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@arizeai/phoenix-mcp

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by Arize-ai
importing-existing-traces.md1.75 kB
# Import Existing Traces Phoenix supports loading data that contains [OpenInference traces](https://arize.com/docs/phoenix/references/openinference). This allows you to load an existing dataframe of traces into your Phoenix instance. Usually these will be traces you've previously saved using [Save All Traces](https://arize.com/docs/phoenix/tracing/how-to-tracing/extract-data-from-spans#save-all-traces). ### Connect to Phoenix Before accessing px.Client(), be sure you've set the following environment variables: ```python import os os.environ["PHOENIX_CLIENT_HEADERS"] = f"api_key=..." os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "https://app.phoenix.arize.com" ``` If you're self-hosting Phoenix, ignore the client headers and change the collector endpoint to your endpoint. ### Importing Traces to an Existing Phoenix Instance ```python import phoenix as px # Re-launch the app using trace data px.launch_app(trace=px.TraceDataset(df)) # Load traces into an existing Phoenix instance px.Client().log_traces(trace_dataset=px.TraceDataset(df)) # Load traces into an existing Phoenix instance from a local file px.launch_app(trace=px.TraceDataset.load('f7733fda-6ad6-4427-a803-55ad2182b662', directory="/my_saved_traces/")) ``` ### Launching a new Phoenix Instance with Saved Traces You can also launch a temporary version of Phoenix in your local notebook to quickly view the traces. But be warned, this Phoenix instance will only last as long as your notebook environment is runing ```python # Load traces from a dataframe px.launch_app(trace=px.TraceDataset.load(my_traces)) # Load traces from a local file px.launch_app(trace=px.TraceDataset.load('f7733fda-6ad6-4427-a803-55ad2182b662', directory="/my_saved_traces/")) ```

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