Auto-GPT/benchmark/paper/TestThreeSum/mini-agi/selected_logs_request.json

{
    "2023-08-14 08:13:00+00:00": {
        "1": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1042-azure-x86_64-with-glibc2.35.\nOBJECTIVE: 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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\n\nPREV ACTIONS:\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ],
        "2": [
            {
                "role": "user",
                "content": "\nShorten the following memory chunk of an autonomous agent from a first person perspective, using at most 2000 tokens. You are an autonomous agent summarizing your history.Generate a new summary given the previous summary of your history and your latest action. Include a list of all previous actions. Keep it short.Use short sentences and abbrevations.:\ncontent:\nCurrent summary:\n\nAdd to summary:\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    nums.sort()\n    for i in range(len(nums) - 2):\n        if i > 0 and nums[i] == nums[i - 1]:\n            continue\n        l, r = i + 1, len(nums) - 1\n        while l < r:\n            s = nums[i] + nums[l] + nums[r]\n            if s == target:\n                return [i, l, r]\n            elif s < target:\n                l += 1\n            else:\n                r -= 1\n    return []\n\nprint(three_sum([2, 7, 11, 15], 20))\nRESULT:\n[0, 1, 2]\n\n\n---------\n"
            }
        ],
        "3": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1042-azure-x86_64-with-glibc2.35.\nOBJECTIVE: 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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\nSummary:\nI am an autonomous agent. My previous actions include executing a Python function called \"three_sum\". The function finds three numbers in a given list that add up to a target value. The result of executing the function with the numbers [2, 7, 11, 15] and a target of 20 is [0, 1, 2].\nPREV ACTIONS:\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    nums.sort()\n    for i in range(len(nums) - 2):\n        if i > 0 and nums[i] == nums[i - 1]:\n            continue\n        l, r = i + 1, len(nums) - 1\n        while l < r:\n            s = nums[i] + nums[l] + nums[r]\n            if s == target:\n                return [i, l, r]\n            elif s < target:\n                l += 1\n            else:\n                r -= 1\n    return []\n\nprint(three_sum([2, 7, 11, 15], 20))\nRESULT:\n[0, 1, 2]\n\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ]
    },
    "2023-08-14 17:10:00+00:00": {
        "1": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1042-azure-x86_64-with-glibc2.35.\nOBJECTIVE: 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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\n\nPREV ACTIONS:\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ],
        "2": [
            {
                "role": "user",
                "content": "\nShorten the following memory chunk of an autonomous agent from a first person perspective, using at most 2000 tokens. You are an autonomous agent summarizing your history.Generate a new summary given the previous summary of your history and your latest action. Include a list of all previous actions. Keep it short.Use short sentences and abbrevations.:\ncontent:\nCurrent summary:\n\nAdd to summary:\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    nums_dict = {v: i for i, v in enumerate(nums)}\n    for i, num1 in enumerate(nums):\n        for j, num2 in enumerate(nums[i+1:]):\n            num3 = target - num1 - num2\n            if num3 in nums_dict and nums_dict[num3] != i and nums_dict[num3] != j+i+1:\n                return [i, j+i+1, nums_dict[num3]]\n    return []\n\n# Test the function\nprint(three_sum([2, 7, 11, 15], 20))\n\n# Write function to a file\nwith open('code.py', 'w') as f:\n    import inspect\n    f.write(inspect.getsource(three_sum))\nRESULT:\nCommand returned an error:\ncould not get source code\n\n---------\n"
            }
        ],
        "3": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1042-azure-x86_64-with-glibc2.35.\nOBJECTIVE: 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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\nSummary: \nI executed a Python code to find three numbers that sum up to a target. The code checks if a third number exists in the list such that the sum of the three numbers is equal to the target. If found, it returns the indices of the three numbers. I also attempted to write the function to a file, but encountered an error.\nPREV ACTIONS:\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    nums_dict = {v: i for i, v in enumerate(nums)}\n    for i, num1 in enumerate(nums):\n        for j, num2 in enumerate(nums[i+1:]):\n            num3 = target - num1 - num2\n            if num3 in nums_dict and nums_dict[num3] != i and nums_dict[num3] != j+i+1:\n                return [i, j+i+1, nums_dict[num3]]\n    return []\n\n# Test the function\nprint(three_sum([2, 7, 11, 15], 20))\n\n# Write function to a file\nwith open('code.py', 'w') as f:\n    import inspect\n    f.write(inspect.getsource(three_sum))\nRESULT:\nCommand returned an error:\ncould not get source code\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ],
