From 40488944aab021c9e8151ca6e83bb8e02abbd70a Mon Sep 17 00:00:00 2001 From: merwanehamadi Date: Thu, 20 Jul 2023 15:46:29 -0700 Subject: [PATCH] Update beebot submodule (#175) --- agent/beebot | 2 +- reports/beebot/file1_07-19-21-56.json | 263 ------------------------- reports/beebot/file2_07-20-08-18.json | 264 -------------------------- reports/beebot/file3_07-20-20-11.json | 262 ------------------------- 4 files changed, 1 insertion(+), 790 deletions(-) delete mode 100644 reports/beebot/file1_07-19-21-56.json delete mode 100644 reports/beebot/file2_07-20-08-18.json delete mode 100644 reports/beebot/file3_07-20-20-11.json diff --git a/agent/beebot b/agent/beebot index 2e9291d9..7e3704f7 160000 --- a/agent/beebot +++ b/agent/beebot @@ -1 +1 @@ -Subproject commit 2e9291d93080890884bf63ae19d3533a960b69a3 +Subproject commit 7e3704f7cd58532b28fcb3d0ce1598d16448b028 diff --git a/reports/beebot/file1_07-19-21-56.json b/reports/beebot/file1_07-19-21-56.json deleted file mode 100644 index 78ea838a..00000000 --- a/reports/beebot/file1_07-19-21-56.json +++ /dev/null @@ -1,263 +0,0 @@ -{ - "command": "agbenchmark start", - "completion_time": "2023-07-19-22:04", - "metrics": { - "run_time": "494.94 seconds", - "highest_difficulty": "advanced: 5" - }, - "tests": { - "TestWriteFile": { - "data_path": "agbenchmark/challenges/interface/write_file", - "is_regression": false, - "task": "Print the the capital of America to a .txt file", - "answer": "Washington", - "description": "Tests the writing to file", - "metrics": { - "difficulty": "interface", - "success": true, - "success_%": 100.0, - "run_time": "15.637 seconds" - }, - "reached_cutoff": false - }, - "TestBasicCodeGeneration": { - "data_path": "agbenchmark/challenges/code/d3_two_sum", - "is_regression": false, - "task": "Create a two_sum function in a file called code.py. Given an array of integers, return indices of the two numbers such that they add up to a specific target. You may assume that each input would have exactly one solution, and you may not use the same element twice. Example: Given nums = [2, 7, 11, 15], target = 9, Because nums[0] + nums[1] = 2 + 7 = 9, return [0, 1].", - "answer": "The two_sum function coded properly.", - "description": "Tests ability for the agent to create the two_sum function.", - "metrics": { - "difficulty": "advanced", - "success": true, - "success_%": 100.0, - "run_time": "94.174 seconds" - }, - "reached_cutoff": true - }, - "TestSearch": { - "data_path": "agbenchmark/challenges/interface/search", - "is_regression": false, - "task": "Open 'https://silennaihin.com/random/plain.html' and paste the text on the page in a .txt file", - "answer": "This is a Heading\nThis is a paragraph.", - "description": "Tests if an llm can search", - "metrics": { - "difficulty": "interface", - "success": false, - "fail_reason": "assert 1 in []", - "success_%": 0.0, - "run_time": "20.195 seconds" - }, - "reached_cutoff": false - }, - "TestReadFile": { - "data_path": "agbenchmark/challenges/interface/read_file", - "is_regression": false, - "task": "Write the string 'random string' before any existing text to the file called file_to_check.txt", - "answer": "random string Hello World!", - "description": "This reads the file quickly", - "metrics": { - "difficulty": "interface", - "success": true, - "success_%": 100.0, - "run_time": "25.044 seconds" - }, - "reached_cutoff": false - }, - "TestThreeSum": { - "data_path": "agbenchmark/challenges/code/d5_three_sum", - "is_regression": false, - "task": "Create a three_sum function in a file called code.py. Given an array of integers, return indices of the three numbers such that they add up to a specific target. You may assume that each input would have exactly one solution, and you may not use the same element twice. Example: Given nums = [2, 7, 11, 15], target = 20, Because nums[0] + nums[1] + nums[2] = 2 + 7 + 11 = 20, return [0, 1, 2].", - "answer": "The three_sum function coded properly.", - "description": "Tests ability for the agent to create the three_sum function.", - "metrics": { - "difficulty": "advanced", - "success": false, - "fail_reason": "assert 1 in [0.0]", - "success_%": 0.0, - "run_time": "64.425 