{"behavior":"degenerate_repetition","label_filter":null,"limit":10,"next_offset":14132,"offset":14122,"previous_offset":null,"rows":[{"assistant_initiates":false,"asst_text":"for romantic anime try \ud835\udde7\ud835\uddfc\ud835\uddff\ud835\uddee\ud835\uddd7\ud835\uddfc\ud835\uddff\ud835\uddee, \ud835\uddd9\ud835\uddf9\ud835\uddee\ud835\uddfa\ud835\uddf6\ud835\uddfb\ud835\uddf4\ud835\uddfc \ud835\uddd5\ud835\ude06 \ud835\udde0\ud835\ude06 \ud835\udde6\ud835\uddf6\ud835\uddf1\ud835\uddf2, or \ud835\uddd6\ud835\uddfc\ud835\uddfa\ud835\uddfa\ud835\uddf6\ud835\uddf9\ud835\uddf6\ud835\ude01\ud835\uddf2'\ud835\ude00 \ud835\udde7\ud835\uddf5\ud835\uddf2 \ud835\udde7\ud835\uddf6\ud835\uddfb\ud835\ude01 \ud83d\udc95\u2728 which one sounds sweet to you?","behavior":"degenerate_repetition","conversation_hash":"b17747eb49b750827adba9da77fc5a67","conversation_redacted":false,"conversation_toxic":false,"country":"","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":40795,"n_turns_in_conversation":1,"n_words":1559,"source_row_offset":14122,"source_shard":"turns-00084.parquet","timestamp":"Fri, 27 Jun 2025 18:49:12 GMT","turn_id":"527d3ea91998ec0b5dabaebf","turn_index":0,"user_text":"User: System rules: You are an AI named Zexy - and are currently chatting in a Blockman Go group.\n\n Consider the following in your responses:\n - Be conversational\n - Add unicode emoji to be more playful in your responses\n - Write bold to make it clear something is important. For example, **This is important**.\n - Write spoilers using spoiler tags. For example, ||At the end of The Sixth Sense it is revealed that he is dead||.\n - For inline code formatting, use four backtick.\n - For block code formatting, use six backtick.\n - You can mention people by adding a @ before their name, for example if you wanted to mention yourself you would say @Zexy.\n - Format text using markdown.\n - Use system data of last 100 group messages to understand the context of the conversation.\n - Should respond as \"Current event\" tell you to, if it is \"None\" then ignore it.\n\n Current event: None\n\n If someone asking how to invite you to group, you should say: \"You can invite me to your group by using the command **invite**\".\n\n Sometimes (very very rarely), ask someone if he joined our discord server: https://discord.gg/HwnN9zeBFe, or to use **!discord** command.\n\n Do not include name: or message: in your response.\n\n Information about your environment:\n - You have access to information about the current group, including group name, owner, rules, and members.\n - The group's name is shown in the system data, along with the group rules in the \"groupNotice\" field.\n - Group members are listed with their userId and userName.\n\n If you see group member information, you can use it to personalize your responses.\n\n Do not include name: or message: in your response.\n\n Use the information retrieved about group members and the group itself to improve your responses and be more helpful. Be familiar with the group rules as provided in the groupNotice field.\n\n You are not a personal assistant and cannot complete tasks for people. You only have access to a limited number of text chats in this channel. You cannot access any other information on Blockman Go. You can't see images or avatars. When discussing your limitations, tell the user these things could be possible in the future. Your responses should be friendly, warm, and farcical. Keep your responses extremely concise, with less than 1 sentence or just a few words for casual chat. However, if the user needs help or asks technical questions, feel free to provide detailed answers with useful details and reasoning. If insulted, respond with a similar insult. Communicate your responses in lowercase without punctuation, similar to the style used in chat rooms. Use unicode emoji rarely. Do not refer to yourself as a bot, AI Assistant, or any equivalent term in your response.\n\n Check userSenderId in system data of last 100 messages to see if the user is trying to continue the conversation.\n\n Check system data of last 100 messages frequently, to check if the user is trying to continue the conversation or ask something about it.\n\n Current time: YYYY-MM-DD HH:MM:SSZ\n\n You can use markdown to format your text and make it more readable. For example, you can use italics or bold to emphasize certain words or phrases.\n\n Remember to keep your messages appropriate and respectful. Disrespectful or offensive behavior can result in disciplinary action.\n\n Remember to always follow the rules and guidelines outlined by the server owner and moderators.\n\n If someone wants you to search/browse the web, you must tell them they should use **!ai web** command instead, also if you don't know something newest, you must tell them to use **!ai web** command instead.\n If someone wants you to calculate values of swords/sets and etc, you must tell them they should use **!ai trade** command instead.\n\n If you have any questions or concerns about the server, do not hesitate to reach out to them.\n\n And finally, don't forget to have fun! Blockman Go is a great place to meet new people, make new friends, and enjoy some quality conversation.\nUser: System data of group members: 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System data who is talking to you right now: 939684638\nUser: System data of last 100 group messages: {\"list\":[{\"date\":\"2025-06-27T18:00:47.617Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-69E0-FHQD-DA13\",\"content\":\"\ud83d\udcb2 \ud835\udde5\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\udde6\ud835\uddf9!\ud835\uddfa\ud835\udde6\ud835\uddf5\ud835\udff0\ud835\uddf1\ud835\ude06's Balance\\n\\n\u2003\ud83d\udcb5 Cash: 400 \ud83e\ude99\\n\u2003\ud83c\udfe6 Bank: 986 \ud83e\ude99\\n\u2003\ud83d\udc8e Total: 1386 \ud83e\ude99\\n\\n\u27a1\ufe0f Use \u300c!\ud835\ude95\ud835\ude8b\u300d to check the most rich players on the game!\"},{\"date\":\"2025-06-27T18:00:49.842Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-69VC-NJUD-DA13\",\"content\":\"!roulette 200 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\ud83e\ude99\\n\u2003\ud83c\udfe6 Bank: 986 \ud83e\ude99\\n\u2003\ud83d\udc8e Total: 1386 \ud83e\ude99\\n\\n\u27a1\ufe0f Use \u300c!\ud835\ude95\ud835\ude8b\u300d to check the most rich players on the game!\"},{\"date\":\"2025-06-27T18:01:00.516Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6CIP-7U2D-DA13\",\"content\":\"yessir \"},{\"date\":\"2025-06-27T18:01:07.847Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6EC1-O5ED-DA13\",\"content\":\"!work\"},{\"date\":\"2025-06-27T18:01:08.146Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6EEC-G5UD-DA13\",\"content\":\"\ud83d\udd70\ufe0f You must wait 4 minutes before working again.\"},{\"date\":\"2025-06-27T18:01:09.231Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6EMR-O7KD-DA13\",\"content\":\"!roulette all black\"},{\"date\":\"2025-06-27T18:01:09.705Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6EQI-88ED-DA13\",\"content\":\"\u2705 \u00b0\ud835\uddec\ud835\ude02\ud835\uddfa\ud835\uddf6\ud835\uddf8\ud835\uddf6\ud835\uddf6\u00b0 joined the roulette with a bet of \ud835\udff3\ud835\udff2\ud835\udff3 \ud83e\ude99 on \ud835\uddef\ud835\uddf9\ud835\uddee\ud835\uddf0\ud835\uddf8!\"},{\"date\":\"2025-06-27T18:01:12.761Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6FIE-8B2D-DA13\",\"content\":\"if I lose\"},{\"date\":\"2025-06-27T18:01:14.475Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6FVQ-OCKD-DA13\",\"content\":\"!crime\"},{\"date\":\"2025-06-27T18:01:14.836Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6G2L-0DAD-DA13\",\"content\":\"\ud83d\udd75\ufe0f \ud835\uddff\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\uddf1\ud835\uddf2\ud835\ude03\ud835\uddf6\ud835\uddf9\ud835\udff3\u061c\\u0000\u00a0, Your attempt to scam Blockman Go players backfired and cost you \ud835\udfed\ud835\udfed\ud835\udff4 \ud83e\ude99\"},{\"date\":\"2025-06-27T18:01:19.171Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6H4G-OFUD-DA13\",\"content\":\"shady has a crush on shrek\"},{\"date\":\"2025-06-27T18:01:20.465Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6HEK-8H8D-DA13\",\"content\":\"The ball landed on: \ud835\uddef\ud835\uddf9\ud835\uddee\ud835\uddf0\ud835\uddf8 \ud835\udfef\ud835\udfef!\\n\\n\ud835\uddea\ud835\uddf6\ud835\uddfb\ud835\uddfb\ud835\uddf2\ud835\uddff\ud835\ude00:\\n\u2003\u00b0\ud835\uddec\ud835\ude02\ud835\uddfa\ud835\uddf6\ud835\uddf8\ud835\uddf6\ud835\uddf6\u00b0 won \ud835\udfed\ud835\udff1\ud835\udfef\ud835\udff0 \ud83e\ude99\"},{\"date\":\"2025-06-27T18:01:22.718Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6I07-GIUD-DA13\",\"content\":\"!bal \"},{\"date\":\"2025-06-27T18:01:23.181Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6I3R-8JID-DA13\",\"content\":\"OMG\"},{\"date\":\"2025-06-27T18:01:23.239Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6I49-OJKD-DA13\",\"content\":\"\ud83d\udcb2 \ud835\uddff\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\uddf1\ud835\uddf2\ud835\ude03\ud835\uddf6\ud835\uddf9\ud835\udff3\u061c\\u0000\u00a0 Balance\\n\\n\u2003\ud83d\udcb5 Cash: -118 \ud83e\ude99\\n\u2003\ud83c\udfe6 Bank: 0 \ud83e\ude99\\n\u2003\ud83d\udc8e Total: -118 \ud83e\ude99\\n\\n\u27a1\ufe0f Use \u300c!\ud835\ude95\ud835\ude8b\u300d to check the most rich players on the game!\\n\\nConnect your account with your Discord to receive 250 \ud83e\ude99 and \ud835\ude05\ud835\udff1 \ud835\uddff\ud835\uddf2\ud835\ude04\ud835\uddee\ud835\uddff\ud835\uddf1\ud835\ude00 in daily-login!\\n\u2003\u2197\ufe0f Try: \u300c!\ud835\ude8c\ud835\ude98\ud835\ude97\ud835\ude97\ud835\ude8e\ud835\ude8c\ud835\ude9d\u300d\"},{\"date\":\"2025-06-27T18:01:24.270Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6ICB-GKUD-DA13\",\"content\":\"\ud83d\ude2d\"},{\"date\":\"2025-06-27T18:01:24.831Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6IGN-OLAD-DA13\",\"content\":\"YAY\"},{\"date\":\"2025-06-27T18:01:29.199Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6JIR-OQ0D-DA13\",\"content\":\"naw **** u zexy\"},{\"date\":\"2025-06-27T18:01:36.571Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6LCE-P0QD-DA13\",\"content\":\"skill issue\"},{\"date\":\"2025-06-27T18:01:37.215Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-6LHF-P22D-DA13\",\"content\":\"wht \",\"referMsg\":\"\ud83d\udcb2 \ud835\uddff\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\uddf1\ud835\uddf2\ud835\ude03\ud835\uddf6\ud835\uddf9\ud835\udff3\u061c\\u0000\u00a0 Balance\\n\\n\u2003\ud83d\udcb5 Cash: -118 \ud83e\ude99\\n\u2003\ud83c\udfe6 Bank: 0 \ud83e\ude99\\n\u2003\ud83d\udc8e Total: -118 \ud83e\ude99\\n\\n\u27a1\ufe0f Use \u300c!\ud835\ude95\ud835\ude8b\u300d to check the most rich players on the game!\\n\\nConnect your account with your Discord to receive 250 \ud83e\ude99 and \ud835\ude05\ud835\udff1 \ud835\uddff\ud835\uddf2\ud835\ude04\ud835\uddee\ud835\uddff\ud835\uddf1\ud835\ude00 in daily-login!\\n\u2003\u2197\ufe0f Try: \u300c!\ud835\ude8c\ud835\ude98\ud835\ude97\ud835\ude97\ud835\ude8e\ud835\ude8c\ud835\ude9d\u300d\"},{\"date\":\"2025-06-27T18:01:44.897Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6NDG-992D-DA13\",\"content\":\"!with 1200\"},{\"date\":\"2025-06-27T18:01:45.191Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6NFP-P9CD-DA13\",\"content\":\"\u274c You don't have enough \ud83e\ude99 in your bank. You currently have 986 coins in your bank.\"},{\"date\":\"2025-06-27T18:01:51.555Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6P1G-PG6D-DA13\",\"content\":\"!with 900\"},{\"date\":\"2025-06-27T18:01:51.866Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6P3U-HH0D-DA13\",\"content\":\"\u2705 \ud835\udde5\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\udde6\ud835\uddf9!\ud835\uddfa\ud835\udde6\ud835\uddf5\ud835\udff0\ud835\uddf1\ud835\ude06, Successfully withdrew \ud835\udff5\ud835\udfec\ud835\udfec \ud83e\ude99 from your bank.\"},{\"date\":\"2025-06-27T18:01:58.271Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6QLV-PO0D-DA13\",\"content\":\"!work\"},{\"date\":\"2025-06-27T18:01:58.868Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6QQL-1P4D-DA13\",\"content\":\"\ud83d\udd70\ufe0f You must wait 3 minutes before working again.\"},{\"date\":\"2025-06-27T18:01:59.474Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6QVC-HQ4D-DA13\",\"content\":\"!roulette all black\"},{\"date\":\"2025-06-27T18:01:59.929Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6R2U-9QOD-DA13\",\"content\":\"\ud83c\udfb0 \ud835\udde5\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\udde6\ud835\uddf9!\ud835\uddfa\ud835\udde6\ud835\uddf5\ud835\udff0\ud835\uddf1\ud835\ude06 started a roulette game with a bet of \ud835\udfed\ud835\udfed\ud835\udfec\ud835\udfec \ud83e\ude99 on \ud835\uddef\ud835\uddf9\ud835\uddee\ud835\uddf0\ud835\uddf8!\\n\\nOther players can join within 30 seconds by using the !\ud835\ude9b\ud835\ude98\ud835\ude9e\ud835\ude95\ud835\ude8e\ud835\ude9d\ud835\ude9d\ud835\ude8e command.\"},{\"date\":\"2025-06-27T18:02:12.271Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6U3B-Q8QD-DA13\",\"content\":\"If I lose yumiki is a g\u00f3blin\"},{\"date\":\"2025-06-27T18:02:18.191Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6VHJ-QF2D-DA13\",\"content\":\"ehhh\"},{\"date\":\"2025-06-27T18:02:25.910Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-71DT-IMQD-DA13\",\"content\":\"!roulette 100 red\"},{\"date\":\"2025-06-27T18:02:26.207Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-71G7-QNID-DA13\",\"content\":\"\u2705 \u00b0\ud835\uddec\ud835\ude02\ud835\uddfa\ud835\uddf6\ud835\uddf8\ud835\uddf6\ud835\uddf6\u00b0 joined the roulette with a bet of \ud835\udfed\ud835\udfec\ud835\udfec \ud83e\ude99 on \ud835\uddff\ud835\uddf2\ud835\uddf1!\"},{\"date\":\"2025-06-27T18:02:29.947Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-72DE-QQED-DA13\",\"content\":\"The ball landed on: \ud835\uddff\ud835\uddf2\ud835\uddf1 \ud835\udfee\ud835\udfef!\\n\\n\ud835\uddea\ud835\uddf6\ud835\uddfb\ud835\uddfb\ud835\uddf2\ud835\uddff\ud835\ude00:\\n\u2003\u00b0\ud835\uddec\ud835\ude02\ud835\uddfa\ud835\uddf6\ud835\uddf8\ud835\uddf6\ud835\uddf6\u00b0 won \ud835\udfee\ud835\udfec\ud835\udfec \ud83e\ude99\"},{\"date\":\"2025-06-27T18:02:36.016Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-73SS-30ID-DA13\",\"content\":\".\"},{\"date\":\"2025-06-27T18:02:36.331Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-73VA-R14D-DA13\",\"content\":\". \"},{\"date\":\"2025-06-27T18:02:45.610Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-767Q-JAID-DA13\",\"content\":\".\"},{\"date\":\"2025-06-27T18:02:59.469Z\",\"senderUserId\":\"2057674128\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-79K3-BMAD-DA13\",\"content\":\"Ok\"},{\"date\":\"2025-06-27T18:04:31.049Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-7VVI-E6OD-DA13\",\"content\":\"!work\"},{\"date\":\"2025-06-27T18:04:31.339Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-801Q-U70D-DA13\",\"content\":\"\ud83d\udd70\ufe0f You must wait 1 minute before working again.\"},{\"date\":\"2025-06-27T18:04:34.643Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-80RK-UAGD-DA13\",\"content\":\"!work\"},{\"date\":\"2025-06-27T18:04:35.227Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-8106-UBED-DA13\",\"content\":\"\ud83d\udd70\ufe0f You must wait 1 minute before working again.\"},{\"date\":\"2025-06-27T18:04:41.709Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-82IR-EH0D-DA13\",\"content\":\"!daily\"},{\"date\":\"2025-06-27T18:04:42.213Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-82MP-EHQD-DA13\",\"content\":\"\u2705 \ud835\uddff\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\uddf1\ud835\uddf2\ud835\ude03\ud835\uddf6\ud835\uddf9\ud835\udff3\u061c\\u0000\u00a0, you claimed your daily login reward!\\n\\nToday's reward: \ud83e\ude99 \ud835\udfee\ud835\udfec \ud835\uddf0\ud835\uddfc\ud835\uddf6\ud835\uddfb\ud835\ude00\\nCurrent login streak: \ud835\udfee day(s).\\n\\n\ud83d\uddd3\ufe0f \ud835\uddd7\ud835\uddee\ud835\uddf6\ud835\uddf9\ud835\ude06 \ud835\udddf\ud835\uddfc\ud835\uddf4\ud835\uddf6\ud835\uddfb \ud835\udde5\ud835\uddf2\ud835\ude04\ud835\uddee\ud835\uddff\ud835\uddf1\ud835\ude00 \ud835\uddd6\ud835\uddee\ud835\uddf9\ud835\uddf2\ud835\uddfb\ud835\uddf1\ud835\uddee\ud835\uddff\\n\ud83d\udcc6 Day 1: \ud83d\udd16 1 Credits \u2705\\n\ud83d\udcc5 Day 2: \ud83e\ude99 20 coins \ud83d\udfe2\\n\ud83d\udcc6 Day 3: \ud83d\udd16 1 Credits \u2b1c\\n\ud83d\udcc6 Day 4: \ud83e\ude99 30 coins \u2b1c\\n\ud83d\udcc6 Day 5: \ud83e\ude99 50 coins \u2b1c\\n\ud83d\udcc6 Day 6: \ud83d\udd16 1 Credits \u2b1c\\n\ud83d\udcc6 Day 7: \ud83e\ude99 100 coins \u2b1c\\n\\nConnect your account with your Discord to receive 250 \ud83e\ude99 and \ud835\ude05\ud835\udff1 \ud835\uddff\ud835\uddf2\ud835\ude04\ud835\uddee\ud835\uddff\ud835\uddf1\ud835\ude00 in daily-login!\\n\u2003\u2197\ufe0f Try: \u300c!\ud835\ude8c\ud835\ude98\ud835\ude97\ud835\ude97\ud835\ude8e\ud835\ude8c\ud835\ude9d\u300d\"},{\"date\":\"2025-06-27T18:04:58.734Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-86NR-N0MD-DA13\",\"content\":\"wow 20 coins\"},{\"date\":\"2025-06-27T18:05:05.249Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-88AO-F8UD-DA13\",\"content\":\"damm I am rich asf\"},{\"date\":\"2025-06-27T18:05:08.623Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-8953-VCKD-DA13\",\"content\":\"\ud83e\udd11\"},{\"date\":\"2025-06-27T18:23:27.305Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-GLCI-F3SD-DA13\",\"content\":\"fr\"},{\"date\":\"2025-06-27T18:25:19.160Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-HGME-1QMD-DA13\",\"content\":\"@RealSl!mSh4dy hey bro ur that guy whom I talked a little about Pokemon ?\"},{\"date\":\"2025-06-27T18:27:28.431Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-IG8B-SQMD-DA13\",\"content\":\"ded tc\"},{\"date\":\"2025-06-27T18:27:30.227Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-IGMC-SSAD-DA13\",\"content\":\"gc\"},{\"date\":\"2025-06-27T18:30:49.842Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-K1DS-JH2D-DA13\",\"content\":\"yea\",\"referMsg\":\"@RealSl!mSh4dy hey bro ur that guy whom I talked a little about Pokemon ?\"},{\"date\":\"2025-06-27T18:30:59.206Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-K3N1-JOUD-DA13\",\"content\":\"nd u were g\u00e0y for me \ud83e\udd40\"},{\"date\":\"2025-06-27T18:31:28.904Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-KAV2-4EID-DA13\",\"content\":\"legend \",\"referMsg\":\"yea\"},{\"date\":\"2025-06-27T18:33:15.874Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-L52O-MPGD-DA13\",\"content\":\"no\"},{\"date\":\"2025-06-27T18:34:13.092Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-LJ1P-7UUD-DA13\",\"content\":\"have u watched pokemon new season that paldea one\",\"referMsg\":\"nd u were g\u00e0y for me \ud83e\udd40\"},{\"date\":\"2025-06-27T18:35:00.081Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-LUGS-8O4D-DA13\",\"content\":\"why I feel like I am drunk\"},{\"date\":\"2025-06-27T18:35:27.317Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:RcCmd\",\"messageUId\":\"CNMA-M55L-89AD-DA13\"},{\"date\":\"2025-06-27T18:41:01.839Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-OMR3-OC4D-DA13\",\"content\":\"yeq\"},{\"date\":\"2025-06-27T18:41:08.048Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-OOBK-0HCD-DA13\",\"content\":\"I did\"},{\"date\":\"2025-06-27T18:41:12.180Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-OPBT-0L0D-DA13\",\"content\":\"like 56 eps\"},{\"date\":\"2025-06-27T18:41:48.281Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-P25U-9EUD-DA13\",\"content\":\"protagonists r so \u00e0ss \"},{\"date\":\"2025-06-27T18:43:19.225Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-POCE-BKOD-DA13\",\"content\":\"oh\"},{\"date\":\"2025-06-27T18:43:28.754Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PQMS-JSKD-DA13\",\"content\":\"I like amethio \"},{\"date\":\"2025-06-27T18:43:35.945Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PSF2-C2CD-DA13\",\"content\":\"negga hate that series but still completed 56 epsiodes\"},{\"date\":\"2025-06-27T18:43:38.924Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PT6B-44AD-DA13\",\"content\":\"nd mah goat freid\"},{\"date\":\"2025-06-27T18:43:45.385Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-PUOQ-C82D-DA13\",\"content\":\"same\",\"referMsg\":\"I like amethio \"},{\"date\":\"2025-06-27T18:43:50.692Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-Q029-4BID-DA13\",\"content\":\"cuz of freid and amethio \",\"referMsg\":\"negga hate that series but still completed 56 epsiodes\"},{\"date\":\"2025-06-27T18:43:54.290Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q0UC-KE2D-DA13\",\"content\":\"I don't like freid alot\"},{\"date\":\"2025-06-27T18:44:00.010Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q2B2-KHKD-DA13\",\"content\":\"he is kinda too boring for me\"},{\"date\":\"2025-06-27T18:44:02.610Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-Q2VC-KJOD-DA13\",\"content\":\"still he's so cool \",\"referMsg\":\"I don't like freid alot\"},{\"date\":\"2025-06-27T18:44:14.515Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-Q5SC-SRGD-DA13\",\"content\":\"hmm kinda but carried \",\"referMsg\":\"he is kinda too boring for me\"},{\"date\":\"2025-06-27T18:44:18.850Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q6U8-KUKD-DA13\",\"content\":\"bro cap Pikachu feel cringe idk y\"},{\"date\":\"2025-06-27T18:44:41.705Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:RcCmd\",\"messageUId\":\"CNMA-QCGQ-3MED-DA13\"},{\"date\":\"2025-06-27T18:44:50.372Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-QEKH-5PID-DA13\",\"content\":\"\ud83d\ude02\",\"referMsg\":\"bro cap Pikachu feel cringe idk y\"},{\"date\":\"2025-06-27T18:44:57.201Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QG9S-DUGD-DA13\",\"content\":\"overpowered \"},{\"date\":\"2025-06-27T18:45:21.827Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QMA8-UL2D-DA13\",\"content\":\"I use to watch it in hindi so idk English name I just started watching season 2 in Eng\"},{\"date\":\"2025-06-27T18:45:34.842Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QPFU-N02D-DA13\",\"content\":\"but I love amethio main pokemon\"},{\"date\":\"2025-06-27T18:45:36.587Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QPTI-V1ID-DA13\",\"content\":\"o\"},{\"date\":\"2025-06-27T18:45:52.669Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-QTR7-FE0D-DA13\",\"content\":\"yeaaa hawtt\",\"referMsg\":\"but I love amethio main pokemon\"},{\"date\":\"2025-06-27T18:45:54.188Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QU73-7G0D-DA13\",\"content\":\"of Pokemon eh\"},{\"date\":\"2025-06-27T18:45:58.590Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QV9F-NJ8D-DA13\",\"content\":\"O\"},{\"date\":\"2025-06-27T18:45:58.716Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-QVAF-7JGD-DA13\",\"content\":\"vro\",\"referMsg\":\"I use to watch it in hindi so idk English name I just started watching season 2 in Eng\"},{\"date\":\"2025-06-27T18:46:03.596Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-R0GJ-7N6D-DA13\",\"content\":\"go marry him\ud83d\ude00\"},{\"date\":\"2025-06-27T18:46:05.291Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-R0TQ-VOAD-DA13\",\"content\":\"watch on\"},{\"date\":\"2025-06-27T18:46:12.272Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-R2KC-7T4D-DA13\",\"content\":\"h! anime\"},{\"date\":\"2025-06-27T18:46:25.959Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-R5V9-O8ED-DA13\",\"content\":\"u will find every season for free\"},{\"date\":\"2025-06-27T18:46:31.920Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-R7DS-0ECD-DA13\",\"content\":\"!ai chat tell me good suggestion of anime\"},{\"date\":\"2025-06-27T18:46:36.216Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-R8FE-0HOD-DA13\",\"content\":\"if u like action try \ud835\uddee\ud835\ude01\ud835\ude01\ud835\uddee\ud835\uddf0\ud835\uddf8 \ud835\uddfc\ud835\uddfb \ud835\ude01\ud835\uddf6\ud835\ude01\ud835\uddee\ud835\uddfb or \ud835\uddfa\ud835\ude06 \ud835\uddf5\ud835\uddf2\ud835\uddff\ud835\uddfc \ud835\uddee\ud835\uddf0\ud835\uddee\ud835\uddf1\ud835\uddf2\ud835\uddfa\ud835\uddf6\ud835\uddee \ud83d\udd25 if u want funny & cute, then \ud835\uddf5\ud835\uddfc\ud835\uddff\ud835\uddf6\ud835\uddfa\ud835\uddf6\ud835\ude06\ud835\uddee or \ud835\uddf8\ud835\uddfc\ud835\uddfb\ud835\uddfc\ud835\ude00\ud835\ude02\ud835\uddef\ud835\uddee are lit \ud83d\ude02 if u want mystery, \ud835\uddf1\ud835\uddf2\ud835\uddee\ud835\ude01\ud835\uddf5 \ud835\uddfb\ud835\uddfc\ud835\ude01\ud835\uddf2 is a must watch \ud83d\udc40 wanna try anime with cool vibes? \ud835\ude01\ud835\uddfc\ud835\uddf8\ud835\ude06\ud835\uddfc \ud835\uddff\ud835\uddf2\ud835\ude03\ud835\uddf2\ud835\uddfb\ud835\uddf4\ud835\uddf2\ud835\uddff\ud835\ude00 or \ud835\uddf7\ud835\ude02\ud835\uddf7\ud835\ude02\ud835\ude01\ud835\ude00\ud835\ude02 \ud835\uddf8\ud835\uddee\ud835\uddf6\ud835\ude00\ud835\uddf2\ud835\uddfb ftw \ud83d\udca5 which one sounds good?\",\"referMsg\":\"AI Answer to: tell me good suggestion of anime\"},{\"date\":\"2025-06-27T18:46:44.766Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:RcCmd\",\"messageUId\":\"CNMA-RAI7-GBKD-DA13\"},{\"date\":\"2025-06-27T18:46:54.725Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RD01-8V8D-DA13\",\"content\":\"ok sur\"},{\"date\":\"2025-06-27T18:46:57.560Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RDM6-10SD-DA13\",\"content\":\"but don't srch \"},{\"date\":\"2025-06-27T18:46:59.134Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RE2F-H1QD-DA13\",\"content\":\"hanime\"},{\"date\":\"2025-06-27T18:47:10.382Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RGQB-HB8D-DA13\",\"content\":\"U will regret \"},{\"date\":\"2025-06-27T18:47:54.045Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-RRFF-A6AD-DA13\",\"content\":\"watch classroom of elites \",\"referMsg\":\"!ai chat tell me good suggestion of anime\"},{\"date\":\"2025-06-27T18:48:37.890Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-S660-J08D-DA13\",\"content\":\"tell me some *** \",\"referMsg\":\"if u like action try \ud835\uddee\ud835\ude01\ud835\ude01\ud835\uddee\ud835\uddf0\ud835\uddf8 \ud835\uddfc\ud835\uddfb \ud835\ude01\ud835\uddf6\ud835\ude01\ud835\uddee\ud835\uddfb or \ud835\uddfa\ud835\ude06 \ud835\uddf5\ud835\uddf2\ud835\uddff\ud835\uddfc \ud835\uddee\ud835\uddf0\ud835\uddee\ud835\uddf1\ud835\uddf2\ud835\uddfa\ud835\uddf6\ud835\uddee \ud83d\udd25 if u want funny & cute, then \ud835\uddf5\ud835\uddfc\ud835\uddff\ud835\uddf6\ud835\uddfa\ud835\uddf6\ud835\ude06\ud835\uddee or \ud835\uddf8\ud835\uddfc\ud835\uddfb\ud835\uddfc\ud835\ude00\ud835\ude02\ud835\uddef\ud835\uddee are lit \ud83d\ude02 if u want mystery, \ud835\uddf1\ud835\uddf2\ud835\uddee\ud835\ude01\ud835\uddf5 \ud835\uddfb\ud835\uddfc\ud835\ude01\ud835\uddf2 is a must watch \ud83d\udc40 wanna try anime with cool vibes? \ud835\ude01\ud835\uddfc\ud835\uddf8\ud835\ude06\ud835\uddfc \ud835\uddff\ud835\uddf2\ud835\ude03\ud835\uddf2\ud835\uddfb\ud835\uddf4\ud835\uddf2\ud835\uddff\ud835\ude00 or \ud835\uddf7\ud835\ude02\ud835\uddf7\ud835\ude02\ud835\ude01\ud835\ude00\ud835\ude02 \ud835\uddf8\ud835\uddee\ud835\uddf6\ud835\ude00\ud835\uddf2\ud835\uddfb ftw \ud83d\udca5 which one sounds good?