/aerospike.mdx b/docs/docs/integrations/providers/aerospike.mdx new file mode 100644 index 0000000000000..9dfbaa68091de --- /dev/null +++ b/docs/docs/integrations/providers/aerospike.mdx @@ -0,0 +1,24 @@ +# Aerospike + +>[Aerospike](https://aerospike.com/docs/vector) is a high-performance, distributed database known for its speed and scalability, now with support for vector storage and search, enabling retrieval and search of embedding vectors for machine learning and AI applications. +> See the documentation for Aerospike Vector Search (AVS) [here](https://aerospike.com/docs/vector). + +## Installation and Setup + +Install the AVS Python SDK and AVS langchain vector store: + +```bash +pip install aerospike-vector-search langchain-community + +See the documentation for the Ptyhon SDK [here](https://aerospike-vector-search-python-client.readthedocs.io/en/latest/index.html). +The documentation for the AVS langchain vector store is [here](https://python.langchain.com/api_reference/community/vectorstores/langchain_community.vectorstores.aerospike.Aerospike.html). + +## Vector Store + +To import this vectorstore: + +```python +from langchain_community.vectorstores import Aerospike + +See a usage example [here](https://python.langchain.com/docs/integrations/vectorstores/aerospike/). + From ecdfc98ef6b3a22e1269430380cad96636c848c0 Mon Sep 17 00:00:00 2001 From: ccurme Date: Thu, 5 Dec 2024 14:39:03 -0500 Subject: [PATCH 011/157] tests[patch]: run standard tests for embeddings and populate embeddings API ref (#28545) plus minor updates to chat models and vector store API refs --- .../integration_tests/chat_models.py | 29 ++++--- .../integration_tests/embeddings.py | 67 +++++++++++++++ .../integration_tests/vectorstores.py | 4 + .../langchain_tests/unit_tests/chat_models.py | 32 +++---- .../langchain_tests/unit_tests/embeddings.py | 85 ++++++++++++++++++- .../tests/unit_tests/test_embeddings.py | 26 ++++++ 6 files changed, 212 insertions(+), 31 deletions(-) create mode 100644 libs/standard-tests/tests/unit_tests/test_embeddings.py diff --git a/libs/standard-tests/langchain_tests/integration_tests/chat_models.py b/libs/standard-tests/langchain_tests/integration_tests/chat_models.py index 1cbec02ad0dac..4e6a811c4516e 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/chat_models.py +++ b/libs/standard-tests/langchain_tests/integration_tests/chat_models.py @@ -75,29 +75,30 @@ def _validate_tool_call_message_no_args(message: BaseMessage) -> None: class ChatModelIntegrationTests(ChatModelTests): """Base class for chat model integration tests. - Test subclasses must implement the following two properties: + Test subclasses must implement the ``chat_model_class`` and + ``chat_model_params`` properties to specify what model to test and its + initialization parameters. - chat_model_class - The chat model class to test, e.g., ``ChatParrotLink``. + Example: - Example: + .. code-block:: python - .. code-block:: python - - @property - def chat_model_class(self) -> Type[ChatParrotLink]: - return ChatParrotLink + from typing import Type - chat_model_params - Initialization parameters for the chat model. + from langchain_tests.integration_tests import ChatModelIntegrationTests + from my_package.chat_models import MyChatModel - Example: - .. code-block:: python + class TestMyChatModelIntegration(ChatModelIntegrationTests): + @property + def chat_model_class(self) -> Type[MyChatModel]: + # Return the chat model class to test here + return MyChatModel @property def chat_model_params(self) -> dict: - return {"model": "bird-brain-001", "temperature": 0} + # Return initialization parameters for the model. + return {"model": "model-001", "temperature": 0} .. note:: API references for individual test methods include troubleshooting tips. diff --git a/libs/standard-tests/langchain_tests/integration_tests/embeddings.py b/libs/standard-tests/langchain_tests/integration_tests/embeddings.py index 7e3689d0f5429..8b4f20bb4a5e7 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/embeddings.py +++ b/libs/standard-tests/langchain_tests/integration_tests/embeddings.py @@ -6,7 +6,47 @@ class EmbeddingsIntegrationTests(EmbeddingsTests): + """Base class for embeddings integration tests. + + Test subclasses must implement the ``embeddings_class`` property to specify the + embeddings model to be tested. You can also override the + ``embedding_model_params`` property to specify initialization parameters. + + Example: + + .. code-block:: python + + from typing import Type + + from langchain_tests.integration_tests import EmbeddingsIntegrationTests + from my_package.embeddings import MyEmbeddingsModel + + + class TestMyEmbeddingsModelIntegration(EmbeddingsIntegrationTests): + @property + def embeddings_class(self) -> Type[MyEmbeddingsModel]: + # Return the embeddings model class to test here + return MyEmbeddingsModel + + @property + def embedding_model_params(self) -> dict: + # Return initialization parameters for the model. + return {"model": "model-001"} + + .. note:: + API references for individual test methods include troubleshooting tips. + """ + def test_embed_query(self, model: Embeddings) -> None: + """Test embedding a string query. + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. The model will generate a list of floats when calling ``.embed_query`` on a string. + 2. The length of the list is consistent across different inputs. + """ # noqa: E501 embedding_1 = model.embed_query("foo") assert isinstance(embedding_1, List) @@ -18,6 +58,15 @@ def test_embed_query(self, model: Embeddings) -> None: assert len(embedding_1) == len(embedding_2) def test_embed_documents(self, model: Embeddings) -> None: + """Test embedding a list of strings. + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. The model will generate a list of lists of floats when calling ``.embed_documents`` on a list of strings. + 2. The length of each list is the same. + """ # noqa: E501 documents = ["foo", "bar", "baz"] embeddings = model.embed_documents(documents) @@ -28,6 +77,15 @@ def test_embed_documents(self, model: Embeddings) -> None: assert all(len(embedding) == len(embeddings[0]) for embedding in embeddings) async def test_aembed_query(self, model: Embeddings) -> None: + """Test embedding a string query async. + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. The model will generate a list of floats when calling ``.aembed_query`` on a string. + 2. The length of the list is consistent across different inputs. + """ # noqa: E501 embedding_1 = await model.aembed_query("foo") assert isinstance(embedding_1, List) @@ -39,6 +97,15 @@ async def test_aembed_query(self, model: Embeddings) -> None: assert len(embedding_1) == len(embedding_2) async def test_aembed_documents(self, model: Embeddings) -> None: + """Test embedding a list of strings async. + + .. dropdown:: Troubleshooting + + If this test fails, check that: + + 1. The model will generate a list of lists of floats when calling ``.aembed_documents`` on a list of strings. + 2. The length of each list is the same. + """ # noqa: E501 documents = ["foo", "bar", "baz"] embeddings = await model.aembed_documents(documents) diff --git a/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py b/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py index 07d5ced720252..36770823be5e2 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py +++ b/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py @@ -76,6 +76,8 @@ def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore store.delete_collection() pass + .. note:: + API references for individual test methods include troubleshooting tips. """ # noqa: E501 @abstractmethod @@ -445,6 +447,8 @@ async def vectorstore(self) -> AsyncGenerator[VectorStore, None]: # type: ignor store.delete_collection() pass + .. note:: + API references for individual test methods include troubleshooting tips. """ # noqa: E501 @abstractmethod diff --git a/libs/standard-tests/langchain_tests/unit_tests/chat_models.py b/libs/standard-tests/langchain_tests/unit_tests/chat_models.py index 2de0776f5e310..71f3dd2169cc1 100644 --- a/libs/standard-tests/langchain_tests/unit_tests/chat_models.py +++ b/libs/standard-tests/langchain_tests/unit_tests/chat_models.py @@ -380,29 +380,30 @@ def supported_usage_metadata_details( class ChatModelUnitTests(ChatModelTests): """Base class for chat model unit tests. - Test subclasses must implement the following two properties: + Test subclasses must implement the ``chat_model_class`` and + ``chat_model_params`` properties to specify what model to test and its + initialization parameters. - chat_model_class - The chat model class to test, e.g., ``ChatParrotLink``. + Example: - Example: + .. code-block:: python - .. code-block:: python + from typing import Type - @property - def chat_model_class(self) -> Type[ChatParrotLink]: - return ChatParrotLink + from langchain_tests.unit_tests import ChatModelUnitTests + from my_package.chat_models import MyChatModel - chat_model_params - Initialization parameters for the chat model. - - Example: - .. code-block:: python + class TestMyChatModelUnit(ChatModelUnitTests): + @property + def chat_model_class(self) -> Type[MyChatModel]: + # Return the chat model class to test here + return MyChatModel @property def chat_model_params(self) -> dict: - return {"model": "bird-brain-001", "temperature": 0} + # Return initialization parameters for the model. + return {"model": "model-001", "temperature": 0} .. note:: API references for individual test methods include troubleshooting tips. @@ -486,7 +487,8 @@ def test_init_from_env(self) -> None: .. dropdown:: Troubleshooting If this test fails, ensure that ``init_from_env_params`` is specified - correctly. + correctly and that model parameters are properly set from environment + variables during initialization. """ env_params, model_params, expected_attrs = self.init_from_env_params if not env_params: diff --git a/libs/standard-tests/langchain_tests/unit_tests/embeddings.py b/libs/standard-tests/langchain_tests/unit_tests/embeddings.py index da7b78513844b..c580243b16d9d 100644 --- a/libs/standard-tests/langchain_tests/unit_tests/embeddings.py +++ b/libs/standard-tests/langchain_tests/unit_tests/embeddings.py @@ -25,17 +25,98 @@ def model(self) -> Embeddings: class EmbeddingsUnitTests(EmbeddingsTests): + """Base class for embeddings unit tests. + + Test subclasses must implement the ``embeddings_class`` property to specify the + embeddings model to be tested. You can also override the + ``embedding_model_params`` property to specify initialization parameters. + + Example: + + .. code-block:: python + + from typing import Type + + from langchain_tests.unit_tests import EmbeddingsUnitTests + from my_package.embeddings import MyEmbeddingsModel + + + class TestMyEmbeddingsModelUnit(EmbeddingsUnitTests): + @property + def embeddings_class(self) -> Type[MyEmbeddingsModel]: + # Return the embeddings model class to test here + return MyEmbeddingsModel + + @property + def embedding_model_params(self) -> dict: + # Return initialization parameters for the model. + return {"model": "model-001"} + + .. note:: + API references for individual test methods include troubleshooting tips. + + Testing initialization from environment variables + Overriding the ``init_from_env_params`` property will enable additional tests + for initialization from environment variables. See below for details. + + .. dropdown:: init_from_env_params + + This property is used in unit tests to test initialization from + environment variables. It should return a tuple of three dictionaries + that specify the environment variables, additional initialization args, + and expected instance attributes to check. + + Defaults to empty dicts. If not overridden, the test is skipped. + + Example: + + .. code-block:: python + + @property + def init_from_env_params(self) -> Tuple[dict, dict, dict]: + return ( + { + "MY_API_KEY": "api_key", + }, + { + "model": "model-001", + }, + { + "my_api_key": "api_key", + }, + ) + """ # noqa: E501 + def test_init(self) -> None: + """Test model initialization. + + .. dropdown:: Troubleshooting + + If this test fails, ensure that ``embedding_model_params`` is specified + and the model can be initialized from those params. + """ model = self.embeddings_class(**self.embedding_model_params) assert model is not None @property def init_from_env_params(self) -> Tuple[dict, dict, dict]: - """Return env vars, init args, and expected instance attrs for initializing - from env vars.""" + """This property is used in unit tests to test initialization from environment + variables. It should return a tuple of three dictionaries that specify the + environment variables, additional initialization args, and expected instance + attributes to check.""" return {}, {}, {} def test_init_from_env(self) -> None: + """Test initialization from environment variables. Relies on the + ``init_from_env_params`` property. Test is skipped if that property is not + set. + + .. dropdown:: Troubleshooting + + If this test fails, ensure that ``init_from_env_params`` is specified + correctly and that model parameters are properly set from environment + variables during initialization. + """ env_params, embeddings_params, expected_attrs = self.init_from_env_params if env_params: with mock.patch.dict(os.environ, env_params): diff --git a/libs/standard-tests/tests/unit_tests/test_embeddings.py b/libs/standard-tests/tests/unit_tests/test_embeddings.py new file mode 100644 index 0000000000000..d2a551deccafe --- /dev/null +++ b/libs/standard-tests/tests/unit_tests/test_embeddings.py @@ -0,0 +1,26 @@ +from typing import Type + +from langchain_core.embeddings import DeterministicFakeEmbedding, Embeddings + +from langchain_tests.integration_tests import EmbeddingsIntegrationTests +from langchain_tests.unit_tests import EmbeddingsUnitTests + + +class TestFakeEmbeddingsUnit(EmbeddingsUnitTests): + @property + def embeddings_class(self) -> Type[Embeddings]: + return DeterministicFakeEmbedding + + @property + def embedding_model_params(self) -> dict: + return {"size": 6} # embedding dimension + + +class TestFakeEmbeddingsIntegration(EmbeddingsIntegrationTests): + @property + def embeddings_class(self) -> Type[Embeddings]: + return DeterministicFakeEmbedding + + @property + def embedding_model_params(self) -> dict: + return {"size": 6} From 3d5493593bd03908fa14ca38aa44eae05b585775 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 5 Dec 2024 12:41:41 -0800 Subject: [PATCH 012/157] docs: deprecated styling (#28546) from ![image](https://github.com/user-attachments/assets/52565861-618b-407c-8bb4-f16dce3b5718) to ![image](https://github.com/user-attachments/assets/fafeef00-6101-42cd-a8c6-ca15808d1e7c) --- docs/api_reference/_static/css/custom.css | 13 ++++++++++++- 1 file changed, 12 insertions(+), 1 deletion(-) diff --git a/docs/api_reference/_static/css/custom.css b/docs/api_reference/_static/css/custom.css index 87195de8f72ef..6775608a72daa 100644 --- a/docs/api_reference/_static/css/custom.css +++ b/docs/api_reference/_static/css/custom.css @@ -80,6 +80,8 @@ html { --pst-font-family-base: 'Inter'; --pst-font-family-heading: 'Inter Tight', sans-serif; + + --pst-icon-versionmodified-deprecated: var(--pst-icon-exclamation-triangle); } /******************************************************************************* @@ -408,4 +410,13 @@ dl[class]:not(.option-list):not(.field-list):not(.footnote):not(.glossary):not(. p { font-size: 0.9rem; margin-bottom: 0.5rem; -} \ No newline at end of file +} + +div.deprecated { + background-color: var(--pst-color-warning-bg); + border-color: var(--pst-color-warning); +} + +span.versionmodified.deprecated:before { + color: var(--pst-color-warning); +} From 66f819c59ebc595d6c4caf0b7061258b7be656c6 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 5 Dec 2024 13:09:25 -0800 Subject: [PATCH 013/157] infra: run cli tests on test changes (#28542) --- .github/scripts/check_diff.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/.github/scripts/check_diff.py b/.github/scripts/check_diff.py index 873a98d158c71..a85f05dc613f8 100644 --- a/.github/scripts/check_diff.py +++ b/.github/scripts/check_diff.py @@ -273,6 +273,8 @@ def _get_configs_for_multi_dirs( # note: won't run on external repo partners dirs_to_run["lint"].add("libs/standard-tests") dirs_to_run["test"].add("libs/standard-tests") + dirs_to_run["lint"].add("libs/cli") + dirs_to_run["test"].add("libs/cli") dirs_to_run["test"].add("libs/partners/mistralai") dirs_to_run["test"].add("libs/partners/openai") dirs_to_run["test"].add("libs/partners/anthropic") From 5519a1c1d37d110d954e2b5f18ea3f2b25bb0fb3 Mon Sep 17 00:00:00 2001 From: ccurme Date: Thu, 5 Dec 2024 16:32:09 -0500 Subject: [PATCH 014/157] docs[patch]: improve integration docs (#28547) Alternative to https://github.com/langchain-ai/langchain/pull/28426 --------- Co-authored-by: Erick Friis --- .../how_to/integrations/index.mdx | 47 +-- .../how_to/integrations/package.mdx | 285 +++++++----------- .../how_to/integrations/standard_tests.ipynb | 103 +++++++ 3 files changed, 236 insertions(+), 199 deletions(-) diff --git a/docs/docs/contributing/how_to/integrations/index.mdx b/docs/docs/contributing/how_to/integrations/index.mdx index eeb0f73b3fdbb..d8cdf2788c088 100644 --- a/docs/docs/contributing/how_to/integrations/index.mdx +++ b/docs/docs/contributing/how_to/integrations/index.mdx @@ -4,14 +4,16 @@ pagination_next: contributing/how_to/integrations/package # Contribute Integrations -LangChain integrations are packages that provide access to language models, vector stores, and other components that can be used in LangChain. +Integrations are a core component of LangChain. +LangChain provides standard interfaces for several different components (language models, vector stores, etc) that are crucial when building LLM applications. -This guide will walk you through how to contribute new integrations to LangChain, by -publishing an integration package to PyPi, and adding documentation for it -to the LangChain Monorepo. -These instructions will evolve over the next few months as we improve our integration -processes. +## Why contribute an integration to LangChain? + +- **Discoverability:** LangChain is the most used framework for building LLM applications, with over 20 million monthly downloads. LangChain integrations are discoverable by a large community of GenAI builders. +- **Interoptability:** LangChain components expose a standard interface, allowing developers to easily swap them for each other. If you implement a LangChain integration, any developer using a different component will easily be able to swap yours in. +- **Best Practices:** Through their standard interface, LangChain components encourage and facilitate best practices (streaming, async, etc) + ## Components to Integrate @@ -22,8 +24,7 @@ supported in LangChain ::: -While any component can be integrated into LangChain, at this time we are only accepting -new integrations in the docs of the following kinds: +While any component can be integrated into LangChain, there are specific types of integrations we encourage more: @@ -60,18 +61,30 @@ new integrations in the docs of the following kinds: ## How to contribute an integration -The only step necessary to "be" a LangChain integration is to add documentation -that will render on this site (https://python.langchain.com/). +In order to contribute an integration, you should follow these steps: -As a prerequisite to adding your integration to our documentation, you must: - -1. Confirm that your integration is in the [list of components](#components-to-integrate) we are currently accepting. -2. [Implement your package](./package.mdx) and publish it to a public github repository. +1. Confirm that your integration is in the [list of components](#components-to-integrate) we are currently encouraging. +2. [Implement your package](/docs/contributing/how_to/integrations/package/) and publish it to a public github repository. 3. [Implement the standard tests](./standard_tests) for your integration and successfully run them. 4. [Publish your integration](./publish.mdx) by publishing the package to PyPi and add docs in the `docs/docs/integrations` directory of the LangChain monorepo. +5. [Optional] Open and merge a PR to add documentation for your integration to the official LangChain docs. +6. [Optional] Engage with the LangChain team for joint co-marketing ([see below](#co-marketing)). -Once you have completed these steps, you can submit a PR to the LangChain monorepo to add your integration to the documentation. +## Co-Marketing -## Further Reading +With over 20 million monthly downloads, LangChain has a large audience of developers building LLM applications. +Besides just adding integrations, we also like to show them examples of cool tools or APIs they can use. -To get started, let's learn [how to bootstrap a new integration package](./package.mdx) for LangChain. +While traditionally called "co-marketing", we like to think of this more as "co-education". +For that reason, while we are happy to highlight your integration through our social media channels, we prefer to highlight examples that also serve some educational purpose. +Our main social media channels are Twitter and LinkedIn. + +Here are some heuristics for types of content we are excited to promote: + +- **Integration announcement:** If you announce the integration with a link to the LangChain documentation page, we are happy to re-tweet/re-share on Twitter/LinkedIn. +- **Educational content:** We highlight good educational content on the weekends - if you write a good blog or make a good YouTube video, we are happy to share there! Note that we prefer content that is NOT framed as "here's how to use integration XYZ", but rather "here's how to do ABC", as we find that is more educational and helpful for developers. +- **End-to-end applications:** End-to-end applications are great resources for developers looking to build. We prefer to highlight applications that are more complex/agentic in nature, and that use [LangGraph](https://github.com/langchain-ai/langgraph) as the orchestration framework. We get particularly excited about anything involving long-term memory, human-in-the-loop interaction patterns, or multi-agent architectures. +- **Research:** We love highlighting novel research! Whether it is research built on top of LangChain or that integrates with it. + +## Further Reading +To get started, let's learn [how to implement an integration package](/docs/contributing/how_to/integrations/package/) for LangChain. diff --git a/docs/docs/contributing/how_to/integrations/package.mdx b/docs/docs/contributing/how_to/integrations/package.mdx index 8189ce97f8ba3..2b5bb97865e5b 100644 --- a/docs/docs/contributing/how_to/integrations/package.mdx +++ b/docs/docs/contributing/how_to/integrations/package.mdx @@ -2,23 +2,117 @@ pagination_next: contributing/how_to/integrations/standard_tests pagination_prev: contributing/how_to/integrations/index --- -# How to bootstrap a new integration package +# How to implement an integration package -This guide walks through the process of publishing a new LangChain integration -package to PyPi. +This guide walks through the process of implementing a LangChain integration +package. Integration packages are just Python packages that can be installed with `pip install `, which contain classes that are compatible with LangChain's core interfaces. +We will cover: + +1. How to implement components, such as [chat models](/docs/concepts/chat_models/) and [vector stores](/docs/concepts/vectorstores/), that adhere +to the LangChain interface; +2. (Optional) How to bootstrap a new integration package. + +## Implementing LangChain components + +LangChain components are subclasses of base classes in [langchain-core](/docs/concepts/architecture/#langchain-core). +Examples include [chat models](/docs/concepts/chat_models/), +[vector stores](/docs/concepts/vectorstores/), [tools](/docs/concepts/tools/), +[embedding models](/docs/concepts/embedding_models/) and [retrievers](/docs/concepts/retrievers/). + +Your integration package will typically implement a subclass of at least one of these +components. Expand the tabs below to see details on each. + +
+ Chat models + +Refer to the [Custom Chat Model Guide](/docs/how_to/custom_chat_model) guide for +detail on a starter chat model [implementation](/docs/how_to/custom_chat_model/#implementation). + +:::tip + +The model from the [Custom Chat Model Guide](/docs/how_to/custom_chat_model) is tested +against the standard unit and integration tests in the LangChain Github repository. +You can also access that implementation directly from Github +[here](https://github.com/langchain-ai/langchain/blob/master/libs/standard-tests/tests/unit_tests/custom_chat_model.py). + +::: + +
+ +
+ Vector stores + +Your vector store implementation will depend on your chosen database technology. +`langchain-core` includes a minimal +[in-memory vector store](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.in_memory.InMemoryVectorStore.html) +that we can use as a guide. You can access the code [here](https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/vectorstores/in_memory.py). + +All vector stores must inherit from the [VectorStore](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) +base class. This interface consists of methods for writing, deleting and searching +for documents in the vector store. + +`VectorStore` supports a variety of synchronous and asynchronous search types (e.g., +nearest-neighbor or maximum marginal relevance), as well as interfaces for adding +documents to the store. See the [API Reference](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) +for all supported methods. The required methods are tabulated below: + +| Method/Property | Description | +|------------------------ |------------------------------------------------------| +| `add_documents` | Add documents to the vector store. | +| `delete` | Delete selected documents from vector store (by IDs) | +| `get_by_ids` | Get selected documents from vector store (by IDs) | +| `similarity_search` | Get documents most similar to a query. | +| `embeddings` (property) | Embeddings object for vector store. | +| `from_texts` | Instantiate vector store via adding texts. | + +Note that `InMemoryVectorStore` implements some optional search types, as well as +convenience methods for loading and dumping the object to a file, but this is not +necessary for all implementations. + +:::tip + +The [in-memory vector store](https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/vectorstores/in_memory.py) +is tested against the standard tests in the LangChain Github repository. + +::: + +
+ + + +## (Optional) bootstrapping a new integration package + In this guide, we will be using [Poetry](https://python-poetry.org/) for dependency management and packaging, and you're welcome to use any other tools you prefer. -## **Prerequisites** +### **Prerequisites** - [GitHub](https://github.com) account - [PyPi](https://pypi.org/) account -## Boostrapping a new Python package with Poetry +### Boostrapping a new Python package with Poetry First, install Poetry: @@ -64,7 +158,7 @@ poetry install --with test You're now ready to start writing your integration package! -## Writing your integration +### Writing your integration Let's say you're building a simple integration package that provides a `ChatParrotLink` chat model integration for LangChain. Here's a simple example of what your project @@ -86,183 +180,10 @@ All of these files should already exist from step 1, except for `chat_models.py` and `test_chat_models.py`! We will implement `test_chat_models.py` later, following the [standard tests](../standard_tests) guide. -To implement `chat_models.py`, let's copy the implementation from our -[Custom Chat Model Guide](../../../../how_to/custom_chat_model). - -
- chat_models.py -```python title="langchain_parrot_link/chat_models.py" -from typing import Any, Dict, Iterator, List, Optional - -from langchain_core.callbacks import ( - CallbackManagerForLLMRun, -) -from langchain_core.language_models import BaseChatModel -from langchain_core.messages import ( - AIMessage, - AIMessageChunk, - BaseMessage, -) -from langchain_core.messages.ai import UsageMetadata -from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult -from pydantic import Field - - -class ChatParrotLink(BaseChatModel): - """A custom chat model that echoes the first `parrot_buffer_length` characters - of the input. - - When contributing an implementation to LangChain, carefully document - the model including the initialization parameters, include - an example of how to initialize the model and include any relevant - links to the underlying models documentation or API. - - Example: - - .. code-block:: python - - model = ChatParrotLink(parrot_buffer_length=2, model="bird-brain-001") - result = model.invoke([HumanMessage(content="hello")]) - result = model.batch([[HumanMessage(content="hello")], - [HumanMessage(content="world")]]) - """ - - model_name: str = Field(alias="model") - """The name of the model""" - parrot_buffer_length: int - """The number of characters from the last message of the prompt to be echoed.""" - temperature: Optional[float] = None - max_tokens: Optional[int] = None - timeout: Optional[int] = None - stop: Optional[List[str]] = None - max_retries: int = 2 - - def _generate( - self, - messages: List[BaseMessage], - stop: Optional[List[str]] = None, - run_manager: Optional[CallbackManagerForLLMRun] = None, - **kwargs: Any, - ) -> ChatResult: - """Override the _generate method to implement the chat model logic. - - This can be a call to an API, a call to a local model, or any other - implementation that generates a response to the input prompt. - - Args: - messages: the prompt composed of a list of messages. - stop: a list of strings on which the model should stop generating. - If generation stops due to a stop token, the stop token itself - SHOULD BE INCLUDED as part of the output. This is not enforced - across models right now, but it's a good practice to follow since - it makes it much easier to parse the output of the model - downstream and understand why generation stopped. - run_manager: A run manager with callbacks for the LLM. - """ - # Replace this with actual logic to generate a response from a list - # of messages. - last_message = messages[-1] - tokens = last_message.content[: self.parrot_buffer_length] - ct_input_tokens = sum(len(message.content) for message in messages) - ct_output_tokens = len(tokens) - message = AIMessage( - content=tokens, - additional_kwargs={}, # Used to add additional payload to the message - response_metadata={ # Use for response metadata - "time_in_seconds": 3, - }, - usage_metadata={ - "input_tokens": ct_input_tokens, - "output_tokens": ct_output_tokens, - "total_tokens": ct_input_tokens + ct_output_tokens, - }, - ) - ## - - generation = ChatGeneration(message=message) - return ChatResult(generations=[generation]) - - def _stream( - self, - messages: List[BaseMessage], - stop: Optional[List[str]] = None, - run_manager: Optional[CallbackManagerForLLMRun] = None, - **kwargs: Any, - ) -> Iterator[ChatGenerationChunk]: - """Stream the output of the model. - - This method should be implemented if the model can generate output - in a streaming fashion. If the model does not support streaming, - do not implement it. In that case streaming requests will be automatically - handled by the _generate method. - - Args: - messages: the prompt composed of a list of messages. - stop: a list of strings on which the model should stop generating. - If generation stops due to a stop token, the stop token itself - SHOULD BE INCLUDED as part of the output. This is not enforced - across models right now, but it's a good practice to follow since - it makes it much easier to parse the output of the model - downstream and understand why generation stopped. - run_manager: A run manager with callbacks for the LLM. - """ - last_message = messages[-1] - tokens = str(last_message.content[: self.parrot_buffer_length]) - ct_input_tokens = sum(len(message.content) for message in messages) - - for token in tokens: - usage_metadata = UsageMetadata( - { - "input_tokens": ct_input_tokens, - "output_tokens": 1, - "total_tokens": ct_input_tokens + 1, - } - ) - ct_input_tokens = 0 - chunk = ChatGenerationChunk( - message=AIMessageChunk(content=token, usage_metadata=usage_metadata) - ) - - if run_manager: - # This is optional in newer versions of LangChain - # The on_llm_new_token will be called automatically - run_manager.on_llm_new_token(token, chunk=chunk) - - yield chunk - - # Let's add some other information (e.g., response metadata) - chunk = ChatGenerationChunk( - message=AIMessageChunk(content="", response_metadata={"time_in_sec": 3}) - ) - if run_manager: - # This is optional in newer versions of LangChain - # The on_llm_new_token will be called automatically - run_manager.on_llm_new_token(token, chunk=chunk) - yield chunk - - @property - def _llm_type(self) -> str: - """Get the type of language model used by this chat model.""" - return "echoing-chat-model-advanced" - - @property - def _identifying_params(self) -> Dict[str, Any]: - """Return a dictionary of identifying parameters. - - This information is used by the LangChain callback system, which - is used for tracing purposes make it possible to monitor LLMs. - """ - return { - # The model name allows users to specify custom token counting - # rules in LLM monitoring applications (e.g., in LangSmith users - # can provide per token pricing for their model and monitor - # costs for the given LLM.) - "model_name": self.model_name, - } -``` -
+For `chat_models.py`, simply paste the contents of the chat model implementation +[above](#implementing-langchain-components). -## Push your package to a public Github repository +### Push your package to a public Github repository This is only required if you want to publish your integration in the LangChain documentation. diff --git a/docs/docs/contributing/how_to/integrations/standard_tests.ipynb b/docs/docs/contributing/how_to/integrations/standard_tests.ipynb index 8bee8a45dd200..a01dc8a60a305 100644 --- a/docs/docs/contributing/how_to/integrations/standard_tests.ipynb +++ b/docs/docs/contributing/how_to/integrations/standard_tests.ipynb @@ -219,6 +219,41 @@ "

Note: The standard tests for chat models are implemented in the example in the main body of this guide too.

" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Chat model standard tests test a range of behaviors, from the most basic requirements (generating a response to a query) to optional capabilities like multi-modal support and tool-calling. For a test run to be successful:\n", + "\n", + "1. If a feature is intended to be supported by the model, it should pass;\n", + "2. If a feature is not intended to be supported by the model, it should be skipped.\n", + "\n", + "Tests for \"optional\" capabilities are controlled via a set of properties that can be overridden on the test model subclass.\n", + "\n", + "You can see the entire list of properties in the API reference [here](https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.chat_models.ChatModelTests.html). These properties are shared by both unit and integration tests.\n", + "\n", + "For example, to enable integration tests for image inputs, we can implement\n", + "\n", + "```python\n", + "@property\n", + "def supports_image_inputs(self) -> bool:\n", + " return True\n", + "```\n", + "\n", + "on the integration test class.\n", + "\n", + ":::note\n", + "\n", + "Details on what tests are run, how each test can be skipped, and troubleshooting tips for each test can be found in the API references. See details:\n", + "\n", + "- [Unit tests API reference](https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.chat_models.ChatModelUnitTests.html)\n", + "- [Integration tests API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.chat_models.ChatModelIntegrationTests.html)\n", + "\n", + ":::\n", + "\n", + "Unit test example:" + ] + }, { "cell_type": "code", "execution_count": null, @@ -246,6 +281,13 @@ " }" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Integration test example:" + ] + }, { "cell_type": "code", "execution_count": null, @@ -418,6 +460,14 @@ " Vector Stores" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here's how you would configure the standard tests for a typical vector store (using\n", + "`ParrotVectorStore` as a placeholder):" + ] + }, { "cell_type": "code", "execution_count": null, @@ -465,6 +515,59 @@ " pass" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "There are separate suites for testing synchronous and asynchronous methods.\n", + "Configuring the tests consists of implementing pytest fixtures for setting up an\n", + "empty vector store and tearing down the vector store after the test run ends.\n", + "\n", + "For example, below is the `ReadWriteTestSuite` for the [Chroma](https://python.langchain.com/docs/integrations/vectorstores/chroma/)\n", + "integration:\n", + "\n", + "```python\n", + "from typing import Generator\n", + "\n", + "import pytest\n", + "from langchain_core.vectorstores import VectorStore\n", + "from langchain_tests.integration_tests.vectorstores import ReadWriteTestSuite\n", + "\n", + "from langchain_chroma import Chroma\n", + "\n", + "\n", + "class TestSync(ReadWriteTestSuite):\n", + " @pytest.fixture()\n", + " def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore\n", + " \"\"\"Get an empty vectorstore.\"\"\"\n", + " store = Chroma(embedding_function=self.get_embeddings())\n", + " try:\n", + " yield store\n", + " finally:\n", + " store.delete_collection()\n", + " pass\n", + "```\n", + "\n", + "Note that before the initial `yield`, we instantiate the vector store with an\n", + "[embeddings](/docs/concepts/embedding_models/) object. This is a pre-defined\n", + "[\"fake\" embeddings model](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.vectorstores.ReadWriteTestSuite.html#langchain_tests.integration_tests.vectorstores.ReadWriteTestSuite.get_embeddings)\n", + "that will generate short, arbitrary vectors for documents. You can use a different\n", + "embeddings object if desired.\n", + "\n", + "In the `finally` block, we call whatever integration-specific logic is needed to\n", + "bring the vector store to a clean state. This logic is executed in between each test\n", + "(e.g., even if tests fail).\n", + "\n", + ":::note\n", + "\n", + "Details on what tests are run, how each test can be skipped, and troubleshooting tips for each test can be found in the API references. See details:\n", + "\n", + "- [Sync tests API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.vectorstores.ReadWriteTestSuite.html)\n", + "- [Async tests API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.vectorstores.AsyncReadWriteTestSuite.html)\n", + "\n", + ":::" + ] + }, { "cell_type": "markdown", "metadata": {}, From 7a96ce132059a750f86e72ac92c0916db3b44a01 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 5 Dec 2024 14:05:25 -0800 Subject: [PATCH 015/157] docs: deprecated styling (#28550) --- docs/api_reference/_static/css/custom.css | 16 +++++++--------- 1 file changed, 7 insertions(+), 9 deletions(-) diff --git a/docs/api_reference/_static/css/custom.css b/docs/api_reference/_static/css/custom.css index 6775608a72daa..19d0c0680db58 100644 --- a/docs/api_reference/_static/css/custom.css +++ b/docs/api_reference/_static/css/custom.css @@ -391,6 +391,13 @@ html[data-theme=dark] .MathJax_SVG * { div.deprecated { margin-top: 0.5em; margin-bottom: 2em; + + background-color: var(--pst-color-warning-bg); + border-color: var(--pst-color-warning); +} + +span.versionmodified.deprecated:before { + color: var(--pst-color-warning); } .admonition-beta.admonition, div.admonition-beta.admonition { @@ -411,12 +418,3 @@ p { font-size: 0.9rem; margin-bottom: 0.5rem; } - -div.deprecated { - background-color: var(--pst-color-warning-bg); - border-color: var(--pst-color-warning); -} - -span.versionmodified.deprecated:before { - color: var(--pst-color-warning); -} From 28f8d436f6778bd21cd310e12996300dc64a6d02 Mon Sep 17 00:00:00 2001 From: blaufink <88979818+blaufink@users.noreply.github.com> Date: Fri, 6 Dec 2024 00:28:12 +0100 Subject: [PATCH 016/157] mistral: fix of issue #26029 (#28233) - Description: Azure AI takes an issue with the safe_mode parameter being set to False instead of None. Therefore, this PR changes the default value of safe_mode from False to None. This results in it being filtered out before the request is sent - avoind the extra-parameter issue described below. - Issue: #26029 - Dependencies: / --------- Co-authored-by: blaufink Co-authored-by: Erick Friis --- libs/partners/mistralai/langchain_mistralai/chat_models.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/libs/partners/mistralai/langchain_mistralai/chat_models.py b/libs/partners/mistralai/langchain_mistralai/chat_models.py index aed0f70542786..9e68e23ae4542 100644 --- a/libs/partners/mistralai/langchain_mistralai/chat_models.py +++ b/libs/partners/mistralai/langchain_mistralai/chat_models.py @@ -388,7 +388,7 @@ class ChatMistralAI(BaseChatModel): """Decode using nucleus sampling: consider the smallest set of tokens whose probability sum is at least top_p. Must be in the closed interval [0.0, 1.0].""" random_seed: Optional[int] = None - safe_mode: bool = False + safe_mode: Optional[bool] = None streaming: bool = False model_config = ConfigDict( From 482e8a785564007e01832c6bee9df9fad807a46e Mon Sep 17 00:00:00 2001 From: cinqisap <158295355+cinqisap@users.noreply.github.com> Date: Fri, 6 Dec 2024 00:29:08 +0100 Subject: [PATCH 017/157] community: Add support for SAP HANA Vector hnsw index creation (#27884) **Issue:** Added support for creating indexes in the SAP HANA Vector engine. **Changes**: 1. Introduced a new function `create_hnsw_index` in `hanavector.py` that enables the creation of indexes for SAP HANA Vector. 2. Added integration tests for the index creation function to ensure functionality. 3. Updated the documentation to reflect the new index creation feature, including examples and output from the notebook. 4. Fix the operator issue in ` _process_filter_object` function and change the array argument to a placeholder in the similarity search SQL statement. --------- Co-authored-by: Erick Friis --- .../vectorstores/sap_hanavector.ipynb | 458 +++++++++++++++--- .../vectorstores/hanavector.py | 91 +++- .../vectorstores/test_hanavector.py | 190 ++++++++ 3 files changed, 681 insertions(+), 58 deletions(-) diff --git a/docs/docs/integrations/vectorstores/sap_hanavector.ipynb b/docs/docs/integrations/vectorstores/sap_hanavector.ipynb index 90a0ed5e668e6..ded2118134bc2 100644 --- a/docs/docs/integrations/vectorstores/sap_hanavector.ipynb +++ b/docs/docs/integrations/vectorstores/sap_hanavector.ipynb @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": { "tags": [] }, @@ -41,7 +41,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 1, "metadata": { "ExecuteTime": { "end_time": "2023-09-09T08:02:16.802456Z", @@ -64,7 +64,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": { "ExecuteTime": { "end_time": "2023-09-09T08:02:28.174088Z", @@ -73,8 +73,10 @@ }, "outputs": [], "source": [ + "from dotenv import load_dotenv\n", "from hdbcli import dbapi\n", "\n", + "load_dotenv()\n", "# Use connection settings from the environment\n", "connection = dbapi.connect(\n", " address=os.environ.get(\"HANA_DB_ADDRESS\"),\n", @@ -102,14 +104,22 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 10, "metadata": { "ExecuteTime": { "end_time": "2023-09-09T08:02:25.452472Z", "start_time": "2023-09-09T08:02:25.441563Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of document chunks: 88\n" + ] + } + ], "source": [ "from langchain_community.document_loaders import TextLoader\n", "from langchain_community.vectorstores.hanavector import HanaDB\n", @@ -134,7 +144,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2023-09-09T08:04:16.696625Z", @@ -157,9 +167,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Delete already existing documents from the table\n", "db.delete(filter={})\n", @@ -178,9 +199,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n", + "\n", + "And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n", + "--------------------------------------------------------------------------------\n", + "As I said last year, especially to our younger transgender Americans, I will always have your back as your President, so you can be yourself and reach your God-given potential. \n", + "\n", + "While it often appears that we never agree, that isn’t true. I signed 80 bipartisan bills into law last year. From preventing government shutdowns to protecting Asian-Americans from still-too-common hate crimes to reforming military justice.\n" + ] + } + ], "source": [ "query = \"What did the president say about Ketanji Brown Jackson\"\n", "docs = db.similarity_search(query, k=2)\n", @@ -199,9 +235,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n", + "\n", + "And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n", + "--------------------------------------------------------------------------------\n", + "As I said last year, especially to our younger transgender Americans, I will always have your back as your President, so you can be yourself and reach your God-given potential. \n", + "\n", + "While it often appears that we never agree, that isn’t true. I signed 80 bipartisan bills into law last year. From preventing government shutdowns to protecting Asian-Americans from still-too-common hate crimes to reforming military justice.\n" + ] + } + ], "source": [ "from langchain_community.vectorstores.utils import DistanceStrategy\n", "\n", @@ -235,7 +286,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": { "ExecuteTime": { "end_time": "2023-09-09T08:05:23.276819Z", @@ -246,7 +297,24 @@ "outputs_hidden": false } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n", + "\n", + "And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n", + "--------------------------------------------------------------------------------\n", + "Groups of citizens blocking tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland. \n", + "\n", + "In this struggle as President Zelenskyy said in his speech to the European Parliament “Light will win over darkness.” The Ukrainian Ambassador to the United States is here tonight. \n", + "\n", + "Let each of us here tonight in this Chamber send an unmistakable signal to Ukraine and to the world.\n" + ] + } + ], "source": [ "docs = db.max_marginal_relevance_search(query, k=2, fetch_k=20)\n", "for doc in docs:\n", @@ -254,6 +322,86 @@ " print(doc.page_content)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Creating an HNSW Vector Index\n", + "\n", + "A vector index can significantly speed up top-k nearest neighbor queries for vectors. Users can create a Hierarchical Navigable Small World (HNSW) vector index using the `create_hnsw_index` function.\n", + "\n", + "For more information about creating an index at the database level, please refer to the [official documentation](https://help.sap.com/docs/hana-cloud-database/sap-hana-cloud-sap-hana-database-vector-engine-guide/create-vector-index-statement-data-definition).\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n", + "\n", + "And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.\n", + "--------------------------------------------------------------------------------\n", + "Groups of citizens blocking tanks with their bodies. Everyone from students to retirees teachers turned soldiers defending their homeland. \n", + "\n", + "In this struggle as President Zelenskyy said in his speech to the European Parliament “Light will win over darkness.” The Ukrainian Ambassador to the United States is here tonight. \n", + "\n", + "Let each of us here tonight in this Chamber send an unmistakable signal to Ukraine and to the world.\n" + ] + } + ], + "source": [ + "# HanaDB instance uses cosine similarity as default:\n", + "db_cosine = HanaDB(\n", + " embedding=embeddings, connection=connection, table_name=\"STATE_OF_THE_UNION\"\n", + ")\n", + "\n", + "# Attempting to create the HNSW index with default parameters\n", + "db_cosine.create_hnsw_index() # If no other parameters are specified, the default values will be used\n", + "# Default values: m=64, ef_construction=128, ef_search=200\n", + "# The default index name will be: STATE_OF_THE_UNION_COSINE_SIMILARITY_IDX (verify this naming pattern in HanaDB class)\n", + "\n", + "\n", + "# Creating a HanaDB instance with L2 distance as the similarity function and defined values\n", + "db_l2 = HanaDB(\n", + " embedding=embeddings,\n", + " connection=connection,\n", + " table_name=\"STATE_OF_THE_UNION\",\n", + " distance_strategy=DistanceStrategy.EUCLIDEAN_DISTANCE, # Specify L2 distance\n", + ")\n", + "\n", + "# This will create an index based on L2 distance strategy.\n", + "db_l2.create_hnsw_index(\n", + " index_name=\"STATE_OF_THE_UNION_L2_index\",\n", + " m=100, # Max number of neighbors per graph node (valid range: 4 to 1000)\n", + " ef_construction=200, # Max number of candidates during graph construction (valid range: 1 to 100000)\n", + " ef_search=500, # Min number of candidates during the search (valid range: 1 to 100000)\n", + ")\n", + "\n", + "# Use L2 index to perform MMR\n", + "docs = db_l2.max_marginal_relevance_search(query, k=2, fetch_k=20)\n", + "for doc in docs:\n", + " print(\"-\" * 80)\n", + " print(doc.page_content)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "**Key Points**:\n", + "- **Similarity Function**: The similarity function for the index is **cosine similarity** by default. If you want to use a different similarity function (e.g., `L2` distance), you need to specify it when initializing the `HanaDB` instance.\n", + "- **Default Parameters**: In the `create_hnsw_index` function, if the user does not provide custom values for parameters like `m`, `ef_construction`, or `ef_search`, the default values (e.g., `m=64`, `ef_construction=128`, `ef_search=200`) will be used automatically. These values ensure the index is created with reasonable performance without requiring user intervention.\n", + "\n" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -263,9 +411,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "db = HanaDB(\n", " connection=connection, embedding=embeddings, table_name=\"LANGCHAIN_DEMO_BASIC\"\n", @@ -284,9 +443,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "docs = [Document(page_content=\"Some text\"), Document(page_content=\"Other docs\")]\n", "db.add_documents(docs)" @@ -301,9 +471,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "docs = [\n", " Document(\n", @@ -327,9 +508,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "foo\n", + "{'start': 100, 'end': 150, 'doc_name': 'foo.txt', 'quality': 'bad'}\n" + ] + } + ], "source": [ "docs = db.similarity_search(\"foobar\", k=2, filter={\"quality\": \"bad\"})\n", "# With filtering on \"quality\"==\"bad\", only one document should be returned\n", @@ -348,9 +539,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n" + ] + } + ], "source": [ "db.delete(filter={\"quality\": \"bad\"})\n", "\n", @@ -385,7 +584,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -433,9 +632,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filter: {'id': {'$ne': 1}}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n", + "Filter: {'id': {'$gt': 1}}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n", + "Filter: {'id': {'$gte': 1}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n", + "Filter: {'id': {'$lt': 1}}\n", + "\n", + "Filter: {'id': {'$lte': 1}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n" + ] + } + ], "source": [ "advanced_filter = {\"id\": {\"$ne\": 1}}\n", "print(f\"Filter: {advanced_filter}\")\n", @@ -467,9 +687,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filter: {'id': {'$between': (1, 2)}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "Filter: {'name': {'$in': ['adam', 'bob']}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "Filter: {'name': {'$nin': ['adam', 'bob']}}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n" + ] + } + ], "source": [ "advanced_filter = {\"id\": {\"$between\": (1, 2)}}\n", "print(f\"Filter: {advanced_filter}\")\n", @@ -493,9 +728,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filter: {'name': {'$like': 'a%'}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "Filter: {'name': {'$like': '%a%'}}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n" + ] + } + ], "source": [ "advanced_filter = {\"name\": {\"$like\": \"a%\"}}\n", "print(f\"Filter: {advanced_filter}\")\n", @@ -515,9 +762,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filter: {'$or': [{'id': 1}, {'name': 'bob'}]}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "Filter: {'$and': [{'id': 1}, {'id': 2}]}\n", + "\n", + "Filter: {'$or': [{'id': 1}, {'id': 2}, {'id': 3}]}\n", + "{'name': 'adam', 'is_active': True, 'id': 1, 'height': 10.0}\n", + "{'name': 'bob', 'is_active': False, 'id': 2, 'height': 5.7}\n", + "{'name': 'jane', 'is_active': True, 'id': 3, 'height': 2.4}\n" + ] + } + ], "source": [ "advanced_filter = {\"$or\": [{\"id\": 1}, {\"name\": \"bob\"}]}\n", "print(f\"Filter: {advanced_filter}\")\n", @@ -541,7 +804,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ @@ -574,7 +837,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -635,9 +898,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Answer from LLM:\n", + "================\n", + "The United States has set up joint patrols with Mexico and Guatemala to catch more human traffickers. This collaboration is part of the efforts to address immigration issues and secure the borders in the region.\n", + "================\n", + "Number of used source document chunks: 5\n" + ] + } + ], "source": [ "question = \"What about Mexico and Guatemala?\"\n", "\n", @@ -679,9 +954,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 34, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Answer from LLM:\n", + "================\n", + "Mexico and Guatemala are involved in joint patrols to catch human traffickers.\n" + ] + } + ], "source": [ "question = \"What about other countries?\"\n", "\n", @@ -711,9 +996,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# Access the vector DB with a new table\n", "db = HanaDB(\n", @@ -742,9 +1038,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('VEC_META', 'NCLOB')\n", + "('VEC_TEXT', 'NCLOB')\n", + "('VEC_VECTOR', 'REAL_VECTOR')\n" + ] + } + ], "source": [ "cur = connection.cursor()\n", "cur.execute(\n", @@ -795,12 +1101,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "None\n", + "Some other text\n", + "{\"start\": 400, \"end\": 450, \"doc_name\": \"other.txt\"}\n", + "\n" + ] + } + ], "source": [ - "# Create a new table \"MY_OWN_TABLE\" with three \"standard\" columns and one additional column\n", - "my_own_table_name = \"MY_OWN_TABLE\"\n", + "# Create a new table \"MY_OWN_TABLE_ADD\" with three \"standard\" columns and one additional column\n", + "my_own_table_name = \"MY_OWN_TABLE_ADD\"\n", "cur = connection.cursor()\n", "cur.execute(\n", " (\n", @@ -851,9 +1168,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "Some other text\n", + "--------------------------------------------------------------------------------\n", + "Some more text\n" + ] + } + ], "source": [ "docs = [\n", " Document(\n", @@ -886,9 +1214,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 41, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Filters on this value are very performant\n", + "Some other text\n", + "{\"start\": 400, \"end\": 450, \"doc_name\": \"other.txt\", \"CUSTOMTEXT\": \"Filters on this value are very performant\"}\n", + "\n" + ] + } + ], "source": [ "# Create a new table \"PERFORMANT_CUSTOMTEXT_FILTER\" with three \"standard\" columns and one additional column\n", "my_own_table_name = \"PERFORMANT_CUSTOMTEXT_FILTER\"\n", @@ -952,9 +1291,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--------------------------------------------------------------------------------\n", + "Some other text\n", + "--------------------------------------------------------------------------------\n", + "Some more text\n" + ] + } + ], "source": [ "docs = [\n", " Document(\n", @@ -994,7 +1344,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.10.14" } }, "nbformat": 4, diff --git a/libs/community/langchain_community/vectorstores/hanavector.py b/libs/community/langchain_community/vectorstores/hanavector.py index 07ced73afe971..6c0a8040b255c 100644 --- a/libs/community/langchain_community/vectorstores/hanavector.py +++ b/libs/community/langchain_community/vectorstores/hanavector.py @@ -256,6 +256,89 @@ def _split_off_special_metadata(self, metadata: dict) -> Tuple[dict, list]: return metadata, special_metadata + def create_hnsw_index( + self, + m: Optional[int] = None, # Optional M parameter + ef_construction: Optional[int] = None, # Optional efConstruction parameter + ef_search: Optional[int] = None, # Optional efSearch parameter + index_name: Optional[str] = None, # Optional custom index name + ) -> None: + """ + Creates an HNSW vector index on a specified table and vector column with + optional build and search configurations. If no configurations are provided, + default parameters from the database are used. If provided values exceed the + valid ranges, an error will be raised. + The index is always created in ONLINE mode. + + Args: + m: (Optional) Maximum number of neighbors per graph node + (Valid Range: [4, 1000]) + ef_construction: (Optional) Maximal candidates to consider when building + the graph (Valid Range: [1, 100000]) + ef_search: (Optional) Minimum candidates for top-k-nearest neighbor + queries (Valid Range: [1, 100000]) + index_name: (Optional) Custom index name. Defaults to + __idx + """ + # Set default index name if not provided + distance_func_name = HANA_DISTANCE_FUNCTION[self.distance_strategy][0] + default_index_name = f"{self.table_name}_{distance_func_name}_idx" + # Use provided index_name or default + index_name = ( + HanaDB._sanitize_name(index_name) if index_name else default_index_name + ) + # Initialize build_config and search_config as empty dictionaries + build_config = {} + search_config = {} + + # Validate and add m parameter to build_config if provided + if m is not None: + m = HanaDB._sanitize_int(m) + if not (4 <= m <= 1000): + raise ValueError("M must be in the range [4, 1000]") + build_config["M"] = m + + # Validate and add ef_construction to build_config if provided + if ef_construction is not None: + ef_construction = HanaDB._sanitize_int(ef_construction) + if not (1 <= ef_construction <= 100000): + raise ValueError("efConstruction must be in the range [1, 100000]") + build_config["efConstruction"] = ef_construction + + # Validate and add ef_search to search_config if provided + if ef_search is not None: + ef_search = HanaDB._sanitize_int(ef_search) + if not (1 <= ef_search <= 100000): + raise ValueError("efSearch