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Arize Phoenix ist die Open-Source-Plattform von Arize für KI-Observability, entwickelt für Experimente, Evaluierung und Fehleranalyse. Für verwaltete Produktions-Workflows bietet Arize zusätzlich [Arize AX](https://arize.com/products/ax/?utm_source=github&utm_medium=community&utm_campaign=px-to-ax&utm_content=readme-de) an. Phoenix bietet: - [**_Tracing_**](https://arize.com/docs/phoenix/tracing/llm-traces) - Verfolgen Sie das Laufzeitverhalten Ihrer LLM-Anwendung mit OpenTelemetry-basierter Instrumentierung. - [**_Evaluierung_**](https://arize.com/docs/phoenix/evaluation/llm-evals) - Nutzen Sie LLMs, um die Leistung Ihrer Anwendung mit Evals für Antworten und Retrieval zu bewerten. - [**_Datasets_**](https://arize.com/docs/phoenix/datasets-and-experiments/overview-datasets) - Erstellen Sie versionierte Datasets mit Beispielen für Experimente, Evaluierung und Fine-Tuning. - [**_Experimente_**](https://arize.com/docs/phoenix/datasets-and-experiments/overview-datasets#experiments) - Verfolgen und bewerten Sie Änderungen an Prompts, LLMs und Retrieval. - [**_Playground_**](https://arize.com/docs/phoenix/prompt-engineering/overview-prompts)- Optimieren Sie Prompts, vergleichen Sie Modelle, passen Sie Parameter an und spielen Sie getracte LLM-Aufrufe erneut ab. - [**_Prompt-Management_**](https://arize.com/docs/phoenix/prompt-engineering/overview-prompts/prompt-management)- Verwalten und testen Sie Prompt-Änderungen systematisch mit Versionskontrolle, Tagging und Experimenten. - [**_PXI (Phoenix Intelligence)_**](https://arize.com/docs/phoenix/pxi) - Ein in Phoenix integrierter KI-Engineering-Agent zum Debuggen von Traces, zum iterativen Verbessern von Prompts und zur Navigation im Produkt. - [**_Remote-MCP-Server_**](https://arize.com/docs/phoenix/integrations/mcp#remote-mcp-server) - Verbinden Sie Claude Code, Cursor und andere MCP-Clients direkt mit dem `/mcp`-Endpunkt Ihrer Phoenix-Instanz, um Traces, Datasets, Experimente und mehr abzufragen.

