From 9daa4677e0922adbec70e308e1f08e1e3cfde7cd Mon Sep 17 00:00:00 2001 From: Li Yin Date: Tue, 9 Jul 2024 12:55:51 -0700 Subject: [PATCH 1/3] improve code in various model clients, update the documentation toml file to use the newest dev code for documentation --- docs/pyproject.toml | 3 +- .../lightrag_design_philosophy.rst | 2 +- .../get_started/lightrag_in_10_mins.rst | 14 +- docs/tests.txt | 405 ------------------ .../components/model_client/cohere_client.py | 9 +- .../components/model_client/google_client.py | 3 +- .../components/model_client/openai_client.py | 6 +- .../model_client/transformers_client.py | 9 +- pyproject.toml | 4 - 9 files changed, 25 insertions(+), 430 deletions(-) delete mode 100644 docs/tests.txt diff --git a/docs/pyproject.toml b/docs/pyproject.toml index be4d3c83..0a5fdc90 100644 --- a/docs/pyproject.toml +++ b/docs/pyproject.toml @@ -8,8 +8,7 @@ packages = [{ from = "_dummy", include = "dummy" }] # empty packages [tool.poetry.dependencies] python = ">=3.11, <4.0" -lightrag = "^0.0.0a13" # Assuming this is the main library you are developing - +lightrag = { path = "lightrag", develop = true } # document always follow the latest version of the library [tool.poetry.group.doc.dependencies] pydata-sphinx-theme = "^0.15.3" diff --git a/docs/source/developer_notes/lightrag_design_philosophy.rst b/docs/source/developer_notes/lightrag_design_philosophy.rst index f2fb932c..fcdee805 100644 --- a/docs/source/developer_notes/lightrag_design_philosophy.rst +++ b/docs/source/developer_notes/lightrag_design_philosophy.rst @@ -10,7 +10,7 @@ We put these three hard rules while designing LightRAG: - Every layer of abstraction needs to be adjusted and overall we do not allow more than 3 layers of abstraction. - We minimize the lines of code instead of maximizing the lines of code. -- Go *deep* and *wide* in order to *simplify*. The clarity we achieve is not the result of being easy, but the result of being deep. +- Go *deep* and *wide* in order to *simplify*. The clarity we achieve is not the result of being easy. diff --git a/docs/source/get_started/lightrag_in_10_mins.rst b/docs/source/get_started/lightrag_in_10_mins.rst index 1bdec107..d046c77f 100644 --- a/docs/source/get_started/lightrag_in_10_mins.rst +++ b/docs/source/get_started/lightrag_in_10_mins.rst @@ -1,13 +1,15 @@ LightRAG in 10 minutes ============================= -[Li] +Coming soon... -Will use end to end trec classifier as an example to demonstrate: +We will showcase a use case end-to-end, including task pipeline, configuration, logging and tracing, evaluation, and optimization. -1. Look at the data and task, create `data class`, `prompt`, and `task`, and set up `log` and tracing. -2. Create datasets with `train`, `eval`, and `test` splits. -3. Eval zero-shot with manual prompts. +.. Will use end to end trec classifier as an example to demonstrate: +.. 1. Look at the data and task, create `data class`, `prompt`, and `task`, and set up `log` and tracing. +.. 2. Create datasets with `train`, `eval`, and `test` splits. +.. 3. Eval zero-shot with manual prompts. -The content will be from `/use_cases/classification/readme.md`. \ No newline at end of file + +.. 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[100%] _static/images/retriever.png - -dumping search index in English (code: en)... done -dumping object inventory... done -build succeeded, 227 warnings. - -The HTML pages are in build. diff --git a/lightrag/lightrag/components/model_client/cohere_client.py b/lightrag/lightrag/components/model_client/cohere_client.py index 2ec3048d..9d6dc00d 100644 --- a/lightrag/lightrag/components/model_client/cohere_client.py +++ b/lightrag/lightrag/components/model_client/cohere_client.py @@ -77,9 +77,12 @@ def convert_inputs_to_api_kwargs( final_model_kwargs = model_kwargs.copy() if model_type == ModelType.RERANKER: final_model_kwargs["query"] = input - assert "model" in final_model_kwargs, "model must be specified" - assert "documents" in final_model_kwargs, "documents must be specified" - assert "top_k" in final_model_kwargs, "top_k must be