Chatbot Service

This service provides the chat interface for the demo’s AI assistant. It serves a Gradio web UI, forwards each user message to the Agent service over HTTP, and renders the reply. It is exposed through the frontend proxy at /chatbot.

Chatbot service source

Instrumentation libraries

This service is not started through the opentelemetry-instrument wrapper. The Dockerfile runs the script directly, and instrumentation is set up in code:

CMD ["python", "run.py"]

Unlike the Agent and MCP services, this service uses the OpenTelemetry SDK directly rather than the Traceloop SDK. Two HTTP client instrumentation libraries are enabled:

RequestsInstrumentor().instrument()
HTTPXClientInstrumentor().instrument()

The call to the agent is made with requests, so opentelemetry-instrumentation-requests produces the client span for it and injects the trace context into the outgoing request. This is what links the chat interface to the agent, and in turn to the LLM and tool calls the agent makes.

The Gradio server itself is not instrumented, so incoming browser requests do not produce server spans. Traces from this service begin at the outbound call to the agent.

Traces

Initializing Tracing

Tracing is configured explicitly in _configure_tracing, which run.py calls at import time. The code creates a tracer provider, adds a batch span processor with an OTLP exporter, and registers the provider globally so that the instrumentation libraries use it:

def _configure_tracing() -> None:
    provider = TracerProvider()
    provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
    trace.set_tracer_provider(provider)

    RequestsInstrumentor().instrument()
    HTTPXClientInstrumentor().instrument()

The exporter is imported from opentelemetry.exporter.otlp.proto.http.trace_exporter, so this service exports over OTLP/HTTP. Docker Compose sets OTEL_EXPORTER_OTLP_ENDPOINT to the OpenTelemetry Collector’s OTLP/HTTP port for this service, whereas most other demo services export over gRPC. Export endpoint, resource attributes, and service name are all taken from the standard OpenTelemetry environment variables.

Create new spans

This service creates no spans of its own. It does not obtain a tracer, does not call start_as_current_span, and does not enrich spans using set_attribute. All of its spans come from the requests and HTTPX instrumentation libraries.

Metrics

No meter provider is configured. The service imports only the trace exporter and never calls metrics.set_meter_provider, so the metrics that the requests and HTTPX instrumentation libraries can emit have nowhere to go and are not exported. See the metric coverage matrix.

Logs

The service configures the Python standard library logger only:

logging.basicConfig(level=logging.INFO)

Requests to the agent, and any errors, are logged through it in chat_with_agent:

logging.info(f"Sending request {payload} to Agent")

Because no LoggerProvider or LoggingHandler is set up, these records go to stdout and are collected by the container runtime instead of being exported over OTLP, so they are not correlated with traces. See the log coverage matrix.

For the full list of environment variables and troubleshooting steps, see the service README.