From 96a9bd429a90cec4c1bb46471fe65882edddb3b5 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Thu, 29 Aug 2024 15:33:16 -0700 Subject: [PATCH] init pkg (#1) * migrate Together * x --- .github/scripts/check_diff.py | 2 +- .github/workflows/_release.yml | 4 +- README.md | 8 +- libs/together/.gitignore | 1 + libs/together/LICENSE | 21 + libs/together/Makefile | 56 + libs/together/README.md | 28 + libs/together/langchain_together/__init__.py | 7 + .../langchain_together/chat_models.py | 364 +++ .../together/langchain_together/embeddings.py | 325 +++ libs/together/langchain_together/llms.py | 224 ++ libs/together/langchain_together/py.typed | 0 libs/together/poetry.lock | 1943 +++++++++++++++++ libs/together/pyproject.toml | 96 + libs/together/scripts/check_imports.py | 19 + libs/together/scripts/check_pydantic.sh | 27 + libs/together/scripts/lint_imports.sh | 17 + libs/together/tests/__init__.py | 0 .../tests/integration_tests/__init__.py | 0 .../integration_tests/test_chat_models.py | 136 ++ .../test_chat_models_standard.py | 38 + .../tests/integration_tests/test_compile.py | 7 + .../integration_tests/test_embeddings.py | 37 + .../tests/integration_tests/test_llms.py | 39 + libs/together/tests/unit_tests/__init__.py | 0 .../tests/unit_tests/test_chat_models.py | 122 ++ .../unit_tests/test_chat_models_standard.py | 20 + .../tests/unit_tests/test_embeddings.py | 25 + .../together/tests/unit_tests/test_imports.py | 7 + libs/together/tests/unit_tests/test_llms.py | 101 + .../together/tests/unit_tests/test_secrets.py | 13 + 31 files changed, 3680 insertions(+), 7 deletions(-) create mode 100644 libs/together/.gitignore create mode 100644 libs/together/LICENSE create mode 100644 libs/together/Makefile create mode 100644 libs/together/README.md create mode 100644 libs/together/langchain_together/__init__.py create mode 100644 libs/together/langchain_together/chat_models.py create mode 100644 libs/together/langchain_together/embeddings.py create mode 100644 libs/together/langchain_together/llms.py create mode 100644 libs/together/langchain_together/py.typed create mode 100644 libs/together/poetry.lock create mode 100644 libs/together/pyproject.toml create mode 100644 libs/together/scripts/check_imports.py create mode 100755 libs/together/scripts/check_pydantic.sh create mode 100755 libs/together/scripts/lint_imports.sh create mode 100644 libs/together/tests/__init__.py create mode 100644 libs/together/tests/integration_tests/__init__.py create mode 100644 libs/together/tests/integration_tests/test_chat_models.py create mode 100644 libs/together/tests/integration_tests/test_chat_models_standard.py create mode 100644 libs/together/tests/integration_tests/test_compile.py create mode 100644 libs/together/tests/integration_tests/test_embeddings.py create mode 100644 libs/together/tests/integration_tests/test_llms.py create mode 100644 libs/together/tests/unit_tests/__init__.py create mode 100644 libs/together/tests/unit_tests/test_chat_models.py create mode 100644 libs/together/tests/unit_tests/test_chat_models_standard.py create mode 100644 libs/together/tests/unit_tests/test_embeddings.py create mode 100644 libs/together/tests/unit_tests/test_imports.py create mode 100644 libs/together/tests/unit_tests/test_llms.py create mode 100644 libs/together/tests/unit_tests/test_secrets.py diff --git a/.github/scripts/check_diff.py b/.github/scripts/check_diff.py index 0fcb163..bfd9615 100644 --- a/.github/scripts/check_diff.py +++ b/.github/scripts/check_diff.py @@ -2,7 +2,7 @@ import sys from typing import Dict -LIB_DIRS = ["libs/{lib}"] +LIB_DIRS = ["libs/together"] if __name__ == "__main__": files = sys.argv[1:] diff --git a/.github/workflows/_release.yml b/.github/workflows/_release.yml index da67979..56b6f07 100644 --- a/.github/workflows/_release.yml +++ b/.github/workflows/_release.yml @@ -12,7 +12,7 @@ on: working-directory: required: true type: string - default: 'libs/' + default: 'libs/together' env: PYTHON_VERSION: "3.11" @@ -159,7 +159,7 @@ jobs: - name: Run integration tests env: - PARTNER_API_KEY: ${{ secrets.PARTNER_API_KEY }} + TOGETHER_API_KEY: ${{ secrets.TOGETHER_API_KEY }} run: make integration_tests working-directory: ${{ inputs.working-directory }} diff --git a/README.md b/README.md index 65ecf8a..ef062b6 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ -# 🦜️🔗 LangChain {partner} +# 🦜️🔗 LangChain Together -This repository contains 1 package with {partner} integrations with LangChain: +This repository contains 1 package with Together integrations with LangChain: - [langchain-{package_lower}](https://pypi.org/project/langchain-{package_lower}/) @@ -46,5 +46,5 @@ Slack - [ ] Set up release alerting in Slack (ask Erick for help) release: -/github subscribe langchain-ai/langchain-{partner_lower} releases workflows:{name:"release"} -/github unsubscribe langchain-ai/langchain-{partner_lower} issues pulls commits deployments +/github subscribe langchain-ai/langchain-together releases workflows:{name:"release"} +/github unsubscribe langchain-ai/langchain-together issues pulls commits deployments diff --git a/libs/together/.gitignore b/libs/together/.gitignore new file mode 100644 index 0000000..bee8a64 --- /dev/null +++ b/libs/together/.gitignore @@ -0,0 +1 @@ +__pycache__ diff --git a/libs/together/LICENSE b/libs/together/LICENSE new file mode 100644 index 0000000..fc0602f --- /dev/null +++ b/libs/together/LICENSE @@ -0,0 +1,21 @@ +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/together/Makefile b/libs/together/Makefile new file mode 100644 index 0000000..c2a1173 --- /dev/null +++ b/libs/together/Makefile @@ -0,0 +1,56 @@ +.