specified" + if "model" not in final_model_kwargs: + raise ValueError("model must be specified") + if "documents" not in final_model_kwargs: + raise ValueError("documents must be specified") + if "top_k" not in final_model_kwargs: + raise ValueError("top_k must be specified") # convert top_k to the api specific, which is top_n final_model_kwargs["top_n"] = final_model_kwargs.pop("top_k") diff --git a/lightrag/lightrag/components/model_client/google_client.py b/lightrag/lightrag/components/model_client/google_client.py index c097a9e6..9c4d57a0 100644 --- a/lightrag/lightrag/components/model_client/google_client.py +++ b/lightrag/lightrag/components/model_client/google_client.py @@ -66,7 +66,8 @@ def convert_inputs_to_api_kwargs( if isinstance(input, str): input = [input] # convert input to input - assert isinstance(input, Sequence), "input must be a sequence of text" + if not isinstance(input, Sequence): + raise TypeError("input must be a sequence of text") final_model_kwargs["input"] = input elif model_type == ModelType.LLM: diff --git a/lightrag/lightrag/components/model_client/openai_client.py b/lightrag/lightrag/components/model_client/openai_client.py index 8dc4874b..b38addda 100644 --- a/lightrag/lightrag/components/model_client/openai_client.py +++ b/lightrag/lightrag/components/model_client/openai_client.py @@ -148,16 +148,14 @@ def convert_inputs_to_api_kwargs( if isinstance(input, str): input = [input] # convert input to input - assert isinstance(input, Sequence), "input must be a sequence of text" + if not isinstance(input, Sequence): + raise TypeError("input must be a sequence of text") final_model_kwargs["input"] = input elif model_type == ModelType.LLM: # convert input to messages messages: List[Dict[str, str]] = [] if input is not None and input != "": messages.append({"role": "system", "content": input}) - assert isinstance( - messages, Sequence - ), "input must be a sequence of messages" final_model_kwargs["messages"] = messages else: raise ValueError(f"model_type {model_type} is not supported") diff --git a/lightrag/lightrag/components/model_client/transformers_client.py b/lightrag/lightrag/components/model_client/transformers_client.py index 1517a8ad..16ab0ae5 100644 --- a/lightrag/lightrag/components/model_client/transformers_client.py +++ b/lightrag/lightrag/components/model_client/transformers_client.py @@ -374,10 +374,11 @@ def parse_embedding_response(self, response: Any) -> EmbedderOutput: return response def call(self, api_kwargs: Dict = {}, model_type: ModelType = ModelType.UNDEFINED): - assert "model" in api_kwargs, "model is required" - assert ( - api_kwargs["model"] in self.support_models - ), f"model {api_kwargs['model']} is not supported" + if "model" not in api_kwargs: + raise ValueError("model must be specified in api_kwargs") + if api_kwargs["model"] not in self.support_models: + raise ValueError(f"model {api_kwargs['model']} is not supported") + if ( model_type == ModelType.EMBEDDER and "model" in api_kwargs diff --git a/pyproject.toml b/pyproject.toml index 5278c225..9e739301 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -11,10 +11,7 @@ packages = [{ from = "_lightrag", include = "lightrag" }] # empty packa python = ">=3.11, <4.0" # lightrag = { path = "lightrag", develop = true } torch = "^2.3.1" -# flagembedding = "^1.2.10" openai = "^1.34.0" -networkx = "^3.3" -pyvis = "^0.3.2" # lightrag = {path = "lightrag/dist/lightrag-0.0.0a11-py3-none-any.whl"} lightrag = "^0.0.0a13" @@ -22,7 +19,6 @@ lightrag = "^0.0.0a13" [tool.poetry.group.dev.dependencies] pre-commit = "^3.7.0" - anthropic = "^0.26.0" torchmetrics = "^1.4.0.post0" jupyter = "^1.0.0" From 41d61cff6e35fa6f2f0530762447734325ab6732 Mon Sep 17 00:00:00 2001 From: Li Yin Date: Tue, 9 Jul 2024 16:24:41 -0700 Subject: [PATCH 2/3] add more tests to lazy import and report error when user trying to subclass lazy import class and inform them the right way to subclass --- README.md | 4 +- docs/.gitignore | 1 + docs/poetry.lock | 1113 +++++++++++++++-- docs/pyproject.toml | 10 +- .../lightrag_design_philosophy.rst | 2 +- docs/source/index.rst | 2 +- lightrag/.gitignore | 1 + .../model_client/anthropic_client.py | 3 + .../components/model_client/cohere_client.py | 3 +- .../components/model_client/openai_client.py | 1 - .../lightrag/components/model_client/utils.py | 1 - lightrag/lightrag/core/__init__.py | 4 +- .../lightrag/database/sqlalchemy/model.py | 10 +- lightrag/lightrag/utils/lazy_import.py | 38 +- lightrag/lightrag/utils/setup_env.py | 13 +- lightrag/poetry.lock | 23 +- lightrag/pyproject.toml | 2 +- 17 files changed, 1077 insertions(+), 154 deletions(-) create mode 100644 lightrag/.gitignore diff --git a/README.md b/README.md index 24570123..9bf7f67f 100644 --- a/README.md +++ b/README.md @@ -12,7 +12,7 @@ ### ⚡ The PyTorch Library for Large Language Model Applications ⚡ -*LightRAG* helps developers with both building and optimizing *Retriever-Agent-Generator (RAG)* pipelines. +*LightRAG* helps developers with both building and optimizing *Retriever-Agent-Generator* pipelines. It is *light*, *modular*, and *robust*, with a 100% readable codebase. @@ -22,7 +22,7 @@ It is *light*, *modular*, and *robust*, with a 100% readable codebase. LLMs are like water; they can almost do anything, from GenAI applications such as chatbots, translation, summarization, code generation, and autonomous agents to classical NLP tasks like text classification and named entity recognition. They interact with the world beyond the model’s internal knowledge via retrievers, memory, and tools (function calls). Each use case is unique in its data, business logic, and user experience. -Because of this, no library can provide out-of-the-box solutions. Users must build towards their own use case, which requires the library to be modular, robust, and have a clean and readable codebase. The only code you should put into production is code you either trust 100% or are 100% clear about how to customize and iterate. +Because of this, no library can provide out-of-the-box solutions. Users must build toward their own use case. This requires the library to be modular, robust, and have a clean, readable codebase. The only code you should put into production is code you either 100% trust or are 100% clear about how to customize and iterate. 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[tool.poetry.dependencies] python = ">=3.11, <4.0" -lightrag = { path = "lightrag", develop = true } # document always follow the latest version of the library +lightrag = { path = "../lightrag", develop = true } # document always follow the latest version of the library [tool.poetry.group.doc.dependencies] pydata-sphinx-theme = "^0.15.3" @@ -19,8 +19,16 @@ nbsphinx = "^0.9.4" nbconvert = "^7.16.4" pandoc = "^2.3" readthedocs-sphinx-search = "^0.3.2" +# add optional packages to compile the documents correctly sqlalchemy = "^2.0.31" google-generativeai = "^0.7.1" +anthropic = "^0.30.1" +cohere = "^5.5.8" +transformers = "^4.42.3" +openai = "^1.35.12" +groq = "^0.9.0" +pgvector = "^0.3.0" +faiss-cpu = "^1.8.0.post1" [build-system] requires = ["poetry-core>=1.0.0"] diff --git a/docs/source/developer_notes/lightrag_design_philosophy.rst b/docs/source/developer_notes/lightrag_design_philosophy.rst index fcdee805..e7242a0d 100644 --- a/docs/source/developer_notes/lightrag_design_philosophy.rst +++ b/docs/source/developer_notes/lightrag_design_philosophy.rst @@ -6,7 +6,7 @@ Right from the begining, `LightRAG` follows three fundamental principles. Principle 1: Simplicity over Complexity ----------------------------------------------------------------------- -We put these three hard rules while designing LightRAG: + We put these three hard rules while designing LightRAG: - Every layer of abstraction needs to be adjusted and overall we do not allow more than 3 layers of abstraction. - We minimize the lines of code instead of maximizing the lines of code. diff --git a/docs/source/index.rst b/docs/source/index.rst index 519db7a7..007139d6 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -26,7 +26,7 @@

- LightRAG helps developers with both building and optimizing Retriever-Agent-Generator (RAG) pipelines.
