Pooja R.

No problem! Just so I'm not missing something, I can call save() via a client only in a notebook/ipython environment?

I would still like to find a way around #1

Also, please ignore #2. It's on our end.

Is there a way to save and load datasets that's not in a notebook? I have the Phoenix server running in a docker container (v3.18.0) and my prediction pipeline is a standalone python script and px.Client(endpoint='http://localhost:6006').get_trace_dataset() returns empty. Sorry, the instrumertor is Langchain - openinference.instrumentation.langchain (0.1.14). I have the instrumentor intialized as the first thing before any other initialization.

resource = Resource(attributes={
    ResourceAttributes.PROJECT_NAME: project_name
})

endpoint = "http://127.0.0.1:6006/v1/traces"
tracer_provider = trace_sdk.TracerProvider(resource=resource)
span_exporter = OTLPSpanExporter(endpoint)
span_processor = SimpleSpanProcessor(span_exporter=span_exporter)
tracer_provider.add_span_processor(span_processor=span_processor)
trace_api.set_tracer_provider(tracer_provider)

LangChainInstrumentor().instrument()