diff --git a/libs/partners/together/.gitignore b/libs/partners/together/.gitignore deleted file mode 100644 index bee8a64b79a..00000000000 --- a/libs/partners/together/.gitignore +++ /dev/null @@ -1 +0,0 @@ -__pycache__ diff --git a/libs/partners/together/LICENSE b/libs/partners/together/LICENSE deleted file mode 100644 index fc0602feecd..00000000000 --- a/libs/partners/together/LICENSE +++ /dev/null @@ -1,21 +0,0 @@ -MIT License - -Copyright (c) 2024 LangChain, Inc. - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in all -copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. diff --git a/libs/partners/together/Makefile b/libs/partners/together/Makefile deleted file mode 100644 index c2a1173ca0e..00000000000 --- a/libs/partners/together/Makefile +++ /dev/null @@ -1,56 +0,0 @@ -.PHONY: all format lint test tests integration_tests docker_tests help extended_tests - -# Default target executed when no arguments are given to make. -all: help - -# Define a variable for the test file path. -TEST_FILE ?= tests/unit_tests/ - -integration_test integration_tests: TEST_FILE=tests/integration_tests/ - -test tests integration_test integration_tests: - poetry run pytest $(TEST_FILE) - -###################### -# LINTING AND FORMATTING -###################### - -# Define a variable for Python and notebook files. -PYTHON_FILES=. -MYPY_CACHE=.mypy_cache -lint format: PYTHON_FILES=. -lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/partners/together --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$') -lint_package: PYTHON_FILES=langchain_together -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) - -spell_check: - poetry run codespell --toml pyproject.toml - -spell_fix: - poetry run codespell --toml pyproject.toml -w - -check_imports: $(shell find langchain_together -name '*.py') - poetry run python ./scripts/check_imports.py $^ - -###################### -# HELP -###################### - -help: - @echo '----' - @echo 'check_imports - check imports' - @echo 'format - run code formatters' - @echo 'lint - run linters' - @echo 'test - run unit tests' - @echo 'tests - run unit tests' - @echo 'test TEST_FILE= - run all tests in file' diff --git a/libs/partners/together/README.md b/libs/partners/together/README.md index 219589533a1..92284c00420 100644 --- a/libs/partners/together/README.md +++ b/libs/partners/together/README.md @@ -1,28 +1,3 @@ -# langchain-together +This package has moved! -This package contains the LangChain integrations for [Together AI](https://www.together.ai/) through their [APIs](https://docs.together.ai/). - -## Installation and Setup - -- Install the LangChain partner package - -```bash -pip install -U langchain-together -``` - -- Get your Together AI api key from the [Together Dashboard](https://api.together.ai/settings/api-keys) and set it as an environment variable (`TOGETHER_API_KEY`) - -## Chat Completions - -This package contains the `ChatTogether` class, which is the recommended way to interface with Together AI chat models. - -ADD USAGE EXAMPLE HERE. -Can we add this in the langchain docs? - -NEED to add image endpoint + completions endpoint as well - -## Embeddings - -See a [usage example](https://python.langchain.com/docs/integrations/text_embedding/together/) - -Use `togethercomputer/m2-bert-80M-8k-retrieval` as the default model for embeddings. +https://github.com/langchain-ai/langchain-together/tree/main/libs/together \ No newline at end of file diff --git a/libs/partners/together/langchain_together/__init__.py b/libs/partners/together/langchain_together/__init__.py deleted file mode 100644 index f4a23d35c0f..00000000000 --- a/libs/partners/together/langchain_together/__init__.py +++ /dev/null @@ -1,7 +0,0 @@ -"""This package provides the Together integration for LangChain.""" - -from langchain_together.chat_models import ChatTogether -from langchain_together.embeddings import TogetherEmbeddings -from langchain_together.llms import Together - -__all__ = ["ChatTogether", "Together", "TogetherEmbeddings"] diff --git a/libs/partners/together/langchain_together/chat_models.py b/libs/partners/together/langchain_together/chat_models.py deleted file mode 100644 index 76d79d8d29d..00000000000 --- a/libs/partners/together/langchain_together/chat_models.py +++ /dev/null @@ -1,364 +0,0 @@ -"""Wrapper around Together AI's Chat Completions API.""" - -from typing import ( - Any, - Dict, - List, - Optional, -) - -import openai -from langchain_core.language_models.chat_models import LangSmithParams -from langchain_core.pydantic_v1 import Field, SecretStr, root_validator -from langchain_core.utils import ( - from_env, - secret_from_env, -) -from langchain_openai.chat_models.base import BaseChatOpenAI - - -class ChatTogether(BaseChatOpenAI): - r"""ChatTogether chat model. - - Setup: - Install ``langchain-together`` and set environment variable ``TOGETHER_API_KEY``. - - .. code-block:: bash - - pip install -U langchain-together - export TOGETHER_API_KEY="your-api-key" - - - Key init args — completion params: - model: str - Name of model to use. - temperature: float - Sampling temperature. - max_tokens: Optional[int] - Max number of tokens to generate. - logprobs: Optional[bool] - Whether to return logprobs. - - Key init args — client params: - timeout: Union[float, Tuple[float, float], Any, None] - Timeout for requests. - max_retries: int - Max number of retries. - api_key: Optional[str] - Together API key. If not passed in will be read from env var OPENAI_API_KEY. - - Instantiate: - .. code-block:: python - - from langhcain_together import ChatTogether - - llm = ChatTogether( - model="meta-llama/Llama-3-70b-chat-hf", - temperature=0, - max_tokens=None, - timeout=None, - max_retries=2, - # api_key="...", - # other params... - ) - - Invoke: - .. code-block:: python - - messages = [ - ( - "system", - "You are a helpful translator. Translate the user sentence to French.", - ), - ("human", "I love programming."), - ] - llm.invoke(messages) - - .. code-block:: python - - AIMessage( - content="J'adore la programmation.", - response_metadata={ - 'token_usage': {'completion_tokens': 9, 'prompt_tokens': 32, 'total_tokens': 41}, - 'model_name': 'meta-llama/Llama-3-70b-chat-hf', - 'system_fingerprint': None, - 'finish_reason': 'stop', - 'logprobs': None - }, - id='run-168dceca-3b8b-4283-94e3-4c739dbc1525-0', - usage_metadata={'input_tokens': 32, 'output_tokens': 9, 'total_tokens': 41}) - - Stream: - .. code-block:: python - - for chunk in llm.stream(messages): - print(chunk) - - .. code-block:: python - - content='J' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' - content="'" id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' - content='ad' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' - content='ore' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' - content=' la' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' - content=' programm' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' - content='ation' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' - content='.' id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' - content='' response_metadata={'finish_reason': 