+ LightRAG helps developers with both building and optimizing Retriever-Agent-Generator pipelines.
It is light, modular, and robust, with a 100% readable codebase.

diff --git a/lightrag/.gitignore b/lightrag/.gitignore new file mode 100644 index 00000000..799780fd --- /dev/null +++ b/lightrag/.gitignore @@ -0,0 +1 @@ +test*.py diff --git a/lightrag/lightrag/components/model_client/anthropic_client.py b/lightrag/lightrag/components/model_client/anthropic_client.py index c53049ef..869d6a2b 100644 --- a/lightrag/lightrag/components/model_client/anthropic_client.py +++ b/lightrag/lightrag/components/model_client/anthropic_client.py @@ -34,6 +34,9 @@ def get_first_message_content(completion: Message) -> str: return completion.content[0].text +__all__ = ["AnthropicAPIClient", "get_first_message_content"] + + # NOTE: using customize parser might make the new_component more complex when we have to handle a callable class AnthropicAPIClient(ModelClient): __doc__ = r"""A component wrapper for the Anthropic API client. diff --git a/lightrag/lightrag/components/model_client/cohere_client.py b/lightrag/lightrag/components/model_client/cohere_client.py index 9d6dc00d..93132234 100644 --- a/lightrag/lightrag/components/model_client/cohere_client.py +++ b/lightrag/lightrag/components/model_client/cohere_client.py @@ -126,7 +126,8 @@ async def acall( ): if self.async_client is None: self.init_async_client() - assert "model" in api_kwargs, "model must be specified" + if "model" not in api_kwargs: + raise ValueError("model must be specified") if model_type == ModelType.RERANKER: response = await self.async_client.rerank(**api_kwargs) top_k_scores = [result.relevance_score for result in response.results] diff --git a/lightrag/lightrag/components/model_client/openai_client.py b/lightrag/lightrag/components/model_client/openai_client.py index b38addda..d374d123 100644 --- a/lightrag/lightrag/components/model_client/openai_client.py +++ b/lightrag/lightrag/components/model_client/openai_client.py @@ -118,7 +118,6 @@ def parse_chat_completion(self, completion: Completion) -> Any: """Parse the completion to a str.""" log.debug(f"completion: {completion}") return self.chat_completion_parser(completion) - # return completion.choices[0].message.content def parse_embedding_response( self, response: CreateEmbeddingResponse diff --git a/lightrag/lightrag/components/model_client/utils.py b/lightrag/lightrag/components/model_client/utils.py index a7bec9aa..2b81d96e 100644 --- a/lightrag/lightrag/components/model_client/utils.py +++ b/lightrag/lightrag/components/model_client/utils.py @@ -1,5 +1,4 @@ "Helpers for model client for integrating models and parsing the output." - from lightrag.core.types import EmbedderOutput, Embedding, Usage diff --git a/lightrag/lightrag/core/__init__.py b/lightrag/lightrag/core/__init__.py index aa246d6b..da3351f0 100644 --- a/lightrag/lightrag/core/__init__.py +++ b/lightrag/lightrag/core/__init__.py @@ -15,7 +15,7 @@ from .types import ( ModelType, - ModelClientType, + # ModelClientType, get_model_args, Embedding, Usage, @@ -65,7 +65,7 @@ "GeneratorOutput", "GeneratorOutputType", "ModelType", - "ModelClientType", + # "ModelClientType", "get_model_args", "Embedding", "Usage", diff --git a/lightrag/lightrag/database/sqlalchemy/model.py b/lightrag/lightrag/database/sqlalchemy/model.py index 2b56f47e..7ba1b728 100644 --- a/lightrag/lightrag/database/sqlalchemy/model.py +++ b/lightrag/lightrag/database/sqlalchemy/model.py @@ -30,7 +30,14 @@ from typing import Optional, Dict, List from datetime import datetime import logging +from lightrag.utils.lazy_import import