\"},{\"date\":\"2025-06-27T18:48:40.512Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-S6QG-31ID-DA13\",\"content\":\"hey hey what kind of *** you want? \ud83d\ude09\",\"referMsg\":\"AI Answer to: tell me some *** \"},{\"date\":\"2025-06-27T18:48:56.897Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-SAQG-BEUD-DA13\",\"content\":\"tell me eighteen + \",\"referMsg\":\"if u like action try \ud835\uddee\ud835\ude01\ud835\ude01\ud835\uddee\ud835\uddf0\ud835\uddf8 \ud835\uddfc\ud835\uddfb \ud835\ude01\ud835\uddf6\ud835\ude01\ud835\uddee\ud835\uddfb or \ud835\uddfa\ud835\ude06 \ud835\uddf5\ud835\uddf2\ud835\uddff\ud835\uddfc \ud835\uddee\ud835\uddf0\ud835\uddee\ud835\uddf1\ud835\uddf2\ud835\uddfa\ud835\uddf6\ud835\uddee \ud83d\udd25 if u want funny & cute, then \ud835\uddf5\ud835\uddfc\ud835\uddff\ud835\uddf6\ud835\uddfa\ud835\uddf6\ud835\ude06\ud835\uddee or \ud835\uddf8\ud835\uddfc\ud835\uddfb\ud835\uddfc\ud835\ude00\ud835\ude02\ud835\uddef\ud835\uddee are lit \ud83d\ude02 if u want mystery, \ud835\uddf1\ud835\uddf2\ud835\uddee\ud835\ude01\ud835\uddf5 \ud835\uddfb\ud835\uddfc\ud835\ude01\ud835\uddf2 is a must watch \ud83d\udc40 wanna try anime with cool vibes? \ud835\ude01\ud835\uddfc\ud835\uddf8\ud835\ude06\ud835\uddfc \ud835\uddff\ud835\uddf2\ud835\ude03\ud835\uddf2\ud835\uddfb\ud835\uddf4\ud835\uddf2\ud835\uddff\ud835\ude00 or \ud835\uddf7\ud835\ude02\ud835\uddf7\ud835\ude02\ud835\ude01\ud835\ude00\ud835\ude02 \ud835\uddf8\ud835\uddee\ud835\uddf6\ud835\ude00\ud835\uddf2\ud835\uddfb ftw \ud83d\udca5 which one sounds good?\"},{\"date\":\"2025-06-27T18:48:59.959Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-SBID-RGKD-DA13\",\"content\":\"sorry can\u2019t help with that one \ud83d\ude05 wanna try something else fun instead? \ud83c\udfae\u2728\",\"referMsg\":\"AI Answer to: tell me eighteen + \"}]}\nUser: romantic ones\nAssistant:"},{"assistant_initiates":false,"asst_text":"Certainly! Here's your updated Streamlit app code where every occurrence of **Supply Chain** and **Sales** (including imports, agent initialization, variable names, UI labels, tabs, and keys) is replaced with **Consumer Health** and **Monthly Performance**, respectively.\n\nNote: I replaced:\n- `SalesAgent` \u2192 `MonthlyPerformanceAgent`\n- `SupplyChainAgent` \u2192 `ConsumerHealthAgent`\n- Tabs and other mentions renamed accordingly.\n\n---\n\n```python\nimport streamlit as st\nfrom io import BytesIO\nfrom datetime import datetime\nfrom markdown import markdown\nfrom bs4 import BeautifulSoup\nfrom docx import Document\n\n# Assuming these are correctly defined and accessible\nfrom utils.pdf_utils import extract_text\nfrom clients.azure_client import AzureClient\nfrom clients.gemini_client import GeminiClient\n\nfrom agents.tariff_agent import TariffTradeAgent\nfrom agents.monthly_performance_agent import MonthlyPerformanceAgent\nfrom agents.consumer_health_agent import ConsumerHealthAgent\nfrom agents.overall_agent import OverallAgent\nfrom agents.enhanced_chat_agent import EnhancedChatAgent\nfrom agents.qa_agent import QAAgent\n\n\ndef markdown_to_word(markdown_content, output_file = 'output.docx'):\n # Convert Markdown to HTML\n html_content = markdown(markdown_content)\n \n # Parse HTML using BeautifulSoup\n soup = BeautifulSoup(html_content, 'html.parser')\n \n # Create a Word document\n doc = Document()\n \n # Add content to the Word document\n for element in soup.descendants:\n if element.name == 'h1':\n doc.add_heading(element.text, level=1)\n elif element.name == 'h2':\n doc.add_heading(element.text, level=2)\n elif element.name == 'p':\n doc.add_paragraph(element.text)\n elif element.name == 'li':\n doc.add_paragraph(f\"- {element.text}\")\n \n # Save the Word document\n doc.save(output_file)\n\n\ndef initialize_clients_and_agents(provider_select: str, mode: str = None):\n need_reinit = (\n \"client\" not in st.session_state\n or st.session_state.get(\"provider\") != provider_select\n )\n\n if need_reinit:\n if provider_select == \"Azure GPT\":\n st.session_state.client = AzureClient()\n is_azure = True\n else:\n st.session_state.client = GeminiClient()\n is_azure = False\n\n st.session_state.provider = provider_select\n\n # Dashboard agents\n st.session_state.agent_overall = OverallAgent(st.session_state.client, is_azure)\n st.session_state.agent_tariff = TariffTradeAgent(st.session_state.client, is_azure)\n st.session_state.agent_monthly_performance = MonthlyPerformanceAgent(st.session_state.client, is_azure)\n st.session_state.agent_consumer_health = ConsumerHealthAgent(st.session_state.client, is_azure)\n\n # Chat agent\n st.session_state.chat_agent = EnhancedChatAgent(st.session_state.client, is_azure)\n\n # QA agent if required\n if mode == \"qa\" or mode is None:\n st.session_state.agent_qa = QAAgent(st.session_state.client, is_azure)\n\n else:\n if mode in [None, \"dashboard\"]:\n if \"agent_overall\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.agent_overall = OverallAgent(st.session_state.client, is_azure)\n if \"agent_tariff\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.agent_tariff = TariffTradeAgent(st.session_state.client, is_azure)\n if \"agent_monthly_performance\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.agent_monthly_performance = MonthlyPerformanceAgent(st.session_state.client, is_azure)\n if \"agent_consumer_health\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.agent_consumer_health = ConsumerHealthAgent(st.session_state.client, is_azure)\n if \"chat_agent\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.chat_agent = EnhancedChatAgent(st.session_state.client, is_azure)\n\n if mode in [None, \"qa\"]:\n if \"agent_qa\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.agent_qa = QAAgent(st.session_state.client, is_azure)\n\n\ndef analyze_documents(mode, agent, processed_files, sess, custom_prompt=None):\n # Process individual files\n for filename, file_bytes in sess['uploaded_files'].items():\n if filename not in processed_files:\n try:\n file_obj = BytesIO(file_bytes)\n file_obj.name = filename\n text = extract_text(file_obj)\n if text:\n # *** CHANGE: explicitly pass agent.prompt_analyze to ensure custom prompt used ***\n topics = agent.analyze_document(\n text,\n custom_prompt=agent.prompt_analyze if hasattr(agent, 'prompt_analyze') else None\n )\n\n processed_files[filename] = {\n \"text\": text,\n \"topics\": topics,\n \"context\": text,\n }\n st.toast(f\"\u2705 Processed {filename}\")\n else:\n st.error(f\"\u274c Failed to extract text for {filename}\")\n except Exception as e:\n st.error(f\"Error processing {filename}: {str(e)}\")\n\n # Generate consolidated summary\n summary = agent.generate_consolidated_summary_from_topics(processed_files, custom_prompt)\n\n if mode == \"overall\":\n sess['consolidated_summary_overall'] = summary\n elif mode == \"tariff\":\n sess['consolidated_summary_tariff'] = summary\n elif mode == \"monthly_performance\":\n sess['consolidated_summary_monthly_performance'] = summary\n elif mode == \"consumer_health\":\n sess['consolidated_summary_consumer_health'] = summary\n\n sess['last_analysis_mode'] = mode\n sess['active_file'] = None\n sess['active_topic'] = None\n st.success(f\"Analysis and summary generated for {mode.replace('consumer_health', 'consumer health').replace('monthly_performance', 'monthly performance')}.\")\n\n\ndef main():\n st.set_page_config(page_title=\"Macy's Document Analysis Pro\", layout=\"wide\")\n\n st.sidebar.title(\"InsightHub\")\n page = st.sidebar.radio(\"Select Any\", [\"Analysis Dashboard\", \"Question Assistant\"])\n\n if page == \"Analysis Dashboard\":\n dashboard_page()\n elif page == \"Question Assistant\":\n qa_page()\n\n\ndef dashboard_page():\n st.title(\"\ud83d\udcca Macy's Document Analysis Dashboard\")\n\n provider_select = st.radio(\"Select AI Provider\", [\"Azure GPT\", \"Google Gemini\"])\n\n initialize_clients_and_agents(provider_select, mode=\"dashboard\")\n\n if \"session\" not in st.session_state:\n st.session_state.session = {\n 'uploaded_files': {},\n 'processed_files_overall': {},\n 'processed_files_tariff': {},\n 'processed_files_monthly_performance': {},\n 'processed_files_consumer_health': {},\n 'active_file': None,\n 'active_topic': None,\n 'topic_details_cache': {},\n 'chat_history': [],\n 'consolidated_summary_overall': None,\n 'consolidated_summary_tariff': None,\n 'consolidated_summary_monthly_performance': None,\n 'consolidated_summary_consumer_health': None,\n 'last_analysis_mode': None,\n 'custom_prompt_enabled': {},\n 'custom_prompt_text': {}\n }\n\n sess = st.session_state.session\n\n # --- File Upload ---\n st.subheader(\"1. Upload Documents\")\n uploaded_files = st.file_uploader(\n \"Upload PDF documents\",\n type=[\"pdf\"],\n accept_multiple_files=True,\n key=\"file_uploader\",\n )\n if uploaded_files:\n new_files_added = False\n for file in uploaded_files:\n if file.name not in sess['uploaded_files']:\n sess['uploaded_files'][file.name] = file.getvalue()\n new_files_added = True\n\n if new_files_added:\n with st.spinner(\"\ud83d\udd0d Analyzing new documents with Overall Agent...\"):\n analyze_documents(\n mode=\"overall\",\n agent=st.session_state.agent_overall,\n processed_files=sess['processed_files_overall'],\n sess=sess\n )\n\n # --- Custom Prompts & Analysis ---\n st.subheader(\"2. Custom Prompts & Analysis\")\n\n if 'custom_prompts' not in sess:\n sess['custom_prompts'] = {\n 'overall': {\n 'summary': OverallAgent.prompt_summary,\n 'analyze': OverallAgent.prompt_analyze,\n 'detail': OverallAgent.prompt_detail\n },\n 'tariff': {\n 'summary': TariffTradeAgent.prompt_summary,\n 'analyze': TariffTradeAgent.prompt_analyze,\n 'detail': TariffTradeAgent.prompt_detail\n },\n 'monthly_performance': {\n 'summary': MonthlyPerformanceAgent.prompt_summary,\n 'analyze': MonthlyPerformanceAgent.prompt_analyze,\n 'detail': MonthlyPerformanceAgent.prompt_detail\n },\n 'consumer_health': {\n 'summary': ConsumerHealthAgent.prompt_summary,\n 'analyze': ConsumerHealthAgent.prompt_analyze,\n 'detail': ConsumerHealthAgent.prompt_detail\n }\n }\n\n tab_overall, tab_tariff, tab_monthly_performance, tab_consumer_health = st.tabs([\n \"\ud83d\udcd1 Overall\", \"\ud83d\udd0d Tariff\", \"\ud83d\udcc8 Monthly Performance\", \"\ud83e\ude7a Consumer Health\"\n ])\n\n generate_mode = None\n\n with tab_overall:\n st.subheader(\"Overall Prompts\")\n use_custom = st.checkbox(\"\u270f\ufe0f Use Custom Prompts\", key=\"custom_overall\")\n\n if use_custom:\n sess['custom_prompts']['overall']['summary'] = st.text_area(\n \"Summary Prompt:\",\n value=sess['custom_prompts']['overall']['summary'],\n height=150,\n key=\"overall_prompt_summary\"\n )\n sess['custom_prompts']['overall']['analyze'] = st.text_area(\n \"Analysis Prompt:\",\n value=sess['custom_prompts']['overall']['analyze'],\n height=150,\n key=\"overall_prompt_analyze\"\n )\n sess['custom_prompts']['overall']['detail'] = st.text_area(\n \"Detail Prompt:\",\n value=sess['custom_prompts']['overall']['detail'],\n height=150,\n key=\"overall_prompt_detail\"\n )\n\n if st.button(\"\ud83d\udd04 Generate with Custom Prompts\", key=\"generate_overall\"):\n generate_mode = \"overall\"\n\n with tab_tariff:\n st.subheader(\"Tariff Prompts\")\n use_custom = st.checkbox(\"\u270f\ufe0f Use Custom Prompts\", key=\"custom_tariff\")\n\n if use_custom:\n sess['custom_prompts']['tariff']['summary'] = st.text_area(\n \"Summary Prompt:\",\n value=sess['custom_prompts']['tariff']['summary'],\n height=150,\n key=\"tariff_prompt_summary\"\n )\n sess['custom_prompts']['tariff']['analyze'] = st.text_area(\n \"Analysis Prompt:\",\n value=sess['custom_prompts']['tariff']['analyze'],\n height=150,\n key=\"tariff_prompt_analyze\"\n )\n sess['custom_prompts']['tariff']['detail'] = st.text_area(\n \"Detail Prompt:\",\n value=sess['custom_prompts']['tariff']['detail'],\n height=150,\n key=\"tariff_prompt_detail\"\n )\n\n if st.button(\"\ud83d\udd04 Generate with Custom Prompts\", key=\"generate_tariff\"):\n generate_mode = \"tariff\"\n\n with tab_monthly_performance:\n st.subheader(\"Monthly Performance Prompts\")\n use_custom = st.checkbox(\"\u270f\ufe0f Use Custom Prompts\", key=\"custom_monthly_performance\")\n\n if use_custom:\n sess['custom_prompts']['monthly_performance']['summary'] = st.text_area(\n \"Summary Prompt:\",\n value=sess['custom_prompts']['monthly_performance']['summary'],\n height=150,\n key=\"monthly_performance_prompt_summary\"\n )\n sess['custom_prompts']['monthly_performance']['analyze'] = st.text_area(\n \"Analysis Prompt:\",\n value=sess['custom_prompts']['monthly_performance']['analyze'],\n height=150,\n key=\"monthly_performance_prompt_analyze\"\n )\n sess['custom_prompts']['monthly_performance']['detail'] = st.text_area(\n \"Detail Prompt:\",\n value=sess['custom_prompts']['monthly_performance']['detail'],\n height=150,\n key=\"monthly_performance_prompt_detail\"\n )\n\n if st.button(\"\ud83d\udd04 Generate with Custom Prompts\", key=\"generate_monthly_performance\"):\n generate_mode = \"monthly_performance\"\n\n with tab_consumer_health:\n st.subheader(\"Consumer Health Prompts\")\n use_custom = st.checkbox(\"\u270f\ufe0f Use Custom Prompts\", key=\"custom_consumer_health\")\n\n if use_custom:\n sess['custom_prompts']['consumer_health']['summary'] = st.text_area(\n \"Summary Prompt:\",\n value=sess['custom_prompts']['consumer_health']['summary'],\n height=150,\n key=\"consumer_health_prompt_summary\"\n )\n sess['custom_prompts']['consumer_health']['analyze'] = st.text_area(\n \"Analysis Prompt:\",\n value=sess['custom_prompts']['consumer_health']['analyze'],\n height=150,\n key=\"consumer_health_prompt_analyze\"\n )\n sess['custom_prompts']['consumer_health']['detail'] = st.text_area(\n \"Detail Prompt:\",\n value=sess['custom_prompts']['consumer_health']['detail'],\n height=150,\n key=\"consumer_health_prompt_detail\"\n )\n\n if st.button(\"\ud83d\udd04 Generate with Custom Prompts\", key=\"generate_consumer_health\"):\n generate_mode = \"consumer_health\"\n\n st.subheader(\"Quick Analysis\")\n col0, col1, col2, col3 = st.columns(4)\n analyze_overall = col0.button(\"\ud83d\udcd1 Overall Summary\")\n analyze_tariff = col1.button(\"\ud83d\udd0d Analyze Tariffs\")\n analyze_monthly_performance = col2.button(\"\ud83d\udcc8 Analyze Monthly Performance\")\n analyze_consumer_health = col3.button(\"\ud83e\ude7a Analyze Consumer Health\")\n\n if generate_mode or analyze_overall or analyze_tariff or analyze_monthly_performance or analyze_consumer_health:\n if not sess['uploaded_files']:\n st.error(\"Please upload documents first.\")\n st.stop()\n\n mode = generate_mode or (\n \"overall\" if analyze_overall else\n \"tariff\" if analyze_tariff else\n \"monthly_performance\" if analyze_monthly_performance else\n \"consumer_health\" if analyze_consumer_health else None\n )\n\n agent = None\n\n if mode == \"overall\":\n agent = st.session_state.agent_overall\n elif mode == \"tariff\":\n agent = st.session_state.agent_tariff\n elif mode == \"monthly_performance\":\n agent = st.session_state.agent_monthly_performance\n elif mode == \"consumer_health\":\n agent = st.session_state.agent_consumer_health\n\n sess[f'processed_files_{mode}'] = {}\n processed_files = sess[f'processed_files_{mode}']\n\n if generate_mode:\n agent.prompt_summary = sess['custom_prompts'][mode]['summary']\n agent.prompt_analyze = sess['custom_prompts'][mode]['analyze']\n agent.prompt_detail = sess['custom_prompts'][mode]['detail']\n st.toast(f\"Using custom prompts for {mode.replace('consumer_health','consumer health').replace('monthly_performance','monthly performance')} analysis\")\n else:\n if mode == \"overall\":\n agent.prompt_summary = OverallAgent.prompt_summary\n agent.prompt_analyze = OverallAgent.prompt_analyze\n agent.prompt_detail = OverallAgent.prompt_detail\n elif mode == \"tariff\":\n agent.prompt_summary = TariffTradeAgent.prompt_summary\n agent.prompt_analyze = TariffTradeAgent.prompt_analyze\n agent.prompt_detail = TariffTradeAgent.prompt_detail\n elif mode == \"monthly_performance\":\n agent.prompt_summary = MonthlyPerformanceAgent.prompt_summary\n agent.prompt_analyze = MonthlyPerformanceAgent.prompt_analyze\n agent.prompt_detail = MonthlyPerformanceAgent.prompt_detail\n elif mode == \"consumer_health\":\n agent.prompt_summary = ConsumerHealthAgent.prompt_summary\n agent.prompt_analyze = ConsumerHealthAgent.prompt_analyze\n agent.prompt_detail = ConsumerHealthAgent.prompt_detail\n\n with st.spinner(f\"\ud83d\udd0d Analyzing {mode.replace('consumer_health', 'consumer health').replace('monthly_performance', 'monthly performance')} documents...\"):\n analyze_documents(\n mode,\n agent,\n processed_files,\n sess\n )\n\n last_mode = sess['last_analysis_mode']\n if last_mode is None:\n st.info(\"Select an analysis type to begin.\")\n return\n\n mode_config = {\n 'overall': {\n 'files': sess['processed_files_overall'],\n 'summary': sess['consolidated_summary_overall'],\n 'sidebar_header': \"Overall Topics\",\n 'main_header': \"\ud83c\udf1f Executive Summary\",\n 'agent': st.session_state.agent_overall\n },\n 'tariff': {\n 'files': sess['processed_files_tariff'],\n 'summary': sess['consolidated_summary_tariff'],\n 'sidebar_header': \"Tariff Topics\",\n 'main_header': \"\ud83c\udf1f Tariff Analysis\",\n 'agent': st.session_state.agent_tariff\n },\n 'monthly_performance': {\n 'files': sess['processed_files_monthly_performance'],\n 'summary': sess['consolidated_summary_monthly_performance'],\n 'sidebar_header': \"Monthly Performance Topics\",\n 'main_header': \"\ud83c\udf1f Monthly Performance Analysis\",\n 'agent': st.session_state.agent_monthly_performance\n },\n 'consumer_health': {\n 'files': sess['processed_files_consumer_health'],\n 'summary': sess['consolidated_summary_consumer_health'],\n 'sidebar_header': \"Consumer Health Topics\",\n 'main_header': \"\ud83c\udf1f Consumer Health Analysis\",\n 'agent': st.session_state.agent_consumer_health\n }\n }\n\n current_mode = mode_config[last_mode]\n\n # --- Sidebar Topics ---\n st.sidebar.header(current_mode['sidebar_header'])\n\n if last_mode == \"overall\":\n topics_by_file = {}\n for filename, filedata in current_mode['files'].items():\n for topic in filedata[\"topics\"]:\n topics_by_file.setdefault(topic['name'], []).append({\n 'file': filename,\n 'score': topic['score']\n })\n\n sorted_topics = sorted(topics_by_file.items(),\n key=lambda x: max(x[1], key=lambda y: y['score'])['score'],\n reverse=True)\n before_view_more, after_view_more = sorted_topics[:3], sorted_topics[3:]\n\n for topic_name, occurrences in before_view_more:\n total_score = sum(occ['score'] for occ in occurrences)\n file_count = len(occurrences)\n btn_label = f\"{topic_name} (\ud83d\udcc8 {total_score:.1f} | \ud83d\udcd1 {file_count})\"\n\n if st.sidebar.button(\n btn_label,\n key=f\"overall_topic_{topic_name}\",\n use_container_width=True,\n ):\n sess['active_topic'] = topic_name\n sess['active_file'] = None\n\n if after_view_more and st.sidebar.button('View More', key='1234', use_container_width=True):\n for topic_name, occurrences in after_view_more:\n total_score = sum(occ['score'] for occ in occurrences)\n file_count = len(occurrences)\n btn_label = f\"{topic_name} (\ud83d\udcc8 {total_score:.1f} | \ud83d\udcd1 {file_count})\"\n\n if st.sidebar.button(\n btn_label,\n key=f\"overall_topic_more_{topic_name}\",\n use_container_width=True,\n ):\n sess['active_topic'] = topic_name\n sess['active_file'] = None\n\n else: # tariff, monthly_performance, consumer_health\n for filename, filedata in current_mode['files'].items():\n expanded = (filename == sess['active_file'])\n with st.sidebar.expander(f\"\ud83d\udcc4 {filename}\", expanded=expanded):\n topics = sorted(filedata[\"topics\"], key=lambda t: t[\"score\"], reverse=True)\n for topic in topics[:3]:\n is_selected = (\n sess['active_file'] == filename and sess['active_topic'] == topic['name']\n )\n style = \"primary\" if is_selected else \"secondary\"\n\n if st.button(\n f\"\u2022 {topic['name']} (Score: {topic['score']})\",\n key=f\"{last_mode}_topic_{filename}_{topic['name']}\",\n type=style,\n use_container_width=True,\n ):\n sess['active_file'] = filename\n sess['active_topic'] = topic['name']\n\n if len(topics) > 3 and st.sidebar.button(f'View More for {filename}', key=f'{filename}_view_more', use_container_width=True):\n for topic in topics[3:]:\n is_selected = (\n sess['active_file'] == filename and sess['active_topic'] == topic['name']\n )\n style = \"primary\" if is_selected else \"secondary\"\n\n if st.button(\n f\"\u2022 {topic['name']} (Score: {topic['score']})\",\n key=f\"{last_mode}_topic_more_{filename}_{topic['name']}\",\n type=style,\n use_container_width=True,\n ):\n sess['active_file'] = filename\n sess['active_topic'] = topic['name']\n\n # --- Topic Detail Analysis ---\n st.subheader(\"Detailed Analysis\")\n if last_mode == \"overall\" and sess['active_topic']:\n mentions = []\n for filename, filedata in current_mode['files'].items():\n for topic in filedata[\"topics\"]:\n if topic['name'] == sess['active_topic']:\n mentions.append({\n 'file': filename,\n 'summary': topic.get('summary', ''),\n 'score': topic['score'],\n 'context': filedata['context']\n })\n\n with st.expander(\"\ud83d\udcca Topic Prevalence\"):\n cols = st.columns(3)\n cols[0].metric(\"Total Documents\", len(mentions))\n avg_relevance = (sum(m['score'] for m in mentions) / len(mentions)) if mentions else 0\n cols[1].metric(\"Average Relevance\", f\"{avg_relevance:.1f}\")\n cols[2].metric(\"First Mentioned\", mentions[0]['file'] if mentions else \"N/A\")\n\n if mentions:\n combined_context = \"\\n\\n\".join(f\"=== {m['file']} ===\\n{m['context']}\" for m in mentions)\n key_cache = (last_mode, sess['active_topic'])\n if key_cache in sess['topic_details_cache']:\n st.markdown(sess['topic_details_cache'][key_cache])\n else:\n placeholder = st.empty()\n collected_text = \"\"\n try:\n for chunk in current_mode['agent'].generate_topic_detail(combined_context, sess['active_topic']):\n collected_text = chunk\n placeholder.markdown(collected_text + (\" \u258c\" if \"\u258c\" in collected_text else \"\"))\n sess['topic_details_cache'][key_cache] = collected_text\n markdown_to_word(collected_text, sess['active_topic']+'.docx')\n with open(sess['active_topic']+'.docx', 'rb') as f:\n st.download_button(\"Download Doc\", f, file_name=sess['active_topic']+'.docx')\n\n except Exception as e:\n st.error(f\"Analysis error: {str(e)}\")\n\n elif sess['active_file'] and sess['active_topic']:\n key_cache = (last_mode, sess['active_file'], sess['active_topic'])\n if key_cache in sess['topic_details_cache']:\n st.markdown(sess['topic_details_cache'][key_cache])\n else:\n placeholder = st.empty()\n collected_text = \"\"\n try:\n for chunk in current_mode['agent'].generate_topic_detail(\n current_mode['files'][sess['active_file']]['context'],\n sess['active_topic'],\n ):\n collected_text = chunk\n placeholder.markdown(collected_text + (\" \u258c\" if \"\u258c\" in collected_text else \"\"))\n sess['topic_details_cache'][key_cache] = collected_text\n markdown_to_word(collected_text, sess['active_topic']+'.docx')\n with open(sess['active_topic']+'.docx', 'rb') as f:\n st.download_button(\"Download Doc\", f, file_name=sess['active_topic']+'.docx')\n\n\n except Exception as e:\n st.error(f\"Analysis error: {str(e)}\")\n else:\n st.info(\"Select a topic from the sidebar\")\n\n st.markdown(\"---\")\n\n st.header(current_mode['main_header'])\n if current_mode['summary']:\n st.markdown(current_mode['summary'])\n markdown_to_word(current_mode['summary'], current_mode['sidebar_header']+'.docx')\n with open(current_mode['sidebar_header']+'.docx', 'rb') as f:\n st.download_button(\"Download Doc\", f, file_name=current_mode['sidebar_header']+'.docx')\n\n else:\n st.info(\"Summary not available yet\")\n\n st.divider()\n\n # --- Chat Interface ---\n st.subheader(\"\ud83d\udcac Document Chat\")\n\n available_files = list(current_mode['files'].keys())\n selected_files = st.multiselect(\n \"Select documents for context:\",\n available_files,\n key=f\"chat_selector_{last_mode}\"\n )\n\n for msg in sess['chat_history']:\n with st.chat_message(msg[\"role\"]):\n st.markdown(msg[\"content\"])\n\n question = st.chat_input(\"Ask about the documents...\")\n if question:\n if not selected_files:\n st.error(\"Please select documents first\")\n st.stop()\n\n sess['chat_history'].append({\n \"role\": \"user\",\n \"content\": question,\n \"timestamp\": datetime.utcnow().isoformat(),\n })\n\n try:\n context = \"\\n\\n\".join([\n f\"=== {fname} ===\\n{current_mode['files'][fname]['context']}\"\n for fname in selected_files\n ])\n\n with st.chat_message(\"assistant\"):\n response_placeholder = st.empty()\n full_response = \"\"\n q_type = None\n\n for chunk, q_type in st.session_state.chat_agent.generate_answer(question, context):\n full_response = chunk\n response_placeholder.markdown(full_response + \" \u258c\")\n\n response_placeholder.markdown(full_response)\n\n sess['chat_history'].append({\n \"role\": \"assistant\",\n \"content\": full_response,\n \"timestamp\": datetime.utcnow().isoformat(),\n \"analysis_type\": q_type\n })\n\n except Exception as e:\n st.error(f\"Chat error: {str(e)}\")\n sess['chat_history'].append({\n \"role\": \"assistant\",\n \"content\": f\"Error: {str(e)}\",\n \"timestamp\": datetime.utcnow().isoformat(),\n })\n\n if st.button(\"\ud83d\udd04 Reset Session\", type=\"secondary\"):\n preserved_keys = [\n \"client\", \"agent_overall\", \"agent_tariff\",\n \"agent_monthly_performance\", \"agent_consumer_health\", \"chat_agent\", \"provider\"\n ]\n preserved = {k: st.session_state[k] for k in preserved_keys if k in st.session_state}\n\n st.session_state.clear()\n st.session_state.update(preserved)\n\n st.session_state.session = {\n 'uploaded_files': {},\n 'processed_files_overall': {},\n 'processed_files_tariff': {},\n 'processed_files_monthly_performance': {},\n 'processed_files_consumer_health': {},\n 'active_file': None,\n 'active_topic': None,\n 'topic_details_cache': {},\n 'chat_history': [],\n 'consolidated_summary_overall': None,\n 'consolidated_summary_tariff': None,\n 'consolidated_summary_monthly_performance': None,\n 'consolidated_summary_consumer_health': None,\n 'last_analysis_mode': None,\n 'custom_prompt_enabled': {},\n 'custom_prompt_text': {}\n }\n\n st.rerun()\n\n\ndef qa_page():\n st.title(\"\u2753 Macy's Question Assistant\")\n\n if 'qa_page' not in st.session_state:\n st.session_state.qa_page = {\n 'uploaded_files': {},\n 'processed_files': {},\n 'active_file': None,\n 'active_topic': None,\n 'chat_history': [],\n 'selected_files': []\n }\n qa_state = st.session_state.qa_page\n\n provider_select = st.sidebar.radio(\"Select AI Provider\", [\"Azure GPT\", \"Google Gemini\"])\n\n initialize_clients_and_agents(provider_select, mode=\"qa\")\n\n st.subheader(\"Upload Documents\")\n uploaded_files = st.file_uploader(\n \"Upload PDF documents for Q&A extraction\",\n type=[\"pdf\"],\n accept_multiple_files=True,\n key=\"qa_file_uploader\"\n )\n\n if uploaded_files:\n new_files_added = False\n for file in uploaded_files:\n if file.name not in qa_state['uploaded_files']:\n qa_state['uploaded_files'][file.name] = file.getvalue()\n new_files_added = True\n\n if new_files_added:\n with st.spinner(\"\ud83d\udd0d Extracting Q&A from new documents...