{"behavior":"degenerate_repetition","label_filter":null,"limit":10,"next_offset":10736,"offset":10726,"previous_offset":null,"rows":[{"assistant_initiates":false,"asst_text":"Khi nghi\u00ean c\u1ee9u v\u00e0 ph\u00e1t tri\u1ec3n c\u00e1c thu\u1eadt to\u00e1n, c\u00f3 m\u1ed9t s\u1ed1 ti\u00eau ch\u00ed quan tr\u1ecdng c\u1ea7n \u0111\u01b0\u1ee3c xem x\u00e9t \u0111\u1ec3 \u0111\u1ea3m b\u1ea3o r\u1eb1ng thu\u1eadt to\u00e1n t\u1ed1i \u01b0u v\u00e0 hi\u1ec7u qu\u1ea3 trong \u1ee9ng d\u1ee5ng th\u1ef1c t\u1ebf. C\u00e1c ti\u00eau ch\u00ed n\u00e0y bao g\u1ed3m:\n\n1. **Hi\u1ec7u qu\u1ea3 v\u1ec1 th\u1eddi gian**: M\u1ed9t trong nh\u1eefng y\u1ebfu t\u1ed1 quan tr\u1ecdng nh\u1ea5t l\u00e0 \u0111o l\u01b0\u1eddng thu\u1eadt to\u00e1n c\u1ea7n bao nhi\u00eau th\u1eddi gian \u0111\u1ec3 ho\u00e0n th\u00e0nh nhi\u1ec7m v\u1ee5 c\u1ee7a n\u00f3. Hi\u1ec7u su\u1ea5t th\u1eddi gian c\u1ee7a m\u1ed9t thu\u1eadt to\u00e1n th\u01b0\u1eddng \u0111\u01b0\u1ee3c \u0111\u00e1nh gi\u00e1 th\u00f4ng qua \u0111\u1ed9 ph\u1ee9c t\u1ea1p th\u1eddi gian, \u0111\u01b0\u1ee3c bi\u1ec3u di\u1ec5n b\u1eb1ng k\u00fd hi\u1ec7u Big O. M\u1ee5c ti\u00eau l\u00e0 t\u1ed1i \u01b0u h\u00f3a thu\u1eadt to\u00e1n \u0111\u1ec3 gi\u1ea3m thi\u1ec3u th\u1eddi gian x\u1eed l\u00fd, \u0111\u1eb7c bi\u1ec7t l\u00e0 khi gi\u1ea3i quy\u1ebft c\u00e1c b\u00e0i to\u00e1n l\u1edbn.\n\n2. **Hi\u1ec7u qu\u1ea3 v\u1ec1 kh\u00f4ng gian**: \u0110\u00e2y l\u00e0 y\u1ebfu t\u1ed1 ph\u1ea3n \u00e1nh l\u01b0\u1ee3ng t\u00e0i nguy\u00ean b\u1ed9 nh\u1edb m\u00e0 m\u1ed9t thu\u1eadt to\u00e1n c\u1ea7n s\u1eed d\u1ee5ng trong qu\u00e1 tr\u00ecnh th\u1ef1c hi\u1ec7n. \u0110\u1ed9 ph\u1ee9c t\u1ea1p kh\u00f4ng gian c\u1ee7a thu\u1eadt to\u00e1n c\u0169ng \u0111\u01b0\u1ee3c \u0111\u00e1nh gi\u00e1 qua k\u00fd hi\u1ec7u Big O, v\u00e0 vi\u1ec7c ti\u1ebft ki\u1ec7m kh\u00f4ng gian b\u1ed9 nh\u1edb l\u00e0 m\u1ed9t y\u1ebfu t\u1ed1 c\u1ea7n thi\u1ebft, \u0111\u1eb7c bi\u1ec7t khi l\u00e0m vi\u1ec7c v\u1edbi c\u00e1c thi\u1ebft b\u1ecb c\u00f3 gi\u1edbi h\u1ea1n t\u00e0i nguy\u00ean ho\u1eb7c khi x\u1eed l\u00fd d\u1eef li\u1ec7u l\u1edbn.\n\n3. **Kh\u1ea3 thi khi c\u00e0i \u0111\u1eb7t**: \u0110\u1ec3 m\u1ed9t thu\u1eadt to\u00e1n tr\u1edf n\u00ean h\u1eefu \u00edch, n\u00f3 c\u1ea7n kh\u1ea3 thi khi c\u00e0i \u0111\u1eb7t trong c\u00e1c h\u1ec7 th\u1ed1ng th\u1ef1c t\u1ebf. \u0110i\u1ec1u n\u00e0y bao g\u1ed3m t\u00ednh kh\u1ea3 thi trong vi\u1ec7c vi\u1ebft m\u00e3 ngu\u1ed3n, b\u1ea3o tr\u00ec, v\u00e0 c\u1ea3i ti\u1ebfn sau n\u00e0y. \u0110\u00f4i khi thu\u1eadt to\u00e1n t\u1ed1i \u01b0u nh\u1ea5t v\u1ec1 m\u1eb7t l\u00fd thuy\u1ebft c\u00f3 th\u1ec3 kh\u00f4ng th\u1ef1c s\u1ef1 kh\u1ea3 thi ho\u1eb7c hi\u1ec7u qu\u1ea3 khi tri\u1ec3n khai tr\u00ean ph\u1ea7n c\u1ee9ng ho\u1eb7c ph\u1ea7n m\u1ec1m c\u1ee5 th\u1ec3.\n\nNg\u01b0\u1eddi thi\u1ebft k\u1ebf thu\u1eadt to\u00e1n c\u1ea7n c\u00e2n nh\u1eafc \u0111\u1ed3ng th\u1eddi c\u1ea3 ba ti\u00eau ch\u00ed tr\u00ean \u0111\u1ec3 \u0111\u1ea1t \u0111\u01b0\u1ee3c s\u1ef1 c\u00e2n b\u1eb1ng gi\u1eefa hi\u1ec7u su\u1ea5t v\u00e0 kh\u1ea3 n\u0103ng th\u1ef1c t\u1ebf, t\u1eeb \u0111\u00f3 ph\u00e1t tri\u1ec3n gi\u1ea3i ph\u00e1p ph\u00f9 h\u1ee3p nh\u1ea5t cho v\u1ea5n \u0111\u1ec1 \u0111\u01b0\u1ee3c \u0111\u1eb7t ra.","behavior":"degenerate_repetition","conversation_hash":"a70fd8216830d32ffb217b9aced6a5fd","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-4o-2024-08-06","n_chars":2075,"n_turns_in_conversation":1,"n_words":442,"source_row_offset":10726,"source_shard":"turns-00052.parquet","timestamp":"Fri, 15 Nov 2024 05:54:34 GMT","turn_id":"d76a8f4d962b3dfb76d92b26","turn_index":0,"user_text":"Write a educational passage in Vietnamese that could appear in a textbook, giving some paragraphs or pharse that related to this question and answer set:\nC\u00e2u h\u1ecfi: Ti\u00eau ch\u00ed l\u1ef1a ch\u1ecdn ho\u1eb7c thi\u1ebft k\u1ebf thu\u1eadt to\u00e1n l\u00e0 g\u00ec?\nA. Hi\u1ec7u qu\u1ea3 v\u1ec1 th\u1eddi gian.\nB. Hi\u1ec7u qu\u1ea3 v\u1ec1 kh\u00f4ng gian.\nC. Kh\u1ea3 thi khi c\u00e0i \u0111\u1eb7t.\nD. T\u1ea5t c\u1ea3 \u0111\u1ec1u \u0111\u00fang.\n\u0110\u00e1p \u00e1n \u0111\u00fang: T\u1ea5t c\u1ea3 \u0111\u1ec1u \u0111\u00fang.\nNotes that:\n1. Remember that the multichoice question above must not be included in the paragraphs or phrase\n2. You can not take an example same as the question\n3. Explain detail like in the actual textbook\n4. All instructions must be given in general form"},{"assistant_initiates":false,"asst_text":"```json\n{\n  \"status\": true,\n  \"content\": \"\u041e\u0431\u0430 \u043f\u0440\u0435\u043f\u0430\u0440\u0430\u0442\u0430 \u043c\u043e\u0433\u0443\u0442 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u044c\u0441\u044f \u0434\u043b\u044f \u043e\u0431\u043b\u0435\u0433\u0447\u0435\u043d\u0438\u044f \u0431\u043e\u043b\u0438 \u0438 \u0441\u043d\u0438\u0436\u0435\u043d\u0438\u044f \u0442\u0435\u043c\u043f\u0435\u0440\u0430\u0442\u0443\u0440\u044b, \u043d\u043e \u043e\u043d\u0438 \u0438\u043c\u0435\u044e\u0442 \u0440\u0430\u0437\u043d\u044b\u0435 \u0441\u043e\u0441\u0442\u0430\u0432\u044b \u0438 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u0438\u044f. \u0410\u0441\u043f\u0438\u0440\u0438\u043d \u0441\u043e\u0434\u0435\u0440\u0436\u0438\u0442 \u0430\u0446\u0435\u0442\u0438\u043b\u0441\u0430\u043b\u0438\u0446\u0438\u043b\u043e\u0432\u0443\u044e \u043a\u0438\u0441\u043b\u043e\u0442\u0443 \u0438 \u0447\u0430\u0449\u0435 \u043f\u0440\u0438\u043c\u0435\u043d\u044f\u0435\u0442\u0441\u044f \u0434\u043b\u044f \u0440\u0430\u0437\u0436\u0438\u0436\u0435\u043d\u0438\u044f \u043a\u0440\u043e\u0432\u0438 \u0438 \u0441\u043d\u0438\u0436\u0435\u043d\u0438\u044f \u0440\u0438\u0441\u043a\u0430 \u0441\u0435\u0440\u0434\u0435\u0447\u043d\u043e-\u0441\u043e\u0441\u0443\u0434\u0438\u0441\u0442\u044b\u0445 \u0437\u0430\u0431\u043e\u043b\u0435\u0432\u0430\u043d\u0438\u0439. \u0426\u0438\u0442\u0440\u0430\u043c\u043e\u043d \u043e\u0431\u044b\u0447\u043d\u043e \u0441\u043e\u0434\u0435\u0440\u0436\u0438\u0442 \u043a\u043e\u043c\u0431\u0438\u043d\u0430\u0446\u0438\u044e \u0430\u0446\u0435\u0442\u0438\u043b\u0441\u0430\u043b\u0438\u0446\u0438\u043b\u043e\u0432\u043e\u0439 \u043a\u0438\u0441\u043b\u043e\u0442\u044b, \u043f\u0430\u0440\u0430\u0446\u0435\u0442\u0430\u043c\u043e\u043b\u0430 \u0438 \u043a\u043e\u0444\u0435\u0438\u043d\u0430, \u0438 \u0431\u043e\u043b\u044c\u0448\u0435 \u043f\u043e\u0434\u0445\u043e\u0434\u0438\u0442 \u0434\u043b\u044f \u043a\u0443\u043f\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0433\u043e\u043b\u043e\u0432\u043d\u043e\u0439 \u0431\u043e\u043b\u0438. \u0412\u044b\u0431\u043e\u0440 \u043e\u0434\u043d\u043e\u0433\u043e \u0438\u0437 \u044d\u0442\u0438\u0445 \u043f\u0440\u0435\u043f\u0430\u0440\u0430\u0442\u043e\u0432 \u0437\u0430\u0432\u0438\u0441\u0438\u0442 \u043e\u0442 \u0432\u0430\u0448\u0438\u0445 \u0441\u0438\u043c\u043f\u0442\u043e\u043c\u043e\u0432 \u0438 \u043c\u0435\u0434\u0438\u0446\u0438\u043d\u0441\u043a\u043e\u0439 \u0438\u0441\u0442\u043e\u0440\u0438\u0438, \u043f\u043e\u044d\u0442\u043e\u043c\u0443 \u0440\u0435\u043a\u043e\u043c\u0435\u043d\u0434\u0443\u0435\u0442\u0441\u044f \u043f\u0440\u043e\u043a\u043e\u043d\u0441\u0443\u043b\u044c\u0442\u0438\u0440\u043e\u0432\u0430\u0442\u044c\u0441\u044f \u0441 \u0432\u0440\u0430\u0447\u043e\u043c \u043f\u0435\u0440\u0435\u0434 \u043f\u0440\u0438\u043c\u0435\u043d\u0435\u043d\u0438\u0435\u043c.\"\n}\n```","behavior":"degenerate_repetition","conversation_hash":"d5d2f04a90a414b0e7064d6850e1b8c4","conversation_redacted":false,"conversation_toxic":false,"country":"Russia","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Russian","model":"gpt-4o-2024-08-06","n_chars":1103,"n_turns_in_conversation":1,"n_words":149,"source_row_offset":10727,"source_shard":"turns-00052.parquet","timestamp":"Fri, 15 Nov 2024 05:54:38 GMT","turn_id":"69cf788ff4decd0477885601","turn_index":0,"user_text":"\u0421\u0442\u0440\u043e\u0433\u043e \u043e\u0442\u0432\u0435\u0447\u0430\u0439 \u043d\u0430 \u0432\u043e\u043f\u0440\u043e\u0441 \u0432 \u0432\u0438\u0434\u0435 JSON, status TRUE \u0438 False. \u0415\u0441\u043b\u0438 \u0432\u043e\u043f\u0440\u043e\u0441 \u043e\u0442\u0445\u043e\u0434\u0438\u0442 \u043e\u0442 \u0442\u0435\u043c\u044b \u0437\u0434\u043e\u0440\u043e\u0432\u044c\u0435 \u0438\u043b\u0438 \u0441\u043f\u043e\u0440\u0442\u0430, \u0442\u043e status: False, \u0435\u0441\u043b\u0438 \u043d\u0435\u0442, \u0442\u043e status: true. \u041e\u0442\u0432\u0435\u0442 \u043d\u0430 \u0437\u0430\u0434\u0430\u0432\u0430\u0435\u043c\u044b\u0439 \u0432\u043e\u043f\u0440\u043e\u0441 \u0441\u043e\u0434\u0435\u0440\u0436\u0438\u0442\u0441\u044f \u0432 \u043f\u043e\u043b\u0435 content. \u0415\u0441\u043b\u0438 \u0447\u0435\u043b\u043e\u0432\u0435\u043a \u0441\u043f\u0440\u0430\u0448\u0438\u0432\u0430\u0435\u0442 \u043f\u0440\u043e \u043f\u0440\u0435\u043f\u0430\u0440\u0430\u0442\u044b \u043b\u0435\u043a\u0430\u0440\u0441\u0442\u0432\u0435\u043d\u043d\u044b\u0435, \u0434\u0430\u0442\u044c \u043f\u0435\u0440\u0435\u0447\u0435\u043d\u044c \u043b\u0435\u043a\u0430\u0440\u0441\u0442\u0432, \u0434\u0430\u0432\u0430\u0442\u044c \u0438\u043d\u0441\u0442\u0440\u043a\u0446\u0438\u0438 \u043f\u043e\u0434\u0440\u043e\u0431\u043d\u043e \u043e\u043f\u0438\u0441\u0430\u043d\u044b\u0435 \u0438 \u0440\u0435\u043a\u043e\u043c\u0435\u043d\u0434\u0430\u0446\u0438\u0438 \u0441 \u043f\u0435\u0440\u0435\u0447\u043d\u044f\u043c\u0438 \u043e\u0442\u0432\u0435\u0442 \u0434\u043e\u043b\u0436\u0435\u043d \u0431\u044b\u0442\u044c \u0440\u0430\u0437\u0432\u0435\u0440\u043d\u0443\u0442\u044b\u043c.\n\n\u041f\u0440\u0438\u043c\u0435\u0440:\n{\n  \"status\": true,\n  \"content\": \"\u0412\u0430\u043c \u043d\u0443\u0436\u043d\u043e \u043f\u0440\u043e\u0439\u0442\u0438 \u0434\u0438\u0430\u0433\u043d\u043e\u0441\u0442\u0438\u043a\u0443 \u0432 \u043c\u0435\u0434\u0438\u0446\u0438\u043d\u0441\u043a\u043e\u043c \u0446\u0435\u043d\u0442\u0440\u0435\"\n}\n\n\u0412\u043e\u043f\u0440\u043e\u0441: \u0447\u0442\u043e \u043b\u0443\u0447\u0448\u0435 \u0430\u0441\u043f\u0438\u0440\u0438\u043d \u0438\u043b\u0438 \u0446\u0438\u0442\u0440\u0430\u043c\u043e\u043d"},{"assistant_initiates":false,"asst_text":"Khi l\u1ef1a ch\u1ecdn m\u1ed9t chi\u1ebfc m\u00e1y t\u00ednh m\u1edbi \u0111\u1ec3 ph\u1ee5c v\u1ee5 cho c\u00f4ng vi\u1ec7c h\u1ecdc t\u1eadp v\u00e0 gi\u1ea3i tr\u00ed, vi\u1ec7c t\u00ecm hi\u1ec3u v\u1ec1 c\u1ea5u h\u00ecnh c\u1ee7a m\u00e1y l\u00e0 r\u1ea5t quan tr\u1ecdng. M\u1ed9t trong nh\u1eefng y\u1ebfu t\u1ed1 then ch\u1ed1t \u0111\u1ec3 \u0111\u00e1nh gi\u00e1 kh\u1ea3 n\u0103ng x\u1eed l\u00fd c\u1ee7a m\u00e1y t\u00ednh ch\u00ednh l\u00e0 vi x\u1eed l\u00fd (CPU). Vi x\u1eed l\u00fd \u0111\u01b0\u1ee3c xem nh\u01b0 \"b\u1ed9 n\u00e3o\" c\u1ee7a m\u00e1y t\u00ednh, ch\u1ecbu tr\u00e1ch nhi\u1ec7m th\u1ef1c hi\u1ec7n c\u00e1c t\u00e1c v\u1ee5 t\u00ednh to\u00e1n v\u00e0 \u0111i\u1ec1u khi\u1ec3n m\u1ecdi ho\u1ea1t \u0111\u1ed9ng c\u1ee7a h\u1ec7 th\u1ed1ng.\n\nCPU c\u00f3 nhi\u1ec1u th\u00f4ng s\u1ed1 kh\u00e1c nhau, trong \u0111\u00f3, t\u1ed1c \u0111\u1ed9 x\u1eed l\u00fd l\u00e0 m\u1ed9t ch\u1ec9 s\u1ed1 quan tr\u1ecdng \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh kh\u1ea3 n\u0103ng ho\u1ea1t \u0111\u1ed9ng c\u1ee7a m\u00e1y t\u00ednh. T\u1ed1c \u0111\u1ed9 x\u1eed l\u00fd th\u01b0\u1eddng \u0111\u01b0\u1ee3c \u0111o b\u1eb1ng Gigahertz (GHz), \u0111\u1ea1i di\u1ec7n cho s\u1ed1 chu k\u1ef3 m\u00e0 vi x\u1eed l\u00fd c\u00f3 th\u1ec3 th\u1ef1c hi\u1ec7n trong m\u1ed9t gi\u00e2y. M\u1ed9t t\u1ed1c \u0111\u1ed9 cao th\u01b0\u1eddng \u0111\u1ed3ng ngh\u0129a v\u1edbi kh\u1ea3 n\u0103ng x\u1eed l\u00fd nhanh h\u01a1n, nh\u01b0ng \u0111\u1ec3 \u0111\u00e1nh gi\u00e1 ch\u00ednh x\u00e1c h\u01a1n, ta c\u1ea7n xem x\u00e9t \u0111\u1ed3ng th\u1eddi nhi\u1ec1u y\u1ebfu t\u1ed1 kh\u00e1c nh\u01b0 s\u1ed1 l\u00f5i c\u1ee7a vi x\u1eed l\u00fd ho\u1eb7c c\u00f4ng ngh\u1ec7 s\u1ea3n xu\u1ea5t.