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Auto-Instrumentation for AI Observability
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OpenInference is a set of conventions and plugins that is complimentary toOpenTelemetry to enable tracing of AI applications. OpenInference is natively supported byarize-phoenix, but can be used with any OpenTelemetry-compatible backend as well.
The OpenInference specification is edited in markdown files found in thespec directory. It's designed to provide insight into the invocation of LLMs and the surrounding application context such as retrieval from vector stores and the usage of external tools such as search engines or APIs. The specification is transport and file-format agnostic, and is intended to be used in conjunction with other specifications such as JSON, ProtoBuf, and DataFrames.
OpenInference provides a set of instrumentations for popular machine learning SDKs and frameworks in a variety of languages.
| Package | Description | Version |
|---|---|---|
openinference-semantic-conventions | Semantic conventions for tracing of LLM Apps. |  |
openinference-instrumentation-openai | OpenInference Instrumentation for OpenAI SDK. |  |
openinference-instrumentation-llama-index | OpenInference Instrumentation for LlamaIndex. |  |
openinference-instrumentation-dspy | OpenInference Instrumentation for DSPy. |  |
openinference-instrumentation-bedrock | OpenInference Instrumentation for AWS Bedrock. |  |
openinference-instrumentation-langchain | OpenInference Instrumentation for LangChain. |  |
openinference-instrumentation-mistralai | OpenInference Instrumentation for MistralAI. |  |
| Name | Description | Complexity Level |
|---|---|---|
| OpenAI SDK | OpenAI Python SDK, including chat completions and embeddings | Beginner |
| MistralAI SDK | MistraAI Python SDK | Beginner |
| LlamaIndex | LlamaIndex query engines | Beginner |
| DSPy | DSPy primitives and custom RAG modules | Beginner |
| Boto3 Bedrock Client | Boto3 Bedrock client | Beginner |
| LangChain | LangChain primitives and simple chains | Beginner |
| LlamaIndex + Next.js Chatbot | A fully functional chatbot using Next.js and a LlamaIndex FastAPI backend | Intermediate |
| LangServe | A LangChain application deployed with LangServe using custom metadata on a per-request basis | Intermediate |
| DSPy | A DSPy RAG application using FastAPI, Weaviate, and Cohere | Intermediate |
| Package | Description | Version |
|---|---|---|
@arizeai/openinference-semantic-conventions | Semantic conventions for tracing of LLM Apps. |  |
@arizeai/openinference-instrumentation-openai | OpenInference Instrumentation for OpenAI SDK. | |
@arizeai/openinference-instrumentation/langchain | OpenInference Instrumentation for LangChain.js. |
| Name | Description | Complexity Level |
|---|---|---|
| OpenAI SDK | OpenAI Node.js client | Beginner |
| LlamaIndex Express App | A fully functional LlamaIndex chatbot with a Next.js frontend and a LlamaIndex Express backend, instrumented usingopeninference-instrumentation-openai | Intermediate |
| LangChain OpenAI | A simple script to call OpenAI via LangChain, instrumented usingopeninference-instrumentation-langchain | Beginner |
| LangChain RAG Express App | A fully functional LangChain chatbot that uses RAG to answer user questions. It has a Next.js frontend and a LangChain Express backend, instrumented usingopeninference-instrumentation-langchain | Intermediate |
| Next.js + OpenAI | A Next.js 13 project bootstrapped withcreate-next-app that uses OpenAI to generate text | Beginner |
OpenInference supports the following destinations as span collectors.
- ✅Arize-Phoenix
- ✅Arize
- ✅ Any OTEL-compatible collector
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