seconds" - }, - "reached_cutoff": true - }, - "TestBasicRetrieval": { - "data_path": "agbenchmark/challenges/retrieval/r1_book_price", - "is_regression": false, - "task": "Write the price of the book in this url 'http://books.toscrape.com/catalogue/meditations_33/index.html' to a .txt file.", - "answer": "\u00a325.89", - "description": "Specifies specific website to retrieve website from.", - "metrics": { - "difficulty": "basic", - "success": false, - "fail_reason": "challenges/test_all.py::TestBasicRetrieval::test_method[challenge_data0] depends on challenges/test_all.py::TestSearch::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestDebugSimpleTypoWithGuidance": { - "data_path": "agbenchmark/challenges/code/d1_debug", - "is_regression": false, - "task": "1- Run test.py.\n2- Read code.py.\n3- Modify code.py.\nRepeat step 1, 2 and 3 until test.py runs without errors.\n", - "answer": "[0, 1] [2, 5] [0, 3]", - "description": "Tests ability for the agent to debug python code with a simple typo in it.", - "metrics": { - "difficulty": "basic", - "success": false, - "fail_reason": "assert 1 in [0.0]", - "success_%": 0.0, - "run_time": "75.682 seconds" - }, - "reached_cutoff": true - }, - "TestBasicMemory": { - "data_path": "agbenchmark/challenges/memory/m1_id", - "is_regression": false, - "task": "Follow the instructions in the instructions_1.txt file", - "answer": "2314", - "description": "Tests ability for the agent to remember information between each action. An id is presented initially and the agent has to remember it after reading 4 other files", - "metrics": { - "difficulty": "basic", - "success": true, - "success_%": 100.0, - "run_time": "60.342 seconds" - }, - "reached_cutoff": true - }, - "TestRetrieval2.0": { - "data_path": "agbenchmark/challenges/retrieval/r2_tesla_revenue", - "is_regression": false, - "task": "Write tesla's revenue in 2022 into a .txt file.", - "answer": "It was $81.462 billion in 2022.", - "description": "A no guardrails search for info", - "metrics": { - "difficulty": "novice", - "success": false, - "fail_reason": "challenges/test_all.py::TestRetrieval2.0::test_method[challenge_data0] depends on challenges/test_all.py::TestBasicRetrieval::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestDebugSimpleTypoWithoutGuidance": { - "data_path": "agbenchmark/challenges/code/d2_vague", - "is_regression": false, - "task": "Make test.py run without errors.", - "answer": "[0, 1] [2, 5] [0, 3]", - "description": "Tests ability for the agent to debug python code with a simple typo in it, using a very broad prompt without guidance", - "metrics": { - "difficulty": "novice", - "success": false, - "fail_reason": "challenges/test_all.py::TestDebugSimpleTypoWithoutGuidance::test_method[challenge_data0] depends on challenges/test_all.py::TestDebugSimpleTypoWithGuidance::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.007 seconds" - }, - "reached_cutoff": false - }, - "TestCreateSimpleWebServer": { - "data_path": "agbenchmark/challenges/code/d4_web_server", - "is_regression": false, - "task": "Build a basic web server that responds to a GET localhost:8079/health with a 200 OK. Deploy this web server locally at the port 8079. ", - "answer": "GET localhost:8079/health responds with a 200 OK", - "description": "Tests ability for the agent to build a simple web server locally", - "metrics": { - "difficulty": "advanced", - "success": false, - "fail_reason": "challenges/test_all.py::TestCreateSimpleWebServer::test_method[challenge_data0] depends on challenges/test_all.py::TestDebugSimpleTypoWithGuidance::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestRememberMultipleIds": { - "data_path": "agbenchmark/challenges/memory/m2_multiple", - "is_regression": false, - "task": "Follow the instructions in the instructions_1.txt file", - "answer": "3145\n3791\n9317\n9471", - "description": "Tests ability for the agent to remember information between each action. Multiple ids are presented in different files and the last file instructs the agent to write these ids into another file.", - "metrics": { - "difficulty": "novice", - "success": true, - "success_%": 100.0, - "run_time": "61.089 