must be in the range [1, 100000]") + search_config["efSearch"] = ef_search + + # Convert build_config and search_config to JSON strings if they contain values + build_config_str = json.dumps(build_config) if build_config else "" + search_config_str = json.dumps(search_config) if search_config else "" + + # Create the index SQL string with the ONLINE keyword + sql_str = ( + f'CREATE HNSW VECTOR INDEX {index_name} ON "{self.table_name}" ' + f'("{self.vector_column}") ' + f"SIMILARITY FUNCTION {distance_func_name} " + ) + + # Append build_config to the SQL string if provided + if build_config_str: + sql_str += f"BUILD CONFIGURATION '{build_config_str}' " + + # Append search_config to the SQL string if provided + if search_config_str: + sql_str += f"SEARCH CONFIGURATION '{search_config_str}' " + + # Always add the ONLINE option + sql_str += "ONLINE " + cur = self.connection.cursor() + try: + cur.execute(sql_str) + finally: + cur.close() + def add_texts( # type: ignore[override] self, texts: Iterable[str], @@ -418,18 +501,18 @@ def similarity_search_with_score_and_vector_by_vector( k = HanaDB._sanitize_int(k) embedding = HanaDB._sanitize_list_float(embedding) distance_func_name = HANA_DISTANCE_FUNCTION[self.distance_strategy][0] - embedding_as_str = ",".join(map(str, embedding)) + embedding_as_str = "[" + ",".join(map(str, embedding)) + "]" sql_str = ( f"SELECT TOP {k}" f' "{self.content_column}", ' # row[0] f' "{self.metadata_column}", ' # row[1] f' TO_NVARCHAR("{self.vector_column}"), ' # row[2] - f' {distance_func_name}("{self.vector_column}", TO_REAL_VECTOR ' - f" (ARRAY({embedding_as_str}))) AS CS " # row[3] + f' {distance_func_name}("{self.vector_column}", TO_REAL_VECTOR (?)) AS CS ' f'FROM "{self.table_name}"' ) order_str = f" order by CS {HANA_DISTANCE_FUNCTION[self.distance_strategy][1]}" where_str, query_tuple = self._create_where_by_filter(filter) + query_tuple = (embedding_as_str,) + tuple(query_tuple) sql_str = sql_str + where_str sql_str = sql_str + order_str try: @@ -512,7 +595,7 @@ def _process_filter_object(self, filter): # type: ignore[no-untyped-def] where_str_logical, query_tuple_logical, ) = self._process_filter_object(logical_operand) - where_str += where_str_logical + where_str += "(" + where_str_logical + ")" query_tuple += query_tuple_logical continue diff --git a/libs/community/tests/integration_tests/vectorstores/test_hanavector.py b/libs/community/tests/integration_tests/vectorstores/test_hanavector.py index fd50baf529077..e1ffcd7af0eac 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_hanavector.py +++ b/libs/community/tests/integration_tests/vectorstores/test_hanavector.py @@ -1432,3 +1432,193 @@ def test_preexisting_specific_columns_for_returned_metadata_completeness( assert docs[0].metadata["quality"] == "good" assert docs[0].metadata["ready"] assert "NonExisting" not in docs[0].metadata.keys() + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_with_default_values(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INDEX_DEFAULT" + + # Delete table if it exists (cleanup from previous tests) + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + ) + + # Test the creation of HNSW index + try: + vectorDB.create_hnsw_index() + except Exception as e: + pytest.fail(f"Failed to create HNSW index: {e}") + + # Perform a search using the index to confirm its correctness + search_result = vectorDB.max_marginal_relevance_search(texts[0], k=2, fetch_k=20) + + assert len(search_result) == 2 + assert search_result[0].page_content == texts[0] + assert search_result[1].page_content != texts[0] + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_with_defined_values(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INDEX_DEFINED" + + # Delete table if it exists (cleanup from previous tests) + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + distance_strategy=DistanceStrategy.EUCLIDEAN_DISTANCE, + ) + + # Test the creation of HNSW index with specific values + try: + vectorDB.create_hnsw_index( + index_name="my_L2_index", ef_search=500, m=100, ef_construction=200 + ) + except Exception as e: + pytest.fail(f"Failed to create HNSW index with defined values: {e}") + + # Perform a search using the index to confirm its correctness + search_result = vectorDB.max_marginal_relevance_search(texts[0], k=2, fetch_k=20) + + assert len(search_result) == 2 + assert search_result[0].page_content == texts[0] + assert search_result[1].page_content != texts[0] + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_after_initialization(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INDEX_AFTER_INIT" + + drop_table(test_setup.conn, table_name) + + # Initialize HanaDB without adding documents yet + vectorDB = HanaDB( + connection=test_setup.conn, + embedding=embedding, + table_name=table_name, + ) + + # Create HNSW index before adding documents + vectorDB.create_hnsw_index( + index_name="index_pre_add", ef_search=400, m=50, ef_construction=150 + ) + + # Add texts after index creation + vectorDB.add_texts(texts=texts) + + # Perform similarity search using the index + search_result = vectorDB.similarity_search(texts[0], k=3) + + # Assert that search result is valid and has expected length + assert len(search_result) == 3 + assert search_result[0].page_content == texts[0] + assert search_result[1].page_content != texts[0] + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_duplicate_hnsw_index_creation(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_DUPLICATE_INDEX" + + # Delete table if it exists (cleanup from previous tests) + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + ) + + # Create HNSW index for the first time + vectorDB.create_hnsw_index( + index_name="index_cosine", + ef_search=300, + m=80, + ef_construction=100, + ) + + with pytest.raises(Exception): + vectorDB.create_hnsw_index(ef_search=300, m=80, ef_construction=100) + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_invalid_m_value(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INVALID_M" + + # Cleanup: drop the table if it exists + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + ) + + # Test invalid `m` value (too low) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(m=3) + + # Test invalid `m` value (too high) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(m=1001) + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_invalid_ef_construction(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INVALID_EF_CONSTRUCTION" + + # Cleanup: drop the table if it exists + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + ) + + # Test invalid `ef_construction` value (too low) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(ef_construction=0) + + # Test invalid `ef_construction` value (too high) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(ef_construction=100001) + + +@pytest.mark.skipif(not hanadb_installed, reason="hanadb not installed") +def test_create_hnsw_index_invalid_ef_search(texts: List[str]) -> None: + table_name = "TEST_TABLE_HNSW_INVALID_EF_SEARCH" + + # Cleanup: drop the table if it exists + drop_table(test_setup.conn, table_name) + + # Create table and insert data + vectorDB = HanaDB.from_texts( + connection=test_setup.conn, + texts=texts, + embedding=embedding, + table_name=table_name, + ) + + # Test invalid `ef_search` value (too low) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(ef_search=0) + + # Test invalid `ef_search` value (too high) + with pytest.raises(ValueError): + vectorDB.create_hnsw_index(ef_search=100001) From 478def8dcce9f0145990a28f2928b43c04a412c9 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 5 Dec 2024 15:35:28 -0800 Subject: [PATCH 018/157] core: deprecation doc removal (#28553) ![ScreenShot 2024-12-05 at 02 33 43PM@2x](https://github.com/user-attachments/assets/e1ce495b-90ca-41c7-9a65-b403a934675c) --- libs/core/langchain_core/_api/deprecation.py | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/libs/core/langchain_core/_api/deprecation.py b/libs/core/langchain_core/_api/deprecation.py index ab6e47d31590a..c7d1e87b3bac8 100644 --- a/libs/core/langchain_core/_api/deprecation.py +++ b/libs/core/langchain_core/_api/deprecation.py @@ -364,8 +364,15 @@ def finalize(wrapper: Callable[..., Any], new_doc: str) -> T: _package or _name.split(".")[0].replace("_", "-") if "." in _name else None ) since_str = f"{package}=={since}" if package else since + if removal: + if removal.startswith("1.") and package and package.startswith("langchain"): + removal_str = f"It will not be removed until {package}=={removal}." + else: + removal_str = f"It will be removed in {package}=={removal}." + else: + removal_str = "" new_doc = f"""\ -.. deprecated:: {since_str} {details} +.. deprecated:: {since_str} {details} {removal_str} {old_doc}\ """ From a197e0ba3d6e4abe1a749b98f5db1cfb93e019c7 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 5 Dec 2024 15:57:54 -0800 Subject: [PATCH 019/157] docs: custom deprecated coloring, organize css a bit (#28555) --- docs/api_reference/_static/css/custom.css | 88 +++++++++-------------- 1 file changed, 32 insertions(+), 56 deletions(-) diff --git a/docs/api_reference/_static/css/custom.css b/docs/api_reference/_static/css/custom.css index 19d0c0680db58..f98ef26197313 100644 --- a/docs/api_reference/_static/css/custom.css +++ b/docs/api_reference/_static/css/custom.css @@ -94,50 +94,7 @@ html { * https://sass-lang.com/documentation/interpolation */ /* Defaults to light mode if data-theme is not set */ -html:not([data-theme]) { - --pst-color-primary: #287977; - --pst-color-primary-bg: #80D6D3; - --pst-color-secondary: #6F3AED; - --pst-color-secondary-bg: #DAD6FE; - --pst-color-accent: #c132af; - --pst-color-accent-bg: #f8dff5; - --pst-color-info: #276be9; - --pst-color-info-bg: #dce7fc; - --pst-color-warning: #f66a0a; - --pst-color-warning-bg: #f8e3d0; - --pst-color-success: #00843f; - --pst-color-success-bg: #d6ece1; - --pst-color-attention: var(--pst-color-warning); - --pst-color-attention-bg: var(--pst-color-warning-bg); - --pst-color-danger: #d72d47; - --pst-color-danger-bg: #f9e1e4; - --pst-color-text-base: #222832; - --pst-color-text-muted: #48566b; - --pst-color-heading-color: #ffffff; - --pst-color-shadow: rgba(0, 0, 0, 0.1); - --pst-color-border: #d1d5da; - --pst-color-border-muted: rgba(23, 23, 26, 0.2); - --pst-color-inline-code: #912583; - --pst-color-inline-code-links: #246161; - --pst-color-target: #f3cf95; - --pst-color-background: #ffffff; - --pst-color-on-background: #F4F9F8; - --pst-color-surface: #F4F9F8; - --pst-color-on-surface: #222832; -} -html:not([data-theme]) { - --pst-color-link: var(--pst-color-primary); - --pst-color-link-hover: var(--pst-color-secondary); -} -html:not([data-theme]) .only-dark, -html:not([data-theme]) .only-dark ~ figcaption { - display: none !important; -} - -/* NOTE: @each {...} is like a for-loop - * https://sass-lang.com/documentation/at-rules/control/each - */ -html[data-theme=light] { +html:not([data-theme]), html[data-theme=light] { --pst-color-primary: #287977; --pst-color-primary-bg: #80D6D3; --pst-color-secondary: #6F3AED; @@ -167,15 +124,8 @@ html[data-theme=light] { --pst-color-on-background: #F4F9F8; --pst-color-surface: #F4F9F8; --pst-color-on-surface: #222832; - color-scheme: light; -} -html[data-theme=light] { - --pst-color-link: var(--pst-color-primary); - --pst-color-link-hover: var(--pst-color-secondary); -} -html[data-theme=light] .only-dark, -html[data-theme=light] .only-dark ~ figcaption { - display: none !important; + --pst-color-deprecated: #f47d2e; + --pst-color-deprecated-bg: #fff3e8; } html[data-theme=dark] { @@ -208,6 +158,8 @@ html[data-theme=dark] { --pst-color-on-background: #222832; --pst-color-surface: #29313d; --pst-color-on-surface: #f3f4f5; + --pst-color-deprecated: #b46f3e; + --pst-color-deprecated-bg: #341906; /* Adjust images in dark mode (unless they have class .only-dark or * .dark-light, in which case assume they're already optimized for dark * mode). @@ -218,6 +170,30 @@ html[data-theme=dark] { */ color-scheme: dark; } + +html:not([data-theme]) { + --pst-color-link: var(--pst-color-primary); + --pst-color-link-hover: var(--pst-color-secondary); +} +html:not([data-theme]) .only-dark, +html:not([data-theme]) .only-dark ~ figcaption { + display: none !important; +} + +/* NOTE: @each {...} is like a for-loop + * https://sass-lang.com/documentation/at-rules/control/each + */ +html[data-theme=light] { + color-scheme: light; +} +html[data-theme=light] { + --pst-color-link: var(--pst-color-primary); + --pst-color-link-hover: var(--pst-color-secondary); +} +html[data-theme=light] .only-dark, +html[data-theme=light] .only-dark ~ figcaption { + display: none !important; +} html[data-theme=dark] { --pst-color-link: var(--pst-color-primary); --pst-color-link-hover: var(--pst-color-secondary); @@ -392,12 +368,12 @@ div.deprecated { margin-top: 0.5em; margin-bottom: 2em; - background-color: var(--pst-color-warning-bg); - border-color: var(--pst-color-warning); + background-color: var(--pst-color-deprecated-bg); + border-color: var(--pst-color-deprecated); } span.versionmodified.deprecated:before { - color: var(--pst-color-warning); + color: var(--pst-color-deprecated); } .admonition-beta.admonition, div.admonition-beta.admonition { From 7ecf38f4facfa36bc630f91fc646adc04796d855 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 5 Dec 2024 16:32:47 -0800 Subject: [PATCH 020/157] cli: create specific files from template (#28556) --- libs/cli/Makefile | 4 +- .../langchain_cli/namespaces/integration.py | 132 +++++++++++------- 2 files changed, 82 insertions(+), 54 deletions(-) diff --git a/libs/cli/Makefile b/libs/cli/Makefile index ac855bd4dc58a..1560bfa65505d 100644 --- a/libs/cli/Makefile +++ b/libs/cli/Makefile @@ -38,10 +38,12 @@ _e2e_test: $(PYTHON) -m pip install --upgrade poetry && \ $(PYTHON) -m pip install -e .. && \ $(PYTHON) -m langchain_cli.cli integration new --name parrot-link --name-class ParrotLink && \ + $(PYTHON) -m langchain_cli.cli integration new --name parrot-link --name-class ParrotLinkB --src=integration_template/chat_models.py --dst=langchain-parrot-link/langchain_parrot_link/chat_models_b.py && \ + $(PYTHON) -m langchain_cli.cli integration create-doc --name parrot-link --name-class ParrotLinkB --component-type ChatModel --destination-dir langchain-parrot-link/docs && \ cd langchain-parrot-link && \ poetry install --with lint,typing,test && \ poetry run pip install -e ../../../standard-tests && \ make format lint tests && \ poetry install --with test_integration && \ rm tests/integration_tests/test_vectorstores.py && \ - make integration_test + make integration_test diff --git a/libs/cli/langchain_cli/namespaces/integration.py b/libs/cli/langchain_cli/namespaces/integration.py index eca9804358561..fbacf1274f177 100644 --- a/libs/cli/langchain_cli/namespaces/integration.py +++ b/libs/cli/langchain_cli/namespaces/integration.py @@ -69,6 +69,21 @@ def new( " This is used to name classes like `MyIntegrationVectorStore`" ), ] = None, + src: Annotated[ + Optional[list[str]], + typer.Option( + help="The name of the single template file to copy." + " e.g. `--src integration_template/chat_models.py " + "--dst my_integration/chat_models.py`. Can be used multiple times.", + ), + ] = None, + dst: Annotated[ + Optional[list[str]], + typer.Option( + help="The relative path to the integration package to place the new file in" + ". e.g. `my-integration/my_integration.py`", + ), + ] = None, ): """ Creates a new integration package. @@ -93,27 +108,66 @@ def new( "Name of integration in PascalCase", default=replacements["__ModuleName__"] ) + project_template_dir = Path(__file__).parents[1] / "integration_template" destination_dir = Path.cwd() / replacements["__package_name__"] - if destination_dir.exists(): - typer.echo(f"Folder {destination_dir} exists.") - raise typer.Exit(code=1) + if not src and not dst: + if destination_dir.exists(): + typer.echo(f"Folder {destination_dir} exists.") + raise typer.Exit(code=1) - # copy over template from ../integration_template - project_template_dir = Path(__file__).parents[1] / "integration_template" - shutil.copytree(project_template_dir, destination_dir, dirs_exist_ok=False) + # copy over template from ../integration_template + shutil.copytree(project_template_dir, destination_dir, dirs_exist_ok=False) - # folder movement - package_dir = destination_dir / replacements["__module_name__"] - shutil.move(destination_dir / "integration_template", package_dir) + # folder movement + package_dir = destination_dir / replacements["__module_name__"] + shutil.move(destination_dir / "integration_template", package_dir) - # replacements in files - replace_glob(destination_dir, "**/*", cast(Dict[str, str], replacements)) + # replacements in files + replace_glob(destination_dir, "**/*", cast(Dict[str, str], replacements)) - # poetry install - subprocess.run( - ["poetry", "install", "--with", "lint,test,typing,test_integration"], - cwd=destination_dir, - ) + # poetry install + subprocess.run( + ["poetry", "install", "--with", "lint,test,typing,test_integration"], + cwd=destination_dir, + ) + else: + # confirm src and dst are the same length + if not src: + typer.echo("Cannot provide --dst without --src.") + raise typer.Exit(code=1) + src_paths = [project_template_dir / p for p in src] + if dst and len(src) != len(dst): + typer.echo("Number of --src and --dst arguments must match.") + raise typer.Exit(code=1) + if not dst: + # assume we're in a package dir, copy to equivalent path + dst_paths = [destination_dir / p for p in src] + else: + dst_paths = [Path.cwd() / p for p in dst] + dst_paths = [ + p / f"{replacements['__package_name_short_snake__']}.ipynb" + if not p.suffix + else p + for p in dst_paths + ] + + # confirm no duplicate dst_paths + if len(dst_paths) != len(set(dst_paths)): + typer.echo( + "Duplicate destination paths provided or computed - please " + "specify them explicitly with --dst." + ) + raise typer.Exit(code=1) + + # confirm no files exist at dst_paths + for dst_path in dst_paths: + if dst_path.exists(): + typer.echo(f"File {dst_path} exists.") + raise typer.Exit(code=1) + + for src_path, dst_path in zip(src_paths, dst_paths): + shutil.copy(src_path, dst_path) + replace_file(dst_path, cast(Dict[str, str], replacements)) TEMPLATE_MAP: dict[str, str] = { @@ -176,43 +230,15 @@ def create_doc( """ Creates a new integration doc. """ - try: - replacements = _process_name(name, community=component_type == "Tool") - except ValueError as e: - typer.echo(e) - raise typer.Exit(code=1) - - if name_class: - if not re.match(r"^[A-Z][a-zA-Z0-9]*$", name_class): - typer.echo( - "Name should only contain letters (a-z, A-Z), numbers, and underscores" - ", and start with a capital letter." - ) - raise typer.Exit(code=1) - replacements["__ModuleName__"] = name_class - else: - replacements["__ModuleName__"] = typer.prompt( - ( - "The PascalCase name of the integration (e.g. `OpenAI`, `VertexAI`). " - "Do not include a 'Chat', 'VectorStore', etc. prefix/suffix." - ), - default=replacements["__ModuleName__"], - ) - destination_path = ( - Path.cwd() - / destination_dir - / (replacements["__package_name_short_snake__"] + ".ipynb") - ) - - # copy over template from ../integration_template - template_dir = Path(__file__).parents[1] / "integration_template" / "docs" - if component_type in TEMPLATE_MAP: - docs_template = template_dir / TEMPLATE_MAP[component_type] - else: - raise ValueError( + if component_type not in TEMPLATE_MAP: + typer.echo( f"Unrecognized {component_type=}. Expected one of {_component_types_str}." ) - shutil.copy(docs_template, destination_path) + raise typer.Exit(code=1) - # replacements in file - replace_file(destination_path, cast(Dict[str, str], replacements)) + new( + name=name, + name_class=name_class, + src=[f"docs/{TEMPLATE_MAP[component_type]}"], + dst=[destination_dir], + ) From bc636ccc6034d60cc59c23a00f0659ab4ed03924 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 5 Dec 2024 16:40:52 -0800 Subject: [PATCH 021/157] cli: release 0.0.35 (#28557) --- libs/cli/poetry.lock | 166 ++++++++++++++++++++-------------------- libs/cli/pyproject.toml | 2 +- 2 files changed, 84 insertions(+), 84 deletions(-) diff --git a/libs/cli/poetry.lock b/libs/cli/poetry.lock index c53e81acdd077..72cd18d604530 100644 --- a/libs/cli/poetry.lock +++ b/libs/cli/poetry.lock @@ -13,87 +13,87 @@ files = [ [[package]] name = "aiohttp" -version = "3.11.9" +version = "3.11.10" description = "Async http client/server framework (asyncio)" optional = false 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"coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "truststore (>=0.9.1)", "uvloop (>=0.21)"] trio = ["trio (>=0.26.1)"] [[package]] diff --git a/libs/cli/pyproject.toml b/libs/cli/pyproject.toml index 3e434fc8e6a53..2e3ee70fea7ab 100644 --- a/libs/cli/pyproject.toml +++ b/libs/cli/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langchain-cli" -version = "0.0.34" +version = "0.0.35" description = "CLI for interacting with LangChain" authors = ["Erick Friis "] readme = "README.md" From 18386c16c7201e54dfaacbc18eed51da7965a7a5 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 5 Dec 2024 16:49:30 -0800 Subject: [PATCH 022/157] core, tests: more tolerant _aget_relevant_documents function (#28462) --- libs/core/langchain_core/retrievers.py | 14 +++++++++++++- libs/core/tests/unit_tests/test_retrievers.py | 0 .../tests/unit_tests/test_basic_retriever.py | 5 +---- 3 files changed, 14 insertions(+), 5 deletions(-) create mode 100644 libs/core/tests/unit_tests/test_retrievers.py diff --git a/libs/core/langchain_core/retrievers.py b/libs/core/langchain_core/retrievers.py index 7462569ddd30d..e1be4588081a2 100644 --- a/libs/core/langchain_core/retrievers.py +++ b/libs/core/langchain_core/retrievers.py @@ -27,7 +27,7 @@ from typing import TYPE_CHECKING, Any, Optional from pydantic import ConfigDict -from typing_extensions import TypedDict +from typing_extensions import Self, TypedDict from langchain_core._api import deprecated from langchain_core.documents import Document @@ -180,6 +180,18 @@ def __init_subclass__(cls, **kwargs: Any) -> None: cls._aget_relevant_documents = aswap # type: ignore[assignment] parameters = signature(cls._get_relevant_documents).parameters cls._new_arg_supported = parameters.get("run_manager") is not None + if ( + not cls._new_arg_supported + and cls._aget_relevant_documents == BaseRetriever._aget_relevant_documents + ): + # we need to tolerate no run_manager in _aget_relevant_documents signature + async def _aget_relevant_documents( + self: Self, query: str + ) -> list[Document]: + return await run_in_executor(None, self._get_relevant_documents, query) # type: ignore + + cls._aget_relevant_documents = _aget_relevant_documents # type: ignore[assignment] + # If a V1 retriever broke the interface and expects additional arguments cls._expects_other_args = ( len(set(parameters.keys()) - {"self", "query", "run_manager"}) > 0 diff --git a/libs/core/tests/unit_tests/test_retrievers.py b/libs/core/tests/unit_tests/test_retrievers.py new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/libs/standard-tests/tests/unit_tests/test_basic_retriever.py b/libs/standard-tests/tests/unit_tests/test_basic_retriever.py index af5d598c722f2..fb7999a09fb5c 100644 --- a/libs/standard-tests/tests/unit_tests/test_basic_retriever.py +++ b/libs/standard-tests/tests/unit_tests/test_basic_retriever.py @@ -1,6 +1,5 @@ from typing import Any, Type -from langchain_core.callbacks import CallbackManagerForRetrieverRun from langchain_core.documents import Document from langchain_core.retrievers import BaseRetriever @@ -11,9 +10,7 @@ class ParrotRetriever(BaseRetriever): parrot_name: str k: int = 3 - def _get_relevant_documents( - self, query: str, *, run_manager: CallbackManagerForRetrieverRun, **kwargs: Any - ) -> list[Document]: + def _get_relevant_documents(self, query: str, **kwargs: Any) -> list[Document]: k = kwargs.get("k", self.k) return [Document(page_content=f"{self.parrot_name} says: {query}")] * k From 5277a021c108fd983710382430f820062f3abec6 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 09:26:34 -0800 Subject: [PATCH 023/157] docs: raw loader codeblock (#28548) Co-authored-by: Chester Curme --- docs/Makefile | 2 + .../how_to/integrations/package.mdx | 212 +++++++++++++----- docs/package.json | 1 + docs/yarn.lock | 8 + libs/standard-tests/poetry.lock | 81 ++++--- libs/standard-tests/pyproject.toml | 5 +- 6 files changed, 223 insertions(+), 86 deletions(-) diff --git a/docs/Makefile b/docs/Makefile index f8d5d96714dd9..107bb1feb4d3d 100644 --- a/docs/Makefile +++ b/docs/Makefile @@ -60,6 +60,7 @@ copy-infra: cp package.json $(OUTPUT_NEW_DIR) cp sidebars.js $(OUTPUT_NEW_DIR) cp -r static $(OUTPUT_NEW_DIR) + cp -r ../libs/cli/langchain_cli/integration_template $(OUTPUT_NEW_DIR)/src/theme cp yarn.lock $(OUTPUT_NEW_DIR) render: @@ -81,6 +82,7 @@ build: install-py-deps generate-files copy-infra render md-sync append-related vercel-build: install-vercel-deps build generate-references rm -rf docs mv $(OUTPUT_NEW_DOCS_DIR) docs + cp -r ../libs/cli/langchain_cli/integration_template src/theme rm -rf build mkdir static/api_reference git clone --depth=1 https://github.com/langchain-ai/langchain-api-docs-html.git diff --git a/docs/docs/contributing/how_to/integrations/package.mdx b/docs/docs/contributing/how_to/integrations/package.mdx index 2b5bb97865e5b..d016ff1bed4fe 100644 --- a/docs/docs/contributing/how_to/integrations/package.mdx +++ b/docs/docs/contributing/how_to/integrations/package.mdx @@ -26,81 +26,193 @@ Examples include [chat models](/docs/concepts/chat_models/), Your integration package will typically implement a subclass of at least one of these components. Expand the tabs below to see details on each. -