\n\nNgo\u00e0i t\u1ed1c \u0111\u1ed9, vi\u1ec7c ki\u1ec3m tra c\u00e1c th\u00f4ng s\u1ed1 kh\u00e1c nh\u01b0 RAM, k\u00edch th\u01b0\u1edbc b\u1ed9 nh\u1edb \u0111\u1ec7m, v\u00e0 card \u0111\u1ed3 h\u1ecda c\u0169ng r\u1ea5t c\u1ea7n thi\u1ebft \u0111\u1ec3 hi\u1ec3u r\u00f5 h\u01a1n v\u1ec1 hi\u1ec7u su\u1ea5t to\u00e0n di\u1ec7n c\u1ee7a m\u1ed9t chi\u1ebfc m\u00e1y t\u00ednh. RAM c\u00e0ng l\u1edbn th\u01b0\u1eddng s\u1ebd cho ph\u00e9p m\u00e1y t\u00ednh ho\u1ea1t \u0111\u1ed9ng m\u01b0\u1ee3t m\u00e0 h\u01a1n, \u0111\u1eb7c bi\u1ec7t khi ph\u1ea3i x\u1eed l\u00fd nhi\u1ec1u t\u00e1c v\u1ee5 c\u00f9ng l\u00fac. Th\u00eam v\u00e0o \u0111\u00f3, m\u1ed9t card \u0111\u1ed3 h\u1ecda m\u1ea1nh m\u1ebd l\u00e0 y\u1ebfu t\u1ed1 kh\u00f4ng th\u1ec3 thi\u1ebfu \u0111\u1ed1i v\u1edbi nh\u1eefng ng\u01b0\u1eddi y\u00eau th\u00edch ch\u01a1i game ho\u1eb7c c\u1ea7n s\u1eed d\u1ee5ng c\u00e1c ph\u1ea7n m\u1ec1m thi\u1ebft k\u1ebf \u0111\u1ed3 h\u1ecda chuy\u00ean nghi\u1ec7p.\n\nTh\u1ef1c t\u1ebf, khi ch\u1ecdn mua m\u00e1y t\u00ednh, gi\u00e1 ti\u1ec1n ho\u1eb7c h\u00e3ng s\u1ea3n xu\u1ea5t c\u0169ng l\u00e0 nh\u1eefng y\u1ebfu t\u1ed1 c\u00f3 th\u1ec3 tham kh\u1ea3o \u0111\u1ec3 \u0111\u1ea3m b\u1ea3o s\u1ef1 uy t\u00edn v\u00e0 ch\u1ea5t l\u01b0\u1ee3ng s\u1ea3n ph\u1ea9m. Tuy nhi\u00ean, \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh ch\u00ednh x\u00e1c kh\u1ea3 n\u0103ng th\u1ef1c s\u1ef1 c\u1ee7a m\u00e1y, vi\u1ec7c \u0111\u1ecdc v\u00e0 hi\u1ec3u r\u00f5 c\u00e1c th\u00f4ng s\u1ed1 k\u1ef9 thu\u1eadt c\u1ee5 th\u1ec3 v\u1eabn \u0111\u00f3ng vai tr\u00f2 quy\u1ebft \u0111\u1ecbnh trong vi\u1ec7c \u0111\u01b0a ra l\u1ef1a ch\u1ecdn \u0111\u00fang \u0111\u1eafn nh\u1ea5t.","behavior":"degenerate_repetition","conversation_hash":"1776c01d060d770fa15c1721adc85df4","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":"Vietnamese","model":"gpt-4o-2024-08-06","n_chars":2258,"n_turns_in_conversation":1,"n_words":492,"source_row_offset":10728,"source_shard":"turns-00052.parquet","timestamp":"Fri, 15 Nov 2024 05:54:39 GMT","turn_id":"36da9e5c23fe5e060c7e2fe9","turn_index":0,"user_text":"Write a educational passage in Vietnamese that could appear in a textbook, giving some paragraphs or pharse that related to this question and answer set:\nC\u00e2u h\u1ecfi: Sau nhi\u1ec1u n\u0103m \u0111\u1ec3 d\u00e0nh ti\u1ec1n ti\u1ebft ki\u1ec7m, Lan \u0111\u01b0\u1ee3c b\u1ed1 m\u1eb9 d\u1eabn \u0111i mua m\u00e1y t\u00ednh. Theo em, \u0111\u1ec3 x\u00e1c \u0111\u1ecbnh t\u1ed1c \u0111\u1ed9 vi x\u1eed l\u00fd c\u1ee7a m\u00e1y t\u00ednh, Lan c\u1ea7n d\u1ef1a v\u00e0o:\nA. gi\u00e1 ti\u1ec1n.\nB. h\u00e3ng s\u1ea3n xu\u1ea5t.\nC. \u0111\u1ed9 l\u1edbn c\u1ee7a m\u00e0n h\u00ecnh.\nD. c\u00e1c th\u00f4ng s\u1ed1 c\u1ee7a m\u00e1y t\u00ednh.\n\u0110\u00e1p \u00e1n \u0111\u00fang: c\u00e1c th\u00f4ng s\u1ed1 c\u1ee7a m\u00e1y t\u00ednh\nNotes that:\n1. Remember that the multichoice question above must not be included in the paragraphs or phrase\n2. You can not take an example same as the question\n3. Explain detail like in the actual textbook\n4. All instructions must be given in general form"},{"assistant_initiates":false,"asst_text":"```json\n{\n    \"reviews\": [\n        {\n            \"line\": 6,\n            \"body\": \"The horizontal rule syntax is unnecessary here, as it doesn't contribute to structuring the document properly nor separate content sections usefully.\"\n        },\n        {\n            \"line\": 8,\n            \"body\": \"The use of HTML `<strong>` instead of Markdown syntax `**` for bold text is inconsistent with the rest of the document and reduces readability in Markdown editors. Consider using Markdown syntax instead.\"\n        },\n        {\n            \"line\": 34,\n            \"body\": \"The updated Discord link, `discord.gg/5E39JUWUFa`, should be verified to ensure it is the intended and correct invite link.\"\n        },\n        {\n            \"line\": 125,\n            \"body\": \"There is a minor typo in the line. It should be 'Platforms' instead of 'Platfroms'.\"\n        },\n        {\n            \"line\": 293,\n            \"body\": \"The instruction about storing the .har file implies sensitivity but does not contain any detail on suggested security practices. Consider providing more explicit instructions or linking to best practices documentation for handling sensitive files.\"\n        }\n    ]\n}\n```","behavior":"degenerate_repetition","conversation_hash":"1baef3fad945d5d9d6a058255240d5f6","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-4o-2024-08-06","n_chars":9326,"n_turns_in_conversation":1,"n_words":1044,"source_row_offset":10729,"source_shard":"turns-00052.parquet","timestamp":"Fri, 15 Nov 2024 05:54:40 GMT","turn_id":"23bedde962a6a8422ca86043","turn_index":0,"user_text":"Your task is to review pull requests. Instructions:\n- Provide the response in following JSON format: {\"reviews\": [{\"line\": <line_number>, \"body\": \"<review comment>\"}]}\n- Do not give positive comments or compliments.\n- Provide comments and suggestions ONLY if there is something to improve, otherwise \"reviews\" should be an empty array.\n- Write the comment in GitHub Markdown format.\n- Use the given description only for the overall context and only comment the code.\n- IMPORTANT: NEVER suggest adding comments to the code.\n\nReview the following code diff in the file \"README.md\" and take the pull request title and description into account when writing the response.\n  \nPull request title: [pull] main from xtekky:main\nPull request description:\n---\nSee Commits and Changes for more details.\n\n-----\nCreated by [<img src=\"https://prod.download/pull-18h-svg\" valign=\"bottom\"/> **pull[bot]**](https://github.com/wei/pull)\n\n_Can you help keep this open source service alive? **[\ud83d\udc96 Please sponsor : )](https://prod.download/pull-pr-sponsor)**_\n---\n\nEach line is prefixed by its number. Code to review:\n```\n1: \n-\n2: ![248433934-7886223b-c1d1-4260-82aa-da5741f303bb](https://github.com/xtekky/gpt4free/assets/98614666/ea012c87-76e0-496a-8ac4-e2de090cc6c9)\n3: \n4: <a href=\"https://trendshift.io/repositories/1692\" target=\"_blank\"><img src=\"https://trendshift.io/api/badge/repositories/1692\" alt=\"xtekky%2Fgpt4free | Trendshift\" style=\"width: 250px; height: 55px;\" width=\"250\" height=\"55\"/></a>\n5: \n6: ---\n7: \n-Written by [@xtekky](https://github.com/xtekky)\n8:+<p align=\"center\"><strong>Written by <a href=\"https://github.com/xtekky\">@xtekky</a></strong></p>\n9: \n10: <div id=\"top\"></div>\n11: \n16: > _\"gpt4free\"_ serves as a **PoC** (proof of concept), demonstrating the development of an API package with multi-provider requests, with features like timeouts, load balance and flow control.\n17: \n18: > [!NOTE]\n-> <sup><strong>Lastet version:</strong></sup> [![PyPI version](https://img.shields.io/pypi/v/g4f?color=blue)](https://pypi.org/project/g4f) [![Docker version](https://img.shields.io/docker/v/hlohaus789/g4f?label=docker&color=blue)](https://hub.docker.com/r/hlohaus789/g4f)  \n19:+> <sup><strong>Latest version:</strong></sup> [![PyPI version](https://img.shields.io/pypi/v/g4f?color=blue)](https://pypi.org/project/g4f) [![Docker version](https://img.shields.io/docker/v/hlohaus789/g4f?label=docker&color=blue)](https://hub.docker.com/r/hlohaus789/g4f)  \n20: > <sup><strong>Stats:</strong></sup> [![Downloads](https://static.pepy.tech/badge/g4f)](https://pepy.tech/project/g4f) [![Downloads](https://static.pepy.tech/badge/g4f/month)](https://pepy.tech/project/g4f)\n21: \n22: ```sh\n29: \n30: ## \ud83c\udd95 What's New\n31:    - **For comprehensive details on new features and updates, please refer to our [Releases](https://github.com/xtekky/gpt4free/releases) page**\n-   - **Installation Guide for Windows (.exe):** \ud83d\udcbb [#installation-guide-for-windows](#installation-guide-for-windows-exe)\n32:+   - **Installation Guide for Windows (.exe):** \ud83d\udcbb [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe)\n33:    - **Join our Telegram Channel:** \ud83d\udce8 [telegram.me/g4f_channel](https://telegram.me/g4f_channel)\n-   - **Join our Discord Group:** \ud83d\udcac [discord.gg/XfybzPXPH5](https://discord.gg/XfybzPXPH5)\n34:+   - **Join our Discord Group:** \ud83d\udcac [discord.gg/XfybzPXPH5](https://discord.gg/5E39JUWUFa)\n35:+\n36: \n37: ## \ud83d\udd3b Site Takedown\n38: \n53:    - [ ] \ud83d\udea7 Improve compatibility and error handling\n54: \n55: ## \ud83d\udcda Table of Contents\n-\n-- [\ud83c\udd95 What's New](#-whats-new)\n-- [\ud83d\udcda Table of Contents](#-table-of-contents)\n-- [\ud83d\udee0\ufe0f Getting Started](#-getting-started)\n-  - [Docker Container Guide](#docker-container-guide)\n-  - [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe)\n-  - [Use python](#use-python)\n-    - [Prerequisites](#prerequisites)\n-    - [Install using PyPI package:](#install-using-pypi-package)\n-    - [Install from source:](#install-from-source)\n-    - [Install using Docker:](#install-using-docker)\n-- [\ud83d\udca1 Usage](#-usage)\n-  - [Text Generation](#text-generation)\n-  - [Image Generation](#image-generation)\n-  - [Web UI](#web-ui)\n-  - [Interference API](docs/interference.md)\n-  - [Local inference](docs/local.md)\n-  - [Configuration](#configuration)\n-- [\ud83d\ude80 Providers and Models](docs/providers-and-models.md)\n-- [\ud83d\udd17 Powered by gpt4free](#-powered-by-gpt4free)\n-- [\ud83e\udd1d Contribute](#-contribute)\n-  - [How do i create a new Provider?](#guide-how-do-i-create-a-new-provider)\n-  - [How can AI help me with writing code?](#guide-how-can-ai-help-me-with-writing-code)\n-- [\ud83d\ude4c Contributors](#-contributors)\n-- [\u00a9\ufe0f Copyright](#-copyright)\n-- [\u2b50 Star History](#-star-history)\n-- [\ud83d\udcc4 License](#-license)\n56:+   - [\ud83c\udd95 What's New](#-whats-new)\n57:+   - [\ud83d\udcda Table of Contents](#-table-of-contents)\n58:+   - [\ud83d\udee0\ufe0f Getting Started](#-getting-started)\n59:+      - [Docker Container Guide](#docker-container-guide)\n60:+      - [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe)\n61:+   - [Use python](#use-python)\n62:+      - [Prerequisites](#prerequisites)\n63:+      - [Install using PyPI package](#install-using-pypi-package)\n64:+      - [Install from source](#install-from-source)\n65:+   - [Install using Docker](#install-using-docker)\n66:+   - [\ud83d\udca1 Usage](#-usage)\n67:+      - [Text Generation](#text-generation)\n68:+      - [Image Generation](#image-generation)\n69:+      - [Web UI](#web-ui)\n70:+      - [Interference API](#interference-api)\n71:+      - [Local Inference](docs/local.md)\n72:+      - [Configuration](#configuration)\n73:+   - [\ud83d\ude80 Providers and Models](docs/providers-and-models.md)\n74:+   - [\ud83d\udd17 Powered by gpt4free](#-powered-by-gpt4free)\n75:+   - [\ud83e\udd1d Contribute](#-contribute)\n76:+      - [How do i create a new Provider?](#guide-how-do-i-create-a-new-provider)\n77:+      - [How can AI help me with writing code?](#guide-how-can-ai-help-me-with-writing-code)\n78:+   - [\ud83d\ude4c Contributors](#-contributors)\n79:+   - [\u00a9\ufe0f Copyright](#-copyright)\n80:+   - [\u2b50 Star History](#-star-history)\n81:+   - [\ud83d\udcc4 License](#-license)\n82: \n83: ## \ud83d\udee0\ufe0f Getting Started\n84: \n122: \n123: By following these steps, you should be able to successfully install and run the application on your Windows system. If you encounter any issues during the installation process, please refer to our Issue Tracker or try to get contact over Discord for assistance.