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pyproject.toml
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pyproject.toml
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[tool.poetry]
name = "llm-app"
version = "0.3.1"
description = "LLM-App is a library for creating responsive AI applications leveraging OpenAI/Hugging Face APIs to provide responses to user queries based on live data sources. Build your own LLM application in 30 lines of code, no vector database required."
authors = [
"Jan Chorowski <[email protected]>",
"Kamil Piechowiak <[email protected]>",
"Jakub Kowalski <[email protected]>",
"Michał Bartoszkiewicz <[email protected]>",
"Mohamed Malhou <[email protected]>",
"Sergey Kulik <[email protected]>",
"Adrian Kosowski <[email protected]>",
"Mateusz Lewandowski <[email protected]>",
]
license = "MIT"
readme = "README.md"
keywords = ["Pathway", "LLM"]
classifiers = [
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"Programming Language :: Python :: Implementation :: CPython",
"License :: OSI Approved :: MIT License",
]
[tool.poetry.urls]
"Homepage" = "https://github.com/pathwaycom/llm-app"
"Source Code" = "https://github.com/pathwaycom/llm-app"
[tool.poetry.dependencies]
python = ">=3.10,<3.13"
pathway = "=0.5.2"
openai = ">=0.27.8,<0.29.0"
requests = "^2.31.0"
diskcache = "^5.6.1"
streamlit = "^1.26.0"
sentence-transformers = { version = "^2.2.2", optional = true }
torch = { version = ">=2.0.0, !=2.0.1", optional = true }
unstructured = { extras = ["all-docs"], version = "^0.10.15", optional = true }
tiktoken = { version = "^0.5.1", optional = true }
psycopg2 = "2.9.6"
[tool.poetry.extras]
local = ["torch", "sentence-transformers"]
unstructured = ["unstructured", "tiktoken"]
[tool.poetry.group.examples]
optional = true
[tool.poetry.group.examples.dependencies]
click = "^8.1.6"
python-dotenv = "^1.0.0"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
[tool.black]
target-version = ["py310", "py311"]
[tool.isort]
profile = "black"
known_first_party = ["llm_app"]
[tool.mypy]
python_version = "3.10"
exclude = ['examples']
ignore_missing_imports = true
check_untyped_defs = true
warn_redundant_casts = true
warn_unused_ignores = true
strict_equality = true