- Chat models +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; +import CodeBlock from '@theme/CodeBlock'; -Refer to the [Custom Chat Model Guide](/docs/how_to/custom_chat_model) guide for -detail on a starter chat model [implementation](/docs/how_to/custom_chat_model/#implementation). + -:::tip + + + Refer to the [Custom Chat Model Guide](/docs/how_to/custom_chat_model) guide for + detail on a starter chat model [implementation](/docs/how_to/custom_chat_model/#implementation). -The model from the [Custom Chat Model Guide](/docs/how_to/custom_chat_model) is tested -against the standard unit and integration tests in the LangChain Github repository. -You can also access that implementation directly from Github -[here](https://github.com/langchain-ai/langchain/blob/master/libs/standard-tests/tests/unit_tests/custom_chat_model.py). + :::tip -::: + The model from the [Custom Chat Model Guide](/docs/how_to/custom_chat_model) is tested + against the standard unit and integration tests in the LangChain Github repository. + You can also access that implementation directly from Github + [here](https://github.com/langchain-ai/langchain/blob/master/libs/standard-tests/tests/unit_tests/custom_chat_model.py). -
+ ::: -
- Vector stores +
+ Example chat model code -Your vector store implementation will depend on your chosen database technology. -`langchain-core` includes a minimal -[in-memory vector store](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.in_memory.InMemoryVectorStore.html) -that we can use as a guide. You can access the code [here](https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/vectorstores/in_memory.py). +import ChatModelSource from '../../../../src/theme/integration_template/integration_template/chat_models.py'; -All vector stores must inherit from the [VectorStore](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) -base class. This interface consists of methods for writing, deleting and searching -for documents in the vector store. + + { + ChatModelSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') + } + -`VectorStore` supports a variety of synchronous and asynchronous search types (e.g., -nearest-neighbor or maximum marginal relevance), as well as interfaces for adding -documents to the store. See the [API Reference](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) -for all supported methods. The required methods are tabulated below: +
+ + + + + Your vector store implementation will depend on your chosen database technology. + `langchain-core` includes a minimal + [in-memory vector store](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.in_memory.InMemoryVectorStore.html) + that we can use as a guide. You can access the code [here](https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/vectorstores/in_memory.py). + + All vector stores must inherit from the [VectorStore](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) + base class. This interface consists of methods for writing, deleting and searching + for documents in the vector store. + + `VectorStore` supports a variety of synchronous and asynchronous search types (e.g., + nearest-neighbor or maximum marginal relevance), as well as interfaces for adding + documents to the store. See the [API Reference](https://python.langchain.com/api_reference/core/vectorstores/langchain_core.vectorstores.base.VectorStore.html) + for all supported methods. The required methods are tabulated below: + + | Method/Property | Description | + |------------------------ |------------------------------------------------------| + | `add_documents` | Add documents to the vector store. | + | `delete` | Delete selected documents from vector store (by IDs) | + | `get_by_ids` | Get selected documents from vector store (by IDs) | + | `similarity_search` | Get documents most similar to a query. | + | `embeddings` (property) | Embeddings object for vector store. | + | `from_texts` | Instantiate vector store via adding texts. | + + Note that `InMemoryVectorStore` implements some optional search types, as well as + convenience methods for loading and dumping the object to a file, but this is not + necessary for all implementations. + + :::tip + + The [in-memory vector store](https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/vectorstores/in_memory.py) + is tested against the standard tests in the LangChain Github repository. + + ::: + +
+ Example vector store code + +import VectorstoreSource from '../../../../src/theme/integration_template/integration_template/vectorstores.py'; + + + { + VectorstoreSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') + } + + +
+ + + + +
+ Example embeddings code + +Embeddings are used to convert `str` objects from `Document.page_content` fields +into a vector representation (represented as a list of floats). + +The `Embeddings` class must inherit from the [Embeddings](https://python.langchain.com/api_reference/core/embeddings/langchain_core.embeddings.embeddings.Embeddings.html#langchain_core.embeddings.embeddings.Embeddings) +base class. This interface has 5 methods that can be implemented. | Method/Property | Description | |------------------------ |------------------------------------------------------| -| `add_documents` | Add documents to the vector store. | -| `delete` | Delete selected documents from vector store (by IDs) | -| `get_by_ids` | Get selected documents from vector store (by IDs) | -| `similarity_search` | Get documents most similar to a query. | -| `embeddings` (property) | Embeddings object for vector store. | -| `from_texts` | Instantiate vector store via adding texts. | +| `__init__` | Initialize the embeddings object. (optional) | +| `embed_query` | Embed a list of texts. (required) | +| `embed_documents` | Embed a list of documents. (required) | +| `aembed_query` | Asynchronously embed a list of texts. (optional) | +| `aembed_documents` | Asynchronously embed a list of documents. (optional) | + +### Constructor + +The `__init__` constructor is optional but common, but can be used to set up any necessary attributes +that a user can pass in when initializing the embeddings object. Common attributes include + +- `model` - the id of the model to use for embeddings + +### Embedding queries vs documents + +The `embed_query` and `embed_documents` methods are required. These methods both operate +on string inputs (the accessing of `Document.page_content` attributes) is handled +by the VectorStore using the embedding model for legacy reasons. + +`embed_query` takes in a single string and returns a single embedding as a list of floats. +If your model has different modes for embedding queries vs the underlying documents, you can +implement this method to handle that. -Note that `InMemoryVectorStore` implements some optional search types, as well as -convenience methods for loading and dumping the object to a file, but this is not -necessary for all implementations. +`embed_documents` takes in a list of strings and returns a list of embeddings as a list of lists of floats. -:::tip -The [in-memory vector store](https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/vectorstores/in_memory.py) -is tested against the standard tests in the LangChain Github repository. +### Async methods -::: -
+import EmbeddingsSource from '/src/theme/integration_template/integration_template/embeddings.py'; - + + + +
+ Example retriever code + +import RetrieverSource from '/src/theme/integration_template/integration_template/retrievers.py'; + + + { + RetrieverSource.replaceAll('__ModuleName__', 'ParrotLink') + .replaceAll('__package_name__', 'langchain-parrot-link') + .replaceAll('__MODULE_NAME__', 'PARROT_LINK') + .replaceAll('__module_name__', 'langchain_parrot_link') + } + + +
+ + + + +--- ## (Optional) bootstrapping a new integration package diff --git a/docs/package.json b/docs/package.json index b82fda1c4c0b3..b02d589e268c2 100644 --- a/docs/package.json +++ b/docs/package.json @@ -35,6 +35,7 @@ "json-loader": "^0.5.7", "prism-react-renderer": "^2.1.0", "process": "^0.11.10", + "raw-loader": "^4.0.2", "react": "^18", "react-dom": "^18", "typescript": "^5.2.2", diff --git a/docs/yarn.lock b/docs/yarn.lock index 94436d8e05823..aad5a86bb52cd 100644 --- a/docs/yarn.lock +++ b/docs/yarn.lock @@ -9043,6 +9043,14 @@ raw-body@2.5.2: iconv-lite "0.4.24" unpipe "1.0.0" +raw-loader@^4.0.2: + version "4.0.2" + resolved "https://registry.yarnpkg.com/raw-loader/-/raw-loader-4.0.2.tgz#1aac6b7d1ad1501e66efdac1522c73e59a584eb6" + integrity sha512-ZnScIV3ag9A4wPX/ZayxL/jZH+euYb6FcUinPcgiQW0+UBtEv0O6Q3lGd3cqJ+GHH+rksEv3Pj99oxJ3u3VIKA== + dependencies: + loader-utils "^2.0.0" + schema-utils "^3.0.0" + rc@1.2.8: version "1.2.8" resolved "https://registry.yarnpkg.com/rc/-/rc-1.2.8.tgz#cd924bf5200a075b83c188cd6b9e211b7fc0d3ed" diff --git a/libs/standard-tests/poetry.lock b/libs/standard-tests/poetry.lock index 0bb01c5870edb..55d58b9c2d6b5 100644 --- a/libs/standard-tests/poetry.lock +++ b/libs/standard-tests/poetry.lock @@ -13,24 +13,24 @@ files = [ [[package]] name = "anyio" -version = "4.6.2.post1" +version = "4.7.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false python-versions = ">=3.9" files = [ - 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Removed some optional methods. --- libs/cli/Makefile | 1 - .../integration_template/vectorstores.py | 266 +++++++++++++----- .../integration_tests/test_vectorstores.py | 4 +- libs/standard-tests/poetry.lock | 4 +- libs/standard-tests/pyproject.toml | 16 +- 5 files changed, 208 insertions(+), 83 deletions(-) diff --git a/libs/cli/Makefile b/libs/cli/Makefile index 1560bfa65505d..d93de61d8cc90 100644 --- a/libs/cli/Makefile +++ b/libs/cli/Makefile @@ -45,5 +45,4 @@ _e2e_test: poetry run pip install -e ../../../standard-tests && \ make format lint tests && \ poetry install --with test_integration && \ - rm tests/integration_tests/test_vectorstores.py && \ make integration_test diff --git a/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py b/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py index 02ab2c7fccd93..cef35ecaf44c5 100644 --- a/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py +++ b/libs/cli/langchain_cli/integration_template/integration_template/vectorstores.py @@ -2,23 +2,23 @@ from __future__ import annotations +import uuid from typing import ( - TYPE_CHECKING, Any, Callable, - Iterable, + Iterator, List, Optional, + Sequence, Tuple, Type, TypeVar, ) +from langchain_core.documents import Document from langchain_core.embeddings import Embeddings from langchain_core.vectorstores import VectorStore - -if TYPE_CHECKING: - from langchain_core.documents import Document +from langchain_core.vectorstores.utils import _cosine_similarity as cosine_similarity VST = TypeVar("VST", bound=VectorStore) @@ -158,40 +158,184 @@ class __ModuleName__VectorStore(VectorStore): """ # noqa: E501 - _database: dict[str, tuple[Document, list[float]]] = {} + def __init__(self, embedding: Embeddings) -> None: + """Initialize with the given embedding function. - def add_texts( - self, - texts: Iterable[str], + Args: + embedding: embedding function to use. + """ + self._database: dict[str, dict[str, Any]] = {} + self.embedding = embedding + + @classmethod + def from_texts( + cls: Type[__ModuleName__VectorStore], + texts: List[str], + embedding: Embeddings, metadatas: Optional[List[dict]] = None, **kwargs: Any, - ) -> List[str]: - raise NotImplementedError + ) -> __ModuleName__VectorStore: + store = cls( + embedding=embedding, + ) + store.add_texts(texts=texts, metadatas=metadatas, **kwargs) + return store # optional: add custom async implementations - # async def aadd_texts( - # self, - # texts: Iterable[str], + # @classmethod + # async def afrom_texts( + # cls: Type[VST], + # texts: List[str], + # embedding: Embeddings, # metadatas: Optional[List[dict]] = None, # **kwargs: Any, - # ) -> List[str]: + # ) -> VST: # return await asyncio.get_running_loop().run_in_executor( - # None, partial(self.add_texts, **kwargs), texts, metadatas + # None, partial(cls.from_texts, **kwargs), texts, embedding, metadatas # ) - def delete(self, ids: Optional[List[str]] = None, **kwargs: Any) -> Optional[bool]: - raise NotImplementedError + @property + def embeddings(self) -> Embeddings: + return self.embedding + + def add_documents( + self, + documents: List[Document], + ids: Optional[List[str]] = None, + **kwargs: Any, + ) -> List[str]: + """Add documents to the store.""" + texts = [doc.page_content for doc in documents] + vectors = self.embedding.embed_documents(texts) + + if ids and len(ids) != len(texts): + msg = ( + f"ids must be the same length as texts. " + f"Got {len(ids)} ids and {len(texts)} texts." + ) + raise ValueError(msg) + + id_iterator: Iterator[Optional[str]] = ( + iter(ids) if ids else iter(doc.id for doc in documents) + ) + + ids_ = [] + + for doc, vector in zip(documents, vectors): + doc_id = next(id_iterator) + doc_id_ = doc_id if doc_id else str(uuid.uuid4()) + ids_.append(doc_id_) + self._database[doc_id_] = { + "id": doc_id_, + "vector": vector, + "text": doc.page_content, + "metadata": doc.metadata, + } + + return ids_ + + # optional: add custom async implementations + # async def aadd_documents( + # self, + # documents: List[Document], + # ids: Optional[List[str]] = None, + # **kwargs: Any, + # ) -> List[str]: + # raise NotImplementedError + + def delete(self, ids: Optional[List[str]] = None, **kwargs: Any) -> None: + if ids: + for _id in ids: + self._database.pop(_id, None) # optional: add custom async implementations # async def adelete( # self, ids: Optional[List[str]] = None, **kwargs: Any - # ) -> Optional[bool]: + # ) -> None: + # raise NotImplementedError + + def get_by_ids(self, ids: Sequence[str], /) -> list[Document]: + """Get documents by their ids. + + Args: + ids: The ids of the documents to get. + + Returns: + A list of Document objects. + """ + documents = [] + + for doc_id in ids: + doc = self._database.get(doc_id) + if doc: + documents.append( + Document( + id=doc["id"], + page_content=doc["text"], + metadata=doc["metadata"], + ) + ) + return documents + + # optional: add custom async implementations + # async def aget_by_ids(self, ids: Sequence[str], /) -> list[Document]: # raise NotImplementedError + # NOTE: the below helper method implements similarity search for in-memory + # storage. It is optional and not a part of the vector store interface. + def _similarity_search_with_score_by_vector( + self, + embedding: List[float], + k: int = 4, + filter: Optional[Callable[[Document], bool]] = None, + **kwargs: Any, + ) -> List[tuple[Document, float, List[float]]]: + # get all docs with fixed order in list + docs = list(self._database.values()) + + if filter is not None: + docs = [ + doc + for doc in docs + if filter(Document(page_content=doc["text"], metadata=doc["metadata"])) + ] + + if not docs: + return [] + + similarity = cosine_similarity([embedding], [doc["vector"] for doc in docs])[0] + + # get the indices ordered by similarity score + top_k_idx = similarity.argsort()[::-1][:k] + + return [ + ( + # Document + Document( + id=doc_dict["id"], + page_content=doc_dict["text"], + metadata=doc_dict["metadata"], + ), + # Score + float(similarity[idx].item()), + # Embedding vector + doc_dict["vector"], + ) + for idx in top_k_idx + # Assign using walrus operator to avoid multiple lookups + if (doc_dict := docs[idx]) + ] + def similarity_search( self, query: str, k: int = 4, **kwargs: Any ) -> List[Document]: - raise NotImplementedError + embedding = self.embedding.embed_query(query) + return [ + doc + for doc, _, _ in self._similarity_search_with_score_by_vector( + embedding=embedding, k=k, **kwargs + ) + ] # optional: add custom async implementations # async def asimilarity_search( @@ -204,9 +348,15 @@ def similarity_search( # return await asyncio.get_event_loop().run_in_executor(None, func) def similarity_search_with_score( - self, *args: Any, **kwargs: Any + self, query: str, k: int = 4, **kwargs: Any ) -> List[Tuple[Document, float]]: - raise NotImplementedError + embedding = self.embedding.embed_query(query) + return [ + (doc, similarity) + for doc, similarity, _ in self._similarity_search_with_score_by_vector( + embedding=embedding, k=k, **kwargs + ) + ] # optional: add custom async implementations # async def asimilarity_search_with_score( @@ -218,10 +368,12 @@ def similarity_search_with_score( # func = partial(self.similarity_search_with_score, *args, **kwargs) # return await asyncio.get_event_loop().run_in_executor(None, func) - def similarity_search_by_vector( - self, embedding: List[float], k: int = 4, **kwargs: Any - ) -> List[Document]: - raise NotImplementedError + ### ADDITIONAL OPTIONAL SEARCH METHODS BELOW ### + + # def similarity_search_by_vector( + # self, embedding: List[float], k: int = 4, **kwargs: Any + # ) -> List[Document]: + # raise NotImplementedError # optional: add custom async implementations # async def asimilarity_search_by_vector( @@ -233,15 +385,15 @@ def similarity_search_by_vector( # func = partial(self.similarity_search_by_vector, embedding, k=k, **kwargs) # return await asyncio.get_event_loop().run_in_executor(None, func) - def max_marginal_relevance_search( - self, - query: str, - k: int = 4, - fetch_k: int = 20, - lambda_mult: float = 0.5, - **kwargs: Any, - ) -> List[Document]: - raise NotImplementedError + # def max_marginal_relevance_search( + # self, + # query: str, + # k: int = 4, + # fetch_k: int = 20, + # lambda_mult: float = 0.5, + # **kwargs: Any, + # ) -> List[Document]: + # raise NotImplementedError # optional: add custom async implementations # async def amax_marginal_relevance_search( @@ -265,18 +417,7 @@ def max_marginal_relevance_search( # ) # return await asyncio.get_event_loop().run_in_executor(None, func) - def max_marginal_relevance_search_by_vector( - self, - embedding: List[float], - k: int = 4, - fetch_k: int = 20, - lambda_mult: float = 0.5, - **kwargs: Any, - ) -> List[Document]: - raise NotImplementedError - - # optional: add custom async implementations - # async def amax_marginal_relevance_search_by_vector( + # def max_marginal_relevance_search_by_vector( # self, # embedding: List[float], # k: int = 4, @@ -286,28 +427,13 @@ def max_marginal_relevance_search_by_vector( # ) -> List[Document]: # raise NotImplementedError - @classmethod - def from_texts( - cls: Type[VST], - texts: List[str], - embedding: Embeddings, - metadatas: Optional[List[dict]] = None, - **kwargs: Any, - ) -> VST: - raise NotImplementedError - # optional: add custom async implementations - # @classmethod - # async def afrom_texts( - # cls: Type[VST], - # texts: List[str], - # embedding: Embeddings, - # metadatas: Optional[List[dict]] = None, + # async def amax_marginal_relevance_search_by_vector( + # self, + # embedding: List[float], + # k: int = 4, + # fetch_k: int = 20, + # lambda_mult: float = 0.5, # **kwargs: Any, - # ) -> VST: - # return await asyncio.get_running_loop().run_in_executor( - # None, partial(cls.from_texts, **kwargs), texts, embedding, metadatas - # ) - - def _select_relevance_score_fn(self) -> Callable[[float], float]: - raise NotImplementedError + # ) -> List[Document]: + # raise NotImplementedError diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py index 2d0820348a3c3..055d1d98ffd9b 100644 --- a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py @@ -13,7 +13,7 @@ class Test__ModuleName__VectorStoreSync(ReadWriteTestSuite): @pytest.fixture() def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore """Get an empty vectorstore for unit tests.""" - store = __ModuleName__VectorStore() + store = __ModuleName__VectorStore(self.get_embeddings()) # note: store should be EMPTY at this point # if you need to delete data, you may do so here try: @@ -27,7 +27,7 @@ class Test__ModuleName__VectorStoreAsync(AsyncReadWriteTestSuite): @pytest.fixture() async def vectorstore(self) -> AsyncGenerator[VectorStore, None]: # type: ignore """Get an empty vectorstore for unit tests.""" - store = __ModuleName__VectorStore() + store = __ModuleName__VectorStore(self.get_embeddings()) # note: store should be EMPTY at this point # if you need to delete data, you may do so here try: diff --git a/libs/standard-tests/poetry.lock b/libs/standard-tests/poetry.lock index 55d58b9c2d6b5..3890a88ea34dd 100644 --- a/libs/standard-tests/poetry.lock +++ b/libs/standard-tests/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "annotated-types" @@ -996,4 +996,4 @@ zstd = ["zstandard (>=0.18.0)"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "430e4bd69a7e58e26703886697a3c1d9965a29caa2afc6eb7d8efc78164f2730" +content-hash = "a7c5efccaeae83ff262999a4b17048a6a3b29b29ee4e16ec9d6ab14b4cf4d21b" diff --git a/libs/standard-tests/pyproject.toml b/libs/standard-tests/pyproject.toml index 9069fbc57de07..4d5f4f85f0697 100644 --- a/libs/standard-tests/pyproject.toml +++ b/libs/standard-tests/pyproject.toml @@ -26,6 +26,14 @@ httpx = ">=0.25.0,<1" syrupy = "^4" pytest-socket = ">=0.6.0,<1" +[[tool.poetry.dependencies.numpy]] +version = "^1.24.0" +python = "<3.12" + +[[tool.poetry.dependencies.numpy]] +version = ">=1.26.2,<3" +python = ">=3.12" + [tool.ruff.lint] select = ["E", "F", "I", "T201"] @@ -55,14 +63,6 @@ optional = true [tool.poetry.group.test.dependencies] -[[tool.poetry.group.test.dependencies.numpy]] -version = "^1.24.0" -python = "<3.12" - -[[tool.poetry.group.test.dependencies.numpy]] -version = "^1.26.0" -python = ">=3.12" - [tool.poetry.group.test_integration.dependencies] [tool.poetry.group.codespell.dependencies] From 15cbc36a2379244db331e77ab3eadb5d7967943b Mon Sep 17 00:00:00 2001 From: ccurme Date: Fri, 6 Dec 2024 13:33:24 -0500 Subject: [PATCH 025/157] docs[patch]: update contributor docs for integrations (#28576) - Reformat tabs - Add code snippets inline - Add embeddings content --- .../how_to/integrations/package.mdx | 25 ++++++++-------- .../how_to/integrations/standard_tests.ipynb | 29 +++++++++++++++++++ 2 files changed, 42 insertions(+), 12 deletions(-) diff --git a/docs/docs/contributing/how_to/integrations/package.mdx b/docs/docs/contributing/how_to/integrations/package.mdx index d016ff1bed4fe..5a4aa697c2519 100644 --- a/docs/docs/contributing/how_to/integrations/package.mdx +++ b/docs/docs/contributing/how_to/integrations/package.mdx @@ -37,14 +37,11 @@ import CodeBlock from '@theme/CodeBlock'; Refer to the [Custom Chat Model Guide](/docs/how_to/custom_chat_model) guide for detail on a starter chat model [implementation](/docs/how_to/custom_chat_model/#implementation). - :::tip - - The model from the [Custom Chat Model Guide](/docs/how_to/custom_chat_model) is tested - against the standard unit and integration tests in the LangChain Github repository. - You can also access that implementation directly from Github - [here](https://github.com/langchain-ai/langchain/blob/master/libs/standard-tests/tests/unit_tests/custom_chat_model.py). - - ::: + The `langchain-cli` package contains [template integrations](https://github.com/langchain-ai/langchain/tree/master/libs/cli/langchain_cli/integration_template/integration_template) + for major LangChain components that are tested against the standard unit and + integration tests in the LangChain Github repository. You can access the starter + chat model implementation [here](https://github.com/langchain-ai/langchain/blob/master/libs/cli/langchain_cli/integration_template/integration_template/chat_models.py). + For convenience, we also include the code below.