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/together/README.md b/libs/together/README.md new file mode 100644 index 0000000..2195895 --- /dev/null +++ b/libs/together/README.md @@ -0,0 +1,28 @@ +# langchain-together + +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. diff --git a/libs/together/langchain_together/__init__.py b/libs/together/langchain_together/__init__.py new file mode 100644 index 0000000..f4a23d3 --- /dev/null +++ b/libs/together/langchain_together/__init__.py @@ -0,0 +1,7 @@ +"""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/together/langchain_together/chat_models.py b/libs/together/langchain_together/chat_models.py new file mode 100644 index 0000000..76d79d8 --- /dev/null +++ b/libs/together/langchain_together/chat_models.py @@ -0,0 +1,364 @@ +"""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/together/langchain_together/embeddings.py b/libs/together/langchain_together/embeddings.py new file mode 100644 index 0000000..80961b3 --- /dev/null +++ b/libs/together/langchain_together/embeddings.py @@ -0,0 +1,325 @@ +"""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/together/langchain_together/llms.py b/libs/together/langchain_together/llms.py new file mode 100644 index 0000000..279fbca --- /dev/null +++ b/libs/together/langchain_together/llms.py @@ -0,0 +1,224 @@ +"""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, + "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} + async with ClientSession() as session: + async with session.post( + self.base_url, json=payload, headers=headers + ) as response: + if response.status >= 500: + raise Exception(f"Together Server: Error {response.status}") + elif response.status >= 400: + raise ValueError( + f"Together received an invalid payload: {response.text}" + ) + elif response.status != 200: + raise Exception( + f"Together returned an unexpected response with status " + f"{response.status}: {response.text}" + ) + + response_json = await response.json() + + output = self._format_output(response_json) + return output diff --git a/libs/together/langchain_together/py.typed b/libs/together/langchain_together/py.typed new file mode 100644 index 0000000..e69de29 diff --git a/libs/together/poetry.lock 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+lock-version = "2.0" +python-versions = ">=3.8.1,<4.0" +content-hash = "99793655b7af7b63e48cc146e3a628648a8d4e9348a1f4483bcd74bb92c45fd7" diff --git a/libs/together/pyproject.toml b/libs/together/pyproject.toml new file mode 100644 index 0000000..d6e34ba --- /dev/null +++ b/libs/together/pyproject.toml @@ -0,0 +1,96 @@ +[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-together" +license = "MIT" + +[tool.mypy] +disallow_untyped_defs = "True" + +[tool.poetry.urls] +"Source Code" = "https://github.com/langchain-ai/langchain-together/tree/main/libs/together" +"Release Notes" = "https://github.com/langchain-ai/langchain-together/releases" + +[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" +langchain-openai = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/partners/openai"} +langchain-core = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/core"} +langchain-standard-tests = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/standard-tests"} + +[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" +langchain-core = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/core"} + +[tool.poetry.group.dev.dependencies] +langchain-core = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/core"} diff --git a/libs/together/scripts/check_imports.py b/libs/together/scripts/check_imports.py new file mode 100644 index 0000000..620bc29 --- /dev/null +++ b/libs/together/scripts/check_imports.py @@ -0,0 +1,19 @@ +"""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/together/scripts/check_pydantic.sh b/libs/together/scripts/check_pydantic.sh new file mode 100755 index 0000000..06b5bb8 --- /dev/null +++ b/libs/together/scripts/check_pydantic.sh @@ -0,0 +1,27 @@ +#!