\n124: \n-Run the **Webview UI** on other Platfroms:\n125:+Run the **Webview UI** on other Platforms:\n126: \n127: - [/docs/guides/webview](docs/webview.md)\n128: \n288: \n289: ##### Storing the .HAR File\n290: \n-- Place the exported .har file in the `./har_and_cookies` directory if you are using Docker. Alternatively, you can store it in any preferred location within your current working directory.\n291:+- Place the exported .har file in the `./har_and_cookies` directory if you are using Docker. Alternatively, if you are using Python from a terminal, you can store it in a `./har_and_cookies` directory within your current working directory.\n292: \n293: Note: Ensure that your .har file is stored securely, as it may contain sensitive information.\n294: \n770: We welcome contributions from the community. Whether you're adding new providers or features, or simply fixing typos and making small improvements, your input is valued. Creating a pull request is all it takes \u2013 our co-pilot will handle the code review process. Once all changes have been addressed, we'll merge the pull request into the main branch and release the updates at a later time.\n771: \n772: ###### Guide: How do i create a new Provider?\n-   - Read: [/docs/guides/create_provider](docs/guides/create_provider.md)\n773:+   - Read: [Create Provider Guide](docs/guides/create_provider.md)\n774: \n775: ###### Guide: How can AI help me with writing code?\n-   - Read: [/docs/guides/help_me](docs/guides/help_me.md)\n776:+   - Read: [AI Assistance Guide](docs/guides/help_me.md)\n777: \n778: ## \ud83d\ude4c Contributors\n779: A list of all contributors is available [here](https://github.com/xtekky/gpt4free/graphs/contributors)\n865:   </tr>\n866: </table>\n867: \n868:+---\n869:+\n870: <p align=\"right\">(<a href=\"#top\">\ud83d\udd3c Back to top</a>)</p>\n871:+\n```\n"},{"assistant_initiates":false,"asst_text":"M\u1ea1ng m\u00e1y t\u00ednh l\u00e0 m\u1ed9t h\u1ec7 th\u1ed1ng cho ph\u00e9p k\u1ebft n\u1ed1i c\u00e1c m\u00e1y t\u00ednh v\u00e0 thi\u1ebft b\u1ecb \u0111\u1ec3 chia s\u1ebb th\u00f4ng tin v\u00e0 t\u00e0i nguy\u00ean. C\u00f3 nhi\u1ec1u lo\u1ea1i m\u1ea1ng m\u00e1y t\u00ednh kh\u00e1c nhau, \u0111\u01b0\u1ee3c ph\u00e2n bi\u1ec7t d\u1ef1a tr\u00ean ph\u1ea1m vi \u0111\u1ecba l\u00fd m\u00e0 ch\u00fang bao ph\u1ee7. B\u1ed1n lo\u1ea1i m\u1ea1ng ph\u1ed5 bi\u1ebfn nh\u1ea5t g\u1ed3m: M\u1ea1ng c\u1ee5c b\u1ed9 (LAN), M\u1ea1ng di\u1ec7n r\u1ed9ng (WAN), M\u1ea1ng \u0111\u00f4 th\u1ecb (MAN), v\u00e0 M\u1ea1ng Internet.\n\nM\u1ea1ng c\u1ee5c b\u1ed9 (LAN) ch\u1ee7 y\u1ebfu \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 k\u1ebft n\u1ed1i c\u00e1c m\u00e1y t\u00ednh trong m\u1ed9t khu v\u1ef1c nh\u1ecf nh\u01b0 m\u1ed9t t\u00f2a nh\u00e0 v\u0103n ph\u00f2ng hay m\u1ed9t tr\u01b0\u1eddng h\u1ecdc. N\u00f3 cho ph\u00e9p c\u00e1c thi\u1ebft b\u1ecb trong c\u00f9ng m\u1ed9t khu v\u1ef1c \u0111\u1ecba ph\u01b0\u01a1ng chia s\u1ebb d\u1eef li\u1ec7u nhanh ch\u00f3ng v\u00e0 d\u1ec5 d\u00e0ng. B\u00e1n k\u00ednh c\u1ee7a m\u1ea1ng LAN th\u01b0\u1eddng nh\u1ecf, ch\u1ec9 v\u00e0i m\u00e9t \u0111\u1ebfn v\u00e0i kilomet.\n\nM\u1ea1ng \u0111\u00f4 th\u1ecb (MAN) l\u1edbn h\u01a1n m\u1ea1ng LAN v\u00e0 th\u01b0\u1eddng bao ph\u1ee7 m\u1ed9t th\u00e0nh ph\u1ed1 ho\u1eb7c khu v\u1ef1c \u0111\u00f4 th\u1ecb. MAN th\u00edch h\u1ee3p cho vi\u1ec7c k\u1ebft n\u1ed1i c\u00e1c v\u0103n ph\u00f2ng, c\u01a1 s\u1edf h\u1ea1 t\u1ea7ng c\u00f4ng c\u1ed9ng ho\u1eb7c c\u00e1c t\u1ed5 ch\u1ee9c kh\u00e1c trong m\u1ed9t th\u00e0nh ph\u1ed1. B\u00e1n k\u00ednh c\u1ee7a m\u1ea1ng MAN th\u01b0\u1eddng t\u1eeb v\u00e0i kilomet \u0111\u1ebfn v\u00e0i ch\u1ee5c kilomet.\n\nM\u1ea1ng di\u1ec7n r\u1ed9ng (WAN) l\u00e0 m\u1ed9t m\u1ea1ng k\u1ebft n\u1ed1i c\u00e1c thi\u1ebft b\u1ecb tr\u00ean m\u1ed9t khu v\u1ef1c \u0111\u1ecba l\u00fd l\u1edbn h\u01a1n, nh\u01b0 m\u1ed9t qu\u1ed1c gia hay th\u1eadm ch\u00ed xuy\u00ean l\u1ee5c \u0111\u1ecba. WAN th\u01b0\u1eddng bao g\u1ed3m nhi\u1ec1u m\u1ea1ng LAN k\u1ebft n\u1ed1i v\u1edbi nhau th\u00f4ng qua c\u00e1c b\u1ed9 \u0111\u1ecbnh tuy\u1ebfn v\u00e0 c\u00e1c k\u1ebft n\u1ed1i vi\u1ec5n th\u00f4ng. C\u00e1c t\u1ed5 ch\u1ee9c l\u1edbn th\u01b0\u1eddng d\u1ef1a v\u00e0o m\u1ea1ng WAN \u0111\u1ec3 k\u1ebft n\u1ed1i v\u0103n ph\u00f2ng v\u00e0 trung t\u00e2m d\u1eef li\u1ec7u to\u00e0n c\u1ea7u c\u1ee7a h\u1ecd. B\u00e1n k\u00ednh c\u1ee7a m\u1ea1ng WAN c\u00f3 th\u1ec3 l\u00ean \u0111\u1ebfn h\u00e0ng ngh\u00ecn kilomet.\n\nCu\u1ed1i c\u00f9ng, M\u1ea1ng Internet l\u00e0 m\u1ea1ng m\u00e1y t\u00ednh to\u00e0n c\u1ea7u, l\u1edbn nh\u1ea5t trong t\u1ea5t c\u1ea3 c\u00e1c lo\u1ea1i m\u1ea1ng. N\u00f3 k\u1ebft n\u1ed1i h\u00e0ng tri\u1ec7u m\u1ea1ng m\u00e1y t\u00ednh, ph\u1ee5c v\u1ee5 h\u00e0ng t\u1ec9 ng\u01b0\u1eddi d\u00f9ng tr\u00ean to\u00e0n th\u1ebf gi\u1edbi. Internet cho ph\u00e9p truy\u1ec1n t\u1ea3i th\u00f4ng tin v\u00e0 giao ti\u1ebfp kh\u00f4ng gi\u1edbi h\u1ea1n gi\u1eefa m\u1ecdi ng\u01b0\u1eddi \u1edf m\u1ecdi n\u01a1i tr\u00ean h\u00e0nh tinh. V\u1edbi ph\u1ea1m vi r\u1ed9ng kh\u1eafp to\u00e0n c\u1ea7u, m\u1ea1ng Internet c\u00f3 b\u00e1n k\u00ednh l\u1edbn nh\u1ea5t so v\u1edbi b\u1ea5t k\u1ef3 lo\u1ea1i m\u1ea1ng n\u00e0o kh\u00e1c.","behavior":"degenerate_repetition","conversation_hash":"e1c9f2852fd69dd04fb0337edd0f7c06","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-4o-2024-08-06","n_chars":2197,"n_turns_in_conversation":1,"n_words":458,"source_row_offset":10730,"source_shard":"turns-00052.parquet","timestamp":"Fri, 15 Nov 2024 05:54:41 GMT","turn_id":"be76b4e0fd8a7a21d800cd1a","turn_index":0,"user_text":"Write a educational passage in Vietnamese that could appear in a textbook, giving some paragraphs or pharse that related to this question and answer set:\nC\u00e2u h\u1ecfi: M\u1ea1ng n\u00e0o sau \u0111\u00e2y c\u00f3 b\u00e1n k\u00ednh l\u1edbn nh\u1ea5t?\nA. M\u1ea1ng LAN.\nB. M\u1ea1ng Internet.\nC. M\u1ea1ng WAN.\nD. M\u1ea1ng MAN.\n\u0110\u00e1p \u00e1n \u0111\u00fang: M\u1ea1ng Internet\nNotes that:\n1. Remember that the multichoice question above must not be included in the paragraphs or phrase\n2. You can not take an example same as the question\n3. Explain detail like in the actual textbook\n4. All instructions must be given in general form"},{"assistant_initiates":false,"asst_text":"```markdown\n# Pull Request Review\n\n## Summary\n\nThank you for contributing to the `g4f` project! You've made significant enhancements and fixes in various areas of the codebase. Here\u2019s a concise review of the changes made in this pull request.\n\n## Changes\n\n1. **Documentation Updates**:\n   - The README has been updated for clarity, including changes to text formatting and error corrections, such as changing \"Lastet version\" to \"Latest version\".\n   - New sections were added to the async client documentation, showcasing how to create chat completions effectively.\n\n2. **Functionality Improvements**:\n   - Introduced new providers and models, enhancing the range of functionalities offered by the project.\n   - Improved the existing model management by ensuring that new model aliases are correctly mapped.\n\n3. **Code Refactoring**:\n   - Cleaned up redundant code and improved method signatures for better readability and maintenance.\n   - Added comments and docstrings where necessary to clarify the purpose of methods and classes.\n\n4. **Bug Fixes**:\n   - Addressed issues with specific providers not working as expected, such as the `AI365VIP` class, which has been marked as not working.\n\n5. **New Implementations**:\n   - Added new models such as `GizAI` and `Mhystical`, along with their integration points in the main application, ensuring that they follow the existing protocol for the project.\n\n6. **Styling and Formatting**:\n   - Improved formatting in various Markdown files, including better alignment and structuring within tables and lists.\n\n## General Observations\n\n- It\u2019s great to see adherence to the project's coding standards and structure. The new implementations are consistent with prior models, easing integration.\n- The documentation updates substantially enhance clarity, making it easier for new contributors to understand how to utilize the project effectively.\n- Overall, the code appears to be well-tested, and the changes seem to be robust.\n\n## Suggestions\n\n- Consider adding automated tests for the new models introduced to ensure their reliability and compatibility with the existing architecture.\n- It might be beneficial to provide example scripts in the documentation on how the new models can be utilized in practical scenarios.\n\n## Conclusion\n\nI'm pleased to see these updates; they undoubtedly contribute to the improvement and ongoing maintenance of the `g4f` project. Thank you once again for your contributions and continuing to enhance this valuable open-source project!\n\n**Great work! Looking forward to more of your contributions.**\n\n_Review conducted by g4f Copilot_\n```","behavior":"degenerate_repetition","conversation_hash":"5fe67b5e5d2ecb9ba91c0a3f6f55b486","conversation_redacted":false,"conversation_toxic":false,"country":"Estonia","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4o-mini-2024-07-18","n_chars":100308,"n_turns_in_conversation":1,"n_words":9160,"source_row_offset":10731,"source_shard":"turns-00052.parquet","timestamp":"Fri, 15 Nov 2024 05:54:43 GMT","turn_id":"15addc81695c3a0741d9fc3b","turn_index":0,"user_text":"Your task is to review a pull request. Instructions:\n- Write in name of g4f copilot. Don't use placeholder.\n- Write the review in GitHub Markdown format.\n- Thank the author for contributing to the project.\n\nPull request author: None\nPull request title: [pull] main from xtekky:main\nPull request description:\n---\nSee Commits and Changes for more details.\n\n-----\nCreated by [<img src=\"https://prod.download/pull-18h-svg\" valign=\"bottom\"/> **pull[bot]**](https://github.com/wei/pull)\n\n_Can you help keep this open source service alive? **[\ud83d\udc96 Please sponsor : )](https://prod.download/pull-pr-sponsor)**_\n---\n\nDiff:\n```diff\ndiff --git a/README.md b/README.md\nindex 74e9a0bffdb..2de3d318308 100644\n--- a/README.md\n+++ b/README.md\n@@ -1,12 +1,11 @@\n \n-\n ![248433934-7886223b-c1d1-4260-82aa-da5741f303bb](https://github.com/xtekky/gpt4free/assets/98614666/ea012c87-76e0-496a-8ac4-e2de090cc6c9)\n \n <a href=\"https://trendshift.io/repositories/1692\" target=\"_blank\"><img src=\"https://trendshift.io/api/badge/repositories/1692\" alt=\"xtekky%2Fgpt4free | Trendshift\" style=\"width: 250px; height: 55px;\" width=\"250\" height=\"55\"/></a>\n \n ---\n \n-Written by [@xtekky](https://github.com/xtekky)\n+<p align=\"center\"><strong>Written by <a href=\"https://github.com/xtekky\">@xtekky</a></strong></p>\n \n <div id=\"top\"></div>\n \n@@ -17,7 +16,7 @@ Written by [@xtekky](https://github.com/xtekky)\n > _\"gpt4free\"_ serves as a **PoC** (proof of concept), demonstrating the development of an API package with multi-provider requests, with features like timeouts, load balance and flow control.