Phoenix ist anbieter- und sprachunabhängig und unterstützt gängige Frameworks ([OpenAI Agents SDK](https://arize.com/docs/phoenix/tracing/integrations-tracing/openai-agents-sdk), [Claude Agent SDK](https://arize.com/docs/phoenix/integrations/python/claude-agent-sdk), [LangGraph](https://arize.com/docs/phoenix/tracing/integrations-tracing/langchain), [Vercel AI SDK](https://arize.com/docs/phoenix/tracing/integrations-tracing/vercel-ai-sdk), [Mastra](https://arize.com/docs/phoenix/integrations/typescript/mastra), [CrewAI](https://arize.com/docs/phoenix/tracing/integrations-tracing/crewai), [LlamaIndex](https://arize.com/docs/phoenix/tracing/integrations-tracing/llamaindex), [DSPy](https://arize.com/docs/phoenix/tracing/integrations-tracing/dspy)) sowie LLM-Anbieter ([OpenAI](https://arize.com/docs/phoenix/tracing/integrations-tracing/openai), [Anthropic](https://arize.com/docs/phoenix/tracing/integrations-tracing/anthropic), [Google GenAI](https://arize.com/docs/phoenix/tracing/integrations-tracing/google-genai), [Google ADK](https://arize.com/docs/phoenix/integrations/llm-providers/google-gen-ai/google-adk-tracing), [AWS Bedrock](https://arize.com/docs/phoenix/tracing/integrations-tracing/bedrock), [OpenRouter](https://arize.com/docs/phoenix/integrations/python/openrouter), [LiteLLM](https://arize.com/docs/phoenix/tracing/integrations-tracing/litellm) und weitere) direkt ab Werk. Details zur automatischen Instrumentierung finden Sie im Projekt [OpenInference](https://github.com/Arize-ai/openinference). Phoenix läuft praktisch überall – auf Ihrem lokalen Rechner, in einem containerisierten Deployment oder in der Cloud. Unter [Umgebungen](https://arize.com/docs/phoenix/self-hosting) finden Sie eine Anleitung zu jeder Option, oder Sie springen direkt zum [Tracing-Schnellstart](https://arize.com/docs/phoenix/get-started/get-started-tracing). > [!NOTE] > Phoenix ist Open Source und selbst gehostet. Als verwaltete Plattform bietet Arize [Arize AX](https://arize.com/products/ax/?utm_source=github&utm_medium=community&utm_campaign=px-to-ax&utm_content=readme-de) an – dieselbe OpenTelemetry-/OpenInference-Instrumentierung funktioniert mit beiden. Siehe den [vollständigen Vergleich](https://arize.com/docs/phoenix/resources/frequently-asked-questions/what-is-the-difference-between-phoenix-and-arize). ## Inhaltsverzeichnis - [Lokal ausführen](#lokal-ausführen) - [Ihre Anwendung tracen](#ihre-anwendung-tracen) - [Deployment](#deployment) - [Pakete](#pakete) - [Tracing-Integrationen](#tracing-integrationen) - [Sandboxes](#sandboxes) - [Für Menschen und Coding-Agenten](#für-menschen-und-coding-agenten) - [Sicherheit & Datenschutz](#sicherheit--datenschutz) - [Community](#community) ## Lokal ausführen Installieren Sie Phoenix über `pip` oder `conda` und Sie erhalten ein voll funktionsfähiges Phoenix. Alle Installations- und Hosting-Optionen finden Sie in der [Installationsanleitung](https://arize.com/docs/phoenix). ```shell pip install arize-phoenix phoenix serve ``` Oder führen Sie es ohne Installation mit [`uvx`](https://docs.astral.sh/uv/) aus: ```shell uvx arize-phoenix serve ``` ## Ihre Anwendung tracen Am schnellsten senden Sie Traces, indem Sie Ihren [Coding-Agenten](https://arize.com/docs/phoenix/integrations/developer-tools/coding-agents) (Claude Code, Codex, Cursor und andere) Ihre App instrumentieren lassen. Führen Sie in Ihrem Projektverzeichnis Folgendes aus: ```shell npx @arizeai/phoenix-cli setup # oder, wenn Phoenix installiert ist: px setup ``` Das Setup erkennt Ihr Framework und Ihren LLM-Anbieter, installiert die passende [OpenInference](https://github.com/Arize-ai/openinference)-Instrumentierung und richtet den Trace-Export ein. Sie richten es lieber im Code ein? Siehe die [Tracing-Dokumentation](https://arize.com/docs/phoenix/tracing/llm-traces). ## Deployment Phoenix-Container-Images sind über [Docker Hub](https://hub.docker.com/r/arizephoenix/phoenix) verfügbar und können mit Docker oder über das [Helm-Chart](https://github.com/Arize-ai/phoenix/tree/main/helm) mit Kubernetes bereitgestellt werden. Informationen zu Docker Compose, Kubernetes/Helm und weiteren Deployment-Optionen finden Sie in der [Dokumentation zum Self-Hosting](https://arize.com/docs/phoenix/self-hosting).