Example chat model code @@ -118,9 +115,6 @@ import VectorstoreSource from '../../../../src/theme/integration_template/integr -
- Example embeddings code - Embeddings are used to convert `str` objects from `Document.page_content` fields into a vector representation (represented as a list of floats). @@ -154,9 +148,16 @@ implement this method to handle that. `embed_documents` takes in a list of strings and returns a list of embeddings as a list of lists of floats. +### Implementation -### Async methods +The `langchain-cli` package contains [template integrations](https://github.com/langchain-ai/langchain/tree/master/libs/cli/langchain_cli/integration_template/integration_template) +for major LangChain components that are tested against the standard unit and +integration tests in the LangChain Github repository. You can access the starter +embedding model implementation [here](https://github.com/langchain-ai/langchain/blob/master/libs/cli/langchain_cli/integration_template/integration_template/embeddings.py). +For convenience, we also include the code below. +
+ Example embeddings code import EmbeddingsSource from '/src/theme/integration_template/integration_template/embeddings.py'; diff --git a/docs/docs/contributing/how_to/integrations/standard_tests.ipynb b/docs/docs/contributing/how_to/integrations/standard_tests.ipynb index a01dc8a60a305..dbf1a1a9b1cd3 100644 --- a/docs/docs/contributing/how_to/integrations/standard_tests.ipynb +++ b/docs/docs/contributing/how_to/integrations/standard_tests.ipynb @@ -324,6 +324,28 @@ " Embedding Models" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To configure standard tests for an embeddings model, we subclass\n", + "`EmbeddingsUnitTests` and `EmbeddingsIntegrationTests`. On each subclass, we\n", + "implement the `embeddings_class` property to specify the embeddings model to be\n", + "tested. We can also override the embedding_model_params property to specify\n", + "initialization parameters. See examples below.\n", + "\n", + ":::note\n", + "\n", + "Details on what tests are run, how each test can be skipped, and troubleshooting tips for each test can be found in the API references. See details:\n", + "\n", + "- [Unit tests API reference](https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.embeddings.EmbeddingsUnitTests.html)\n", + "- [Integration tests API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.embeddings.EmbeddingsIntegrationTests.html)\n", + "\n", + ":::\n", + "\n", + "Unit test example:" + ] + }, { "cell_type": "code", "execution_count": null, @@ -347,6 +369,13 @@ " return {\"model\": \"nest-embed-001\", \"temperature\": 0}" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Integration test example:" + ] + }, { "cell_type": "code", "execution_count": null, From dda9f90047d2728612eff7286b95c0f84dbcfec7 Mon Sep 17 00:00:00 2001 From: Bagatur <22008038+baskaryan@users.noreply.github.com> Date: Fri, 6 Dec 2024 11:36:53 -0800 Subject: [PATCH 026/157] core[patch]: Release 0.3.22 (#28582) --- libs/core/pyproject.toml | 83 ++++++++-------------------------------- 1 file changed, 15 insertions(+), 68 deletions(-) diff --git a/libs/core/pyproject.toml b/libs/core/pyproject.toml index 8ba3b07011ce5..af153d8b66267 100644 --- a/libs/core/pyproject.toml +++ b/libs/core/pyproject.toml @@ -1,10 +1,10 @@ [build-system] -requires = ["poetry-core>=1.0.0"] +requires = [ "poetry-core>=1.0.0",] build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain-core" -version = "0.3.21" +version = "0.3.22" description = "Building applications with LLMs through composability" authors = [] license = "MIT" @@ -12,16 +12,10 @@ readme = "README.md" repository = "https://github.com/langchain-ai/langchain" [tool.mypy] -exclude = [ - "notebooks", - "examples", - "example_data", - "langchain_core/pydantic", - "tests/unit_tests/utils/test_function_calling.py", -] +exclude = [ "notebooks", "examples", "example_data", "langchain_core/pydantic", "tests/unit_tests/utils/test_function_calling.py",] disallow_untyped_defs = "True" [[tool.mypy.overrides]] -module = ["numpy", "pytest"] +module = [ "numpy", "pytest",] ignore_missing_imports = true [tool.ruff] @@ -50,53 +44,17 @@ python = ">=3.12.4" [tool.poetry.extras] [tool.ruff.lint] -select = [ - "ASYNC", - "B", - "C4", - "COM", - "DJ", - "E", - "EM", - "EXE", - "F", - "FLY", - "FURB", - "I", - "ICN", - "INT", - "LOG", - "N", - "NPY", - "PD", - "PIE", - "Q", - "RSE", - "S", - "SIM", - "SLOT", - "T10", - "T201", - "TID", - "UP", - "W", - "YTT", -] -ignore = ["COM812", "UP007", "W293", "S101", "S110", "S112"] +select = [ "ASYNC", "B", "C4", "COM", "DJ", "E", "EM", "EXE", "F", "FLY", "FURB", "I", "ICN", "INT", "LOG", "N", "NPY", "PD", "PIE", "Q", "RSE", "S", "SIM", "SLOT", "T10", "T201", "TID", "UP", "W", "YTT",] +ignore = [ "COM812", "UP007", "W293", "S101", "S110", "S112",] [tool.coverage.run] -omit = ["tests/*"] +omit = [ "tests/*",] [tool.pytest.ini_options] addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5" -markers = [ - "requires: mark tests as requiring a specific library", - "compile: mark placeholder test used to compile integration tests without running them", -] +markers = [ "requires: mark tests as requiring a specific library", "compile: mark placeholder test used to compile integration tests without running them",] asyncio_mode = "auto" -filterwarnings = [ - "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning", -] +filterwarnings = [ "ignore::langchain_core._api.beta_decorator.LangChainBetaWarning",] [tool.poetry.group.lint] optional = true @@ -114,37 +72,29 @@ optional = true optional = true [tool.ruff.lint.pep8-naming] -classmethod-decorators = [ - "classmethod", - "langchain_core.utils.pydantic.pre_init", - "pydantic.field_validator", - "pydantic.v1.root_validator", -] +classmethod-decorators = [ "classmethod", "langchain_core.utils.pydantic.pre_init", "pydantic.field_validator", "pydantic.v1.root_validator",] [tool.ruff.lint.per-file-ignores] -"tests/unit_tests/prompts/test_chat.py" = ["E501"] -"tests/unit_tests/runnables/test_runnable.py" = ["E501"] -"tests/unit_tests/runnables/test_graph.py" = ["E501"] -"tests/**" = ["S"] -"scripts/**" = ["S"] +"tests/unit_tests/prompts/test_chat.py" = [ "E501",] +"tests/unit_tests/runnables/test_runnable.py" = [ "E501",] +"tests/unit_tests/runnables/test_graph.py" = [ "E501",] +"tests/**" = [ "S",] +"scripts/**" = [ "S",] [tool.poetry.group.lint.dependencies] ruff = "^0.5" - [tool.poetry.group.typing.dependencies] mypy = ">=1.10,<1.11" types-pyyaml = "^6.0.12.2" types-requests = "^2.28.11.5" types-jinja2 = "^2.11.9" - [tool.poetry.group.dev.dependencies] jupyter = "^1.0.0" setuptools = "^67.6.1" grandalf = "^0.8" - [tool.poetry.group.test.dependencies] pytest = "^8" freezegun = "^1.2.2" @@ -163,15 +113,12 @@ python = "<3.12" version = ">=1.26.0,<3" python = ">=3.12" - [tool.poetry.group.test_integration.dependencies] - [tool.poetry.group.typing.dependencies.langchain-text-splitters] path = "../text-splitters" develop = true - [tool.poetry.group.test.dependencies.langchain-tests] path = "../standard-tests" develop = true From 2c6bc74cb150a3befae629fb98c978e3045174be Mon Sep 17 00:00:00 2001 From: ccurme Date: Fri, 6 Dec 2024 14:55:06 -0500 Subject: [PATCH 027/157] multiple: combine sync/async vector store standard test suites (#28580) Breaking change in `langchain-tests`. --- .../how_to/integrations/standard_tests.ipynb | 40 ++--- .../integration_tests/test_vectorstores.py | 23 +-- .../vectorstores/test_aperturedb.py | 16 +- .../unit_tests/vectorstores/test_inmemory.py | 13 +- .../unit_tests/vectorstores/test_in_memory.py | 13 +- .../tests/integration_tests/test_standard.py | 21 +-- .../integration_tests/__init__.py | 5 +- .../integration_tests/vectorstores.py | 140 ++++-------------- .../unit_tests/test_in_memory_vectorstore.py | 14 +- 9 files changed, 56 insertions(+), 229 deletions(-) diff --git a/docs/docs/contributing/how_to/integrations/standard_tests.ipynb b/docs/docs/contributing/how_to/integrations/standard_tests.ipynb index dbf1a1a9b1cd3..46b20e24fa8d6 100644 --- a/docs/docs/contributing/how_to/integrations/standard_tests.ipynb +++ b/docs/docs/contributing/how_to/integrations/standard_tests.ipynb @@ -505,36 +505,21 @@ "source": [ "# title=\"tests/integration_tests/test_vectorstores_sync.py\"\n", "\n", - "from typing import AsyncGenerator, Generator\n", + "from typing import Generator\n", "\n", "import pytest\n", "from langchain_core.vectorstores import VectorStore\n", "from langchain_parrot_link.vectorstores import ParrotVectorStore\n", "from langchain_standard_tests.integration_tests.vectorstores import (\n", - " AsyncReadWriteTestSuite,\n", - " ReadWriteTestSuite,\n", + " VectorStoreIntegrationTests,\n", ")\n", "\n", "\n", - "class TestSync(ReadWriteTestSuite):\n", + "class TestParrotVectorStore(VectorStoreIntegrationTests):\n", " @pytest.fixture()\n", " def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore\n", " \"\"\"Get an empty vectorstore for unit tests.\"\"\"\n", - " store = ParrotVectorStore()\n", - " # note: store should be EMPTY at this point\n", - " # if you need to delete data, you may do so here\n", - " try:\n", - " yield store\n", - " finally:\n", - " # cleanup operations, or deleting data\n", - " pass\n", - "\n", - "\n", - "class TestAsync(AsyncReadWriteTestSuite):\n", - " @pytest.fixture()\n", - " async def vectorstore(self) -> AsyncGenerator[VectorStore, None]: # type: ignore\n", - " \"\"\"Get an empty vectorstore for unit tests.\"\"\"\n", - " store = ParrotVectorStore()\n", + " store = ParrotVectorStore(self.get_embeddings())\n", " # note: store should be EMPTY at this point\n", " # if you need to delete data, you may do so here\n", " try:\n", @@ -548,11 +533,10 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "There are separate suites for testing synchronous and asynchronous methods.\n", "Configuring the tests consists of implementing pytest fixtures for setting up an\n", "empty vector store and tearing down the vector store after the test run ends.\n", "\n", - "For example, below is the `ReadWriteTestSuite` for the [Chroma](https://python.langchain.com/docs/integrations/vectorstores/chroma/)\n", + "For example, below is the `VectorStoreIntegrationTests` class for the [Chroma](https://python.langchain.com/docs/integrations/vectorstores/chroma/)\n", "integration:\n", "\n", "```python\n", @@ -560,26 +544,27 @@ "\n", "import pytest\n", "from langchain_core.vectorstores import VectorStore\n", - "from langchain_tests.integration_tests.vectorstores import ReadWriteTestSuite\n", + "from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests\n", "\n", "from langchain_chroma import Chroma\n", "\n", "\n", - "class TestSync(ReadWriteTestSuite):\n", + "class TestChromaStandard(VectorStoreIntegrationTests):\n", " @pytest.fixture()\n", " def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore\n", - " \"\"\"Get an empty vectorstore.\"\"\"\n", + " \"\"\"Get an empty vectorstore for unit tests.\"\"\"\n", " store = Chroma(embedding_function=self.get_embeddings())\n", " try:\n", " yield store\n", " finally:\n", " store.delete_collection()\n", " pass\n", + "\n", "```\n", "\n", "Note that before the initial `yield`, we instantiate the vector store with an\n", "[embeddings](/docs/concepts/embedding_models/) object. This is a pre-defined\n", - "[\"fake\" embeddings model](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.vectorstores.ReadWriteTestSuite.html#langchain_tests.integration_tests.vectorstores.ReadWriteTestSuite.get_embeddings)\n", + "[\"fake\" embeddings model](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.vectorstores.VectorStoreIntegrationTests.html#langchain_tests.integration_tests.vectorstores.VectorStoreIntegrationTests.get_embeddings)\n", "that will generate short, arbitrary vectors for documents. You can use a different\n", "embeddings object if desired.\n", "\n", @@ -589,10 +574,7 @@ "\n", ":::note\n", "\n", - "Details on what tests are run, how each test can be skipped, and troubleshooting tips for each test can be found in the API references. See details:\n", - "\n", - "- [Sync tests API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.vectorstores.ReadWriteTestSuite.html)\n", - "- [Async tests API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.vectorstores.AsyncReadWriteTestSuite.html)\n", + "Details on what tests are run and troubleshooting tips for each test can be found in the [API reference](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.vectorstores.VectorStoreIntegrationTests.html).\n", "\n", ":::" ] diff --git a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py index 055d1d98ffd9b..d7c71f662d951 100644 --- a/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py +++ b/libs/cli/langchain_cli/integration_template/tests/integration_tests/test_vectorstores.py @@ -1,15 +1,12 @@ -from typing import AsyncGenerator, Generator +from typing import Generator import pytest from __module_name__.vectorstores import __ModuleName__VectorStore from langchain_core.vectorstores import VectorStore -from langchain_tests.integration_tests import ( - AsyncReadWriteTestSuite, - ReadWriteTestSuite, -) +from langchain_tests.integration_tests import VectorStoreIntegrationTests -class Test__ModuleName__VectorStoreSync(ReadWriteTestSuite): +class Test__ModuleName__VectorStore(VectorStoreIntegrationTests): @pytest.fixture() def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore """Get an empty vectorstore for unit tests.""" @@ -21,17 +18,3 @@ def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore finally: # cleanup operations, or deleting data pass - - -class Test__ModuleName__VectorStoreAsync(AsyncReadWriteTestSuite): - @pytest.fixture() - async def vectorstore(self) -> AsyncGenerator[VectorStore, None]: # type: ignore - """Get an empty vectorstore for unit tests.""" - store = __ModuleName__VectorStore(self.get_embeddings()) - # note: store should be EMPTY at this point - # if you need to delete data, you may do so here - try: - yield store - finally: - # cleanup operations, or deleting data - pass diff --git a/libs/community/tests/integration_tests/vectorstores/test_aperturedb.py b/libs/community/tests/integration_tests/vectorstores/test_aperturedb.py index 15d65de90b136..8b6bc19912a79 100644 --- a/libs/community/tests/integration_tests/vectorstores/test_aperturedb.py +++ b/libs/community/tests/integration_tests/vectorstores/test_aperturedb.py @@ -3,27 +3,15 @@ import uuid import pytest -from langchain_tests.integration_tests.vectorstores import ( - AsyncReadWriteTestSuite, - ReadWriteTestSuite, -) +from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests from langchain_community.vectorstores import ApertureDB -class TestApertureDBReadWriteTestSuite(ReadWriteTestSuite): +class TestApertureStandard(VectorStoreIntegrationTests): @pytest.fixture def vectorstore(self) -> ApertureDB: descriptor_set = uuid.uuid4().hex # Fresh descriptor set for each test return ApertureDB( embeddings=self.get_embeddings(), descriptor_set=descriptor_set ) - - -class TestAsyncApertureDBReadWriteTestSuite(AsyncReadWriteTestSuite): - @pytest.fixture - async def vectorstore(self) -> ApertureDB: - descriptor_set = uuid.uuid4().hex # Fresh descriptor set for each test - return ApertureDB( - embeddings=self.get_embeddings(), descriptor_set=descriptor_set - ) diff --git a/libs/community/tests/unit_tests/vectorstores/test_inmemory.py b/libs/community/tests/unit_tests/vectorstores/test_inmemory.py index b650cda14fdd1..a2bebcd426982 100644 --- a/libs/community/tests/unit_tests/vectorstores/test_inmemory.py +++ b/libs/community/tests/unit_tests/vectorstores/test_inmemory.py @@ -3,10 +3,7 @@ import pytest from langchain_core.documents import Document -from langchain_tests.integration_tests.vectorstores import ( - AsyncReadWriteTestSuite, - ReadWriteTestSuite, -) +from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests from langchain_community.vectorstores.inmemory import InMemoryVectorStore from tests.integration_tests.vectorstores.fake_embeddings import ( @@ -26,18 +23,12 @@ def _AnyDocument(**kwargs: Any) -> Document: return doc -class TestInMemoryReadWriteTestSuite(ReadWriteTestSuite): +class TestInMemoryStandard(VectorStoreIntegrationTests): @pytest.fixture def vectorstore(self) -> InMemoryVectorStore: return InMemoryVectorStore(embedding=self.get_embeddings()) -class TestAsyncInMemoryReadWriteTestSuite(AsyncReadWriteTestSuite): - @pytest.fixture - async def vectorstore(self) -> InMemoryVectorStore: - return InMemoryVectorStore(embedding=self.get_embeddings()) - - async def test_inmemory() -> None: """Test end to end construction and search.""" store = await InMemoryVectorStore.afrom_texts( diff --git a/libs/core/tests/unit_tests/vectorstores/test_in_memory.py b/libs/core/tests/unit_tests/vectorstores/test_in_memory.py index 34764f99c1016..e76f843616be8 100644 --- a/libs/core/tests/unit_tests/vectorstores/test_in_memory.py +++ b/libs/core/tests/unit_tests/vectorstores/test_in_memory.py @@ -2,10 +2,7 @@ from unittest.mock import AsyncMock, Mock import pytest -from langchain_tests.integration_tests.vectorstores import ( - AsyncReadWriteTestSuite, - ReadWriteTestSuite, -) +from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests from langchain_core.documents import Document from langchain_core.embeddings.fake import DeterministicFakeEmbedding @@ -13,18 +10,12 @@ from tests.unit_tests.stubs import _any_id_document -class TestInMemoryReadWriteTestSuite(ReadWriteTestSuite): +class TestInMemoryStandard(VectorStoreIntegrationTests): @pytest.fixture def vectorstore(self) -> InMemoryVectorStore: return InMemoryVectorStore(embedding=self.get_embeddings()) -class TestAsyncInMemoryReadWriteTestSuite(AsyncReadWriteTestSuite): - @pytest.fixture - async def vectorstore(self) -> InMemoryVectorStore: - return InMemoryVectorStore(embedding=self.get_embeddings()) - - async def test_inmemory_similarity_search() -> None: """Test end to end similarity search.""" store = await InMemoryVectorStore.afrom_texts( diff --git a/libs/partners/chroma/tests/integration_tests/test_standard.py b/libs/partners/chroma/tests/integration_tests/test_standard.py index 4396cf8df5eb4..3e2945cb7fa39 100644 --- a/libs/partners/chroma/tests/integration_tests/test_standard.py +++ b/libs/partners/chroma/tests/integration_tests/test_standard.py @@ -1,16 +1,13 @@ -from typing import AsyncGenerator, Generator +from typing import Generator import pytest from langchain_core.vectorstores import VectorStore -from langchain_tests.integration_tests.vectorstores import ( - AsyncReadWriteTestSuite, - ReadWriteTestSuite, -) +from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests from langchain_chroma import Chroma -class TestSync(ReadWriteTestSuite): +class TestChromaStandard(VectorStoreIntegrationTests): @pytest.fixture() def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore """Get an empty vectorstore for unit tests.""" @@ -20,15 +17,3 @@ def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore finally: store.delete_collection() pass - - -class TestAsync(AsyncReadWriteTestSuite): - @pytest.fixture() - async def vectorstore(self) -> AsyncGenerator[VectorStore, None]: # type: ignore - """Get an empty vectorstore for unit tests.""" - store = Chroma(embedding_function=self.get_embeddings()) - try: - yield store - finally: - store.delete_collection() - pass diff --git a/libs/standard-tests/langchain_tests/integration_tests/__init__.py b/libs/standard-tests/langchain_tests/integration_tests/__init__.py index 734af1608c6cb..b6f0a1b0f2a23 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/__init__.py +++ b/libs/standard-tests/langchain_tests/integration_tests/__init__.py @@ -23,7 +23,7 @@ from .embeddings import EmbeddingsIntegrationTests from .retrievers import RetrieversIntegrationTests from .tools import ToolsIntegrationTests -from .vectorstores import AsyncReadWriteTestSuite, ReadWriteTestSuite +from .vectorstores import VectorStoreIntegrationTests __all__ = [ "ChatModelIntegrationTests", @@ -33,7 +33,6 @@ "BaseStoreSyncTests", "AsyncCacheTestSuite", "SyncCacheTestSuite", - "AsyncReadWriteTestSuite", - "ReadWriteTestSuite", + "VectorStoreIntegrationTests", "RetrieversIntegrationTests", ] diff --git a/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py b/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py index 36770823be5e2..0ffab430939cc 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py +++ b/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py @@ -14,8 +14,8 @@ EMBEDDING_SIZE = 6 -class ReadWriteTestSuite(BaseStandardTests): - """Test suite for checking the synchronous read-write API of a vector store. +class VectorStoreIntegrationTests(BaseStandardTests): + """Test suite for checking the read-write API of a vector store. Implementers should subclass this test suite and provide a fixture that returns an empty vector store for each test. @@ -32,10 +32,10 @@ class ReadWriteTestSuite(BaseStandardTests): import pytest from langchain_core.vectorstores import VectorStore from langchain_parrot_link.vectorstores import ParrotVectorStore - from langchain_tests.integration_tests.vectorstores import ReadWriteTestSuite + from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests - class TestSync(ReadWriteTestSuite): + class TestParrotVectorStore(VectorStoreIntegrationTests): @pytest.fixture() def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore \"\"\"Get an empty vectorstore.\"\"\" @@ -60,15 +60,15 @@ def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore import pytest from langchain_core.vectorstores import VectorStore - from langchain_tests.integration_tests.vectorstores import ReadWriteTestSuite + from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests from langchain_chroma import Chroma - class TestSync(ReadWriteTestSuite): + class TestChromaStandard(VectorStoreIntegrationTests): @pytest.fixture() def vectorstore(self) -> Generator[VectorStore, None, None]: # type: ignore - \"\"\"Get an empty vectorstore.\"\"\" + \"\"\"Get an empty vectorstore for unit tests.\"\"\" store = Chroma(embedding_function=self.get_embeddings()) try: yield store @@ -107,7 +107,7 @@ def test_vectorstore_is_empty(self, vectorstore: VectorStore) -> None: .. dropdown:: Troubleshooting If this test fails, check that the test class (i.e., sub class of - ``ReadWriteTestSuite``) initializes an empty vector store in the + ``VectorStoreIntegrationTests``) initializes an empty vector store in the ``vectorestore`` fixture. """ assert vectorstore.similarity_search("foo", k=1) == [] @@ -149,7 +149,7 @@ def test_vectorstore_still_empty(self, vectorstore: VectorStore) -> None: .. dropdown:: Troubleshooting If this test fails, check that the test class (i.e., sub class of - ``ReadWriteTestSuite``) correctly clears the vector store in the + ``VectorStoreIntegrationTests``) correctly clears the vector store in the ``finally`` block. """ assert vectorstore.similarity_search("foo", k=1) == [] @@ -384,106 +384,18 @@ def test_add_documents_with_existing_ids(self, vectorstore: VectorStore) -> None Document(page_content="bar", metadata={"id": 2}, id=ids[1]), ] - -class AsyncReadWriteTestSuite(BaseStandardTests): - """Test suite for checking the async read-write API of a vector store. - - Implementers should subclass this test suite and provide a fixture - that returns an empty vector store for each test. - - The fixture should use the ``get_embeddings`` method to get a pre-defined - embeddings model that should be used for this test suite. - - Here is a template: - - .. code-block:: python - - from typing import AsyncGenerator - - import pytest - from langchain_core.vectorstores import VectorStore - from langchain_parrot_link.vectorstores import ParrotVectorStore - from langchain_tests.integration_tests.vectorstores import AsyncReadWriteTestSuite - - - class TestAsync(AsyncReadWriteTestSuite): - @pytest.fixture() - def vectorstore(self) -> AsyncGenerator[VectorStore, None]: # type: ignore - \"\"\"Get an empty vectorstore.\"\"\" - store = ParrotVectorStore(self.get_embeddings()) - # note: store should be EMPTY at this point - # if you need to delete data, you may do so here - try: - yield store - finally: - # cleanup operations, or deleting data - pass - - In the fixture, before the ``yield`` we instantiate an empty vector store. In the - ``finally`` block, we call whatever logic is necessary to bring the vector store - to a clean state. - - Example: - - .. code-block:: python - - from typing import AsyncGenerator, Generator - - import pytest - from langchain_core.vectorstores import VectorStore - from langchain_tests.integration_tests.vectorstores import AsyncReadWriteTestSuite - - from langchain_chroma import Chroma - - - class TestAsync(AsyncReadWriteTestSuite): - @pytest.fixture() - async def vectorstore(self) -> AsyncGenerator[VectorStore, None]: # type: ignore - \"\"\"Get an empty vectorstore for unit tests.