From f47b185a9e96fb573a06301bf3f63b59288a1d35 Mon Sep 17 00:00:00 2001 From: Rita Aleksziev Date: Wed, 27 Nov 2024 10:53:48 +0100 Subject: [PATCH 1/9] feat/add correctness score calculation with LLM as a judge --- .gitignore | 1 - .../llm/prompts/answer_question.txt | 2 + .../llm/prompts/answer_question_kg.txt | 2 + .../llm/prompts/context_for_question.txt | 2 + evals/llm_as_a_judge.py | 110 ++++++++++++++++++ 5 files changed, 116 insertions(+), 1 deletion(-) create mode 100644 cognee/infrastructure/llm/prompts/answer_question.txt create mode 100644 cognee/infrastructure/llm/prompts/answer_question_kg.txt create mode 100644 cognee/infrastructure/llm/prompts/context_for_question.txt create mode 100644 evals/llm_as_a_judge.py diff --git a/.gitignore b/.gitignore index d256013d2..5096c96b4 100644 --- a/.gitignore +++ b/.gitignore @@ -12,7 +12,6 @@ __pycache__/ *$py.class full_run.ipynb -evals/ # C extensions *.so diff --git a/cognee/infrastructure/llm/prompts/answer_question.txt b/cognee/infrastructure/llm/prompts/answer_question.txt new file mode 100644 index 000000000..06a0602d1 --- /dev/null +++ b/cognee/infrastructure/llm/prompts/answer_question.txt @@ -0,0 +1,2 @@ +Answer the question using the provided context. Be as brief as possible. +Each entry in the context is a paragraph, which is represented as a list with two elements [title, sentences] and sentences is a list of strings. \ No newline at end of file diff --git a/cognee/infrastructure/llm/prompts/answer_question_kg.txt b/cognee/infrastructure/llm/prompts/answer_question_kg.txt new file mode 100644 index 000000000..df303f54a --- /dev/null +++ b/cognee/infrastructure/llm/prompts/answer_question_kg.txt @@ -0,0 +1,2 @@ +Answer the question using the provided context. Be as brief as possible. +Each entry in the context is tuple of length 3, representing an edge of a knowledge graph with its two nodes. \ No newline at end of file diff --git a/cognee/infrastructure/llm/prompts/context_for_question.txt b/cognee/infrastructure/llm/prompts/context_for_question.txt new file mode 100644 index 000000000..cc9ccffa3 --- /dev/null +++ b/cognee/infrastructure/llm/prompts/context_for_question.txt @@ -0,0 +1,2 @@ +The question is: `{{ question }}` +And here is the context: `{{ context }}` \ No newline at end of file diff --git a/evals/llm_as_a_judge.py b/evals/llm_as_a_judge.py new file mode 100644 index 000000000..239c7aea9 --- /dev/null +++ b/evals/llm_as_a_judge.py @@ -0,0 +1,110 @@ +import argparse +import asyncio +import json +import statistics +from pathlib import Path + +import wget +from deepeval.dataset import EvaluationDataset +from deepeval.metrics import GEval +from deepeval.test_case import LLMTestCase, LLMTestCaseParams +from tqdm import tqdm + +import cognee +from cognee.api.v1.search import SearchType +from cognee.base_config import get_base_config +from cognee.infrastructure.llm.get_llm_client import get_llm_client +from cognee.infrastructure.llm.prompts import read_query_prompt, render_prompt + + +async def answer_without_cognee(instance): + args = { + "question": instance["question"], + "context": instance["context"], + } + user_prompt = render_prompt("context_for_question.txt", args) + system_prompt = read_query_prompt("answer_question.txt") + + llm_client = get_llm_client() + answer_prediction = await llm_client.acreate_structured_output( + text_input=user_prompt, + system_prompt=system_prompt, + response_model=str, + ) + return answer_prediction + +async def answer_with_cognee(instance): + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + for (title, sentences) in instance["context"]: + await cognee.add("\n".join(sentences), dataset_name = "HotPotQA") + await cognee.cognify("HotPotQA") + + search_results = await cognee.search( + SearchType.INSIGHTS, query_text=instance["question"] + ) + + args = { + "question": instance["question"], + "context": search_results, + } + user_prompt = render_prompt("context_for_question.txt", args) + system_prompt = read_query_prompt("answer_question_kg.txt") + + llm_client = get_llm_client() + answer_prediction = await llm_client.acreate_structured_output( + text_input=user_prompt, + system_prompt=system_prompt, + response_model=str, + ) + return answer_prediction + +correctness_metric = GEval( + name="Correctness", + model="gpt-4o-mini", + evaluation_params=[ + LLMTestCaseParams.ACTUAL_OUTPUT, + LLMTestCaseParams.EXPECTED_OUTPUT + ], + evaluation_steps=[ + "Determine whether the actual output is factually correct based on the expected output." + ] + ) + + +async def eval_correctness(with_cognee=True, num_samples=None): + base_config = get_base_config() + data_root_dir = base_config.data_root_directory + filepath = data_root_dir / Path("hotpot_dev_fullwiki_v1.json") + if not filepath.exists(): + url = 'http://curtis.ml.cmu.edu/datasets/hotpot/hotpot_dev_fullwiki_v1.json' + wget.download(url, out=data_root_dir) + with open(filepath, "r") as file: + dataset = json.load(file) + test_cases = [] + if not num_samples: + num_samples = len(dataset) + for instance in tqdm(dataset[:num_samples], desc="Evaluating correctness"): + if with_cognee: + answer = await answer_with_cognee(instance) + else: + answer = await answer_without_cognee(instance) + test_case = LLMTestCase( + input=instance["question"], + actual_output=answer, + expected_output=instance["answer"] + ) + test_cases.append(test_case) + evalset = EvaluationDataset(test_cases) + evalresults = evalset.evaluate([correctness_metric]) + avg_correctness = statistics.mean([result.metrics_data[0].score for result in evalresults.test_results]) + return avg_correctness + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--with_cognee", action="store_true") + parser.add_argument("--num_samples", type=int, default=500) + args = parser.parse_args() + avg_correctness = asyncio.run(eval_correctness(args.with_cognee, args.num_samples)) + print(f"Average correctness: {avg_correctness}") \ No newline at end of file From 4aa634d5e1a6697f444a417018a0cc81b1e698c4 Mon Sep 17 00:00:00 2001 From: Rita Aleksziev Date: Wed, 27 Nov 2024 16:14:05 +0100 Subject: [PATCH 2/9] Eval function takes eval_metric as input. Works with deepeval metrics like AnswerRelevancyMetric --- evals/llm_as_a_judge.py | 72 ++++++++++++++++++++++------------------- 1 file changed, 39 insertions(+), 33 deletions(-) diff --git a/evals/llm_as_a_judge.py b/evals/llm_as_a_judge.py index 239c7aea9..8dd1518a7 100644 --- a/evals/llm_as_a_judge.py +++ b/evals/llm_as_a_judge.py @@ -4,13 +4,14 @@ import json import statistics from pathlib import Path +import deepeval.metrics import wget from deepeval.dataset import EvaluationDataset -from deepeval.metrics import GEval -from deepeval.test_case import LLMTestCase, LLMTestCaseParams +from deepeval.test_case import LLMTestCase from tqdm import tqdm import cognee +import evals.deepeval_metrics from cognee.api.v1.search import SearchType from cognee.base_config import get_base_config from cognee.infrastructure.llm.get_llm_client import get_llm_client @@ -34,7 +35,6 @@ async def answer_without_cognee(instance): return answer_prediction async def answer_with_cognee(instance): - await cognee.prune.prune_data() await cognee.prune.prune_system(metadata=True) for (title, sentences) in instance["context"]: @@ -60,20 +60,23 @@ async def answer_with_cognee(instance): ) return answer_prediction -correctness_metric = GEval( - name="Correctness", - model="gpt-4o-mini", - evaluation_params=[ - LLMTestCaseParams.ACTUAL_OUTPUT, - LLMTestCaseParams.EXPECTED_OUTPUT - ], - evaluation_steps=[ - "Determine whether the actual output is factually correct based on the expected output." - ] - ) +async def eval_answers(instances, answers, eval_metric): + test_cases = [] + for i in range(len(answers)): + instance = instances[i] + answer = answers[i] + test_case = LLMTestCase( + input=instance["question"], + actual_output=answer, + expected_output=instance["answer"] + ) + test_cases.append(test_case) + evalset = EvaluationDataset(test_cases) + evalresults = evalset.evaluate([eval_metric]) + return evalresults -async def eval_correctness(with_cognee=True, num_samples=None): +async def eval_on_hotpotQA(answer_provider, num_samples, eval_metric): base_config = get_base_config() data_root_dir = base_config.data_root_directory filepath = data_root_dir / Path("hotpot_dev_fullwiki_v1.json") @@ -82,29 +85,32 @@ async def eval_correctness(with_cognee=True, num_samples=None): wget.download(url, out=data_root_dir) with open(filepath, "r") as file: dataset = json.load(file) - test_cases = [] if not num_samples: num_samples = len(dataset) - for instance in tqdm(dataset[:num_samples], desc="Evaluating correctness"): - if with_cognee: - answer = await answer_with_cognee(instance) - else: - answer = await answer_without_cognee(instance) - test_case = LLMTestCase( - input=instance["question"], - actual_output=answer, - expected_output=instance["answer"] - ) - test_cases.append(test_case) - evalset = EvaluationDataset(test_cases) - evalresults = evalset.evaluate([correctness_metric]) - avg_correctness = statistics.mean([result.metrics_data[0].score for result in evalresults.test_results]) - return avg_correctness + instances = dataset[:num_samples] + answers = [] + for instance in tqdm(instances, desc="Getting answers"): + answer = await answer_provider(instance) + answers.append(answer) + evalresults = await eval_answers(instances, answers, eval_metric) + avg_score = statistics.mean([result.metrics_data[0].score for result in evalresults.test_results]) + return avg_score if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--with_cognee", action="store_true") parser.add_argument("--num_samples", type=int, default=500) + parser.add_argument("--metric", type=str, default="correctness_metric") args = parser.parse_args() - avg_correctness = asyncio.run(eval_correctness(args.with_cognee, args.num_samples)) - print(f"Average correctness: {avg_correctness}") \ No newline at end of file + + try: + metric_cls = getattr(deepeval.metrics, args.metric) + metric = metric_cls() + except AttributeError: + metric = getattr(evals.deepeval_metrics, args.metric) + if args.with_cognee: + answer_provider = answer_with_cognee + else: + answer_provider = answer_without_cognee + avg_score = asyncio.run(eval_on_hotpotQA(answer_provider, args.num_samples, metric)) + print(f"Average {args.metric}: {avg_score}") \ No newline at end of file From 996b3a658b3570e76fcdf64b903a9c7a8d31b78e Mon Sep 17 00:00:00 2001 From: Rita Aleksziev Date: Thu, 28 Nov 2024 16:53:33 +0100 Subject: [PATCH 3/9] add custom metric implementation --- evals/deepeval_metrics.py | 14 ++++++++++++++ 1 file changed, 14 insertions(+) create mode 100644 evals/deepeval_metrics.py diff --git a/evals/deepeval_metrics.py b/evals/deepeval_metrics.py new file mode 100644 index 000000000..03f9f6dba --- /dev/null +++ b/evals/deepeval_metrics.py @@ -0,0 +1,14 @@ +from deepeval.metrics import GEval +from deepeval.test_case import LLMTestCaseParams + +correctness_metric = GEval( + name="Correctness", + model="gpt-4o-mini", + evaluation_params=[ + LLMTestCaseParams.ACTUAL_OUTPUT, + LLMTestCaseParams.EXPECTED_OUTPUT + ], + evaluation_steps=[ + "Determine whether the actual output is factually correct based on the expected output." + ] + ) From f966f099fc0064a7b7fcaf236255b069d64a35d9 Mon Sep 17 00:00:00 2001 From: Rita Aleksziev Date: Mon, 2 Dec 2024 12:18:00 +0100 Subject: [PATCH 4/9] Prompt renaming to more specific names. Minor code changes. --- ...uestion.txt => answer_hotpot_question.txt} | 0 ... => answer_hotpot_using_cognee_search.txt} | 0 evals/llm_as_a_judge.py | 21 +++++++++---------- 3 files changed, 10 insertions(+), 11 deletions(-) rename cognee/infrastructure/llm/prompts/{answer_question.txt => answer_hotpot_question.txt} (100%) rename cognee/infrastructure/llm/prompts/{answer_question_kg.txt => answer_hotpot_using_cognee_search.txt} (100%) diff --git a/cognee/infrastructure/llm/prompts/answer_question.txt b/cognee/infrastructure/llm/prompts/answer_hotpot_question.txt similarity index 100% rename from cognee/infrastructure/llm/prompts/answer_question.txt rename to cognee/infrastructure/llm/prompts/answer_hotpot_question.txt diff --git a/cognee/infrastructure/llm/prompts/answer_question_kg.txt b/cognee/infrastructure/llm/prompts/answer_hotpot_using_cognee_search.txt similarity index 100% rename from cognee/infrastructure/llm/prompts/answer_question_kg.txt rename to cognee/infrastructure/llm/prompts/answer_hotpot_using_cognee_search.txt diff --git a/evals/llm_as_a_judge.py b/evals/llm_as_a_judge.py index 8dd1518a7..0398f9422 100644 --- a/evals/llm_as_a_judge.py +++ b/evals/llm_as_a_judge.py @@ -63,37 +63,36 @@ async def answer_with_cognee(instance): async def eval_answers(instances, answers, eval_metric): test_cases = [] - for i in range(len(answers)): - instance = instances[i] - answer = answers[i] + for instance, answer in zip(instances, answers): test_case = LLMTestCase( input=instance["question"], actual_output=answer, expected_output=instance["answer"] ) test_cases.append(test_case) - evalset = EvaluationDataset(test_cases) - evalresults = evalset.evaluate([eval_metric]) - return evalresults + eval_set = EvaluationDataset(test_cases) + eval_results = eval_set.evaluate([eval_metric]) + return eval_results async def eval_on_hotpotQA(answer_provider, num_samples, eval_metric): base_config = get_base_config() data_root_dir = base_config.data_root_directory + if not Path(data_root_dir).exists(): + data_root_dir.mkdir() filepath = data_root_dir / Path("hotpot_dev_fullwiki_v1.json") if not filepath.exists(): url = 'http://curtis.ml.cmu.edu/datasets/hotpot/hotpot_dev_fullwiki_v1.json' wget.download(url, out=data_root_dir) with open(filepath, "r") as file: dataset = json.load(file) - if not num_samples: - num_samples = len(dataset) - instances = dataset[:num_samples] + + instances = dataset if not num_samples else dataset[:num_samples] answers = [] for instance in tqdm(instances, desc="Getting answers"): answer = await answer_provider(instance) answers.append(answer) - evalresults = await eval_answers(instances, answers, eval_metric) - avg_score = statistics.mean([result.metrics_data[0].score for result in evalresults.test_results]) + eval_results = await eval_answers(instances, answers, eval_metric) + avg_score = statistics.mean([result.metrics_data[0].score for result in eval_results.test_results]) return avg_score if __name__ == "__main__": From 0eb40d07617e244d43552853588d465f47bac57c Mon Sep 17 00:00:00 2001 From: Rita Aleksziev Date: Mon, 2 Dec 2024 13:31:39 +0100 Subject: [PATCH 5/9] updating dependencies with deepeval as optional --- poetry.lock | 2068 +++++++++++++++++++++++++++--------------------- pyproject.toml | 1 + 2 files changed, 1146 insertions(+), 923 deletions(-) diff --git a/poetry.lock b/poetry.lock index 96f9aec27..0450b1b12 100644 --- a/poetry.lock +++ b/poetry.lock @@ -13,13 +13,13 @@ files = [ [[package]] name = "aiohappyeyeballs" -version = "2.4.3" +version = "2.4.4" description = "Happy Eyeballs for asyncio" optional = false python-versions = ">=3.8" files = [ - {file = "aiohappyeyeballs-2.4.3-py3-none-any.whl", hash = "sha256:8a7a83727b2756f394ab2895ea0765a0a8c475e3c71e98d43d76f22b4b435572"}, - {file = "aiohappyeyeballs-2.4.3.tar.gz", hash = "sha256:75cf88a15106a5002a8eb1dab212525c00d1f4c0fa96e551c9fbe6f09a621586"}, + {file = 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deletion(-) diff --git a/evals/llm_as_a_judge.py b/evals/llm_as_a_judge.py index 0398f9422..e4bb7998c 100644 --- a/evals/llm_as_a_judge.py +++ b/evals/llm_as_a_judge.py @@ -78,7 +78,7 @@ async def eval_on_hotpotQA(answer_provider, num_samples, eval_metric): base_config = get_base_config() data_root_dir = base_config.data_root_directory if not Path(data_root_dir).exists(): - data_root_dir.mkdir() + Path(data_root_dir).mkdir() filepath = data_root_dir / Path("hotpot_dev_fullwiki_v1.json") if not filepath.exists(): url = 'http://curtis.ml.cmu.edu/datasets/hotpot/hotpot_dev_fullwiki_v1.json' From 0fbb50960b683cbee291362c0bbcd759c1c5eb05 Mon Sep 17 00:00:00 2001 From: Rita Aleksziev Date: Tue, 3 Dec 2024 15:59:03 +0100 Subject: [PATCH 7/9] prompt renaming --- evals/llm_as_a_judge.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/evals/llm_as_a_judge.py b/evals/llm_as_a_judge.py index e4bb7998c..c84795642 100644 --- a/evals/llm_as_a_judge.py +++ 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++++++++++++++++++++++----------------------- pyproject.toml | 4 +- 3 files changed, 208 insertions(+), 219 deletions(-) diff --git a/cognee/__init__.py b/cognee/__init__.py index e89ef1dc3..591140b87 100644 --- a/cognee/__init__.py +++ b/cognee/__init__.py @@ -1,9 +1,14 @@ -from .api.v1.config.config import config from .api.v1.add import add from .api.v1.cognify import cognify +from .api.v1.config.config import config from .api.v1.datasets.datasets import datasets -from .api.v1.search import search, SearchType, get_search_history from .api.v1.prune import prune - +from .api.v1.search import SearchType, get_search_history, search # Pipelines from .modules import pipelines + +try: + import dotenv + dotenv.load_dotenv() +except ImportError: + pass diff --git a/poetry.lock b/poetry.lock index 0450b1b12..7f2780406 100644 --- a/poetry.lock +++ b/poetry.lock @@ -359,21 +359,6 @@ files = [ astroid = ["astroid (>=2,<4)"] test = ["astroid (>=2,<4)", "pytest", "pytest-cov", "pytest-xdist"] 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