'stop', 'model_name': 'meta-llama/Llama-3-70b-chat-hf'} id='run-1bc996b5-293f-4114-96a1-e0f755c05eb9' - - - Async: - .. code-block:: python - - await llm.ainvoke(messages) - - # stream: - # async for chunk in (await llm.astream(messages)) - - # batch: - # await llm.abatch([messages]) - - .. code-block:: python - - AIMessage( - content="J'adore la programmation.", - response_metadata={ - 'token_usage': {'completion_tokens': 9, 'prompt_tokens': 32, 'total_tokens': 41}, - 'model_name': 'meta-llama/Llama-3-70b-chat-hf', - 'system_fingerprint': None, - 'finish_reason': 'stop', - 'logprobs': None - }, - id='run-09371a11-7f72-4c53-8e7c-9de5c238b34c-0', - usage_metadata={'input_tokens': 32, 'output_tokens': 9, 'total_tokens': 41}) - - Tool calling: - .. code-block:: python - - from langchain_core.pydantic_v1 import BaseModel, Field - - # Only certain models support tool calling, check the together website to confirm compatibility - llm = ChatTogether(model="mistralai/Mixtral-8x7B-Instruct-v0.1") - - class GetWeather(BaseModel): - '''Get the current weather in a given location''' - - location: str = Field( - ..., description="The city and state, e.g. San Francisco, CA" - ) - - class GetPopulation(BaseModel): - '''Get the current population in a given location''' - - location: str = Field( - ..., description="The city and state, e.g. San Francisco, CA" - ) - - llm_with_tools = llm.bind_tools([GetWeather, GetPopulation]) - ai_msg = llm_with_tools.invoke( - "Which city is bigger: LA or NY?" - ) - ai_msg.tool_calls - - - .. code-block:: python - - [ - { - 'name': 'GetPopulation', - 'args': {'location': 'NY'}, - 'id': 'call_m5tstyn2004pre9bfuxvom8x', - 'type': 'tool_call' - }, - { - 'name': 'GetPopulation', - 'args': {'location': 'LA'}, - 'id': 'call_0vjgq455gq1av5sp9eb1pw6a', - 'type': 'tool_call' - } - ] - - Structured output: - .. code-block:: python - - from typing import Optional - - from langchain_core.pydantic_v1 import BaseModel, Field - - - class Joke(BaseModel): - '''Joke to tell user.''' - - setup: str = Field(description="The setup of the joke") - punchline: str = Field(description="The punchline to the joke") - rating: Optional[int] = Field(description="How funny the joke is, from 1 to 10") - - - structured_llm = llm.with_structured_output(Joke) - structured_llm.invoke("Tell me a joke about cats") - - .. code-block:: python - - Joke( - setup='Why was the cat sitting on the computer?', - punchline='To keep an eye on the mouse!', - rating=7 - ) - - JSON mode: - .. code-block:: python - - json_llm = llm.bind(response_format={"type": "json_object"}) - ai_msg = json_llm.invoke( - "Return a JSON object with key 'random_ints' and a value of 10 random ints in [0-99]" - ) - ai_msg.content - - .. code-block:: python - - ' {\\n"random_ints": [\\n13,\\n54,\\n78,\\n45,\\n67,\\n90,\\n11,\\n29,\\n84,\\n33\\n]\\n}' - - Token usage: - .. code-block:: python - - ai_msg = llm.invoke(messages) - ai_msg.usage_metadata - - .. code-block:: python - - {'input_tokens': 37, 'output_tokens': 6, 'total_tokens': 43} - - Logprobs: - .. code-block:: python - - logprobs_llm = llm.bind(logprobs=True) - messages=[("human","Say Hello World! Do not return anything else.")] - ai_msg = logprobs_llm.invoke(messages) - ai_msg.response_metadata["logprobs"] - - .. code-block:: python - - { - 'content': None, - 'token_ids': [22557, 3304, 28808, 2], - 'tokens': [' Hello', ' World', '!', ''], - 'token_logprobs': [-4.7683716e-06, -5.9604645e-07, 0, -0.057373047] - } - - - Response metadata - .. code-block:: python - - ai_msg = llm.invoke(messages) - ai_msg.response_metadata - - .. code-block:: python - - { - 'token_usage': { - 'completion_tokens': 4, - 'prompt_tokens': 19, - 'total_tokens': 23 - }, - 'model_name': 'mistralai/Mixtral-8x7B-Instruct-v0.1', - 'system_fingerprint': None, - 'finish_reason': 'eos', - 'logprobs': None - } - - """ # noqa: E501 - - @property - def lc_secrets(self) -> Dict[str, str]: - """A map of constructor argument names to secret ids. - - For example, - {"together_api_key": "TOGETHER_API_KEY"} - """ - return {"together_api_key": "TOGETHER_API_KEY"} - - @classmethod - def get_lc_namespace(cls) -> List[str]: - """Get the namespace of the langchain object.""" - return ["langchain", "chat_models", "together"] - - @property - def lc_attributes(self) -> Dict[str, Any]: - """List of attribute names that should be included in the serialized kwargs. - - These attributes must be accepted by the constructor. - """ - attributes: Dict[str, Any] = {} - - if self.together_api_base: - attributes["together_api_base"] = self.together_api_base - - return attributes - - @property - def _llm_type(self) -> str: - """Return type of chat model.""" - return "together-chat" - - def _get_ls_params( - self, stop: Optional[List[str]] = None, **kwargs: Any - ) -> LangSmithParams: - """Get the parameters used to invoke the model.""" - params = super()._get_ls_params(stop=stop, **kwargs) - params["ls_provider"] = "together" - return params - - model_name: str = Field(default="meta-llama/Llama-3-8b-chat-hf", alias="model") - """Model name to use.""" - together_api_key: Optional[SecretStr] = Field( - alias="api_key", - default_factory=secret_from_env("TOGETHER_API_KEY", default=None), - ) - """Together AI API key. - - Automatically read from env variable `TOGETHER_API_KEY` if not provided. - """ - together_api_base: str = Field( - default_factory=from_env( - "TOGETHER_API_BASE", default="https://api.together.xyz/v1/" - ), - alias="base_url", - ) - - class Config: - """Pydantic config.""" - - allow_population_by_field_name = True - - @root_validator(pre=False, skip_on_failure=True) - def validate_environment(cls, values: Dict) -> Dict: - """Validate that api key and python package exists in environment.""" - if values["n"] < 1: - raise ValueError("n must be at least 1.") - if values["n"] > 1 and values["streaming"]: - raise ValueError("n must be 1 when streaming.") - - client_params = { - "api_key": ( - values["together_api_key"].get_secret_value() - if values["together_api_key"] - else None - ), - "base_url": values["together_api_base"], - "timeout": values["request_timeout"], - "max_retries": values["max_retries"], - "default_headers": values["default_headers"], - "default_query": values["default_query"], - } - - if not values.get("client"): - sync_specific = {"http_client": values["http_client"]} - values["client"] = openai.OpenAI( - **client_params, **sync_specific - ).chat.completions - if not values.get("async_client"): - async_specific = {"http_client": values["http_async_client"]} - values["async_client"] = openai.AsyncOpenAI( - **client_params, **async_specific - ).chat.completions - return values diff --git a/libs/partners/together/langchain_together/embeddings.py b/libs/partners/together/langchain_together/embeddings.py deleted file mode 100644 index 80961b3b4af..00000000000 --- a/libs/partners/together/langchain_together/embeddings.py +++ /dev/null @@ -1,325 +0,0 @@ -"""Wrapper around Together AI's Embeddings API.""" - -import logging -import warnings -from typing import ( - Any, - Dict, - List, - Literal, - Mapping, - Optional, - Sequence, - Set, - Tuple, - Union, -) - -import openai -from langchain_core.embeddings import Embeddings -from langchain_core.pydantic_v1 import ( - BaseModel, - Field, - SecretStr, - root_validator, -) -from langchain_core.utils import ( - from_env, - get_pydantic_field_names, - secret_from_env, -) - -logger = logging.getLogger(__name__) - - -class TogetherEmbeddings(BaseModel, Embeddings): - """Together embedding model integration. - - Setup: - Install ``langchain_together`` and set environment variable - ``TOGETHER_API_KEY``. - - .. code-block:: bash - - pip install -U langchain_together - export TOGETHER_API_KEY="your-api-key" - - Key init args — completion params: - model: str - Name of Together model to use. - - Key init args — client params: - api_key: Optional[SecretStr] - - See full list of supported init args and their descriptions in the params section. - - Instantiate: - .. code-block:: python - - from __module_name__ import TogetherEmbeddings - - embed = TogetherEmbeddings( - model="togethercomputer/m2-bert-80M-8k-retrieval", - # api_key="...", - # other params... - ) - - Embed single text: - .. code-block:: python - - input_text = "The meaning of life is 42" - vector = embed.embed_query(input_text) - print(vector[:3]) - - .. code-block:: python - - [-0.024603435769677162, -0.007543657906353474, 0.0039630369283258915] - - Embed multiple texts: - .. code-block:: python - - input_texts = ["Document 1...", "Document 2..."] - vectors = embed.embed_documents(input_texts) - print(len(vectors)) - # The first 3 coordinates for the first vector - print(vectors[0][:3]) - - .. code-block:: python - - 2 - [-0.024603435769677162, -0.007543657906353474, 0.0039630369283258915] - - Async: - .. code-block:: python - - vector = await embed.aembed_query(input_text) - print(vector[:3]) - - # multiple: - # await embed.aembed_documents(input_texts) - - .. code-block:: python - - [-0.009100092574954033, 0.005071679595857859, -0.0029193938244134188] - """ - - client: Any = Field(default=None, exclude=True) #: :meta private: - async_client: Any = Field(default=None, exclude=True) #: :meta private: - model: str = "togethercomputer/m2-bert-80M-8k-retrieval" - """Embeddings model name to use. - Instead, use 'togethercomputer/m2-bert-80M-8k-retrieval' for example. - """ - dimensions: Optional[int] = None - """The number of dimensions the resulting output embeddings should have. - - Not yet supported. - """ - together_api_key: Optional[SecretStr] = Field( - alias="api_key", - default_factory=secret_from_env("TOGETHER_API_KEY", default=None), - ) - """Together AI API key. - - Automatically read from env variable `TOGETHER_API_KEY` if not provided. - """ - together_api_base: str = Field( - default_factory=from_env( - "TOGETHER_API_BASE", default="https://api.together.xyz/v1/" - ), - alias="base_url", - ) - """Endpoint URL to use.""" - embedding_ctx_length: int = 4096 - """The maximum number of tokens to embed at once. - - Not yet supported. - """ - allowed_special: Union[Literal["all"], Set[str]] = set() - """Not yet supported.""" - disallowed_special: Union[Literal["all"], Set[str], Sequence[str]] = "all" - """Not yet supported.""" - chunk_size: int = 1000 - """Maximum number of texts to embed in each batch. - - Not yet supported. - """ - max_retries: int = 2 - """Maximum number of retries to make when generating.""" - request_timeout: Optional[Union[float, Tuple[float, float], Any]] = Field( - default=None, alias="timeout" - ) - """Timeout for requests to Together embedding API. Can be float, httpx.Timeout or - None.""" - show_progress_bar: bool = False - """Whether to show a progress bar when embedding. - - Not yet supported. - """ - model_kwargs: Dict[str, Any] = Field(default_factory=dict) - """Holds any model parameters valid for `create` call not explicitly specified.""" - skip_empty: bool = False - """Whether to skip empty strings when embedding or raise an error. - Defaults to not skipping. - - Not yet supported.""" - default_headers: Union[Mapping[str, str], None] = None - default_query: Union[Mapping[str, object], None] = None - # Configure a custom httpx client. See the - # [httpx documentation](https://www.python-httpx.org/api/#client) for more details. - http_client: Union[Any, None] = None - """Optional httpx.Client. Only used for sync invocations. Must specify - http_async_client as well if you'd like a custom client for async invocations. - """ - http_async_client: Union[Any, None] = None - """Optional httpx.AsyncClient. Only used for async invocations. Must specify - http_client as well if you'd like a custom client for sync invocations.""" - - class Config: - """Configuration for this pydantic object.""" - - extra = "forbid" - allow_population_by_field_name = True - - @root_validator(pre=True) - def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]: - """Build extra kwargs from additional params that were passed in.""" - all_required_field_names = get_pydantic_field_names(cls) - extra = values.get("model_kwargs", {}) - for field_name in list(values): - if field_name in extra: - raise ValueError(f"Found {field_name} supplied twice.") - if field_name not in all_required_field_names: - warnings.warn( - f"""WARNING! {field_name} is not default parameter. - {field_name} was transferred to model_kwargs. - Please confirm that {field_name} is what you intended.""" - ) - extra[field_name] = values.pop(field_name) - - invalid_model_kwargs = all_required_field_names.intersection(extra.keys()) - if invalid_model_kwargs: - raise ValueError( - f"Parameters {invalid_model_kwargs} should be specified explicitly. " - f"Instead they were passed in as part of `model_kwargs` parameter." - ) - - values["model_kwargs"] = extra - return values - - @root_validator(pre=False, skip_on_failure=True) - def post_init(cls, values: Dict) -> Dict: - """Logic that will post Pydantic initialization.""" - client_params = { - "api_key": ( - values["together_api_key"].get_secret_value() - if values["together_api_key"] - else None - ), - "base_url": values["together_api_base"], - "timeout": values["request_timeout"], - "max_retries": values["max_retries"], - "default_headers": values["default_headers"], - "default_query": values["default_query"], - } - if not