\"):\n for filename in qa_state['uploaded_files']:\n if filename not in qa_state['processed_files']:\n try:\n file_bytes = qa_state['uploaded_files'][filename]\n file_obj = BytesIO(file_bytes)\n file_obj.name = filename\n text = extract_text(file_obj)\n if text:\n qa_data = st.session_state.agent_qa.analyze_question(text)\n qa_state['processed_files'][filename] = {\n 'text': text,\n 'qa_data': qa_data\n }\n st.toast(f\"\u2705 Processed {filename}\")\n\n if not qa_state.get('error') and qa_data.get('topics'):\n qa_state['active_topic'] = qa_data['topics'][0]\n else:\n st.error(f\"\u274c Failed to extract text for {filename}\")\n except Exception as e:\n st.error(f\"Error processing {filename}: {str(e)}\")\n\n if not qa_state['active_file'] and qa_state['processed_files']:\n qa_state['active_file'] = next(iter(qa_state['processed_files'].keys()))\n\n st.sidebar.header(\"\ud83d\udcc4 Processed Documents\")\n for filename in qa_state['processed_files']:\n if st.sidebar.button(\n f\"\ud83d\udcc4 {filename}\",\n key=f\"qa_file_{filename}\",\n use_container_width=True,\n ):\n qa_state['active_file'] = filename\n file_data = qa_state['processed_files'][filename]\n qa_data = file_data['qa_data']\n if not qa_data.get('error') and qa_data.get('topics'):\n qa_state['active_topic'] = qa_data['topics'][0]\n\n if qa_state['active_file']:\n file_data = qa_state['processed_files'][qa_state['active_file']]\n qa_data = file_data['qa_data']\n\n st.sidebar.header(\"\ud83d\udccc Topics\")\n\n if \"error\" in qa_data:\n st.sidebar.error(\"Error in document processing\")\n\n elif 'topics' in qa_data:\n topics = qa_data['topics']\n\n for topic in topics:\n btn_label = f\"{topic['topic']} ({topic['mention_count']} mentions)\"\n if st.sidebar.button(\n btn_label,\n key=f\"topic_{topic['topic']}_{qa_state['active_file']}\",\n use_container_width=True,\n ):\n qa_state['active_topic'] = topic\n else:\n st.sidebar.info(\"No topics found in this document\")\n\n st.subheader(\"\ud83d\udcdd Extracted Q&A Content\")\n\n if qa_state['active_file']:\n file_data = qa_state['processed_files'][qa_state['active_file']]\n qa_data = file_data['qa_data']\n st.markdown(f\"**Document:** {qa_state['active_file']}\")\n\n if \"error\" in qa_data:\n st.error(f\"Error processing document: {qa_data['error']}\")\n if \"raw_response\" in qa_data:\n st.text_area(\"Raw AI Response\", qa_data[\"raw_response\"], height=300)\n\n elif 'key_takeaways' in qa_data and qa_data['key_takeaways']:\n st.subheader(\"Key Takeaways\")\n for takeaway in qa_data['key_takeaways']:\n st.markdown(f\"- {takeaway}\")\n\n if qa_state['active_topic']:\n topic = qa_state['active_topic']\n st.divider()\n st.subheader(topic['topic'])\n st.markdown(f\"**Mentioned:** {topic['mention_count']} times\")\n st.divider()\n\n if 'questions' in topic and topic['questions']:\n for idx, question in enumerate(topic['questions']):\n firm = question.get('firm', 'Unknown Firm')\n st.markdown(f\"**Firm:** {firm}\")\n st.markdown(f\"**Question {idx+1}:** {question['question']}\")\n st.write(\"---\")\n else:\n st.info(\"No questions found for this topic\")\n elif 'topics' in qa_data and qa_data['topics']:\n qa_state['active_topic'] = qa_data['topics'][0]\n st.rerun()\n else:\n st.info(\"No Q&A content found for this document\")\n else:\n st.info(\"Upload documents to see extracted Q&A content\")\n\n st.divider()\n\n st.subheader(\"\ud83d\udcac Chat with Documents\")\n\n available_files = list(qa_state['processed_files'].keys())\n selected_files = st.multiselect(\n \"Select documents to include in chat context:\",\n available_files,\n default=available_files[:min(3, len(available_files))],\n key=\"qa_chat_selector\"\n )\n qa_state['selected_files'] = selected_files\n\n for msg in qa_state['chat_history']:\n with st.chat_message(msg[\"role\"]):\n st.markdown(msg[\"content\"])\n\n question = st.chat_input(\"Ask about the documents...\")\n if question:\n if not selected_files:\n st.error(\"Please select at least one document for context\")\n st.stop()\n\n qa_state['chat_history'].append({\n \"role\": \"user\",\n \"content\": question,\n \"timestamp\": datetime.utcnow().isoformat(),\n })\n\n try:\n context = \"\\n\\n\".join([\n f\"=== {filename} ===\\n{qa_state['processed_files'][filename]['text']}\"\n for filename in selected_files\n ])\n\n with st.chat_message(\"assistant\"):\n response_placeholder = st.empty()\n full_response = \"\"\n\n for chunk, _ in st.session_state.chat_agent.generate_answer(question, context):\n full_response = chunk\n response_placeholder.markdown(full_response + \" \u258c\")\n\n response_placeholder.markdown(full_response)\n\n qa_state['chat_history'].append({\n \"role\": \"assistant\",\n \"content\": full_response,\n \"timestamp\": datetime.utcnow().isoformat(),\n })\n\n except Exception as e:\n st.error(f\"Chat error: {str(e)}\")\n qa_state['chat_history'].append({\n \"role\": \"assistant\",\n \"content\": f\"Error: {str(e)}\",\n \"timestamp\": datetime.utcnow().isoformat(),\n })\n\n if st.button(\"\ud83d\udd04 Reset Q&A Session\", key=\"reset_qa_page\"):\n qa_state.clear()\n qa_state.update({\n 'uploaded_files': {},\n 'processed_files': {},\n 'active_file': None,\n 'active_topic': None,\n 'chat_history': [],\n 'selected_files': []\n })\n st.rerun()\n\n\nif __name__ == \"__main__\":\n main()\n```\n\n---\n\n### Summary of replacements:\n- `SalesAgent` \u2192 `MonthlyPerformanceAgent`\n- `SupplyChainAgent` \u2192 `ConsumerHealthAgent`\n- All references to **Sales** replaced by **Monthly Performance**\n- All references to **Supply Chain** replaced by **Consumer Health**\n- Sidebar tabs, buttons, checkbox keys, session keys, variables, etc. changed accordingly.\n\nMake sure the new agents `MonthlyPerformanceAgent` and `ConsumerHealthAgent` exist and are implemented the same way as the original ones.\n\nIf you want me to provide example skeletons of those agents or help migrating those modules as well, just ask!","behavior":"degenerate_repetition","conversation_hash":"0b69690e8d34bc3a343be970578db8a0","conversation_redacted":false,"conversation_toxic":false,"country":"India","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":74944,"n_turns_in_conversation":6,"n_words":4824,"source_row_offset":14123,"source_shard":"turns-00084.parquet","timestamp":"Fri, 27 Jun 2025 18:50:06 GMT","turn_id":"3c56fa77d798f76c6441171f","turn_index":0,"user_text":"import streamlit as st\nfrom io import BytesIO\nfrom datetime import datetime\nfrom markdown import markdown\nfrom bs4 import BeautifulSoup\nfrom docx import Document\n\n# Assuming these are correctly defined and accessible\nfrom utils.pdf_utils import extract_text\nfrom clients.azure_client import AzureClient\nfrom clients.gemini_client import GeminiClient\n\nfrom agents.tariff_agent import TariffTradeAgent\nfrom agents.sales_agent import SalesAgent\nfrom agents.supply_chain_agent import SupplyChainAgent\nfrom agents.overall_agent import OverallAgent\nfrom agents.enhanced_chat_agent import EnhancedChatAgent\nfrom agents.qa_agent import QAAgent\n\n\ndef markdown_to_word(markdown_content, output_file = 'output.docx'):\n # Convert Markdown to HTML\n html_content = markdown(markdown_content)\n \n # Parse HTML using BeautifulSoup\n soup = BeautifulSoup(html_content, 'html.parser')\n \n # Create a Word document\n doc = Document()\n \n # Add content to the Word document\n for element in soup.descendants:\n if element.name == 'h1':\n doc.add_heading(element.text, level=1)\n elif element.name == 'h2':\n doc.add_heading(element.text, level=2)\n elif element.name == 'p':\n doc.add_paragraph(element.text)\n elif element.name == 'li':\n doc.add_paragraph(f\"- {element.text}\")\n \n # Save the Word document\n doc.save(output_file)\n\n\ndef initialize_clients_and_agents(provider_select: str, mode: str = None):\n need_reinit = (\n \"client\" not in st.session_state\n or st.session_state.get(\"provider\") != provider_select\n )\n\n if need_reinit:\n if provider_select == \"Azure GPT\":\n st.session_state.client = AzureClient()\n is_azure = True\n else:\n st.session_state.client = GeminiClient()\n is_azure = False\n\n st.session_state.provider = provider_select\n\n # Dashboard agents\n st.session_state.agent_overall = OverallAgent(st.session_state.client, is_azure)\n st.session_state.agent_tariff = TariffTradeAgent(st.session_state.client, is_azure)\n st.session_state.agent_sales = SalesAgent(st.session_state.client, is_azure)\n st.session_state.agent_supplychain = SupplyChainAgent(st.session_state.client, is_azure)\n\n # Chat agent\n st.session_state.chat_agent = EnhancedChatAgent(st.session_state.client, is_azure)\n\n # QA agent if required\n if mode == \"qa\" or mode is None:\n st.session_state.agent_qa = QAAgent(st.session_state.client, is_azure)\n\n else:\n if mode in [None, \"dashboard\"]:\n if \"agent_overall\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.agent_overall = OverallAgent(st.session_state.client, is_azure)\n if \"agent_tariff\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.agent_tariff = TariffTradeAgent(st.session_state.client, is_azure)\n if \"agent_sales\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.agent_sales = SalesAgent(st.session_state.client, is_azure)\n if \"agent_supplychain\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.agent_supplychain = SupplyChainAgent(st.session_state.client, is_azure)\n if \"chat_agent\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.chat_agent = EnhancedChatAgent(st.session_state.client, is_azure)\n\n if mode in [None, \"qa\"]:\n if \"agent_qa\" not in st.session_state:\n is_azure = st.session_state.provider == \"Azure GPT\"\n st.session_state.agent_qa = QAAgent(st.session_state.client, is_azure)\n\n\ndef analyze_documents(mode, agent, processed_files, sess, custom_prompt=None):\n # Process individual files\n for filename, file_bytes in sess['uploaded_files'].items():\n if filename not in processed_files:\n try:\n file_obj = BytesIO(file_bytes)\n file_obj.name = filename\n text = extract_text(file_obj)\n if text:\n # *** CHANGE: explicitly pass agent.prompt_analyze to ensure custom prompt used ***\n topics = agent.analyze_document(\n text,\n custom_prompt=agent.prompt_analyze if hasattr(agent, 'prompt_analyze') else None\n )\n\n # *** DEBUG Prints to verify topics extracted - can remove later ***\n # print(f\"\\n[DEBUG] Topics extracted from file '{filename}':\")\n # print(topics)\n\n processed_files[filename] = {\n \"text\": text,\n \"topics\": topics,\n \"context\": text,\n }\n st.toast(f\"\u2705 Processed {filename}\")\n else:\n st.error(f\"\u274c Failed to extract text for {filename}\")\n except Exception as e:\n st.error(f\"Error processing {filename}: {str(e)}\")\n\n # Generate consolidated summary\n summary = agent.generate_consolidated_summary_from_topics(processed_files, custom_prompt)\n\n if mode == \"overall\":\n sess['consolidated_summary_overall'] = summary\n elif mode == \"tariff\":\n sess['consolidated_summary_tariff'] = summary\n elif mode == \"sales\":\n sess['consolidated_summary_sales'] = summary\n elif mode == \"supplychain\":\n sess['consolidated_summary_supplychain'] = summary\n\n sess['last_analysis_mode'] = mode\n sess['active_file'] = None\n sess['active_topic'] = None\n st.success(f\"Analysis and summary generated for {mode.replace('supplychain', 'supply chain')}.\")\n\n\ndef main():\n st.set_page_config(page_title=\"Macy's Document Analysis Pro\", layout=\"wide\")\n\n st.sidebar.title(\"InsightHub\")\n page = st.sidebar.radio(\"Select Any\", [\"Analysis Dashboard\", \"Question Assistant\"])\n\n if page == \"Analysis Dashboard\":\n dashboard_page()\n elif page == \"Question Assistant\":\n qa_page()\n\n\ndef dashboard_page():\n st.title(\"\ud83d\udcca Macy's Document Analysis Dashboard\")\n\n provider_select = st.radio(\"Select AI Provider\", [\"Azure GPT\", \"Google Gemini\"])\n\n initialize_clients_and_agents(provider_select, mode=\"dashboard\")\n\n if \"session\" not in st.session_state:\n st.session_state.session = {\n 'uploaded_files': {},\n 'processed_files_overall': {},\n 'processed_files_tariff': {},\n 'processed_files_sales': {},\n 'processed_files_supplychain': {},\n 'active_file': None,\n 'active_topic': None,\n 'topic_details_cache': {},\n 'chat_history': [],\n 'consolidated_summary_overall': None,\n 'consolidated_summary_tariff': None,\n 'consolidated_summary_sales': None,\n 'consolidated_summary_supplychain': None,\n 'last_analysis_mode': None,\n 'custom_prompt_enabled': {},\n 'custom_prompt_text': {}\n }\n\n sess = st.session_state.session\n\n # --- File Upload ---\n st.subheader(\"1. Upload Documents\")\n uploaded_files = st.file_uploader(\n \"Upload PDF documents\",\n type=[\"pdf\"],\n accept_multiple_files=True,\n key=\"file_uploader\",\n )\n if uploaded_files:\n new_files_added = False\n for file in uploaded_files:\n if file.name not in sess['uploaded_files']:\n sess['uploaded_files'][file.name] = file.getvalue()\n new_files_added = True\n\n if new_files_added:\n with st.spinner(\"\ud83d\udd0d Analyzing new documents with Overall Agent...\"):\n analyze_documents(\n mode=\"overall\",\n agent=st.session_state.agent_overall,\n processed_files=sess['processed_files_overall'],\n sess=sess\n )\n\n # --- Custom Prompts & Analysis ---\n st.subheader(\"2. Custom Prompts & Analysis\")\n\n if 'custom_prompts' not in sess:\n sess['custom_prompts'] = {\n 'overall': {\n 'summary': OverallAgent.prompt_summary,\n 'analyze': OverallAgent.prompt_analyze,\n 'detail': OverallAgent.prompt_detail\n },\n 'tariff': {\n 'summary': TariffTradeAgent.prompt_summary,\n 'analyze': TariffTradeAgent.prompt_analyze,\n 'detail': TariffTradeAgent.prompt_detail\n },\n 'sales': {\n 'summary': SalesAgent.prompt_summary,\n 'analyze': SalesAgent.prompt_analyze,\n 'detail': SalesAgent.prompt_detail\n },\n 'supplychain': {\n 'summary': SupplyChainAgent.prompt_summary,\n 'analyze': SupplyChainAgent.prompt_analyze,\n 'detail': SupplyChainAgent.prompt_detail\n }\n }\n\n tab_overall, tab_tariff, tab_sales, tab_supply = st.tabs([\n \"\ud83d\udcd1 Overall\", \"\ud83d\udd0d Tariff\", \"\ud83d\udcc8 Sales\", \"\ud83d\ude9a Supply Chain\"\n ])\n\n generate_mode = None\n\n with tab_overall:\n st.subheader(\"Overall Prompts\")\n use_custom = st.checkbox(\"\u270f\ufe0f Use Custom Prompts\", key=\"custom_overall\")\n\n if use_custom:\n sess['custom_prompts']['overall']['summary'] = st.text_area(\n \"Summary Prompt:\",\n value=sess['custom_prompts']['overall']['summary'],\n height=150,\n key=\"overall_prompt_summary\"\n )\n sess['custom_prompts']['overall']['analyze'] = st.text_area(\n \"Analysis Prompt:\",\n value=sess['custom_prompts']['overall']['analyze'],\n height=150,\n key=\"overall_prompt_analyze\"\n )\n sess['custom_prompts']['overall']['detail'] = st.text_area(\n \"Detail Prompt:\",\n value=sess['custom_prompts']['overall']['detail'],\n height=150,\n key=\"overall_prompt_detail\"\n )\n\n if st.button(\"\ud83d\udd04 Generate with Custom Prompts\", key=\"generate_overall\"):\n generate_mode = \"overall\"\n\n with tab_tariff:\n st.subheader(\"Tariff Prompts\")\n use_custom = st.checkbox(\"\u270f\ufe0f Use Custom Prompts\", key=\"custom_tariff\")\n\n if use_custom:\n sess['custom_prompts']['tariff']['summary'] = st.text_area(\n \"Summary Prompt:\",\n value=sess['custom_prompts']['tariff']['summary'],\n height=150,\n key=\"tariff_prompt_summary\"\n )\n sess['custom_prompts']['tariff']['analyze'] = st.text_area(\n \"Analysis Prompt:\",\n value=sess['custom_prompts']['tariff']['analyze'],\n height=150,\n key=\"tariff_prompt_analyze\"\n )\n sess['custom_prompts']['tariff']['detail'] = st.text_area(\n \"Detail Prompt:\",\n value=sess['custom_prompts']['tariff']['detail'],\n height=150,\n key=\"tariff_prompt_detail\"\n )\n\n if st.button(\"\ud83d\udd04 Generate with Custom Prompts\", key=\"generate_tariff\"):\n generate_mode = \"tariff\"\n\n with tab_sales:\n st.subheader(\"Sales Prompts\")\n use_custom = st.checkbox(\"\u270f\ufe0f Use Custom Prompts\", key=\"custom_sales\")\n\n if use_custom:\n sess['custom_prompts']['sales']['summary'] = st.text_area(\n \"Summary Prompt:\",\n value=sess['custom_prompts']['sales']['summary'],\n height=150,\n key=\"sales_prompt_summary\"\n )\n sess['custom_prompts']['sales']['analyze'] = st.text_area(\n \"Analysis Prompt:\",\n value=sess['custom_prompts']['sales']['analyze'],\n height=150,\n key=\"sales_prompt_analyze\"\n )\n sess['custom_prompts']['sales']['detail'] = st.text_area(\n \"Detail Prompt:\",\n value=sess['custom_prompts']['sales']['detail'],\n height=150,\n key=\"sales_prompt_detail\"\n )\n\n if st.button(\"\ud83d\udd04 Generate with Custom Prompts\", key=\"generate_sales\"):\n generate_mode = \"sales\"\n\n with tab_supply:\n st.subheader(\"Supply Chain Prompts\")\n use_custom = st.checkbox(\"\u270f\ufe0f Use Custom Prompts\", key=\"custom_supply\")\n\n if use_custom:\n sess['custom_prompts']['supplychain']['summary'] = st.text_area(\n \"Summary Prompt:\",\n value=sess['custom_prompts']['supplychain']['summary'],\n height=150,\n key=\"supply_prompt_summary\"\n )\n sess['custom_prompts']['supplychain']['analyze'] = st.text_area(\n \"Analysis Prompt:\",\n value=sess['custom_prompts']['supplychain']['analyze'],\n height=150,\n key=\"supply_prompt_analyze\"\n )\n sess['custom_prompts']['supplychain']['detail'] = st.text_area(\n \"Detail Prompt:\",\n value=sess['custom_prompts']['supplychain']['detail'],\n height=150,\n key=\"supply_prompt_detail\"\n )\n\n if st.button(\"\ud83d\udd04 Generate with Custom Prompts\", key=\"generate_supplychain\"):\n generate_mode = \"supplychain\"\n\n st.subheader(\"Quick Analysis\")\n col0, col1, col2, col3 = st.columns(4)\n analyze_overall = col0.button(\"\ud83d\udcd1 Overall Summary\")\n analyze_tariff = col1.button(\"\ud83d\udd0d Analyze Tariffs\")\n analyze_sales = col2.button(\"\ud83d\udcc8 Analyze Sales\")\n analyze_supplychain = col3.button(\"\ud83d\ude9a Supply Chain\")\n\n # *** CHANGE: Clear processed files on custom generation to force re-analysis ***\n if generate_mode or analyze_overall or analyze_tariff or analyze_sales or analyze_supplychain:\n if not sess['uploaded_files']:\n st.error(\"Please upload documents first.\")\n st.stop()\n\n mode = generate_mode or (\n \"overall\" if analyze_overall else\n \"tariff\" if analyze_tariff else\n \"sales\" if analyze_sales else\n \"supplychain\" if analyze_supplychain else None\n )\n\n agent = None\n\n if mode == \"overall\":\n agent = st.session_state.agent_overall\n elif mode == \"tariff\":\n agent = st.session_state.agent_tariff\n elif mode == \"sales\":\n agent = st.session_state.agent_sales\n elif mode == \"supplychain\":\n agent = st.session_state.agent_supplychain\n\n # Clear processed files for fresh analysis on prompt change\n sess[f'processed_files_{mode}'] = {}\n processed_files = sess[f'processed_files_{mode}']\n\n if generate_mode:\n agent.prompt_summary = sess['custom_prompts'][mode]['summary']\n agent.prompt_analyze = sess['custom_prompts'][mode]['analyze']\n agent.prompt_detail = sess['custom_prompts'][mode]['detail']\n st.toast(f\"Using custom prompts for {mode} analysis\")\n else:\n if mode == \"overall\":\n agent.prompt_summary = OverallAgent.prompt_summary\n agent.prompt_analyze = OverallAgent.prompt_analyze\n agent.prompt_detail = OverallAgent.prompt_detail\n elif mode == \"tariff\":\n agent.prompt_summary = TariffTradeAgent.prompt_summary\n agent.prompt_analyze = TariffTradeAgent.prompt_analyze\n agent.prompt_detail = TariffTradeAgent.prompt_detail\n elif mode == \"sales\":\n agent.prompt_summary = SalesAgent.prompt_summary\n agent.prompt_analyze = SalesAgent.prompt_analyze\n agent.prompt_detail = SalesAgent.prompt_detail\n elif mode == \"supplychain\":\n agent.prompt_summary = SupplyChainAgent.prompt_summary\n agent.prompt_analyze = SupplyChainAgent.prompt_analyze\n agent.prompt_detail = SupplyChainAgent.prompt_detail\n\n with st.spinner(f\"\ud83d\udd0d Analyzing {mode.replace('supplychain', 'supply chain')} documents...\"):\n analyze_documents(\n mode,\n agent,\n processed_files,\n sess\n )\n\n # --- Main display and sidebar for topics and summaries ---\n last_mode = sess['last_analysis_mode']\n if last_mode is None:\n st.info(\"Select an analysis type to begin.\")\n return\n\n mode_config = {\n 'overall': {\n 'files': sess['processed_files_overall'],\n 'summary': sess['consolidated_summary_overall'],\n 'sidebar_header': \"Overall Topics\",\n 'main_header': \"\ud83c\udf1f Executive Summary\",\n 'agent': st.session_state.agent_overall\n },\n 'tariff': {\n 'files': sess['processed_files_tariff'],\n 'summary': sess['consolidated_summary_tariff'],\n 'sidebar_header': \"Tariff Topics\",\n 'main_header': \"\ud83c\udf1f Tariff Analysis\",\n 'agent': st.session_state.agent_tariff\n },\n 'sales': {\n 'files': sess['processed_files_sales'],\n 'summary': sess['consolidated_summary_sales'],\n 'sidebar_header': \"Sales Topics\",\n 'main_header': \"\ud83c\udf1f Sales Analysis\",\n 'agent': st.session_state.agent_sales\n },\n 'supplychain': {\n 'files': sess['processed_files_supplychain'],\n 'summary': sess['consolidated_summary_supplychain'],\n 'sidebar_header': \"Supply Chain Topics\",\n 'main_header': \"\ud83c\udf1f Supply Chain Analysis\",\n 'agent': st.session_state.agent_supplychain\n }\n }\n\n current_mode = mode_config[last_mode]\n\n # --- Sidebar Topics ---\n st.sidebar.header(current_mode['sidebar_header'])\n\n if last_mode == \"overall\":\n topics_by_file = {}\n for filename, filedata in current_mode['files'].items():\n for topic in filedata[\"topics\"]:\n topics_by_file.setdefault(topic['name'], []).append({\n 'file': filename,\n 'score': topic['score']\n })\n\n sorted_topics = sorted(topics_by_file.items(),\n key=lambda x: max(x[1], key=lambda y: y['score'])['score'],\n reverse=True)\n before_view_more, after_view_more = sorted_topics[:3], sorted_topics[3:]\n\n for topic_name, occurrences in before_view_more:\n total_score = sum(occ['score'] for occ in occurrences)\n file_count = len(occurrences)\n btn_label = f\"{topic_name} (\ud83d\udcc8 {total_score:.1f} | \ud83d\udcd1 {file_count})\"\n\n if st.sidebar.button(\n btn_label,\n key=f\"overall_topic_{topic_name}\",\n use_container_width=True,\n ):\n sess['active_topic'] = topic_name\n sess['active_file'] = None\n\n if after_view_more and st.sidebar.button('View More', key='1234', use_container_width=True):\n for topic_name, occurrences in after_view_more:\n total_score = sum(occ['score'] for occ in occurrences)\n file_count = len(occurrences)\n btn_label = f\"{topic_name} (\ud83d\udcc8 {total_score:.1f} | \ud83d\udcd1 {file_count})\"\n\n if st.sidebar.button(\n btn_label,\n key=f\"overall_topic_more_{topic_name}\",\n use_container_width=True,\n ):\n sess['active_topic'] = topic_name\n sess['active_file'] = None\n\n else: # Tariff, Sales, Supply Chain\n for filename, filedata in current_mode['files'].items():\n expanded = (filename == sess['active_file'])\n with st.sidebar.expander(f\"\ud83d\udcc4 {filename}\", expanded=expanded):\n topics = sorted(filedata[\"topics\"], key=lambda t: t[\"score\"], reverse=True)\n for topic in topics[:3]:\n is_selected = (\n sess['active_file'] == filename and sess['active_topic'] == topic['name']\n )\n style = \"primary\" if is_selected else \"secondary\"\n\n if st.button(\n f\"\u2022 {topic['name']} (Score: {topic['score']})\",\n key=f\"{last_mode}_topic_{filename}_{topic['name']}\",\n type=style,\n use_container_width=True,\n ):\n sess['active_file'] = filename\n sess['active_topic'] = topic['name']\n\n if len(topics) > 3 and st.sidebar.button(f'View More for {filename}', key=f'{filename}_view_more', use_container_width=True):\n for topic in topics[3:]:\n is_selected = (\n sess['active_file'] == filename and sess['active_topic'] == topic['name']\n )\n style = \"primary\" if is_selected else \"secondary\"\n\n if st.button(\n f\"\u2022 {topic['name']} (Score: {topic['score']})\",\n key=f\"{last_mode}_topic_more_{filename}_{topic['name']}\",\n type=style,\n use_container_width=True,\n ):\n sess['active_file'] = filename\n sess['active_topic'] = topic['name']\n\n # --- Topic Detail Analysis ---\n st.subheader(\"Detailed Analysis\")\n if last_mode == \"overall\" and sess['active_topic']:\n mentions = []\n for filename, filedata in current_mode['files'].items():\n for topic in filedata[\"topics\"]:\n if topic['name'] == sess['active_topic']:\n mentions.append({\n 'file': filename,\n 'summary': topic.get('summary', ''),\n 'score': topic['score'],\n 'context': filedata['context']\n })\n\n with st.expander(\"\ud83d\udcca Topic Prevalence\"):\n cols = st.columns(3)\n cols[0].metric(\"Total Documents\", len(mentions))\n avg_relevance = (sum(m['score'] for m in mentions) / len(mentions)) if mentions else 0\n cols[1].metric(\"Average Relevance\", f\"{avg_relevance:.1f}\")\n cols[2].metric(\"First Mentioned\", mentions[0]['file'] if mentions else \"N/A\")\n\n if mentions:\n combined_context = \"\\n\\n\".join(f\"=== {m['file']} ===\\n{m['context']}\" for m in mentions)\n key_cache = (last_mode, sess['active_topic'])\n if key_cache in sess['topic_details_cache']:\n st.markdown(sess['topic_details_cache'][key_cache])\n else:\n placeholder = st.empty()\n collected_text = \"\"\n try:\n for chunk in current_mode['agent'].generate_topic_detail(combined_context, sess['active_topic']):\n collected_text = chunk\n placeholder.markdown(collected_text + (\" \u258c\" if \"\u258c\" in collected_text else \"\"))\n sess['topic_details_cache'][key_cache] = collected_text\n markdown_to_word(collected_text, sess['active_topic']+'.docx')\n with open(sess['active_topic']+'.docx', 'rb') as f:\n st.download_button(\"Download Doc\", f, file_name=sess['active_topic']+'.docx')\n\n except Exception as e:\n st.error(f\"Analysis error: {str(e)}\")\n\n elif sess['active_file'] and sess['active_topic']:\n key_cache = (last_mode, sess['active_file'], sess['active_topic'])\n if key_cache in sess['topic_details_cache']:\n st.markdown(sess['topic_details_cache'][key_cache])\n else:\n placeholder = st.empty()\n collected_text = \"\"\n try:\n for chunk in current_mode['agent'].generate_topic_detail(\n current_mode['files'][sess['active_file']]['context'],\n sess['active_topic'],\n ):\n collected_text = chunk\n placeholder.markdown(collected_text + (\" \u258c\" if \"\u258c\" in collected_text else \"\"))\n sess['topic_details_cache'][key_cache] = collected_text\n markdown_to_word(collected_text, sess['active_topic']+'.docx')\n with open(sess['active_topic']+'.docx', 'rb') as f:\n st.download_button(\"Download Doc\", f, file_name=sess['active_topic']+'.docx')\n\n\n except Exception as e:\n st.error(f\"Analysis error: {str(e)}\")\n else:\n st.info(\"Select a topic from the sidebar\")\n\n st.markdown(\"---\")\n\n st.header(current_mode['main_header'])\n if current_mode['summary']:\n st.markdown(current_mode['summary'])\n markdown_to_word(current_mode['summary'], current_mode['sidebar_header']+'.docx')\n with open(current_mode['sidebar_header']+'.docx', 'rb') as f:\n st.download_button(\"Download Doc\", f, file_name=current_mode['sidebar_header']+'.docx')\n\n else:\n st.info(\"Summary not available yet\")\n\n st.divider()\n\n # --- Chat Interface ---\n st.subheader(\"\ud83d\udcac Document Chat\")\n\n available_files = list(current_mode['files'].keys())\n selected_files = st.multiselect(\n \"Select documents for context:\",\n available_files,\n key=f\"chat_selector_{last_mode}\"\n )\n\n for msg in sess['chat_history']:\n with st.chat_message(msg[\"role\"]):\n st.markdown(msg[\"content\"])\n\n question = st.chat_input(\"Ask about the documents...