{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence"}],"enrichment":{"capability":"Provides tokenizers, validation, and normalization utilities for working with Mistral AI models, supporting text, images, and tool calls with versioned tokenizers for backward compatibility.","skillfed_tags":["mistral-ai","tokenization","llm-utilities"],"use_cases":["Tokenize text and images before sending to Mistral models to verify token counts and optimize prompt engineering.","Validate and normalize API requests and tool calls to match Mistral's expected format before calling the model.","Build custom LLM applications that need consistent tokenization behavior across multiple model versions.","Integrate Mistral model support into frameworks that require standardized token counting and validation.","Develop local preprocessing pipelines that mirror Mistral's server-side validation without API calls."],"what_it_does":"mistral-common is a utility library that exposes Mistral AI's internal tokenization, validation, and normalization code for public use. It handles tokenization of text, images, and tool calls, plus request/response validation built on Pydantic. The library is versioned to guarantee backward compatibility with released models.\n\nThe package is designed for two audiences: developers integrating Mistral models into applications, and those building custom models who want to use Mistral's tokenization and validation approach. It ships with eight runtime dependencies (pydantic, requests, numpy, pillow, tiktoken, jsonschema, typing-extensions, pydantic-extra-types) and supports optional extras for image, audio, Hugging Face Hub integration, and experimental server mode.","worth_installing":"Yes. mistral-common is actively maintained, has no known vulnerabilities, and low install friction. Install it if you are building applications with Mistral models and need local tokenization, validation, or want to ensure token counts match what the API will see. The permissive Apache 2.0 license poses no restrictions. Skip it only if you are not using Mistral models or do not need pre-flight validation."},"id":"mistral-common","links":{"html":"https://skillfed.io/packages/mistral-common","md":"https://skillfed.io/packages/mistral-common.md","pypi":"https://pypi.org/project/mistral-common/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-23","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"mistral_common","python_support":"supports_current","summary":"Mistral-common is a library of common utilities for Mistral AI."},"popularity":{"monthly_downloads":8944595,"position":1573,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.11.7"}