c3c25db48c
- Use cases related to LLM call: https://cinnamon-ai.atlassian.net/browse/AUR-388?focusedCommentId=34873 - Sample usages: `test_llms_chat_models.py` and `test_llms_completion_models.py`: ```python from kotaemon.llms.chats.openai import AzureChatOpenAI model = AzureChatOpenAI( openai_api_base="https://test.openai.azure.com/", openai_api_key="some-key", openai_api_version="2023-03-15-preview", deployment_name="gpt35turbo", temperature=0, request_timeout=60, ) output = model("hello world") ``` For the LLM-call component, I decide to wrap around Langchain's LLM models and Langchain's Chat models. And set the interface as follow: - Completion LLM component: ```python class CompletionLLM: def run_raw(self, text: str) -> LLMInterface: # Run text completion: str in -> LLMInterface out def run_batch_raw(self, text: list[str]) -> list[LLMInterface]: # Run text completion in batch: list[str] in -> list[LLMInterface] out # run_document and run_batch_document just reuse run_raw and run_batch_raw, due to unclear use case ``` - Chat LLM component: ```python class ChatLLM: def run_raw(self, text: str) -> LLMInterface: # Run chat completion (no chat history): str in -> LLMInterface out def run_batch_raw(self, text: list[str]) -> list[LLMInterface]: # Run chat completion in batch mode (no chat history): list[str] in -> list[LLMInterface] out def run_document(self, text: list[BaseMessage]) -> LLMInterface: # Run chat completion (with chat history): list[langchain's BaseMessage] in -> LLMInterface out def run_batch_document(self, text: list[list[BaseMessage]]) -> list[LLMInterface]: # Run chat completion in batch mode (with chat history): list[list[langchain's BaseMessage]] in -> list[LLMInterface] out ``` - The LLMInterface is as follow: ```python @dataclass class LLMInterface: text: list[str] completion_tokens: int = -1 total_tokens: int = -1 prompt_tokens: int = -1 logits: list[list[float]] = field(default_factory=list) ```
58 lines
1.5 KiB
Python
58 lines
1.5 KiB
Python
import codecs
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import re
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from pathlib import Path
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import setuptools
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def read(file_path: str) -> str:
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return codecs.open(file_path, "r").read()
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def get_version() -> str:
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version_file = read(str(Path("kotaemon", "__init__.py")))
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match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", version_file, re.M)
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if match:
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return match.group(1)
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raise RuntimeError("Cannot find verison string")
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setuptools.setup(
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name="kotaemon",
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version=get_version(),
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author="john",
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author_email="john@cinnamon.com",
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description="Kotaemon core library for AI development",
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long_description=read("README.md"),
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long_description_content_type="text/markdown",
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url="https://github.com/Cinnamon/kotaemon/",
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packages=setuptools.find_packages(exclude=("tests", "tests.*")),
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install_requires=[
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"farm-haystack==1.19.0",
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"langchain",
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"theflow",
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],
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extras_require={
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"dev": [
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"ipython",
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"pytest",
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"pre-commit",
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"black",
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"flake8",
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"sphinx",
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"coverage",
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# optional dependency needed for test
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"openai"
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],
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},
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entry_points={"console_scripts": ["kh=kotaemon.cli:main"]},
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python_requires=">=3",
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classifiers=[
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"Programming Language :: Python :: 3",
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"License :: OSI Approved :: MIT License",
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"Operating System :: OS Independent",
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],
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include_package_data=True,
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)
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