Metadata-Version: 2.1
Name: semantic-kernel
Version: 1.8.3
Summary: Semantic Kernel Python SDK
Author-email: Microsoft <SK-Support@microsoft.com>
Requires-Python: >=3.10,<3.13
Description-Content-Type: text/markdown
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Framework :: Pydantic :: 2
Classifier: Typing :: Typed
Requires-Dist: aiohttp ~= 3.8
Requires-Dist: pydantic ~= 2.0
Requires-Dist: pydantic-settings ~= 2.0
Requires-Dist: defusedxml ~= 0.7
Requires-Dist: numpy ~= 1.25.0; python_version < '3.12'
Requires-Dist: numpy ~= 1.26.0; python_version >= '3.12'
Requires-Dist: openai ~= 1.0
Requires-Dist: openapi_core >= 0.18,<0.20
Requires-Dist: opentelemetry-api ~= 1.24
Requires-Dist: opentelemetry-sdk ~= 1.24
Requires-Dist: prance ~= 23.6.21.0
Requires-Dist: pybars4 ~= 0.9
Requires-Dist: jinja2 ~= 3.1
Requires-Dist: nest-asyncio ~= 1.6
Requires-Dist: anthropic ~= 0.32 ; extra == "anthropic"
Requires-Dist: azure-ai-inference >= 1.0.0b3 ; extra == "azure"
Requires-Dist: azure-search-documents >= 11.6.0b4 ; extra == "azure"
Requires-Dist: azure-identity ~= 1.13 ; extra == "azure"
Requires-Dist: azure-cosmos ~= 4.7 ; extra == "azure"
Requires-Dist: chromadb >= 0.4,<0.6 ; extra == "chroma"
Requires-Dist: google-cloud-aiplatform ~= 1.60 ; extra == "google"
Requires-Dist: google-generativeai ~= 0.7 ; extra == "google"
Requires-Dist: transformers[torch] ~= 4.28 ; extra == "hugging_face"
Requires-Dist: sentence-transformers ~= 2.2 ; extra == "hugging_face"
Requires-Dist: torch == 2.2.2 ; extra == "hugging_face"
Requires-Dist: pymilvus >= 2.3,<2.4 ; extra == "milvus"
Requires-Dist: milvus >= 2.3,<2.3.8 ; extra == "milvus" and ( platform_system != 'Windows')
Requires-Dist: mistralai ~= 0.4 ; extra == "mistralai"
Requires-Dist: motor ~= 3.3.2 ; extra == "mongo"
Requires-Dist: ipykernel ~= 6.29 ; extra == "notebooks"
Requires-Dist: ollama ~= 0.2 ; extra == "ollama"
Requires-Dist: pandas ~= 2.2 ; extra == "pandas"
Requires-Dist: pinecone-client ~= 5.0 ; extra == "pinecone"
Requires-Dist: psycopg[binary,pool] ~= 3.2 ; extra == "postgres"
Requires-Dist: qdrant-client ~= 1.9 ; extra == "qdrant"
Requires-Dist: redis[hiredis] ~= 5.0 ; extra == "redis"
Requires-Dist: types-redis ~= 4.6.0.20240425 ; extra == "redis"
Requires-Dist: usearch ~= 2.9 ; extra == "usearch"
Requires-Dist: pyarrow >= 12.0,<18.0 ; extra == "usearch"
Requires-Dist: weaviate-client >= 3.18,<5.0 ; extra == "weaviate"
Project-URL: homepage, https://learn.microsoft.com/en-us/semantic-kernel/overview/
Project-URL: issues, https://github.com/microsoft/semantic-kernel/issues
Project-URL: release_notes, https://github.com/microsoft/semantic-kernel/releases?q=tag%3Apython-1&expanded=true
Project-URL: source, https://github.com/microsoft/semantic-kernel/tree/main/python
Provides-Extra: anthropic
Provides-Extra: azure
Provides-Extra: chroma
Provides-Extra: google
Provides-Extra: hugging_face
Provides-Extra: milvus
Provides-Extra: mistralai
Provides-Extra: mongo
Provides-Extra: notebooks
Provides-Extra: ollama
Provides-Extra: pandas
Provides-Extra: pinecone
Provides-Extra: postgres
Provides-Extra: qdrant
Provides-Extra: redis
Provides-Extra: usearch
Provides-Extra: weaviate

# About Semantic Kernel

**Semantic Kernel (SK)** is a lightweight SDK enabling integration of AI Large
Language Models (LLMs) with conventional programming languages. The SK
extensible programming model combines natural language **semantic functions**,
traditional code **native functions**, and **embeddings-based memory** unlocking
new potential and adding value to applications with AI.

Semantic Kernel incorporates cutting-edge design patterns from the latest in AI
research. This enables developers to augment their applications with advanced
capabilities, such as prompt engineering, prompt chaining, retrieval-augmented
generation, contextual and long-term vectorized memory, embeddings,
summarization, zero or few-shot learning, semantic indexing, recursive
reasoning, intelligent planning, and access to external knowledge stores and
proprietary data.

# Getting Started ⚡

- Learn more at the [documentation site](https://aka.ms/SK-Docs).
- Join the [Discord community](https://aka.ms/SKDiscord).
- Follow the team on [Semantic Kernel blog](https://aka.ms/sk/blog).
- Check out the [GitHub repository](https://github.com/microsoft/semantic-kernel) for the latest updates.

