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@arizeai/phoenix-mcp

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by Arize-ai
litellm-tracing.md1.72 kB
# LiteLLM Tracing [LiteLLM](https://github.com/BerriAI/litellm) allows developers to call all LLM APIs using the openAI format. [LiteLLM Proxy](https://docs.litellm.ai/docs/simple_proxy) is a proxy server to call 100+ LLMs in OpenAI format. Both are supported by this auto-instrumentation. Any calls made to the following functions will be automatically captured by this integration: * completion() * acompletion() * completion\_with\_retries() * embedding() * aembedding() * image\_generation() * aimage\_generation() ## Launch Phoenix {% include "../../../../phoenix-integrations/.gitbook/includes/sign-up-for-phoenix-sign-up....md" %} ## Install ```bash pip install openinference-instrumentation-litellm litellm ``` ## Setup Use the register function to connect your application to Phoenix: ```python from phoenix.otel import register # configure the Phoenix tracer tracer_provider = register( project_name="my-llm-app", # Default is 'default' auto_instrument=True # Auto-instrument your app based on installed OI dependencies ) ``` Add any API keys needed by the models you are using with LiteLLM. ```python import os os.environ["OPENAI_API_KEY"] = "PASTE_YOUR_API_KEY_HERE" ``` ## Run LiteLLM You can now use LiteLLM as normal and calls will be traces in Phoenix. ```python import litellm completion_response = litellm.completion(model="gpt-3.5-turbo", messages=[{"content": "What's the capital of China?", "role": "user"}]) print(completion_response) ``` ## Observe Traces should now be visible in Phoenix! ## Resources * [OpenInference Instrumentation](https://github.com/Arize-ai/openinference/tree/main/python/instrumentation/openinference-instrumentation-litellm)

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