chore: import upstream snapshot with attribution

docs-website/reference_versioned_docs/version-2.30/haystack-api/evaluation_api.md

@@ -0,0 +1,108 @@
+---
+title: "Evaluation"
+id: evaluation-api
+description: "Represents the results of evaluation."
+slug: "/evaluation-api"
+---
+
+
+## eval_run_result
+
+### EvaluationRunResult
+
+Contains the inputs and the outputs of an evaluation pipeline and provides methods to inspect them.
+
+#### __init__
+
+```python
+__init__(
+    run_name: str,
+    inputs: dict[str, list[Any]],
+    results: dict[str, dict[str, Any]],
+) -> None
+```
+
+Initialize a new evaluation run result.
+
+**Parameters:**
+
+- **run_name** (<code>str</code>) – Name of the evaluation run.
+- **inputs** (<code>dict\[str, list\[Any\]\]</code>) – Dictionary containing the inputs used for the run. Each key is the name of the input and its value is a list
+  of input values. The length of the lists should be the same.
+- **results** (<code>dict\[str, dict\[str, Any\]\]</code>) – Dictionary containing the results of the evaluators used in the evaluation pipeline. Each key is the name
+  of the metric and its value is dictionary with the following keys:
+  - 'score': The aggregated score for the metric.
+  - 'individual_scores': A list of scores for each input sample.
+
+#### aggregated_report
+
+```python
+aggregated_report(
+    output_format: Literal["json", "csv", "df"] = "json",
+    csv_file: str | None = None,
+) -> Union[dict[str, list[Any]], DataFrame, str]
+```
+
+Generates a report with aggregated scores for each metric.
+
+**Parameters:**
+
+- **output_format** (<code>Literal['json', 'csv', 'df']</code>) – The output format for the report, "json", "csv", or "df", default to "json".
+- **csv_file** (<code>str | None</code>) – Filepath to save CSV output if `output_format` is "csv", must be provided.
+
+**Returns:**
+
+- <code>Union\[dict\[str, list\[Any\]\], DataFrame, str\]</code> – JSON or DataFrame with aggregated scores, in case the output is set to a CSV file, a message confirming the
+  successful write or an error message.
+
+#### detailed_report
+
+```python
+detailed_report(
+    output_format: Literal["json", "csv", "df"] = "json",
+    csv_file: str | None = None,
+) -> Union[dict[str, list[Any]], DataFrame, str]
+```
+
+Generates a report with detailed scores for each metric.
+
+**Parameters:**
+
+- **output_format** (<code>Literal['json', 'csv', 'df']</code>) – The output format for the report, "json", "csv", or "df", default to "json".
+- **csv_file** (<code>str | None</code>) – Filepath to save CSV output if `output_format` is "csv", must be provided.
+
+**Returns:**
+
+- <code>Union\[dict\[str, list\[Any\]\], DataFrame, str\]</code> – JSON or DataFrame with the detailed scores, in case the output is set to a CSV file, a message confirming
+  the successful write or an error message.
+
+#### comparative_detailed_report
+
+```python
+comparative_detailed_report(
+    other: EvaluationRunResult,
+    keep_columns: list[str] | None = None,
+    output_format: Literal["json", "csv", "df"] = "json",
+    csv_file: str | None = None,
+) -> Union[str, DataFrame, None]
+```
+
+Generates a report with detailed scores for each metric from two evaluation runs for comparison.
+
+**Parameters:**
+
+- **other** (<code>EvaluationRunResult</code>) – Results of another evaluation run to compare with.
+- **keep_columns** (<code>list\[str\] | None</code>) – List of common column names to keep from the inputs of the evaluation runs to compare.
+- **output_format** (<code>Literal['json', 'csv', 'df']</code>) – The output format for the report, "json", "csv", or "df", default to "json".
+- **csv_file** (<code>str | None</code>) – Filepath to save CSV output if `output_format` is "csv", must be provided.
+
+**Returns:**
+
+- <code>Union\[str, DataFrame, None\]</code> – JSON or DataFrame with a comparison of the detailed scores, in case the output is set to a CSV file,
+  a message confirming the successful write or an error message.
+
+**Raises:**
+
+- <code>TypeError</code> – If `other` is not an EvaluationRunResult instance, or if the detailed reports are not
+  dictionaries.
+- <code>ValueError</code> – If the `other` parameter is missing required attributes.