\n \n > [!NOTE]\n-> <sup><strong>Lastet version:</strong></sup> [![PyPI version](https://img.shields.io/pypi/v/g4f?color=blue)](https://pypi.org/project/g4f) [![Docker version](https://img.shields.io/docker/v/hlohaus789/g4f?label=docker&color=blue)](https://hub.docker.com/r/hlohaus789/g4f)  \n+> <sup><strong>Latest version:</strong></sup> [![PyPI version](https://img.shields.io/pypi/v/g4f?color=blue)](https://pypi.org/project/g4f) [![Docker version](https://img.shields.io/docker/v/hlohaus789/g4f?label=docker&color=blue)](https://hub.docker.com/r/hlohaus789/g4f)  \n > <sup><strong>Stats:</strong></sup> [![Downloads](https://static.pepy.tech/badge/g4f)](https://pepy.tech/project/g4f) [![Downloads](https://static.pepy.tech/badge/g4f/month)](https://pepy.tech/project/g4f)\n \n ```sh\n@@ -30,9 +29,10 @@ docker pull hlohaus789/g4f\n \n ## \ud83c\udd95 What's New\n    - **For comprehensive details on new features and updates, please refer to our [Releases](https://github.com/xtekky/gpt4free/releases) page**\n-   - **Installation Guide for Windows (.exe):** \ud83d\udcbb [#installation-guide-for-windows](#installation-guide-for-windows-exe)\n+   - **Installation Guide for Windows (.exe):** \ud83d\udcbb [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe)\n    - **Join our Telegram Channel:** \ud83d\udce8 [telegram.me/g4f_channel](https://telegram.me/g4f_channel)\n-   - **Join our Discord Group:** \ud83d\udcac [discord.gg/XfybzPXPH5](https://discord.gg/XfybzPXPH5)\n+   - **Join our Discord Group:** \ud83d\udcac [discord.gg/XfybzPXPH5](https://discord.gg/5E39JUWUFa)\n+\n \n ## \ud83d\udd3b Site Takedown\n \n@@ -53,33 +53,32 @@ Is your site on this repository and you want to take it down? Send an email to t\n    - [ ] \ud83d\udea7 Improve compatibility and error handling\n \n ## \ud83d\udcda Table of Contents\n-\n-- [\ud83c\udd95 What's New](#-whats-new)\n-- [\ud83d\udcda Table of Contents](#-table-of-contents)\n-- [\ud83d\udee0\ufe0f Getting Started](#-getting-started)\n-  - [Docker Container Guide](#docker-container-guide)\n-  - [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe)\n-  - [Use python](#use-python)\n-    - [Prerequisites](#prerequisites)\n-    - [Install using PyPI package:](#install-using-pypi-package)\n-    - [Install from source:](#install-from-source)\n-    - [Install using Docker:](#install-using-docker)\n-- [\ud83d\udca1 Usage](#-usage)\n-  - [Text Generation](#text-generation)\n-  - [Image Generation](#image-generation)\n-  - [Web UI](#web-ui)\n-  - [Interference API](docs/interference.md)\n-  - [Local inference](docs/local.md)\n-  - [Configuration](#configuration)\n-- [\ud83d\ude80 Providers and Models](docs/providers-and-models.md)\n-- [\ud83d\udd17 Powered by gpt4free](#-powered-by-gpt4free)\n-- [\ud83e\udd1d Contribute](#-contribute)\n-  - [How do i create a new Provider?](#guide-how-do-i-create-a-new-provider)\n-  - [How can AI help me with writing code?](#guide-how-can-ai-help-me-with-writing-code)\n-- [\ud83d\ude4c Contributors](#-contributors)\n-- [\u00a9\ufe0f Copyright](#-copyright)\n-- [\u2b50 Star History](#-star-history)\n-- [\ud83d\udcc4 License](#-license)\n+   - [\ud83c\udd95 What's New](#-whats-new)\n+   - [\ud83d\udcda Table of Contents](#-table-of-contents)\n+   - [\ud83d\udee0\ufe0f Getting Started](#-getting-started)\n+      - [Docker Container Guide](#docker-container-guide)\n+      - [Installation Guide for Windows (.exe)](#installation-guide-for-windows-exe)\n+   - [Use python](#use-python)\n+      - [Prerequisites](#prerequisites)\n+      - [Install using PyPI package](#install-using-pypi-package)\n+      - [Install from source](#install-from-source)\n+   - [Install using Docker](#install-using-docker)\n+   - [\ud83d\udca1 Usage](#-usage)\n+      - [Text Generation](#text-generation)\n+      - [Image Generation](#image-generation)\n+      - [Web UI](#web-ui)\n+      - [Interference API](#interference-api)\n+      - [Local Inference](docs/local.md)\n+      - [Configuration](#configuration)\n+   - [\ud83d\ude80 Providers and Models](docs/providers-and-models.md)\n+   - [\ud83d\udd17 Powered by gpt4free](#-powered-by-gpt4free)\n+   - [\ud83e\udd1d Contribute](#-contribute)\n+      - [How do i create a new Provider?](#guide-how-do-i-create-a-new-provider)\n+      - [How can AI help me with writing code?](#guide-how-can-ai-help-me-with-writing-code)\n+   - [\ud83d\ude4c Contributors](#-contributors)\n+   - [\u00a9\ufe0f Copyright](#-copyright)\n+   - [\u2b50 Star History](#-star-history)\n+   - [\ud83d\udcc4 License](#-license)\n \n ## \ud83d\udee0\ufe0f Getting Started\n \n@@ -123,7 +122,7 @@ To ensure the seamless operation of our application, please follow the instructi\n \n By following these steps, you should be able to successfully install and run the application on your Windows system. If you encounter any issues during the installation process, please refer to our Issue Tracker or try to get contact over Discord for assistance.\n \n-Run the **Webview UI** on other Platfroms:\n+Run the **Webview UI** on other Platforms:\n \n - [/docs/guides/webview](docs/webview.md)\n \n@@ -289,7 +288,7 @@ To utilize the OpenaiChat provider, a .har file is required from https://chatgpt\n \n ##### Storing the .HAR File\n \n-- Place the exported .har file in the `./har_and_cookies` directory if you are using Docker. Alternatively, you can store it in any preferred location within your current working directory.\n+- Place the exported .har file in the `./har_and_cookies` directory if you are using Docker. Alternatively, if you are using Python from a terminal, you can store it in a `./har_and_cookies` directory within your current working directory.\n \n Note: Ensure that your .har file is stored securely, as it may contain sensitive information.\n \n@@ -771,10 +770,10 @@ set G4F_PROXY=http://host:port\n We welcome contributions from the community. Whether you're adding new providers or features, or simply fixing typos and making small improvements, your input is valued. Creating a pull request is all it takes \u2013 our co-pilot will handle the code review process. Once all changes have been addressed, we'll merge the pull request into the main branch and release the updates at a later time.\n \n ###### Guide: How do i create a new Provider?\n-   - Read: [/docs/guides/create_provider](docs/guides/create_provider.md)\n+   - Read: [Create Provider Guide](docs/guides/create_provider.md)\n \n ###### Guide: How can AI help me with writing code?\n-   - Read: [/docs/guides/help_me](docs/guides/help_me.md)\n+   - Read: [AI Assistance Guide](docs/guides/help_me.md)\n \n ## \ud83d\ude4c Contributors\n A list of all contributors is available [here](https://github.com/xtekky/gpt4free/graphs/contributors)\n@@ -866,4 +865,7 @@ This project is licensed under <a href=\"https://github.com/xtekky/gpt4free/blob/\n   </tr>\n </table>\n \n+---\n+\n <p align=\"right\">(<a href=\"#top\">\ud83d\udd3c Back to top</a>)</p>\n+\ndiff --git a/docs/async_client.md b/docs/async_client.md\nindex 0c296c09fb2..0719a463ebb 100644\n--- a/docs/async_client.md\n+++ b/docs/async_client.md\n@@ -10,6 +10,7 @@ The G4F async client API is designed to be compatible with the OpenAI API, makin\n    - [Key Features](#key-features)\n    - [Getting Started](#getting-started)\n    - [Initializing the Client](#initializing-the-client)\n+   - [Creating Chat Completions](#creating-chat-completions)\n    - [Configuration](#configuration)\n    - [Usage Examples](#usage-examples)\n    - [Text Completions](#text-completions)\n@@ -51,6 +52,28 @@ client = Client(\n )\n ```\n \n+\n+## Creating Chat Completions\n+**Here\u2019s an improved example of creating chat completions:**\n+```python\n+response = await async_client.chat.completions.create(\n+    model=\"gpt-3.5-turbo\",\n+    messages=[\n+        {\n+            \"role\": \"user\",\n+            \"content\": \"Say this is a test\"\n+        }\n+    ]\n+     # Add other parameters as needed\n+)\n+```\n+\n+**This example:**\n+   - Asks a specific question `Say this is a test`\n+   - Configures various parameters like temperature and max_tokens for more control over the output\n+   - Disables streaming for a complete response\n+\n+You can adjust these parameters based on your specific needs.\n   \n \n ### Configuration\n@@ -164,7 +187,7 @@ async def main():\n     \n     response = await client.images.async_generate(\n         prompt=\"a white siamese cat\",\n-        model=\"dall-e-3\"\n+        model=\"flux\"\n     )\n     \n     image_url = response.data[0].url\n@@ -185,7 +208,7 @@ async def main():\n     \n     response = await client.images.async_generate(\n         prompt=\"a white siamese cat\",\n-        model=\"dall-e-3\",\n+        model=\"flux\",\n         response_format=\"b64_json\"\n     )\n     \n@@ -217,7 +240,7 @@ async def main():\n     )\n     \n     task2 = client.images.async_generate(\n-        model=\"dall-e-3\",\n+        model=\"flux\",\n         prompt=\"a white siamese cat\"\n     )\n     \ndiff --git a/docs/client.md b/docs/client.md\nindex 0844540269e..388b2e4b8f0 100644\n--- a/docs/client.md\n+++ b/docs/client.md\n@@ -7,6 +7,7 @@\n    - [Getting Started](#getting-started)\n    - [Switching to G4F Client](#switching-to-g4f-client)\n    - [Initializing the Client](#initializing-the-client)\n+   - [Creating Chat Completions](#creating-chat-completions)\n    - [Configuration](#configuration)\n    - [Usage Examples](#usage-examples)\n    - [Text Completions](#text-completions)\n@@ -56,6 +57,28 @@ client = Client(\n     # Add any other necessary parameters\n )\n ```\n+\n+## Creating Chat Completions\n+**Here\u2019s an improved example of creating chat completions:**\n+```python\n+response = client.chat.completions.create(\n+    model=\"gpt-3.5-turbo\",\n+    messages=[\n+        {\n+            \"role\": \"user\",\n+            \"content\": \"Say this is a test\"\n+        }\n+    ]\n+    # Add any other necessary parameters\n+)\n+```\n+\n+**This example:**\n+   - Asks a specific question `Say this is a test`\n+   - Configures various parameters like temperature and max_tokens for more control over the output\n+   - Disables streaming for a complete response\n+\n+You can adjust these parameters based on your specific needs.\n  \n \n ## Configuration\n@@ -129,7 +152,7 @@ from g4f.client import Client\n client = Client()\n \n response = client.images.generate(\n-    model=\"dall-e-3\",\n+    model=\"flux\",\n     prompt=\"a white siamese cat\"\n     # Add any other necessary parameters\n )\n@@ -139,6 +162,23 @@ image_url = response.data[0].url\n print(f\"Generated image URL: {image_url}\")\n ```\n \n+\n+#### Base64 Response Format\n+```python\n+from g4f.client import Client\n+\n+client = Client()\n+\n+response = client.images.generate(\n+    model=\"flux\",\n+    prompt=\"a white siamese cat\",\n+    response_format=\"b64_json\"\n+)\n+\n+base64_text = response.data[0].b64_json\n+print(base64_text)\n+```\n+\n   \n \n ### Creating Image Variations\ndiff --git a/docs/interference-api.md b/docs/interference-api.md\nindex 4050f84fd93..b8e38fae575 100644\n--- a/docs/interference-api.md\n+++ b/docs/interference-api.md\n@@ -1,23 +1,30 @@\n-\n # G4F - Interference API Usage Guide\n-\n+  \n \n ## Table of Contents\n    - [Introduction](#introduction)\n    - [Running the Interference API](#running-the-interference-api)\n    - [From PyPI Package](#from-pypi-package)\n    - [From Repository](#from-repository)\n-   - [Usage with OpenAI Library](#usage-with-openai-library)\n-   - [Usage with Requests Library](#usage-with-requests-library)\n+   - [Using the Interference API](#using-the-interference-api)\n+   - [Basic Usage](#basic-usage)\n+   - [With OpenAI Library](#with-openai-library)\n+   - [With Requests Library](#with-requests-library)\n    - [Key Points](#key-points)\n+   - [Conclusion](#conclusion)\n+  \n \n ## Introduction\n-The Interference API allows you to serve other OpenAI integrations with G4F. It acts as a proxy, translating requests to the OpenAI API into requests to the G4F providers.