# Send traces with OpenInference

> Send traces from applications instrumented with OpenInference.

This guide sends traces from an application instrumented with [OpenInference](https://github.com/Arize-ai/openinference), which has instrumentations for OpenAI, Anthropic, LangChain, LlamaIndex, DSPy and other libraries. Tracing reads the model, tokens and messages of LLM spans, and the input and output of chain, tool and retriever spans.

## Before you start

You need an API key with the `traces:write` scope. Create one under **Settings** in the dashboard, or run `div login`.

## Send traces

1. Install the OpenTelemetry SDK, the OTLP exporter and the instrumentation for your library. This example uses OpenAI's.

   ```bash
   pip install opentelemetry-sdk opentelemetry-exporter-otlp-proto-http openinference-instrumentation-openai
   ```

2. Set the exporter's endpoint and key.

   ```bash
   export OTEL_EXPORTER_OTLP_ENDPOINT=https://api.divergentlabs.xyz/api/otlp
   export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Bearer%20$DIVERGENT_API_KEY"
   export OTEL_SERVICE_NAME=my-app
   ```

3. Set up the tracer provider and instrument the library.

   ```python
   from opentelemetry import trace
   from opentelemetry.sdk.trace import TracerProvider
   from opentelemetry.sdk.trace.export import BatchSpanProcessor
   from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
   from openinference.instrumentation.openai import OpenAIInstrumentor

   provider = TracerProvider()
   provider.add_span_processor(BatchSpanProcessor(OTLPSpanExporter()))
   trace.set_tracer_provider(provider)
   OpenAIInstrumentor().instrument(tracer_provider=provider)
   ```

4. Run your application, then list the traces.

   ```bash
   div traces --since 10m
   ```

## Sessions and users

OpenInference's `using_session` and `using_user` context managers set `session.id` and `user.id`, which tracing reads:

```python
from openinference.instrumentation import using_session, using_user

with using_session(session_id), using_user(user_id):
    client.chat.completions.create(model="gpt-4o-mini", messages=messages)
```

## Keep content out of traces

Set `OPENINFERENCE_HIDE_INPUTS=true` and `OPENINFERENCE_HIDE_OUTPUTS=true`.