values.get("client"): - sync_specific = ( - {"http_client": values["http_client"]} if values["http_client"] else {} - ) - values["client"] = openai.OpenAI( - **client_params, **sync_specific - ).embeddings - if not values.get("async_client"): - async_specific = ( - {"http_client": values["http_async_client"]} - if values["http_async_client"] - else {} - ) - values["async_client"] = openai.AsyncOpenAI( - **client_params, **async_specific - ).embeddings - return values - - @property - def _invocation_params(self) -> Dict[str, Any]: - params: Dict = {"model": self.model, **self.model_kwargs} - if self.dimensions is not None: - params["dimensions"] = self.dimensions - return params - - def embed_documents(self, texts: List[str]) -> List[List[float]]: - """Embed a list of document texts using passage model. - - Args: - texts: The list of texts to embed. - - Returns: - List of embeddings, one for each text. - """ - embeddings = [] - params = self._invocation_params - params["model"] = params["model"] - - for text in texts: - response = self.client.create(input=text, **params) - - if not isinstance(response, dict): - response = response.model_dump() - embeddings.extend([i["embedding"] for i in response["data"]]) - return embeddings - - def embed_query(self, text: str) -> List[float]: - """Embed query text using query model. - - Args: - text: The text to embed. - - Returns: - Embedding for the text. - """ - params = self._invocation_params - params["model"] = params["model"] - - response = self.client.create(input=text, **params) - - if not isinstance(response, dict): - response = response.model_dump() - return response["data"][0]["embedding"] - - async def aembed_documents(self, texts: List[str]) -> List[List[float]]: - """Embed a list of document texts using passage model asynchronously. - - Args: - texts: The list of texts to embed. - - Returns: - List of embeddings, one for each text. - """ - embeddings = [] - params = self._invocation_params - params["model"] = params["model"] - - for text in texts: - response = await self.async_client.create(input=text, **params) - - if not isinstance(response, dict): - response = response.model_dump() - embeddings.extend([i["embedding"] for i in response["data"]]) - return embeddings - - async def aembed_query(self, text: str) -> List[float]: - """Asynchronous Embed query text using query model. - - Args: - text: The text to embed. - - Returns: - Embedding for the text. - """ - params = self._invocation_params - params["model"] = params["model"] - - response = await self.async_client.create(input=text, **params) - - if not isinstance(response, dict): - response = response.model_dump() - return response["data"][0]["embedding"] diff --git a/libs/partners/together/langchain_together/llms.py b/libs/partners/together/langchain_together/llms.py deleted file mode 100644 index 279fbcaaaf2..00000000000 --- a/libs/partners/together/langchain_together/llms.py +++ /dev/null @@ -1,224 +0,0 @@ -"""Wrapper around Together AI's Completion API.""" - -import logging -import warnings -from typing import Any, Dict, List, Optional - -import requests -from aiohttp import ClientSession -from langchain_core.callbacks import ( - AsyncCallbackManagerForLLMRun, - CallbackManagerForLLMRun, -) -from langchain_core.language_models.llms import LLM -from langchain_core.pydantic_v1 import Field, SecretStr, root_validator -from langchain_core.utils import ( - secret_from_env, -) - -logger = logging.getLogger(__name__) - - -class Together(LLM): - """LLM models from `Together`. - - To use, you'll need an API key which you can find here: - https://api.together.ai/settings/api-keys. This can be passed in as init param - ``together_api_key`` or set as environment variable ``TOGETHER_API_KEY``. - - Together AI API reference: https://docs.together.ai/reference/completions - - Example: - .. code-block:: python - - from langchain_together import Together - - model = Together(model_name="mistralai/Mixtral-8x7B-Instruct-v0.1") - """ - - base_url: str = "https://api.together.xyz/v1/completions" - """Base completions API URL.""" - together_api_key: SecretStr = Field( - alias="api_key", - default_factory=secret_from_env("TOGETHER_API_KEY"), - ) - """Together AI API key. - - Automatically read from env variable `TOGETHER_API_KEY` if not provided. - """ - model: str - """Model name. Available models listed here: - Base Models: https://docs.together.ai/docs/inference-models#language-models - Chat Models: https://docs.together.ai/docs/inference-models#chat-models - """ - temperature: Optional[float] = None - """Model temperature.""" - top_p: Optional[float] = None - """Used to dynamically adjust the number of choices for each predicted token based - on the cumulative probabilities. A value of 1 will always yield the same - output. A temperature less than 1 favors more correctness and is appropriate - for question answering or summarization. A value greater than 1 introduces more - randomness in the output. - """ - top_k: Optional[int] = None - """Used to limit the number of choices for the next predicted word or token. It - specifies the maximum number of tokens to consider at each step, based on their - probability of occurrence. This technique helps to speed up the generation - process and can improve the quality of the generated text by focusing on the - most likely options. - """ - max_tokens: Optional[int] = None - """The maximum number of tokens to generate.""" - repetition_penalty: Optional[float] = None - """A number that controls the diversity of generated text by reducing the - likelihood of repeated sequences. Higher values decrease repetition. - """ - logprobs: Optional[int] = None - """An integer that specifies how many top token log probabilities are included in - the response for each token generation step. - """ - - class Config: - """Configuration for this pydantic object.""" - - extra = "forbid" - allow_population_by_field_name = True - - @root_validator(pre=True) - def validate_environment(cls, values: Dict) -> Dict: - """Validate that api key exists in environment.""" - if values.get("max_tokens") is None: - warnings.warn( - "The completions endpoint, has 'max_tokens' as required argument. " - "The default value is being set to 200 " - "Consider setting this value, when initializing LLM" - ) - values["max_tokens"] = 200 # Default Value - return values - - @property - def _llm_type(self) -> str: - """Return type of model.""" - return "together" - - def _format_output(self, output: dict) -> str: - return output["choices"][0]["text"] - - @property - def default_params(self) -> Dict[str, Any]: - """Return the default parameters for the Together model. - - Returns: - A dictionary containing the default parameters. - """ - return { - "model": self.model, - "temperature": self.temperature, - "top_p": self.top_p, - "top_k": self.top_k, - "max_tokens": self.max_tokens, - "repetition_penalty": self.repetition_penalty, - } - - def _call( - self, - prompt: str, - stop: Optional[List[str]] = None, - run_manager: Optional[CallbackManagerForLLMRun] = None, - **kwargs: Any, - ) -> str: - """Call out to Together's text generation endpoint. - - Args: - prompt: The prompt to pass into the model. - stop: Optional list of stop words to use when generating. - run_manager: The CallbackManager for LLM run, it's not used at the moment. - kwargs: Additional parameters to pass to the model. - - Returns: - The string generated by the model.. - """ - headers = { - "Authorization": f"Bearer {self.together_api_key.get_secret_value()}", - "Content-Type": "application/json", - } - stop_to_use = stop[0] if stop and len(stop) == 1 else stop - payload: Dict[str, Any] = { - **self.default_params, - "prompt": prompt, - "stop": stop_to_use, - **kwargs, - } - - # filter None values to not pass them to the http payload - payload = {k: v for k, v in payload.items() if v is not None} - response = requests.post(url=self.base_url, json=payload, headers=headers) - - if response.status_code >= 500: - raise Exception(f"Together Server: Error {response.status_code}") - elif response.status_code >= 400: - raise ValueError(f"Together received an invalid payload: {response.text}") - elif response.status_code != 200: - raise Exception( - f"Together returned an unexpected response with status " - f"{response.status_code}: {response.text}" - ) - - data = response.json() - - output = self._format_output(data) - - return output - - async def _acall( - self, - prompt: str, - stop: Optional[List[str]] = None, - run_manager: Optional[AsyncCallbackManagerForLLMRun] = None, - **kwargs: Any, - ) -> str: - """Call Together model to get predictions based on the prompt. - - Args: - prompt: The prompt to pass into the model. - stop: Optional list of stop words to use when generating. - run_manager: The CallbackManager for LLM run, it's not used at the moment. - kwargs: Additional parameters to pass to the model. - - Returns: - The string generated by the model. - """ - headers = { - "Authorization": f"Bearer {self.together_api_key.get_secret_value()}", - "Content-Type": "application/json", - } - stop_to_use = stop[0] if stop and len(stop) == 1 else stop - payload: Dict[str, Any] = { - **self.default_params, - "prompt": prompt, - 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-[package.dependencies] -idna = ">=2.0" -multidict = ">=4.0" - -[metadata] -lock-version = "2.0" -python-versions = ">=3.8.1,<4.0" -content-hash = "a1e7ca78b40f3db9a32d3e9f776cc287d374d6eb1d54875b3ce82b72076b88fa" diff --git a/libs/partners/together/pyproject.toml b/libs/partners/together/pyproject.toml deleted file mode 100644 index 51bd0970bda..00000000000 --- a/libs/partners/together/pyproject.toml +++ /dev/null @@ -1,109 +0,0 @@ -[build-system] -requires = [ "poetry-core>=1.0.0",] -build-backend = "poetry.core.masonry.api" - -[tool.poetry] -name = "langchain-together" -version = "0.1.6" -description = "An integration package connecting Together AI and LangChain" -authors = [] -readme = "README.md" -repository = "https://github.com/langchain-ai/langchain" -license = "MIT" - -[tool.mypy] -disallow_untyped_defs = "True" - -[tool.poetry.urls] -"Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/together" -"Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22langchain-together%3D%3D0%22&expanded=true" - -[tool.poetry.dependencies] -python = ">=3.8.1,<4.0" -langchain-core = "^0.2.35" -langchain-openai = "^0.1.16" -requests = "^2" -aiohttp = "^3.9.1" - -[tool.ruff.lint] -select = [ "E", "F", "I", "D",] - -[tool.coverage.run] -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", "asyncio: mark tests as requiring asyncio", "compile: mark placeholder test used to compile integration tests without running them",] -asyncio_mode = "auto" - -[tool.poetry.group.test] -optional = true - -[tool.poetry.group.codespell] -optional = true - -[tool.poetry.group.test_integration] -optional = true - -[tool.poetry.group.lint] -optional = true - -[tool.poetry.group.typing] -optional = true - -[tool.poetry.group.dev] -optional = true - -[tool.ruff.lint.pydocstyle] -convention = "google" - -[tool.ruff.lint.per-file-ignores] -"tests/**" = [ "D",] - -[tool.poetry.group.test.dependencies] -pytest = "^7.3.0" -freezegun = "^1.2.2" -pytest-mock = "^3.10.0" -syrupy = "^4.0.2" -pytest-watcher = "^0.3.4" -pytest-asyncio = "^0.21.1" -docarray = "^0.32.1" - -[tool.poetry.group.codespell.dependencies] -codespell = "^2.2.0" - -[tool.poetry.group.test_integration.dependencies] -[[tool.poetry.group.test_integration.dependencies.numpy]] -version = "^1" -python = "<3.12" - -[[tool.poetry.group.test_integration.dependencies.numpy]] -version = "^1.26.0" -python = ">=3.12" - -[tool.poetry.group.lint.dependencies] -ruff = "^0.5" - -[tool.poetry.group.typing.dependencies] -mypy = "^1.10" -types-requests = "^2" - -[tool.poetry.group.test.dependencies.langchain-openai] -path = "../openai" -develop = true - -[tool.poetry.group.test.dependencies.langchain-core] -path = "../../core" -develop = true - -[tool.poetry.group.test.dependencies.langchain-standard-tests] -path = "../../standard-tests" -develop = true - -[tool.poetry.group.typing.dependencies.langchain-core] -path = "../../core" -develop = true - -[tool.poetry.group.dev.dependencies.langchain-core] -path = "../../core" -develop = true diff --git a/libs/partners/together/scripts/check_imports.py b/libs/partners/together/scripts/check_imports.py deleted file mode 100644 index 620bc296aa8..00000000000 --- a/libs/partners/together/scripts/check_imports.py +++ /dev/null @@ -1,19 +0,0 @@ -"""This module checks if the given python files can be imported without error.""" - -import sys -import traceback -from importlib.machinery import SourceFileLoader - -if __name__ == "__main__": - files = sys.argv[1:] - has_failure = False - for file in files: - try: - SourceFileLoader("x", file).load_module() - except Exception: - has_failure = True - print(file) - traceback.print_exc() - print() - - sys.exit(1 if has_failure else 0) diff --git a/libs/partners/together/scripts/check_pydantic.sh b/libs/partners/together/scripts/check_pydantic.sh deleted file mode 100755 index 06b5bb81ae2..00000000000 --- a/libs/partners/together/scripts/check_pydantic.sh +++ /dev/null @@ -1,27 +0,0 @@ -#!