/bin/bash +# +# This script searches for lines starting with "import pydantic" or "from pydantic" +# in tracked files within a Git repository. +# +# Usage: ./scripts/check_pydantic.sh /path/to/repository + +# Check if a path argument is provided +if [ $# -ne 1 ]; then + echo "Usage: $0 /path/to/repository" + exit 1 +fi + +repository_path="$1" + +# Search for lines matching the pattern within the specified repository +result=$(git -C "$repository_path" grep -E '^import pydantic|^from pydantic') + +# Check if any matching lines were found +if [ -n "$result" ]; then + echo "ERROR: The following lines need to be updated:" + echo "$result" + echo "Please replace the code with an import from langchain_core.pydantic_v1." + echo "For example, replace 'from pydantic import BaseModel'" + echo "with 'from langchain_core.pydantic_v1 import BaseModel'" + exit 1 +fi diff --git a/libs/together/scripts/lint_imports.sh b/libs/together/scripts/lint_imports.sh new file mode 100755 index 0000000..695613c --- /dev/null +++ b/libs/together/scripts/lint_imports.sh @@ -0,0 +1,17 @@ +#!/bin/bash + +set -eu + +# Initialize a variable to keep track of errors +errors=0 + +# make sure not importing from langchain or langchain_experimental +git --no-pager grep '^from langchain\.' . && errors=$((errors+1)) +git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1)) + +# Decide on an exit status based on the errors +if [ "$errors" -gt 0 ]; then + exit 1 +else + exit 0 +fi diff --git a/libs/together/tests/__init__.py b/libs/together/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/libs/together/tests/integration_tests/__init__.py b/libs/together/tests/integration_tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/libs/together/tests/integration_tests/test_chat_models.py b/libs/together/tests/integration_tests/test_chat_models.py new file mode 100644 index 0000000..459e6bb --- /dev/null +++ b/libs/together/tests/integration_tests/test_chat_models.py @@ -0,0 +1,136 @@ +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/together/tests/integration_tests/test_chat_models_standard.py b/libs/together/tests/integration_tests/test_chat_models_standard.py new file mode 100644 index 0000000..f4c8cc7 --- /dev/null +++ b/libs/together/tests/integration_tests/test_chat_models_standard.py @@ -0,0 +1,38 @@ +"""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/together/tests/integration_tests/test_compile.py b/libs/together/tests/integration_tests/test_compile.py new file mode 100644 index 0000000..5196f4c --- /dev/null +++ b/libs/together/tests/integration_tests/test_compile.py @@ -0,0 +1,7 @@ +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/together/tests/integration_tests/test_embeddings.py b/libs/together/tests/integration_tests/test_embeddings.py new file mode 100644 index 0000000..c2a54b4 --- /dev/null +++ b/libs/together/tests/integration_tests/test_embeddings.py @@ -0,0 +1,37 @@ +"""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/together/tests/integration_tests/test_llms.py b/libs/together/tests/integration_tests/test_llms.py new file mode 100644 index 0000000..bfc4168 --- /dev/null +++ b/libs/together/tests/integration_tests/test_llms.py @@ -0,0 +1,39 @@ +"""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/together/tests/unit_tests/__init__.py b/libs/together/tests/unit_tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/libs/together/tests/unit_tests/test_chat_models.py b/libs/together/tests/unit_tests/test_chat_models.py new file mode 100644 index 0000000..39dccc0 --- /dev/null +++ b/libs/together/tests/unit_tests/test_chat_models.py @@ -0,0 +1,122 @@ +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/together/tests/unit_tests/test_chat_models_standard.py b/libs/together/tests/unit_tests/test_chat_models_standard.py new file mode 100644 index 0000000..688752c --- /dev/null +++ b/libs/together/tests/unit_tests/test_chat_models_standard.py @@ -0,0 +1,20 @@ +"""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/together/tests/unit_tests/test_embeddings.py b/libs/together/tests/unit_tests/test_embeddings.py new file mode 100644 index 0000000..3765c33 --- /dev/null +++ b/libs/together/tests/unit_tests/test_embeddings.py @@ -0,0 +1,25 @@ +"""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/together/tests/unit_tests/test_imports.py b/libs/together/tests/unit_tests/test_imports.py new file mode 100644 index 0000000..8ca3f67 --- /dev/null +++ b/libs/together/tests/unit_tests/test_imports.py @@ -0,0 +1,7 @@ +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/together/tests/unit_tests/test_llms.py b/libs/together/tests/unit_tests/test_llms.py new file mode 100644 index 0000000..ebed1d7 --- /dev/null +++ b/libs/together/tests/unit_tests/test_llms.py @@ -0,0 +1,101 @@ +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/together/tests/unit_tests/test_secrets.py b/libs/together/tests/unit_tests/test_secrets.py new file mode 100644 index 0000000..0778313 --- /dev/null +++ b/libs/together/tests/unit_tests/test_secrets.py @@ -0,0 +1,13 @@ +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