Feat/cog 946 abstract eval dataset (#418)
* QA eval dataset as argument, with hotpot and 2wikimultihop as options. Json schema validation for datasets. * Load dataset file by filename, outsource utilities * Use requests.get instead of wget
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2 changed files with 93 additions and 26 deletions
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@ -1,11 +1,7 @@
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import argparse
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import asyncio
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import json
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import statistics
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from pathlib import Path
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import deepeval.metrics
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import wget
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from deepeval.dataset import EvaluationDataset
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from deepeval.test_case import LLMTestCase
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from tqdm import tqdm
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@ -13,9 +9,9 @@ from tqdm import tqdm
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import cognee
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import evals.deepeval_metrics
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from cognee.api.v1.search import SearchType
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from cognee.base_config import get_base_config
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from cognee.infrastructure.llm.get_llm_client import get_llm_client
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from cognee.infrastructure.llm.prompts import read_query_prompt, render_prompt
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from evals.qa_dataset_utils import load_qa_dataset
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async def answer_without_cognee(instance):
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@ -40,12 +36,8 @@ async def answer_with_cognee(instance):
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await cognee.prune.prune_system(metadata=True)
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for title, sentences in instance["context"]:
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await cognee.add("\n".join(sentences), dataset_name="HotPotQA")
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for n in range(1, 4):
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print(n)
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await cognee.cognify("HotPotQA")
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await cognee.add("\n".join(sentences), dataset_name="QA")
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await cognee.cognify("QA")
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search_results = await cognee.search(SearchType.INSIGHTS, query_text=instance["question"])
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search_results_second = await cognee.search(
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@ -85,20 +77,10 @@ async def eval_answers(instances, answers, eval_metric):
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return eval_results
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async def eval_on_hotpotQA(answer_provider, num_samples, eval_metric):
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base_config = get_base_config()
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data_root_dir = base_config.data_root_directory
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if not Path(data_root_dir).exists():
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Path(data_root_dir).mkdir()
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filepath = data_root_dir / Path("hotpot_dev_fullwiki_v1.json")
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if not filepath.exists():
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url = "http://curtis.ml.cmu.edu/datasets/hotpot/hotpot_dev_fullwiki_v1.json"
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wget.download(url, out=data_root_dir)
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with open(filepath, "r") as file:
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dataset = json.load(file)
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async def eval_on_QA_dataset(
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dataset_name_or_filename: str, answer_provider, num_samples, eval_metric
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):
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dataset = load_qa_dataset(dataset_name_or_filename)
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instances = dataset if not num_samples else dataset[:num_samples]
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answers = []
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@ -117,6 +99,7 @@ async def eval_on_hotpotQA(answer_provider, num_samples, eval_metric):
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--dataset", type=str, help="Which dataset to evaluate on")
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parser.add_argument("--with_cognee", action="store_true")
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parser.add_argument("--num_samples", type=int, default=500)
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parser.add_argument(
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@ -142,5 +125,7 @@ if __name__ == "__main__":
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else:
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answer_provider = answer_without_cognee
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avg_score = asyncio.run(eval_on_hotpotQA(answer_provider, args.num_samples, metric))
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avg_score = asyncio.run(
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eval_on_QA_dataset(args.dataset, answer_provider, args.num_samples, metric)
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)
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print(f"Average {args.metric}: {avg_score}")
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82
evals/qa_dataset_utils.py
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82
evals/qa_dataset_utils.py
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@ -0,0 +1,82 @@
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from cognee.root_dir import get_absolute_path
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import json
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import requests
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from jsonschema import ValidationError, validate
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from pathlib import Path
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qa_datasets = {
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"hotpotqa": {
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"filename": "hotpot_dev_fullwiki_v1.json",
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"URL": "http://curtis.ml.cmu.edu/datasets/hotpot/hotpot_dev_fullwiki_v1.json",
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},
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"2wikimultihop": {
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"filename": "data/dev.json",
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"URL": "https://www.dropbox.com/scl/fi/heid2pkiswhfaqr5g0piw/data.zip?rlkey=ira57daau8lxfj022xvk1irju&e=1",
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},
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}
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qa_json_schema = {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"answer": {"type": "string"},
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"question": {"type": "string"},
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"context": {"type": "array"},
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},
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"required": ["answer", "question", "context"],
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"additionalProperties": True,
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},
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}
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def download_qa_dataset(dataset_name: str, filepath: Path):
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if dataset_name not in qa_datasets:
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raise ValueError(f"{dataset_name} is not a supported dataset.")
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url = qa_datasets[dataset_name]["URL"]
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if dataset_name == "2wikimultihop":
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raise Exception(
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"Please download 2wikimultihop dataset (data.zip) manually from \
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https://www.dropbox.com/scl/fi/heid2pkiswhfaqr5g0piw/data.zip?rlkey=ira57daau8lxfj022xvk1irju&e=1 \
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and unzip it."
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)
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response = requests.get(url, stream=True)
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if response.status_code == 200:
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with open(filepath, "wb") as file:
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for chunk in response.iter_content(chunk_size=8192):
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file.write(chunk)
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print(f"Dataset {dataset_name} downloaded and saved to {filepath}")
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else:
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print(f"Failed to download {dataset_name}. Status code: {response.status_code}")
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def load_qa_dataset(dataset_name_or_filename: str):
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if dataset_name_or_filename in qa_datasets:
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dataset_name = dataset_name_or_filename
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filename = qa_datasets[dataset_name]["filename"]
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data_root_dir = get_absolute_path("../.data")
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if not Path(data_root_dir).exists():
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Path(data_root_dir).mkdir()
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filepath = data_root_dir / Path(filename)
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if not filepath.exists():
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download_qa_dataset(dataset_name, filepath)
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else:
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filename = dataset_name_or_filename
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filepath = Path(filename)
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with open(filepath, "r") as file:
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dataset = json.load(file)
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try:
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validate(instance=dataset, schema=qa_json_schema)
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except ValidationError as e:
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print("File is not a valid QA dataset:", e.message)
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return dataset
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