/bin/bash -# -# This script searches for lines starting with "import pydantic" or "from pydantic" -# in tracked files within a Git repository. -# -# Usage: ./scripts/check_pydantic.sh /path/to/repository - -# Check if a path argument is provided -if [ $# -ne 1 ]; then - echo "Usage: $0 /path/to/repository" - exit 1 -fi - -repository_path="$1" - -# Search for lines matching the pattern within the specified repository -result=$(git -C "$repository_path" grep -E '^import pydantic|^from pydantic') - -# Check if any matching lines were found -if [ -n "$result" ]; then - echo "ERROR: The following lines need to be updated:" - echo "$result" - echo "Please replace the code with an import from langchain_core.pydantic_v1." - echo "For example, replace 'from pydantic import BaseModel'" - echo "with 'from langchain_core.pydantic_v1 import BaseModel'" - exit 1 -fi diff --git a/libs/partners/together/scripts/lint_imports.sh b/libs/partners/together/scripts/lint_imports.sh deleted file mode 100755 index 695613c7ba8..00000000000 --- a/libs/partners/together/scripts/lint_imports.sh +++ /dev/null @@ -1,17 +0,0 @@ -#!/bin/bash - -set -eu - -# Initialize a variable to keep track of errors -errors=0 - -# make sure not importing from langchain or langchain_experimental -git --no-pager grep '^from langchain\.' . && errors=$((errors+1)) -git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1)) - -# Decide on an exit status based on the errors -if [ "$errors" -gt 0 ]; then - exit 1 -else - exit 0 -fi diff --git a/libs/partners/together/tests/__init__.py b/libs/partners/together/tests/__init__.py deleted file mode 100644 index e69de29bb2d..00000000000 diff --git a/libs/partners/together/tests/integration_tests/__init__.py b/libs/partners/together/tests/integration_tests/__init__.py deleted file mode 100644 index e69de29bb2d..00000000000 diff --git a/libs/partners/together/tests/integration_tests/test_chat_models.py b/libs/partners/together/tests/integration_tests/test_chat_models.py deleted file mode 100644 index 459e6bb19cc..00000000000 --- a/libs/partners/together/tests/integration_tests/test_chat_models.py +++ /dev/null @@ -1,136 +0,0 @@ -import pytest # type: ignore[import-not-found] -from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage - -from langchain_together import ChatTogether - - -def test_chat_together_model() -> None: - """Test ChatTogether wrapper handles model_name.""" - chat = ChatTogether(model="foo") - assert chat.model_name == "foo" - chat = ChatTogether(model_name="bar") # type: ignore[call-arg] - assert chat.model_name == "bar" - - -def test_chat_together_system_message() -> None: - """Test ChatOpenAI wrapper with system message.""" - chat = ChatTogether(max_tokens=10) - system_message = SystemMessage(content="You are to chat with the user.") - human_message = HumanMessage(content="Hello") - response = chat([system_message, human_message]) - assert isinstance(response, BaseMessage) - assert isinstance(response.content, str) - - -def test_chat_together_llm_output_contains_model_name() -> None: - """Test llm_output contains model_name.""" - chat = ChatTogether(max_tokens=10) - message = HumanMessage(content="Hello") - llm_result = chat.generate([[message]]) - assert llm_result.llm_output is not None - assert llm_result.llm_output["model_name"] == chat.model_name - - -def test_chat_together_streaming_llm_output_contains_model_name() -> None: - """Test llm_output contains model_name.""" - chat = ChatTogether(max_tokens=10, streaming=True) - message = HumanMessage(content="Hello") - llm_result = chat.generate([[message]]) - assert llm_result.llm_output is not None - assert llm_result.llm_output["model_name"] == chat.model_name - - -def test_chat_together_invalid_streaming_params() -> None: - """Test that streaming correctly invokes on_llm_new_token callback.""" - with pytest.raises(ValueError): - ChatTogether( - max_tokens=10, - streaming=True, - temperature=0, - n=5, - ) - - -def test_chat_together_extra_kwargs() -> None: - """Test extra kwargs to chat together.""" - # Check that foo is saved in extra_kwargs. - llm = ChatTogether(foo=3, max_tokens=10) # type: ignore[call-arg] - assert llm.max_tokens == 10 - assert llm.model_kwargs == {"foo": 3} - - # Test that if extra_kwargs are provided, they are added to it. - llm = ChatTogether(foo=3, model_kwargs={"bar": 2}) # type: ignore[call-arg] - assert llm.model_kwargs == {"foo": 3, "bar": 2} - - # Test that if provided twice it errors - with pytest.raises(ValueError): - ChatTogether(foo=3, model_kwargs={"foo": 2}) # type: ignore[call-arg] - - # Test that if explicit param is specified in kwargs it errors - with pytest.raises(ValueError): - ChatTogether(model_kwargs={"temperature": 0.2}) - - # Test that "model" cannot be specified in kwargs - with pytest.raises(ValueError): - ChatTogether(model_kwargs={"model": "meta-llama/Llama-3-8b-chat-hf"}) - - -def test_stream() -> None: - """Test streaming tokens from Together AI.""" - llm = ChatTogether() - - for token in llm.stream("I'm Pickle Rick"): - assert isinstance(token.content, str) - - -async def test_astream() -> None: - """Test streaming tokens from Together AI.""" - llm = ChatTogether() - - async for token in llm.astream("I'm Pickle Rick"): - assert isinstance(token.content, str) - - -async def test_abatch() -> None: - """Test streaming tokens from ChatTogether.""" - llm = ChatTogether() - - result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"]) - for token in result: - assert isinstance(token.content, str) - - -async def test_abatch_tags() -> None: - """Test batch tokens from ChatTogether.""" - llm = ChatTogether() - - 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 ChatTogether.""" - llm = ChatTogether() - - 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 ChatTogether.""" - llm = ChatTogether() - - result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]}) - assert isinstance(result.content, str) - - -def test_invoke() -> None: - """Test invoke tokens from ChatTogether.""" - llm = ChatTogether() - - result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"])) - assert isinstance(result.content, str) diff --git a/libs/partners/together/tests/integration_tests/test_chat_models_standard.py b/libs/partners/together/tests/integration_tests/test_chat_models_standard.py deleted file mode 100644 index f4c8cc7002d..00000000000 --- a/libs/partners/together/tests/integration_tests/test_chat_models_standard.py +++ /dev/null @@ -1,38 +0,0 @@ -"""Standard LangChain interface tests""" - -from typing import Optional, Type - -import pytest -from langchain_core.language_models import BaseChatModel -from langchain_core.rate_limiters import InMemoryRateLimiter -from langchain_standard_tests.integration_tests import ChatModelIntegrationTests - -from langchain_together import ChatTogether - -# Initialize the rate limiter in global scope, so it can be re-used -# across tests. -rate_limiter = InMemoryRateLimiter( - requests_per_second=0.5, -) - - -class TestTogetherStandard(ChatModelIntegrationTests): - @property - def chat_model_class(self) -> Type[BaseChatModel]: - return ChatTogether - - @property - def chat_model_params(self) -> dict: - return { - "model": "mistralai/Mixtral-8x7B-Instruct-v0.1", - "rate_limiter": rate_limiter, - } - - @property - def