{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring"}],"enrichment":{"capability":"Automatically captures and traces calls to the Mistral AI API using OpenTelemetry, recording request and response data as span attributes for observability and debugging.","skillfed_tags":["observability","llm-tracing","mistral-ai"],"use_cases":["Debug Mistral API calls in development by inspecting prompts and responses in your trace backend","Monitor production LLM applications to detect latency, errors, or unexpected model behavior","Correlate Mistral API calls with other application traces for end-to-end request tracing","Audit what data is being sent to Mistral for compliance or privacy reviews","Evaluate model output quality by reviewing completions stored in trace spans"],"what_it_does":"This package is an OpenTelemetry instrumentation plugin that automatically intercepts and traces calls made through the official Mistral AI Python library. Once initialized with a single call to `MistralAiInstrumentor().instrument()`, it captures request and response data as span attributes, giving you visibility into what your LLM application is sending to and receiving from Mistral's endpoints.\n\nBy default, it logs prompts, completions, and embeddings to trace spans\u2014useful for debugging and understanding model behavior. However, you can disable this content logging by setting the `TRACELOOP_TRACE_CONTENT` environment variable to `false` if you need to protect sensitive user data or reduce trace size. The instrumentation integrates with your existing OpenTelemetry collector setup, so traces flow into whatever backend you're already using.","worth_installing":"Yes, if you are already using OpenTelemetry and the Mistral AI library. Installation is straightforward, maintenance is active, and there are no known vulnerabilities. The permissive Apache-2.0 license poses no barrier. The main consideration is whether your observability stack is already OpenTelemetry-based; if not, you would need to set that up first. Privacy-conscious teams should enable `TRACELOOP_TRACE_CONTENT=false` to avoid logging sensitive prompts."},"id":"opentelemetry-instrumentation-mistralai","links":{"html":"https://skillfed.io/packages/opentelemetry-instrumentation-mistralai","md":"https://skillfed.io/packages/opentelemetry-instrumentation-mistralai.md","pypi":"https://pypi.org/project/opentelemetry-instrumentation-mistralai/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-10","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"opentelemetry-instrumentation-mistralai","python_support":"supports_current","summary":"OpenTelemetry Mistral AI instrumentation"},"popularity":{"monthly_downloads":6833585,"position":1838,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"0.62.3"}