> ## Documentation Index
> Fetch the complete documentation index at: https://docs.honeyhive.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Tracing Quickstart

> Trace your first AI application in 5 minutes

This guide walks you through tracing an LLM call with HoneyHive. By the end, you'll see your first trace in the dashboard.

**Expected time**: 5 minutes

<Steps>
  <Step title="Create a project">
    Go to [HoneyHive Projects](https://app.us.honeyhive.ai/projects) and click **New Project**. Name it `my-first-project`.
  </Step>

  <Step title="Get your API key">
    Go to [**Settings > Project > API Keys**](https://app.us.honeyhive.ai/settings/project/keys) and click **Create API Key**. Copy the key from the modal - it will only be shown once.
  </Step>

  <Step title="Install dependencies">
    ```bash theme={null}
    pip install honeyhive openai openinference-instrumentation-openai
    ```

    Using a different provider? See our [integration guides](/v2/integrations/openai) for Anthropic, Google, AWS Bedrock, and more.
  </Step>

  <Step title="Run this script">
    Create a new file called `quickstart.py` and paste the following code. Replace the placeholder values with your HoneyHive API key and project name.

    ```python theme={null}
    from honeyhive import HoneyHiveTracer
    from openinference.instrumentation.openai import OpenAIInstrumentor
    from openai import OpenAI

    # Initialize HoneyHive tracing
    tracer = HoneyHiveTracer.init(
        api_key="your-honeyhive-api-key",
        project="my-first-project",
        source="development",  # Optional: Label where traces come from
        session_name="quickstart-session",  # Optional: Group related traces
        # server_url="https://your-instance.honeyhive.ai"  # Required for self-hosted/dedicated
    )

    # Add the OpenAI instrumentor
    OpenAIInstrumentor().instrument(tracer_provider=tracer.provider)

    # Make a traced OpenAI call
    client = OpenAI()
    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": "Write a fun haiku about honeybees"}]
    )

    print(response.choices[0].message.content)
    ```

    <Note>
      This quickstart keeps tracing setup simple: initialize the tracer first, then initialize the instrumentor with `tracer.provider`.
    </Note>

    <Tip>
      To see where to initialize the tracer for your environment, including AWS Lambda and long-running servers, see [Tracer Initialization](/v2/tracing/tracer-initialization).
    </Tip>

    Run the script:

    ```bash theme={null}
    python quickstart.py
    ```
  </Step>

  <Step title="View your trace">
    Go to the [Traces](https://app.us.honeyhive.ai/traces/sessions) page in HoneyHive. Click on your trace to see the full request and response.

    <Frame>
      <img src="https://mintcdn.com/honeyhiveai/KYET_f7js_xlbTkv/images/quickstart-trace.png?fit=max&auto=format&n=KYET_f7js_xlbTkv&q=85&s=f0e91b431d2bc9748e161a5df6a34ddc" width="2648" height="1664" data-path="images/quickstart-trace.png" />
    </Frame>
  </Step>
</Steps>

## What's next?

Now that you're tracing, try the [Experiments Quickstart](/v2/introduction/experiments-quickstart) to run your first evaluation and compare prompt variations.

Or explore our [Key Concepts](/v2/concepts) to understand sessions, spans, and how HoneyHive structures your trace data.

<CardGroup cols={2}>
  <Card title="Choose runtime setup" icon="route" href="/v2/tracing/tracer-initialization">
    See where to initialize the tracer for Lambda, web servers, and script-style apps.
  </Card>

  <Card title="Add more providers" icon="plug" href="/v2/integrations/openai">
    Trace Anthropic, Google, AWS Bedrock, and more.
  </Card>

  <Card title="Trace custom functions" icon="brackets-curly" href="/v2/tracing/custom-spans">
    Use decorators to trace your own business logic.
  </Card>

  <Card title="Enrich your traces" icon="tags" href="/v2/tracing/enrich-traces">
    Add feedback, metadata, and user information.
  </Card>

  <Card title="Run evaluations" icon="flask" href="/v2/introduction/experiments-quickstart">
    Set up automated evaluations on your traces.
  </Card>
</CardGroup>