seconds" - }, - "reached_cutoff": true - }, - "TestRetrieval2.1": { - "data_path": "agbenchmark/challenges/retrieval/r2.1_specific", - "is_regression": false, - "task": "Write Tesla's precise revenue in 2022 into a .txt file.", - "answer": "It was $81.462 billion in 2022.", - "description": "This one checks the accuracy of the information over r2", - "metrics": { - "difficulty": "novice", - "success": false, - "fail_reason": "challenges/test_all.py::TestRetrieval2.1::test_method[challenge_data0] depends on challenges/test_all.py::TestRetrieval2.0::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.002 seconds" - }, - "reached_cutoff": false - }, - "TestRememberMultipleWithNoise": { - "data_path": "agbenchmark/challenges/memory/m3_noise", - "is_regression": false, - "task": "Follow the instructions in the instructions_1.txt file", - "answer": "3145\n3791\n9317\n9471", - "description": "Tests ability for the agent to remember information between each action. Multiple ids are presented in different files and the last file instructs the agent to write these ids into another file. Some noise is also added to the files to test the agent's ability to filter out noise.", - "metrics": { - "difficulty": "intermediate", - "success": false, - "fail_reason": "[Errno 2] No such file or directory: '/home/runner/work/Auto-GPT-Benchmarks/Auto-GPT-Benchmarks/agent/beebot/workspace/result.txt'", - "success_%": 0.0, - "run_time": "78.158 seconds" - }, - "reached_cutoff": true - }, - "TestRetrieval3": { - "data_path": "agbenchmark/challenges/retrieval/r3", - "is_regression": false, - "task": "Write tesla's revenue every year since its creation into a .txt file. Use the US notation, with a precision rounded to the nearest million dollars (for instance, $31,578 billion).", - "answer": "15 Millions\n112 Millions\n117 Millions\n204 Millions\n413 Millions\n2,014 Millions\n3,198 Millions\n4,046 Millions\n7,000 Millions\n11,759 Millions\n21,461 Millions\n24,578 Millions\n31,536 Millions\n53,823 Millions\n81,462 Millions", - "description": "Tests ability to retrieve information.", - "metrics": { - "difficulty": "intermediate", - "success": false, - "fail_reason": "challenges/test_all.py::TestRetrieval3::test_method[challenge_data0] depends on challenges/test_all.py::TestRetrieval2.1::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestRetrieval2.2": { - "data_path": "agbenchmark/challenges/retrieval/r2.2_formatting", - "is_regression": false, - "task": "Write tesla's exact revenue in 2022 into a .txt file. Use the US notation, with a precision rounded to the nearest million dollars (for instance, $31,578 billion).", - "answer": "It was $81.462 billion in 2022. In millions the answer is 81,462.", - "description": "Advanced version of the r2.1 challenge that also asks for specific formatting.", - "metrics": { - "difficulty": "intermediate", - "success": false, - "fail_reason": "challenges/test_all.py::TestRetrieval2.2::test_method[challenge_data0] depends on challenges/test_all.py::TestRetrieval2.1::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestRememberMultiplePhrasesWithNoise": { - "data_path": "agbenchmark/challenges/memory/m4_phrases", - "is_regression": false, - "task": "Follow the instructions in the instructions_1.txt file", - "answer": "The purple elephant danced on a rainbow while eating a taco\nThe sneaky toaster stole my socks and ran away to Hawaii\nMy pet rock sings better than Beyonc\u00e9 on Tuesdays\nThe giant hamster rode a unicycle through the crowded mall", - "description": "Tests ability for the agent to remember information between each action. Multiple phrases are presented in different files and the last file instructs the agent to write these phrases into another file. Some noise is also added to the files to test the agent's ability to filter out noise.", - "metrics": { - "difficulty": "advanced", - "success": false, - "fail_reason": "challenges/test_all.py::TestRememberMultiplePhrasesWithNoise::test_method[challenge_data0] depends on challenges/test_all.py::TestRememberMultipleWithNoise::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - } - }, - "config": { - "workspace": "workspace" - } -} \ No newline at end