IBM/spnl

Span Queries: What if we had a way to plan and optimize GenAI like we do for SQL?

51
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Established

This project helps AI developers optimize complex AI applications like Retrieval-Augmented Generation (RAG) and AI agents. It provides a way to define and execute 'span queries' that combine multiple AI inference calls, tool uses, and database lookups. Developers input these span queries and receive optimized execution plans that significantly reduce the cost of running these advanced AI workflows.

Use this if you are building sophisticated AI applications that involve chaining together multiple large language model interactions and need to drastically cut down on inference costs without sacrificing accuracy.

Not ideal if you are only running simple, single-prompt chat interactions or basic LLM calls without complex orchestration requirements.

AI-application-development LLM-cost-optimization AI-workflow-orchestration Agentic-AI-development RAG-optimization
No Package No Dependents
Maintenance 10 / 25
Adoption 10 / 25
Maturity 15 / 25
Community 16 / 25

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Stars

13

Forks

7

Language

Rust

License

Apache-2.0

Last pushed

Mar 09, 2026

Monthly downloads

110

Commits (30d)

0

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