> [!NOTE] > Die Google-Cloud-Schaltfläche baut Phoenix in Cloud Shell aus dem Quellcode, statt das vorgefertigte Docker-Hub-Image bereitzustellen. Die Azure-Vorlage stellt unverschlüsseltes HTTP bereit (Azure Container Instances terminiert kein TLS) – schalten Sie vor dem Produktiveinsatz einen TLS-Proxy wie ein Application Gateway davor. ## Pakete Das Paket `arize-phoenix` enthält die gesamte Phoenix-Plattform. Wenn Sie die Phoenix-Plattform bereits bereitgestellt haben, gibt es jedoch schlanke Python-Unterpakete und TypeScript-Pakete, die zusammen mit der Plattform verwendet werden können. ### Python-Unterpakete | Paket | Version & Doku | Beschreibung | | --------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------ | | [arize-phoenix-otel](https://github.com/Arize-ai/phoenix/tree/main/packages/phoenix-otel) | [![PyPI Version](https://img.shields.io/pypi/v/arize-phoenix-otel)](https://pypi.org/project/arize-phoenix-otel/) [![Docs](https://img.shields.io/badge/docs-blue?logo=readthedocs&logoColor=white)](https://arize-phoenix.readthedocs.io/projects/otel/en/latest/index.html) | Stellt einen schlanken Wrapper um OpenTelemetry-Primitive mit auf Phoenix abgestimmten Standardwerten bereit | | [arize-phoenix-client](https://github.com/Arize-ai/phoenix/tree/main/packages/phoenix-client) | [![PyPI Version](https://img.shields.io/pypi/v/arize-phoenix-client)](https://pypi.org/project/arize-phoenix-client/) [![Docs](https://img.shields.io/badge/docs-blue?logo=readthedocs&logoColor=white)](https://arize-phoenix.readthedocs.io/projects/client/en/latest/index.html) | Schlanker Client für die Interaktion mit dem Phoenix-Server über dessen OpenAPI-REST-Schnittstelle | | [arize-phoenix-evals](https://github.com/Arize-ai/phoenix/tree/main/packages/phoenix-evals) | [![PyPI Version](https://img.shields.io/pypi/v/arize-phoenix-evals)](https://pypi.org/project/arize-phoenix-evals/) [![Docs](https://img.shields.io/badge/docs-blue?logo=readthedocs&logoColor=white)](https://arize-phoenix.readthedocs.io/projects/evals/en/latest/index.html) | Werkzeuge zur Evaluierung von LLM-Anwendungen, einschließlich RAG-Relevanz, Antwortrelevanz und mehr | ### TypeScript-Unterpakete | Paket | Version & Doku | Beschreibung | | --------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------ | | [@arizeai/phoenix-otel](https://github.com/Arize-ai/phoenix/tree/main/js/packages/phoenix-otel) | [![NPM Version](https://img.shields.io/npm/v/%40arizeai%2Fphoenix-otel)](https://www.npmjs.com/package/@arizeai/phoenix-otel) [![Docs](https://img.shields.io/badge/docs-blue?logo=typescript&logoColor=white)](https://arize-ai.github.io/phoenix/) | Stellt einen schlanken Wrapper um OpenTelemetry-Primitive mit auf Phoenix abgestimmten Standardwerten bereit | | [@arizeai/phoenix-client](https://github.com/Arize-ai/phoenix/tree/main/js/packages/phoenix-client) | [![NPM Version](https://img.shields.io/npm/v/%40arizeai%2Fphoenix-client)](https://www.npmjs.com/package/@arizeai/phoenix-client) [![Docs](https://img.shields.io/badge/docs-blue?logo=typescript&logoColor=white)](https://arize-ai.github.io/phoenix/) | Client für die Arize-Phoenix-API | | [@arizeai/phoenix-evals](https://github.com/Arize-ai/phoenix/tree/main/js/packages/phoenix-evals) | [![NPM Version](https://img.shields.io/npm/v/%40arizeai%2Fphoenix-evals)](https://www.npmjs.com/package/@arizeai/phoenix-evals) [![Docs](https://img.shields.io/badge/docs-blue?logo=typescript&logoColor=white)](https://arize-ai.github.io/phoenix/) | TypeScript-Evaluierungsbibliothek für LLM-Anwendungen (Alpha-Version) | | [@arizeai/phoenix-cli](https://github.com/Arize-ai/phoenix/tree/main/js/packages/phoenix-cli) | [![NPM Version](https://img.shields.io/npm/v/%40arizeai%2Fphoenix-cli)](https://www.npmjs.com/package/@arizeai/phoenix-cli) [![Docs](https://img.shields.io/badge/docs-blue?logo=typescript&logoColor=white)](https://arize.com/docs/phoenix/sdk-api-reference/typescript/arizeai-phoenix-cli) | CLI zum Abrufen von Traces, Datasets und Experimenten zur Verwendung mit Claude Code, Cursor und anderen Coding-Agenten | ## Tracing-Integrationen Phoenix basiert auf OpenTelemetry und ist anbieter-, sprach- und frameworkunabhängig. Details zu Tracing-Integrationen und Beispielanwendungen finden Sie im Projekt [OpenInference](https://github.com/Arize-ai/openinference) und in der [Integrationsdokumentation](https://arize.com/docs/phoenix/integrations). **Python-Integrationen** | | Integration | Paket | Version | |:---:|---|---|---| |

| [OpenAI](https://arize.com/docs/phoenix/tracing/integrations-tracing/openai) | `openinference-instrumentation-openai` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-openai.svg)](https://pypi.python.org/pypi/openinference-instrumentation-openai) | |

| [OpenAI Agents](https://arize.com/docs/phoenix/tracing/integrations-tracing/openai-agents-sdk) | `openinference-instrumentation-openai-agents` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-openai-agents.svg)](https://pypi.python.org/pypi/openinference-instrumentation-openai-agents) | |

| [LlamaIndex](https://arize.com/docs/phoenix/tracing/integrations-tracing/llamaindex) | `openinference-instrumentation-llama-index` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-llama-index.svg)](https://pypi.python.org/pypi/openinference-instrumentation-llama-index) | | | [DSPy](https://arize.com/docs/phoenix/tracing/integrations-tracing/dspy) | `openinference-instrumentation-dspy` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-dspy.svg)](https://pypi.python.org/pypi/openinference-instrumentation-dspy) | |

| [AWS Bedrock](https://arize.com/docs/phoenix/tracing/integrations-tracing/bedrock) | `openinference-instrumentation-bedrock` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-bedrock.svg)](https://pypi.python.org/pypi/openinference-instrumentation-bedrock) | |

| [LangChain](https://arize.com/docs/phoenix/tracing/integrations-tracing/langchain) | `openinference-instrumentation-langchain` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-langchain.svg)](https://pypi.python.org/pypi/openinference-instrumentation-langchain) | |

| [LangGraph](https://arize.com/docs/phoenix/integrations/python/langgraph) | `openinference-instrumentation-langchain` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-langchain.svg)](https://pypi.python.org/pypi/openinference-instrumentation-langchain) | |