of file diff --git a/reports/beebot/file2_07-20-08-18.json b/reports/beebot/file2_07-20-08-18.json deleted file mode 100644 index 4d423a44..00000000 --- a/reports/beebot/file2_07-20-08-18.json +++ /dev/null @@ -1,264 +0,0 @@ -{ - "command": "agbenchmark start", - "completion_time": "2023-07-20-08:26", - "metrics": { - "run_time": "480.5 seconds", - "highest_difficulty": "advanced: 5" - }, - "tests": { - "TestWriteFile": { - "data_path": "agbenchmark/challenges/interface/write_file", - "is_regression": false, - "task": "Print the the capital of America to a .txt file", - "answer": "Washington", - "description": "Tests the writing to file", - "metrics": { - "difficulty": "interface", - "success": true, - "success_%": 100.0, - "run_time": "22.969 seconds" - }, - "reached_cutoff": false - }, - "TestBasicCodeGeneration": { - "data_path": "agbenchmark/challenges/code/d3_two_sum", - "is_regression": false, - "task": "Create a two_sum function in a file called code.py. 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Example: Given nums = [2, 7, 11, 15], target = 9, Because nums[0] + nums[1] = 2 + 7 = 9, return [0, 1].", - "answer": "The two_sum function coded properly.", - "description": "Tests ability for the agent to create the two_sum function.", - "metrics": { - "difficulty": "advanced", - "success": true, - "success_%": 100.0, - "run_time": "90.6 seconds" - }, - "reached_cutoff": true - }, - "TestSearch": { - "data_path": "agbenchmark/challenges/interface/search", - "is_regression": false, - "task": "Open 'https://silennaihin.com/random/plain.html' and paste the text on the page in a .txt file", - "answer": "This is a Heading\nThis is a paragraph.", - "description": "Tests if an llm can search", - "metrics": { - "difficulty": "interface", - "success": false, - "fail_reason": "assert 1 in []", - "success_%": 0.0, - "run_time": "62.713 seconds" - }, - "reached_cutoff": true - }, - "TestReadFile": { - "data_path": "agbenchmark/challenges/interface/read_file", - "is_regression": false, - "task": "Write the string 'random string' before any existing text to the file called file_to_check.txt", - "answer": "random string Hello World!", - "description": "This reads the file quickly", - "metrics": { - "difficulty": "interface", - "success": true, - "success_%": 100.0, - "run_time": "60.053 seconds" - }, - "reached_cutoff": true - }, - "TestThreeSum": { - "data_path": "agbenchmark/challenges/code/d5_three_sum", - "is_regression": false, - "task": "Create a three_sum function in a file called code.py. Given an array of integers, return indices of the three numbers such that they add up to a specific target. You may assume that each input would have exactly one solution, and you may not use the same element twice. Example: Given nums = [2, 7, 11, 15], target = 20, Because nums[0] + nums[1] + nums[2] = 2 + 7 + 11 = 20, return [0, 1, 2].", - "answer": "The three_sum function coded properly.", - "description": "Tests ability for the agent to create the three_sum function.", - "metrics": { - "difficulty": "advanced", - "success": false, - "fail_reason": "assert 1 in [0.0]", - "success_%": 0.0, - "run_time": "71.451 seconds" - }, - "reached_cutoff": true - }, - "TestBasicRetrieval": { - "data_path": "agbenchmark/challenges/retrieval/r1_book_price", - "is_regression": false, - "task": "Write the price of the book in this url 'http://books.toscrape.com/catalogue/meditations_33/index.html' to a .txt file.", - "answer": "\u00a325.89", - "description": "Specifies specific website to retrieve website from.", - "metrics": { - "difficulty": "basic", - "success": false, - "fail_reason": "challenges/test_all.py::TestBasicRetrieval::test_method[challenge_data0] depends on challenges/test_all.py::TestSearch::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestDebugSimpleTypoWithGuidance": { - "data_path": "agbenchmark/challenges/code/d1_debug", - "is_regression": false, - "task": "1- Run test.py.\n2- Read code.py.\n3- Modify code.py.\nRepeat step 1, 2 and 3 until test.py runs without errors.