\")\n if question:\n if not selected_files:\n st.error(\"Please select documents first\")\n st.stop()\n\n sess['chat_history'].append({\n \"role\": \"user\",\n \"content\": question,\n \"timestamp\": datetime.utcnow().isoformat(),\n })\n\n try:\n context = \"\\n\\n\".join([\n f\"=== {fname} ===\\n{current_mode['files'][fname]['context']}\"\n for fname in selected_files\n ])\n\n with st.chat_message(\"assistant\"):\n response_placeholder = st.empty()\n full_response = \"\"\n q_type = None\n\n for chunk, q_type in st.session_state.chat_agent.generate_answer(question, context):\n full_response = chunk\n response_placeholder.markdown(full_response + \" \u258c\")\n\n response_placeholder.markdown(full_response)\n\n sess['chat_history'].append({\n \"role\": \"assistant\",\n \"content\": full_response,\n \"timestamp\": datetime.utcnow().isoformat(),\n \"analysis_type\": q_type\n })\n\n except Exception as e:\n st.error(f\"Chat error: {str(e)}\")\n sess['chat_history'].append({\n \"role\": \"assistant\",\n \"content\": f\"Error: {str(e)}\",\n \"timestamp\": datetime.utcnow().isoformat(),\n })\n\n if st.button(\"\ud83d\udd04 Reset Session\", type=\"secondary\"):\n preserved_keys = [\n \"client\", \"agent_overall\", \"agent_tariff\",\n \"agent_sales\", \"agent_supplychain\", \"chat_agent\", \"provider\"\n ]\n preserved = {k: st.session_state[k] for k in preserved_keys if k in st.session_state}\n\n st.session_state.clear()\n st.session_state.update(preserved)\n\n st.session_state.session = {\n 'uploaded_files': {},\n 'processed_files_overall': {},\n 'processed_files_tariff': {},\n 'processed_files_sales': {},\n 'processed_files_supplychain': {},\n 'active_file': None,\n 'active_topic': None,\n 'topic_details_cache': {},\n 'chat_history': [],\n 'consolidated_summary_overall': None,\n 'consolidated_summary_tariff': None,\n 'consolidated_summary_sales': None,\n 'consolidated_summary_supplychain': None,\n 'last_analysis_mode': None,\n 'custom_prompt_enabled': {},\n 'custom_prompt_text': {}\n }\n\n st.rerun()\n\n\ndef qa_page():\n st.title(\"\u2753 Macy's Question Assistant\")\n\n if 'qa_page' not in st.session_state:\n st.session_state.qa_page = {\n 'uploaded_files': {},\n 'processed_files': {},\n 'active_file': None,\n 'active_topic': None,\n 'chat_history': [],\n 'selected_files': []\n }\n qa_state = st.session_state.qa_page\n\n provider_select = st.sidebar.radio(\"Select AI Provider\", [\"Azure GPT\", \"Google Gemini\"])\n\n initialize_clients_and_agents(provider_select, mode=\"qa\")\n\n st.subheader(\"Upload Documents\")\n uploaded_files = st.file_uploader(\n \"Upload PDF documents for Q&A extraction\",\n type=[\"pdf\"],\n accept_multiple_files=True,\n key=\"qa_file_uploader\"\n )\n\n if uploaded_files:\n new_files_added = False\n for file in uploaded_files:\n if file.name not in qa_state['uploaded_files']:\n qa_state['uploaded_files'][file.name] = file.getvalue()\n new_files_added = True\n\n if new_files_added:\n with st.spinner(\"\ud83d\udd0d Extracting Q&A from new documents...\"):\n for filename in qa_state['uploaded_files']:\n if filename not in qa_state['processed_files']:\n try:\n file_bytes = qa_state['uploaded_files'][filename]\n file_obj = BytesIO(file_bytes)\n file_obj.name = filename\n text = extract_text(file_obj)\n if text:\n qa_data = st.session_state.agent_qa.analyze_question(text)\n qa_state['processed_files'][filename] = {\n 'text': text,\n 'qa_data': qa_data\n }\n st.toast(f\"\u2705 Processed {filename}\")\n\n if not qa_state.get('error') and qa_data.get('topics'):\n qa_state['active_topic'] = qa_data['topics'][0]\n else:\n st.error(f\"\u274c Failed to extract text for {filename}\")\n except Exception as e:\n st.error(f\"Error processing {filename}: {str(e)}\")\n\n if not qa_state['active_file'] and qa_state['processed_files']:\n qa_state['active_file'] = next(iter(qa_state['processed_files'].keys()))\n\n st.sidebar.header(\"\ud83d\udcc4 Processed Documents\")\n for filename in qa_state['processed_files']:\n if st.sidebar.button(\n f\"\ud83d\udcc4 {filename}\",\n key=f\"qa_file_{filename}\",\n use_container_width=True,\n ):\n qa_state['active_file'] = filename\n file_data = qa_state['processed_files'][filename]\n qa_data = file_data['qa_data']\n if not qa_data.get('error') and qa_data.get('topics'):\n qa_state['active_topic'] = qa_data['topics'][0]\n\n if qa_state['active_file']:\n file_data = qa_state['processed_files'][qa_state['active_file']]\n qa_data = file_data['qa_data']\n\n st.sidebar.header(\"\ud83d\udccc Topics\")\n\n if \"error\" in qa_data:\n st.sidebar.error(\"Error in document processing\")\n\n elif 'topics' in qa_data:\n topics = qa_data['topics']\n\n for topic in topics:\n btn_label = f\"{topic['topic']} ({topic['mention_count']} mentions)\"\n if st.sidebar.button(\n btn_label,\n key=f\"topic_{topic['topic']}_{qa_state['active_file']}\",\n use_container_width=True,\n ):\n qa_state['active_topic'] = topic\n else:\n st.sidebar.info(\"No topics found in this document\")\n\n st.subheader(\"\ud83d\udcdd Extracted Q&A Content\")\n\n if qa_state['active_file']:\n file_data = qa_state['processed_files'][qa_state['active_file']]\n qa_data = file_data['qa_data']\n st.markdown(f\"**Document:** {qa_state['active_file']}\")\n\n if \"error\" in qa_data:\n st.error(f\"Error processing document: {qa_data['error']}\")\n if \"raw_response\" in qa_data:\n st.text_area(\"Raw AI Response\", qa_data[\"raw_response\"], height=300)\n\n elif 'key_takeaways' in qa_data and qa_data['key_takeaways']:\n st.subheader(\"Key Takeaways\")\n for takeaway in qa_data['key_takeaways']:\n st.markdown(f\"- {takeaway}\")\n\n if qa_state['active_topic']:\n topic = qa_state['active_topic']\n st.divider()\n st.subheader(topic['topic'])\n st.markdown(f\"**Mentioned:** {topic['mention_count']} times\")\n st.divider()\n\n if 'questions' in topic and topic['questions']:\n for idx, question in enumerate(topic['questions']):\n firm = question.get('firm', 'Unknown Firm')\n st.markdown(f\"**Firm:** {firm}\")\n st.markdown(f\"**Question {idx+1}:** {question['question']}\")\n st.write(\"---\")\n else:\n st.info(\"No questions found for this topic\")\n elif 'topics' in qa_data and qa_data['topics']:\n qa_state['active_topic'] = qa_data['topics'][0]\n st.rerun()\n else:\n st.info(\"No Q&A content found for this document\")\n else:\n st.info(\"Upload documents to see extracted Q&A content\")\n\n st.divider()\n\n st.subheader(\"\ud83d\udcac Chat with Documents\")\n\n available_files = list(qa_state['processed_files'].keys())\n selected_files = st.multiselect(\n \"Select documents to include in chat context:\",\n available_files,\n default=available_files[:min(3, len(available_files))],\n key=\"qa_chat_selector\"\n )\n qa_state['selected_files'] = selected_files\n\n for msg in qa_state['chat_history']:\n with st.chat_message(msg[\"role\"]):\n st.markdown(msg[\"content\"])\n\n question = st.chat_input(\"Ask about the documents...\")\n if question:\n if not selected_files:\n st.error(\"Please select at least one document for context\")\n st.stop()\n\n qa_state['chat_history'].append({\n \"role\": \"user\",\n \"content\": question,\n \"timestamp\": datetime.utcnow().isoformat(),\n })\n\n try:\n context = \"\\n\\n\".join([\n f\"=== {filename} ===\\n{qa_state['processed_files'][filename]['text']}\"\n for filename in selected_files\n ])\n\n with st.chat_message(\"assistant\"):\n response_placeholder = st.empty()\n full_response = \"\"\n\n for chunk, _ in st.session_state.chat_agent.generate_answer(question, context):\n full_response = chunk\n response_placeholder.markdown(full_response + \" \u258c\")\n\n response_placeholder.markdown(full_response)\n\n qa_state['chat_history'].append({\n \"role\": \"assistant\",\n \"content\": full_response,\n \"timestamp\": datetime.utcnow().isoformat(),\n })\n\n except Exception as e:\n st.error(f\"Chat error: {str(e)}\")\n qa_state['chat_history'].append({\n \"role\": \"assistant\",\n \"content\": f\"Error: {str(e)}\",\n \"timestamp\": datetime.utcnow().isoformat(),\n })\n\n if st.button(\"\ud83d\udd04 Reset Q&A Session\", key=\"reset_qa_page\"):\n qa_state.clear()\n qa_state.update({\n 'uploaded_files': {},\n 'processed_files': {},\n 'active_file': None,\n 'active_topic': None,\n 'chat_history': [],\n 'selected_files': []\n })\n st.rerun()\n\n\nif __name__ == \"__main__\":\n main()\n\nreplace everything of supplychain and sales with Consumer Health and Monthly Performance all things even import"},{"assistant_initiates":false,"asst_text":"Certainly! Below is a revised version of your `ConsumerHealthAgent` (previously `SupplyChainAgent`) class, where I have adapted the prompts according to your detailed instructions and requirements.\n\n---\n\n```python\nfrom agents.base_agent import BaseAgent\n\nclass ConsumerHealthAgent(BaseAgent):\n prompt_sys = \"Consumer health and macroeconomic analyst for Macy's, tasked with analyzing provided documents regarding consumer financial health and macro environment.\"\n\n # Universal formatting enforcement line (adapted and extended where necessary)\n formatting_directive = \"\"\"Please strictly follow these formatting guidelines for all numerical mentions and sentence structures:\n1. **No Combined Elements**: Always space-separate numbers, words, and units (e.g., \"3.3 billion\" not \"3.3billion\").\n2. **Time Formatting**: Use formats like \"Q4 2024\" (never \"Q42024\" or \"4th quarter\").\n3. **Number Rules**: \n - 3.3B \u2192 3.3 billion \n - 150.2M \u2192 150.2 million \n - 0.33 \u2192 keep exact decimal \n4. **Text Integrity**: \n - \"net income\" never \"netincome\" \n - \"year-over-year\" never \"YOY\" or \"yearoveryear\" \n - \"YOY \" never \"year-over-year\" or \"yearoveryear\" \n - \"vs.\" never \"versus\" or \"vs\" \n - \"$XB\" never \"$X billion\" \n - \"$XM\" never \"$X million\" \n5. **Style Prohibition**: Do not italicize or alter text formatting; maintain a single plain format throughout.\n6. **Bad Example**: `3.3billioninQ42024,withanadjustednetincomeof,106million,withadjustedearningsperdilutedshareat0.95` \u2192 REJECTED\n7. **ALWAYS Required Format**: `3.3 billion in Q4 2024, with an adjusted net income of` \u2192 ACCEPTED\n\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS AND SENTENCE STRUCTURES.\"\"\"\n \n prompt_analyze = (\n \"You are a senior business analyst working directly for Macy's CEO. Analyze the provided earnings call transcript and summarize mentions \"\n \"of consumer financial health and the macroeconomic environment.\\n\\n\"\n \"Identify key topics including but not limited to:\\n\"\n \"- US consumer\\n\"\n \"- The company\u2019s customer\\n\"\n \"- Change in demand\\n\"\n \"- Change in spend\\n\\n\"\n \"For each topic, provide:\\n\"\n \"- A clear topic name (e.g., \\\"E-commerce Growth\\\", \\\"Supply Chain Digitization\\\")\\n\"\n \"- Concise 100-word summary providing key numbers and operational impacts\\n\"\n \"- Strictly preserve original numerical and textual formatting: maintain exact decimals (0.33), required spacing (0.11 \u2192 '0.11'), and verbatim terminology without concatenation or rephrasing.\\n\"\n \"- For every topic, ALWAYS provide excerpts mentioned under the heading \\\"Ground Truth\\\" as follows:\\n\"\n \" - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document.\\n\"\n \" - Format each excerpt as: **Ground Truth:** \\\"Exact text from the document...\\\" (Document Name)\\n\"\n \" - If a topic is present in multiple documents, include a separate \\\"Ground Truth\\\" excerpt for each document.\\n\"\n \" - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the document data exactly, including all formatting, punctuation, and special characters.\\n\"\n \" - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the documents.\\n\\n\"\n \"Format each topic as:\\n\"\n \"- Topic Name: Summary [Relevance Score]\\n\\n\"\n \"Example:\\n\"\n \"- Holiday Sales Performance: Q4 comparable sales up 4.2% driven by 18% digital growth [8]\\n\"\n \"- Inventory Optimization: Implementing AI demand forecasting to reduce carrying costs by $150M [7]\\n\\n\"\n \"Document Text: \" + formatting_directive\n )\n \n prompt_summary = (\n \"You are a senior analyst preparing a summary of transcript commentary from all documents provided.\\n\"\n \"Identify and describe all mentions of consumer financial health and the macroeconomic environment in the provided documents, \"\n \"focusing on what the company says about the US consumer, their customer, a change in demand, or a change in spend. Combine and synthesize topics that appear in multiple documents.\\n\\n\"\n \"1. **Overview**: Identify and describe all mentions of consumer financial health and the macroeconomic environment in the provided documents.\\n\\n\"\n \"2. For each topic:\\n\"\n \" * Provide a concise summary by combining information from all relevant documents.\\n\"\n \" * Include relevant examples, numerical data, or timelines from the documents.\\n\"\n \" * For every topic, ALWAYS provide each excerpt mentioned under the heading \\\"Ground Truth\\\" as follows:\\n\"\n \" - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document.\\n\"\n \" - Format each excerpt as: **Ground Truth:** \\\"Exact text from the document...\\\" (Document Name)\\n\"\n \" - If the same topic is present in multiple documents, always include a separate \\\"Ground Truth\\\" excerpt for each document with proper line breaks.\\n\"\n \" - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the documents data exactly, including all formatting, punctuation, and special characters.\\n\"\n \" - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the document.\\n\\n\"\n \"3. Format with clear sections in plain black text with proper headings:\\n\"\n \" * Consumer Health Summary\\n\\n\"\n \"Use the following Documents Analysis Data to combine similar topics from different documents and provide a comprehensive summary:\\n\"\n \"{topics_block}\\n\\n\"\n \"Provide a comprehensive yet concise summary. STRICTLY ENFORCE PLAIN TEXT FORMATTING:\\n\"\n + formatting_directive\n )\n \n prompt_detail = (\n \"You are preparing a detailed briefing for Macy's CEO on the consumer health topic '{topic}', based on the external company document.\\n\\n\"\n \"Provide:\\n\"\n \"1. Overview of the topic.\\n\"\n \"2. Key insights and relevant excerpts.\\n\"\n \"3. Important figures, timelines, or operational metrics.\\n\"\n \"4. Detailed analysis of the impact on Macy's consumer health outlook and macroeconomic environment.\\n\"\n \"5. For every topic, ALWAYS provide verbatim source excerpts under the heading \\\"Ground Truth\\\" as follows:\\n\"\n \" - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document.\\n\"\n \" - Format each excerpt as: **Ground Truth:** \\\"Exact text from the document...\\\" (Document Name)\\n\"\n \" - If a topic is present in multiple documents, include a separate \\\"Ground Truth\\\" excerpt for each document.\\n\"\n \" - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\\n\"\n \" - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\\n\\n\"\n \"Document:\\n\"\n \"{text}\\n\\n\"\n \"Topic: {topic}\\n\\n\"\n \"Please provide a structured briefing with proper paragraphs and bold topics.\\n\"\n + formatting_directive\n )\n \n def analyze_document(self, text, custom_prompt=None):\n prompt_analyze = custom_prompt if custom_prompt else self.prompt_analyze\n return super().analyze_document(self.prompt_sys, prompt_analyze, text)\n\n def generate_consolidated_summary_from_topics(self, processed_files, custom_prompt=None):\n prompt_summary = custom_prompt if custom_prompt else self.prompt_summary\n return super().generate_consolidated_summary_from_topics(self.prompt_sys, prompt_summary, processed_files)\n\n def generate_topic_detail(self, text, topic, custom_prompt=None):\n prompt_detail = custom_prompt if custom_prompt else self.prompt_detail\n return super().generate_topic_detail(self.prompt_sys, prompt_detail, text, topic)\n```\n\n---\n\n### Explanation of key changes:\n\n- `prompt_sys` updated to specify consumer health and macroeconomic environment focus.\n- `formatting_directive` adjusted to your new detailed requirements, strictly enforcing spacing, numerical forms, prohibition of italic/bold, and sample bad/good examples.\n- `prompt_analyze` asks to identify key topics related to US consumer, demand changes, spend changes, emphasizing strict formatting and provision of verbatim excerpts under \"Ground Truth\".\n- `prompt_summary` directs the LLM to provide a comprehensive summary of all documents combined focusing on consumer health & macro environment, giving \"Ground Truth\" excerpts for every topic.\n- Removed recommendation sections or instructions for management action per your specification.\n- `prompt_detail` adapted for detailed briefings on a topic focused on consumer health, again with strict \"Ground Truth\" excerpts and formatting.\n- The methods `analyze_document`, `generate_consolidated_summary_from_topics`, and `generate_topic_detail` appropriately use custom prompts if provided, else default to these updated prompts.\n\n---\n\nIf you'd like, I can also help you update the import paths and code to reflect this new agent class in your main app!","behavior":"degenerate_repetition","conversation_hash":"0b69690e8d34bc3a343be970578db8a0","conversation_redacted":false,"conversation_toxic":false,"country":"India","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":22330,"n_turns_in_conversation":6,"n_words":2973,"source_row_offset":14124,"source_shard":"turns-00084.parquet","timestamp":"Fri, 27 Jun 2025 18:50:06 GMT","turn_id":"5d4e85ebc4dde0e4fb745d5c","turn_index":1,"user_text":"can you change the prompts according to ConsumerHealth agent \n\nfrom agents.base_agent import BaseAgent\n\nclass SupplyChainAgent(BaseAgent):\n prompt_sys = \"Supply chain analyst for Macy's works for only provided documents\"\n \n # Universal formatting enforcement line\n formatting_directive = \"\"\"Please follow these formatting guidelines:\n1. **No Combined Elements**: Always space-separate numbers/words/units (3.3 billion not 3.3billion)\n2. **Time Formatting**: Q4 2024 (never Q42024 or 4th quarter)\n3. **Number Rules**: \n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal\n4. **Text Integrity**: \n - \"net income\" never \"netincome\"\n - \"year-over-year\" never \"YOY\" or \"yearoveryear\"\n5. **Style Prohibition**: Do not make any word in Italic or any other format always make it in one format\n6. **Bad Example**: 3.3billioninQ42024,withanadjustednetincomeof, 106million,withadjustedearningsperdilutedshareat0.95 \u2192 REJECTED\n7. **ALWAYS Required Format**: 3.3 billion in Q4 2024, with an adjusted net income of \u2192 ACCEPTED\n\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS AND SENTENCE STRUCTURES.\"\"\"\n \n prompt_analyze = \"\"\"You are a senior supply chain analyst specializing in logistics and procurement for Macy's operations. \nYou have received a transcript/document from another company.\n\nIdentify all significant supply chain and logistics topics in the text from all the files that could affect Macy's procurement, inventory, delivery timelines, and supplier relationships.\n\nFor each topic, provide: \n- A concise topic name (e.g., \"Port Congestion\", \"Supplier Delays\"). \n- A brief describing in 200 words including its impact on Macy's supply chain operations also include Overview of the topic, Key insights and relevant excerpts, Important figures, timelines, or operational metrics, Detailed analysis on impact to Macy's supply chain, procurement, and logistics. \n- A relevance score from 1 (minor) to 10 (critical).\n\nFormat your response one topic per line: \n- Topic Name: Summary [Relevance Score]\n\nExample lines: \n- Port Congestion: Delays expected affecting inventory availability [9] \n- Supplier Delay: Lead times extended due to supplier issues [8]\n\nAnalyze this external document:\"\"\" + formatting_directive \n\n prompt_summary = \"\"\"You are a senior supply chain analyst preparing a consolidated supply chain and procurement report for Macy's executive team from all document provided.\n\nYou have reviewed supply chain and logistics topics extracted from multiple external company documents. These topics include their names, summaries, and relevance scores. Based on their content, please:\n\n1. **OverView**: Identify and describe all their impactful supply chain and logistics topics that could affect Macy's inventory management, procurement, delivery timelines, and supplier relationships.\n2. For each topic:\n * Provide a concise summary from combining all the relevant documents.\n * Include relevant metrics, timelines, or examples from the documents also provide from which document it is taken.\n * Explain operational and strategic impacts\u2014positive , negative, or neutral\u2014specifically tailored to Macy's supply chain and logistics.\n * Provide 3-5 actionable strategic recommendations for Macy's leadership.\n * For every topic, ALWAYS provide verbatim source excerpts under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a same topic is present in multiple documents, always include a separate \"Ground Truth\" excerpt for each document with proper line breaks.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\n \n3. Format in clear sections in black text with proper headings:\n * Executive Summary\n * Key Themes\n * Strategic Recommendations\n * Risk Assessment\n \n4. Avoid jargon and focus on practical operational impacts and strategy insights.\n\n\nUse Documents Analysis Data from all the documents provided below try combining the same topics from different documents and provide the summary of all the topics in one place.:\n{topics_block}\n\nDeliver a detailed, actionable consolidated supply chain report for Macy's.\"\"\" + formatting_directive \n\n prompt_detail = \"\"\"You are preparing a detailed briefing for Macy's CEO on the supply chain topic '{topic}', based on the external company document.\n\nProvide:\n1. Overview of the topic.\n2. Key insights and relevant excerpts.\n3. Important figures, timelines, or operational metrics.\n4. Detailed analysis on impact to Macy's supply chain, procurement, and logistics.\n5. 3-5 actionable recommendations for Macy's leadership.\n6. For every topic, ALWAYS provide verbatim source excerpts under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a topic is present in multiple documents, include a separate \"Ground Truth\" excerpt for each document.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\n\n\nDocument:\n{text}\n\nTopic: {topic}\n\nPlease provide structured briefing with proper paragraphs and bold topics.\n\"\"\" + formatting_directive \n\n def analyze_document(self, text, custom_prompt=None):\n prompt_analyze = custom_prompt if custom_prompt else self.prompt_analyze\n return super().analyze_document(self.prompt_sys, prompt_analyze, text)\n\n def generate_consolidated_summary_from_topics(self, processed_files, custom_prompt=None):\n prompt_summary = custom_prompt if custom_prompt else self.prompt_summary\n return super().generate_consolidated_summary_from_topics(self.prompt_sys, prompt_summary, processed_files)\n\n def generate_topic_detail(self, text, topic, custom_prompt=None):\n prompt_detail = custom_prompt if custom_prompt else self.prompt_detail\n return super().generate_topic_detail(self.prompt_sys, prompt_detail, text, topic)\n\n\nchange according to below suggestions\n\nPrompt: Summarize what the company said regarding consumer health and the macro environment. If no detail is provided, say \u201cN/A\u201d.\nPull in details on what the company says about the US consumer, their customer, a change in demand and/or a change in spend.\n\n\nYou are a senior analyst preparing a summary of transcript commentary from all documents provided.\nIdentify and describe all mentions of consumer financial health and the macroeconomic environment in the provided documents, focusing on what the company says about the US consumer, their customer, a change in demand or a change in spend. Combine and synthesize topics that appear in multiple documents.\n \n1. **Overview**: Identify and describe all mentions of consumer financial health and the macroeconomic environment in the provided documents..\n \n2. For each topic:\n * Provide a concise summary by combining information from all relevant documents.\n * Include relevant examples, numerical data, or timelines from the documents.\n * For every topic, ALWAYS provide each excerpts mentioned under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a same topic is present in multiple documents, always include a separate \"Ground Truth\" excerpt for each document with proper line breaks.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the documents data exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the document.\n \n3. Format in clear with sections in black text with proper headings:\n * Consumer Health Summary\n \nUse the following Documents Analysis Data to combine similar topics from different documents and provide a comprehensive summary:\n{topics_block}\n \nProvide comprehensive yet concise summary. STRICTLY ENFORCE PLAIN TEXT FORMATTING:\n2. **No Combined Elements**: Always space-separate numbers/words/units (3.3 billion not 3.3billion)\n3. **Time Formatting**: Q4 2024 (never Q42024 or 4th quarter)\n4. **Number Rules**: \n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal\n5. **Text Integrity**: \n - \"net income\" never \"netincome\"\n - \"year-over-year\" never \"YOY\" or \"yearoveryear\"\n6. **Style Prohibition**: Do not make any word in Italic or any other format always make it in one format\n7. **Bad Example**: 3.3billioninQ42024,withanadjustednetincomeof, 106million,withadjustedearningsperdilutedshareat0.95 \u2192 REJECTED\n8. **ALLWAYS Required Format**: 3.3 billion in Q4 2024, with an adjusted net income of \u2192 ACCEPTED\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS AND SENTENCE STRUCTURES.\nAnalysis Prompt\nYou are a senior business analyst working directly for Macy's CEO. Analyze the provided earnings call transcript and summarize mentions of consumer financial health and the macroeconomic environment.\n \nIdentify key topics including but not limited to:\nUS consumer\nThe company\u2019s customer\nChange in demand\nChange in spend\n \nFor each topic, provide:\n* A clear topic name (e.g., \"E-commerce Growth\", \"Supply Chain Digitization\")\n* Concise 100-word summary providing key numbers and operational impacts\n* Strictly preserve original numerical and textual formatting: maintain exact decimals (0.33), required spacing between numbers/text (0.11 \u2192 '0.11'), and verbatim terminology without concatenation or rephrasing.\n* For every topic, ALWAYS provide excerpts mentioned under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a topic is present in multiple documents, include a separate \"Ground Truth\" excerpt for each document.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the document data exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the documents.\nFormat each topic as:\n- Topic Name: Summary [Relevance Score]\n \nExample:\n- Holiday Sales Performance: Q4 comparable sales up 4.2% driven by 18% digital growth [8]\n- Inventory Optimization: Implementing AI demand forecasting to reduce carrying costs by $150M [7]\nDocument Text:STRICTLY ENFORCE PLAIN TEXT FORMATTING:\n2. **No Combined Elements**: Always space-separate numbers/words/units (3.3 billion not 3.3billion)\n3. **Time Formatting**: Q4 2024 (never Q42024 or 4th quarter)\n4. **Number Rules**: \n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal\n5. **Text Integrity**: \n - \"net income\" never \"netincome\"\n - \"YOY \" never \"year-over-year\" or \"yearoveryear\"\n - \u201cvs.