| [MistralAI](https://arize.com/docs/phoenix/tracing/integrations-tracing/mistralai) | `openinference-instrumentation-mistralai` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-mistralai.svg)](https://pypi.python.org/pypi/openinference-instrumentation-mistralai) | |

| [Cohere](https://arize.com/docs/phoenix/integrations/llm-providers/cohere) | `openinference-instrumentation-cohere` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-cohere.svg)](https://pypi.python.org/pypi/openinference-instrumentation-cohere) | |

| [Together AI](https://arize.com/docs/phoenix/integrations/llm-providers/together) | `openinference-instrumentation-together` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-together.svg)](https://pypi.python.org/pypi/openinference-instrumentation-together) | |

| [Ollama](https://arize.com/docs/phoenix/integrations/llm-providers/ollama) | `openinference-instrumentation-ollama` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-ollama.svg)](https://pypi.python.org/pypi/openinference-instrumentation-ollama) | |

| [Google GenAI](https://arize.com/docs/phoenix/tracing/integrations-tracing/google-gen-ai) | `openinference-instrumentation-google-genai` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-google-genai.svg)](https://pypi.python.org/pypi/openinference-instrumentation-google-genai) | |

| [Google ADK](https://arize.com/docs/phoenix/integrations/llm-providers/google-gen-ai/google-adk-tracing) | `openinference-instrumentation-google-adk` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-google-adk.svg)](https://pypi.python.org/pypi/openinference-instrumentation-google-adk) | | | [Guardrails](https://arize.com/docs/phoenix/tracing/integrations-tracing/guardrails) | `openinference-instrumentation-guardrails` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-guardrails.svg)](https://pypi.python.org/pypi/openinference-instrumentation-guardrails) | |

| [VertexAI](https://arize.com/docs/phoenix/tracing/integrations-tracing/vertexai) | `openinference-instrumentation-vertexai` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-vertexai.svg)](https://pypi.python.org/pypi/openinference-instrumentation-vertexai) | |

| [CrewAI](https://arize.com/docs/phoenix/tracing/integrations-tracing/crewai) | `openinference-instrumentation-crewai` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-crewai.svg)](https://pypi.python.org/pypi/openinference-instrumentation-crewai) | | | [Haystack](https://arize.com/docs/phoenix/tracing/integrations-tracing/haystack) | `openinference-instrumentation-haystack` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-haystack.svg)](https://pypi.python.org/pypi/openinference-instrumentation-haystack) | | | [LiteLLM](https://arize.com/docs/phoenix/tracing/integrations-tracing/litellm) | `openinference-instrumentation-litellm` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-litellm.svg)](https://pypi.python.org/pypi/openinference-instrumentation-litellm) | | | [OpenRouter](https://arize.com/docs/phoenix/integrations/llm-providers/openrouter) | `openinference-instrumentation-openai` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-openai.svg)](https://pypi.python.org/pypi/openinference-instrumentation-openai) | | | [OrcaRouter](https://arize.com/docs/phoenix/integrations/llm-providers/orcarouter) | `openinference-instrumentation-openai` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-openai.svg)](https://pypi.python.org/pypi/openinference-instrumentation-openai) | |

| [Groq](https://arize.com/docs/phoenix/tracing/integrations-tracing/groq) | `openinference-instrumentation-groq` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-groq.svg)](https://pypi.python.org/pypi/openinference-instrumentation-groq) | | | [Instructor](https://arize.com/docs/phoenix/tracing/integrations-tracing/instructor) | `openinference-instrumentation-instructor` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-instructor.svg)](https://pypi.python.org/pypi/openinference-instrumentation-instructor) | |

| [Anthropic](https://arize.com/docs/phoenix/tracing/integrations-tracing/anthropic) | `openinference-instrumentation-anthropic` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-anthropic.svg)](https://pypi.python.org/pypi/openinference-instrumentation-anthropic) | |

| [Smolagents](https://huggingface.co/docs/smolagents/en/tutorials/inspect_runs) | `openinference-instrumentation-smolagents` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-smolagents.svg)](https://pypi.python.org/pypi/openinference-instrumentation-smolagents) | | | [Agno](https://arize.com/docs/phoenix/tracing/integrations-tracing/agno) | `openinference-instrumentation-agno` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-agno.svg)](https://pypi.python.org/pypi/openinference-instrumentation-agno) | | | [BeeAI](https://arize.com/docs/phoenix/integrations/python/beeai) | `openinference-instrumentation-beeai` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-beeai.svg)](https://pypi.python.org/pypi/openinference-instrumentation-beeai) | | | [Strands Agents](https://arize.com/docs/phoenix/integrations/python/strands-agents) | `openinference-instrumentation-strands-agents` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-strands-agents.svg)](https://pypi.python.org/pypi/openinference-instrumentation-strands-agents) | | | [Restate](https://arize.com/docs/phoenix/integrations/python/restate) | `openinference-instrumentation-openai-agents` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-openai-agents.svg)](https://pypi.python.org/pypi/openinference-instrumentation-openai-agents) | |

