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Forces model-generated tool call arguments to match a JSON Schema during decoding, preventing malformed output.
Distinct from Constrained Decoding: Distinct from general Constrained Decoding: focuses specifically on tool call argument schemas rather than arbitrary output formats.
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mistral.rs is an inference engine for large language models that runs locally and exposes models behind OpenAI and Anthropic-compatible APIs. It serves as a multi-model serving platform, capable of loading several models in a single server process with per-request routing and on-demand loading and unloading. The engine supports multimodal inference, processing text alongside images, video, audio, and speech inputs, and includes a quantized model deployment runtime that reduces memory use and speeds up inference on consumer hardware. The project distinguishes itself through an agentic tool exe
Enforces JSON Schema on tool call arguments during decoding to prevent malformed output.