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pyproject.toml
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54 lines (47 loc) · 1.66 KB
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[tool.poetry]
name = "python-ai-lab"
version = "1.0.0"
description = "Programatic examples for learning AI"
authors = ["Mario Codes <mariocodes1993@gmail.com>"]
readme = "README.md"
packages = [
{ include = "openai_lab" },
{ include = "langchain_lab" },
{ include = "rag" },
{ include = "vector_databases" },
{ include = "agent_framework_lab" },
]
[tool.poetry.dependencies]
python = ">=3.13,<3.14"
python-dotenv = "^1.2.1"
pandas = "^2.3.3"
openai = "^2.11.0"
langchain-openai = "^1.1.7"
langchain = "^1.2.3"
azure-cosmos = "^4.15.0"
pypdf = "^6.7.5"
langchain-community = "^0.4.1"
langchain-text-splitters = "^1.1.1"
langchain-experimental = "^0.4.1"
agent-framework = "^1.2.0"
[tool.poetry.scripts]
# Agent Framework
agent-framework-chat-stream = "agent_framework_lab.agent_streaming_chat:main"
agent-framework-tool = "agent_framework_lab.agent_with_tools:main"
agent-framework-multi-chat = "agent_framework_lab.agent_multi_turn_chat:main"
agent-framework-persistence = "agent_framework_lab.agent_memory_persistence:main"
# LangChain
langchain-basics = "langchain_lab.langchain_basics:main"
langchain-lcel = "langchain_lab.langchain_lcel:main"
# OpenAI
call-to-openai = "openai_lab.call_to_openai:main"
# RAG
setup-cosmosdb-for-rag = "rag.setup_cosmos_vector_container:main"
insert-rag-files = "rag.chunk_files_into_cosmos:main"
ask-rag-question = "rag.ask_with_rag_context:main"
# Vector Databases
insert-embeddings = "vector_databases.insert_embeddings:main"
query-embeddings = "vector_databases.query_vectorial_db:main"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"