James C.

# init code
def init_tracer(spawn_server: bool = True):
    resource = Resource(attributes={ResourceAttributes.PROJECT_NAME: "viv4"})
    tracer_provider = TracerProvider(resource=resource)
    trace.set_tracer_provider(tracer_provider)
    collector_endpoint = f"http://{get_env_host()}:{get_env_port()}/v1/traces"
    span_exporter = OTLPSpanExporter(endpoint=collector_endpoint)
    simple_span_processor = SimpleSpanProcessor(span_exporter=span_exporter)
    trace.get_tracer_provider().add_span_processor(simple_span_processor)
    LlamaIndexInstrumentor().instrument(tracer_provider=tracer_provider)
    return trace.get_tracer(__name__)

# manual instrumentation 
def run():
    tracer = init_tracer()
    span = tracer.start_span(
        "apprun", attributes={SpanAttributes.OPENINFERENCE_SPAN_KIND: "CHAIN"}
    )
    with trace.use_span(span, end_on_exit=False):
        # configures global state so the right embedding models, LLMs will be used by the agent
        init_models()
        span.set_attribute(SpanAttributes.INPUT_VALUE, "")
        span.set_attribute(
            SpanAttributes.INPUT_MIME_TYPE, OpenInferenceMimeTypeValues.TEXT.value
        )
        # creates all the tools to be used by the agent
        tools = create_all_tools()

        output = agent2.run(tools)
        span.set_attribute(SpanAttributes.OUTPUT_VALUE, json.dumps(output.response))
        span.set_attribute(
            SpanAttributes.OUTPUT_MIME_TYPE, OpenInferenceMimeTypeValues.TEXT.value
        )

        span.end()