Metadata-Version: 2.4
Name: llama-index-core
Version: 0.14.10
Summary: Interface between LLMs and your data
Project-URL: Homepage, https://llamaindex.ai
Project-URL: Repository, https://github.com/run-llama/llama_index
Project-URL: Documentation, https://docs.llamaindex.ai/en/stable/
Author-email: Jerry Liu <jerry@llamaindex.ai>
Maintainer-email: Andrei Fajardo <andrei@runllama.ai>, Haotian Zhang <ht@runllama.ai>, Jerry Liu <jerry@llamaindex.ai>, Logan Markewich <logan@llamaindex.ai>, Simon Suo <simon@llamaindex.ai>, Sourabh Desai <sourabh@llamaindex.ai>
License-Expression: MIT
License-File: LICENSE
Keywords: LLM,NLP,RAG,data,devtools,index,retrieval
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Application Frameworks
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: <4.0,>=3.9
Requires-Dist: aiohttp<4,>=3.8.6
Requires-Dist: aiosqlite
Requires-Dist: banks<3,>=2.2.0
Requires-Dist: dataclasses-json
Requires-Dist: deprecated>=1.2.9.3
Requires-Dist: dirtyjson<2,>=1.0.8
Requires-Dist: eval-type-backport<0.3,>=0.2.0; python_version < '3.10'
Requires-Dist: filetype<2,>=1.2.0
Requires-Dist: fsspec>=2023.5.0
Requires-Dist: httpx
Requires-Dist: llama-index-workflows!=2.9.0,<3,>=2
Requires-Dist: nest-asyncio<2,>=1.5.8
Requires-Dist: networkx>=3.0
Requires-Dist: nltk>3.8.1
Requires-Dist: numpy
Requires-Dist: pillow>=9.0.0
Requires-Dist: platformdirs
Requires-Dist: pydantic>=2.8.0
Requires-Dist: pyyaml>=6.0.1
Requires-Dist: requests>=2.31.0
Requires-Dist: setuptools>=80.9.0
Requires-Dist: sqlalchemy[asyncio]>=1.4.49
Requires-Dist: tenacity!=8.4.0,<10.0.0,>=8.2.0
Requires-Dist: tiktoken>=0.7.0
Requires-Dist: tqdm<5,>=4.66.1
Requires-Dist: typing-extensions>=4.5.0
Requires-Dist: typing-inspect>=0.8.0
Requires-Dist: wrapt
Description-Content-Type: text/markdown

# LlamaIndex Core

The core python package to the LlamaIndex library. Core classes and abstractions
represent the foundational building blocks for LLM applications, most notably,
RAG. Such building blocks include abstractions for LLMs, Vector Stores, Embeddings,
Storage, Callables and several others.

We've designed the core library so that it can be easily extended through subclasses.
Building LLM applications with LlamaIndex thus involves building with LlamaIndex
core as well as with the LlamaIndex [integrations](https://github.com/run-llama/llama_index/tree/main/llama-index-integrations) needed for your application.