| [MCP](https://arize.com/docs/phoenix/tracing/integrations-tracing/model-context-protocol-mcp) | `openinference-instrumentation-mcp` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-mcp.svg)](https://pypi.python.org/pypi/openinference-instrumentation-mcp) | |

| [Pydantic AI](https://arize.com/docs/phoenix/integrations/python/pydantic) | `openinference-instrumentation-pydantic-ai` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-pydantic-ai.svg)](https://pypi.python.org/pypi/openinference-instrumentation-pydantic-ai) | | | [AG2](https://arize.com/docs/phoenix/integrations/python/ag2) | `openinference-instrumentation-ag2` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-ag2.svg)](https://pypi.python.org/pypi/openinference-instrumentation-ag2) | | | [Autogen AgentChat](https://arize.com/docs/phoenix/integrations/frameworks/autogen/autogen-tracing) | `openinference-instrumentation-autogen-agentchat` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-autogen-agentchat.svg)](https://pypi.python.org/pypi/openinference-instrumentation-autogen-agentchat) | | | [Portkey](https://arize.com/docs/phoenix/integrations/portkey) | `openinference-instrumentation-portkey` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-portkey.svg)](https://pypi.python.org/pypi/openinference-instrumentation-portkey) | | | [Agent Spec](https://arize.com/docs/phoenix/tracing/integrations-tracing/agentspec) | `openinference-instrumentation-agentspec` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-agentspec.svg)](https://pypi.python.org/pypi/openinference-instrumentation-agentspec) | |

| [Claude Agent SDK](https://arize.com/docs/phoenix/integrations/python/claude-agent-sdk) | `openinference-instrumentation-claude-agent-sdk` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-claude-agent-sdk.svg)](https://pypi.python.org/pypi/openinference-instrumentation-claude-agent-sdk) | | | [TypeSafe AI](https://arize.com/docs/phoenix/integrations/llm-providers/typesafe/typesafe-python) | `openinference-instrumentation-typesafe` | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-typesafe.svg)](https://pypi.python.org/pypi/openinference-instrumentation-typesafe) | ## Span-Prozessoren Normalisieren und konvertieren Sie Daten aus anderen Instrumentierungsbibliotheken, indem Sie Span-Prozessoren hinzufügen, die die Daten vereinheitlichen. | Paket | Beschreibung | Version | | ----------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | [`openinference-instrumentation-openlit`](https://pypi.org/project/openinference-instrumentation-openlit/) | OpenInference-Span-Prozessor für OpenLIT-Traces. | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-openlit.svg)](https://pypi.python.org/pypi/openinference-instrumentation-openlit) | | [`openinference-instrumentation-openllmetry`](https://pypi.org/project/openinference-instrumentation-openllmetry/) | OpenInference-Span-Prozessor für OpenLLMetry-(Traceloop-)Traces. | [![PyPI Version](https://img.shields.io/pypi/v/openinference-instrumentation-openllmetry.svg)](https://pypi.python.org/pypi/openinference-instrumentation-openllmetry) | ### JavaScript-Integrationen | | Integration | Paket | Version | | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------------------- | --------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | |

| [OpenAI](https://arize.com/docs/phoenix/tracing/integrations-tracing/openai-node-sdk) | `@arizeai/openinference-instrumentation-openai` | [![NPM Version](https://img.shields.io/npm/v/@arizeai/openinference-instrumentation-openai.svg)](https://www.npmjs.com/package/@arizeai/openinference-instrumentation-openai) | |

| [OpenAI Agents](https://arize.com/docs/phoenix/integrations/typescript/openai-agents) | `@arizeai/openinference-instrumentation-openai-agents` | [![NPM Version](https://img.shields.io/npm/v/@arizeai%2Fopeninference-instrumentation-openai-agents.svg)](https://www.npmjs.com/package/@arizeai/openinference-instrumentation-openai-agents) | |

| [LangChain.js](https://arize.com/docs/phoenix/tracing/integrations-tracing/langchain) | `@arizeai/openinference-instrumentation-langchain` | [![NPM Version](https://img.shields.io/npm/v/@arizeai/openinference-instrumentation-langchain.svg)](https://www.npmjs.com/package/@arizeai/openinference-instrumentation-langchain) | | | [TanStack AI](https://arize.com/docs/phoenix/integrations/typescript/tanstack-ai) | `@arizeai/openinference-tanstack-ai` | [![NPM Version](https://img.shields.io/npm/v/@arizeai/openinference-tanstack-ai.svg)](https://www.npmjs.com/package/@arizeai/openinference-tanstack-ai) | |