\n+The G4F Interference API is a powerful tool that allows you to serve other OpenAI integrations using G4F (Gpt4free). It acts as a proxy, translating requests intended for the OpenAI API into requests compatible with G4F providers. This guide will walk you through the process of setting up, running, and using the Interference API effectively.\n+  \n \n ## Running the Interference API\n+**You can run the Interference API in two ways:** using the PyPI package or from the repository.\n+  \n \n ### From PyPI Package\n-**You can run the Interference API directly from the G4F PyPI package:**\n+**To run the Interference API directly from the G4F PyPI package, use the following Python code:**\n+\n ```python\n from g4f.api import run_api\n \n@@ -25,37 +32,84 @@ run_api()\n ```\n \n   \n-\n ### From Repository\n-Alternatively, you can run the Interference API from the cloned repository.  \n+**If you prefer to run the Interference API from the cloned repository, you have two options:**\n \n-**Run the server with:**\n+1. **Using the command line:**\n ```bash\n g4f api\n ```\n-or\n+\n+2. **Using Python:**\n ```bash\n python -m g4f.api.run\n ```\n \n-  \n+**Once running, the API will be accessible at:** `http://localhost:1337/v1`\n+\n+**(Advanced) Bind to custom port:**\n+```bash\n+python -m g4f.cli api --bind \"0.0.0.0:2400\" \n+```\n \n-## Usage with OpenAI Library\n+## Using the Interference API\n \n-  \n+### Basic Usage\n+**You can interact with the Interference API using curl commands for both text and image generation:**\n \n+**For text generation:**\n+```bash\n+curl -X POST \"http://localhost:1337/v1/chat/completions\" \\\n+     -H \"Content-Type: application/json\" \\\n+     -d '{\n+           \"messages\": [\n+             {\n+               \"role\": \"user\",\n+               \"content\": \"Hello\"\n+             }\n+           ],\n+           \"model\": \"gpt-3.5-turbo\"\n+         }'\n+```\n+\n+**For image generation:**\n+1. **url:**\n+```bash\n+curl -X POST \"http://localhost:1337/v1/images/generate\" \\\n+     -H \"Content-Type: application/json\" \\\n+     -d '{\n+           \"prompt\": \"a white siamese cat\",\n+           \"model\": \"flux\",\n+           \"response_format\": \"url\"\n+         }'\n+```\n+\n+2. **b64_json**\n+```bash\n+curl -X POST \"http://localhost:1337/v1/images/generate\" \\\n+     -H \"Content-Type: application/json\" \\\n+     -d '{\n+           \"prompt\": \"a white siamese cat\",\n+           \"model\": \"flux\",\n+           \"response_format\": \"b64_json\"\n+         }'\n+```\n+\n+\n+### With OpenAI Library\n+\n+**You can use the Interference API with the OpenAI Python library by changing the `base_url`:**\n ```python\n from openai import OpenAI\n \n client = OpenAI(\n     api_key=\"\",\n-    # Change the API base URL to the local interference API\n-    base_url=\"http://localhost:1337/v1\"  \n+    base_url=\"http://localhost:1337/v1\"\n )\n \n response = client.chat.completions.create(\n     model=\"gpt-3.5-turbo\",\n-    messages=[{\"role\": \"user\", \"content\": \"write a poem about a tree\"}],\n+    messages=[{\"role\": \"user\", \"content\": \"Write a poem about a tree\"}],\n     stream=True,\n )\n \n@@ -68,20 +122,20 @@ else:\n         content = token.choices[0].delta.content\n         if content is not None:\n             print(content, end=\"\", flush=True)\n-```\n \n+```\n   \n \n-## Usage with Requests Library\n-You can also send requests directly to the Interference API using the requests library. \n+### With Requests Library\n \n-**Send a POST request to `/v1/chat/completions` with the request body containing the model and other parameters:**\n+**You can also send requests directly to the Interference API using the `requests` library:**\n ```python\n import requests\n \n url = \"http://localhost:1337/v1/chat/completions\"\n+\n body = {\n-    \"model\": \"gpt-3.5-turbo\", \n+    \"model\": \"gpt-3.5-turbo\",\n     \"stream\": False,\n     \"messages\": [\n         {\"role\": \"assistant\", \"content\": \"What can you do?\"}\n@@ -92,18 +146,20 @@ json_response = requests.post(url, json=body).json().get('choices', [])\n \n for choice in json_response:\n     print(choice.get('message', {}).get('content', ''))\n-```\n \n-  \n+```\n \n ## Key Points\n-- The Interference API translates OpenAI API requests into G4F provider requests\n-- You can run it from the PyPI package or the cloned repository\n-- It supports usage with the OpenAI Python library by changing the `base_url`\n-- Direct requests can be sent to the API endpoints using libraries like `requests`\n+   - The Interference API translates OpenAI API requests into G4F provider requests.\n+   - It can be run from either the PyPI package or the cloned repository.\n+   - The API supports usage with the OpenAI Python library by changing the `base_url`.\n+   - Direct requests can be sent to the API endpoints using libraries like `requests`.\n+   - Both text and image generation are supported.\n \n   \n-**_The Interference API allows easy integration of G4F with existing OpenAI-based applications and tools._**\n+## Conclusion\n+The G4F Interference API provides a seamless way to integrate G4F with existing OpenAI-based applications and tools. By following this guide, you should now be able to set up, run, and use the Interference API effectively. Whether you're using it for text generation, image creation, or as a drop-in replacement for OpenAI in your projects, the Interference API offers flexibility and power for your AI-driven applications.\n+ \n \n ---\n \ndiff --git a/docs/providers-and-models.md b/docs/providers-and-models.md\nindex a6d7ec4ba76..b3dbd9f16b8 100644\n--- a/docs/providers-and-models.md\n+++ b/docs/providers-and-models.md\n@@ -51,6 +51,7 @@ This document provides an overview of various AI providers and models, including\n |[free.netfly.top](https://free.netfly.top)|`g4f.Provider.FreeNetfly`|\u2714|\u274c|\u274c|?|![Cloudflare](https://img.shields.io/badge/Cloudflare-f48d37)|\u274c|\n |[gemini.google.com](https://gemini.google.com)|`g4f.Provider.Gemini`|\u2714|\u274c|\u274c|\u2714|![Active](https://img.shields.io/badge/Active-brightgreen)|\u2714|\n |[ai.google.dev](https://ai.google.dev)|`g4f.Provider.GeminiPro`|\u2714|\u274c|\u2714|?|![Active](https://img.shields.io/badge/Active-brightgreen)|\u2714|\n+|[app.giz.ai](https://app.giz.ai/assistant/)|`g4f.Provider.GizAI`|`gemini-flash, gemini-pro, gpt-4o-mini, gpt-4o, claude-3.5-sonnet, claude-3-haiku, llama-3.1-70b, llama-3.1-8b, mistral-large`|`sdxl, sd-1.5, sd-3.5, dalle-3, flux-schnell, flux1-pro`|\u274c|\u2714|![Active](https://img.shields.io/badge/Active-brightgreen)|\u274c|\n |[developers.sber.ru](https://developers.sber.ru/gigachat)|`g4f.Provider.GigaChat`|\u2714|\u274c|\u274c|\u2714|![Active](https://img.shields.io/badge/Active-brightgreen)|\u2714|\n |[gprochat.com](https://gprochat.com)|`g4f.Provider.GPROChat`|`gemini-pro`|\u274c|\u274c|\u2714|![Active](https://img.shields.io/badge/Active-brightgreen)|\u274c|\n |[console.groq.com/playground](https://console.groq.com/playground)|`g4f.Provider.Groq`|\u2714|\u274c|\u274c|?|![Active](https://img.shields.io/badge/Active-brightgreen)|\u2714|\n@@ -63,10 +64,7 @@ This document provides an overview of various AI providers and models, including\n |[app.myshell.ai/chat](https://app.myshell.ai/chat)|`g4f.Provider.MyShell`|\u2714|\u274c|?|?|![Disabled](https://img.shields.io/badge/Disabled-red)|\u274c|\n |[nexra.aryahcr.cc/bing](https://nexra.aryahcr.cc/documentation/bing/en)|`g4f.Provider.NexraBing`|\u2714|\u274c|\u274c|\u2714|![Disabled](https://img.shields.io/badge/Disabled-red)|\u274c|\n |[nexra.aryahcr.cc/blackbox](https://nexra.aryahcr.cc/documentation/blackbox/en)|`g4f.Provider.NexraBlackbox`|`blackboxai` |\u274c|\u274c|\u2714|![Active](https://img.shields.io/badge/Active-brightgreen)|\u274c|\n-|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGPT`|`gpt-4, gpt-3.5-turbo, gpt-3` |\u274c|\u274c|\u2714|![Active](https://img.shields.io/badge/Active-brightgreen)|\u274c|\n-|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGPT4o`|`gpt-4o` |\u274c|\u274c|\u2714|![Active](https://img.shields.io/badge/Active-brightgreen)|\u274c|\n-|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGptV2`|`gpt-4` |\u274c|\u274c|\u2714|![Active](https://img.shields.io/badge/Active-brightgreen)|\u274c|\n-|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGptWeb`|`gpt-4` |\u274c|\u274c|\u2714|![Active](https://img.shields.io/badge/Active-brightgreen)|\u274c|\n+|[nexra.aryahcr.cc/chatgpt](https://nexra.aryahcr.cc/documentation/chatgpt/en)|`g4f.Provider.NexraChatGPT`|`gpt-4, gpt-3.5-turbo, gpt-3, gpt-4o` |\u274c|\u274c|\u2714|![Active](https://img.shields.io/badge/Active-brightgreen)|\u274c|\n |[nexra.aryahcr.cc/dall-e](https://nexra.aryahcr.cc/documentation/dall-e/en)|`g4f.Provider.NexraDallE`|\u274c|`dalle`|\u274c|\u274c|![Active](https://img.shields.io/badge/Active-brightgreen)|\u274c|\n |[nexra.aryahcr.cc/dall-e](https://nexra.aryahcr.cc/documentation/dall-e/en)|`g4f.Provider.NexraDallE2`|\u274c|`dalle-2`|\u274c|\u274c|![Active](https://img.shields.io/badge/Active-brightgreen)|\u274c|\n |[nexra.aryahcr.cc/emi](https://nexra.aryahcr.cc/documentation/emi/en)|`g4f.Provider.NexraEmi`|\u274c|`emi`|\u274c|\u274c|![Active](https://img.shields.io/badge/Active-brightgreen)|\u274c|\n@@ -108,18 +106,18 @@ This document provides an overview of various AI providers and models, including\n |-------|---------------|-----------|---------|\n |gpt-3|OpenAI|1+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-base)|\n |gpt-3.5-turbo|OpenAI|5+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-3-5-turbo)|\n-|gpt-4|OpenAI|33+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|\n-|gpt-4-turbo|OpenAI|2+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|\n-|gpt-4o|OpenAI|7+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4o)|\n+|gpt-4|OpenAI|7+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|\n+|gpt-4-turbo|OpenAI|3+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4)|\n+|gpt-4o|OpenAI|10+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4o)|\n |gpt-4o-mini|OpenAI|14+ Providers|[platform.openai.com](https://platform.openai.com/docs/models/gpt-4o-mini)|\n |o1|OpenAI|1+ Providers|[platform.openai.com](https://openai.com/index/introducing-openai-o1-preview/)|\n-|o1-mini|OpenAI|1+ Providers|[platform.openai.com](https://openai.com/index/openai-o1-mini-advancing-cost-efficient-reasoning/)|\n+|o1-mini|OpenAI|2+ Providers|[platform.openai.com](https://openai.com/index/openai-o1-mini-advancing-cost-efficient-reasoning/)|\n |llama-2-7b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/Llama-2-7b)|\n |llama-2-13b|Meta Llama|1+ Providers|[llama.com](https://www.llama.com/llama2/)|\n |llama-3-8b|Meta Llama|4+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3/)|\n |llama-3-70b|Meta Llama|4+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3/)|\n |llama-3.1-8b|Meta Llama|7+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|\n-|llama-3.1-70b|Meta Llama|13+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|\n+|llama-3.1-70b|Meta Llama|14+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|\n |llama-3.1-405b|Meta Llama|5+ Providers|[ai.meta.com](https://ai.meta.com/blog/meta-llama-3-1/)|\n |llama-3.2-1b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/Llama-3.2-1B)|\n |llama-3.2-3b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/blog/llama32)|\n@@ -127,17 +125,17 @@ This document provides an overview of various AI providers and models, including\n |llama-3.2-90b|Meta Llama|2+ Providers|[ai.meta.com](https://ai.meta.com/blog/llama-3-2-connect-2024-vision-edge-mobile-devices/)|\n |llamaguard-7b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/LlamaGuard-7b)|\n |llamaguard-2-8b|Meta Llama|1+ Providers|[huggingface.co](https://huggingface.co/meta-llama/Meta-Llama-Guard-2-8B)|\n-|mistral-7b|Mistral AI|5+ Providers|[mistral.ai](https://mistral.ai/news/announcing-mistral-7b/)|\n+|mistral-7b|Mistral AI|4+ Providers|[mistral.ai](https://mistral.ai/news/announcing-mistral-7b/)|\n |mixtral-8x7b|Mistral AI|6+ Providers|[mistral.ai](https://mistral.ai/news/mixtral-of-experts/)|\n |mixtral-8x22b|Mistral AI|3+ Providers|[mistral.ai](https://mistral.ai/news/mixtral-8x22b/)|\n-|mistral-nemo|Mistral AI|1+ Providers|[huggingface.co](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)|\n-|mistral-large|Mistral AI|1+ Providers|[mistral.ai](https://mistral.ai/news/mistral-large-2407/)|\n+|mistral-nemo|Mistral AI|2+ Providers|[huggingface.co](https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407)|\n+|mistral-large|Mistral AI|2+ Providers|[mistral.ai](https://mistral.ai/news/mistral-large-2407/)|\n |mixtral-8x7b-dpo|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO)|\n |yi-34b|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Nous-Hermes-2-Yi-34B)|\n-|hermes-3|NousResearch|1+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B)|\n+|hermes-3|NousResearch|2+ Providers|[huggingface.co](https://huggingface.co/NousResearch/Hermes-3-Llama-3.1-8B)|\n |gemini|Google DeepMind|1+ Providers|[deepmind.google](http://deepmind.google/technologies/gemini/)|\n-|gemini-flash|Google DeepMind|3+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/flash/)|\n-|gemini-pro|Google DeepMind|9+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/pro/)|\n+|gemini-flash|Google DeepMind|4+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/flash/)|\n+|gemini-pro|Google DeepMind|10+ Providers|[deepmind.google](https://deepmind.google/technologies/gemini/pro/)|\n |gemma-2b|Google|5+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2b)|\n |gemma-2b-9b|Google|1+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2-9b)|\n |gemma-2b-27b|Google|2+ Providers|[huggingface.co](https://huggingface.co/google/gemma-2-27b)|\n@@ -145,10 +143,10 @@ This document provides an overview of various AI providers and models, including\n |gemma-2|Google|2+ Providers|[huggingface.co](https://huggingface.co/blog/gemma2)|\n |gemma_2_27b|Google|1+ Providers|[huggingface.co](https://huggingface.co/blog/gemma2)|\n |claude-2.1|Anthropic|1+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-2)|\n-|claude-3-haiku|Anthropic|3+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-haiku)|\n+|claude-3-haiku|Anthropic|4+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-haiku)|\n |claude-3-sonnet|Anthropic|2+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-family)|\n |claude-3-opus|Anthropic|2+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-family)|\n-|claude-3.5-sonnet|Anthropic|5+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-5-sonnet)|\n+|claude-3.5-sonnet|Anthropic|6+ Providers|[anthropic.com](https://www.anthropic.com/news/claude-3-5-sonnet)|\n |blackboxai|Blackbox AI|2+ Providers|[docs.blackbox.chat](https://docs.blackbox.chat/blackbox-ai-1)|\n |blackboxai-pro|Blackbox AI|1+ Providers|[docs.blackbox.chat](https://docs.blackbox.chat/blackbox-ai-1)|\n |yi-1.5-9b|01-ai|1+ Providers|[huggingface.co](https://huggingface.co/01-ai/Yi-1.5-9B)|\n@@ -196,11 +194,12 @@ This document provides an overview of various AI providers and models, including\n ### Image Models\n | Model | Base Provider | Providers | Website |\n |-------|---------------|-----------|---------|\n-|sdxl|Stability AI|2+ Providers|[huggingface.co](https://huggingface.co/docs/diffusers/en/using-diffusers/sdxl)|\n+|sdxl|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/docs/diffusers/en/using-diffusers/sdxl)|\n |sdxl-lora|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/blog/lcm_lora)|\n |sdxl-turbo|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/stabilityai/sdxl-turbo)|\n |sd-1.5|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/runwayml/stable-diffusion-v1-5)|\n |sd-3|Stability AI|1+ Providers|[huggingface.co](https://huggingface.co/docs/diffusers/main/en/api/pipelines/stable_diffusion/stable_diffusion_3)|\n+|sd-3.5|Stability AI|1+ Providers|[stability.ai](https://stability.ai/news/introducing-stable-diffusion-3-5)|\n |playground-v2.5|Playground AI|1+ Providers|[huggingface.co](https://huggingface.co/playgroundai/playground-v2.5-1024px-aesthetic)|\n |flux|Black Forest Labs|2+ Providers|[github.com/black-forest-labs/flux](https://github.com/black-forest-labs/flux)|\n |flux-pro|Black Forest Labs|2+ Providers|[github.com/black-forest-labs/flux](https://github.com/black-forest-labs/flux)|\n@@ -210,10 +209,9 @@ This document provides an overview of various AI providers and models, including\n |flux-disney|Flux AI|1+ Providers|[]()|\n |flux-pixel|Flux AI|1+ Providers|[]()|\n |flux-4o|Flux AI|1+ Providers|[]()|\n-|flux-schnell|Black Forest Labs|1+ Providers|[huggingface.co](https://huggingface.co/black-forest-labs/FLUX.1-schnell)|\n+|flux-schnell|Black Forest Labs|2+ Providers|[huggingface.co](https://huggingface.co/black-forest-labs/FLUX.1-schnell)|\n |dalle|OpenAI|1+ Providers|[openai.com](https://openai.com/index/dall-e/)|\n |dalle-2|OpenAI|1+ Providers|[openai.com](https://openai.com/index/dall-e-2/)|\n-|dalle-3|OpenAI|2+ Providers|[openai.com](https://openai.com/index/dall-e-3/)|\n |emi||1+ Providers|[]()|\n |any-dark||1+ Providers|[]()|\n |midjourney|Midjourney|1+ Providers|[docs.midjourney.com](https://docs.midjourney.com/docs/model-versions)|\ndiff --git a/g4f/Provider/AI365VIP.py b/g4f/Provider/AI365VIP.py\nindex c7ebf6b527b..511ad568515 100644\n--- a/g4f/Provider/AI365VIP.py\n+++ b/g4f/Provider/AI365VIP.py\n@@ -10,7 +10,7 @@\n class AI365VIP(AsyncGeneratorProvider, ProviderModelMixin):\n     url = \"https://chat.ai365vip.com\"\n     api_endpoint = \"/api/chat\"\n-    working = True\n+    working = False\n     default_model = 'gpt-3.5-turbo'\n     models = [\n         'gpt-3.5-turbo',\ndiff --git a/g4f/Provider/AiMathGPT.py b/g4f/Provider/AiMathGPT.py\nindex 4399320a705..90931691a60 100644\n--- a/g4f/Provider/AiMathGPT.py\n+++ b/g4f/Provider/AiMathGPT.py\n@@ -59,10 +59,6 @@ async def create_async_generator(\n         async with ClientSession(headers=headers) as session:\n             data = {\n                 \"messages\": [\n-                    {\n-                        \"role\": \"system\",\n-                        \"content\": \"\"\n-                    },\n                     {\n                         \"role\": \"user\",\n                         \"content\": format_prompt(messages)\ndiff --git a/g4f/Provider/Blackbox.py b/g4f/Provider/Blackbox.py\nindex 5cd43eed961..4052893adff 100644\n--- a/g4f/Provider/Blackbox.py\n+++ b/g4f/Provider/Blackbox.py\n@@ -51,7 +51,6 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):\n         'ReactAgent',\n         'XcodeAgent',\n         'AngularJSAgent',\n-        'RepoMap',\n     ]\n \n     agentMode = {\n@@ -78,7 +77,6 @@ class Blackbox(AsyncGeneratorProvider, ProviderModelMixin):\n         'ReactAgent': {'mode': True, 'id': \"React Agent\"},\n         'XcodeAgent': {'mode': True, 'id': \"Xcode Agent\"},\n         'AngularJSAgent': {'mode': True, 'id': \"AngularJS Agent\"},\n-        'RepoMap': {'mode': True, 'id': \"repomap\"},\n     }\n \n     userSelectedModel = {\n@@ -174,7 +172,7 @@ async def create_async_generator(\n         proxy: Optional[str] = None,\n         image: ImageType = None,\n         image_name: str = None,\n-        websearch: bool = False,\n+        web_search: bool = False,\n         **kwargs\n     ) -> AsyncGenerator[Union[str, ImageResponse], None]:\n         \"\"\"\n@@ -186,7 +184,7 @@ async def create_async_generator(\n             proxy (Optional[str]): Proxy URL, if needed.\n             image (ImageType): Image data to be processed, if any.\n             image_name (str): Name of the image file, if an image is provided.\n-            websearch (bool): Enables or disables web search mode.\n+            web_search (bool): Enables or disables web search mode.\n             **kwargs: Additional keyword arguments.\n \n         Yields:\n@@ -276,7 +274,7 @@ async def create_async_generator(\n             \"clickedForceWebSearch\": False,\n             \"visitFromDelta\": False,\n             \"mobileClient\": False,\n-            \"webSearchMode\": websearch,\n+            \"webSearchMode\": web_search,\n             \"userSelectedModel\": cls.userSelectedModel.get(model, model)\n         }\n \n@@ -313,7 +311,7 @@ async def create_async_generator(\n                         else:\n                             yield cleaned_response\n                     else:\n-                        if websearch:\n+                        if web_search:\n                             match = re.search(r'\\$~~~\\$(.*?)\\$~~~\\$', cleaned_response, re.DOTALL)\n                             if match:\n                                 source_part = match.group(1).strip()\ndiff --git a/g4f/Provider/GeminiPro.py b/g4f/Provider/GeminiPro.py\nindex 06bf69ee765..e7174c5922d 100644\n--- a/g4f/Provider/GeminiPro.py\n+++ b/g4f/Provider/GeminiPro.py\n@@ -104,4 +104,8 @@ async def create_async_generator(\n                             lines.append(chunk)\n                 else:\n                     data = await response.json()\n-                    yield data[\"candidates\"][0][\"content\"][\"parts\"][0][\"text\"]\n\\ No newline at end of file\n+                    candidate = data[\"candidates\"][0]\n+                    if candidate[\"finishReason\"] == \"STOP\":\n+                        yield candidate[\"content\"][\"parts\"][0][\"text\"]\n+                    else:\n+                        yield candidate[\"finishReason\"] + ' ' + candidate[\"safetyRatings\"]\n\\ No newline at end of file\ndiff --git a/g4f/Provider/GizAI.py b/g4f/Provider/GizAI.py\nnew file mode 100644\nindex 00000000000..127edc9e42d\n--- /dev/null\n+++ b/g4f/Provider/GizAI.py\n@@ -0,0 +1,151 @@\n+from __future__ import annotations\n+\n+import json\n+from aiohttp import ClientSession\n+\n+from ..typing import AsyncResult, Messages\n+from ..image import ImageResponse\n+from .base_provider import AsyncGeneratorProvider, ProviderModelMixin\n+from .helper import format_prompt\n+\n+class GizAI(AsyncGeneratorProvider, ProviderModelMixin):\n+    url = \"https://app.giz.ai/assistant/\"\n+    api_endpoint = \"https://app.giz.ai/api/data/users/inferenceServer.infer\"\n+    working = True\n+    \n+    supports_system_message = True\n+    supports_message_history = True\n+    \n+    # Chat models\n+    default_model = 'chat-gemini-flash'\n+    chat_models = [\n+        default_model,\n+        'chat-gemini-pro',\n+        'chat-gpt4m',\n+        'chat-gpt4',\n+        'claude-sonnet',\n+        'claude-haiku',\n+        'llama-3-70b',\n+        'llama-3-8b',\n+        'mistral-large',\n+        'chat-o1-mini'\n+    ]\n+\n+    # Image models\n+    image_models = [\n+        'flux1',\n+        'sdxl',\n+        'sd',\n+        'sd35',\n+    ]\n+\n+    models = [*chat_models, *image_models]\n+    \n+    model_aliases = {\n+        # Chat model aliases\n+        \"gemini-flash\": \"chat-gemini-flash\",\n+        \"gemini-pro\": \"chat-gemini-pro\",\n+        \"gpt-4o-mini\": \"chat-gpt4m\",\n+        \"gpt-4o\": \"chat-gpt4\",\n+        \"claude-3.5-sonnet\": \"claude-sonnet\",\n+        \"claude-3-haiku\": \"claude-haiku\",\n+        \"llama-3.1-70b\": \"llama-3-70b\",\n+        \"llama-3.1-8b\": \"llama-3-8b\",\n+        \"o1-mini\": \"chat-o1-mini\",\n+        # Image model