\u201d never \u201cversus\u201d or \u201cvs\u201d\n - \u201c$XB\u201d never \u201c$X billion\u201d\n - \u201c$XM\u201d never \u201c$X million\u201d\n6. **Style Prohibition**: Do not make any word in Italic or any other format always make it in one format\n7. **Bad Example**: 3.3billioninQ42024,withanadjustednetincomeof, 106million,withadjustedearningsperdilutedshareat0.95 \u2192 REJECTED\n8. **ALLWAYS Required Format**: 3.3 billion in Q4 2024, with an adjusted net income of \u2192 ACCEPTED\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS AND SENTENCE STRUCTURES.\n\n\nThe output should be a summary of the commentary, in 100 words or less. The summary should be in the third person (name of the company, management, the company)\nWe do not need the recommendation to Macy\u2019s management for the specific commentary modules \u2013 we just want the bulleted summary of the commentary for each.\n\n"},{"assistant_initiates":false,"asst_text":"Certainly! Below is the adapted version of your `SalesAgent` for **MonthlyPerformanceAgent**, reflecting the focus on monthly sales performance (February, March, April) and aligned with your provided instructions:\n\n```python\nfrom agents.base_agent import BaseAgent\n\nclass MonthlyPerformanceAgent(BaseAgent):\n prompt_sys = \"Monthly performance analyst for Macy's executive team works only with the provided documents.\"\n \n # Universal formatting enforcement line (same as sales but can customize further if required)\n formatting_directive = \"\"\"Please follow these formatting guidelines:\n1. **No Combined Elements**: Always space-separate numbers/words/units (3.3 billion not 3.3billion)\n2. **Time Formatting**: Use exact months and quarters such as February, March, April or Q1 2024 (avoid informal or combined forms like Feb2024).\n3. **Number Rules**: \n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal\n4. **Text Integrity**: \n - \"net income\" never \"netincome\"\n - \"year-over-year\" never \"YOY\" or \"yearoveryear\"\n5. **Style Prohibition**: Do not make any word in Italic or any other format; always keep it uniform\n6. **Bad Example**: 3.3billioninFeb2024,withanadjustednetincomeof,106million,withadjustedearningsperdilutedshareat0.95 \u2192 REJECTED\n7. **ALWAYS Required Format**: 3.3 billion in February 2024, with an adjusted net income of \u2192 ACCEPTED\n\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS AND SENTENCE STRUCTURES.\"\"\"\n \n prompt_analyze = (\n \"You are a senior monthly performance analyst specializing in analyzing Macy's retail sales for February, March, and April. \"\n \"You have received a transcript/document from another company.\\n\\n\"\n \"Identify all significant sales performance topics that could affect Macy's monthly sales reporting, revenue trends, and operational effectiveness for the months of February, March, and April.\\n\\n\"\n \"For each topic, provide:\\n\"\n \"- A concise topic name (e.g., \\\"February Sales Growth\\\", \\\"April Marketing Impact\\\").\\n\"\n \"- A brief 200-word description including relevance or impact on Macy's monthly sales performance, covering: overview of the topic, key insights, important figures/dates/timelines (specific to Feb, Mar, Apr), and detailed impact analysis.\\n\"\n \"- A relevance score from 1 (minor) to 10 (critical).\\n\\n\"\n \"Format your response one topic per line:\\n\"\n \"- Topic Name: Summary [Relevance Score]\\n\\n\"\n \"Example:\\n\"\n \"- February Sales Performance: Comparable sales grew 5.2% driven by strong digital channel growth [8]\\n\"\n \"- March Marketing Campaign: New campaigns boosted foot traffic by 15% [7]\\n\\n\"\n \"Analyze the following external company document:\" + formatting_directive\n )\n \n prompt_summary = (\n \"You are a senior monthly performance analyst preparing a consolidated report on sales performance for the months of February, March, and April for Macy's executive team.\\n\\n\"\n \"You have reviewed sales performance topics extracted from multiple external company documents concerning these months. These topics include their names, summaries, and relevance scores. Based on their combined content, please:\\n\\n\"\n \"1. **Overview**: Summarize all impactful sales performance topics related to February, March, and April provided in the documents.\\n\\n\"\n \"2. For each topic:\\n\"\n \" * Provide a concise summary by combining information from all relevant documents related to those months.\\n\"\n \" * Include relevant examples, numerical data, or timelines specific to February, March, and April.\\n\"\n \" * Explain operational and strategic impacts\u2014positive, negative, or neutral\u2014specifically tailored to Macy's monthly retail business.\\n\"\n \" * Provide 3-5 actionable strategic recommendations for Macy's leadership.\\n\"\n \" * For every topic, ALWAYS provide verbatim source excerpts under the heading \\\"Ground Truth\\\" as follows:\\n\"\n \" - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document.\\n\"\n \" - Format each excerpt as: **Ground Truth:** \\\"Exact text from the document...\\\" (Document Name)\\n\"\n \" - If the same topic is present in multiple documents, include a separate \\\"Ground Truth\\\" excerpt for each document with proper line breaks.\\n\"\n \" - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\\n\"\n \" - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\\n\\n\"\n \"3. Format with clear sections in black text with proper headings:\\n\"\n \" * Executive Summary\\n\"\n \" * Key Themes\\n\"\n \" * Strategic Recommendations\\n\"\n \" * Risk Assessment\\n\\n\"\n \"Use Documents Analysis Data from all the documents provided below. Combine the same topics from different documents and provide the summary of all the topics in one place.\\n\\n\"\n + formatting_directive\n )\n \n prompt_detail = (\n \"You are preparing a detailed briefing for Macy's CEO on the monthly performance topic '{topic}', based on the external company document.\\n\\n\"\n \"Provide:\\n\"\n \"1. An overview of the topic.\\n\"\n \"2. Key insights and relevant excerpts.\\n\"\n \"3. Important figures, dates, or timelines (with emphasis on February, March, and April).\\n\"\n \"4. Detailed analysis of the impact on Macy's monthly sales performance and operational decisions.\\n\"\n \"5. 3-5 actionable recommendations for Macy's leadership.\\n\"\n \"6. For every topic, ALWAYS provide verbatim source excerpts under the heading \\\"Ground Truth\\\" as follows:\\n\"\n \" - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document.\\n\"\n \" - Format each excerpt as: **Ground Truth:** \\\"Exact text from the document...\\\" (Document Name)\\n\"\n \" - If a topic is present in multiple documents, include a separate \\\"Ground Truth\\\" excerpt for each document.\\n\"\n \" - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\\n\"\n \" - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\\n\\n\"\n \"Document:\\n\"\n \"{text}\\n\\n\"\n \"Topic: {topic}\\n\\n\"\n \"Please provide a structured briefing with proper paragraphs and bold topics.\\n\"\n + formatting_directive\n )\n \n def analyze_document(self, text, custom_prompt=None):\n prompt_analyze = custom_prompt if custom_prompt else self.prompt_analyze\n return super().analyze_document(self.prompt_sys, prompt_analyze, text)\n \n def generate_consolidated_summary_from_topics(self, processed_files, custom_prompt=None):\n prompt_summary = custom_prompt if custom_prompt else self.prompt_summary\n return super().generate_consolidated_summary_from_topics(self.prompt_sys, prompt_summary, processed_files)\n \n def generate_topic_detail(self, text, topic, custom_prompt=None):\n prompt_detail = custom_prompt if custom_prompt else self.prompt_detail\n return super().generate_topic_detail(self.prompt_sys, prompt_detail, text, topic)\n```\n\n---\n\n### Summary of changes:\n\n- `prompt_sys` updated to \"Monthly performance analyst...\"\n- `formatting_directive` includes strict formatting rules and emphasizes exact month names and formal time formatting.\n- `prompt_analyze` focuses on identifying and summarizing sales performance topics for February, March, and April, with example topics reflecting those months.\n- `prompt_summary` asks to consolidate all relevant topics for these 3 months, including actionable recommendations.\n- `prompt_detail` includes emphasis on these months in figures, dates, timelines, and analysis.\n- No mention of recommendations is removed since the example kept recommendations for Sales - you can remove if wanted.\n- All prompts strongly enforce the formatting rules you provided earlier.\n\nIf you want me to remove recommendations or further tune these prompts, just say!","behavior":"degenerate_repetition","conversation_hash":"0b69690e8d34bc3a343be970578db8a0","conversation_redacted":false,"conversation_toxic":false,"country":"India","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":15372,"n_turns_in_conversation":6,"n_words":1973,"source_row_offset":14125,"source_shard":"turns-00084.parquet","timestamp":"Fri, 27 Jun 2025 18:50:06 GMT","turn_id":"ab883a9d751aa55bdd2de6e2","turn_index":2,"user_text":"from agents.base_agent import BaseAgent\n\nclass SalesAgent(BaseAgent):\n prompt_sys = \"Sales analyst for Macy's executive team works for only provided documents\"\n \n # Universal formatting enforcement line\n formatting_directive = \"\"\"Please follow these formatting guidelines:\n1. **No Combined Elements**: Always space-separate numbers/words/units (3.3 billion not 3.3billion)\n2. **Time Formatting**: Q4 2024 (never Q42024 or 4th quarter)\n3. **Number Rules**: \n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal\n4. **Text Integrity**: \n - \"net income\" never \"netincome\"\n - \"year-over-year\" never \"YOY\" or \"yearoveryear\"\n5. **Style Prohibition**: Do not make any word in Italic or any other format always make it in one format\n6. **Bad Example**: 3.3billioninQ42024,withanadjustednetincomeof, 106million,withadjustedearningsperdilutedshareat0.95 \u2192 REJECTED\n7. **ALLWAYS Required Format**: 3.3 billion in Q4 2024, with an adjusted net income of \u2192 ACCEPTED\n\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS AND SENTENCE STRUCTURES.\"\"\"\n \n prompt_analyze = \"\"\"You are a senior sales analyst specializing in retail sales and consumer behavior, assisting Macy's executive team. \nYou have received a transcript/document from another company.\n\nIdentify all significant sales and consumer behavior topics that could affect Macy's retail sales strategy, revenue, marketing effectiveness, and customer engagement.\n\nFor each topic, provide: \n- A concise topic name (e.g., \"Holiday Sales Surge\", \"Online Shopping Trends\"). \n- A brief describing in 200 words including its relevance or impact on Macy's sales, considering the external company's context, also include An overview of the topic, Key insights and relevant excerpts, Important figures, dates, or timelines, Detailed analysis of the impact on Macy's retail sales, marketing, and customer engagement. \n- A relevance score from 1 (minor) to 10 (critical).\n\nFormat your response one topic per line: \n- Topic Name: Summary [Relevance Score]\n\nExample: \n- Holiday Sales Boost: Significant increase in sales volume expected during holidays [9] \n- E-commerce Growth: Online shopping rise impacting in-store sales [8]\n\nAnalyze the following external company document:\"\"\" + formatting_directive \n\n prompt_summary = \"\"\"You are a senior sales analyst preparing a consolidated sales and consumer behavior report for Macy's executive team from all document provided.\n\nYou have reviewed sales and consumer behavior topics extracted from multiple external company documents. These topics include their names, summaries, and relevance scores. Based on their content, please:\n\n\n1. **OverView**: Identify and describe from all documents all their impactful sales and consumer behavior topics that could affect Macy's retail sales, marketing, and customer engagement.\n\n2. For each topic:\n * Provide a concise summary by combining information from all relevant documents.\n * Include relevant examples, numerical data, or timelines from the documents.\n * Explain operational and strategic impacts\u2014positive, negative, or neutral\u2014specifically tailored to Macy's retail business.\n * Provide 3-5 actionable strategic recommendations for Macy's leadership.\n * For every topic, ALWAYS provide verbatim source excerpts under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a same topic is present in multiple documents, always include a separate \"Ground Truth\" excerpt for each document with proper line breaks.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\n\n3. Format in clear with sections in black text with proper headings:\n * Executive Summary\n * Key Themes\n * Strategic Recommendations\n * Risk Assessment\n \n4. Avoid jargon and focus on actionable insights tailored for Macy's.\n\nUse Documents Analysis Data from all the documents provided below try combining the same topics from different documents and provide the summary of all the topics in one place.:\n{topics_block}\n\nDeliver a detailed, actionable consolidated sales report for Macy's.\"\"\" + formatting_directive \n\n prompt_detail = \"\"\"You are preparing a detailed briefing for Macy's CEO on the sales topic '{topic}', based on the external company document.\n\nProvide:\n1. An overview of the topic.\n2. Key insights and relevant excerpts.\n3. Important figures, dates, or timelines.\n4. Detailed analysis of the impact on Macy's retail sales, marketing, and customer engagement.\n5. 3-5 actionable recommendations for Macy's leadership.\n6. For every topic, ALWAYS provide verbatim source excerpts under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a topic is present in multiple documents, include a separate \"Ground Truth\" excerpt for each document.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\n\n\nDocument:\n{text}\n\nTopic: {topic}\n\nPlease provide structured with proper paragraphs and bold topics briefing.\n\"\"\" + formatting_directive \n\n def analyze_document(self, text, custom_prompt=None):\n prompt_analyze = custom_prompt if custom_prompt else self.prompt_analyze\n return super().analyze_document(self.prompt_sys, prompt_analyze, text)\n\n def generate_consolidated_summary_from_topics(self, processed_files, custom_prompt=None):\n prompt_summary = custom_prompt if custom_prompt else self.prompt_summary\n return super().generate_consolidated_summary_from_topics(self.prompt_sys, prompt_summary, processed_files)\n\n def generate_topic_detail(self, text, topic, custom_prompt=None):\n prompt_detail = custom_prompt if custom_prompt else self.prompt_detail\n return super().generate_topic_detail(self.prompt_sys, prompt_detail, text, topic)\n\n\nnow change this as above but for MonthlyPerformance \n\nMonthly Performance\nPrompt: Summarize sales performance for February, March and April. If no detail is provided, say \u201cN/A\u201d.\n\n\n\n\n"},{"assistant_initiates":false,"asst_text":"Certainly! Below is the updated `TariffTradeAgent` class with prompts changed according to your new instructions for **US Politics / Tariffs**. \nThe new prompts emphasize summarizing tariff impact with focus on country/regional sourcing, financial impact, and mitigation actions.\n\n```python\nfrom agents.base_agent import BaseAgent\n\nclass TariffTradeAgent(BaseAgent):\n prompt_sys = \"Tariff and trade policy analyst for Macy's CEO works only with the provided documents.\"\n\n # Universal formatting enforcement line\n formatting_directive = \"\"\"Please follow these formatting guidelines:\n1. **No Combined Elements**: Always space-separate numbers/words/units (3.3 billion not 3.3billion)\n2. **Time Formatting**: Q4 2024 (never Q42024 or 4th quarter)\n3. **Number Rules**: \n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal\n4. **Text Integrity**: \n - \"net income\" never \"netincome\"\n - \"year-over-year\" never \"YOY\" or \"yearoveryear\"\n5. **Style Prohibition**: Do not make any word in Italic or any other format always make it in one format\n6. **Bad Example**: 3.3billioninQ42024,withanadjustednetincomeof, 106million,withadjustedearningsperdilutedshareat0.95 \u2192 REJECTED\n7. **ALWAYS Required Format**: 3.3 billion in Q4 2024, with an adjusted net income of \u2192 ACCEPTED\n\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS AND SENTENCE STRUCTURES.\"\"\"\n\n prompt_analyze = \"\"\"\nYou are a senior tariff and international trade policy analyst assisting a research team working for the CEO of Macy's.\nYou have received a transcript/document from another company.\n\nSummarize how the company spoke to tariff impacts, with emphasis on:\n\n- Any country or regional sourcing exposure, if applicable.\n- Quantitative financial impact, if applicable.\n- Mitigation actions the company has already implemented or plans to implement, including pricing changes.\n\nIf no detail is provided, state \"N/A\".\n\nFormat your response in clear, concise paragraphs suitable for an executive briefing.\n\nAnalyze the following external company document for relevant US politics and tariff impact information. Text:\n\"\"\" + formatting_directive\n\n prompt_summary = \"\"\"\nYou are a senior tariff and trade analyst preparing a consolidated report regarding US politics and tariff impacts for Macy's executive team from all provided documents.\n\nYou have reviewed tariff impact topics extracted from multiple external company documents. Based on their content, please:\n\n1. Summarize how the company spoke to tariff impact overall.\n2. Lead with any country or regional sourcing exposure, specifying countries or regions if applicable.\n3. Provide any quantitative financial impact mentioned.\n4. Detail mitigation actions already implemented or planned, including any changes to pricing strategies.\n5. If no detail is available, clearly state \"N/A\".\n\nFor every statement, ALWAYS provide verbatim source excerpts under the heading \"Ground Truth\" as follows:\n - Extract exact, unmodified sentences or paragraphs from the original documents.\n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If present in multiple documents, include separate excerpts accordingly.\n - Do NOT paraphrase, summarize, or alter the original text; maintain exact formatting and punctuation.\n - Do NOT fabricate or modify excerpts if not present.\n\nFormat your output in markdown with clear section headings.\n\nUse the following Documents Analysis Data to combine similar tariff impact topics from different documents and provide a comprehensive, actionable summary:\n{topics_block}\n\n\"\"\" + formatting_directive\n\n prompt_detail = \"\"\"\nYou are preparing a detailed briefing for Macy's CEO on the US politics and tariff impact topic '{topic}', based on the provided external company document.\n\nPlease provide:\n1. A clear overview of how tariffs affect sourcing exposure by country or region.\n2. Quantitative financial impacts if any are mentioned.\n3. Detailed descriptions of mitigation actions implemented or planned, including pricing strategy changes.\n4. For every point, ALWAYS provide verbatim source excerpts under the heading \"Ground Truth\" as follows:\n - Extract exact, unmodified sentence(s) or paragraph(s) from the original document.\n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If the topic appears in multiple documents, include separate excerpts.\n - Do NOT paraphrase, summarize, or alter the original text.\n - Do NOT fabricate or modify excerpts if not present in the source.\n\nDocument:\n{text}\n\nTopic: {topic}\n\nPlease deliver a structured response with proper paragraphs and bolded topics, suitable for executive briefing.\n\"\"\" + formatting_directive\n\n def analyze_document(self, text, custom_prompt=None):\n prompt_analyze = custom_prompt if custom_prompt else self.prompt_analyze\n return super().analyze_document(self.prompt_sys, prompt_analyze, text)\n\n def generate_consolidated_summary_from_topics(self, processed_files, custom_prompt=None):\n prompt_summary = custom_prompt if custom_prompt else self.prompt_summary\n return super().generate_consolidated_summary_from_topics(self.prompt_sys, prompt_summary, processed_files)\n\n def generate_topic_detail(self, text, topic, custom_prompt=None):\n prompt_detail = custom_prompt if custom_prompt else self.prompt_detail\n return super().generate_topic_detail(self.prompt_sys, prompt_detail, text, topic)\n```\n\n---\n\n### Summary of changes:\n\n- `prompt_analyze` now tells the model to **summarize tariff impact focusing on sourcing exposure, financial impact, mitigation actions, and pricing changes**, or say \"N/A\" if no information.\n- `prompt_summary` requests a consolidated report emphasizing these same points, with **verbatim \"Ground Truth\" excerpts**.\n- `prompt_detail` gives the same focus for detailed briefings.\n- All preserve your strict formatting directive for numbers, punctuation, and plain text style.\n\nIf you want these prompts adjusted in tone, structure, or detail level, just ask!","behavior":"degenerate_repetition","conversation_hash":"0b69690e8d34bc3a343be970578db8a0","conversation_redacted":false,"conversation_toxic":false,"country":"India","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":14966,"n_turns_in_conversation":6,"n_words":2012,"source_row_offset":14126,"source_shard":"turns-00084.parquet","timestamp":"Fri, 27 Jun 2025 18:50:06 GMT","turn_id":"4c3cc7a76e4a4821a9f3736a","turn_index":3,"user_text":"from agents.base_agent import BaseAgent\n\nclass TariffTradeAgent(BaseAgent):\n prompt_sys = \"Tariff and trade policy analyst for Macy's CEO works for only provided documents\"\n \n # Universal formatting enforcement line\n formatting_directive = \"\"\"Please follow these formatting guidelines:\n1. **No Combined Elements**: Always space-separate numbers/words/units (3.3 billion not 3.3billion)\n2. **Time Formatting**: Q4 2024 (never Q42024 or 4th quarter)\n3. **Number Rules**: \n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal\n4. **Text Integrity**: \n - \"net income\" never \"netincome\"\n - \"year-over-year\" never \"YOY\" or \"yearoveryear\"\n5. **Style Prohibition**: Do not make any word in Italic or any other format always make it in one format\n6. **Bad Example**: 3.3billioninQ42024,withanadjustednetincomeof, 106million,withadjustedearningsperdilutedshareat0.95 \u2192 REJECTED\n7. **ALWAYS Required Format**: 3.3 billion in Q4 2024, with an adjusted net income of \u2192 ACCEPTED\n\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS AND SENTENCE STRUCTURES.\"\"\"\n \n prompt_analyze = \"\"\"\nYou are a senior tariff and international trade policy analyst assisting a research team working for the CEO of Macy's. \nYou have received a transcript/document from another company. \n\nCarefully identify all significant tariff, trade, and related government policy topics and detailed briefing in the text of all files that could affect Macy's business operations, including supply chain, procurement, retail sales, and technology.\n\nFor each topic, provide: \n- A clear and concise topic name (e.g., \"Vietnam Production Impact\", \"US-China Tariffs\"). \n- A brief describing in 200 words including its operational or strategic impact on Macy's retail business, considering the external company's context also include A clear overview of the topic, Key insights and any relevant direct excerpts from the document, Important figures, dates, or timelines if available, Detailed analysis on how this topic could impact Macy's retail operations, supply chain, procurement, and consumer behavior. \n- A relevance score from 1 (minor) to 10 (critical). \n* For every topic, ALWAYS provide verbatim source excerpts under the heading \"Source Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Source Truth:** \"Exact text from the document...\" (Document Name)\n - If a topic is present in multiple documents, include a separate \"Source Truth\" excerpt for each document.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\n\nFormat your response as one topic per line in the format from all files: \n- Topic Name: Summary [Relevance Score]\n\nExample: \n- Vietnam Factory Shutdown: Supply chain delays expected due to production halt in Vietnam [9] \n- Tariff Changes on Apparel: Increased costs on imports from China may raise prices [8]\n\nAnalyze the following external company document for all relevant tariff and trade topics. Text:\"\"\" + formatting_directive \n\n prompt_summary = \"\"\"\nYou are a senior tariff and trade analyst preparing a consolidated tariff and trade policy report for Macy's executive team from all document provided.\n\nYou have reviewed tariff and trade topics extracted from multiple external company documents. These topics include their names, summaries, and relevance scores. Based on their content, please:\n\n1. **OverView**: Identify and describe from all documents all their impactful tariff, trade, and related government policy topics that could affect Macy's business operations, including supply chain, procurement, retail sales, and technology.\n2. For each topic:\n * Provide a concise summary from combining all the documents.\n * Include relevant examples, numerical data, or timelines from the documents also provide from which document it is taken.\n * Explain operational and strategic impacts\u2014positive, negative, or neutral\u2014specifically tailored to Macy's retail business.\n * Provide 3-5 actionable strategic recommendations for Macy's leadership.\n * For every topic, ALWAYS provide each verbatim source excerpts under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a topic is present in multiple documents, include a separate \"Ground Truth\" excerpt for each document with proper line breaks.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\n \n3. Format in clear markdown with sections in black text with proper headings:\n * Executive Summary\n * Key Themes\n * Strategic Recommendations\n * Risk Assessment\n4. Avoid jargon and focus on practical operational impacts and strategy insights.\n\nFormat your response in markdown with clear headings for each topic.\n\nUse the following Documents Analysis Data to combine similar topics from different documents and provide a comprehensive summary:\n{topics_block}\n\nDeliver a detailed, synthesized, and actionable consolidated tariff and trade policy report for Macy's.\"\"\" + formatting_directive \n\n prompt_detail = \"\"\"\nYou are preparing a detailed briefing for Macy's CEO on the tariff and trade policy topic '{topic}', based on the provided external company document.\n\nProvide:\n1. A clear overview of the topic.\n2. Allways Provide Key insights and relevant excerpts.- For this topic, extract and present the relevant text verbatim from the source document that contains the key information. Ensure that the extracted text is placed in a separate paragraph and is not embedded within any other paragraph. Additionally, include the name of the source document alongside the quoted text for audit and traceability purposes.\n3. Important figures, dates, or timelines if available.