| [Vercel AI SDK](https://arize.com/docs/phoenix/tracing/integrations-tracing/vercel-ai-sdk) | `@arizeai/openinference-vercel` | [![NPM Version](https://img.shields.io/npm/v/@arizeai/openinference-vercel)](https://www.npmjs.com/package/@arizeai/openinference-vercel) | | | [BeeAI](https://arize.com/docs/phoenix/tracing/integrations-tracing/beeai) | `@arizeai/openinference-instrumentation-beeai` | [![NPM Version](https://img.shields.io/npm/v/@arizeai/openinference-instrumentation-beeai.svg)](https://www.npmjs.com/package/@arizeai/openinference-instrumentation-beeai) | |

| [Claude Agent SDK](https://arize.com/docs/phoenix/integrations/typescript/claude-agent-sdk) | `@arizeai/openinference-instrumentation-claude-agent-sdk` | [![NPM Version](https://img.shields.io/npm/v/@arizeai%2Fopeninference-instrumentation-claude-agent-sdk.svg)](https://www.npmjs.com/package/@arizeai/openinference-instrumentation-claude-agent-sdk) | |

| [Mastra](https://arize.com/docs/phoenix/integrations/typescript/mastra) | `@mastra/arize` | [![NPM Version](https://img.shields.io/npm/v/@mastra/arize.svg)](https://www.npmjs.com/package/@mastra/arize) | |

| [MCP](https://arize.com/docs/phoenix/integrations/typescript/mcp) | `@arizeai/openinference-instrumentation-mcp` | [![NPM Version](https://img.shields.io/npm/v/@arizeai%2Fopeninference-instrumentation-mcp.svg)](https://www.npmjs.com/package/@arizeai/openinference-instrumentation-mcp) | | | [TypeSafe AI](https://arize.com/docs/phoenix/integrations/llm-providers/typesafe/typesafe-typescript) | `@arizeai/openinference-instrumentation-typesafe` | [![NPM Version](https://img.shields.io/npm/v/@arizeai%2Fopeninference-instrumentation-typesafe.svg)](https://www.npmjs.com/package/@arizeai/openinference-instrumentation-typesafe) | ### Java-Integrationen | | Integration | Paket | Version | | :-------------------------------------------------------------------------------------------------: | --------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | |

| [LangChain4j](https://github.com/Arize-ai/openinference/tree/main/java/instrumentation/openinference-instrumentation-langchain4j) | `openinference-instrumentation-langchain4j` | [![Maven Central](https://img.shields.io/maven-central/v/com.arize/openinference-instrumentation-langchain4j.svg)](https://central.sonatype.com/artifact/com.arize/openinference-instrumentation-langchain4j) | | | SpringAI | `openinference-instrumentation-springAI` | [![Maven Central](https://img.shields.io/maven-central/v/com.arize/openinference-instrumentation-springAI.svg)](https://central.sonatype.com/artifact/com.arize/openinference-instrumentation-springAI) | |

| [Arconia](https://docs.arconia.io/arconia/latest/observability/semantic-conventions/openinference/) für Spring AI | `io.arconia:arconia-openinference-semantic-conventions` | [![Maven Central](https://img.shields.io/maven-central/v/io.arconia/arconia-openinference-ai-semantic-conventions.svg)](https://central.sonatype.com/artifact/io.arconia/arconia-openinference-ai-semantic-conventions) | |

| [Google ADK](https://arize.com/docs/phoenix/integrations/java/google-adk/google-adk-tracing) | `openinference-instrumentation-adk-java` | [![Maven Central](https://img.shields.io/maven-central/v/com.arize/openinference-instrumentation-adk-java.svg)](https://central.sonatype.com/artifact/com.arize/openinference-instrumentation-adk-java) | ### Go-Integrationen | | Integration | Paket | Version | | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | |

| [OpenAI](https://github.com/Arize-ai/openinference/tree/main/go/openinference-instrumentation-openai-go) | `github.com/Arize-ai/openinference/go/openinference-instrumentation-openai-go` | [![Go Reference](https://pkg.go.dev/badge/github.com/Arize-ai/openinference/go/openinference-instrumentation-openai-go.svg)](https://pkg.go.dev/github.com/Arize-ai/openinference/go/openinference-instrumentation-openai-go) | |

| [Anthropic](https://github.com/Arize-ai/openinference/tree/main/go/openinference-instrumentation-anthropic-sdk-go) | `github.com/Arize-ai/openinference/go/openinference-instrumentation-anthropic-sdk-go` | [![Go Reference](https://pkg.go.dev/badge/github.com/Arize-ai/openinference/go/openinference-instrumentation-anthropic-sdk-go.svg)](https://pkg.go.dev/github.com/Arize-ai/openinference/go/openinference-instrumentation-anthropic-sdk-go) | ### Plattformen | | Plattform | Beschreibung | Doku | | :----------------------------------------------------------------------------------------------: | -------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------- | | | [BeeAI](https://docs.beeai.dev/observability/agents-traceability) | KI-Agenten-Framework mit integrierter Observability | [Integrationsleitfaden](https://docs.beeai.dev/observability/agents-traceability) | |

