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Evaluation Dataset

Dataset Class

The Dataset class is a convenient class that represent a dataset that can be used for evaluation.

The dataset class can be initialized with a path to a folder or a file. The folder should contain the following files:

  • dataset.jsonl which contains a collection of query / instructions and corresponding reference outputs by the modules in the pipeline.
  • an optional manifest.yaml which declares the structure and fields of the dataset, the license and other metadata.
from continuous_eval.eval import Dataset
dataset = Dataset("path_to_folder") # or Dataset("path_to_file.jsonl")

Alternatively, you can also create a dataset from a list of dictionaries:

dataset = Dataset.from_data([
{"question": "What is the capital of France?", "answer": "Paris"},
{"question": "What is the capital of Germany?", "answer": "Berlin"},

To access the raw data, you can use the data attribute:


Dataset fields

Suppose you want to reference a dataset field, you can use the DatasetField class:

class DatasetField:
name: str
type: type = typing.Any # type: ignore
description: str = ""
is_ground_truth: bool = False

When you load the dataset, the Dataset class will automatically infer the fields from the data.

type(dataset.question) # DatasetField

this will be particularly useful when defining the input and output of the modules in the pipeline.

Example Data Folder

Here’s an example golden dataset that contains uid, question, answer (ground truth answers), and tool_calls (the tools that are supposed to be used).

Dataset File

"uuid": "1",
"question": "What is Uber revenue as of March 2022?",
"answer": [
"Uber's revenue as of March 2022 is $6,854 million.",
"$6,854 million",
"tool_calls": [
"name": "march"
"uuid": "2",
"question": "What is Uber revenue as of Sept 2022?",
"answer": [
"Uber's revenue as of September 2022 is $23,270 million.",
"$23,270 million",
"tool_calls": [
"name": "sept"
"uuid": "3",
"question": "What is Uber revenue as of June 2022?",
"answer": [
"Uber's revenue as of September 2022 is $8,073 million.",
"$8,073 million",
"tool_calls": [
"name": "june"

Manifest (optional)

name: Uber 10Q
description: Uber 10Q filings from 2022
format: jsonl
license: CC0
description: Unique identifier for the filing
type: UUID
description: The question asked in the filing
type: str
description: The answer to the question
type: List[str]
description: The tools used to extract the question and answer
type: List[Dict[str, str]]