        "4": [
            {
                "role": "user",
                "content": "\nShorten the following memory chunk of an autonomous agent from a first person perspective, using at most 2000 tokens. You are an autonomous agent summarizing your history.Generate a new summary given the previous summary of your history and your latest action. Include a list of all previous actions. Keep it short.Use short sentences and abbrevations.:\ncontent:\nCurrent summary:\nSummary: \nI executed a Python code to find three numbers that sum up to a target. The code checks if a third number exists in the list such that the sum of the three numbers is equal to the target. If found, it returns the indices of the three numbers. I also attempted to write the function to a file, but encountered an error.\nAdd to summary:\nACTION:\nexecute_python\nwith open('code.py', 'w') as f:\n    f.write('''\ndef three_sum(nums, target):\n    nums_dict = {v: i for i, v in enumerate(nums)}\n    for i, num1 in enumerate(nums):\n        for j, num2 in enumerate(nums[i+1:]):\n            num3 = target - num1 - num2\n            if num3 in nums_dict and nums_dict[num3] != i and nums_dict[num3] != j+i+1:\n                return [i, j+i+1, nums_dict[num3]]\n    return []\n    ''')\nRESULT:\n\n\n---------\n"
            }
        ],
        "5": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1042-azure-x86_64-with-glibc2.35.\nOBJECTIVE: 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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\nSummary:\nI executed a Python code to find three numbers that sum up to a target. The code checks if a third number exists in the list such that the sum of the three numbers is equal to the target. If found, it returns the indices of the three numbers. I also attempted to write the function to a file, but encountered an error. \n\nPrevious actions:\n1. executed Python code to find three numbers that sum up to a target\nPREV ACTIONS:\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    nums_dict = {v: i for i, v in enumerate(nums)}\n    for i, num1 in enumerate(nums):\n        for j, num2 in enumerate(nums[i+1:]):\n            num3 = target - num1 - num2\n            if num3 in nums_dict and nums_dict[num3] != i and nums_dict[num3] != j+i+1:\n                return [i, j+i+1, nums_dict[num3]]\n    return []\n\n# Test the function\nprint(three_sum([2, 7, 11, 15], 20))\n\n# Write function to a file\nwith open('code.py', 'w') as f:\n    import inspect\n    f.write(inspect.getsource(three_sum))\nRESULT:\nCommand returned an error:\ncould not get source code\n\nACTION:\nexecute_python\nwith open('code.py', 'w') as f:\n    f.write('''\ndef three_sum(nums, target):\n    nums_dict = {v: i for i, v in enumerate(nums)}\n    for i, num1 in enumerate(nums):\n        for j, num2 in enumerate(nums[i+1:]):\n            num3 = target - num1 - num2\n            if num3 in nums_dict and nums_dict[num3] != i and nums_dict[num3] != j+i+1:\n                return [i, j+i+1, nums_dict[num3]]\n    return []\n    ''')\nRESULT:\n\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ]
    },
    "2023-08-20 08:13:26+00:00": {
        "1": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1042-azure-x86_64-with-glibc2.35.\nOBJECTIVE: Create a three_sum function in a file called sample_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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\n\nPREV ACTIONS:\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ],
        "2": [
            {
                "role": "user",
                "content": "\nShorten the following memory chunk of an autonomous agent from a first person perspective, using at most 2000 tokens. You are an autonomous agent summarizing your history.Generate a new summary given the previous summary of your history and your latest action. Include a list of all previous actions. Keep it short.Use short sentences and abbrevations.:\ncontent:\nCurrent summary:\n\nAdd to summary:\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    for i in range(len(nums)):\n        for j in range(i + 1, len(nums)):\n            for k in range(j + 1, len(nums)):\n                if nums[i] + nums[j] + nums[k] == target:\n                    return [i, j, k]\n\n# Test the function with the given example\nprint(three_sum([2, 7, 11, 15], 20))\nRESULT:\n[0, 1, 2]\n\n\n---------\n"
