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krypticmouseHigh-performance Rust framework for building Language Model applications
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DSRs (DSPy Rust) is a high-performance, ground-up rewrite of the DSPy framework in Rust, designed for building robust, efficient, and reliable Language Model (LM)-powered applications. It targets developers seeking a more performant and memory-safe foundation for their LLM projects, leveraging Rust's advanced features.
How It Works
DSRs utilizes Rust's strong type system, memory safety guarantees, and concurrency primitives to achieve superior performance and reliability compared to Python-based frameworks. Its architecture is modular, featuring core abstractions for LMs, Modules, and Signatures, alongside dedicated components for LM provider adapters, data structures, built-in predictors, an evaluation framework, and optimization tools. Signatures define clear input/output specifications, while Modules enable composable pipeline construction, and Predictors offer pre-built LM interaction patterns.
Quick Start & Requirements
dspy-rs to your Cargo.toml or use cargo add dsrs --package dspy-rs.OPENAI_API_KEY environment variable for default configurations. Local models (e.g., vLLM, Ollama) require separate setup.Highlighted Details
DataLoader provides typed loaders that ingest data directly into Example<S> structures, enforcing schema correctness.facet::Facet.reasoning field to predictions.Maintenance & Community
DSRs is under active development with a stabilizing API. Contributions are welcomed via a dedicated Contributing Guide. Community support is available on Discord.
Licensing & Compatibility
This project is licensed under the Apache License 2.0, which is permissive for commercial use and integration into closed-source projects.
Limitations & Caveats
DSRs is currently in a Beta Release. While the API is stabilizing, users should anticipate potential breaking changes as development continues.
3 days ago
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