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<!-- Thank you for contributing to LangChain! Please title your PR "<package>: <description>", where <package> is whichever of langchain, community, core, experimental, etc. is being modified. Replace this entire comment with: - **Description:** Adding Oracle Cloud Infrastructure Generative AI integration. Oracle Cloud Infrastructure (OCI) Generative AI is a fully managed service that provides a set of state-of-the-art, customizable large language models (LLMs) that cover a wide range of use cases, and which is available through a single API. Using the OCI Generative AI service you can access ready-to-use pretrained models, or create and host your own fine-tuned custom models based on your own data on dedicated AI clusters. https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm - **Issue:** None, - **Dependencies:** OCI Python SDK, - **Twitter handle:** we announce bigger features on Twitter. If your PR gets announced, and you'd like a mention, we'll gladly shout you out! Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` from the root of the package you've modified to check this locally. Passed See contribution guidelines for more information on how to write/run tests, lint, etc: https://python.langchain.com/docs/contributing/ If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/docs/integrations` directory. we provide unit tests. However, we cannot provide integration tests due to Oracle policies that prohibit public sharing of api keys. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. --> --------- Co-authored-by: Arthur Cheng <arthur.cheng@oracle.com> Co-authored-by: Bagatur <baskaryan@gmail.com>
100 lines
1.9 KiB
Python
100 lines
1.9 KiB
Python
from langchain_core.language_models.llms import BaseLLM
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from langchain_community import llms
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EXPECT_ALL = [
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"AI21",
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"AlephAlpha",
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"AmazonAPIGateway",
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"Anthropic",
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"Anyscale",
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"Aphrodite",
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"Arcee",
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"Aviary",
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"AzureMLOnlineEndpoint",
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"AzureOpenAI",
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"Banana",
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"Baseten",
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"Beam",
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"Bedrock",
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"CTransformers",
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"CTranslate2",
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"CerebriumAI",
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"ChatGLM",
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"Clarifai",
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"Cohere",
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"Databricks",
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"DeepInfra",
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"DeepSparse",
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"EdenAI",
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"FakeListLLM",
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"Fireworks",
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"ForefrontAI",
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"GigaChat",
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"GPT4All",
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"GooglePalm",
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"GooseAI",
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"GradientLLM",
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"HuggingFaceEndpoint",
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"HuggingFaceHub",
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"HuggingFacePipeline",
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"HuggingFaceTextGenInference",
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"HumanInputLLM",
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"KoboldApiLLM",
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"Konko",
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"LlamaCpp",
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"TextGen",
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"ManifestWrapper",
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"Minimax",
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"MlflowAIGateway",
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"Modal",
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"MosaicML",
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"Nebula",
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"OCIModelDeploymentTGI",
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"OCIModelDeploymentVLLM",
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"OCIGenAI",
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"NIBittensorLLM",
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"NLPCloud",
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"Ollama",
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"OpenAI",
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"OpenAIChat",
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"OpenLLM",
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"OpenLM",
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"PaiEasEndpoint",
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"Petals",
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"PipelineAI",
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"Predibase",
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"PredictionGuard",
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"PromptLayerOpenAI",
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"PromptLayerOpenAIChat",
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"OpaquePrompts",
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"RWKV",
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"Replicate",
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"SagemakerEndpoint",
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"SelfHostedHuggingFaceLLM",
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"SelfHostedPipeline",
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"StochasticAI",
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"TitanTakeoff",
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"TitanTakeoffPro",
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"Tongyi",
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"VertexAI",
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"VertexAIModelGarden",
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"VLLM",
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"VLLMOpenAI",
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"Writer",
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"OctoAIEndpoint",
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"Xinference",
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"JavelinAIGateway",
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"QianfanLLMEndpoint",
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"YandexGPT",
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"VolcEngineMaasLLM",
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"WatsonxLLM",
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]
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def test_all_imports() -> None:
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"""Simple test to make sure all things can be imported."""
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for cls in llms.__all__:
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assert issubclass(getattr(llms, cls), BaseLLM)
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assert set(llms.__all__) == set(EXPECT_ALL)
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