safe_import, OptionalPackages +sqlalchemy = safe_import( + OptionalPackages.SQLALCHEMY.value[0], OptionalPackages.SQLALCHEMY.value[1] +) +pgvector = safe_import( + OptionalPackages.PGVECTOR.value[0], OptionalPackages.PGVECTOR.value[1] +) from sqlalchemy import ( Column, Integer, @@ -48,11 +55,8 @@ from pgvector.sqlalchemy import Vector -from lightrag.utils.lazy_import import safe_import, OptionalPackages from lightrag.database.sqlalchemy.base import Base -safe_import(OptionalPackages.SQLALCHEMY.value[0], OptionalPackages.SQLALCHEMY.value[1]) -safe_import(OptionalPackages.PGVECTOR.value[0], OptionalPackages.PGVECTOR.value[1]) log = logging.getLogger(__name__) diff --git a/lightrag/lightrag/utils/lazy_import.py b/lightrag/lightrag/utils/lazy_import.py index 18741b68..db0d1293 100644 --- a/lightrag/lightrag/utils/lazy_import.py +++ b/lightrag/lightrag/utils/lazy_import.py @@ -2,6 +2,7 @@ import importlib import logging +from types import ModuleType from enum import Enum @@ -65,7 +66,16 @@ class LazyImport: optional_package (OptionalPackages): The optional package to import, it helps define the package name and error message. """ - def __init__(self, import_path: str, optional_package: OptionalPackages): + def __init__( + self, import_path: str, optional_package: OptionalPackages, *args, **kwargs + ): + if args or kwargs: + raise TypeError( + "LazyImport does not support subclassing or additional arguments. " + "Import the class directly from its specific module instead. For example, " + "from lightrag.components.model_client.cohere_client import CohereAPIClient" + "instead of using the lazy import with: from lightrag.components.model_client import CohereAPIClient" + ) self.import_path = import_path self.optional_package = optional_package self.module = None @@ -100,10 +110,34 @@ def __call__(self, *args, **kwargs): return self.class_(*args, **kwargs) -def safe_import(module_name, install_message): +def safe_import(module_name: str, install_message: str) -> ModuleType: """Safely import a module and raise an ImportError with the install message if the module is not found. Mainly used internally to import optional packages only when needed. + + Example: + + 1. Tests + + .. code-block:: python + + try: + numpy = safe_import("numpy", "Please install numpy with: pip install numpy") + print(numpy.__version__) + except ImportError as e: + print(e) + + When numpy is not installed, it will raise an ImportError with the install message. + When numpy is installed, it will print the numpy version. + + 2. Use it to delay the import of optional packages in the library. + + .. code-block:: python + + from lightrag.utils.lazy_import import safe_import, OptionalPackages + + numpy = safe_import(OptionalPackages.NUMPY.value[0], OptionalPackages.NUMPY.value[1]) + """ try: return importlib.import_module(module_name) diff --git a/lightrag/lightrag/utils/setup_env.py b/lightrag/lightrag/utils/setup_env.py index a201d070..d2250e26 100644 --- a/lightrag/lightrag/utils/setup_env.py +++ b/lightrag/lightrag/utils/setup_env.py @@ -1,7 +1,18 @@ import dotenv +import os +import logging + +log = logging.getLogger(__name__) def setup_env(dotenv_path: str = ".env"): """Load environment variables from .env file.""" - dotenv.load_dotenv(dotenv_path=dotenv_path) + if not os.path.exists(dotenv_path): + raise FileNotFoundError(f"File not found: {dotenv_path}") + + try: + dotenv.load_dotenv(dotenv_path=dotenv_path, verbose=True, override=False) + except Exception as e: + log.error(f"Error loading .env file: {e}") + raise e diff --git a/lightrag/poetry.lock b/lightrag/poetry.lock index 1fb66df7..02d8f4b7 100644 --- a/lightrag/poetry.lock +++ b/lightrag/poetry.lock @@ -507,13 +507,13 @@ typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "t [[package]] name = "identify" -version = "2.5.36" +version = "2.6.0" description = "File identification library for Python" optional = false python-versions = ">=3.8" files = [ - {file = "identify-2.5.36-py2.py3-none-any.whl", hash = "sha256:37d93f380f4de590500d9dba7db359d0d3da95ffe7f9de1753faa159e71e7dfa"}, - {file = "identify-2.5.36.tar.gz", hash = "sha256:e5e00f54165f9047fbebeb4a560f9acfb8af4c88232be60a488e9b68d122745d"}, + {file = "identify-2.6.0-py2.py3-none-any.whl", hash = "sha256:e79ae4406387a9d300332b5fd366d8994f1525e8414984e1a59e058b2eda2dd0"}, + {file = "identify-2.6.0.tar.gz", hash = "sha256:cb171c685bdc31bcc4c1734698736a7d5b6c8bf2e0c15117f4d469c8640ae5cf"}, ] [package.extras] @@ -966,13 +966,13 @@ files = [ [[package]] name = "openai" -version = "1.35.10" +version = "1.35.12" description = "The official Python library for the openai API" optional = false python-versions = ">=3.7.1" files = [ - {file = "openai-1.35.10-py3-none-any.whl", hash = "sha256:962cb5c23224b5cbd16078308dabab97a08b0a5ad736a4fdb3dc2ffc44ac974f"}, - {file = "openai-1.35.10.tar.gz", hash = "sha256:85966949f4f960f3e4b239a659f9fd64d3a97ecc43c44dc0a044b5c7f11cccc6"}, + {file = "openai-1.35.12-py3-none-any.whl", hash = "sha256:c3a8c9be524480ae32a3212b78d90786b112844eb8f96235ebb8bc5f35cb1e72"}, + {file = "openai-1.35.12.tar.gz", hash = "sha256:2dd0f1d9ff34bf6bc89d15246245369d281b2ba01ae07eae5555a00da4b51e0b"}, ] [package.dependencies] @@ -1614,17 +1614,20 @@ sqlcipher = ["sqlcipher3_binary"] [[package]] name = "sympy" -version = "1.12.1" +version = "1.13.0" description = "Computer algebra system (CAS) in Python" optional = false python-versions = ">=3.8" files = [ - {file = "sympy-1.12.1-py3-none-any.whl", hash = "sha256:9b2cbc7f1a640289430e13d2a56f02f867a1da0190f2f99d8968c2f74da0e515"}, - {file = "sympy-1.12.1.tar.gz", hash = "sha256:2877b03f998cd8c08f07cd0de5b767119cd3ef40d09f41c30d722f6686b0fb88"}, + {file = "sympy-1.13.0-py3-none-any.whl", hash = "sha256:6b0b32a4673fb91bd3cac3b55406c8e01d53ae22780be467301cc452f6680c92"}, + {file = "sympy-1.13.0.tar.gz", hash = "sha256:3b6af8f4d008b9a1a6a4268b335b984b23835f26d1d60b0526ebc71d48a25f57"}, ] [package.dependencies] -mpmath = ">=1.1.0,<1.4.0" +mpmath = ">=1.1.0,<1.4" + +[package.extras] +dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"] [[package]] name = "tbb" diff --git a/lightrag/pyproject.toml b/lightrag/pyproject.toml index bc8c91d7..44d6a9de 100644 --- a/lightrag/pyproject.toml +++ b/lightrag/pyproject.toml @@ -2,7 +2,7 @@ name = "lightrag" version = "0.0.0-alpha.16" -description = "The 'PyTorch' library for LLM applications. RAG=Retriever-Agent-Generator." +description = "The 'PyTorch' library for LLM applications." authors = ["Li Yin "] readme = "README.md" repository = "https://github.com/SylphAI-Inc/LightRAG" From ae00738a800287ab7344c69a02aa3f88373187bc Mon Sep 17 00:00:00 2001 From: Li Yin Date: Tue, 9 Jul 2024 16:31:38 -0700 Subject: [PATCH 3/3] revert the change --- lightrag/lightrag/core/__init__.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/lightrag/lightrag/core/__init__.py b/lightrag/lightrag/core/__init__.py index da3351f0..aa246d6b 100644 --- a/lightrag/lightrag/core/__init__.py +++ b/lightrag/lightrag/core/__init__.py @@ -15,7 +15,7 @@ from .types import ( ModelType, - # ModelClientType, + ModelClientType, get_model_args, Embedding, Usage, @@ -65,7 +65,7 @@ "GeneratorOutput", "GeneratorOutputType", "ModelType", - # "ModelClientType", + "ModelClientType", "get_model_args", "Embedding", "Usage",