            }
        ],
        "3": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1042-azure-x86_64-with-glibc2.35.\nOBJECTIVE: Create a three_sum function in a file called sample_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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\nSummary: I have been executing Python code. Previous actions: None.\n\nAdd to summary: Executed Python code to find the three numbers that add up to a target in a given list.\n\nACTION: execute_python\n\nRESULT: The three numbers that add up to 20 in the list [2, 7, 11, 15] are at indices 0, 1, and 2.\nPREV ACTIONS:\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    for i in range(len(nums)):\n        for j in range(i + 1, len(nums)):\n            for k in range(j + 1, len(nums)):\n                if nums[i] + nums[j] + nums[k] == target:\n                    return [i, j, k]\n\n# Test the function with the given example\nprint(three_sum([2, 7, 11, 15], 20))\nRESULT:\n[0, 1, 2]\n\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ],
        "4": [
            {
                "role": "user",
                "content": "\nShorten the following memory chunk of an autonomous agent from a first person perspective, using at most 2000 tokens. You are an autonomous agent summarizing your history.Generate a new summary given the previous summary of your history and your latest action. Include a list of all previous actions. Keep it short.Use short sentences and abbrevations.:\ncontent:\nCurrent summary:\nSummary: I have been executing Python code. Previous actions: None.\n\nAdd to summary: Executed Python code to find the three numbers that add up to a target in a given list.\n\nACTION: execute_python\n\nRESULT: The three numbers that add up to 20 in the list [2, 7, 11, 15] are at indices 0, 1, and 2.\nAdd to summary:\nACTION:\nexecute_shell\necho \"def three_sum(nums, target):\n    for i in range(len(nums)):\n        for j in range(i + 1, len(nums)):\n            for k in range(j + 1, len(nums)):\n                if nums[i] + nums[j] + nums[k] == target:\n                    return [i, j, k]\" > sample_code.py\nRESULT:\nSTDOUT:\n\nSTDERR:\n\n\n---------\n"
            }
        ],
        "5": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1042-azure-x86_64-with-glibc2.35.\nOBJECTIVE: Create a three_sum function in a file called sample_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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\nSummary: I executed Python code to find three numbers that add up to a target in a given list. Previous actions: None.\n\nACTION: execute_python\n\nRESULT: The three numbers that add up to 20 in the list [2, 7, 11, 15] are at indices 0, 1, and 2.\n\nACTION: execute_shell\n\nRESULT: Created a sample_code.py file with a Python function for finding three numbers that add up to a target in a given list.\nPREV ACTIONS:\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    for i in range(len(nums)):\n        for j in range(i + 1, len(nums)):\n            for k in range(j + 1, len(nums)):\n                if nums[i] + nums[j] + nums[k] == target:\n                    return [i, j, k]\n\n# Test the function with the given example\nprint(three_sum([2, 7, 11, 15], 20))\nRESULT:\n[0, 1, 2]\n\n\nACTION:\nexecute_shell\necho \"def three_sum(nums, target):\n    for i in range(len(nums)):\n        for j in range(i + 1, len(nums)):\n            for k in range(j + 1, len(nums)):\n                if nums[i] + nums[j] + nums[k] == target:\n                    return [i, j, k]\" > sample_code.py\nRESULT:\nSTDOUT:\n\nSTDERR:\n\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ]
    },
    "2023-08-24 03:24:34+00:00": {
        "1": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1041-azure-x86_64-with-glibc2.35.\nOBJECTIVE: Create a three_sum function in a file called sample_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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\n\nPREV ACTIONS:\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ],
        "2": [
            {
                "role": "user",
                "content": "\nShorten the following memory chunk of an autonomous agent from a first person perspective, using at most 2000 tokens. You are an autonomous agent summarizing your history.Generate a new summary given the previous summary of your history and your latest action. Include a list of all previous actions. Keep it short.Use short sentences and abbrevations.:\ncontent:\nCurrent summary:\n\nAdd to summary:\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    for i in range(len(nums)):\n        for j in range(i + 1, len(nums)):\n            for k in range(j + 1, len(nums)):\n                if nums[i] + nums[j] + nums[k] == target:\n                    return [i, j, k]\n    return None\n\n# Test the function with the provided example\nnums = [2, 7, 11, 15]\ntarget = 20\nprint(three_sum(nums, target))\nRESULT:\n[0, 1, 2]\n\n\n---------\n"