\"\"\" - store = Chroma(embedding_function=self.get_embeddings()) - try: - yield store - finally: - store.delete_collection() - pass - - .. note:: - API references for individual test methods include troubleshooting tips. - """ # noqa: E501 - - @abstractmethod - @pytest.fixture - async def vectorstore(self) -> VectorStore: - """Get the vectorstore class to test. - - The returned vectorstore should be EMPTY. - """ - - @staticmethod - def get_embeddings() -> Embeddings: - """A pre-defined embeddings model that should be used for this test. - - This currently uses ``DeterministicFakeEmbedding`` from ``langchain-core``, - which uses numpy to generate random numbers based on a hash of the input text. - - The resulting embeddings are not meaningful, but they are deterministic. - """ - return DeterministicFakeEmbedding( - size=EMBEDDING_SIZE, - ) - - async def test_vectorstore_is_empty(self, vectorstore: VectorStore) -> None: + async def test_vectorstore_is_empty_async(self, vectorstore: VectorStore) -> None: """Test that the vectorstore is empty. .. dropdown:: Troubleshooting If this test fails, check that the test class (i.e., sub class of - ``AsyncReadWriteTestSuite``) initializes an empty vector store in the + ``VectorStoreIntegrationTests``) initializes an empty vector store in the ``vectorestore`` fixture. """ assert await vectorstore.asimilarity_search("foo", k=1) == [] - async def test_add_documents(self, vectorstore: VectorStore) -> None: + async def test_add_documents_async(self, vectorstore: VectorStore) -> None: """Test adding documents into the vectorstore. .. dropdown:: Troubleshooting @@ -512,7 +424,9 @@ async def test_add_documents(self, vectorstore: VectorStore) -> None: Document(page_content="bar", metadata={"id": 2}), ] - async def test_vectorstore_still_empty(self, vectorstore: VectorStore) -> None: + async def test_vectorstore_still_empty_async( + self, vectorstore: VectorStore + ) -> None: """This test should follow a test that adds documents. This just verifies that the fixture is set up properly to be empty @@ -521,12 +435,12 @@ async def test_vectorstore_still_empty(self, vectorstore: VectorStore) -> None: .. dropdown:: Troubleshooting If this test fails, check that the test class (i.e., sub class of - ``AsyncReadWriteTestSuite``) correctly clears the vector store in the + ``VectorStoreIntegrationTests``) correctly clears the vector store in the ``finally`` block. """ assert await vectorstore.asimilarity_search("foo", k=1) == [] - async def test_deleting_documents(self, vectorstore: VectorStore) -> None: + async def test_deleting_documents_async(self, vectorstore: VectorStore) -> None: """Test deleting documents from the vectorstore. .. dropdown:: Troubleshooting @@ -545,7 +459,9 @@ async def test_deleting_documents(self, vectorstore: VectorStore) -> None: documents = await vectorstore.asimilarity_search("foo", k=1) assert documents == [Document(page_content="bar", metadata={"id": 2}, id="2")] - async def test_deleting_bulk_documents(self, vectorstore: VectorStore) -> None: + async def test_deleting_bulk_documents_async( + self, vectorstore: VectorStore + ) -> None: """Test that we can delete several documents at once. .. dropdown:: Troubleshooting @@ -564,7 +480,7 @@ async def test_deleting_bulk_documents(self, vectorstore: VectorStore) -> None: documents = await vectorstore.asimilarity_search("foo", k=1) assert documents == [Document(page_content="baz", metadata={"id": 3}, id="3")] - async def test_delete_missing_content(self, vectorstore: VectorStore) -> None: + async def test_delete_missing_content_async(self, vectorstore: VectorStore) -> None: """Deleting missing content should not raise an exception. .. dropdown:: Troubleshooting @@ -575,7 +491,7 @@ async def test_delete_missing_content(self, vectorstore: VectorStore) -> None: await vectorstore.adelete(["1"]) await vectorstore.adelete(["1", "2", "3"]) - async def test_add_documents_with_ids_is_idempotent( + async def test_add_documents_with_ids_is_idempotent_async( self, vectorstore: VectorStore ) -> None: """Adding by ID should be idempotent. @@ -598,7 +514,7 @@ async def test_add_documents_with_ids_is_idempotent( Document(page_content="foo", metadata={"id": 1}, id="1"), ] - async def test_add_documents_by_id_with_mutation( + async def test_add_documents_by_id_with_mutation_async( self, vectorstore: VectorStore ) -> None: """Test that we can overwrite by ID using add_documents. @@ -636,7 +552,7 @@ async def test_add_documents_by_id_with_mutation( Document(id="2", page_content="bar", metadata={"id": 2}), ] - async def test_get_by_ids(self, vectorstore: VectorStore) -> None: + async def test_get_by_ids_async(self, vectorstore: VectorStore) -> None: """Test get by IDs. This test requires that ``get_by_ids`` be implemented on the vector store. @@ -668,7 +584,7 @@ async def test_get_by_ids(self, vectorstore: VectorStore) -> None: Document(page_content="bar", metadata={"id": 2}, id=ids[1]), ] - async def test_get_by_ids_missing(self, vectorstore: VectorStore) -> None: + async def test_get_by_ids_missing_async(self, vectorstore: VectorStore) -> None: """Test get by IDs with missing IDs. .. dropdown:: Troubleshooting @@ -690,7 +606,9 @@ async def test_get_by_ids_missing(self, vectorstore: VectorStore) -> None: # This should not raise an exception assert await vectorstore.aget_by_ids(["1", "2", "3"]) == [] - async def test_add_documents_documents(self, vectorstore: VectorStore) -> None: + async def test_add_documents_documents_async( + self, vectorstore: VectorStore + ) -> None: """Run add_documents tests. .. dropdown:: Troubleshooting @@ -722,7 +640,7 @@ async def test_add_documents_documents(self, vectorstore: VectorStore) -> None: Document(page_content="bar", metadata={"id": 2}, id=ids[1]), ] - async def test_add_documents_with_existing_ids( + async def test_add_documents_with_existing_ids_async( self, vectorstore: VectorStore ) -> None: """Test that add_documents with existing IDs is idempotent. diff --git a/libs/standard-tests/tests/unit_tests/test_in_memory_vectorstore.py b/libs/standard-tests/tests/unit_tests/test_in_memory_vectorstore.py index 8a3bf5d0a32b2..53b9dd1a9c8d4 100644 --- a/libs/standard-tests/tests/unit_tests/test_in_memory_vectorstore.py +++ b/libs/standard-tests/tests/unit_tests/test_in_memory_vectorstore.py @@ -4,21 +4,11 @@ VectorStore, ) -from langchain_tests.integration_tests.vectorstores import ( - AsyncReadWriteTestSuite, - ReadWriteTestSuite, -) +from langchain_tests.integration_tests.vectorstores import VectorStoreIntegrationTests -class TestInMemoryVectorStore(ReadWriteTestSuite): +class TestInMemoryVectorStore(VectorStoreIntegrationTests): @pytest.fixture def vectorstore(self) -> VectorStore: embeddings = self.get_embeddings() return InMemoryVectorStore(embedding=embeddings) - - -class TestAsyncInMemoryVectorStore(AsyncReadWriteTestSuite): - @pytest.fixture - async def vectorstore(self) -> VectorStore: - embeddings = self.get_embeddings() - return InMemoryVectorStore(embedding=embeddings) From c38b845d7ebd4673fb7d41abc95f3953b297713c Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 12:05:18 -0800 Subject: [PATCH 028/157] core: fix path test (#28584) --- libs/core/tests/unit_tests/_api/test_path.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/libs/core/tests/unit_tests/_api/test_path.py b/libs/core/tests/unit_tests/_api/test_path.py index 89428c7cfcb85..93896aab1158e 100644 --- a/libs/core/tests/unit_tests/_api/test_path.py +++ b/libs/core/tests/unit_tests/_api/test_path.py @@ -10,7 +10,11 @@ def test_as_import_path() -> None: """Test that the path is converted to a LangChain import path.""" # Verify that default paths are correct - assert path.PACKAGE_DIR == ROOT / "langchain_core" + + # if editable install, check directory structure + if path.PACKAGE_DIR == ROOT / "langchain_core": + assert path.PACKAGE_DIR == ROOT / "langchain_core" + # Verify that as import path works correctly assert path.as_import_path(HERE, relative_to=ROOT) == "tests.unit_tests._api" assert ( From e6663b69f368bff8fd1da54125bca8ed22afc980 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 12:20:24 -0800 Subject: [PATCH 029/157] langchain: release 0.3.10 (#28585) --- libs/langchain/poetry.lock | 1250 ++++++++++++++++----------------- libs/langchain/pyproject.toml | 4 +- 2 files changed, 626 insertions(+), 628 deletions(-) diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock index 5864ac56eeac0..6b965558b4b22 100644 --- a/libs/langchain/poetry.lock +++ b/libs/langchain/poetry.lock @@ -1,99 +1,99 @@ -# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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"sha256:ac1801c45cbf77b6c99242eeff4fffb5e4e73a800b5c4ad4fc0be5def634d2e1"}, ] [package.dependencies] @@ -4973,4 +4971,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "49339ee21f898abb08e43b110a54e89823192e23fddbfcffdbed8bf27e8417b2" +content-hash = "281ab0dd41e4fc73f4d91dab9dbfccf0282c4eb34068f3059f28b9b67aec40e0" diff --git a/libs/langchain/pyproject.toml b/libs/langchain/pyproject.toml index e649ac585a155..85bb4fc724e41 100644 --- a/libs/langchain/pyproject.toml +++ b/libs/langchain/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api" [tool.poetry] name = "langchain" -version = "0.3.9" +version = "0.3.10" description = "Building applications with LLMs through composability" authors = [] license = "MIT" @@ -33,7 +33,7 @@ langchain-server = "langchain.server:main" [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.21" +langchain-core = "^0.3.22" langchain-text-splitters = "^0.3.0" langsmith = "^0.1.17" pydantic = "^2.7.4" From 221ab03fe41fcc8a172bbc049ba7fd680507ad96 Mon Sep 17 00:00:00 2001 From: Bagatur <22008038+baskaryan@users.noreply.github.com> Date: Fri, 6 Dec 2024 12:52:15 -0800 Subject: [PATCH 030/157] docs: readme/intro nits (#28581) --- README.md | 11 ++++++----- docs/docs/concepts/architecture.mdx | 2 +- docs/docs/introduction.mdx | 8 ++++---- 3 files changed, 11 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index 04de99fad0f4c..23528cacfb5a6 100644 --- a/README.md +++ b/README.md @@ -38,18 +38,19 @@ conda install langchain -c conda-forge For these applications, LangChain simplifies the entire application lifecycle: + - **Open-source libraries**: Build your applications using LangChain's open-source [building blocks](https://python.langchain.com/docs/concepts/#langchain-expression-language-lcel), [components](https://python.langchain.com/docs/concepts/), and [third-party integrations](https://python.langchain.com/docs/integrations/providers/). Use [LangGraph](https://langchain-ai.github.io/langgraph/) to build stateful agents with first-class streaming and human-in-the-loop support. - **Productionization**: Inspect, monitor, and evaluate your apps with [LangSmith](https://docs.smith.langchain.com/) so that you can constantly optimize and deploy with confidence. -- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/). +- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/). ### Open-source libraries - **`langchain-core`**: Base abstractions and LangChain Expression Language. -- **`langchain-community`**: Third party integrations. - - Some integrations have been further split into **partner packages** that only rely on **`langchain-core`**. Examples include **`langchain_openai`** and **`langchain_anthropic`**. +- **Integration packages** (e.g. **`langchain-openai`**, **`langchain-anthropic`**, etc.): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers. - **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture. -- **[`LangGraph`](https://langchain-ai.github.io/langgraph/)**: A library for building robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph). +- **`langchain-community`**: Third-party integrations that are community maintained. +- **[LangGraph](https://langchain-ai.github.io/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph). ### Productionization: @@ -57,7 +58,7 @@ For these applications, LangChain simplifies the entire application lifecycle: ### Deployment: -- **[LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/)**: Turn your LangGraph applications into production-ready APIs and Assistants. +- **[LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/)**: Turn your LangGraph applications into production-ready APIs and Assistants. ![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](docs/static/svg/langchain_stack_112024.svg#gh-light-mode-only "LangChain Architecture Overview") ![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](docs/static/svg/langchain_stack_112024_dark.svg#gh-dark-mode-only "LangChain Architecture Overview") diff --git a/docs/docs/concepts/architecture.mdx b/docs/docs/concepts/architecture.mdx index 923ee5a705f20..66272190080b9 100644 --- a/docs/docs/concepts/architecture.mdx +++ b/docs/docs/concepts/architecture.mdx @@ -65,7 +65,7 @@ A package to deploy LangChain chains as REST APIs. Makes it easy to get a produc :::important LangServe is designed to primarily deploy simple Runnables and work with well-known primitives in langchain-core. -If you need a deployment option for LangGraph, you should instead be looking at LangGraph Cloud (beta) which will be better suited for deploying LangGraph applications. +If you need a deployment option for LangGraph, you should instead be looking at LangGraph Platform (beta) which will be better suited for deploying LangGraph applications. ::: For more information, see the [LangServe documentation](/docs/langserve). diff --git a/docs/docs/introduction.mdx b/docs/docs/introduction.mdx index b3edcfbd15dff..e0110afd973bb 100644 --- a/docs/docs/introduction.mdx +++ b/docs/docs/introduction.mdx @@ -11,7 +11,7 @@ LangChain simplifies every stage of the LLM application lifecycle: - **Development**: Build your applications using LangChain's open-source [building blocks](/docs/concepts/lcel), [components](/docs/concepts), and [third-party integrations](/docs/integrations/providers/). Use [LangGraph](/docs/concepts/architecture/#langgraph) to build stateful agents with first-class streaming and human-in-the-loop support. - **Productionization**: Use [LangSmith](https://docs.smith.langchain.com/) to inspect, monitor and evaluate your chains, so that you can continuously optimize and deploy with confidence. -- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Cloud](https://langchain-ai.github.io/langgraph/cloud/). +- **Deployment**: Turn your LangGraph applications into production-ready APIs and Assistants with [LangGraph Platform](https://langchain-ai.github.io/langgraph/cloud/). import ThemedImage from '@theme/ThemedImage'; import useBaseUrl from '@docusaurus/useBaseUrl'; @@ -29,11 +29,11 @@ import useBaseUrl from '@docusaurus/useBaseUrl'; Concretely, the framework consists of the following open-source libraries: - **`langchain-core`**: Base abstractions and LangChain Expression Language. -- Integration packages (e.g. **`langchain-openai`**, **`langchain-anthropic`**, etc.): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers. +- **Integration packages** (e.g. `langchain-openai`, `langchain-anthropic`, etc.): Important integrations have been split into lightweight packages that are co-maintained by the LangChain team and the integration developers. - **`langchain`**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture. - **`langchain-community`**: Third-party integrations that are community maintained. -- **[LangGraph](https://langchain-ai.github.io/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. -- **[LangGraphPlatform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform)**: Deploy LLM applications built with LangGraph to production. +- **[LangGraph](https://langchain-ai.github.io/langgraph)**: Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it. To learn more about LangGraph, check out our first LangChain Academy course, *Introduction to LangGraph*, available [here](https://academy.langchain.com/courses/intro-to-langgraph). +- **[LangGraph Platform](https://langchain-ai.github.io/langgraph/concepts/#langgraph-platform)**: Deploy LLM applications built with LangGraph to production. - **[LangSmith](https://docs.smith.langchain.com)**: A developer platform that lets you debug, test, evaluate, and monitor LLM applications. From 4f999521295bbdd4e8f6748a493559eb1fcbad3d Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 13:19:52 -0800 Subject: [PATCH 031/157] docs: enable private docstring members sphinx (#28586) --- docs/api_reference/create_api_rst.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docs/api_reference/create_api_rst.py b/docs/api_reference/create_api_rst.py index b66e1938fe399..0635dbb7ff862 100644 --- a/docs/api_reference/create_api_rst.py +++ b/docs/api_reference/create_api_rst.py @@ -80,6 +80,8 @@ def _load_module_members(module_path: str, namespace: str) -> ModuleMembers: continue if type_.__module__ != module_path: continue + if ":private:" in (type_.__doc__ or ""): + continue if inspect.isclass(type_): # The type of the class is used to select a template From 791d7e965e5cec1e5056c80a64d06a688e3cd808 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 13:23:06 -0800 Subject: [PATCH 032/157] docs: enable private docstring modules sphinx (#28588) --- docs/api_reference/create_api_rst.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/docs/api_reference/create_api_rst.py b/docs/api_reference/create_api_rst.py index 0635dbb7ff862..1d4a35b9f0dd1 100644 --- a/docs/api_reference/create_api_rst.py +++ b/docs/api_reference/create_api_rst.py @@ -72,9 +72,14 @@ def _load_module_members(module_path: str, namespace: str) -> ModuleMembers: Returns: list: A list of loaded module objects. """ + classes_: List[ClassInfo] = [] functions: List[FunctionInfo] = [] module = importlib.import_module(module_path) + + if ":private:" in (module.__doc__ or ""): + return ModuleMembers(classes_=[], functions=[]) + for name, type_ in inspect.getmembers(module): if not hasattr(type_, "__module__"): continue From 1cedf401a7fefa9d97d3265e294c6a97eb0fc03f Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 13:36:34 -0800 Subject: [PATCH 033/157] docs: enable private docstring submembers sphinx (#28589) --- docs/api_reference/conf.py | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/docs/api_reference/conf.py b/docs/api_reference/conf.py index 3f742b051571a..4e01aefcbad69 100644 --- a/docs/api_reference/conf.py +++ b/docs/api_reference/conf.py @@ -87,6 +87,14 @@ def run(self): def setup(app): app.add_directive("example_links", ExampleLinksDirective) app.add_directive("beta", Beta) + app.connect('autodoc-skip-member', skip_private_members) + +def skip_private_members(app, what, name, obj, skip, options): + if skip: + return True + if hasattr(obj, '__doc__') and obj.__doc__ and ':private:' in obj.__doc__: + return True + return None # -- Project information ----------------------------------------------------- From 246c10a1cc22651c61369651083e1a0bfae02d6e Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 13:52:58 -0800 Subject: [PATCH 034/157] standard-tests: private members and tools unit troubleshoot (#28590) --- .../langchain_tests/__init__.py | 7 +++ libs/standard-tests/langchain_tests/base.py | 4 ++ .../langchain_tests/unit_tests/tools.py | 62 ++++++++++++++++--- .../langchain_tests/utils/pydantic.py | 6 +- 4 files changed, 69 insertions(+), 10 deletions(-) diff --git a/libs/standard-tests/langchain_tests/__init__.py b/libs/standard-tests/langchain_tests/__init__.py index e69de29bb2d1d..1ebd42cf78968 100644 --- a/libs/standard-tests/langchain_tests/__init__.py +++ b/libs/standard-tests/langchain_tests/__init__.py @@ -0,0 +1,7 @@ +""" +Base Test classes for standard testing. + +To learn how to use these classes, see the +`Integration standard testing `_ +guide +""" diff --git a/libs/standard-tests/langchain_tests/base.py b/libs/standard-tests/langchain_tests/base.py index f2b7ca1f7e92d..7c01639db5114 100644 --- a/libs/standard-tests/langchain_tests/base.py +++ b/libs/standard-tests/langchain_tests/base.py @@ -3,6 +3,10 @@ class BaseStandardTests(ABC): + """ + :private: + """ + def test_no_overrides_DO_NOT_OVERRIDE(self) -> None: """ Test that no standard tests are overridden. diff --git a/libs/standard-tests/langchain_tests/unit_tests/tools.py b/libs/standard-tests/langchain_tests/unit_tests/tools.py index 93701437da340..d674dfe4f48f0 100644 --- a/libs/standard-tests/langchain_tests/unit_tests/tools.py +++ b/libs/standard-tests/langchain_tests/unit_tests/tools.py @@ -1,3 +1,8 @@ +""" +.. autosummary:: + :exclude-members: ToolsTests +""" + import os from abc import abstractmethod from typing import Tuple, Type, Union @@ -11,12 +16,25 @@ class ToolsTests(BaseStandardTests): + """ + :private: + Base class for testing tools. This won't show in the documentation, but + the docstrings will be inherited by subclasses. + """ + @property @abstractmethod - def tool_constructor(self) -> Union[Type[BaseTool], BaseTool]: ... + def tool_constructor(self) -> Union[Type[BaseTool], BaseTool]: + """ + Returns a class or instance of a tool to be tested. + """ + ... @property def tool_constructor_params(self) -> dict: + """ + Returns a dictionary of parameters to pass to the tool constructor. + """ return {} @property @@ -24,13 +42,16 @@ def tool_invoke_params_example(self) -> dict: """ Returns a dictionary representing the "args" of an example tool call. - This should NOT be a ToolCall dict - i.e. it should not + This should NOT be a ToolCall dict - it should not have {"name", "id", "args"} keys. """ return {} @pytest.fixture def tool(self) -> BaseTool: + """ + :private: + """ if isinstance(self.tool_constructor, BaseTool): if self.tool_constructor_params != {}: msg = ( @@ -43,19 +64,24 @@ def tool(self) -> BaseTool: class ToolsUnitTests(ToolsTests): + @property + def init_from_env_params(self) -> Tuple[dict, dict, dict]: + """Return env vars, init args, and expected instance attrs for initializing + from env vars.""" + return {}, {}, {} + def test_init(self) -> None: + """ + Test that the tool can be initialized with :attr:`tool_constructor` and + :attr:`tool_constructor_params`. If this fails, check that the + keyword args defined in :attr:`tool_constructor_params` are valid. + """ if isinstance(self.tool_constructor, BaseTool): tool = self.tool_constructor else: tool = self.tool_constructor(**self.tool_constructor_params) assert tool is not None - @property - def init_from_env_params(self) -> Tuple[dict, dict, dict]: - """Return env vars, init args, and expected instance attrs for initializing - from env vars.""" - return {}, {}, {} - def test_init_from_env(self) -> None: env_params, tools_params, expected_attrs = self.init_from_env_params if env_params: @@ -69,14 +95,32 @@ def test_init_from_env(self) -> None: assert actual == expected def test_has_name(self, tool: BaseTool) -> None: + """ + Tests that the tool has a name attribute to pass to chat models. + + If this fails, add a `name` parameter to your tool. + """ assert tool.name def test_has_input_schema(self, tool: BaseTool) -> None: + """ + Tests that the tool has an input schema. + + If this fails, add an `args_schema` to your tool. + + See + `this guide `_ + and see how `CalculatorInput` is configured in the + `CustomCalculatorTool.args_schema` attribute + """ assert tool.get_input_schema() def test_input_schema_matches_invoke_params(self, tool: BaseTool) -> None: """ - Tests that the provided example params match the declared input schema + Tests that the provided example params match the declared input schema. + + If this fails, update the `tool_invoke_params_example` attribute to match + the input schema (`args_schema`) of the tool. """ # this will be a pydantic object input_schema = tool.get_input_schema() diff --git a/libs/standard-tests/langchain_tests/utils/pydantic.py b/libs/standard-tests/langchain_tests/utils/pydantic.py index 6aa0408a092d7..52720bbd081b2 100644 --- a/libs/standard-tests/langchain_tests/utils/pydantic.py +++ b/libs/standard-tests/langchain_tests/utils/pydantic.py @@ -1,4 +1,8 @@ -"""Utilities for working with pydantic models.""" +""" +Utilities for working with pydantic models. + +:private: +""" def get_pydantic_major_version() -> int: From 9e2abcd1521628330bc93f7075513c5370dd583a Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 14:48:13 -0800 Subject: [PATCH 035/157] standard-tests: show right classes in api docs (#28591) --- .../integration_tests/base_store.py | 8 + .../integration_tests/cache.py | 8 + .../integration_tests/chat_models.py | 245 ++++++++++++-- .../integration_tests/indexer.py | 10 +- .../langchain_tests/unit_tests/chat_models.py | 317 +++++++++--------- .../langchain_tests/unit_tests/embeddings.py | 4 + 6 files changed, 412 insertions(+), 180 deletions(-) diff --git a/libs/standard-tests/langchain_tests/integration_tests/base_store.py b/libs/standard-tests/langchain_tests/integration_tests/base_store.py index cc5fab8bcf7a4..ff9e178aea903 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/base_store.py +++ b/libs/standard-tests/langchain_tests/integration_tests/base_store.py @@ -1,3 +1,11 @@ +""" +Standard tests for the BaseStore abstraction + +We don't recommend implementing externally managed BaseStore abstractions at this time. + +:private: +""" + from abc import abstractmethod from typing import AsyncGenerator, Generator, Generic, Tuple, TypeVar diff --git a/libs/standard-tests/langchain_tests/integration_tests/cache.py b/libs/standard-tests/langchain_tests/integration_tests/cache.py index 7087da8ea07b3..3d04731d16a74 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/cache.py +++ b/libs/standard-tests/langchain_tests/integration_tests/cache.py @@ -1,3 +1,11 @@ +""" +Standard tests for the BaseCache abstraction + +We don't recommend implementing externally managed BaseCache abstractions at this time. + +:private: +""" + from abc import abstractmethod import pytest diff --git a/libs/standard-tests/langchain_tests/integration_tests/chat_models.py b/libs/standard-tests/langchain_tests/integration_tests/chat_models.py index 4e6a811c4516e..0dd5334cc4867 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/chat_models.py +++ b/libs/standard-tests/langchain_tests/integration_tests/chat_models.py @@ -16,7 +16,7 @@ ) from langchain_core.output_parsers import StrOutputParser from langchain_core.prompts import ChatPromptTemplate -from langchain_core.tools import tool +from langchain_core.tools import BaseTool, tool from langchain_core.utils.function_calling import tool_example_to_messages from pydantic import BaseModel, Field from pydantic.v1 import BaseModel as BaseModelV1 @@ -24,16 +24,29 @@ from langchain_tests.unit_tests.chat_models import ( ChatModelTests, - my_adder_tool, ) from langchain_tests.utils.pydantic import PYDANTIC_MAJOR_VERSION -class MagicFunctionSchema(BaseModel): +def _get_joke_class() -> type[BaseModel]: + """ + :private: + """ + + class Joke(BaseModel): + """Joke to tell user.""" + + setup: str = Field(description="question to set up a joke") + punchline: str = Field(description="answer to resolve the joke") + + return Joke + + +class _MagicFunctionSchema(BaseModel): input: int = Field(..., gt=-1000, lt=1000) -@tool(args_schema=MagicFunctionSchema) +@tool(args_schema=_MagicFunctionSchema) def magic_function(input: int) -> int: """Applies a magic function to an input.""" return input + 2 @@ -45,13 +58,6 @@ def magic_function_no_args() -> int: return 5 -class Joke(BaseModel): - """Joke to tell user.""" - - setup: str = Field(description="question to set up a joke") - punchline: str = Field(description="answer to resolve the joke") - - def _validate_tool_call_message(message: BaseMessage) -> None: assert isinstance(message, AIMessage) assert