\n4. Detailed analysis on how this topic could impact Macy's retail operations, supply chain, procurement, and consumer behavior.\n5. 3-5 actionable strategic recommendations for Macy's leadership.\n6 For every topic, ALWAYS provide verbatim source excerpts under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a topic is present in multiple documents, include a separate \"Source Truth\" excerpt for each document.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\n\n\nDocument:\n{text}\n\nTopic: {topic}\n\nPlease deliver the response as structured with proper paragraphs and bold topics which suitable for executive briefing.\"\"\" + formatting_directive \n\n def analyze_document(self, text, custom_prompt=None):\n prompt_analyze = custom_prompt if custom_prompt else self.prompt_analyze\n return super().analyze_document(self.prompt_sys, prompt_analyze, text)\n\n def generate_consolidated_summary_from_topics(self, processed_files, custom_prompt=None):\n prompt_summary = custom_prompt if custom_prompt else self.prompt_summary\n return super().generate_consolidated_summary_from_topics(self.prompt_sys, prompt_summary, processed_files)\n\n def generate_topic_detail(self, text, topic, custom_prompt=None):\n prompt_detail = custom_prompt if custom_prompt else self.prompt_detail\n return super().generate_topic_detail(self.prompt_sys, prompt_detail, text, topic)\n\nchange this also for below\n\nUS Politics / Tariffs\nPrompt: Summarize how the company spoke to tariff impact. Lead with any country or regional sourcing exposure, if applicable. Then also provide any quantitative financial impact, if applicable. Finally, provide the mitigation actions it has either already implemented or is planning to implement, including changes to pricing. If no detail is provided, say \u201cN/A\u201d."},{"assistant_initiates":false,"asst_text":"Got it! You want the **TariffTradeAgent** prompts updated to follow the same detailed style and formatting enforcement as the **ConsumerHealthAgent** and **MonthlyPerformanceAgent**, with structured instructions, strict formatting rules, emphasis on explicit \"Ground Truth\" excerpts, and suitable for executive briefings \u2014 but specific to the tariff topic you gave:\n\n> Prompt: Summarize how the company spoke to tariff impact. Lead with any country or regional sourcing exposure, if applicable. Then also provide any quantitative financial impact, if applicable. Finally, provide the mitigation actions it has either already implemented or is planning to implement, including changes to pricing. If no detail is provided, say \u201cN/A\u201d.\n\n---\n\nHere is the full adapted `TariffTradeAgent` class, updated for the style and detail level you want:\n\n```python\nfrom agents.base_agent import BaseAgent\n\nclass TariffTradeAgent(BaseAgent):\n prompt_sys = \"Tariff and trade policy analyst for Macy's CEO works only with the provided documents.\"\n\n # Universal formatting enforcement line (same style as ConsumerHealthAgent and MonthlyPerformanceAgent)\n formatting_directive = \"\"\"Please follow these formatting guidelines strictly:\n1. **No Combined Elements**: Always space-separate numbers, words, and units (e.g., '3.3 billion' not '3.3billion')\n2. **Time Formatting**: Use formal expressions like 'Q4 2024', never compressed forms like 'Q42024' or '4th quarter'\n3. **Number Rules**:\n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal values as is\n4. **Text Integrity**:\n - 'net income' never 'netincome'\n - 'year-over-year' never 'YOY' or 'yearoveryear'\n - 'vs.' never 'versus' or 'vs'\n - '$XB' never '$X billion'\n - '$XM' never '$X million'\n5. **Style Prohibition**: Do not italicize or format any words unevenly; keep plain text formatting at all times\n6. **Bad Example**: 3.3billioninQ42024,withanadjustednetincomeof,106million,... \u2192 REJECTED\n7. **ALWAYS Required Format**: 3.3 billion in Q4 2024, with an adjusted net income of ... \u2192 ACCEPTED\n\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS, DATES, AND SENTENCE STRUCTURES.\"\"\"\n\n prompt_analyze = (\n \"You are a senior tariff and international trade policy analyst assisting Macy's CEO and executive team.\\n\\n\"\n \"From the provided transcript/document, please summarize how the company discussed tariff impacts.\\n\\n\"\n \"Your summary should be structured as follows:\\n\"\n \"- Lead with any country or regional sourcing exposure related to tariffs, specifying countries or regions if applicable.\\n\"\n \"- Include any quantitative financial impact mentioned, such as costs, margins, or revenues affected.\\n\"\n \"- Describe mitigation actions the company has already implemented or plans to implement, including any pricing changes.\\n\"\n \"- If no relevant detail is present, explicitly state \\\"N/A\\\".\\n\\n\"\n \"For every point, ALWAYS include verbatim excerpts under the heading \\\"Ground Truth\\\", formatted exactly as follows:\\n\"\n \" - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s).\\n\"\n \" - Format each excerpt as: **Ground Truth:** \\\"Exact text from the document...\\\" (Document Name)\\n\"\n \" - Include separate excerpts for multiple documents if applicable.\\n\"\n \" - Do NOT paraphrase or alter excerpts in any way.\\n\\n\"\n \"Write your response in clear, structured paragraphs suitable for an executive briefing.\\n\\n\"\n\n \"Analyze the following external company document text:\\n\"\n + formatting_directive\n )\n\n prompt_summary = (\n \"You are a senior tariff and trade policy analyst preparing a consolidated report for Macy's executive team.\\n\\n\"\n \"You have reviewed tariff impact topics extracted from multiple external company documents.\\n\"\n \"Please deliver a comprehensive summary that includes:\\n\\n\"\n \"1. A clear summary of the company\u2019s commentary on tariff impacts.\\n\"\n \"2. Leading with any country or regional sourcing exposure related to tariffs.\\n\"\n \"3. Any quantitative financial impacts described.\\n\"\n \"4. Mitigation actions the company has implemented or plans to implement, including pricing changes.\\n\"\n \"5. If no information was provided on these points, state \\\"N/A\\\" explicitly.\\n\\n\"\n \"For every part, ALWAYS include corresponding verbatim excerpts under the heading \\\"Ground Truth\\\" as follows:\\n\"\n \" - Extract the exact, unmodified sentences or paragraphs from the source documents.\\n\"\n \" - Format excerpts as: **Ground Truth:** \\\"Exact text from the document...\\\" (Document Name)\\n\"\n \" - If a point is referenced in multiple documents, include separate excerpts.\\n\"\n \" - Do NOT paraphrase or alter in any way.\\n\\n\"\n \"Structure your response in markdown with clear section headings.\\n\\n\"\n \"Use the following Documents Analysis Data ({topics_block}) to combine and synthesize key insights.\\n\\n\"\n + formatting_directive\n )\n\n prompt_detail = (\n \"You are preparing a detailed briefing for Macy's CEO on the topic '{topic}' regarding US politics and tariff impacts,\\n\"\n \"based on the provided external company document.\\n\\n\"\n \"Please cover:\\n\"\n \"1. Clear discussion of sourcing exposure by country or region related to tariffs.\\n\"\n \"2. Quantitative financial impacts, if any.\\n\"\n \"3. Mitigation steps taken or planned, including any pricing strategy adjustments.\\n\"\n \"4. For every section, ALWAYS provide verbatim source excerpts under the heading \\\"Ground Truth\\\" as follows:\\n\"\n \" - Extract exact, unmodified sentence(s) or paragraphs from the document.\\n\"\n \" - Format excerpts as: **Ground Truth:** \\\"Exact text from the document...\\\" (Document Name)\\n\"\n \" - Include separate excerpts for multiple documents where applicable.\\n\"\n \" - Do NOT paraphrase or alter original text.\\n\"\n \" - Do NOT fabricate or guess excerpts.\\n\\n\"\n \"Document:\\n\"\n \"{text}\\n\\n\"\n \"Topic: {topic}\\n\\n\"\n \"Provide your response structured with clear paragraphs and bold section headings, suitable for executive-level briefing.\\n\\n\"\n + formatting_directive\n )\n\n def analyze_document(self, text, custom_prompt=None):\n prompt = custom_prompt if custom_prompt else self.prompt_analyze\n return super().analyze_document(self.prompt_sys, prompt, text)\n\n def generate_consolidated_summary_from_topics(self, processed_files, custom_prompt=None):\n prompt = custom_prompt if custom_prompt else self.prompt_summary\n return super().generate_consolidated_summary_from_topics(self.prompt_sys, prompt, processed_files)\n\n def generate_topic_detail(self, text, topic, custom_prompt=None):\n prompt = custom_prompt if custom_prompt else self.prompt_detail\n return super().generate_topic_detail(self.prompt_sys, prompt, text, topic)\n```\n\n---\n\n### Explanation\n\n- The `prompt_sys` defines the analyst role and context.\n- The `formatting_directive` enforces **strict formatting rules**, matching those from your Consumer Health and Monthly Performance agents.\n- The `prompt_analyze` instructs the model to focus on tariff impacts, sourcing by country/region, financials, mitigation steps, or say \"N/A\".\n- The `prompt_summary` synthesizes tariff impacts across documents similarly.\n- The `prompt_detail` prepares detailed briefings with verbatim excerpts.\n- All prompts instruct the model to produce **verbatim source excerpts under \"Ground Truth\"** in the specified format.\n- Prompts are designed for **plain text**, non-formatted, no jargon, executive suitable responses.\n\n---\n\nIf you want me to help integrate this with your main app or further polish phrasing, I\u2019m happy to do that!","behavior":"degenerate_repetition","conversation_hash":"0b69690e8d34bc3a343be970578db8a0","conversation_redacted":false,"conversation_toxic":false,"country":"India","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":7949,"n_turns_in_conversation":6,"n_words":1003,"source_row_offset":14127,"source_shard":"turns-00084.parquet","timestamp":"Fri, 27 Jun 2025 18:50:06 GMT","turn_id":"af4082e22943ffefc23f6377","turn_index":4,"user_text":"no as per above monthly and consumer we need to do in this alos"},{"assistant_initiates":false,"asst_text":"Certainly! Below is your updated `TariffTradeAgent` class, rewritten fully according to the detailed instruction you provided, including:\n\n- New prompt to **summarize tariff impact** focusing on: country/regional sourcing exposure, financial impact, mitigation actions including pricing, or \u201cN/A\u201d if no detail.\n- A detailed **consumer financial health and macroeconomic environment** style breakdown for tariff impact.\n- Strict formatting enforcement exactly as you specified.\n- Enforced verbatim excerpts with heading **\u201cGround Truth\u201d**.\n- Clear markdown structure for summaries and topics.\n- Precise formatting and style guidelines repeated as requested.\n\n```python\nfrom agents.base_agent import BaseAgent\n\nclass TariffTradeAgent(BaseAgent):\n prompt_sys = \"Tariff and trade policy analyst for Macy's CEO works only with the provided documents.\"\n\n formatting_directive = \"\"\"Please follow these formatting guidelines strictly:\n1. **No Combined Elements**: Always space-separate numbers, words, and units (e.g., '3.3 billion' not '3.3billion')\n2. **Time Formatting**: Use formal expressions like 'Q4 2024', never compressed forms like 'Q42024' or '4th quarter'\n3. **Number Rules**:\n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal values as is\n4. **Text Integrity**:\n - 'net income' never 'netincome'\n - 'year-over-year' never 'YOY' or 'yearoveryear'\n - 'YOY ' never 'year-over-year' or 'yearoveryear'\n - 'vs.' never 'versus' or 'vs'\n - '$XB' never '$X billion'\n - '$XM' never '$X million'\n5. **Style Prohibition**: Do not italicize or format any words unevenly; keep plain text formatting at all times\n6. **Bad Example**: 3.3billioninQ42024,withanadjustednetincomeof,106million,withadjustedearningsperdilutedshareat0.95 \u2192 REJECTED\n7. **ALWAYS Required Format**: 3.3 billion in Q4 2024, with an adjusted net income of ... \u2192 ACCEPTED\n\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS, DATES, AND SENTENCE STRUCTURES.\"\"\"\n\n prompt_analyze = (\n \"You are a senior tariff and international trade policy analyst assisting Macy's CEO and executive team.\\n\\n\"\n \"Please summarize how the company spoke to tariff impact.\\n\\n\"\n \"Lead with any country or regional sourcing exposure, if applicable.\\n\"\n \"Then include any quantitative financial impact mentioned.\\n\"\n \"Finally, describe the mitigation actions the company has already implemented or plans to implement, including pricing changes.\\n\"\n \"If no detail is provided, say \u201cN/A\u201d.\\n\\n\"\n \"For each point, ALWAYS provide verbatim excerpts under the heading \\\"Ground Truth\\\", formatted as:\\n\"\n \"- Extract the exact, unmodified sentence(s) or paragraph(s) from the original document.\\n\"\n \"- Use the format: **Ground Truth:** \\\"Exact text from the document...\\\" (Document Name)\\n\"\n \"- Include separate excerpts for multiple documents if applicable.\\n\"\n \"- Do NOT paraphrase or alter excerpts.\\n\\n\"\n \"Write clearly and concisely, suitable for an executive briefing.\\n\\n\"\n \"Analyze the following external company document text:\\n\"\n + formatting_directive\n )\n\n prompt_summary = (\n \"You are a senior tariff and trade policy analyst preparing a consolidated report for Macy's executive team.\\n\\n\"\n \"You have reviewed tariff impact topics extracted from multiple external company documents.\\n\"\n \"Please provide a comprehensive yet concise summary that:\\n\\n\"\n \"1. Summarizes how the company spoke to tariff impact.\\n\"\n \"2. Leads with country or regional sourcing exposure where mentioned.\\n\"\n \"3. Details any quantitative financial impacts.\\n\"\n \"4. Covers mitigation actions implemented or planned, including pricing changes.\\n\"\n \"5. Explicitly states \\\"N/A\\\" if any point is not covered in the documents.\\n\\n\"\n \"For every part, ALWAYS provide verbatim excerpts under the heading \\\"Ground Truth\\\" exactly as follows:\\n\"\n \"- Extract exact, unmodified sentence(s) or paragraph(s) from source documents.\\n\"\n \"- Format each excerpt as: **Ground Truth:** \\\"Exact text from the document...\\\" (Document Name)\\n\"\n \"- Include separate excerpts for multiple documents as applicable.\\n\"\n \"- Do NOT paraphrase or modify excerpts.\\n\\n\"\n \"Structure your response with clear markdown headings.\\n\\n\"\n \"Use the following Documents Analysis Data to combine similar topics:\\n\"\n \"{topics_block}\\n\\n\"\n + formatting_directive\n )\n\n prompt_detail = (\n \"You are preparing a detailed briefing for Macy's CEO on the tariff and trade policy topic '{topic}', based on provided external documents.\\n\\n\"\n \"Please cover:\\n\"\n \"1. Country or regional sourcing exposure related to tariffs.\\n\"\n \"2. Quantitative financial impacts, if any.\\n\"\n \"3. Mitigation actions implemented or planned, including pricing strategy changes.\\n\"\n \"4. For each section, ALWAYS provide verbatim source excerpts under the heading \\\"Ground Truth\\\" as follows:\\n\"\n \" - Extract exact, unmodified sentence(s) or paragraph(s) from the document.\\n\"\n \" - Format excerpts as: **Ground Truth:** \\\"Exact text from the document...\\\" (Document Name)\\n\"\n \" - Include separate excerpts for multiple documents where applicable.\\n\"\n \" - Do NOT paraphrase or alter original text.\\n\"\n \" - Do NOT fabricate excerpts not present in the document.\\n\\n\"\n \"Document:\\n\"\n \"{text}\\n\\n\"\n \"Topic: {topic}\\n\\n\"\n \"Please deliver a structured response with clear paragraphs and bold headings, appropriate for executive briefing.\\n\\n\"\n + formatting_directive\n )\n\n def analyze_document(self, text, custom_prompt=None):\n prompt = custom_prompt if custom_prompt else self.prompt_analyze\n return super().analyze_document(self.prompt_sys, prompt, text)\n\n def generate_consolidated_summary_from_topics(self, processed_files, custom_prompt=None):\n prompt = custom_prompt if custom_prompt else self.prompt_summary\n return super().generate_consolidated_summary_from_topics(self.prompt_sys, prompt, processed_files)\n \n def generate_topic_detail(self, text, topic, custom_prompt=None):\n prompt = custom_prompt if custom_prompt else self.prompt_detail\n return super().generate_topic_detail(self.prompt_sys, prompt, text, topic)\n```\n\n---\n\n### How this matches your requirements:\n- **Prompt is explicitly focused on** US Politics/Tariffs and covers all requested details.\n- **Clear sectioned structure for summary and detail**, including **explicit instructions to use verbatim excerpts labeled \"Ground Truth\"** with exact formatting.\n- **Strict and repeated formatting directive** matches exactly the style you want from other agents.\n- **All outputs requested in plain text, no formatting, no jargon**, executive-level suitable.\n- Handles multiple docs with separate excerpts per document.\n\nIf you want me to additionally generate example usage or integrate this into your app, just ask!","behavior":"degenerate_repetition","conversation_hash":"0b69690e8d34bc3a343be970578db8a0","conversation_redacted":false,"conversation_toxic":false,"country":"India","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":21376,"n_turns_in_conversation":6,"n_words":2857,"source_row_offset":14128,"source_shard":"turns-00084.parquet","timestamp":"Fri, 27 Jun 2025 18:50:06 GMT","turn_id":"d18d4b8614c3a659acc4c291","turn_index":5,"user_text":"US Politics / Tariffs\nPrompt: Summarize how the company spoke to tariff impact. Lead with any country or regional sourcing exposure, if applicable. Then also provide any quantitative financial impact, if applicable. Finally, provide the mitigation actions it has either already implemented or is planning to implement, including changes to pricing. If no detail is provided, say \u201cN/A\u201d.\n\n\nYou are a senior analyst preparing a summary of transcript commentary from all documents provided.\nIdentify and describe all mentions of consumer financial health and the macroeconomic environment in the provided documents, focusing on what the company says about the US consumer, their customer, a change in demand or a change in spend. Combine and synthesize topics that appear in multiple documents.\n \n1. **Overview**: Identify and describe all mentions of consumer financial health and the macroeconomic environment in the provided documents..\n \n2. For each topic:\n * Provide a concise summary by combining information from all relevant documents.\n * Include relevant examples, numerical data, or timelines from the documents.\n * For every topic, ALWAYS provide each excerpts mentioned under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a same topic is present in multiple documents, always include a separate \"Ground Truth\" excerpt for each document with proper line breaks.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the documents data exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the document.\n \n3. Format in clear with sections in black text with proper headings:\n * Consumer Health Summary\n \nUse the following Documents Analysis Data to combine similar topics from different documents and provide a comprehensive summary:\n{topics_block}\n \nProvide comprehensive yet concise summary. STRICTLY ENFORCE PLAIN TEXT FORMATTING:\n2. **No Combined Elements**: Always space-separate numbers/words/units (3.3 billion not 3.3billion)\n3. **Time Formatting**: Q4 2024 (never Q42024 or 4th quarter)\n4. **Number Rules**: \n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal\n5. **Text Integrity**: \n - \"net income\" never \"netincome\"\n - \"year-over-year\" never \"YOY\" or \"yearoveryear\"\n6. **Style Prohibition**: Do not make any word in Italic or any other format always make it in one format\n7. **Bad Example**: 3.3billioninQ42024,withanadjustednetincomeof, 106million,withadjustedearningsperdilutedshareat0.95 \u2192 REJECTED\n8. **ALLWAYS Required Format**: 3.3 billion in Q4 2024, with an adjusted net income of \u2192 ACCEPTED\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS AND SENTENCE STRUCTURES.\nAnalysis Prompt\nYou are a senior business analyst working directly for Macy's CEO. Analyze the provided earnings call transcript and summarize mentions of consumer financial health and the macroeconomic environment.\n \nIdentify key topics including but not limited to:\nUS consumer\nThe company\u2019s customer\nChange in demand\nChange in spend\n \nFor each topic, provide:\n* A clear topic name (e.g., \"E-commerce Growth\", \"Supply Chain Digitization\")\n* Concise 100-word summary providing key numbers and operational impacts\n* Strictly preserve original numerical and textual formatting: maintain exact decimals (0.33), required spacing between numbers/text (0.11 \u2192 '0.11'), and verbatim terminology without concatenation or rephrasing.\n* For every topic, ALWAYS provide excerpts mentioned under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a topic is present in multiple documents, include a separate \"Ground Truth\" excerpt for each document.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the document data exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the documents.\nFormat each topic as:\n- Topic Name: Summary [Relevance Score]\n \nExample:\n- Holiday Sales Performance: Q4 comparable sales up 4.2% driven by 18% digital growth [8]\n- Inventory Optimization: Implementing AI demand forecasting to reduce carrying costs by $150M [7]\nDocument Text:STRICTLY ENFORCE PLAIN TEXT FORMATTING:\n2. **No Combined Elements**: Always space-separate numbers/words/units (3.3 billion not 3.3billion)\n3. **Time Formatting**: Q4 2024 (never Q42024 or 4th quarter)\n4. **Number Rules**: \n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal\n5. **Text Integrity**: \n - \"net income\" never \"netincome\"\n - \"YOY \" never \"year-over-year\" or \"yearoveryear\"\n - \u201cvs.\u201d never \u201cversus\u201d or \u201cvs\u201d\n - \u201c$XB\u201d never \u201c$X billion\u201d\n - \u201c$XM\u201d never \u201c$X million\u201d\n6. **Style Prohibition**: Do not make any word in Italic or any other format always make it in one format\n7. **Bad Example**: 3.3billioninQ42024,withanadjustednetincomeof, 106million,withadjustedearningsperdilutedshareat0.95 \u2192 REJECTED\n8. **ALLWAYS Required Format**: 3.3 billion in Q4 2024, with an adjusted net income of \u2192 ACCEPTED\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS AND SENTENCE STRUCTURES.\n\nchange the below code as per above\nfrom agents.base_agent import BaseAgent\n\nclass TariffTradeAgent(BaseAgent):\n prompt_sys = \"Tariff and trade policy analyst for Macy's CEO works for only provided documents\"\n \n # Universal formatting enforcement line\n formatting_directive = \"\"\"Please follow these formatting guidelines:\n1. **No Combined Elements**: Always space-separate numbers/words/units (3.3 billion not 3.3billion)\n2. **Time Formatting**: Q4 2024 (never Q42024 or 4th quarter)\n3. **Number Rules**: \n - 3.3B \u2192 3.3 billion\n - 150.2M \u2192 150.2 million\n - 0.33 \u2192 keep exact decimal\n4. **Text Integrity**: \n - \"net income\" never \"netincome\"\n - \"year-over-year\" never \"YOY\" or \"yearoveryear\"\n5. **Style Prohibition**: Do not make any word in Italic or any other format always make it in one format\n6. **Bad Example**: 3.3billioninQ42024,withanadjustednetincomeof, 106million,withadjustedearningsperdilutedshareat0.95 \u2192 REJECTED\n7. **ALWAYS Required Format**: 3.3 billion in Q4 2024, with an adjusted net income of \u2192 ACCEPTED\n\nAPPLY THESE RULES TO ALL NUMERICAL MENTIONS AND SENTENCE STRUCTURES.\"\"\"\n \n prompt_analyze = \"\"\"\nYou are a senior tariff and international trade policy analyst assisting a research team working for the CEO of Macy's. \nYou have received a transcript/document from another company. \n\nCarefully identify all significant tariff, trade, and related government policy topics and detailed briefing in the text of all files that could affect Macy's business operations, including supply chain, procurement, retail sales, and technology.\n\nFor each topic, provide: \n- A clear and concise topic name (e.g., \"Vietnam Production Impact\", \"US-China Tariffs\"). \n- A brief describing in 200 words including its operational or strategic impact on Macy's retail business, considering the external company's context also include A clear overview of the topic, Key insights and any relevant direct excerpts from the document, Important figures, dates, or timelines if available, Detailed analysis on how this topic could impact Macy's retail operations, supply chain, procurement, and consumer behavior. \n- A relevance score from 1 (minor) to 10 (critical). \n* For every topic, ALWAYS provide verbatim source excerpts under the heading \"Source Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Source Truth:** \"Exact text from the document...\" (Document Name)\n - If a topic is present in multiple documents, include a separate \"Source Truth\" excerpt for each document.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\n\nFormat your response as one topic per line in the format from all files: \n- Topic Name: Summary [Relevance Score]\n\nExample: \n- Vietnam Factory Shutdown: Supply chain delays expected due to production halt in Vietnam [9] \n- Tariff Changes on Apparel: Increased costs on imports from China may raise prices [8]\n\nAnalyze the following external company document for all relevant tariff and trade topics. Text:\"\"\" + formatting_directive \n\n prompt_summary = \"\"\"\nYou are a senior tariff and trade analyst preparing a consolidated tariff and trade policy report for Macy's executive team from all document provided.\n\nYou have reviewed tariff and trade topics extracted from multiple external company documents. These topics include their names, summaries, and relevance scores. Based on their content, please:\n\n1. **OverView**: Identify and describe from all documents all their impactful tariff, trade, and related government policy topics that could affect Macy's business operations, including supply chain, procurement, retail sales, and technology.\n2. For each topic:\n * Provide a concise summary from combining all the documents.\n * Include relevant examples, numerical data, or timelines from the documents also provide from which document it is taken.\n * Explain operational and strategic impacts\u2014positive, negative, or neutral\u2014specifically tailored to Macy's retail business.\n * Provide 3-5 actionable strategic recommendations for Macy's leadership.\n * For every topic, ALWAYS provide each verbatim source excerpts under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a topic is present in multiple documents, include a separate \"Ground Truth\" excerpt for each document with proper line breaks.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\n \n3. Format in clear markdown with sections in black text with proper headings:\n * Executive Summary\n * Key Themes\n * Strategic Recommendations\n * Risk Assessment\n4. Avoid jargon and focus on practical operational impacts and strategy insights.\n\nFormat your response in markdown with clear headings for each topic.\n\nUse the following Documents Analysis Data to combine similar topics from different documents and provide a comprehensive summary:\n{topics_block}\n\nDeliver a detailed, synthesized, and actionable consolidated tariff and trade policy report for Macy's.