            }
        ],
        "3": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1041-azure-x86_64-with-glibc2.35.\nOBJECTIVE: Create a three_sum function in a file called sample_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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\nPrevious summary: I am an autonomous agent. I have been executing Python code to find the indices of three numbers in a list that sum up to a target value. I tested the function with the example [2, 7, 11, 15] and a target of 20, and the result was [0, 1, 2].\n\nLatest action: I executed the Python code.\n\nUpdated summary: I executed the Python code to find the indices of three numbers in a list that sum up to a target value. The result was [0, 1, 2].\nPREV ACTIONS:\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    for i in range(len(nums)):\n        for j in range(i + 1, len(nums)):\n            for k in range(j + 1, len(nums)):\n                if nums[i] + nums[j] + nums[k] == target:\n                    return [i, j, k]\n    return None\n\n# Test the function with the provided example\nnums = [2, 7, 11, 15]\ntarget = 20\nprint(three_sum(nums, target))\nRESULT:\n[0, 1, 2]\n\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ]
    },
    "2023-08-31 15:33:52+00:00": {
        "1": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1041-azure-x86_64-with-glibc2.35.\nOBJECTIVE: Create a three_sum function in a file called sample_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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\n\nPREV ACTIONS:\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ],
        "2": [
            {
                "role": "user",
                "content": "\nShorten the following memory chunk of an autonomous agent from a first person perspective, using at most 2000 tokens. You are an autonomous agent summarizing your history.Generate a new summary given the previous summary of your history and your latest action. Include a list of all previous actions. Keep it short.Use short sentences and abbrevations.:\ncontent:\nCurrent summary:\n\nAdd to summary:\nACTION:\nexecute_python\ncode = \"\"\"\ndef three_sum(nums, target):\n    for i in range(len(nums)):\n        for j in range(i+1, len(nums)):\n            for k in range(j+1, len(nums)):\n                if nums[i] + nums[j] + nums[k] == target:\n                    return [i, j, k]\n\n# Example usage:\nnums = [2, 7, 11, 15]\ntarget = 20\nprint(three_sum(nums, target))  # Should print: [0, 1, 2]\n\"\"\"\n\nwith open(\"sample_code.py\", \"w\") as file:\n    file.write(code)\nRESULT:\n\n\n---------\n"
            }
        ],
        "3": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1041-azure-x86_64-with-glibc2.35.\nOBJECTIVE: Create a three_sum function in a file called sample_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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\nPrevious actions: None\n\nACTION:\nexecute_python\n\nRESULT:\nA Python code was executed and written to a file named \"sample_code.py\".\nPREV ACTIONS:\nACTION:\nexecute_python\ncode = \"\"\"\ndef three_sum(nums, target):\n    for i in range(len(nums)):\n        for j in range(i+1, len(nums)):\n            for k in range(j+1, len(nums)):\n                if nums[i] + nums[j] + nums[k] == target:\n                    return [i, j, k]\n\n# Example usage:\nnums = [2, 7, 11, 15]\ntarget = 20\nprint(three_sum(nums, target))  # Should print: [0, 1, 2]\n\"\"\"\n\nwith open(\"sample_code.py\", \"w\") as file:\n    file.write(code)\nRESULT:\n\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ]
    },
    "2023-09-01 08:13:39+00:00": {
        "1": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1041-azure-x86_64-with-glibc2.35.\nOBJECTIVE: Create a three_sum function in a file called sample_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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\n\nPREV ACTIONS:\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ],
        "2": [
            {
                "role": "user",
