Fix linter issues

This commit is contained in:
vasilije 2025-01-05 20:24:04 +01:00
parent 2675836149
commit cbd15b98a5

View file

@ -1112,16 +1112,16 @@
}, },
"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"from evals.eval_on_hotpot import eval_on_hotpotQA\n", "# from evals.eval_on_hotpot import eval_on_hotpotQA\n",
"from evals.eval_on_hotpot import answer_with_cognee\n", "# from evals.eval_on_hotpot import answer_with_cognee\n",
"from evals.eval_on_hotpot import answer_without_cognee\n", "# from evals.eval_on_hotpot import answer_without_cognee\n",
"from evals.eval_on_hotpot import eval_answers\n", "# from evals.eval_on_hotpot import eval_answers\n",
"from cognee.base_config import get_base_config\n", "# from cognee.base_config import get_base_config\n",
"from pathlib import Path\n", "# from pathlib import Path\n",
"from tqdm import tqdm\n", "# from tqdm import tqdm\n",
"import wget\n", "# import wget\n",
"import json\n", "# import json\n",
"import statistics" "# import statistics"
], ],
"id": "5f36b67668fdb646", "id": "5f36b67668fdb646",
"outputs": [], "outputs": [],
@ -1136,27 +1136,27 @@
}, },
"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"answer_provider = answer_without_cognee # For native LLM answers use answer_without_cognee\n", "# answer_provider = answer_without_cognee # For native LLM answers use answer_without_cognee\n",
"num_samples = 10 # With cognee, it takes ~1m10s per sample\n", "# num_samples = 10 # With cognee, it takes ~1m10s per sample\n",
"\n", "# \n",
"base_config = get_base_config()\n", "# base_config = get_base_config()\n",
"data_root_dir = base_config.data_root_directory\n", "# data_root_dir = base_config.data_root_directory\n",
"\n", "# \n",
"if not Path(data_root_dir).exists():\n", "# if not Path(data_root_dir).exists():\n",
" Path(data_root_dir).mkdir()\n", "# Path(data_root_dir).mkdir()\n",
"\n", "# \n",
"filepath = data_root_dir / Path(\"hotpot_dev_fullwiki_v1.json\")\n", "# filepath = data_root_dir / Path(\"hotpot_dev_fullwiki_v1.json\")\n",
"if not filepath.exists():\n", "# if not filepath.exists():\n",
" url = 'http://curtis.ml.cmu.edu/datasets/hotpot/hotpot_dev_fullwiki_v1.json'\n", "# url = 'http://curtis.ml.cmu.edu/datasets/hotpot/hotpot_dev_fullwiki_v1.json'\n",
" wget.download(url, out=data_root_dir)\n", "# wget.download(url, out=data_root_dir)\n",
"\n", "# \n",
"with open(filepath, \"r\") as file:\n", "# with open(filepath, \"r\") as file:\n",
" dataset = json.load(file)\n", "# dataset = json.load(file)\n",
"instances = dataset if not num_samples else dataset[:num_samples]\n", "# instances = dataset if not num_samples else dataset[:num_samples]\n",
"answers = []\n", "# answers = []\n",
"for instance in tqdm(instances, desc=\"Getting answers\"):\n", "# for instance in tqdm(instances, desc=\"Getting answers\"):\n",
" answer = await answer_provider(instance)\n", "# answer = await answer_provider(instance)\n",
" answers.append(answer)" "# answers.append(answer)"
], ],
"id": "d5af4b516c6621a3", "id": "d5af4b516c6621a3",
"outputs": [ "outputs": [
@ -1179,8 +1179,8 @@
}, },
"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"from evals.deepeval_metrics import f1_score_metric\n", "# from evals.deepeval_metrics import f1_score_metric\n",
"from evals.deepeval_metrics import em_score_metric" "# from evals.deepeval_metrics import em_score_metric"
], ],
"id": "2bf69048a272158c", "id": "2bf69048a272158c",
"outputs": [], "outputs": [],
@ -1195,10 +1195,10 @@
}, },
"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"f1_metric = f1_score_metric()\n", "# f1_metric = f1_score_metric()\n",
"eval_results = await eval_answers(instances, answers, f1_metric)\n", "# eval_results = await eval_answers(instances, answers, f1_metric)\n",
"avg_f1_score = statistics.mean([result.metrics_data[0].score for result in eval_results.test_results])\n", "# avg_f1_score = statistics.mean([result.metrics_data[0].score for result in eval_results.test_results])\n",
"print(\"F1 score: \", avg_f1_score)" "# print(\"F1 score: \", avg_f1_score)"
], ],
"id": "72ba5f89cccbee6b", "id": "72ba5f89cccbee6b",
"outputs": [ "outputs": [
@ -1421,28 +1421,15 @@
{ {
"metadata": { "metadata": {
"ExecuteTime": { "ExecuteTime": {
"end_time": "2024-12-24T15:26:14.946766Z", "end_time": "2025-01-05T19:23:30.332977Z",
"start_time": "2024-12-24T15:26:14.944741Z" "start_time": "2025-01-05T19:23:30.331538Z"
} }
}, },
"cell_type": "code", "cell_type": "code",
"source": [ "source": "",
"for n in range(1,4):\n",
" print(n)"
],
"id": "783985c35d1126de", "id": "783985c35d1126de",
"outputs": [ "outputs": [],
{ "execution_count": null
"name": "stdout",
"output_type": "stream",
"text": [
"1\n",
"2\n",
"3\n"
]
}
],
"execution_count": 38
}, },
{ {
"cell_type": "markdown", "cell_type": "markdown",