aliases\n+        \"sd-1.5\": \"sd\",\n+        \"sd-3.5\": \"sd35\",\n+        \"flux-schnell\": \"flux1\",\n+    }\n+\n+    @classmethod\n+    def get_model(cls, model: str) -> str:\n+        if model in cls.models:\n+            return model\n+        elif model in cls.model_aliases:\n+            return cls.model_aliases[model]\n+        else:\n+            return cls.default_model\n+\n+    @classmethod\n+    def is_image_model(cls, model: str) -> bool:\n+        return model in cls.image_models\n+\n+    @classmethod\n+    async def create_async_generator(\n+        cls,\n+        model: str,\n+        messages: Messages,\n+        proxy: str = None,\n+        **kwargs\n+    ) -> AsyncResult:\n+        model = cls.get_model(model)\n+        \n+        headers = {\n+            'Accept': 'application/json, text/plain, */*',\n+            'Accept-Language': 'en-US,en;q=0.9',\n+            'Cache-Control': 'no-cache',\n+            'Connection': 'keep-alive',\n+            'Content-Type': 'application/json',\n+            'Origin': 'https://app.giz.ai',\n+            'Pragma': 'no-cache',\n+            'Sec-Fetch-Dest': 'empty',\n+            'Sec-Fetch-Mode': 'cors',\n+            'Sec-Fetch-Site': 'same-origin',\n+            'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36',\n+            'sec-ch-ua': '\"Not?A_Brand\";v=\"99\", \"Chromium\";v=\"130\"',\n+            'sec-ch-ua-mobile': '?0',\n+            'sec-ch-ua-platform': '\"Linux\"'\n+        }\n+\n+        async with ClientSession() as session:\n+            if cls.is_image_model(model):\n+                # Image generation\n+                prompt = messages[-1][\"content\"]\n+                data = {\n+                    \"model\": model,\n+                    \"input\": {\n+                        \"width\": \"1024\",\n+                        \"height\": \"1024\",\n+                        \"steps\": 4,\n+                        \"output_format\": \"webp\",\n+                        \"batch_size\": 1,\n+                        \"mode\": \"plan\",\n+                        \"prompt\": prompt\n+                    }\n+                }\n+                async with session.post(\n+                    cls.api_endpoint,\n+                    headers=headers,\n+                    data=json.dumps(data),\n+                    proxy=proxy\n+                ) as response:\n+                    response.raise_for_status()\n+                    response_data = await response.json()\n+                    if response_data.get('status') == 'completed' and response_data.get('output'):\n+                        for url in response_data['output']:\n+                            yield ImageResponse(images=url, alt=\"Generated Image\")\n+            else:\n+                # Chat completion\n+                data = {\n+                    \"model\": model,\n+                    \"input\": {\n+                        \"messages\": [\n+                            {\n+                                \"type\": \"human\",\n+                                \"content\": format_prompt(messages)\n+                            }\n+                        ],\n+                        \"mode\": \"plan\"\n+                    },\n+                    \"noStream\": True\n+                }\n+                async with session.post(\n+                    cls.api_endpoint,\n+                    headers=headers,\n+                    data=json.dumps(data),\n+                    proxy=proxy\n+                ) as response:\n+                    response.raise_for_status()\n+                    result = await response.json()\n+                    yield result.get('output', '')\ndiff --git a/g4f/Provider/Mhystical.py b/g4f/Provider/Mhystical.py\nnew file mode 100644\nindex 00000000000..44b326043b2\n--- /dev/null\n+++ b/g4f/Provider/Mhystical.py\n@@ -0,0 +1,88 @@\n+from __future__ import annotations\n+\n+import json\n+import logging\n+from aiohttp import ClientSession\n+from ..typing import AsyncResult, Messages\n+from .base_provider import AsyncGeneratorProvider, ProviderModelMixin\n+from .helper import format_prompt\n+\n+\"\"\"\n+    Mhystical.cc\n+    ~~~~~~~~~~~~\n+    Author: NoelP.dev\n+    Last Updated: 2024-05-11\n+    \n+    Author Site: https://noelp.dev\n+    Provider Site: https://mhystical.cc\n+\n+\"\"\"\n+\n+class Mhystical(AsyncGeneratorProvider, ProviderModelMixin):\n+    url = \"https://api.mhystical.cc\"\n+    api_endpoint = \"https://api.mhystical.cc/v1/completions\"\n+    working = True\n+    supports_stream = False  # Set to False, as streaming is not specified in ChatifyAI\n+    supports_system_message = False\n+    supports_message_history = True\n+    \n+    default_model = 'gpt-4'\n+    models = [default_model]\n+    model_aliases = {}\n+\n+    @classmethod\n+    def get_model(cls, model: str) -> str:\n+        if model in cls.models:\n+            return model\n+        elif model in cls.model_aliases:\n+            return cls.model_aliases.get(model, cls.default_model)\n+        else:\n+            return cls.default_model\n+\n+    @classmethod\n+    async def create_async_generator(\n+        cls,\n+        model: str,\n+        messages: Messages,\n+        proxy: str = None,\n+        **kwargs\n+    ) -> AsyncResult:\n+        model = cls.get_model(model)\n+        \n+        headers = {\n+            \"x-api-key\": \"mhystical\",\n+            \"Content-Type\": \"application/json\",\n+            \"accept\": \"*/*\",\n+            \"cache-control\": \"no-cache\",\n+            \"origin\": cls.url,\n+            \"referer\": f\"{cls.url}/\",\n+            \"user-agent\": \"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36\"\n+        }\n+        \n+        async with ClientSession(headers=headers) as session:\n+            data = {\n+                \"model\": model,\n+                \"messages\": [{\"role\": \"user\", \"content\": format_prompt(messages)}]\n+            }\n+            async with session.post(cls.api_endpoint, json=data, headers=headers, proxy=proxy) as response:\n+                if response.status == 400:\n+                    yield \"Error: API key is missing\"\n+                elif response.status == 429:\n+                    yield \"Error: Rate limit exceeded\"\n+                elif response.status == 500:\n+                    yield \"Error: Internal server error\"\n+                else:\n+                    response.raise_for_status()\n+                    response_text = await response.text()\n+                    filtered_response = cls.filter_response(response_text)\n+                    yield filtered_response\n+\n+    @staticmethod\n+    def filter_response(response_text: str) -> str:\n+        try:\n+            json_response = json.loads(response_text)\n+            message_content = json_response[\"choices\"][0][\"message\"][\"content\"]\n+            return message_content\n+        except (KeyError, IndexError, json.JSONDecodeError) as e:\n+            logging.error(\"Error parsing response: %s\", e)\n+            return \"Error: Failed to parse response from API.\"\n\\ No newline at end of file\ndiff --git a/g4f/Provider/__init__.py b/g4f/Provider/__init__.py\nindex 8f36606ba49..a313a9b396c 100644\n--- a/g4f/Provider/__init__.py\n+++ b/g4f/Provider/__init__.py\n@@ -47,6 +47,7 @@\n from .FreeGpt          import FreeGpt\n from .FreeNetfly       import FreeNetfly\n from .GeminiPro        import GeminiPro\n+from .GizAI            import GizAI\n from .GPROChat         import GPROChat\n from .HuggingChat      import HuggingChat\n from .HuggingFace      import HuggingFace\n@@ -69,6 +70,7 @@\n from .Upstage          import Upstage\n from .WhiteRabbitNeo   import WhiteRabbitNeo\n from .You              import You\n+from .Mhystical       import Mhystical\n \n import sys\n \ndiff --git a/g4f/Provider/nexra/NexraChatGPT.py b/g4f/Provider/nexra/NexraChatGPT.py\nindex fc5051eeaaf..074a0363c15 100644\n--- a/g4f/Provider/nexra/NexraChatGPT.py\n+++ b/g4f/Provider/nexra/NexraChatGPT.py\n@@ -1,45 +1,52 @@\n from __future__ import annotations\n \n+import asyncio\n import json\n import requests\n+from typing import Any, Dict\n \n-from ...typing import CreateResult, Messages\n-from ..base_provider import ProviderModelMixin, AbstractProvider\n+from ...typing import AsyncResult, Messages\n+from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin\n from ..helper import format_prompt\n \n-class NexraChatGPT(AbstractProvider, ProviderModelMixin):\n+\n+class NexraChatGPT(AsyncGeneratorProvider, ProviderModelMixin):\n     label = \"Nexra ChatGPT\"\n     url = \"https://nexra.aryahcr.cc/documentation/chatgpt/en\"\n-    api_endpoint = \"https://nexra.aryahcr.cc/api/chat/gpt\"\n+    api_endpoint_nexra_chatgpt = \"https://nexra.aryahcr.cc/api/chat/gpt\"\n+    api_endpoint_nexra_chatgpt4o = \"https://nexra.aryahcr.cc/api/chat/complements\"\n+    api_endpoint_nexra_chatgpt_v2 = \"https://nexra.aryahcr.cc/api/chat/complements\"\n+    api_endpoint_nexra_gptweb = \"https://nexra.aryahcr.cc/api/chat/gptweb\"\n     working = True\n+    supports_system_message = True\n+    supports_message_history = True\n+    supports_stream = True\n     \n     default_model = 'gpt-3.5-turbo'\n-    models = ['gpt-4', 'gpt-4-0613', 'gpt-4-0314', 'gpt-4-32k-0314', default_model, 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo-0301', 'text-davinci-003', 'text-davinci-002', 'code-davinci-002', 'gpt-3', 'text-curie-001', 'text-babbage-001', 'text-ada-001', 'davinci', 'curie', 'babbage', 'ada', 'babbage-002', 'davinci-002']\n+    nexra_chatgpt = [\n+        'gpt-4', 'gpt-4-0613', 'gpt-4-0314', 'gpt-4-32k-0314',\n+        default_model, 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', 'gpt-3.5-turbo-0301', \n+        'text-davinci-003', 'text-davinci-002', 'code-davinci-002', 'gpt-3', 'text-curie-001', 'text-babbage-001', 'text-ada-001', 'davinci', 'curie', 'babbage', 'ada', 'babbage-002', 'davinci-002'\n+    ]\n+    nexra_chatgpt4o = ['gpt-4o']\n+    nexra_chatgptv2 = ['chatgpt']\n+    nexra_gptweb = ['gptweb']\n+    models = nexra_chatgpt + nexra_chatgpt4o + nexra_chatgptv2 + nexra_gptweb\n     \n     model_aliases = {\n         \"gpt-4\": \"gpt-4-0613\",\n-        \"gpt-4\": \"gpt-4-32k\",\n-        \"gpt-4\": \"gpt-4-0314\",\n-        \"gpt-4\": \"gpt-4-32k-0314\",\n-        \n+        \"gpt-4-32k\": \"gpt-4-32k-0314\",\n         \"gpt-3.5-turbo\": \"gpt-3.5-turbo-16k\",\n-        \"gpt-3.5-turbo\": \"gpt-3.5-turbo-0613\",\n-        \"gpt-3.5-turbo\": \"gpt-3.5-turbo-16k-0613\",\n-        \"gpt-3.5-turbo\": \"gpt-3.5-turbo-0301\",\n-        \n+        \"gpt-3.5-turbo-0613\": \"gpt-3.5-turbo-16k-0613\",\n         \"gpt-3\": \"text-davinci-003\",\n-        \"gpt-3\": \"text-davinci-002\",\n-        \"gpt-3\": \"code-davinci-002\",\n-        \"gpt-3\": \"text-curie-001\",\n-        \"gpt-3\": \"text-babbage-001\",\n-        \"gpt-3\": \"text-ada-001\",\n-        \"gpt-3\": \"text-ada-001\",\n-        \"gpt-3\": \"davinci\",\n-        \"gpt-3\": \"curie\",\n-        \"gpt-3\": \"babbage\",\n-        \"gpt-3\": \"ada\",\n-        \"gpt-3\": \"babbage-002\",\n-        \"gpt-3\": \"davinci-002\",\n+        \"text-davinci-002\": \"code-davinci-002\",\n+        \"text-curie-001\": \"text-babbage-001\",\n+        \"text-ada-001\": \"davinci\",\n+        \"curie\": \"babbage\",\n+        \"ada\": \"babbage-002\",\n+        \"davinci-002\": \"davinci-002\",\n+        \"chatgpt\": \"chatgpt\",\n+        \"gptweb\": \"gptweb\"\n     }\n \n     @classmethod\n@@ -50,40 +57,229 @@ def get_model(cls, model: str) -> str:\n             return cls.model_aliases[model]\n         else:\n             return