tool_choice_value(self) -> Optional[str]: - """Value to use for tool choice when used in tests.""" - return "tool_name" - - @pytest.mark.xfail(reason="Not yet supported.") - def test_usage_metadata_streaming(self, model: BaseChatModel) -> None: - super().test_usage_metadata_streaming(model) diff --git a/libs/partners/together/tests/integration_tests/test_compile.py b/libs/partners/together/tests/integration_tests/test_compile.py deleted file mode 100644 index 5196f4c0f8c..00000000000 --- a/libs/partners/together/tests/integration_tests/test_compile.py +++ /dev/null @@ -1,7 +0,0 @@ -import pytest # type: ignore[import-not-found] - - -@pytest.mark.compile -def test_placeholder() -> None: - """Used for compiling integration tests without running any real tests.""" - pass diff --git a/libs/partners/together/tests/integration_tests/test_embeddings.py b/libs/partners/together/tests/integration_tests/test_embeddings.py deleted file mode 100644 index c2a54b45e34..00000000000 --- a/libs/partners/together/tests/integration_tests/test_embeddings.py +++ /dev/null @@ -1,37 +0,0 @@ -"""Test Together AI embeddings.""" - -from langchain_together import TogetherEmbeddings - - -def test_langchain_together_embed_documents() -> None: - """Test Together AI embeddings.""" - documents = ["foo bar", "bar foo"] - embedding = TogetherEmbeddings() - output = embedding.embed_documents(documents) - assert len(output) == 2 - assert len(output[0]) > 0 - - -def test_langchain_together_embed_query() -> None: - """Test Together AI embeddings.""" - query = "foo bar" - embedding = TogetherEmbeddings() - output = embedding.embed_query(query) - assert len(output) > 0 - - -async def test_langchain_together_aembed_documents() -> None: - """Test Together AI embeddings asynchronous.""" - documents = ["foo bar", "bar foo"] - embedding = TogetherEmbeddings() - output = await embedding.aembed_documents(documents) - assert len(output) == 2 - assert len(output[0]) > 0 - - -async def test_langchain_together_aembed_query() -> None: - """Test Together AI embeddings asynchronous.""" - query = "foo bar" - embedding = TogetherEmbeddings() - output = await embedding.aembed_query(query) - assert len(output) > 0 diff --git a/libs/partners/together/tests/integration_tests/test_llms.py b/libs/partners/together/tests/integration_tests/test_llms.py deleted file mode 100644 index bfc416832ac..00000000000 --- a/libs/partners/together/tests/integration_tests/test_llms.py +++ /dev/null @@ -1,39 +0,0 @@ -"""Test Together API wrapper. -In order to run this test, you need to have an Together api key. -You can get it by registering for free at https://api.together.ai/. -A test key can be found at https://api.together.xyz/settings/api-keys -You'll then need to set TOGETHER_API_KEY environment variable to your api key. -""" - -import pytest as pytest # type: ignore[import-not-found] - -from langchain_together import Together - - -def test_together_call() -> None: - """Test simple call to together.""" - llm = Together( # type: ignore[call-arg] - model="togethercomputer/RedPajama-INCITE-7B-Base", - temperature=0.2, - max_tokens=250, - ) - output = llm.invoke("Say foo:") - - assert llm._llm_type == "together" - assert isinstance(output, str) - assert len(output) > 0 - - -async def test_together_acall() -> None: - """Test simple call to together.""" - llm = Together( # type: ignore[call-arg] - model="togethercomputer/RedPajama-INCITE-7B-Base", - temperature=0.2, - max_tokens=250, - ) - output = await llm.agenerate(["Say foo:"], stop=["bar"]) - - assert llm._llm_type == "together" - output_text = output.generations[0][0].text - assert isinstance(output_text, str) - assert output_text.count("bar") <= 1 diff --git a/libs/partners/together/tests/unit_tests/__init__.py b/libs/partners/together/tests/unit_tests/__init__.py deleted file mode 100644 index e69de29bb2d..00000000000 diff --git a/libs/partners/together/tests/unit_tests/test_chat_models.py b/libs/partners/together/tests/unit_tests/test_chat_models.py deleted file mode 100644 index 39dccc0a5ba..00000000000 --- a/libs/partners/together/tests/unit_tests/test_chat_models.py +++ /dev/null @@ -1,122 +0,0 @@ -import json - -import pytest # type: ignore[import-not-found] -from langchain_core.messages import ( - AIMessage, - FunctionMessage, - HumanMessage, - SystemMessage, - ToolMessage, -) -from langchain_openai.chat_models.base import ( - _convert_dict_to_message, - _convert_message_to_dict, -) - -from langchain_together import ChatTogether - - -def test_initialization() -> None: - """Test chat model initialization.""" - ChatTogether() - - -def test_together_model_param() -> None: - llm = ChatTogether(model="foo") - assert llm.model_name == "foo" - llm = ChatTogether(model_name="foo") # type: ignore[call-arg] - assert llm.model_name == "foo" - ls_params = llm._get_ls_params() - assert ls_params["ls_provider"] == "together" - - -def test_function_dict_to_message_function_message() -> None: - content = json.dumps({"result": "Example #1"}) - name = "test_function" - result = _convert_dict_to_message( - { - "role": "function", - "name": name, - "content": content, - } - ) - assert isinstance(result, FunctionMessage) - assert result.name == name - assert result.content == content - - -def test_convert_dict_to_message_human() -> None: - message = {"role": "user", "content": "foo"} - result = _convert_dict_to_message(message) - expected_output = HumanMessage(content="foo") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test__convert_dict_to_message_human_with_name() -> None: - message = {"role": "user", "content": "foo", "name": "test"} - result = _convert_dict_to_message(message) - expected_output = HumanMessage(content="foo", name="test") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test_convert_dict_to_message_ai() -> None: - message = {"role": "assistant", "content": "foo"} - result = _convert_dict_to_message(message) - expected_output = AIMessage(content="foo") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test_convert_dict_to_message_ai_with_name() -> None: - message = {"role": "assistant", "content": "foo", "name": "test"} - result = _convert_dict_to_message(message) - expected_output = AIMessage(content="foo", name="test") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test_convert_dict_to_message_system() -> None: - message = {"role": "system", "content": "foo"} - result = _convert_dict_to_message(message) - expected_output = SystemMessage(content="foo") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test_convert_dict_to_message_system_with_name() -> None: - message = {"role": "system", "content": "foo", "name": "test"} - result = _convert_dict_to_message(message) - expected_output = SystemMessage(content="foo", name="test") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -def test_convert_dict_to_message_tool() -> None: - message = {"role": "tool", "content": "foo", "tool_call_id": "bar"} - result = _convert_dict_to_message(message) - expected_output = ToolMessage(content="foo", tool_call_id="bar") - assert result == expected_output - assert _convert_message_to_dict(expected_output) == message - - -@pytest.fixture -def mock_completion() -> dict: - return { - "id": "chatcmpl-7fcZavknQda3SQ", - "object": "chat.completion", - "created": 1689989000, - "model": "meta-llama/Llama-3-8b-chat-hf", - "choices": [ - { - "index": 0, - "message": { - "role": "assistant", - "content": "Bab", - "name": "KimSolar", - }, - "finish_reason": "stop", - } - ], - } diff --git a/libs/partners/together/tests/unit_tests/test_chat_models_standard.py b/libs/partners/together/tests/unit_tests/test_chat_models_standard.py deleted file mode 100644 index 688752cdb09..00000000000 --- a/libs/partners/together/tests/unit_tests/test_chat_models_standard.py +++ /dev/null @@ -1,20 +0,0 @@ -"""Standard LangChain interface tests""" - -from typing import Type - -from langchain_core.language_models import BaseChatModel -from langchain_standard_tests.unit_tests import ( # type: ignore[import-not-found] - ChatModelUnitTests, # type: ignore[import-not-found] -) - -from langchain_together import ChatTogether - - -class TestTogetherStandard(ChatModelUnitTests): - @property - def chat_model_class(self) -> Type[BaseChatModel]: - return ChatTogether - - @property - def chat_model_params(self) -> dict: - return {"model": "meta-llama/Llama-3-8b-chat-hf"} diff --git a/libs/partners/together/tests/unit_tests/test_embeddings.py b/libs/partners/together/tests/unit_tests/test_embeddings.py deleted file mode 100644 index 3765c3359c3..00000000000 --- a/libs/partners/together/tests/unit_tests/test_embeddings.py +++ /dev/null @@ -1,25 +0,0 @@ -"""Test embedding model integration.""" - -import os - -import pytest # type: ignore[import-not-found] - -from langchain_together import TogetherEmbeddings - -os.environ["TOGETHER_API_KEY"] = "foo" - - -def test_initialization() -> None: - """Test embedding model initialization.""" - TogetherEmbeddings() - - -def test_together_invalid_model_kwargs() -> None: - with pytest.raises(ValueError): - TogetherEmbeddings(model_kwargs={"model": "foo"}) - - -def test_together_incorrect_field() -> None: - with pytest.warns(match="not default parameter"): - llm = TogetherEmbeddings(foo="bar") # type: ignore[call-arg] - assert llm.model_kwargs == {"foo": "bar"} diff --git a/libs/partners/together/tests/unit_tests/test_imports.py b/libs/partners/together/tests/unit_tests/test_imports.py deleted file mode 100644 index 8ca3f67f09b..00000000000 --- a/libs/partners/together/tests/unit_tests/test_imports.py +++ /dev/null @@ -1,7 +0,0 @@ -from langchain_together import __all__ - -EXPECTED_ALL = ["ChatTogether", "TogetherEmbeddings", "Together"] - - -def test_all_imports() -> None: - assert sorted(EXPECTED_ALL) == sorted(__all__) diff --git a/libs/partners/together/tests/unit_tests/test_llms.py b/libs/partners/together/tests/unit_tests/test_llms.py deleted file mode 100644 index ebed1d71997..00000000000 --- a/libs/partners/together/tests/unit_tests/test_llms.py +++ /dev/null @@ -1,101 +0,0 @@ -from typing import cast - -from langchain_core.pydantic_v1 import SecretStr -from pytest import CaptureFixture, MonkeyPatch # type: ignore[import-not-found] - -from langchain_together import Together - - -def test_together_api_key_is_secret_string() -> None: - """Test that the API key is stored as a SecretStr.""" - llm = Together( - together_api_key="secret-api-key", # type: ignore[call-arg] - model="togethercomputer/RedPajama-INCITE-7B-Base", - temperature=0.2, - max_tokens=250, - ) - assert isinstance(llm.together_api_key, SecretStr) - - -def test_together_api_key_masked_when_passed_from_env( - monkeypatch: MonkeyPatch, capsys: CaptureFixture -) -> None: - """Test that the API key is masked when passed from an environment variable.""" - monkeypatch.setenv("TOGETHER_API_KEY", "secret-api-key") - llm = Together( # type: ignore[call-arg] - model="togethercomputer/RedPajama-INCITE-7B-Base", - temperature=0.2, - max_tokens=250, - ) - print(llm.together_api_key, end="") - captured = capsys.readouterr() - - assert captured.out == "**********" - - -def test_together_api_key_masked_when_passed_via_constructor( - capsys: CaptureFixture, -) -> None: - """Test that the API key is masked when passed via the constructor.""" - llm = Together( - together_api_key="secret-api-key", # type: ignore[call-arg] - model="togethercomputer/RedPajama-INCITE-7B-Base", - temperature=0.2, - max_tokens=250, - ) - print(llm.together_api_key, end="") - captured = capsys.readouterr() - - assert captured.out == "**********" - - -def test_together_uses_actual_secret_value_from_secretstr() -> None: - """Test that the actual secret value is correctly retrieved.""" - llm = Together( - together_api_key="secret-api-key", # type: ignore[call-arg] - model="togethercomputer/RedPajama-INCITE-7B-Base", - temperature=0.2, - max_tokens=250, - ) - assert cast(SecretStr, llm.together_api_key).get_secret_value() == "secret-api-key" - - -def test_together_uses_actual_secret_value_from_secretstr_api_key() -> None: - """Test that the actual secret value is correctly retrieved.""" - llm = Together( - api_key="secret-api-key", # type: ignore[arg-type] - model="togethercomputer/RedPajama-INCITE-7B-Base", - temperature=0.2, - max_tokens=250, - ) - assert cast(SecretStr, llm.together_api_key).get_secret_value() == "secret-api-key" - - -def test_together_model_params() -> None: - # Test standard tracing params - llm = Together( - api_key="secret-api-key", # type: ignore[arg-type] - model="foo", - ) - ls_params = llm._get_ls_params() - assert ls_params == { - "ls_provider": "together", - "ls_model_type": "llm", - "ls_model_name": "foo", - "ls_max_tokens": 200, - } - - llm = Together( - api_key="secret-api-key", # type: ignore[arg-type] - model="foo", - temperature=0.2, - max_tokens=250, - ) - ls_params = llm._get_ls_params() - assert ls_params == { - "ls_provider": "together", - "ls_model_type": "llm", - "ls_model_name": "foo", - "ls_max_tokens": 250, - "ls_temperature": 0.2, - } diff --git a/libs/partners/together/tests/unit_tests/test_secrets.py b/libs/partners/together/tests/unit_tests/test_secrets.py deleted file mode 100644 index 07783133582..00000000000 --- a/libs/partners/together/tests/unit_tests/test_secrets.py +++ /dev/null @@ -1,13 +0,0 @@ -from langchain_together import ChatTogether, TogetherEmbeddings - - -def test_chat_together_secrets() -> None: - o = ChatTogether(together_api_key="foo") # type: ignore[call-arg] - s = str(o) - assert "foo" not in s - - -def test_together_embeddings_secrets() -> None: - o = TogetherEmbeddings(together_api_key="foo") # type: ignore[call-arg] - s = str(o) - assert "foo" not in s