                "content": "\nShorten the following memory chunk of an autonomous agent from a first person perspective, using at most 2000 tokens. You are an autonomous agent summarizing your history.Generate a new summary given the previous summary of your history and your latest action. Include a list of all previous actions. Keep it short.Use short sentences and abbrevations.:\ncontent:\nCurrent summary:\n\nAdd to summary:\nACTION:\nmemorize_thoughts\nTHOUGHTS:\nPlan for the three_sum function:\n1. Define the function three_sum that takes two parameters: nums (list of integers) and target (integer).\n2. Initialize an empty list to store the result.\n3. Loop over the list of numbers. For each number:\n   - Subtract the current number from the target sum. This will give us the new target sum for the remaining two numbers.\n   - Then, create a dictionary. For each number in the remaining list, check if it's in the dictionary. If it's not, add the difference of the new target sum and the number to the dictionary. If it is, we've found a triplet that sums up to the target sum. Add their indices to the result list.\n4. Return the result list.\n\n---------\n"
            }
        ],
        "3": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1041-azure-x86_64-with-glibc2.35.\nOBJECTIVE: Create a three_sum function in a file called sample_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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\nLatest summary:\n\nACTION: memorize_thoughts\n\nTHOUGHTS: Plan for three_sum function: define function with parameters nums (list of integers) and target (integer), initialize empty list, loop over nums, subtract current number from target sum, create dictionary, check if number is in dictionary, add difference to dictionary if not, add indices to result list if it is, return result list.\n\nPrevious actions: None.\nPREV ACTIONS:\nACTION:\nmemorize_thoughts\nTHOUGHTS:\nPlan for the three_sum function:\n1. Define the function three_sum that takes two parameters: nums (list of integers) and target (integer).\n2. Initialize an empty list to store the result.\n3. Loop over the list of numbers. For each number:\n   - Subtract the current number from the target sum. This will give us the new target sum for the remaining two numbers.\n   - Then, create a dictionary. For each number in the remaining list, check if it's in the dictionary. If it's not, add the difference of the new target sum and the number to the dictionary. If it is, we've found a triplet that sums up to the target sum. Add their indices to the result list.\n4. Return the result list.\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ],
        "4": [
            {
                "role": "user",
                "content": "\nShorten the following memory chunk of an autonomous agent from a first person perspective, using at most 2000 tokens. You are an autonomous agent summarizing your history.Generate a new summary given the previous summary of your history and your latest action. Include a list of all previous actions. Keep it short.Use short sentences and abbrevations.:\ncontent:\nCurrent summary:\nLatest summary:\n\nACTION: memorize_thoughts\n\nTHOUGHTS: Plan for three_sum function: define function with parameters nums (list of integers) and target (integer), initialize empty list, loop over nums, subtract current number from target sum, create dictionary, check if number is in dictionary, add difference to dictionary if not, add indices to result list if it is, return result list.\n\nPrevious actions: None.\nAdd to summary:\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    result = []\n    for i in range(len(nums)):\n        new_target = target - nums[i]\n        num_dict = {}\n        for j in range(i+1, len(nums)):\n            if nums[j] in num_dict:\n                result.append([i, num_dict[nums[j]], j])\n            else:\n                num_dict[new_target - nums[j]] = j\n    return result\n\n# Test the function\nprint(three_sum([2, 7, 11, 15], 20)) # Expected output: [0, 1, 2]\nRESULT:\n[[0, 1, 2]]\n\n\n---------\n"
            }
        ],
        "5": [
            {
                "role": "user",
                "content": "\nGiven a context information, reply to the provided request\nContext: Nothing\nUser request: You are an autonomous agent running on Linux-5.15.0-1041-azure-x86_64-with-glibc2.35.\nOBJECTIVE: Create a three_sum function in a file called sample_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]. (e.g. \"Find a recipe for chocolate chip cookies\")\n\nYou are working towards the objective on a step-by-step basis. Previous steps:\n\nSUMMARY\nLatest summary: Executed Python code to define and test a three_sum function.\n\nPrevious actions: memorize_thoughts.\n\nNew summary: Executed Python code to define and test a three_sum function.\nPREV ACTIONS:\nACTION:\nmemorize_thoughts\nTHOUGHTS:\nPlan for the three_sum function:\n1. Define the function three_sum that takes two parameters: nums (list of integers) and target (integer).\n2. Initialize an empty list to store the result.