# Observability for AG2 with Opik

> Start here to integrate Opik into your AG2-based genai application for end-to-end LLM observability, unit testing, and optimization.

[AG2](https://ag2.ai/) is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks.

AG2's primary advantage is its multi-agent conversation patterns and autonomous workflows, making it ideal for complex tasks that require collaboration between specialized agents with different roles and capabilities.

<Frame>
  <img src="https://files.buildwithfern.com/https://opik.docs.buildwithfern.com/docs/opik/2026-01-30T17:33:07.444Z/img/tracing/ag2_integration.png" alt="AG2 tracing" />
</Frame>

## Getting started

To use the AG2 integration with Opik, you will need to have the following
packages installed:

```bash
pip install -U "ag2[openai]" opik opentelemetry-sdk opentelemetry-instrumentation-openai opentelemetry-instrumentation-threading opentelemetry-exporter-otlp
```

In addition, you will need to set the following environment variables to
configure the OpenTelemetry integration:

<Tabs>
  <Tab value="Opik Cloud" title="Opik Cloud">
    If you are using Opik Cloud, you will need to set the following
    environment variables:

    ```bash wordWrap
    export OTEL_EXPORTER_OTLP_ENDPOINT=https://www.comet.com/opik/api/v1/private/otel
    export OTEL_EXPORTER_OTLP_HEADERS='Authorization=<your-api-key>,Comet-Workspace=default'
    ```

    <Tip>
      To log the traces to a specific project, you can add the
      `projectName` parameter to the `OTEL_EXPORTER_OTLP_HEADERS`
      environment variable:

      ```bash wordWrap
      export OTEL_EXPORTER_OTLP_HEADERS='Authorization=<your-api-key>,Comet-Workspace=default,projectName=<your-project-name>'
      ```

      You can also update the `Comet-Workspace` parameter to a different
      value if you would like to log the data to a different workspace.
    </Tip>
  </Tab>

  <Tab value="Enterprise deployment" title="Enterprise deployment">
    If you are using an Enterprise deployment of Opik, you will need to set the following
    environment variables:

    ```bash wordWrap
    export OTEL_EXPORTER_OTLP_ENDPOINT=https://<comet-deployment-url>/opik/api/v1/private/otel
    export OTEL_EXPORTER_OTLP_HEADERS='Authorization=<your-api-key>,Comet-Workspace=default'
    ```

    <Tip>
      To log the traces to a specific project, you can add the
      `projectName` parameter to the `OTEL_EXPORTER_OTLP_HEADERS`
      environment variable:

      ```bash wordWrap
      export OTEL_EXPORTER_OTLP_HEADERS='Authorization=<your-api-key>,Comet-Workspace=default,projectName=<your-project-name>'
      ```

      You can also update the `Comet-Workspace` parameter to a different
      value if you would like to log the data to a different workspace.
    </Tip>
  </Tab>

  <Tab value="Self-hosted instance" title="Self-hosted instance">
    If you are self-hosting Opik, you will need to set the following environment
    variables:

    ```bash
    export OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:5173/api/v1/private/otel
    ```

    <Tip>
      To log the traces to a specific project, you can add the `projectName`
      parameter to the `OTEL_EXPORTER_OTLP_HEADERS` environment variable:

      ```bash
      export OTEL_EXPORTER_OTLP_HEADERS='projectName=<your-project-name>'
      ```
    </Tip>
  </Tab>
</Tabs>

## Using Opik with AG2

The example below shows how to use the AG2 integration with Opik:

```python
## First we will configure the OpenTelemetry
from opentelemetry import trace
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.instrumentation.openai import OpenAIInstrumentor
from opentelemetry.instrumentation.threading import ThreadingInstrumentor


def setup_telemetry():
    """Configure OpenTelemetry with HTTP exporter"""
    # Create a resource with service name and other metadata
    resource = Resource.create(
        {
            "service.name": "ag2-demo",
            "service.version": "1.0.0",
            "deployment.environment": "development",
        }
    )

    # Create TracerProvider with the resource
    provider = TracerProvider(resource=resource)

    # Create BatchSpanProcessor with OTLPSpanExporter
    processor = BatchSpanProcessor(OTLPSpanExporter())
    provider.add_span_processor(processor)

    # Set the TracerProvider
    trace.set_tracer_provider(provider)

    tracer = trace.get_tracer(__name__)

    # Instrument OpenAI calls
    OpenAIInstrumentor().instrument(tracer_provider=provider)

    # AG2 calls OpenAI in background threads, propagate the context so all spans ends up in the same trace
    ThreadingInstrumentor().instrument()

    return tracer, provider