| [Dify](https://docs.dify.ai/en/guides/monitoring/integrate-external-ops-tools/integrate-phoenix) | Open-Source-Plattform zur Entwicklung von LLM-Apps | [Integrationsleitfaden](https://docs.dify.ai/en/guides/monitoring/integrate-external-ops-tools/integrate-phoenix) | | | [Envoy AI Gateway](https://github.com/envoyproxy/ai-gateway) | Auf Envoy Proxy basierendes AI Gateway für KI-Workloads | [Integrationsleitfaden](https://github.com/envoyproxy/ai-gateway/tree/main/cmd/aigw#opentelemetry-setup-with-phoenix) | | | [LangFlow](https://arize.com/docs/phoenix/tracing/integrations-tracing/langflow) | Visuelles Framework zum Erstellen von Multi-Agenten- und RAG-Anwendungen | [Integrationsleitfaden](https://arize.com/docs/phoenix/tracing/integrations-tracing/langflow) | | | [LiteLLM Proxy](https://docs.litellm.ai/docs/observability/phoenix_integration#using-with-litellm-proxy) | Proxy-Server für LLMs | [Integrationsleitfaden](https://docs.litellm.ai/docs/observability/phoenix_integration#using-with-litellm-proxy) | | | [Flowise](https://arize.com/docs/phoenix/integrations/platforms/flowise) | Visuelles Framework zum Erstellen von LLM-Anwendungen | [Integrationsleitfaden](https://arize.com/docs/phoenix/integrations/platforms/flowise) | | | [Prompt Flow](https://arize.com/docs/phoenix/integrations/platforms/prompt-flow) | Microsofts Werkzeug zur Orchestrierung von Prompt-Flows | [Integrationsleitfaden](https://arize.com/docs/phoenix/integrations/platforms/prompt-flow) | |

