LLMObs.annotate

This release enhances LLM Observability with features like prompt management, image support, and OpenAI Realtime API instrumentation. It also introduces safer ID generation in Lambda, OpenTelemetry integration, and improved exception profiling.

This release introduces significant enhancements to AI Guard, LLM Observability, and AppSec, including new features for handling audio, improving evaluation, and detecting LLM usage. It also brings instrumentation support for Ray Serve and Mistral AI, along with profiling improvements and bug fixes.

This release introduces significant enhancements to AI Guard, LLM Observability, and AppSec, including new features for handling audio in LLM messages, improved AI Guard controls, and enhanced detection of LLM usage in API endpoints. It also brings instrumentation support for Ray Serve and Mistral AI, along with various bug fixes and performance improvements.

This release introduces significant enhancements to AI Guard, LLM Observability (including audio support and sampling configuration), and adds tracing support for Ray Serve and Mistral AI client calls. It also includes bug fixes and infrastructure updates like a new normalized route tag for Tornado.

This release focuses on stability and correctness, primarily addressing several bug fixes related to LLM Observability, tracing race conditions, and code origin inspection stability.

This release introduces significant enhancements for LLM Observability, AI Guard integration, and CI Visibility, alongside fixing several critical bugs related to coverage and tracing instrumentation. A breaking change affects how HTTP status codes are reported for Azure CosmosDB spans.

This release introduces LLM Observability cost tagging and a configuration to exclude modules from lock profiling. It also fixes a startup deadlock related to Snowflake and resolves an issue with the lock profiler under gevent.

This release focuses on LLM Observability improvements, making size limits configurable via environment variables and fixing serialization issues for nested Pydantic models and return values in @llm decorated functions.

This release enhances LLM Observability by adding prompt retrieval, improved experiment span context, and dataset tagging capabilities. It also includes several bug fixes related to large dataset uploads and profiling initialization.

This major release introduces significant API breaking changes, removes support for Python 3.8 and 32-bit Linux, and adds an OpenFeature provider implementation. It also updates default tracing behavior for Django and removes several deprecated integrations and configuration methods.

This major release introduces significant breaking changes, including the removal of Python 3.8 support and deprecated APIs, while adding new features like OpenFeature provider support and enhanced LLM Observability capabilities.

This major release introduces significant API breaking changes, including the removal of Python 3.8 support, deprecated methods, and configuration variables. New features focus on AAP, profiling enhancements, and LLM Observability updates, while Django tracing defaults to a minimal mode.

This release introduces AI Guard support for LangChain, makes `ml_app` optional for LLM Observability, and includes numerous bug fixes across AAP, Django, asyncpg, exception replay, and CI Visibility.

This release introduces AI Guard support for LangChain and enhances LLM Observability by making `ml_app` optional and adding tool definition support to annotations. Numerous bug fixes address issues across AAP, Django, asyncpg, exception replay, and CI Visibility.

This release introduces AI Guard support for LangChain and enhances LLM Observability by making `ml_app` optional and adding tool definition annotation capabilities. Several bug fixes address issues in asyncpg, exception replay, LLM observability, and CI Visibility.

This release introduces significant new features for LLM Observability across multiple integrations (Bedrock, GenAI, OpenAI, VertexAI) and adds experimental OTLP log exporting support via OpenTelemetry. It also includes several bug fixes, notably around websocket span closing and sampling rules, and deprecates ddtrace.tracer.Pin.

This release introduces significant LLM Observability enhancements for tool usage across multiple integrations (Bedrock, GenAI, OpenAI, VertexAI) and adds experimental OTLP log exporting support. It also deprecates `ddtrace.tracer.Pin` and includes numerous bug fixes across tracing, AAP, and sampling.

This release focuses on performance improvements for profiling via upgrades to echion and optimizations to the stack sampler, alongside new features for LLM Observability and various tracing and profiling bug fixes.

This release focuses on performance improvements for profiling by upgrading `echion` and optimizing the stack sampler, alongside introducing support for custom evaluations in LLM Observability.

This release introduces significant enhancements to LLM Observability, including Deepseek support and improved context management, alongside new tracing features like inferred AWS API Gateway spans and better GraphQL error reporting. Numerous bug fixes address issues across ASM, IAST, Profiling, and Tracing components.

This release introduces significant enhancements to LLM Observability, including improved context management and Deepseek labeling, alongside new tracing features like inferred AWS API Gateway spans and better GraphQL error reporting. Numerous bug fixes address issues across ASM, IAST, Profiling, and core Tracing functionality.

Version 3.0.0 drops support for Python 3.7 and removes numerous deprecated interfaces across Tracing and LLM Observability modules. This release standardizes CI Visibility plugins and updates several environment variables.