LOTUS is a semantic query engine designed for efficient LLM-powered data processing, targeting data scientists and engineers who need to build complex reasoning pipelines over structured and unstructured data. It offers a declarative, Pandas-like API with semantic operators that leverage natural language expressions for data transformations, simplifying the creation of AI-driven analytics.

How It Works

LOTUS implements a semantic operator model, extending traditional relational operators with natural language predicates. This approach allows users to define data operations (like joins, filters, and aggregations) using high-level, human-readable expressions. The engine then optimizes and executes these operations using various AI-based algorithms, abstracting away the underlying LLM complexities and enabling flexible, composable AI pipelines.

Quick Start & Requirements

• Installation: pip install lotus-ai (stable) or pip install git+https://github.com/lotus-data/lotus.git@main (latest).
• Prerequisites: Python 3.10, Conda recommended. For Mac users, specific Faiss installations (CPU or GPU) are required. Requires LLM API keys (e.g., OpenAI, Ollama, vLLM) configured via lotus.settings.configure(lm=lm).
• Resources: LLM API usage costs apply.
• Docs/Demo: Colab tutorial, Documentation, Examples.

Highlighted Details

• Supports a wide range of LLMs via LiteLLM and SentenceTransformers for retrieval/reranking.
• Offers semantic operators like sem_join, sem_filter, sem_map, sem_extract, sem_agg, sem_topk, sem_sim_join, and sem_search.
• Integrates seamlessly with Pandas DataFrames.
• Leverages natural language expressions for defining complex data operations.

Maintenance & Community

• Active development with contributions from Stanford researchers.
• Community support via [Slack](https://join.slack.com/t/lotus-community/shared_invite/zt-2h940935p-7f84494700738630316073000373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373076063730760637307606373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