# Add metrics locally

RagaAI allows users to define and upload custom metrics locally, catering to specific requirements that involve specialized libraries or unique metric definitions to an user. This feature is particularly useful for metrics that are not universally accessible or are highly specific to the user's needs. Users can upload these metrics at both the **Trace Level** and **Span Level**, and these metrics will be added during trace execution.

***

**How to Upload Metrics Locally?**

**1. Span Level Metric**

Span-level metrics are added to specific spans within a trace. This is done by defining the tracer decorator and using the `add_metrics()` method.

**Example Code:**

```python
@tracer.trace_tool(name="span_name")
def function():
    tracer.span('span_name').add_metrics(
        name='metric_name', 
        score=score, 
        reasoning=reasoning, 
        cost=cost, 
        latency=latency
    )
    pass
```

**Key Parameters:**

* **`name`**: The name of the metric. This will appear as a column in the dataset.
* **`score`**: The metric score for the specific input.
* **`reasoning`**: (Optional) Explanation or reasoning for the metric score.
* **`cost`**: (Optional) The cost associated with the metric.
* **`latency`**: (Optional) The latency value for the metric.

**Points to Note:**

* Metric names are **case-insensitive**.
* No two spans can have the same metric name. If duplicate names are used:
  * The SDK will treat the first occurrence as the default name.
  * Subsequent metrics with the same name will have a suffix in the format `{metric_name_(n-1)}`.

***

**2. Trace Level Metric**

Trace-level metrics apply to the entire trace and can be defined at a higher level than spans. The process to add these metrics follows similar principles but applies them globally across the trace.

User can add the metric anywhere between tracer.start() and tracer.stop() using the method:

```python
    tracer.add_metrics(
        name='metric_name', 
        score=score, 
        reasoning=reasoning, #optional
        cost=cost, #optional
        latency=latency #optional
    )
```

***


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.raga.ai/ragaai-catalyst/agentic-testing/add-metrics-locally.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.