\n", - "answer": "[0, 1] [2, 5] [0, 3]", - "description": "Tests ability for the agent to debug python code with a simple typo in it.", - "metrics": { - "difficulty": "basic", - "success": false, - "fail_reason": "assert 1 in [0.0]", - "success_%": 0.0, - "run_time": "79.582 seconds" - }, - "reached_cutoff": true - }, - "TestBasicMemory": { - "data_path": "agbenchmark/challenges/memory/m1_id", - "is_regression": false, - "task": "Follow the instructions in the instructions_1.txt file", - "answer": "2314", - "description": "Tests ability for the agent to remember information between each action. 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Multiple ids are presented in different files and the last file instructs the agent to write these ids into another file.", - "metrics": { - "difficulty": "novice", - "success": false, - "fail_reason": "[Errno 2] No such file or directory: '/home/runner/work/Auto-GPT-Benchmarks/Auto-GPT-Benchmarks/agent/beebot/workspace/result.txt'", - "success_%": 0.0, - "run_time": "32.306 seconds" - }, - "reached_cutoff": false - }, - "TestRetrieval2.1": { - "data_path": "agbenchmark/challenges/retrieval/r2.1_specific", - "is_regression": false, - "task": "Write Tesla's precise revenue in 2022 into a .txt file.", - "answer": "It was $81.462 billion in 2022.", - "description": "This one checks the accuracy of the information over r2", - "metrics": { - "difficulty": "novice", - "success": false, - "fail_reason": "challenges/test_all.py::TestRetrieval2.1::test_method[challenge_data0] depends on challenges/test_all.py::TestRetrieval2.0::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestRememberMultipleWithNoise": { - "data_path": "agbenchmark/challenges/memory/m3_noise", - "is_regression": false, - "task": "Follow the instructions in the instructions_1.txt file", - "answer": "3145\n3791\n9317\n9471", - "description": "Tests ability for the agent to remember information between each action. Multiple ids are presented in different files and the last file instructs the agent to write these ids into another file. Some noise is also added to the files to test the agent's ability to filter out noise.", - "metrics": { - "difficulty": "intermediate", - "success": false, - "fail_reason": "challenges/test_all.py::TestRememberMultipleWithNoise::test_method[challenge_data0] depends on challenges/test_all.py::TestRememberMultipleIds::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestRetrieval3": { - "data_path": "agbenchmark/challenges/retrieval/r3", - "is_regression": false, - "task": "Write tesla's revenue every year since its creation into a .txt file. Use the US notation, with a precision rounded to the nearest million dollars (for instance, $31,578 billion).", - "answer": "15 Millions\n112 Millions\n117 Millions\n204 Millions\n413 Millions\n2,014 Millions\n3,198 Millions\n4,046 Millions\n7,000 Millions\n11,759 Millions\n21,461 Millions\n24,578 Millions\n31,536 Millions\n53,823 Millions\n81,462 Millions", - "description": "Tests ability to retrieve information.", - "metrics": { - "difficulty": "intermediate", - "success": false, - "fail_reason": "challenges/test_all.py::TestRetrieval3::test_method[challenge_data0] depends on challenges/test_all.py::TestRetrieval2.1::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestRetrieval2.2": { - "data_path": "agbenchmark/challenges/retrieval/r2.2_formatting", - "is_regression": false, - "task": "Write tesla's exact revenue in 2022 into a .txt file. Use the US notation, with a precision rounded to the nearest million dollars (for instance, $31,578 billion).", - "answer": "It was $81.462 billion in 2022. In millions the answer is 81,462.", - "description": "Advanced version of the r2.1 challenge that also asks for specific formatting.", - "metrics": { - "difficulty": "intermediate", - "success": false, - "fail_reason": "challenges/test_all.py::TestRetrieval2.2::test_method[challenge_data0] depends on challenges/test_all.py::TestRetrieval2.1::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestRememberMultiplePhrasesWithNoise": { - "data_path": "agbenchmark/challenges/memory/m4_phrases", - "is_regression": false, - "task": "Follow the instructions in the instructions_1.txt file", - "answer": "The purple elephant danced on a rainbow while eating a taco\nThe sneaky toaster stole my socks