Metadata-Version: 2.4
Name: lumis-ai
Version: 0.1.1a7
Summary: An AI agent framework for building LLM-powered applications
Project-URL: Homepage, https://github.com/tareksanger/lumis
Project-URL: Repository, https://github.com/tareksanger/lumis
Project-URL: Issues, https://github.com/tareksanger/lumis/issues
Author-email: tareksanger <23141675+tareksanger@users.noreply.github.com>
License-Expression: MIT
License-File: LICENSE
Keywords: agents,ai,embeddings,llm,nlp,vector-search
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
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Requires-Dist: torch>=2.5.0
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Requires-Dist: wikipedia>=1.4.0
Provides-Extra: django
Requires-Dist: django>=4.2; extra == 'django'
Provides-Extra: search
Requires-Dist: arxiv>=0.5.0; extra == 'search'
Requires-Dist: pytrends>=4.5.0; extra == 'search'
Requires-Dist: tavily-python>=0.3.0; extra == 'search'
Requires-Dist: yfinance>=0.2.0; extra == 'search'
Provides-Extra: spacy
Requires-Dist: pytextrank>=3.2.0; extra == 'spacy'
Requires-Dist: spacy-llm>=0.7.2; extra == 'spacy'
Requires-Dist: spacy<3.8.0,>=3.7.0; extra == 'spacy'
Description-Content-Type: text/markdown

# lumis

An AI agent framework for building LLM-powered applications with multi-provider LLM support, graph-based workflows, vector storage, and NLP pipelines.

## Features

- **Multi-provider LLMs** — Unified interface across OpenAI, Gemini, Ollama, and Perplexity with middleware support and automatic token counting
- **Agents** — ReAct, research, and graph-based agent architectures with event-driven lifecycle hooks
- **Graph Workflows** — Composable, stateful DAG execution with sync and async node support
- **Embeddings** — OpenAI and HuggingFace embedding backends
- **Vector Storage** — Chroma and FAISS vector database integrations
- **NLP** — Named entity recognition, summarization, semantic parsing, and coreference resolution
- **Search & Tools** — Web scraping, arXiv, Wikipedia, Yahoo Finance, Google Trends, and Tavily integrations
- **Memory** — Pluggable memory backends for stateful agent conversations

## Installation

```bash
pip install lumis-ai
```

### Optional extras

Some integrations are opt-in to keep the base install lighter:

| Extra      | What it adds                                  | Install                           |
|------------|-----------------------------------------------|-----------------------------------|
| `spacy`    | NER, fact extraction, coreference resolution  | `pip install lumis-ai[spacy]`     |
| `search`   | arXiv, Google Trends, Yahoo Finance           | `pip install lumis-ai[search]`    |
| `django`   | Django ORM memory backend                     | `pip install lumis-ai[django]`    |

The `spacy` extra requires language models. After installing, download them:

```bash
python -m spacy download en_core_web_lg
python -m spacy download en_core_web_trf
```

## License

MIT — see [LICENSE](LICENSE) for details.