| [NVIDIA NeMo](https://arize.com/docs/phoenix/integrations/python/nvidia) | NVIDIA NeMo Agent Toolkit für Enterprise-Agenten | [Integrationsleitfaden](https://arize.com/docs/phoenix/integrations/python/nvidia) | | | [Graphite](https://arize.com/docs/phoenix/integrations/python/graphite) | Multi-Agenten-Framework für LLM-Workflows mit visuellem Editor | [Integrationsleitfaden](https://arize.com/docs/phoenix/integrations/python/graphite) | ### Vektordatenbanken | Integration | Beschreibung | Doku | | ----------------------------------------------------------------------------------- | ---------------------------------------------------- | --------------------------------------------------------------------------------------- | | [Qdrant](https://arize.com/docs/phoenix/integrations/vector-databases/qdrant) | Tracing mehrstufiger hybrider Suche mit Dense, Sparse und RRF | [Integrationsleitfaden](https://arize.com/docs/phoenix/integrations/vector-databases/qdrant) | ## Sandboxes Führen Sie Phoenix-[Code-Evaluatoren](https://arize.com/docs/phoenix/evaluation/server-evals/code-evaluators) bei gehosteten Sandbox-Anbietern aus – für Isolation auf Kernel-Ebene und die Installation von Abhängigkeiten zur Laufzeit. | Integration | Beschreibung | Doku | | --------------------------------------------------------------------------------- | ---------------------------------------------------------------- | ---------------------------------------------------------------------------------- | | [E2B](https://arize.com/docs/phoenix/integrations/sandboxes/e2b) | Gehostete Micro-VM-Sandboxes für KI-generierten Code | [Integrationsleitfaden](https://arize.com/docs/phoenix/integrations/sandboxes/e2b) | | [Daytona](https://arize.com/docs/phoenix/integrations/sandboxes/daytona) | Verwaltete Entwicklungs-Sandboxes mit Start aus Snapshots | [Integrationsleitfaden](https://arize.com/docs/phoenix/integrations/sandboxes/daytona) | | [Vercel Sandbox](https://arize.com/docs/phoenix/integrations/sandboxes/vercel) | Kurzlebige Rechenressourcen auf der Infrastruktur von Vercel | [Integrationsleitfaden](https://arize.com/docs/phoenix/integrations/sandboxes/vercel) | | [Modal](https://arize.com/docs/phoenix/integrations/sandboxes/modal) | Serverlose Container-Plattform mit Fokus auf Python | [Integrationsleitfaden](https://arize.com/docs/phoenix/integrations/sandboxes/modal) | | [Docker Sandboxes](https://arize.com/docs/phoenix/integrations/sandboxes/docker) | Von Docker gehostete Cloud-Sandboxes | [Integrationsleitfaden](https://arize.com/docs/phoenix/integrations/sandboxes/docker) | ## Für Menschen und Coding-Agenten Phoenix ist so gebaut, dass es von Menschen und KI-Coding-Agenten gleichermaßen gesteuert werden kann. Über drei Schnittstellen können Agenten (Claude Code, Codex, Cursor und andere) mit Ihren Traces, Datasets und Experimenten arbeiten: - **[CLI](https://arize.com/docs/phoenix/sdk-api-reference/typescript/arizeai-phoenix-cli)** — `npx @arizeai/phoenix-cli` ruft Traces, Datasets und Experimente ab und instrumentiert Ihre App (`setup`), sodass ein Agent Kontext abrufen und direkt im Terminal darauf reagieren kann. - **[Skills](https://docs.anthropic.com/en/docs/claude-code/skills)** — [`skills/`](../../skills/) bündelt Workflows, die Agenten beibringen, wie sie mit Phoenix debuggen, evaluieren und tracen. - **[Remote-MCP-Server](https://arize.com/docs/phoenix/integrations/mcp#remote-mcp-server)** — verbinden Sie einen beliebigen MCP-Client mit dem `/mcp`-Endpunkt Ihrer Instanz, um Phoenix direkt abzufragen. Einrichtung und Verwendung sind in der [Dokumentation zu Coding-Agenten](https://arize.com/docs/phoenix/integrations/developer-tools/coding-agents) beschrieben. | Skill | Beschreibung | | -------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------- | | [phoenix-cli](../../skills/phoenix-cli/) | LLM-Anwendungen mit der Phoenix-CLI debuggen – Traces abrufen, Fehler analysieren, Experimente prüfen und die GraphQL-API abfragen | | [phoenix-evals](../../skills/phoenix-evals/) | Evaluatoren für KI-/LLM-Anwendungen mit Phoenix erstellen und ausführen | | [phoenix-tracing](../../skills/phoenix-tracing/) | Semantische Konventionen und Instrumentierung von OpenInference für das Tracing von LLM-Anwendungen | ## Sicherheit & Datenschutz Wir nehmen Datensicherheit und Datenschutz sehr ernst. Weitere Details finden Sie in unserer [Dokumentation zu Sicherheit und Datenschutz](https://arize.com/docs/phoenix/self-hosting/security/privacy). ### Telemetrie Standardmäßig erfasst Phoenix grundlegende Web-Analysedaten (z. B. Seitenaufrufe, UI-Interaktionen), damit wir verstehen, wie Phoenix genutzt wird, und das Produkt verbessern können. **Ihre Trace-Daten, Evaluierungsergebnisse oder andere sensible Informationen werden niemals erfasst.** Sie können die Telemetrie deaktivieren, indem Sie die folgende Umgebungsvariable setzen: `PHOENIX_TELEMETRY_ENABLED=false` ## Community Treten Sie unserer Community bei und vernetzen Sie sich mit Tausenden von KI-Entwicklern. - 🌍 Treten Sie unserer [Slack-Community](https://join.slack.com/t/arize-ai/shared_invite/zt-3r07iavnk-ammtATWSlF0pSrd1DsMW7g) bei. - 📚 Lesen Sie unsere [Dokumentation](https://arize.com/docs/phoenix). - 💡 Stellen Sie Fragen und geben Sie Feedback im Kanal _#phoenix-support_. - 🌟 Geben Sie uns einen Stern auf [GitHub](https://github.com/Arize-ai/phoenix). - 🐞 Melden Sie Fehler über [GitHub Issues](https://github.com/Arize-ai/phoenix/issues). - 𝕏 Folgen Sie uns auf [𝕏](https://twitter.com/ArizePhoenix). - 💼 Folgen Sie uns auf [LinkedIn](https://www.linkedin.com/showcase/113218220). - 🗺️ Werfen Sie einen Blick auf unsere [Roadmap](https://github.com/orgs/Arize-ai/projects/45), um zu sehen, wohin die Reise geht. - 🧑‍🏫 Tauchen Sie in den Learning Hubs von Arize tief in alles rund um [Agenten](http://arize.com/ai-agents/) und [LLM-Evaluierungen](https://arize.com/llm-evaluation) ein. ## Breaking Changes Eine Liste der Breaking Changes finden Sie im [Migrationsleitfaden](../../MIGRATION.md). ## Copyright, Patente und Lizenz Copyright 2025 Arize AI, Inc. Alle Rechte vorbehalten. Teile dieses Codes sind durch ein oder mehrere US-Patente geschützt. Siehe [IP_NOTICE](https://github.com/Arize-ai/phoenix/blob/main/IP_NOTICE). Diese Software ist unter den Bedingungen der Elastic License 2.0 (ELv2) lizenziert. Siehe [LICENSE](https://github.com/Arize-ai/phoenix/blob/main/LICENSE). ## Star History Phoenix is fully open source and built in the open. If it helps you, please [⭐ star the repo](https://github.com/Arize-ai/phoenix) to support the project.