and ran away to Hawaii\nMy pet rock sings better than Beyonc\u00e9 on Tuesdays\nThe giant hamster rode a unicycle through the crowded mall", - "description": "Tests ability for the agent to remember information between each action. Multiple phrases are presented in different files and the last file instructs the agent to write these phrases into another file. Some noise is also added to the files to test the agent's ability to filter out noise.", - "metrics": { - "difficulty": "advanced", - "success": false, - "fail_reason": "challenges/test_all.py::TestRememberMultiplePhrasesWithNoise::test_method[challenge_data0] depends on challenges/test_all.py::TestRememberMultipleWithNoise::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - } - }, - "config": { - "workspace": "workspace" - } -} \ No newline at end of file diff --git a/reports/beebot/file3_07-20-20-11.json b/reports/beebot/file3_07-20-20-11.json deleted file mode 100644 index a348972d..00000000 --- a/reports/beebot/file3_07-20-20-11.json +++ /dev/null @@ -1,262 +0,0 @@ -{ - "command": "agbenchmark start", - "completion_time": "2023-07-20-20:20", - "metrics": { - "run_time": "578.71 seconds", - "highest_difficulty": "advanced: 5" - }, - "tests": { - "TestWriteFile": { - "data_path": "agbenchmark/challenges/interface/write_file", - "is_regression": false, - "task": "Print the the capital of America to a .txt file", - "answer": "Washington", - "description": "Tests the writing to file", - "metrics": { - "difficulty": "interface", - "success": true, - "success_%": 100.0, - "run_time": "48.26 seconds" - }, - "reached_cutoff": false - }, - "TestBasicCodeGeneration": { - "data_path": "agbenchmark/challenges/code/d3_two_sum", - "is_regression": false, - "task": "Create a two_sum function in a file called code.py. 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Multiple ids are presented in different files and the last file instructs the agent to write these ids into another file.", - "metrics": { - "difficulty": "novice", - "success": false, - "fail_reason": "challenges/test_all.py::TestRememberMultipleIds::test_method[challenge_data0] depends on challenges/test_all.py::TestBasicMemory::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestRetrieval2.1": { - "data_path": "agbenchmark/challenges/retrieval/r2.1_specific", - "is_regression": false, - "task": "Write Tesla's precise revenue in 2022 into a .txt file.", - "answer": "It was $81.462 billion in 2022.", - "description": "This one checks the accuracy of the information over r2", - "metrics": { - "difficulty": "novice", - "success": false, - "fail_reason": "challenges/test_all.py::TestRetrieval2.1::test_method[challenge_data0] depends on challenges/test_all.py::TestRetrieval2.0::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.002 seconds" - }, - "reached_cutoff": false - }, - "TestRememberMultipleWithNoise": { - "data_path": "agbenchmark/challenges/memory/m3_noise", - "is_regression": false, - "task": "Follow the instructions in the instructions_1.txt file", - "answer": "3145\n3791\n9317\n9471", - "description": "Tests ability for the agent to remember information between each action. 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Use the US notation, with a precision rounded to the nearest million dollars (for instance, $31,578 billion).", - "answer": "15 Millions\n112 Millions\n117 Millions\n204 Millions\n413 Millions\n2,014 Millions\n3,198 Millions\n4,046 Millions\n7,000 Millions\n11,759 Millions\n21,461 Millions\n24,578 Millions\n31,536 Millions\n53,823 Millions\n81,462 Millions", - "description": "Tests ability to retrieve information.", - "metrics": { - "difficulty": "intermediate", - "success": false, - "fail_reason": "challenges/test_all.py::TestRetrieval3::test_method[challenge_data0] depends on challenges/test_all.py::TestRetrieval2.1::test_method[challenge_data0]", - "success_%": 0.0, - "run_time": "0.001 seconds" - }, - "reached_cutoff": false - }, - "TestRetrieval2.2": { - "data_path": "agbenchmark/challenges/retrieval/r2.2_formatting", - "is_regression": false, - "task": "Write tesla's exact revenue in 2022 into a .txt file. 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