len(message.tool_calls) == 1 @@ -103,12 +109,201 @@ def chat_model_params(self) -> dict: .. note:: API references for individual test methods include troubleshooting tips. - .. note:: - Test subclasses can control what features are tested (such as tool - calling or multi-modality) by selectively overriding the properties on the - class. Relevant properties are mentioned in the references for each method. - See this page for detail on all properties: - https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.chat_models.ChatModelTests.html + + Test subclasses must implement the following two properties: + + chat_model_class + The chat model class to test, e.g., ``ChatParrotLink``. + + Example: + + .. code-block:: python + + @property + def chat_model_class(self) -> Type[ChatParrotLink]: + return ChatParrotLink + + chat_model_params + Initialization parameters for the chat model. + + Example: + + .. code-block:: python + + @property + def chat_model_params(self) -> dict: + return {"model": "bird-brain-001", "temperature": 0} + + In addition, test subclasses can control what features are tested (such as tool + calling or multi-modality) by selectively overriding the following properties. + Expand to see details: + + .. dropdown:: has_tool_calling + + Boolean property indicating whether the chat model supports tool calling. + + By default, this is determined by whether the chat model's `bind_tools` method + is overridden. It typically does not need to be overridden on the test class. + + .. dropdown:: tool_choice_value + + Value to use for tool choice when used in tests. + + Some tests for tool calling features attempt to force tool calling via a + `tool_choice` parameter. A common value for this parameter is "any". Defaults + to `None`. + + Note: if the value is set to "tool_name", the name of the tool used in each + test will be set as the value for `tool_choice`. + + Example: + + .. code-block:: python + + @property + def tool_choice_value(self) -> Optional[str]: + return "any" + + .. dropdown:: has_structured_output + + Boolean property indicating whether the chat model supports structured + output. + + By default, this is determined by whether the chat model's + `with_structured_output` method is overridden. If the base implementation is + intended to be used, this method should be overridden. + + See: https://python.langchain.com/docs/concepts/structured_outputs/ + + Example: + + .. code-block:: python + + @property + def has_structured_output(self) -> bool: + return True + + .. dropdown:: supports_image_inputs + + Boolean property indicating whether the chat model supports image inputs. + Defaults to ``False``. + + If set to ``True``, the chat model will be tested using content blocks of the + form + + .. code-block:: python + + [ + {"type": "text", "text": "describe the weather in this image"}, + { + "type": "image_url", + "image_url": {"url": f"data:image/jpeg;base64,{image_data}"}, + }, + ] + + See https://python.langchain.com/docs/concepts/multimodality/ + + Example: + + .. code-block:: python + + @property + def supports_image_inputs(self) -> bool: + return True + + .. dropdown:: supports_video_inputs + + Boolean property indicating whether the chat model supports image inputs. + Defaults to ``False``. No current tests are written for this feature. + + .. dropdown:: returns_usage_metadata + + Boolean property indicating whether the chat model returns usage metadata + on invoke and streaming responses. + + ``usage_metadata`` is an optional dict attribute on AIMessages that track input + and output tokens: https://python.langchain.com/api_reference/core/messages/langchain_core.messages.ai.UsageMetadata.html + + Example: + + .. code-block:: python + + @property + def returns_usage_metadata(self) -> bool: + return False + + .. dropdown:: supports_anthropic_inputs + + Boolean property indicating whether the chat model supports Anthropic-style + inputs. + + These inputs might feature "tool use" and "tool result" content blocks, e.g., + + .. code-block:: python + + [ + {"type": "text", "text": "Hmm let me think about that"}, + { + "type": "tool_use", + "input": {"fav_color": "green"}, + "id": "foo", + "name": "color_picker", + }, + ] + + If set to ``True``, the chat model will be tested using content blocks of this + form. + + Example: + + .. code-block:: python + + @property + def supports_anthropic_inputs(self) -> bool: + return False + + .. dropdown:: supports_image_tool_message + + Boolean property indicating whether the chat model supports ToolMessages + that include image content, e.g., + + .. code-block:: python + + ToolMessage( + content=[ + { + "type": "image_url", + "image_url": {"url": f"data:image/jpeg;base64,{image_data}"}, + }, + ], + tool_call_id="1", + name="random_image", + ) + + If set to ``True``, the chat model will be tested with message sequences that + include ToolMessages of this form. + + Example: + + .. code-block:: python + + @property + def supports_image_tool_message(self) -> bool: + return False + + .. dropdown:: supported_usage_metadata_details + + Property controlling what usage metadata details are emitted in both invoke + and stream. + + ``usage_metadata`` is an optional dict attribute on AIMessages that track input + and output tokens: https://python.langchain.com/api_reference/core/messages/langchain_core.messages.ai.UsageMetadata.html + + It includes optional keys ``input_token_details`` and ``output_token_details`` + that can track usage details associated with special types of tokens, such as + cached, audio, or reasoning. + + Only needs to be overridden if these details are supplied. """ @property @@ -908,6 +1103,7 @@ def has_tool_calling(self) -> bool: if not self.has_tool_calling: pytest.skip("Test requires tool calling.") + Joke = _get_joke_class() # Pydantic class # Type ignoring since the interface only officially supports pydantic 1 # or pydantic.v1.BaseModel but not pydantic.BaseModel from pydantic 2. @@ -960,6 +1156,8 @@ def has_tool_calling(self) -> bool: if not self.has_tool_calling: pytest.skip("Test requires tool calling.") + Joke = _get_joke_class() + # Pydantic class # Type ignoring since the interface only officially supports pydantic 1 # or pydantic.v1.BaseModel but not pydantic.BaseModel from pydantic 2. @@ -1089,7 +1287,9 @@ class Joke(BaseModel): joke_result = chat.invoke("Give me a joke about cats, include the punchline.") assert isinstance(joke_result, Joke) - def test_tool_message_histories_string_content(self, model: BaseChatModel) -> None: + def test_tool_message_histories_string_content( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: """Test that message histories are compatible with string tool contents (e.g. OpenAI format). If a model passes this test, it should be compatible with messages generated from providers following OpenAI format. @@ -1158,6 +1358,7 @@ def test_tool_message_histories_string_content(self, model: BaseChatModel) -> No def test_tool_message_histories_list_content( self, model: BaseChatModel, + my_adder_tool: BaseTool, ) -> None: """Test that message histories are compatible with list tool contents (e.g. Anthropic format). @@ -1246,7 +1447,9 @@ def test_tool_message_histories_list_content(self, model: BaseChatModel) -> None result_list_content = model_with_tools.invoke(messages_list_content) assert isinstance(result_list_content, AIMessage) - def test_structured_few_shot_examples(self, model: BaseChatModel) -> None: + def test_structured_few_shot_examples( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: """Test that the model can process few-shot examples with tool calls. These are represented as a sequence of messages of the following form: @@ -1557,7 +1760,9 @@ class color_picker(BaseModelV1): ] model.bind_tools([color_picker]).invoke(messages) - def test_tool_message_error_status(self, model: BaseChatModel) -> None: + def test_tool_message_error_status( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: """Test that ToolMessage with ``status="error"`` can be handled. These messages may take the form: diff --git a/libs/standard-tests/langchain_tests/integration_tests/indexer.py b/libs/standard-tests/langchain_tests/integration_tests/indexer.py index f1e5d9eee0a43..bdc0fc2e6b408 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/indexer.py +++ b/libs/standard-tests/langchain_tests/integration_tests/indexer.py @@ -1,4 +1,12 @@ -"""Test suite to check index implementations.""" +"""Test suite to check index implementations. + +Standard tests for the DocumentIndex abstraction + +We don't recommend implementing externally managed DocumentIndex abstractions at this +time. + +:private: +""" import inspect import uuid diff --git a/libs/standard-tests/langchain_tests/unit_tests/chat_models.py b/libs/standard-tests/langchain_tests/unit_tests/chat_models.py index 71f3dd2169cc1..19225c1f2a6f6 100644 --- a/libs/standard-tests/langchain_tests/unit_tests/chat_models.py +++ b/libs/standard-tests/langchain_tests/unit_tests/chat_models.py @@ -11,7 +11,7 @@ from langchain_core.language_models import BaseChatModel from langchain_core.load import dumpd, load from langchain_core.runnables import RunnableBinding -from langchain_core.tools import tool +from langchain_core.tools import BaseTool, tool from pydantic import BaseModel, Field, SecretStr from pydantic.v1 import ( BaseModel as BaseModelV1, @@ -28,15 +28,12 @@ from langchain_tests.utils.pydantic import PYDANTIC_MAJOR_VERSION -class Person(BaseModel): # Used by some dependent tests. Should be deprecated. - """Record attributes of a person.""" - - name: str = Field(..., description="The name of the person.") - age: int = Field(..., description="The age of the person.") - - def generate_schema_pydantic_v1_from_2() -> Any: - """Use to generate a schema from v1 namespace in pydantic 2.""" + """ + Use to generate a schema from v1 namespace in pydantic 2. + + :private: + """ if PYDANTIC_MAJOR_VERSION != 2: raise AssertionError("This function is only compatible with Pydantic v2.") @@ -50,7 +47,11 @@ class PersonB(BaseModelV1): def generate_schema_pydantic() -> Any: - """Works with either pydantic 1 or 2""" + """ + Works with either pydantic 1 or 2 + + :private: + """ class PersonA(BaseModel): """Record attributes of a person.""" @@ -67,19 +68,152 @@ class PersonA(BaseModel): TEST_PYDANTIC_MODELS.append(generate_schema_pydantic_v1_from_2()) -@tool -def my_adder_tool(a: int, b: int) -> int: - """Takes two integers, a and b, and returns their sum.""" - return a + b +class ChatModelTests(BaseStandardTests): + """Base class for chat model tests. + :private: + """ # noqa: E501 -def my_adder(a: int, b: int) -> int: - """Takes two integers, a and b, and returns their sum.""" - return a + b + @property + @abstractmethod + def chat_model_class(self) -> Type[BaseChatModel]: + """The chat model class to test, e.g., `ChatParrotLink`.""" + ... + @property + def chat_model_params(self) -> dict: + """Initialization parameters for the chat mobdel.""" + return {} + + @property + def standard_chat_model_params(self) -> dict: + """:meta private:""" + return { + "temperature": 0, + "max_tokens": 100, + "timeout": 60, + "stop": [], + "max_retries": 2, + } + + @pytest.fixture + def model(self) -> BaseChatModel: + """Fixture that returns an instance of the chat model. Should not be + overridden.""" + return self.chat_model_class( + **{**self.standard_chat_model_params, **self.chat_model_params} + ) + + @pytest.fixture + def my_adder_tool(self) -> BaseTool: + @tool + def my_adder_tool(a: int, b: int) -> int: + """Takes two integers, a and b, and returns their sum.""" + return a + b + + return my_adder_tool + + @property + def has_tool_calling(self) -> bool: + """Boolean property indicating whether the model supports tool calling.""" + return self.chat_model_class.bind_tools is not BaseChatModel.bind_tools + + @property + def tool_choice_value(self) -> Optional[str]: + """Value to use for tool choice when used in tests.""" + return None + + @property + def has_structured_output(self) -> bool: + """Boolean property indicating whether the chat model supports structured + output.""" + return ( + self.chat_model_class.with_structured_output + is not BaseChatModel.with_structured_output + ) + + @property + def supports_image_inputs(self) -> bool: + """Boolean property indicating whether the chat model supports image inputs. + Defaults to ``False``.""" + return False + + @property + def supports_video_inputs(self) -> bool: + """Boolean property indicating whether the chat model supports image inputs. + Defaults to ``False``. No current tests are written for this feature.""" + return False + + @property + def returns_usage_metadata(self) -> bool: + """Boolean property indicating whether the chat model returns usage metadata + on invoke and streaming responses.""" + return True + + @property + def supports_anthropic_inputs(self) -> bool: + """Boolean property indicating whether the chat model supports Anthropic-style + inputs.""" + return False + + @property + def supports_image_tool_message(self) -> bool: + """Boolean property indicating whether the chat model supports ToolMessages + that include image content.""" + return False + + @property + def supported_usage_metadata_details( + self, + ) -> Dict[ + Literal["invoke", "stream"], + List[ + Literal[ + "audio_input", + "audio_output", + "reasoning_output", + "cache_read_input", + "cache_creation_input", + ] + ], + ]: + """Property controlling what usage metadata details are emitted in both invoke + and stream. Only needs to be overridden if these details are returned by the + model.""" + return {"invoke": [], "stream": []} + + +class ChatModelUnitTests(ChatModelTests): + """Base class for chat model unit tests. + + Test subclasses must implement the ``chat_model_class`` and + ``chat_model_params`` properties to specify what model to test and its + initialization parameters. + + Example: + + .. code-block:: python + + from typing import Type + + from langchain_tests.unit_tests import ChatModelUnitTests + from my_package.chat_models import MyChatModel + + + class TestMyChatModelUnit(ChatModelUnitTests): + @property + def chat_model_class(self) -> Type[MyChatModel]: + # Return the chat model class to test here + return MyChatModel + + @property + def chat_model_params(self) -> dict: + # Return initialization parameters for the model. + return {"model": "model-001", "temperature": 0} + + .. note:: + API references for individual test methods include troubleshooting tips. -class ChatModelTests(BaseStandardTests): - """Base class for chat model tests. Test subclasses must implement the following two properties: @@ -275,146 +409,6 @@ def supports_image_tool_message(self) -> bool: cached, audio, or reasoning. Only needs to be overridden if these details are supplied. - """ # noqa: E501 - - @property - @abstractmethod - def chat_model_class(self) -> Type[BaseChatModel]: - """The chat model class to test, e.g., `ChatParrotLink`.""" - ... - - @property - def chat_model_params(self) -> dict: - """Initialization parameters for the chat mobdel.""" - return {} - - @property - def standard_chat_model_params(self) -> dict: - """:meta private:""" - return { - "temperature": 0, - "max_tokens": 100, - "timeout": 60, - "stop": [], - "max_retries": 2, - } - - @pytest.fixture - def model(self) -> BaseChatModel: - """Fixture that returns an instance of the chat model. Should not be - overridden.""" - return self.chat_model_class( - **{**self.standard_chat_model_params, **self.chat_model_params} - ) - - @property - def has_tool_calling(self) -> bool: - """Boolean property indicating whether the model supports tool calling.""" - return self.chat_model_class.bind_tools is not BaseChatModel.bind_tools - - @property - def tool_choice_value(self) -> Optional[str]: - """Value to use for tool choice when used in tests.""" - return None - - @property - def has_structured_output(self) -> bool: - """Boolean property indicating whether the chat model supports structured - output.""" - return ( - self.chat_model_class.with_structured_output - is not BaseChatModel.with_structured_output - ) - - @property - def supports_image_inputs(self) -> bool: - """Boolean property indicating whether the chat model supports image inputs. - Defaults to ``False``.""" - return False - - @property - def supports_video_inputs(self) -> bool: - """Boolean property indicating whether the chat model supports image inputs. - Defaults to ``False``. No current tests are written for this feature.""" - return False - - @property - def returns_usage_metadata(self) -> bool: - """Boolean property indicating whether the chat model returns usage metadata - on invoke and streaming responses.""" - return True - - @property - def supports_anthropic_inputs(self) -> bool: - """Boolean property indicating whether the chat model supports Anthropic-style - inputs.""" - return False - - @property - def supports_image_tool_message(self) -> bool: - """Boolean property indicating whether the chat model supports ToolMessages - that include image content.""" - return False - - @property - def supported_usage_metadata_details( - self, - ) -> Dict[ - Literal["invoke", "stream"], - List[ - Literal[ - "audio_input", - "audio_output", - "reasoning_output", - "cache_read_input", - "cache_creation_input", - ] - ], - ]: - """Property controlling what usage metadata details are emitted in both invoke - and stream. Only needs to be overridden if these details are returned by the - model.""" - return {"invoke": [], "stream": []} - - -class ChatModelUnitTests(ChatModelTests): - """Base class for chat model unit tests. - - Test subclasses must implement the ``chat_model_class`` and - ``chat_model_params`` properties to specify what model to test and its - initialization parameters. - - Example: - - .. code-block:: python - - from typing import Type - - from langchain_tests.unit_tests import ChatModelUnitTests - from my_package.chat_models import MyChatModel - - - class TestMyChatModelUnit(ChatModelUnitTests): - @property - def chat_model_class(self) -> Type[MyChatModel]: - # Return the chat model class to test here - return MyChatModel - - @property - def chat_model_params(self) -> dict: - # Return initialization parameters for the model. - return {"model": "model-001", "temperature": 0} - - .. note:: - API references for individual test methods include troubleshooting tips. - - .. note:: - Test subclasses can control what features are tested (such as tool - calling or multi-modality) by selectively overriding the properties on the - class. Relevant properties are mentioned in the references for each method. - See this page for detail on all properties: - https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.chat_models.ChatModelTests.html - Testing initialization from environment variables Some unit tests may require testing initialization from environment variables. @@ -526,6 +520,7 @@ def test_init_streaming( def test_bind_tool_pydantic( self, model: BaseChatModel, + my_adder_tool: BaseTool, ) -> None: """Test that chat model correctly handles Pydantic models that are passed into ``bind_tools``. Test is skipped if the ``has_tool_calling`` property @@ -542,6 +537,10 @@ def test_bind_tool_pydantic( if not self.has_tool_calling: return + def my_adder(a: int, b: int) -> int: + """Takes two integers, a and b, and returns their sum.""" + return a + b + tools = [my_adder_tool, my_adder] for pydantic_model in TEST_PYDANTIC_MODELS: diff --git a/libs/standard-tests/langchain_tests/unit_tests/embeddings.py b/libs/standard-tests/langchain_tests/unit_tests/embeddings.py index c580243b16d9d..527be61e8be98 100644 --- a/libs/standard-tests/langchain_tests/unit_tests/embeddings.py +++ b/libs/standard-tests/langchain_tests/unit_tests/embeddings.py @@ -11,6 +11,10 @@ class EmbeddingsTests(BaseStandardTests): + """ + :private: + """ + @property @abstractmethod def embeddings_class(self) -> Type[Embeddings]: ... From f943205ebfd9e518fb9ef476843002ab11f22437 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 15:07:53 -0800 Subject: [PATCH 036/157] docs: dont document root init (#28592) --- docs/api_reference/conf.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/docs/api_reference/conf.py b/docs/api_reference/conf.py index 4e01aefcbad69..d16ed7b234783 100644 --- a/docs/api_reference/conf.py +++ b/docs/api_reference/conf.py @@ -94,6 +94,9 @@ def skip_private_members(app, what, name, obj, skip, options): return True if hasattr(obj, '__doc__') and obj.__doc__ and ':private:' in obj.__doc__: return True + if name == '__init__' and obj.__objclass__ is object: + # dont document default init + return True return None From 925ca75ca588cb66942599a817d1b669ce6260e2 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 15:08:25 -0800 Subject: [PATCH 037/157] docs: format (#28593) --- docs/api_reference/conf.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/docs/api_reference/conf.py b/docs/api_reference/conf.py index d16ed7b234783..acc77ab2aa6d9 100644 --- a/docs/api_reference/conf.py +++ b/docs/api_reference/conf.py @@ -87,14 +87,15 @@ def run(self): def setup(app): app.add_directive("example_links", ExampleLinksDirective) app.add_directive("beta", Beta) - app.connect('autodoc-skip-member', skip_private_members) + app.connect("autodoc-skip-member", skip_private_members) + def skip_private_members(app, what, name, obj, skip, options): if skip: return True - if hasattr(obj, '__doc__') and obj.__doc__ and ':private:' in obj.__doc__: + if hasattr(obj, "__doc__") and obj.__doc__ and ":private:" in obj.__doc__: return True - if name == '__init__' and obj.__objclass__ is object: + if name == "__init__" and obj.__objclass__ is object: # dont document default init return True return None From b7c2029e840915b8d4f80eae715cfdf594e61830 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 15:14:52 -0800 Subject: [PATCH 038/157] standard-tests: root docstrings (#28595) --- .../integration_tests/retrievers.py | 4 ++++ .../integration_tests/tools.py | 24 ++++++++++++++++++- .../integration_tests/vectorstores.py | 2 +- .../langchain_tests/unit_tests/tools.py | 9 ++++--- 4 files changed, 32 insertions(+), 7 deletions(-) diff --git a/libs/standard-tests/langchain_tests/integration_tests/retrievers.py b/libs/standard-tests/langchain_tests/integration_tests/retrievers.py index cf55e62f468ae..fa23d26674256 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/retrievers.py +++ b/libs/standard-tests/langchain_tests/integration_tests/retrievers.py @@ -9,6 +9,10 @@ class RetrieversIntegrationTests(BaseStandardTests): + """ + Base class for retrievers integration tests. + """ + @property @abstractmethod def retriever_constructor(self) -> Type[BaseRetriever]: ... diff --git a/libs/standard-tests/langchain_tests/integration_tests/tools.py b/libs/standard-tests/langchain_tests/integration_tests/tools.py index 4987626037863..2fcd610ccc052 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/tools.py +++ b/libs/standard-tests/langchain_tests/integration_tests/tools.py @@ -5,9 +5,21 @@ class ToolsIntegrationTests(ToolsTests): + """ + Base class for tools integration tests. + """ + def test_invoke_matches_output_schema(self, tool: BaseTool) -> None: """ If invoked with a ToolCall, the tool should return a valid ToolMessage content. + + If you have followed the `custom tool guide `_, + this test should always pass because ToolCall inputs are handled by the + :class:`langchain_core.tools.BaseTool` class. + + If you have not followed this guide, you should ensure that your tool's + `invoke` method returns a valid ToolMessage content when it receives + a dict representing a ToolCall as input (as opposed to distinct args). """ tool_call = ToolCall( name=tool.name, @@ -36,6 +48,8 @@ def test_invoke_matches_output_schema(self, tool: BaseTool) -> None: async def test_async_invoke_matches_output_schema(self, tool: BaseTool) -> None: """ If ainvoked with a ToolCall, the tool should return a valid ToolMessage content. + + For debugging tips, see :meth:`test_invoke_matches_output_schema`. """ tool_call = ToolCall( name=tool.name, @@ -65,12 +79,20 @@ def test_invoke_no_tool_call(self, tool: BaseTool) -> None: """ If invoked without a ToolCall, the tool can return anything but it shouldn't throw an error + + If this test fails, your tool may not be handling the input you defined + in `tool_invoke_params_example` correctly, and it's throwing an error. + + This test doesn't have any checks. It's just to ensure that the tool + doesn't throw an error when invoked with a dictionary of kwargs. """ tool.invoke(self.tool_invoke_params_example) async def test_async_invoke_no_tool_call(self, tool: BaseTool) -> None: """ - If invoked without a ToolCall, the tool can return anything + If ainvoked without a ToolCall, the tool can return anything but it shouldn't throw an error + + For debugging tips, see :meth:`test_invoke_no_tool_call`. """ await tool.ainvoke(self.tool_invoke_params_example) diff --git a/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py b/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py index 0ffab430939cc..71ec7d8bfbab1 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py +++ b/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py @@ -15,7 +15,7 @@ class VectorStoreIntegrationTests(BaseStandardTests): - """Test suite for checking the read-write API of a vector store. + """Base class for checking the read-write API of a vector store. Implementers should subclass this test suite and provide a fixture that returns an empty vector store for each test. diff --git a/libs/standard-tests/langchain_tests/unit_tests/tools.py b/libs/standard-tests/langchain_tests/unit_tests/tools.py index d674dfe4f48f0..bdc2df1c9fb62 100644 --- a/libs/standard-tests/langchain_tests/unit_tests/tools.py +++ b/libs/standard-tests/langchain_tests/unit_tests/tools.py @@ -1,8 +1,3 @@ -""" -.. autosummary:: - :exclude-members: ToolsTests -""" - import os from abc import abstractmethod from typing import Tuple, Type, Union @@ -64,6 +59,10 @@ def tool(self) -> BaseTool: class ToolsUnitTests(ToolsTests): + """ + Base class for tools unit tests. + """ + @property def init_from_env_params(self) -> Tuple[dict, dict, dict]: """Return env vars, init args, and expected instance attrs for initializing From 0eb7ab65f1a938fb9fd66840a32c64148addc836 