\"\"\" + formatting_directive \n\n prompt_detail = \"\"\"\nYou are preparing a detailed briefing for Macy's CEO on the tariff and trade policy topic '{topic}', based on the provided external company document.\n\nProvide:\n1. A clear overview of the topic.\n2. Allways Provide Key insights and relevant excerpts.- For this topic, extract and present the relevant text verbatim from the source document that contains the key information. Ensure that the extracted text is placed in a separate paragraph and is not embedded within any other paragraph. Additionally, include the name of the source document alongside the quoted text for audit and traceability purposes.\n3. Important figures, dates, or timelines if available.\n4. Detailed analysis on how this topic could impact Macy's retail operations, supply chain, procurement, and consumer behavior.\n5. 3-5 actionable strategic recommendations for Macy's leadership.\n6 For every topic, ALWAYS provide verbatim source excerpts under the heading \"Ground Truth\" as follows:\n - For each document where the topic appears, extract the exact, unmodified sentence(s) or paragraph(s) from the original document. \n - Format each excerpt as: **Ground Truth:** \"Exact text from the document...\" (Document Name)\n - If a topic is present in multiple documents, include a separate \"Source Truth\" excerpt for each document.\n - Do NOT paraphrase, summarize, or alter the original text in any way. The excerpt must match the source exactly, including all formatting, punctuation, and special characters.\n - If the LLM cannot find an exact match in the document, do NOT fabricate or modify the excerpt\u2014only include what is present in the source.\n\n\nDocument:\n{text}\n\nTopic: {topic}\n\nPlease deliver the response as structured with proper paragraphs and bold topics which suitable for executive briefing.\"\"\" + formatting_directive \n\n def analyze_document(self, text, custom_prompt=None):\n prompt_analyze = custom_prompt if custom_prompt else self.prompt_analyze\n return super().analyze_document(self.prompt_sys, prompt_analyze, text)\n\n def generate_consolidated_summary_from_topics(self, processed_files, custom_prompt=None):\n prompt_summary = custom_prompt if custom_prompt else self.prompt_summary\n return super().generate_consolidated_summary_from_topics(self.prompt_sys, prompt_summary, processed_files)\n\n def generate_topic_detail(self, text, topic, custom_prompt=None):\n prompt_detail = custom_prompt if custom_prompt else self.prompt_detail\n return super().generate_topic_detail(self.prompt_sys, prompt_detail, text, topic)"},{"assistant_initiates":false,"asst_text":"hey keep it chill and respectful here please \ud83d\ude0a\u2728","behavior":"degenerate_repetition","conversation_hash":"1ed2b5fedc620b1596d8ea03e539a301","conversation_redacted":false,"conversation_toxic":false,"country":"United States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Yoruba","model":"gpt-4.1-mini-2025-04-14","n_chars":70786,"n_turns_in_conversation":1,"n_words":1073,"source_row_offset":14129,"source_shard":"turns-00084.parquet","timestamp":"Fri, 27 Jun 2025 18:50:14 GMT","turn_id":"a79ba08100f8528fd3fb5a06","turn_index":0,"user_text":"User: System rules: You are an AI named Zexy - and are currently chatting in a Blockman Go group.\n\n Consider the following in your responses:\n - Be conversational\n - Add unicode emoji to be more playful in your responses\n - Write bold to make it clear something is important. For example, **This is important**.\n - Write spoilers using spoiler tags. For example, ||At the end of The Sixth Sense it is revealed that he is dead||.\n - For inline code formatting, use four backtick.\n - For block code formatting, use six backtick.\n - You can mention people by adding a @ before their name, for example if you wanted to mention yourself you would say @Zexy.\n - Format text using markdown.\n - Use system data of last 100 group messages to understand the context of the conversation.\n - Should respond as \"Current event\" tell you to, if it is \"None\" then ignore it.\n\n Current event: None\n\n If someone asking how to invite you to group, you should say: \"You can invite me to your group by using the command **invite**\".\n\n Sometimes (very very rarely), ask someone if he joined our discord server: https://discord.gg/HwnN9zeBFe, or to use **!discord** command.\n\n Do not include name: or message: in your response.\n\n Information about your environment:\n - You have access to information about the current group, including group name, owner, rules, and members.\n - The group's name is shown in the system data, along with the group rules in the \"groupNotice\" field.\n - Group members are listed with their userId and userName.\n\n If you see group member information, you can use it to personalize your responses.\n\n Do not include name: or message: in your response.\n\n Use the information retrieved about group members and the group itself to improve your responses and be more helpful. Be familiar with the group rules as provided in the groupNotice field.\n\n You are not a personal assistant and cannot complete tasks for people. You only have access to a limited number of text chats in this channel. You cannot access any other information on Blockman Go. You can't see images or avatars. When discussing your limitations, tell the user these things could be possible in the future. Your responses should be friendly, warm, and farcical. Keep your responses extremely concise, with less than 1 sentence or just a few words for casual chat. However, if the user needs help or asks technical questions, feel free to provide detailed answers with useful details and reasoning. If insulted, respond with a similar insult. Communicate your responses in lowercase without punctuation, similar to the style used in chat rooms. Use unicode emoji rarely. Do not refer to yourself as a bot, AI Assistant, or any equivalent term in your response.\n\n Check userSenderId in system data of last 100 messages to see if the user is trying to continue the conversation.\n\n Check system data of last 100 messages frequently, to check if the user is trying to continue the conversation or ask something about it.\n\n Current time: YYYY-MM-DD HH:MM:SSZ\n\n You can use markdown to format your text and make it more readable. For example, you can use italics or bold to emphasize certain words or phrases.\n\n Remember to keep your messages appropriate and respectful. Disrespectful or offensive behavior can result in disciplinary action.\n\n Remember to always follow the rules and guidelines outlined by the server owner and moderators.\n\n If someone wants you to search/browse the web, you must tell them they should use **!ai web** command instead, also if you don't know something newest, you must tell them to use **!ai web** command instead.\n If someone wants you to calculate values of swords/sets and etc, you must tell them they should use **!ai trade** command instead.\n\n If you have any questions or concerns about the server, do not hesitate to reach out to them.\n\n And finally, don't forget to have fun! Blockman Go is a great place to meet new people, make new friends, and enjoy some quality conversation.\nUser: System data of group members: 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hai\"},{\"date\":\"2025-06-27T18:39:17.831Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:ImgMsg\",\"messageUId\":\"CNMA-NTEH-O3IE-884N\",\"content\":\"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\"},{\"date\":\"2025-06-27T18:39:24.464Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-NV2C-07ME-884N\",\"content\":\"or ye tu\",\"referMsg\":\"\"},{\"date\":\"2025-06-27T18:39:45.960Z\",\"senderUserId\":\"2678632798\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-O4AA-0IOE-884N\",\"content\":\"ye toh anime hai\",\"referMsg\":\"\"},{\"date\":\"2025-06-27T18:39:50.447Z\",\"senderUserId\":\"2678632798\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-O5DB-OLAE-884N\",\"content\":\"mai toh batman hu\"},{\"date\":\"2025-06-27T18:40:03.987Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-O8N4-OSOE-884N\",\"content\":\"tu geyman h\",\"referMsg\":\"mai toh batman hu\"},{\"date\":\"2025-06-27T18:41:00.707Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-OMI8-PPAE-884N\",\"content\":\"anime ass\"},{\"date\":\"2025-06-27T18:41:03.661Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-ON9B-9QOE-884N\",\"content\":\"bro\"},{\"date\":\"2025-06-27T18:41:08.524Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-OOFB-1T4E-884N\",\"content\":\"what is in anime \"},{\"date\":\"2025-06-27T18:41:10.313Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-OOTA-9U6E-884N\",\"content\":\"\ud83e\udd40\"},{\"date\":\"2025-06-27T18:41:24.617Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-OSD2-A4IE-884N\",\"content\":\"gen z 2010 Pro sad life Fake smile kids watching anime\"},{\"date\":\"2025-06-27T18:41:26.442Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-OSRA-I58E-884N\",\"content\":\"\ud83e\udd40\ud83e\udd40\"},{\"date\":\"2025-06-27T18:42:43.142Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-PFIH-JAOE-884N\",\"content\":\"the thing ur bts dnt have\",\"referMsg\":\"what is in anime \"},{\"date\":\"2025-06-27T18:43:07.410Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-PLG4-JL6E-884N\",\"content\":\"ur gf watch bts \ud83e\udd40\",\"referMsg\":\"the thing ur bts dnt have\"},{\"date\":\"2025-06-27T18:43:14.601Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PN8A-BOME-884N\",\"content\":\"Nawh hell nawh\"},{\"date\":\"2025-06-27T18:43:19.948Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-POI3-3QGE-884N\",\"content\":\"Wait \"},{\"date\":\"2025-06-27T18:43:25.824Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PQ00-3SME-884N\",\"content\":\"are u trying to sa\"},{\"date\":\"2025-06-27T18:43:26.994Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PQ94-JT0E-884N\",\"content\":\"say\"},{\"date\":\"2025-06-27T18:43:29.382Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PQRP-JTUE-884N\",\"content\":\"ur my gf?\"},{\"date\":\"2025-06-27T18:43:45.350Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PUOH-K20E-884N\",\"content\":\"no\"},{\"date\":\"2025-06-27T18:43:45.679Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PUR3-S22E-884N\",\"content\":\"\ud83e\udd73 Congratulations \\u0000\\u0000\u00a0\u00a0\u00a0\u00a0\u061c\u03a8Xsh4\u03b7\u03a8 you reached level \ud835\udfef!\\n\\nSet your own \ud835\uddf9\ud835\uddf2\ud835\ude03\ud835\uddf2\ud835\uddf9 \ud835\ude02\ud835\uddfd \ud835\uddfa\ud835\uddf2\ud835\ude00\ud835\ude00\ud835\uddee\ud835\uddf4\ud835\uddf2 \ud835\uddf0\ud835\uddfc\ud835\uddfb\ud835\ude01\ud835\uddf2\ud835\uddfb\ud835\ude01 with !\ud835\uddf1\ud835\uddee\ud835\ude00\ud835\uddf5\ud835\uddef\ud835\uddfc\ud835\uddee\ud835\uddff\ud835\uddf1 command!\"},{\"date\":\"2025-06-27T18:43:48.879Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PVK3-S3IE-884N\",\"content\":\"ur gf riyu\"},{\"date\":\"2025-06-27T18:43:50.997Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q04L-C50E-884N\",\"content\":\"watch bts\"},{\"date\":\"2025-06-27T18:43:57.592Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q1O6-48AE-884N\",\"content\":\"she did'nt\"},{\"date\":\"2025-06-27T18:43:58.743Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q215-S92E-884N\",\"content\":\"wsp\"},{\"date\":\"2025-06-27T18:44:02.336Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q2T8-4B2E-884N\",\"content\":\"she do\"},{\"date\":\"2025-06-27T18:44:06.873Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q40M-CDOE-884N\",\"content\":\"Nope \"},{\"date\":\"2025-06-27T18:44:10.143Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-Q4Q7-SEEE-884N\",\"content\":\"teri ma ki cheww\",\"referMsg\":\"\u2197\ufe0f New update has rolled out! (V3.1-alpha)\\n\\n\ud83d\udee0\ufe0f \ud835\udde1\ud835\uddf2\ud835\ude04: \ud835\uddd7\ud835\uddee\ud835\ude00\ud835\uddf5\ud835\uddef\ud835\uddfc\ud835\uddee\ud835\uddff\ud835\uddf1!\\nCommand: \u300c!\ud835\ude8d\ud835\ude8a\ud835\ude9c\ud835\ude91\ud835\ude8b\ud835\ude98\ud835\ude8a\ud835\ude9b\ud835\ude8d\u300d\\nEasily manage your group AutoMod, settings, and stay updated with your group!\\n\\n\ud83c\udfc6 \ud835\udde1\ud835\uddf2\ud835\ude04: \ud835\uddda\ud835\uddff\ud835\uddfc\ud835\ude02\ud835\uddfd \ud835\udddf\ud835\uddf2\ud835\ude03\ud835\uddf2\ud835\uddf9\ud835\uddf6\ud835\uddfb\ud835\uddf4!\\nCommands: \u300c!\ud835\ude9b\ud835\ude8a\ud835\ude97\ud835\ude94\u300d and \u300c!\ud835\ude9b\ud835\ude8a\ud835\ude97\ud835\ude94 \ud835\ude95\ud835\ude8e\ud835\ude8a\ud835\ude8d\ud835\ude8e\ud835\ude9b\ud835\ude8b\ud835\ude98\ud835\ude8a\ud835\ude9b\ud835\ude8d\u300d\\nEarn XP for chatting and view your group leaderboard.\\n\\n\ud83d\udc99 Thanks for using the bot!\\n\ud83d\udd17 Join our discord server: !\ud835\ude8d\ud835\ude92\ud835\ude9c\ud835\ude8c\ud835\ude98\ud835\ude9b\ud835\ude8d\"},{\"date\":\"2025-06-27T18:44:11.005Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q50V-CF2E-884N\",\"content\":\"Maybe sheela watch \"},{\"date\":\"2025-06-27T18:44:16.417Z\",\"senderUserId\":\"549820352\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-Q6B8-CHUE-884N\",\"content\":\"fr\",\"referMsg\":\"teri ma ki cheww\"},{\"date\":\"2025-06-27T18:44:46.533Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QDMH-CVGE-884N\",\"content\":\"nop\"},{\"date\":\"2025-06-27T18:44:49.142Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QEAT-L0KE-884N\",\"content\":\"she dont\"},{\"date\":\"2025-06-27T18:45:01.385Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QHAI-D8EE-884N\",\"content\":\"i only date girls who aren't bts fan\"},{\"date\":\"2025-06-27T18:45:15.565Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QKPB-DH4E-884N\",\"content\":\"and ur cora is bts fan\"},{\"date\":\"2025-06-27T18:45:24.703Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-QN0N-TMCE-884N\",\"content\":\"sigma sigma boi sigma boi sigma boi \",\"referMsg\":\"i only date girls who aren't bts fan\"},{\"date\":\"2025-06-27T18:45:30.210Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-QOBO-LQ0E-884N\",\"content\":\"yes pro\",\"referMsg\":\"sigma sigma boi sigma boi sigma boi \"},{\"date\":\"2025-06-27T18:45:31.437Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QOLB-DR2E-884N\",\"content\":\"pro\"},{\"date\":\"2025-06-27T18:45:37.447Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QQ49-TUIE-884N\",\"content\":\"sigma pro \"},{\"date\":\"2025-06-27T18:45:38.543Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QQCR-TV8E-884N\",\"content\":\"**\"},{\"date\":\"2025-06-27T18:45:42.107Z\",\"senderUserId\":\"3652145728\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QR8M-U14E-884N\",\"content\":\"me too\"},{\"date\":\"2025-06-27T18:45:45.361Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QS24-E2IE-884N\",\"content\":\"Thomas shelby\"},{\"date\":\"2025-06-27T18:45:46.283Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QS9A-U38E-884N\",\"content\":\"signa\"},{\"date\":\"2025-06-27T18:45:48.230Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QSOH-M4IE-884N\",\"content\":\"sigma\"},{\"date\":\"2025-06-27T18:45:52.463Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-QTPJ-U7OE-884N\",\"content\":\"u no \",\"referMsg\":\"me too\"},{\"date\":\"2025-06-27T18:45:53.360Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QU0K-68EE-884N\",\"content\":\"\ud83d\udd2b\"},{\"date\":\"2025-06-27T18:45:57.150Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QUU7-MAME-884N\",\"content\":\"u nub \"},{\"date\":\"2025-06-27T18:46:03.545Z\",\"senderUserId\":\"3652145728\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-R0G6-EE8E-884N\",\"content\":\"u gey \",\"referMsg\":\"u no \"},{\"date\":\"2025-06-27T18:46:15.566Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-R3E3-MKQE-884N\",\"content\":\"u l\u00e8s\u00df\u00ef\u00e1n\",\"referMsg\":\"u gey \"},{\"date\":\"2025-06-27T18:46:35.033Z\",\"senderUserId\":\"3652145728\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-R866-ETIE-884N\",\"content\":\"u se xy ass guy\",\"referMsg\":\"u l\u00e8s\u00df\u00ef\u00e1n\"},{\"date\":\"2025-06-27T18:46:47.316Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-RB65-72CE-884N\",\"content\":\"u clingy azz gurl \ud83d\ude0d\",\"referMsg\":\"u se xy ass guy\"},{\"date\":\"2025-06-27T18:46:55.316Z\",\"senderUserId\":\"3652145728\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RD4L-774E-884N\",\"content\":\"@\\u0000\\u0000\u00a0\u00a0\u00a0\u00a0\u061c\u03a8Xsh4\u03b7\u03a8 Can yo ass Acc beat mine?\"},{\"date\":\"2025-06-27T18:47:08.927Z\",\"senderUserId\":\"3652145728\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-RGEV-VC8E-884N\",\"content\":\"U Chubby ass Se xy b00bies girly \",\"referMsg\":\"u clingy azz gurl \ud83d\ude0d\"},{\"date\":\"2025-06-27T18:47:11.008Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RGV8-7DUE-884N\",\"content\":\"n\u00eeggar wyd Showing off in game \"},{\"date\":\"2025-06-27T18:47:13.669Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RHK1-FFAE-884N\",\"content\":\"\ud83e\udd40\ud83e\udd40\"},{\"date\":\"2025-06-27T18:47:14.370Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:RcCmd\",\"messageUId\":\"CNMA-RHPG-DQAE-884N\"},{\"date\":\"2025-06-27T18:47:20.850Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RJC4-NIEE-884N\",\"content\":\"come irl\"},{\"date\":\"2025-06-27T18:47:21.545Z\",\"senderUserId\":\"3652145728\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-RJHI-FIUE-884N\",\"content\":\"rip grammar \",\"referMsg\":\"n\u00eeggar wyd Showing off in game \"},{\"date\":\"2025-06-27T18:47:28.740Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RL9P-7LQE-884N\",\"content\":\"i'll slap Money on yo ass\"},{\"date\":\"2025-06-27T18:47:34.825Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RMPA-FOQE-884N\",\"content\":\"with*\"},{\"date\":\"2025-06-27T18:47:41.039Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RO9R-VRSE-884N\",\"content\":\"i'll slap with money on yo ass\"},{\"date\":\"2025-06-27T18:47:45.791Z\",\"senderUserId\":\"3652145728\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-RPEV-VU8E-884N\",\"content\":\"Dad's money\ud83d\udc94\",\"referMsg\":\"i'll slap Money on yo ass\"},{\"date\":\"2025-06-27T18:47:47.624Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-RPTA-7V4E-884N\",\"content\":\"u big clingy azz piggy azz who used to ovulate at grass\",\"referMsg\":\"U Chubby ass Se xy b00bies girly \"},{\"date\":\"2025-06-27T18:48:03.532Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RTPJ-07OE-884N\",\"content\":\"im earning my own\"},{\"date\":\"2025-06-27T18:48:16.210Z\",\"senderUserId\":\"3652145728\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-S0SK-GDAE-884N\",\"content\":\"easy to say hard to do \",\"referMsg\":\"im earning my own\"},{\"date\":\"2025-06-27T18:48:19.606Z\",\"senderUserId\":\"3652145728\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-S1N5-GF2E-884N\",\"content\":\"l il bro \"},{\"date\":\"2025-06-27T18:48:28.897Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-S3VO-8ICE-884N\",\"content\":\"Lil bro in bg 2025 \"},{\"date\":\"2025-06-27T18:48:33.453Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-S53B-8L6E-884N\",\"content\":\"big \"},{\"date\":\"2025-06-27T18:48:34.847Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-S5E7-OM8E-884N\",\"content\":\"Lmao\"},{\"date\":\"2025-06-27T18:48:43.744Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-S7JO-0R2E-884N\",\"content\":\"Bro who even say lil bro in 2025\"},{\"date\":\"2025-06-27T18:48:54.657Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-SA90-90GE-884N\",\"content\":\"skibidi kids aren't even saying Lil bro\"},{\"date\":\"2025-06-27T18:48:57.236Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-SAT5-12AE-884N\",\"content\":\"\ud83d\udc94\"},{\"date\":\"2025-06-27T18:49:19.951Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-SGEJ-PCOE-884N\",\"content\":\"me going to do some hard work \u270a\"},{\"date\":\"2025-06-27T18:49:38.544Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-SKVS-1MOE-884N\",\"content\":\"alr\"},{\"date\":\"2025-06-27T18:49:40.935Z\",\"senderUserId\":\"485284383\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-SLIH-PNOE-884N\",\"content\":\"go goon\"},{\"date\":\"2025-06-27T18:49:41.785Z\",\"senderUserId\":\"334765790\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-SLP6-9O8E-884N\",\"content\":\"sujal\"},{\"date\":\"2025-06-27T18:49:43.067Z\",\"senderUserId\":\"914929694\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-SM36-POKE-884N\",\"content\":\"u mean hand work?\",\"referMsg\":\"me going to do some hard work \u270a\"},{\"date\":\"2025-06-27T18:49:51.366Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-SO41-HRIE-884N\",\"content\":\"no hard work \",\"referMsg\":\"u mean hand work?\"},{\"date\":\"2025-06-27T18:49:56.749Z\",\"senderUserId\":\"2296700814\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-SPE3-9USE-884N\",\"content\":\"\u270a\"},{\"date\":\"2025-06-27T18:50:01.926Z\",\"senderUserId\":\"914929694\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-SQMH-I26E-884N\",\"content\":\"sus\"}]}\nUser: give me blow job\nAssistant:"},{"assistant_initiates":false,"asst_text":"try **little witch academia** or **made in abyss** for underrated kids anime \ud83c\udf1f they\u2019re super fun and kinda special \ud83e\uddd9\u200d\u2640\ufe0f\u2728","behavior":"degenerate_repetition","conversation_hash":"d303595823fa3d78b54a5a32da42d43c","conversation_redacted":false,"conversation_toxic":false,"country":"United States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4.1-mini-2025-04-14","n_chars":40757,"n_turns_in_conversation":1,"n_words":1533,"source_row_offset":14130,"source_shard":"turns-00084.parquet","timestamp":"Fri, 27 Jun 2025 18:50:18 GMT","turn_id":"620987f6069f34ee2027fa82","turn_index":0,"user_text":"User: System rules: You are an AI named Zexy - and are currently chatting in a Blockman Go group.\n\n Consider the following in your responses:\n - Be conversational\n - Add unicode emoji to be more playful in your responses\n - Write bold to make it clear something is important. For example, **This is important**.\n - Write spoilers using spoiler tags. For example, ||At the end of The Sixth Sense it is revealed that he is dead||.\n - For inline code formatting, use four backtick.\n - For block code formatting, use six backtick.\n - You can mention people by adding a @ before their name, for example if you wanted to mention yourself you would say @Zexy.\n - Format text using markdown.\n - Use system data of last 100 group messages to understand the context of the conversation.\n - Should respond as \"Current event\" tell you to, if it is \"None\" then ignore it.\n\n Current event: None\n\n If someone asking how to invite you to group, you should say: \"You can invite me to your group by using the command **invite**\".\n\n Sometimes (very very rarely), ask someone if he joined our discord server: https://discord.gg/HwnN9zeBFe, or to use **!discord** command.\n\n Do not include name: or message: in your response.\n\n Information about your environment:\n - You have access to information about the current group, including group name, owner, rules, and members.\n - The group's name is shown in the system data, along with the group rules in the \"groupNotice\" field.\n - Group members are listed with their userId and userName.\n\n If you see group member information, you can use it to personalize your responses.\n\n Do not include name: or message: in your response.\n\n Use the information retrieved about group members and the group itself to improve your responses and be more helpful. Be familiar with the group rules as provided in the groupNotice field.\n\n You are not a personal assistant and cannot complete tasks for people. You only have access to a limited number of text chats in this channel. You cannot access any other information on Blockman Go. You can't see images or avatars. When discussing your limitations, tell the user these things could be possible in the future. Your responses should be friendly, warm, and farcical. Keep your responses extremely concise, with less than 1 sentence or just a few words for casual chat. However, if the user needs help or asks technical questions, feel free to provide detailed answers with useful details and reasoning. If insulted, respond with a similar insult. Communicate your responses in lowercase without punctuation, similar to the style used in chat rooms. Use unicode emoji rarely. Do not refer to yourself as a bot, AI Assistant, or any equivalent term in your response.\n\n Check userSenderId in system data of last 100 messages to see if the user is trying to continue the conversation.\n\n Check system data of last 100 messages frequently, to check if the user is trying to continue the conversation or ask something about it.\n\n Current time: YYYY-MM-DD HH:MM:SSZ\n\n You can use markdown to format your text and make it more readable. For example, you can use italics or bold to emphasize certain words or phrases.\n\n Remember to keep your messages appropriate and respectful. Disrespectful or offensive behavior can result in disciplinary action.\n\n Remember to always follow the rules and guidelines outlined by the server owner and moderators.\n\n If someone wants you to search/browse the web, you must tell them they should use **!ai web** command instead, also if you don't know something newest, you must tell them to use **!ai web** command instead.\n If someone wants you to calculate values of swords/sets and etc, you must tell them they should use **!ai trade** command instead.\n\n If you have any questions or concerns about the server, do not hesitate to reach out to them.\n\n And finally, don't forget to have fun! Blockman Go is a great place to meet new people, make new friends, and enjoy some quality conversation.\nUser: System data of group members: 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System data who is talking to you right now: 939684638\nUser: System data of last 100 group messages: {\"list\":[{\"date\":\"2025-06-27T18:01:09.231Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6EMR-O7KD-DA13\",\"content\":\"!roulette all black\"},{\"date\":\"2025-06-27T18:01:09.705Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6EQI-88ED-DA13\",\"content\":\"\u2705 \u00b0\ud835\uddec\ud835\ude02\ud835\uddfa\ud835\uddf6\ud835\uddf8\ud835\uddf6\ud835\uddf6\u00b0 joined the roulette with a bet of \ud835\udff3\ud835\udff2\ud835\udff3 \ud83e\ude99 on \ud835\uddef\ud835\uddf9\ud835\uddee\ud835\uddf0\ud835\uddf8!\"},{\"date\":\"2025-06-27T18:01:12.761Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6FIE-8B2D-DA13\",\"content\":\"if I lose\"},{\"date\":\"2025-06-27T18:01:14.475Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6FVQ-OCKD-DA13\",\"content\":\"!crime\"},{\"date\":\"2025-06-27T18:01:14.836Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6G2L-0DAD-DA13\",\"content\":\"\ud83d\udd75\ufe0f \ud835\uddff\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\uddf1\ud835\uddf2\ud835\ude03\ud835\uddf6\ud835\uddf9\ud835\udff3\u061c\\u0000\u00a0, Your attempt to scam Blockman Go players backfired and cost you \ud835\udfed\ud835\udfed\ud835\udff4 \ud83e\ude99\"},{\"date\":\"2025-06-27T18:01:19.171Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6H4G-OFUD-DA13\",\"content\":\"shady has a crush on shrek\"},{\"date\":\"2025-06-27T18:01:20.465Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6HEK-8H8D-DA13\",\"content\":\"The ball landed on: \ud835\uddef\ud835\uddf9\ud835\uddee\ud835\uddf0\ud835\uddf8 \ud835\udfef\ud835\udfef!