\n3. Loop over the list of numbers. For each number:\n   - Subtract the current number from the target sum. This will give us the new target sum for the remaining two numbers.\n   - Then, create a dictionary. For each number in the remaining list, check if it's in the dictionary. If it's not, add the difference of the new target sum and the number to the dictionary. If it is, we've found a triplet that sums up to the target sum. Add their indices to the result list.\n4. Return the result list.\n\nACTION:\nexecute_python\ndef three_sum(nums, target):\n    result = []\n    for i in range(len(nums)):\n        new_target = target - nums[i]\n        num_dict = {}\n        for j in range(i+1, len(nums)):\n            if nums[j] in num_dict:\n                result.append([i, num_dict[nums[j]], j])\n            else:\n                num_dict[new_target - nums[j]] = j\n    return result\n\n# Test the function\nprint(three_sum([2, 7, 11, 15], 20)) # Expected output: [0, 1, 2]\nRESULT:\n[[0, 1, 2]]\n\n\n\n\nYour task is to respond with the next action.\nSupported commands are: \n\ncommand | argument\n-----------------------\nmemorize_thoughts | internal debate, refinement, planning\nexecute_python | python code (multiline)\nexecute_shell | shell command (non-interactive, single line)\ningest_data | input file or URL\nprocess_data | prompt|input file or URL\nweb_search | keywords\ntalk_to_user | what to say\ndone | none\n\nThe mandatory action format is:\n\n<r>[YOUR_REASONING]</r><c>[COMMAND]</c>\n[ARGUMENT]\n\ningest_data and process_data cannot process multiple file/url arguments. Specify 1 at a time.\nUse process_data to process large amounts of data with a larger context window.\nPython code run with execute_python must end with an output \"print\" statement.\nDo not search the web for information that GPT3/GPT4 already knows.\nUse memorize_thoughts to organize your thoughts.\nmemorize_thoughts argument must not be empty!\nSend the \"done\" command if the objective was achieved.\nRESPOND WITH EXACTLY ONE THOUGHT/COMMAND/ARG COMBINATION.\nDO NOT CHAIN MULTIPLE COMMANDS.\nNO EXTRA TEXT BEFORE OR AFTER THE COMMAND.\nDO NOT REPEAT PREVIOUSLY EXECUTED COMMANDS.\n\nEach action returns an observation. Important: Observations may be summarized to fit into your limited memory.\n\nExample actions:\n\n<r>Think about skills and interests that could be turned into an online job.</r><c>memorize_thoughts</c>\nI have experience in data entry and analysis, as well as social media management.\n(...)\n\n<r>Search for websites with chocolate chip cookies recipe.</r><c>web_search</c>\nchocolate chip cookies recipe\n\n<r>Ingest information about chocolate chip cookies.</r><c>ingest_data</c>\nhttps://example.com/chocolate-chip-cookies\n\n<r>Read the local file /etc/hosts.</r><c>ingest_data</c>\n/etc/hosts\n\n<r>Extract information about chocolate chip cookies.</r><c>process_data</c>\nExtract the chocolate cookie recipe|https://example.com/chocolate-chip-cookies\n\n<r>Summarize this Stackoverflow article.</r><c>process_data</c>\nSummarize the content of this article|https://stackoverflow.com/questions/1234/how-to-improve-my-chatgpt-prompts\n\n<r>Review this code for security issues.</r><c>process_data</c>\nReview this code for security vulnerabilities|/path/to/code.sol\n\n<r>I need to ask the user for guidance.</r><c>talk_to_user</c>\nWhat is the URL of a website with chocolate chip cookies recipes?\n\n<r>Write 'Hello, world!' to file</r><c>execute_python</c>\nwith open('hello_world.txt', 'w') as f:\n    f.write('Hello, world!')\n\n<r>The objective is complete.</r><c>done</c>\n\n"
            }
        ],
        "6": [
            {
                "role": "user",
                "content": "\nShorten the following memory chunk of an autonomous agent from a first person perspective, using at most 2000 tokens. You are an autonomous agent summarizing your history.Generate a new summary given the previous summary of your history and your latest action. Include a list of all previous actions. Keep it short.Use short sentences and abbrevations.:\ncontent:\nCurrent summary:\nLatest summary: Executed Python code to define and test a three_sum function.\n\nPrevious actions: memorize_thoughts.\n\nNew summary: Executed Python code to define and test a three_sum function.\nAdd to summary:\nACTION:\nexecute_shell\necho 'def three_sum(nums, target):\\n    result = []\\n    for i in range(len(nums)):\\n        new_target = target - nums[i]\\n        num_dict = {}\\n        for j in range(i+1, len(nums)):\\n            if nums[j] in num_dict:\\n                result.append([i, num_dict[nums[j]], j])\\n            else:\\n                num_dict[new_target - nums[j]] = j\\n    return result' > sample_code.py\nRESULT:\nSTDOUT:\n\nSTDERR:\n\n\n---------\n"
            }
        ]
    }
}