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 15:39:47 -0800 Subject: [PATCH 039/157] multiple: fix xfailed signatures (#28597) --- .../tests/integration_tests/test_standard.py | 7 +++++-- .../tests/integration_tests/test_standard.py | 13 +++++++++---- .../chat_models/test_azure_standard.py | 7 +++++-- .../test_chat_models_standard.py | 19 +++++++++++++------ 4 files changed, 32 insertions(+), 14 deletions(-) diff --git a/libs/partners/fireworks/tests/integration_tests/test_standard.py b/libs/partners/fireworks/tests/integration_tests/test_standard.py index 692dcb40cf357..7a595e4c7da44 100644 --- a/libs/partners/fireworks/tests/integration_tests/test_standard.py +++ b/libs/partners/fireworks/tests/integration_tests/test_standard.py @@ -4,6 +4,7 @@ import pytest from langchain_core.language_models import BaseChatModel +from langchain_core.tools import BaseTool from langchain_tests.integration_tests import ( # type: ignore[import-not-found] ChatModelIntegrationTests, # type: ignore[import-not-found] ) @@ -24,5 +25,7 @@ def chat_model_params(self) -> dict: } @pytest.mark.xfail(reason="Not yet implemented.") - def test_tool_message_histories_list_content(self, model: BaseChatModel) -> None: - super().test_tool_message_histories_list_content(model) + def test_tool_message_histories_list_content( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_tool_message_histories_list_content(model, my_adder_tool) diff --git a/libs/partners/groq/tests/integration_tests/test_standard.py b/libs/partners/groq/tests/integration_tests/test_standard.py index 3870ae953f6ee..b97b8c10422ef 100644 --- a/libs/partners/groq/tests/integration_tests/test_standard.py +++ b/libs/partners/groq/tests/integration_tests/test_standard.py @@ -5,6 +5,7 @@ import pytest from langchain_core.language_models import BaseChatModel from langchain_core.rate_limiters import InMemoryRateLimiter +from langchain_core.tools import BaseTool from langchain_tests.integration_tests import ( ChatModelIntegrationTests, ) @@ -20,8 +21,10 @@ def chat_model_class(self) -> Type[BaseChatModel]: return ChatGroq @pytest.mark.xfail(reason="Not yet implemented.") - def test_tool_message_histories_list_content(self, model: BaseChatModel) -> None: - super().test_tool_message_histories_list_content(model) + def test_tool_message_histories_list_content( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_tool_message_histories_list_content(model, my_adder_tool) class TestGroqLlama(BaseTestGroq): @@ -47,8 +50,10 @@ def test_tool_calling_with_no_arguments(self, model: BaseChatModel) -> None: @pytest.mark.xfail( reason=("Fails with 'Failed to call a function. Please adjust your prompt.'") ) - def test_tool_message_histories_string_content(self, model: BaseChatModel) -> None: - super().test_tool_message_histories_string_content(model) + def test_tool_message_histories_string_content( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_tool_message_histories_string_content(model, my_adder_tool) @pytest.mark.xfail( reason=( diff --git a/libs/partners/openai/tests/unit_tests/chat_models/test_azure_standard.py b/libs/partners/openai/tests/unit_tests/chat_models/test_azure_standard.py index 3d1faa97db485..f74f1c6804f3a 100644 --- a/libs/partners/openai/tests/unit_tests/chat_models/test_azure_standard.py +++ b/libs/partners/openai/tests/unit_tests/chat_models/test_azure_standard.py @@ -4,6 +4,7 @@ import pytest from langchain_core.language_models import BaseChatModel +from langchain_core.tools import BaseTool from langchain_tests.unit_tests import ChatModelUnitTests from langchain_openai import AzureChatOpenAI @@ -23,8 +24,10 @@ def chat_model_params(self) -> dict: } @pytest.mark.xfail(reason="AzureOpenAI does not support tool_choice='any'") - def test_bind_tool_pydantic(self, model: BaseChatModel) -> None: - super().test_bind_tool_pydantic(model) + def test_bind_tool_pydantic( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_bind_tool_pydantic(model, my_adder_tool) @property def init_from_env_params(self) -> Tuple[dict, dict, dict]: diff --git a/libs/partners/xai/tests/integration_tests/test_chat_models_standard.py b/libs/partners/xai/tests/integration_tests/test_chat_models_standard.py index 1152fe44946f7..edcaf93eebf02 100644 --- a/libs/partners/xai/tests/integration_tests/test_chat_models_standard.py +++ b/libs/partners/xai/tests/integration_tests/test_chat_models_standard.py @@ -5,6 +5,7 @@ import pytest # type: ignore[import-not-found] from langchain_core.language_models import BaseChatModel from langchain_core.rate_limiters import InMemoryRateLimiter +from langchain_core.tools import BaseTool from langchain_tests.integration_tests import ( # type: ignore[import-not-found] ChatModelIntegrationTests, # type: ignore[import-not-found] ) @@ -40,13 +41,19 @@ def test_usage_metadata_streaming(self, model: BaseChatModel) -> None: super().test_usage_metadata_streaming(model) @pytest.mark.xfail(reason="Can't handle AIMessage with empty content.") - def test_tool_message_error_status(self, model: BaseChatModel) -> None: - super().test_tool_message_error_status(model) + def test_tool_message_error_status( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_tool_message_error_status(model, my_adder_tool) @pytest.mark.xfail(reason="Can't handle AIMessage with empty content.") - def test_structured_few_shot_examples(self, model: BaseChatModel) -> None: - super().test_structured_few_shot_examples(model) + def test_structured_few_shot_examples( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_structured_few_shot_examples(model, my_adder_tool) @pytest.mark.xfail(reason="Can't handle AIMessage with empty content.") - def test_tool_message_histories_string_content(self, model: BaseChatModel) -> None: - super().test_tool_message_histories_string_content(model) + def test_tool_message_histories_string_content( + self, model: BaseChatModel, my_adder_tool: BaseTool + ) -> None: + super().test_tool_message_histories_string_content(model, my_adder_tool) From 80a88f8f045408c11b5605c254bdc23c1536daef Mon Sep 17 00:00:00 2001 From: ccurme Date: Fri, 6 Dec 2024 19:00:14 -0500 Subject: [PATCH 040/157] tests[patch]: update API ref for chat models (#28594) --- .../how_to/integrations/standard_tests.ipynb | 4 +- .../integration_tests/chat_models.py | 27 ++++++--- .../langchain_tests/unit_tests/chat_models.py | 56 ++++++++++--------- 3 files changed, 52 insertions(+), 35 deletions(-) diff --git a/docs/docs/contributing/how_to/integrations/standard_tests.ipynb b/docs/docs/contributing/how_to/integrations/standard_tests.ipynb index 46b20e24fa8d6..c567393d95b84 100644 --- a/docs/docs/contributing/how_to/integrations/standard_tests.ipynb +++ b/docs/docs/contributing/how_to/integrations/standard_tests.ipynb @@ -230,7 +230,9 @@ "\n", "Tests for \"optional\" capabilities are controlled via a set of properties that can be overridden on the test model subclass.\n", "\n", - "You can see the entire list of properties in the API reference [here](https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.chat_models.ChatModelTests.html). These properties are shared by both unit and integration tests.\n", + "You can see the entire list of properties in the API references for\n", + "[unit tests](https://python.langchain.com/api_reference/standard_tests/unit_tests/langchain_tests.unit_tests.chat_models.ChatModelUnitTests.html)\n", + "and [integration tests](https://python.langchain.com/api_reference/standard_tests/integration_tests/langchain_tests.integration_tests.chat_models.ChatModelIntegrationTests.html).\n", "\n", "For example, to enable integration tests for image inputs, we can implement\n", "\n", diff --git a/libs/standard-tests/langchain_tests/integration_tests/chat_models.py b/libs/standard-tests/langchain_tests/integration_tests/chat_models.py index 0dd5334cc4867..7a787563b267b 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/chat_models.py +++ b/libs/standard-tests/langchain_tests/integration_tests/chat_models.py @@ -145,6 +145,14 @@ def chat_model_params(self) -> dict: By default, this is determined by whether the chat model's `bind_tools` method is overridden. It typically does not need to be overridden on the test class. + Example override: + + .. code-block:: python + + @property + def has_tool_calling(self) -> bool: + return True + .. dropdown:: tool_choice_value Value to use for tool choice when used in tests. @@ -308,7 +316,7 @@ def supports_image_tool_message(self) -> bool: @property def standard_chat_model_params(self) -> dict: - """:meta private:""" + """:private:""" return {} def test_invoke(self, model: BaseChatModel) -> None: @@ -1323,8 +1331,8 @@ def has_tool_calling(self) -> bool: .. code-block:: python @pytest.mark.xfail(reason=("Not implemented.")) - def test_tool_message_histories_string_content(self, model: BaseChatModel) -> None: - super().test_tool_message_histories_string_content(model) + def test_tool_message_histories_string_content(self, *args: Any) -> None: + super().test_tool_message_histories_string_content(*args) """ # noqa: E501 if not self.has_tool_calling: pytest.skip("Test requires tool calling.") @@ -1407,8 +1415,8 @@ def has_tool_calling(self) -> bool: .. code-block:: python @pytest.mark.xfail(reason=("Not implemented.")) - def test_tool_message_histories_list_content(self, model: BaseChatModel) -> None: - super().test_tool_message_histories_list_content(model) + def test_tool_message_histories_list_content(self, *args: Any) -> None: + super().test_tool_message_histories_list_content(*args) """ # noqa: E501 if not self.has_tool_calling: pytest.skip("Test requires tool calling.") @@ -1489,8 +1497,8 @@ def has_tool_calling(self) -> bool: .. code-block:: python @pytest.mark.xfail(reason=("Not implemented.")) - def test_structured_few_shot_examples(self, model: BaseChatModel) -> None: - super().test_structured_few_shot_examples(model) + def test_structured_few_shot_examples(self, *args: Any) -> None: + super().test_structured_few_shot_examples(*args) """ # noqa: E501 if not self.has_tool_calling: pytest.skip("Test requires tool calling.") @@ -1852,16 +1860,21 @@ def test_message_with_name(self, model: BaseChatModel) -> None: assert len(result.content) > 0 def invoke_with_audio_input(self, *, stream: bool = False) -> AIMessage: + """:private:""" raise NotImplementedError() def invoke_with_audio_output(self, *, stream: bool = False) -> AIMessage: + """:private:""" raise NotImplementedError() def invoke_with_reasoning_output(self, *, stream: bool = False) -> AIMessage: + """:private:""" raise NotImplementedError() def invoke_with_cache_read_input(self, *, stream: bool = False) -> AIMessage: + """:private:""" raise NotImplementedError() def invoke_with_cache_creation_input(self, *, stream: bool = False) -> AIMessage: + """:private:""" raise NotImplementedError() diff --git a/libs/standard-tests/langchain_tests/unit_tests/chat_models.py b/libs/standard-tests/langchain_tests/unit_tests/chat_models.py index 19225c1f2a6f6..f698f658d08c9 100644 --- a/libs/standard-tests/langchain_tests/unit_tests/chat_models.py +++ b/libs/standard-tests/langchain_tests/unit_tests/chat_models.py @@ -77,17 +77,17 @@ class ChatModelTests(BaseStandardTests): @property @abstractmethod def chat_model_class(self) -> Type[BaseChatModel]: - """The chat model class to test, e.g., `ChatParrotLink`.""" + """The chat model class to test, e.g., ``ChatParrotLink``.""" ... @property def chat_model_params(self) -> dict: - """Initialization parameters for the chat mobdel.""" + """Initialization parameters for the chat model.""" return {} @property def standard_chat_model_params(self) -> dict: - """:meta private:""" + """:private:""" return { "temperature": 0, "max_tokens": 100, @@ -98,8 +98,7 @@ def standard_chat_model_params(self) -> dict: @pytest.fixture def model(self) -> BaseChatModel: - """Fixture that returns an instance of the chat model. Should not be - overridden.""" + """:private:""" return self.chat_model_class( **{**self.standard_chat_model_params, **self.chat_model_params} ) @@ -115,18 +114,17 @@ def my_adder_tool(a: int, b: int) -> int: @property def has_tool_calling(self) -> bool: - """Boolean property indicating whether the model supports tool calling.""" + """(bool) whether the model supports tool calling.""" return self.chat_model_class.bind_tools is not BaseChatModel.bind_tools @property def tool_choice_value(self) -> Optional[str]: - """Value to use for tool choice when used in tests.""" + """(None or str) to use for tool choice when used in tests.""" return None @property def has_structured_output(self) -> bool: - """Boolean property indicating whether the chat model supports structured - output.""" + """(bool) whether the chat model supports structured output.""" return ( self.chat_model_class.with_structured_output is not BaseChatModel.with_structured_output @@ -134,32 +132,31 @@ def has_structured_output(self) -> bool: @property def supports_image_inputs(self) -> bool: - """Boolean property indicating whether the chat model supports image inputs. - Defaults to ``False``.""" + """(bool) whether the chat model supports image inputs, defaults to + ``False``.""" return False @property def supports_video_inputs(self) -> bool: - """Boolean property indicating whether the chat model supports image inputs. - Defaults to ``False``. No current tests are written for this feature.""" + """(bool) whether the chat model supports video inputs, efaults to ``False``. + No current tests are written for this feature.""" return False @property def returns_usage_metadata(self) -> bool: - """Boolean property indicating whether the chat model returns usage metadata - on invoke and streaming responses.""" + """(bool) whether the chat model returns usage metadata on invoke and streaming + responses.""" return True @property def supports_anthropic_inputs(self) -> bool: - """Boolean property indicating whether the chat model supports Anthropic-style - inputs.""" + """(bool) whether the chat model supports Anthropic-style inputs.""" return False @property def supports_image_tool_message(self) -> bool: - """Boolean property indicating whether the chat model supports ToolMessages - that include image content.""" + """(bool) whether the chat model supports ToolMessages that include image + content.""" return False @property @@ -177,9 +174,8 @@ def supported_usage_metadata_details( ] ], ]: - """Property controlling what usage metadata details are emitted in both invoke - and stream. Only needs to be overridden if these details are returned by the - model.""" + """(dict) what usage metadata details are emitted in invoke and stream. Only + needs to be overridden if these details are returned by the model.""" return {"invoke": [], "stream": []} @@ -250,6 +246,14 @@ def chat_model_params(self) -> dict: By default, this is determined by whether the chat model's `bind_tools` method is overridden. It typically does not need to be overridden on the test class. + Example override: + + .. code-block:: python + + @property + def has_tool_calling(self) -> bool: + return True + .. dropdown:: tool_choice_value Value to use for tool choice when used in tests. @@ -445,17 +449,15 @@ def init_from_env_params(self) -> Tuple[dict, dict, dict]: @property def standard_chat_model_params(self) -> dict: - """:meta private:""" + """:private:""" params = super().standard_chat_model_params params["api_key"] = "test" return params @property def init_from_env_params(self) -> Tuple[dict, dict, dict]: - """This property is used in unit tests to test initialization from environment - variables. It should return a tuple of three dictionaries that specify the - environment variables, additional initialization args, and expected instance - attributes to check.""" + """(tuple) environment variables, additional initialization args, and expected + instance attributes for testing initialization from environment variables.""" return {}, {}, {} def test_init(self) -> None: From 4a7dc6ec4cf2639232b7ed472d03cfc0baee92fd Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 16:05:04 -0800 Subject: [PATCH 041/157] standard-tests: release 0.3.6 (#28599) --- libs/standard-tests/poetry.lock | 76 +++++++++++++++++++++++++++--- libs/standard-tests/pyproject.toml | 4 +- 2 files changed, 72 insertions(+), 8 deletions(-) diff --git a/libs/standard-tests/poetry.lock b/libs/standard-tests/poetry.lock index 3890a88ea34dd..8f814f087b377 100644 --- a/libs/standard-tests/poetry.lock +++ b/libs/standard-tests/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" @@ -234,13 +234,13 @@ trio = ["trio (>=0.22.0,<1.0)"] [[package]] name = "httpx" -version = "0.28.0" +version = "0.28.1" description = "The next generation HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpx-0.28.0-py3-none-any.whl", hash = "sha256:dc0b419a0cfeb6e8b34e85167c0da2671206f5095f1baa9663d23bcfd6b535fc"}, - {file = "httpx-0.28.0.tar.gz", hash = "sha256:0858d3bab51ba7e386637f22a61d8ccddaeec5f3fe4209da3a6168dbb91573e0"}, + {file = "httpx-0.28.1-py3-none-any.whl", hash = "sha256:d909fcccc110f8c7faf814ca82a9a4d816bc5a6dbfea25d6591d6985b8ba59ad"}, + {file = "httpx-0.28.1.tar.gz", hash = "sha256:75e98c5f16b0f35b567856f597f06ff2270a374470a5c2392242528e3e3e42fc"}, ] [package.dependencies] @@ -308,7 +308,7 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.21" +version = "0.3.22" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.9,<4.0" @@ 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integrations." authors = [] license = "MIT" @@ -30,8 +30,8 @@ ignore-words-list = "momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogy [tool.poetry.dependencies] python = ">=3.9,<4.0" -langchain-core = "^0.3.21" -langchain = "^0.3.8" +langchain-core = "^0.3.22" +langchain = "^0.3.10" SQLAlchemy = ">=1.4,<3" requests = "^2" PyYAML = ">=5.3" From a32035d17dbd526d6215f56f1ae9c9867d4f738e Mon Sep 17 00:00:00 2001 From: Ikko Eltociear Ashimine Date: Sat, 7 Dec 2024 09:09:48 +0900 Subject: [PATCH 043/157] docs: update uptrain.ipynb (#28561) evluate -> evaluate --- docs/docs/integrations/callbacks/uptrain.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/docs/integrations/callbacks/uptrain.ipynb b/docs/docs/integrations/callbacks/uptrain.ipynb index 7dcf97c517517..51619215d09a0 100644 --- a/docs/docs/integrations/callbacks/uptrain.ipynb +++ b/docs/docs/integrations/callbacks/uptrain.ipynb @@ -336,7 +336,7 @@ "\n", "The **MultiQueryRetriever** is used to tackle the problem that the RAG pipeline might not return the best set of documents based on the query. It generates multiple queries that mean the same as the original query and then fetches documents for each.\n", "\n", - "To evluate this retriever, UpTrain will run the following evaluation:\n", + "To evaluate this retriever, UpTrain will run the following evaluation:\n", "- **[Multi Query Accuracy](https://docs.uptrain.ai/predefined-evaluations/query-quality/multi-query-accuracy)**: Checks if the multi-queries generated mean the same as the original query." ] }, From d801c6ffc789c89e3bb763e5ca00d64af903f059 Mon Sep 17 00:00:00 2001 From: ccurme Date: Fri, 6 Dec 2024 19:13:04 -0500 Subject: [PATCH 044/157] tests[patch]: nits (#28601) --- libs/standard-tests/langchain_tests/__init__.py | 2 +- .../langchain_tests/integration_tests/vectorstores.py | 2 +- libs/standard-tests/langchain_tests/unit_tests/chat_models.py | 2 ++ 3 files changed, 4 insertions(+), 2 deletions(-) diff --git a/libs/standard-tests/langchain_tests/__init__.py b/libs/standard-tests/langchain_tests/__init__.py index 1ebd42cf78968..0f41b67980ccc 100644 --- a/libs/standard-tests/langchain_tests/__init__.py +++ b/libs/standard-tests/langchain_tests/__init__.py @@ -3,5 +3,5 @@ To learn how to use these classes, see the `Integration standard testing `_ -guide +guide. """ diff --git a/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py b/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py index 71ec7d8bfbab1..c043023f3ac48 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py +++ b/libs/standard-tests/langchain_tests/integration_tests/vectorstores.py @@ -15,7 +15,7 @@ class VectorStoreIntegrationTests(BaseStandardTests): - """Base class for checking the read-write API of a vector store. + """Base class for vector store integration tests. Implementers should subclass this test suite and provide a fixture that returns an empty vector store for each test. diff --git a/libs/standard-tests/langchain_tests/unit_tests/chat_models.py b/libs/standard-tests/langchain_tests/unit_tests/chat_models.py index f698f658d08c9..9d3b20de4ceb9 100644 --- a/libs/standard-tests/langchain_tests/unit_tests/chat_models.py +++ b/libs/standard-tests/langchain_tests/unit_tests/chat_models.py @@ -105,6 +105,8 @@ def model(self) -> BaseChatModel: @pytest.fixture def my_adder_tool(self) -> BaseTool: + """:private:""" + @tool def my_adder_tool(a: int, b: int) -> int: """Takes two integers, a and b, and returns their sum.""" From 5e8553c31ac30042c91c7f4a903b9b3b996cb4b1 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 16:32:19 -0800 Subject: [PATCH 045/157] standard-tests: retriever docstrings (#28596) --- libs/standard-tests/langchain_tests/base.py | 2 + .../integration_tests/retrievers.py | 58 ++++++++++++++++++- 2 files changed, 57 insertions(+), 3 deletions(-) diff --git a/libs/standard-tests/langchain_tests/base.py b/libs/standard-tests/langchain_tests/base.py index 7c01639db5114..df99a39b71d62 100644 --- a/libs/standard-tests/langchain_tests/base.py +++ b/libs/standard-tests/langchain_tests/base.py @@ -10,6 +10,8 @@ class BaseStandardTests(ABC): def test_no_overrides_DO_NOT_OVERRIDE(self) -> None: """ Test that no standard tests are overridden. + + :private: """ # find path to standard test implementations comparison_class = None diff --git a/libs/standard-tests/langchain_tests/integration_tests/retrievers.py b/libs/standard-tests/langchain_tests/integration_tests/retrievers.py index fa23d26674256..72425f30c7cab 100644 --- a/libs/standard-tests/langchain_tests/integration_tests/retrievers.py +++ b/libs/standard-tests/langchain_tests/integration_tests/retrievers.py @@ -15,27 +15,52 @@ class RetrieversIntegrationTests(BaseStandardTests): @property @abstractmethod - def retriever_constructor(self) -> Type[BaseRetriever]: ... + def retriever_constructor(self) -> Type[BaseRetriever]: + """ + A BaseRetriever subclass to be tested. + """ + ... @property def retriever_constructor_params(self) -> dict: + """ + Returns a dictionary of parameters to pass to the retriever constructor. + """ return {} @property @abstractmethod def retriever_query_example(self) -> str: """ - Returns a dictionary representing the "args" of an example retriever call. + Returns a str representing the "query" of an example retriever call. """ ... @pytest.fixture def retriever(self) -> BaseRetriever: + """ + :private: + """ return self.retriever_constructor(**self.retriever_constructor_params) def test_k_constructor_param(self) -> None: """ - Test that the retriever constructor accepts a k parameter. + Test that the retriever constructor accepts a k parameter, representing + the number of documents to return. + + .. dropdown:: Troubleshooting + + If this test fails, either the retriever constructor does not accept a k + parameter, or the retriever does not return the correct number of documents + (`k`) when it is set. + + For example, a retriever like + + .. code-block:: python + + MyRetriever(k=3).invoke("query") + + should return 3 documents when invoked with a query. """ params = { k: v for k, v in self.retriever_constructor_params.items() if k != "k" @@ -53,6 +78,24 @@ def test_k_constructor_param(self) -> None: assert all(isinstance(doc, Document) for doc in result_1) def test_invoke_with_k_kwarg(self, retriever: BaseRetriever) -> None: + """ + Test that the invoke method accepts a k parameter, representing the number of + documents to return. + + .. dropdown:: Troubleshooting + + If this test fails, the retriever's invoke method does not accept a k + parameter, or the retriever does not return the correct number of documents + (`k`) when it is set. + + For example, a retriever like + + .. code-block:: python + + MyRetriever().invoke("query", k=3) + + should return 3 documents when invoked with a query. + """ result_1 = retriever.invoke(self.retriever_query_example, k=1) assert len(result_1) == 1 assert all(isinstance(doc, Document) for doc in result_1) @@ -65,6 +108,12 @@ def test_invoke_returns_documents(self, retriever: BaseRetriever) -> None: """ If invoked with the example params, the retriever should return a list of Documents. + + .. dropdown:: Troubleshooting + + If this test fails, the retriever's invoke method does not return a list of + `langchain_core.document.Document` objects. Please confirm that your + `_get_relevant_documents` method returns a list of `Document` objects. """ result = retriever.invoke(self.retriever_query_example) @@ -75,6 +124,9 @@ async def test_ainvoke_returns_documents(self, retriever: BaseRetriever) -> None """ If ainvoked with the example params, the retriever should return a list of Documents. + + See :meth:`test_invoke_returns_documents` for more information on + troubleshooting. """ result = await retriever.ainvoke(self.retriever_query_example) From 9b848491c8ff0731aaf7d0706da19782680eb5a2 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Fri, 6 Dec 2024 16:36:55 -0800 Subject: [PATCH 046/157] docs: tool, retriever contributing docs (#28602) --- .../how_to/integrations/index.mdx | 3 +- .../how_to/integrations/package.mdx | 98 +++++++++++++++++++ 2 files changed, 100 insertions(+), 1 deletion(-) diff --git a/docs/docs/contributing/how_to/integrations/index.mdx b/docs/docs/contributing/how_to/integrations/index.mdx index d8cdf2788c088..63b09faa70edb 100644 --- a/docs/docs/contributing/how_to/integrations/index.mdx +++ b/docs/docs/contributing/how_to/integrations/index.mdx @@ -1,4 +1,5 @@ --- +pagination_prev: null pagination_next: contributing/how_to/integrations/package --- @@ -37,7 +38,6 @@ While any component can be integrated into LangChain, there are specific types o
  • Chat Models
  • Tools/Toolkits
  • Retrievers
    • -
  • Document Loaders
  • Vector Stores
  • Embedding Models
    • @@ -45,6 +45,7 @@ While any component can be integrated into LangChain, there are specific types o