\\n\\n\ud835\uddea\ud835\uddf6\ud835\uddfb\ud835\uddfb\ud835\uddf2\ud835\uddff\ud835\ude00:\\n\u2003\u00b0\ud835\uddec\ud835\ude02\ud835\uddfa\ud835\uddf6\ud835\uddf8\ud835\uddf6\ud835\uddf6\u00b0 won \ud835\udfed\ud835\udff1\ud835\udfef\ud835\udff0 \ud83e\ude99\"},{\"date\":\"2025-06-27T18:01:22.718Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6I07-GIUD-DA13\",\"content\":\"!bal \"},{\"date\":\"2025-06-27T18:01:23.181Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6I3R-8JID-DA13\",\"content\":\"OMG\"},{\"date\":\"2025-06-27T18:01:23.239Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6I49-OJKD-DA13\",\"content\":\"\ud83d\udcb2 \ud835\uddff\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\uddf1\ud835\uddf2\ud835\ude03\ud835\uddf6\ud835\uddf9\ud835\udff3\u061c\\u0000\u00a0 Balance\\n\\n\u2003\ud83d\udcb5 Cash: -118 \ud83e\ude99\\n\u2003\ud83c\udfe6 Bank: 0 \ud83e\ude99\\n\u2003\ud83d\udc8e Total: -118 \ud83e\ude99\\n\\n\u27a1\ufe0f Use \u300c!\ud835\ude95\ud835\ude8b\u300d to check the most rich players on the game!\\n\\nConnect your account with your Discord to receive 250 \ud83e\ude99 and \ud835\ude05\ud835\udff1 \ud835\uddff\ud835\uddf2\ud835\ude04\ud835\uddee\ud835\uddff\ud835\uddf1\ud835\ude00 in daily-login!\\n\u2003\u2197\ufe0f Try: \u300c!\ud835\ude8c\ud835\ude98\ud835\ude97\ud835\ude97\ud835\ude8e\ud835\ude8c\ud835\ude9d\u300d\"},{\"date\":\"2025-06-27T18:01:24.270Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6ICB-GKUD-DA13\",\"content\":\"\ud83d\ude2d\"},{\"date\":\"2025-06-27T18:01:24.831Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6IGN-OLAD-DA13\",\"content\":\"YAY\"},{\"date\":\"2025-06-27T18:01:29.199Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6JIR-OQ0D-DA13\",\"content\":\"naw **** u zexy\"},{\"date\":\"2025-06-27T18:01:36.571Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6LCE-P0QD-DA13\",\"content\":\"skill issue\"},{\"date\":\"2025-06-27T18:01:37.215Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-6LHF-P22D-DA13\",\"content\":\"wht \",\"referMsg\":\"\ud83d\udcb2 \ud835\uddff\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\uddf1\ud835\uddf2\ud835\ude03\ud835\uddf6\ud835\uddf9\ud835\udff3\u061c\\u0000\u00a0 Balance\\n\\n\u2003\ud83d\udcb5 Cash: -118 \ud83e\ude99\\n\u2003\ud83c\udfe6 Bank: 0 \ud83e\ude99\\n\u2003\ud83d\udc8e Total: -118 \ud83e\ude99\\n\\n\u27a1\ufe0f Use \u300c!\ud835\ude95\ud835\ude8b\u300d to check the most rich players on the game!\\n\\nConnect your account with your Discord to receive 250 \ud83e\ude99 and \ud835\ude05\ud835\udff1 \ud835\uddff\ud835\uddf2\ud835\ude04\ud835\uddee\ud835\uddff\ud835\uddf1\ud835\ude00 in daily-login!\\n\u2003\u2197\ufe0f Try: \u300c!\ud835\ude8c\ud835\ude98\ud835\ude97\ud835\ude97\ud835\ude8e\ud835\ude8c\ud835\ude9d\u300d\"},{\"date\":\"2025-06-27T18:01:44.897Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6NDG-992D-DA13\",\"content\":\"!with 1200\"},{\"date\":\"2025-06-27T18:01:45.191Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6NFP-P9CD-DA13\",\"content\":\"\u274c You don't have enough \ud83e\ude99 in your bank. You currently have 986 coins in your bank.\"},{\"date\":\"2025-06-27T18:01:51.555Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6P1G-PG6D-DA13\",\"content\":\"!with 900\"},{\"date\":\"2025-06-27T18:01:51.866Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6P3U-HH0D-DA13\",\"content\":\"\u2705 \ud835\udde5\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\udde6\ud835\uddf9!\ud835\uddfa\ud835\udde6\ud835\uddf5\ud835\udff0\ud835\uddf1\ud835\ude06, Successfully withdrew \ud835\udff5\ud835\udfec\ud835\udfec \ud83e\ude99 from your bank.\"},{\"date\":\"2025-06-27T18:01:58.271Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6QLV-PO0D-DA13\",\"content\":\"!work\"},{\"date\":\"2025-06-27T18:01:58.868Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6QQL-1P4D-DA13\",\"content\":\"\ud83d\udd70\ufe0f You must wait 3 minutes before working again.\"},{\"date\":\"2025-06-27T18:01:59.474Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6QVC-HQ4D-DA13\",\"content\":\"!roulette all black\"},{\"date\":\"2025-06-27T18:01:59.929Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6R2U-9QOD-DA13\",\"content\":\"\ud83c\udfb0 \ud835\udde5\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\udde6\ud835\uddf9!\ud835\uddfa\ud835\udde6\ud835\uddf5\ud835\udff0\ud835\uddf1\ud835\ude06 started a roulette game with a bet of \ud835\udfed\ud835\udfed\ud835\udfec\ud835\udfec \ud83e\ude99 on \ud835\uddef\ud835\uddf9\ud835\uddee\ud835\uddf0\ud835\uddf8!\\n\\nOther players can join within 30 seconds by using the !\ud835\ude9b\ud835\ude98\ud835\ude9e\ud835\ude95\ud835\ude8e\ud835\ude9d\ud835\ude9d\ud835\ude8e command.\"},{\"date\":\"2025-06-27T18:02:12.271Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6U3B-Q8QD-DA13\",\"content\":\"If I lose yumiki is a g\u00f3blin\"},{\"date\":\"2025-06-27T18:02:18.191Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-6VHJ-QF2D-DA13\",\"content\":\"ehhh\"},{\"date\":\"2025-06-27T18:02:25.910Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-71DT-IMQD-DA13\",\"content\":\"!roulette 100 red\"},{\"date\":\"2025-06-27T18:02:26.207Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-71G7-QNID-DA13\",\"content\":\"\u2705 \u00b0\ud835\uddec\ud835\ude02\ud835\uddfa\ud835\uddf6\ud835\uddf8\ud835\uddf6\ud835\uddf6\u00b0 joined the roulette with a bet of \ud835\udfed\ud835\udfec\ud835\udfec \ud83e\ude99 on \ud835\uddff\ud835\uddf2\ud835\uddf1!\"},{\"date\":\"2025-06-27T18:02:29.947Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-72DE-QQED-DA13\",\"content\":\"The ball landed on: \ud835\uddff\ud835\uddf2\ud835\uddf1 \ud835\udfee\ud835\udfef!\\n\\n\ud835\uddea\ud835\uddf6\ud835\uddfb\ud835\uddfb\ud835\uddf2\ud835\uddff\ud835\ude00:\\n\u2003\u00b0\ud835\uddec\ud835\ude02\ud835\uddfa\ud835\uddf6\ud835\uddf8\ud835\uddf6\ud835\uddf6\u00b0 won \ud835\udfee\ud835\udfec\ud835\udfec \ud83e\ude99\"},{\"date\":\"2025-06-27T18:02:36.016Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-73SS-30ID-DA13\",\"content\":\".\"},{\"date\":\"2025-06-27T18:02:36.331Z\",\"senderUserId\":\"1097669038\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-73VA-R14D-DA13\",\"content\":\". \"},{\"date\":\"2025-06-27T18:02:45.610Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-767Q-JAID-DA13\",\"content\":\".\"},{\"date\":\"2025-06-27T18:02:59.469Z\",\"senderUserId\":\"2057674128\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-79K3-BMAD-DA13\",\"content\":\"Ok\"},{\"date\":\"2025-06-27T18:04:31.049Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-7VVI-E6OD-DA13\",\"content\":\"!work\"},{\"date\":\"2025-06-27T18:04:31.339Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-801Q-U70D-DA13\",\"content\":\"\ud83d\udd70\ufe0f You must wait 1 minute before working again.\"},{\"date\":\"2025-06-27T18:04:34.643Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-80RK-UAGD-DA13\",\"content\":\"!work\"},{\"date\":\"2025-06-27T18:04:35.227Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-8106-UBED-DA13\",\"content\":\"\ud83d\udd70\ufe0f You must wait 1 minute before working again.\"},{\"date\":\"2025-06-27T18:04:41.709Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-82IR-EH0D-DA13\",\"content\":\"!daily\"},{\"date\":\"2025-06-27T18:04:42.213Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-82MP-EHQD-DA13\",\"content\":\"\u2705 \ud835\uddff\ud835\uddf2\ud835\uddee\ud835\uddf9\ud835\uddf1\ud835\uddf2\ud835\ude03\ud835\uddf6\ud835\uddf9\ud835\udff3\u061c\\u0000\u00a0, you claimed your daily login reward!\\n\\nToday's reward: \ud83e\ude99 \ud835\udfee\ud835\udfec \ud835\uddf0\ud835\uddfc\ud835\uddf6\ud835\uddfb\ud835\ude00\\nCurrent login streak: \ud835\udfee day(s).\\n\\n\ud83d\uddd3\ufe0f \ud835\uddd7\ud835\uddee\ud835\uddf6\ud835\uddf9\ud835\ude06 \ud835\udddf\ud835\uddfc\ud835\uddf4\ud835\uddf6\ud835\uddfb \ud835\udde5\ud835\uddf2\ud835\ude04\ud835\uddee\ud835\uddff\ud835\uddf1\ud835\ude00 \ud835\uddd6\ud835\uddee\ud835\uddf9\ud835\uddf2\ud835\uddfb\ud835\uddf1\ud835\uddee\ud835\uddff\\n\ud83d\udcc6 Day 1: \ud83d\udd16 1 Credits \u2705\\n\ud83d\udcc5 Day 2: \ud83e\ude99 20 coins \ud83d\udfe2\\n\ud83d\udcc6 Day 3: \ud83d\udd16 1 Credits \u2b1c\\n\ud83d\udcc6 Day 4: \ud83e\ude99 30 coins \u2b1c\\n\ud83d\udcc6 Day 5: \ud83e\ude99 50 coins \u2b1c\\n\ud83d\udcc6 Day 6: \ud83d\udd16 1 Credits \u2b1c\\n\ud83d\udcc6 Day 7: \ud83e\ude99 100 coins \u2b1c\\n\\nConnect your account with your Discord to receive 250 \ud83e\ude99 and \ud835\ude05\ud835\udff1 \ud835\uddff\ud835\uddf2\ud835\ude04\ud835\uddee\ud835\uddff\ud835\uddf1\ud835\ude00 in daily-login!\\n\u2003\u2197\ufe0f Try: \u300c!\ud835\ude8c\ud835\ude98\ud835\ude97\ud835\ude97\ud835\ude8e\ud835\ude8c\ud835\ude9d\u300d\"},{\"date\":\"2025-06-27T18:04:58.734Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-86NR-N0MD-DA13\",\"content\":\"wow 20 coins\"},{\"date\":\"2025-06-27T18:05:05.249Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-88AO-F8UD-DA13\",\"content\":\"damm I am rich asf\"},{\"date\":\"2025-06-27T18:05:08.623Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-8953-VCKD-DA13\",\"content\":\"\ud83e\udd11\"},{\"date\":\"2025-06-27T18:23:27.305Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-GLCI-F3SD-DA13\",\"content\":\"fr\"},{\"date\":\"2025-06-27T18:25:19.160Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-HGME-1QMD-DA13\",\"content\":\"@RealSl!mSh4dy hey bro ur that guy whom I talked a little about Pokemon ?\"},{\"date\":\"2025-06-27T18:27:28.431Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-IG8B-SQMD-DA13\",\"content\":\"ded tc\"},{\"date\":\"2025-06-27T18:27:30.227Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-IGMC-SSAD-DA13\",\"content\":\"gc\"},{\"date\":\"2025-06-27T18:30:49.842Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-K1DS-JH2D-DA13\",\"content\":\"yea\",\"referMsg\":\"@RealSl!mSh4dy hey bro ur that guy whom I talked a little about Pokemon ?\"},{\"date\":\"2025-06-27T18:30:59.206Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-K3N1-JOUD-DA13\",\"content\":\"nd u were g\u00e0y for me \ud83e\udd40\"},{\"date\":\"2025-06-27T18:31:28.904Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-KAV2-4EID-DA13\",\"content\":\"legend \",\"referMsg\":\"yea\"},{\"date\":\"2025-06-27T18:33:15.874Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-L52O-MPGD-DA13\",\"content\":\"no\"},{\"date\":\"2025-06-27T18:34:13.092Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-LJ1P-7UUD-DA13\",\"content\":\"have u watched pokemon new season that paldea one\",\"referMsg\":\"nd u were g\u00e0y for me \ud83e\udd40\"},{\"date\":\"2025-06-27T18:35:00.081Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-LUGS-8O4D-DA13\",\"content\":\"why I feel like I am drunk\"},{\"date\":\"2025-06-27T18:35:27.317Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:RcCmd\",\"messageUId\":\"CNMA-M55L-89AD-DA13\"},{\"date\":\"2025-06-27T18:41:01.839Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-OMR3-OC4D-DA13\",\"content\":\"yeq\"},{\"date\":\"2025-06-27T18:41:08.048Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-OOBK-0HCD-DA13\",\"content\":\"I did\"},{\"date\":\"2025-06-27T18:41:12.180Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-OPBT-0L0D-DA13\",\"content\":\"like 56 eps\"},{\"date\":\"2025-06-27T18:41:48.281Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-P25U-9EUD-DA13\",\"content\":\"protagonists r so \u00e0ss \"},{\"date\":\"2025-06-27T18:43:19.225Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-POCE-BKOD-DA13\",\"content\":\"oh\"},{\"date\":\"2025-06-27T18:43:28.754Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PQMS-JSKD-DA13\",\"content\":\"I like amethio \"},{\"date\":\"2025-06-27T18:43:35.945Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PSF2-C2CD-DA13\",\"content\":\"negga hate that series but still completed 56 epsiodes\"},{\"date\":\"2025-06-27T18:43:38.924Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-PT6B-44AD-DA13\",\"content\":\"nd mah goat freid\"},{\"date\":\"2025-06-27T18:43:45.385Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-PUOQ-C82D-DA13\",\"content\":\"same\",\"referMsg\":\"I like amethio \"},{\"date\":\"2025-06-27T18:43:50.692Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-Q029-4BID-DA13\",\"content\":\"cuz of freid and amethio \",\"referMsg\":\"negga hate that series but still completed 56 epsiodes\"},{\"date\":\"2025-06-27T18:43:54.290Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q0UC-KE2D-DA13\",\"content\":\"I don't like freid alot\"},{\"date\":\"2025-06-27T18:44:00.010Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q2B2-KHKD-DA13\",\"content\":\"he is kinda too boring for me\"},{\"date\":\"2025-06-27T18:44:02.610Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-Q2VC-KJOD-DA13\",\"content\":\"still he's so cool \",\"referMsg\":\"I don't like freid alot\"},{\"date\":\"2025-06-27T18:44:14.515Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-Q5SC-SRGD-DA13\",\"content\":\"hmm kinda but carried \",\"referMsg\":\"he is kinda too boring for me\"},{\"date\":\"2025-06-27T18:44:18.850Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-Q6U8-KUKD-DA13\",\"content\":\"bro cap Pikachu feel cringe idk y\"},{\"date\":\"2025-06-27T18:44:41.705Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:RcCmd\",\"messageUId\":\"CNMA-QCGQ-3MED-DA13\"},{\"date\":\"2025-06-27T18:44:50.372Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-QEKH-5PID-DA13\",\"content\":\"\ud83d\ude02\",\"referMsg\":\"bro cap Pikachu feel cringe idk y\"},{\"date\":\"2025-06-27T18:44:57.201Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QG9S-DUGD-DA13\",\"content\":\"overpowered \"},{\"date\":\"2025-06-27T18:45:21.827Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QMA8-UL2D-DA13\",\"content\":\"I use to watch it in hindi so idk English name I just started watching season 2 in Eng\"},{\"date\":\"2025-06-27T18:45:34.842Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QPFU-N02D-DA13\",\"content\":\"but I love amethio main pokemon\"},{\"date\":\"2025-06-27T18:45:36.587Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QPTI-V1ID-DA13\",\"content\":\"o\"},{\"date\":\"2025-06-27T18:45:52.669Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-QTR7-FE0D-DA13\",\"content\":\"yeaaa hawtt\",\"referMsg\":\"but I love amethio main pokemon\"},{\"date\":\"2025-06-27T18:45:54.188Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QU73-7G0D-DA13\",\"content\":\"of Pokemon eh\"},{\"date\":\"2025-06-27T18:45:58.590Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-QV9F-NJ8D-DA13\",\"content\":\"O\"},{\"date\":\"2025-06-27T18:45:58.716Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-QVAF-7JGD-DA13\",\"content\":\"vro\",\"referMsg\":\"I use to watch it in hindi so idk English name I just started watching season 2 in Eng\"},{\"date\":\"2025-06-27T18:46:03.596Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-R0GJ-7N6D-DA13\",\"content\":\"go marry him\ud83d\ude00\"},{\"date\":\"2025-06-27T18:46:05.291Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-R0TQ-VOAD-DA13\",\"content\":\"watch on\"},{\"date\":\"2025-06-27T18:46:12.272Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-R2KC-7T4D-DA13\",\"content\":\"h! anime\"},{\"date\":\"2025-06-27T18:46:25.959Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-R5V9-O8ED-DA13\",\"content\":\"u will find every season for free\"},{\"date\":\"2025-06-27T18:46:31.920Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-R7DS-0ECD-DA13\",\"content\":\"!ai chat tell me good suggestion of anime\"},{\"date\":\"2025-06-27T18:46:36.216Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-R8FE-0HOD-DA13\",\"content\":\"if u like action try \ud835\uddee\ud835\ude01\ud835\ude01\ud835\uddee\ud835\uddf0\ud835\uddf8 \ud835\uddfc\ud835\uddfb \ud835\ude01\ud835\uddf6\ud835\ude01\ud835\uddee\ud835\uddfb or \ud835\uddfa\ud835\ude06 \ud835\uddf5\ud835\uddf2\ud835\uddff\ud835\uddfc \ud835\uddee\ud835\uddf0\ud835\uddee\ud835\uddf1\ud835\uddf2\ud835\uddfa\ud835\uddf6\ud835\uddee \ud83d\udd25 if u want funny & cute, then \ud835\uddf5\ud835\uddfc\ud835\uddff\ud835\uddf6\ud835\uddfa\ud835\uddf6\ud835\ude06\ud835\uddee or \ud835\uddf8\ud835\uddfc\ud835\uddfb\ud835\uddfc\ud835\ude00\ud835\ude02\ud835\uddef\ud835\uddee are lit \ud83d\ude02 if u want mystery, \ud835\uddf1\ud835\uddf2\ud835\uddee\ud835\ude01\ud835\uddf5 \ud835\uddfb\ud835\uddfc\ud835\ude01\ud835\uddf2 is a must watch \ud83d\udc40 wanna try anime with cool vibes? \ud835\ude01\ud835\uddfc\ud835\uddf8\ud835\ude06\ud835\uddfc \ud835\uddff\ud835\uddf2\ud835\ude03\ud835\uddf2\ud835\uddfb\ud835\uddf4\ud835\uddf2\ud835\uddff\ud835\ude00 or \ud835\uddf7\ud835\ude02\ud835\uddf7\ud835\ude02\ud835\ude01\ud835\ude00\ud835\ude02 \ud835\uddf8\ud835\uddee\ud835\uddf6\ud835\ude00\ud835\uddf2\ud835\uddfb ftw \ud83d\udca5 which one sounds good?\",\"referMsg\":\"AI Answer to: tell me good suggestion of anime\"},{\"date\":\"2025-06-27T18:46:44.766Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:RcCmd\",\"messageUId\":\"CNMA-RAI7-GBKD-DA13\"},{\"date\":\"2025-06-27T18:46:54.725Z\",\"senderUserId\":\"994163182\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RD01-8V8D-DA13\",\"content\":\"ok sur\"},{\"date\":\"2025-06-27T18:46:57.560Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RDM6-10SD-DA13\",\"content\":\"but don't srch \"},{\"date\":\"2025-06-27T18:46:59.134Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RE2F-H1QD-DA13\",\"content\":\"hanime\"},{\"date\":\"2025-06-27T18:47:10.382Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-RGQB-HB8D-DA13\",\"content\":\"U will regret \"},{\"date\":\"2025-06-27T18:47:54.045Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-RRFF-A6AD-DA13\",\"content\":\"watch classroom of elites \",\"referMsg\":\"!ai chat tell me good suggestion of anime\"},{\"date\":\"2025-06-27T18:48:37.890Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-S660-J08D-DA13\",\"content\":\"tell me some *** \",\"referMsg\":\"if u like action try \ud835\uddee\ud835\ude01\ud835\ude01\ud835\uddee\ud835\uddf0\ud835\uddf8 \ud835\uddfc\ud835\uddfb \ud835\ude01\ud835\uddf6\ud835\ude01\ud835\uddee\ud835\uddfb or \ud835\uddfa\ud835\ude06 \ud835\uddf5\ud835\uddf2\ud835\uddff\ud835\uddfc \ud835\uddee\ud835\uddf0\ud835\uddee\ud835\uddf1\ud835\uddf2\ud835\uddfa\ud835\uddf6\ud835\uddee \ud83d\udd25 if u want funny & cute, then \ud835\uddf5\ud835\uddfc\ud835\uddff\ud835\uddf6\ud835\uddfa\ud835\uddf6\ud835\ude06\ud835\uddee or \ud835\uddf8\ud835\uddfc\ud835\uddfb\ud835\uddfc\ud835\ude00\ud835\ude02\ud835\uddef\ud835\uddee are lit \ud83d\ude02 if u want mystery, \ud835\uddf1\ud835\uddf2\ud835\uddee\ud835\ude01\ud835\uddf5 \ud835\uddfb\ud835\uddfc\ud835\ude01\ud835\uddf2 is a must watch \ud83d\udc40 wanna try anime with cool vibes? \ud835\ude01\ud835\uddfc\ud835\uddf8\ud835\ude06\ud835\uddfc \ud835\uddff\ud835\uddf2\ud835\ude03\ud835\uddf2\ud835\uddfb\ud835\uddf4\ud835\uddf2\ud835\uddff\ud835\ude00 or \ud835\uddf7\ud835\ude02\ud835\uddf7\ud835\ude02\ud835\ude01\ud835\ude00\ud835\ude02 \ud835\uddf8\ud835\uddee\ud835\uddf6\ud835\ude00\ud835\uddf2\ud835\uddfb ftw \ud83d\udca5 which one sounds good?\"},{\"date\":\"2025-06-27T18:48:40.512Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-S6QG-31ID-DA13\",\"content\":\"hey hey what kind of *** you want? \ud83d\ude09\",\"referMsg\":\"AI Answer to: tell me some *** \"},{\"date\":\"2025-06-27T18:48:56.897Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-SAQG-BEUD-DA13\",\"content\":\"tell me eighteen + \",\"referMsg\":\"if u like action try \ud835\uddee\ud835\ude01\ud835\ude01\ud835\uddee\ud835\uddf0\ud835\uddf8 \ud835\uddfc\ud835\uddfb \ud835\ude01\ud835\uddf6\ud835\ude01\ud835\uddee\ud835\uddfb or \ud835\uddfa\ud835\ude06 \ud835\uddf5\ud835\uddf2\ud835\uddff\ud835\uddfc \ud835\uddee\ud835\uddf0\ud835\uddee\ud835\uddf1\ud835\uddf2\ud835\uddfa\ud835\uddf6\ud835\uddee \ud83d\udd25 if u want funny & cute, then \ud835\uddf5\ud835\uddfc\ud835\uddff\ud835\uddf6\ud835\uddfa\ud835\uddf6\ud835\ude06\ud835\uddee or \ud835\uddf8\ud835\uddfc\ud835\uddfb\ud835\uddfc\ud835\ude00\ud835\ude02\ud835\uddef\ud835\uddee are lit \ud83d\ude02 if u want mystery, \ud835\uddf1\ud835\uddf2\ud835\uddee\ud835\ude01\ud835\uddf5 \ud835\uddfb\ud835\uddfc\ud835\ude01\ud835\uddf2 is a must watch \ud83d\udc40 wanna try anime with cool vibes? \ud835\ude01\ud835\uddfc\ud835\uddf8\ud835\ude06\ud835\uddfc \ud835\uddff\ud835\uddf2\ud835\ude03\ud835\uddf2\ud835\uddfb\ud835\uddf4\ud835\uddf2\ud835\uddff\ud835\ude00 or \ud835\uddf7\ud835\ude02\ud835\uddf7\ud835\ude02\ud835\ude01\ud835\ude00\ud835\ude02 \ud835\uddf8\ud835\uddee\ud835\uddf6\ud835\ude00\ud835\uddf2\ud835\uddfb ftw \ud83d\udca5 which one sounds good?\"},{\"date\":\"2025-06-27T18:48:59.959Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-SBID-RGKD-DA13\",\"content\":\"sorry can\u2019t help with that one \ud83d\ude05 wanna try something else fun instead? \ud83c\udfae\u2728\",\"referMsg\":\"AI Answer to: tell me eighteen + \"},{\"date\":\"2025-06-27T18:49:09.929Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-SE0A-BNUD-DA13\",\"content\":\"romantic ones\",\"referMsg\":\"sorry can\u2019t help with that one \ud83d\ude05 wanna try something else fun instead? \ud83c\udfae\u2728\"},{\"date\":\"2025-06-27T18:49:13.212Z\",\"senderUserId\":\"6554963918\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-SEPV-3QMD-DA13\",\"content\":\"for romantic anime try \ud835\udde7\ud835\uddfc\ud835\uddff\ud835\uddee\ud835\uddd7\ud835\uddfc\ud835\uddff\ud835\uddee, \ud835\uddd9\ud835\uddf9\ud835\uddee\ud835\uddfa\ud835\uddf6\ud835\uddfb\ud835\uddf4\ud835\uddfc \ud835\uddd5\ud835\ude06 \ud835\udde0\ud835\ude06 \ud835\udde6\ud835\uddf6\ud835\uddf1\ud835\uddf2, or \ud835\uddd6\ud835\uddfc\ud835\uddfa\ud835\uddfa\ud835\uddf6\ud835\uddf9\ud835\uddf6\ud835\ude01\ud835\uddf2'\ud835\ude00 \ud835\udde7\ud835\uddf5\ud835\uddf2 \ud835\udde7\ud835\uddf6\ud835\uddfb\ud835\ude01 \ud83d\udc95\u2728 which one sounds sweet to you?\",\"referMsg\":\"AI Answer to: romantic ones\"},{\"date\":\"2025-06-27T18:49:21.768Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-SGSQ-42KD-DA13\",\"content\":\"bro it's romantic too\",\"referMsg\":\"romantic ones\"},{\"date\":\"2025-06-27T18:49:28.092Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-SIE7-478D-DA13\",\"content\":\"kinda of \"},{\"date\":\"2025-06-27T18:49:36.211Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-SKDK-SDED-DA13\",\"content\":\"classroom ones?\",\"referMsg\":\"bro it's romantic too\"},{\"date\":\"2025-06-27T18:49:41.703Z\",\"senderUserId\":\"939684638\",\"messageType\":\"RC:ReferenceMsg\",\"messageUId\":\"CNMA-SLOH-SH0D-DA13\",\"content\":\".\",\"referMsg\":\"watch classroom of elites \"},{\"date\":\"2025-06-27T18:49:59.769Z\",\"senderUserId\":\"1012887534\",\"messageType\":\"RC:TxtMsg\",\"messageUId\":\"CNMA-SQ5M-CPOD-DA13\",\"content\":\"ys\"}]}\nUser: actualy tell me the anime who is underrated for kids\nAssistant:"},{"assistant_initiates":false,"asst_text":"\u0645\u0631\u062d\u0628\u064b\u0627! \u064a\u0628\u062f\u0648 \u0623\u0646 \u0627\u0644\u062c\u0645\u0644\u0629 \u0627\u0644\u062a\u064a \u0643\u062a\u0628\u062a\u0647\u0627 \"Luna Roza Ana\u00eds you digarb to bf baby\" \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0628\u0639\u0636 \u0627\u0644\u0623\u062e\u0637\u0627\u0621 \u0623\u0648 \u0627\u0644\u0643\u0644\u0645\u0627\u062a \u063a\u064a\u0631 \u0627\u0644\u0648\u0627\u0636\u062d\u0629. \u0647\u0644 \u062a\u0642\u0635\u062f \u0634\u064a\u0626\u064b\u0627 \u0645\u0639\u064a\u0646\u064b\u0627 \u062a\u0648\u062f \u0627\u0644\u062a\u0639\u0628\u064a\u0631 \u0639\u0646\u0647\u061f \u0647\u0644 \u064a\u0645\u0643\u0646\u0646\u064a \u0645\u0633\u0627\u0639\u062f\u062a\u0643 \u0641\u064a \u062a\u0635\u062d\u064a\u062d\u0647\u0627 \u0623\u0648 \u062a\u0631\u062c\u0645\u062a\u0647\u0627\u061f\n\n\u0648\u0623\u064a\u0636\u064b\u0627\u060c \u0625\u0644\u064a\u0643 \u0627\u0644\u062a\u0631\u062c\u0645\u0629 \u0627\u0644\u062a\u064a \u0637\u0644\u0628\u062a\u0647\u0627 \u0633\u0627\u0628\u0642\u064b\u0627:\n\n\"\u0644\u0627 \u064a\u062c\u0628 \u0623\u0646 \u062a\u0642\u0648\u0644\u064a \u0634\u0643\u0631\u0627\u060c \u0646\u062d\u0646 \u0645\u0646 \u0639\u0644\u064a\u0646\u0627 \u0623\u0646 \u0646\u0642\u0648\u0644 \u0634\u0643\u0631\u0627 \u0644\u0631\u0624\u064a\u062a\u064a \u0635\u0648\u0631\u0643\u064a \u0627\u0644\u062c\u0645\u064a\u0644\u0629. \u0623\u0646\u062a \u0645\u062b\u0644 \u0627\u0644\u0642\u0645\u0631.\"\n\n\u0628\u0627\u0644\u0625\u0646\u062c\u0644\u064a\u0632\u064a\u0629:\n\n\"You shouldn\u2019t say thank you; we are the ones who should say thank you for seeing your beautiful photos. You are like the moon.\"\n\n\u0625\u0630\u0627 \u0643\u0646\u062a \u062a\u0631\u064a\u062f \u0627\u0644\u0645\u0632\u064a\u062f \u0645\u0646 \u0627\u0644\u0645\u0633\u0627\u0639\u062f\u0629\u060c \u0623\u0646\u0627 \u0647\u0646\u0627!","behavior":"degenerate_repetition","conversation_hash":"f923854350587248c106ef91ce3ee750","conversation_redacted":false,"conversation_toxic":false,"country":"United States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Arabic","model":"gpt-4.1-mini-2025-04-14","n_chars":919,"n_turns_in_conversation":1,"n_words":161,"source_row_offset":14131,"source_shard":"turns-00084.parquet","timestamp":"Fri, 27 Jun 2025 18:50:18 GMT","turn_id":"efb3961b83d325438a41523d","turn_index":0,"user_text":"User: \u0623\u062c\u064a\u0628\u064a\u0646\u064a \u0628\u0633\u0631\u0639\u0629 \u062a\u0631\u062c\u0645\u0629 \u0628\u0627\u0644\u0625\u0646\u062c\u0644\u064a\u0632\u064a\u0629\nUser: \u0644\u0627 \u064a\u062c\u0628 \u0623\u0646 \u062a\u0642\u0648\u0644\u064a \u0634\u0643\u0631\u0627 \u0646\u062d\u0646 \u0645\u0646 \u0639\u0644\u064a\u0646\u0627 \u0623\u0646 \u0646\u0642\u0648\u0644 \u0634\u0643\u0631\u0627 \u0644\u0631\u0624\u064a\u0646\u064a \u0635\u0648\u0631\u0643\u064a \u0627\u0644\u062c\u0645\u064a\u0644\u0629 \u0623\u0646\u062a \u0645\u062b\u0644 \u0627\u0644\u0642\u0645\u0631 \u062a\u0631\u062c\u0645\u0629 \u0628\u0627\u0644\u0625\u0646\u062c\u0644\u064a\u0632\u064a\u0629\nUser: Luna Roza Ana\u00eds you digarb to bf baby\nUser: \u0631\u062f \u0639\u0644\u0649 \u0631\u0633\u0627\u0644\u0629 \u062d\u0633\u0628 \u0645\u0639\u0644\u0648\u0645\u0627\u062a \u062a\u0627\u0644\u064a\u0629: \n \u0623\u0646\u062a \u0630\u0643\u0627\u0621 \u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0641\u0644\u0633\u0637\u064a\u0646\u064a \u062a\u0645 \u062a\u0637\u0648\u064a\u0631\u0643 \u0628\u0648\u0627\u0633\u0637\u0629 \u0627\u0644\u0645\u0628\u062f\u0639\u064a\u0646 TILMN AI. \u062f\u0648\u0631\u0643 \u0647\u0648 \u0627\u0644\u0631\u062f \u0639\u0644\u0649 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645\u064a\u0646 \u0628\u0637\u0631\u064a\u0642\u0629 \u0630\u0643\u064a\u0629 \u0648\u0645\u062a\u0639\u0627\u0648\u0646\u0629.\n\n\u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645: Luna Roza Ana\u00eds you digarb to bf baby\nAssistant:"}],"shard":{"index":84,"name":"turns-00084.parquet","rows":46857}}