cls.default_model\n-            \n+\n     @classmethod\n-    def create_completion(\n+    async def create_async_generator(\n         cls,\n         model: str,\n         messages: Messages,\n+        stream: bool = False,\n         proxy: str = None,\n         markdown: bool = False,\n         **kwargs\n-    ) -> CreateResult:\n-        model = cls.get_model(model)\n+    ) -> AsyncResult:\n+        if model in cls.nexra_chatgpt:\n+            async for chunk in cls._create_async_generator_nexra_chatgpt(model, messages, proxy, **kwargs):\n+                yield chunk\n+        elif model in cls.nexra_chatgpt4o:\n+            async for chunk in cls._create_async_generator_nexra_chatgpt4o(model, messages, stream, proxy, markdown, **kwargs):\n+                yield chunk\n+        elif model in cls.nexra_chatgptv2:\n+            async for chunk in cls._create_async_generator_nexra_chatgpt_v2(model, messages, stream, proxy, markdown, **kwargs):\n+                yield chunk\n+        elif model in cls.nexra_gptweb:\n+            async for chunk in cls._create_async_generator_nexra_gptweb(model, messages, proxy, **kwargs):\n+                yield chunk\n \n+    @classmethod\n+    async def _create_async_generator_nexra_chatgpt(\n+        cls,\n+        model: str,\n+        messages: Messages,\n+        proxy: str = None,\n+        markdown: bool = False,\n+        **kwargs\n+    ) -> AsyncResult:\n+        model = cls.get_model(model)\n+        \n         headers = {\n-            'Content-Type': 'application/json'\n+            \"Content-Type\": \"application/json\"\n         }\n         \n+        prompt = format_prompt(messages)\n         data = {\n-            \"messages\": [],\n-            \"prompt\": format_prompt(messages),\n+            \"messages\": messages,\n+            \"prompt\": prompt,\n             \"model\": model,\n             \"markdown\": markdown\n         }\n+\n+        loop = asyncio.get_event_loop()\n+        try:\n+            response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt, data, headers, proxy)\n+            filtered_response = cls._filter_response(response)\n+            \n+            for chunk in filtered_response:\n+                yield chunk\n+        except Exception as e:\n+            print(f\"Error during API request (nexra_chatgpt): {e}\")\n+\n+    @classmethod\n+    async def _create_async_generator_nexra_chatgpt4o(\n+        cls,\n+        model: str,\n+        messages: Messages,\n+        stream: bool = False,\n+        proxy: str = None,\n+        markdown: bool = False,\n+        **kwargs\n+    ) -> AsyncResult:\n+        model = cls.get_model(model)\n         \n-        response = requests.post(cls.api_endpoint, headers=headers, json=data)\n+        headers = {\n+            \"Content-Type\": \"application/json\"\n+        }\n+        \n+        prompt = format_prompt(messages)\n+        data = {\n+            \"messages\": [\n+                {\n+                    \"role\": \"user\",\n+                    \"content\": prompt\n+                }\n+            ],\n+            \"stream\": stream,\n+            \"markdown\": markdown,\n+            \"model\": model\n+        }\n \n-        return cls.process_response(response)\n+        loop = asyncio.get_event_loop()\n+        try:\n+            response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt4o, data, headers, proxy, stream)\n+            \n+            if stream:\n+                async for chunk in cls._process_streaming_response(response):\n+                    yield chunk\n+            else:\n+                for chunk in cls._process_non_streaming_response(response):\n+                    yield chunk\n+        except Exception as e:\n+            print(f\"Error during API request (nexra_chatgpt4o): {e}\")\n \n     @classmethod\n-    def process_response(cls, response):\n+    async def _create_async_generator_nexra_chatgpt_v2(\n+        cls,\n+        model: str,\n+        messages: Messages,\n+        stream: bool = False,\n+        proxy: str = None,\n+        markdown: bool = False,\n+        **kwargs\n+    ) -> AsyncResult:\n+        model = cls.get_model(model)\n+        \n+        headers = {\n+            \"Content-Type\": \"application/json\"\n+        }\n+        \n+        prompt = format_prompt(messages)\n+        data = {\n+            \"messages\": [\n+                {\n+                    \"role\": \"user\",\n+                    \"content\": prompt\n+                }\n+            ],\n+            \"stream\": stream,\n+            \"markdown\": markdown,\n+            \"model\": model\n+        }\n+\n+        loop = asyncio.get_event_loop()\n+        try:\n+            response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_chatgpt_v2, data, headers, proxy, stream)\n+            \n+            if stream:\n+                async for chunk in cls._process_streaming_response(response):\n+                    yield chunk\n+            else:\n+                for chunk in cls._process_non_streaming_response(response):\n+                    yield chunk\n+        except Exception as e:\n+            print(f\"Error during API request (nexra_chatgpt_v2): {e}\")\n+\n+    @classmethod\n+    async def _create_async_generator_nexra_gptweb(\n+        cls,\n+        model: str,\n+        messages: Messages,\n+        proxy: str = None,\n+        markdown: bool = False,\n+        **kwargs\n+    ) -> AsyncResult:\n+        model = cls.get_model(model)\n+        \n+        headers = {\n+            \"Content-Type\": \"application/json\"\n+        }\n+        \n+        prompt = format_prompt(messages)\n+        data = {\n+            \"prompt\": prompt,\n+            \"markdown\": markdown,\n+        }\n+\n+        loop = asyncio.get_event_loop()\n+        try:\n+            response = await loop.run_in_executor(None, cls._sync_post_request, cls.api_endpoint_nexra_gptweb, data, headers, proxy)\n+            \n+            for chunk in response.iter_content(1024):\n+                if chunk:\n+                    decoded_chunk = chunk.decode().lstrip('_')\n+                    try:\n+                        response_json = json.loads(decoded_chunk)\n+                        if response_json.get(\"status\"):\n+                            yield response_json.get(\"gpt\", \"\")\n+                    except json.JSONDecodeError:\n+                        continue\n+        except Exception as e:\n+            print(f\"Error during API request (nexra_gptweb): {e}\")\n+\n+    @staticmethod\n+    def _sync_post_request(url: str, data: Dict[str, Any], headers: Dict[str, str], proxy: str = None, stream: bool = False) -> requests.Response:\n+        proxies = {\n+            \"http\": proxy,\n+            \"https\": proxy,\n+        } if proxy else None\n+        \n+        try:\n+            response = requests.post(url, json=data, headers=headers, proxies=proxies, stream=stream)\n+            response.raise_for_status()\n+            return response\n+        except requests.RequestException as e:\n+            print(f\"Request failed: {e}\")\n+            raise\n+\n+    @staticmethod\n+    def _process_non_streaming_response(response: requests.Response) -> str:\n         if response.status_code == 200:\n             try:\n-                data = response.json()\n-                return data.get('gpt', '')\n+                content = response.text.lstrip('\u001e')\n+                data = json.loads(content)\n+                return data.get('message', '')\n             except json.JSONDecodeError:\n                 return \"Error: Unable to decode JSON response\"\n         else:\n             return f\"Error: {response.status_code}\"\n+\n+    @staticmethod\n+    async def _process_streaming_response(response: requests.Response):\n+        full_message = \"\"\n+        for line in response.iter_lines(decode_unicode=True):\n+            if line:\n+                try:\n+                    line = line.lstrip('\u001e')\n+                    data = json.loads(line)\n+                    if data.get('finish'):\n+                        break\n+                    message = data.get('message', '')\n+                    if message:\n+                        yield message[len(full_message):]\n+                        full_message = message\n+                except json.JSONDecodeError:\n+                    pass\n+\n+    @staticmethod\n+    def _filter_response(response: requests.Response) -> str:\n+        response_json = response.json()\n+        return response_json.get(\"gpt\", \"\")\ndiff --git a/g4f/Provider/nexra/NexraChatGPT4o.py b/g4f/Provider/nexra/NexraChatGPT4o.py\ndeleted file mode 100644\nindex 126d32b8bfb..00000000000\n--- a/g4f/Provider/nexra/NexraChatGPT4o.py\n+++ /dev/null\n@@ -1,86 +0,0 @@\n-from __future__ import annotations\n-\n-import json\n-import requests\n-\n-from ...typing import CreateResult, Messages\n-from ..base_provider import ProviderModelMixin, AbstractProvider\n-from ..helper import format_prompt\n-\n-class NexraChatGPT4o(AbstractProvider, ProviderModelMixin):\n-    label = \"Nexra ChatGPT4o\"\n-    url = \"https://nexra.aryahcr.cc/documentation/chatgpt/en\"\n-    api_endpoint = \"https://nexra.aryahcr.cc/api/chat/complements\"\n-    working = True\n-    supports_stream = True\n-    \n-    default_model = \"gpt-4o\"\n-    models = [default_model]\n-\n-    @classmethod\n-    def get_model(cls, model: str) -> str:\n-        return cls.default_model\n-            \n-    @classmethod\n-    def create_completion(\n-        cls,\n-        model: str,\n-        messages: Messages,\n-        stream: bool,\n-        proxy: str = None,\n-        markdown: bool = False,\n-        **kwargs\n-    ) -> CreateResult:\n-        model = cls.get_model(model)\n-\n-        headers = {\n-            'Content-Type': 'application/json'\n-        }\n-        \n-        data = {\n-            \"messages\": [\n-                {\n-                    \"role\": \"user\",\n-                    \"content\": format_prompt(messages)\n-                }\n-            ],\n-            \"stream\": stream,\n-            \"markdown\": markdown,\n-            \"model\": model\n-        }\n-        \n-        response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream)\n-\n-        if stream:\n-            return cls.process_streaming_response(response)\n-        else:\n-            return cls.process_non_streaming_response(response)\n-\n-    @classmethod\n-    def process_non_streaming_response(cls, response):\n-        if response.status_code == 200:\n-            try:\n-                content = response.text.lstrip('\u001e')\n-                data = json.loads(content)\n-                return data.get('message', '')\n-            except json.JSONDecodeError:\n-                return \"Error: Unable to decode JSON response\"\n-        else:\n-            return f\"Error: {response.status_code}\"\n-\n-    @classmethod\n-    def process_streaming_response(cls, response):\n-        full_message = \"\"\n-        for line in response.iter_lines(decode_unicode=True):\n-            if line:\n-                try:\n-                    line = line.lstrip('\u001e')\n-                    data = json.loads(line)\n-                    if data.get('finish'):\n-                        break\n-                    message = data.get('message', '')\n-                    if message and message != full_message:\n-                        yield message[len(full_message):]\n-                        full_message = message\n-                except json.JSONDecodeError:\n-                    pass\ndiff --git a/g4f/Provider/nexra/NexraChatGptV2.py b/g4f/Provider/nexra/NexraChatGptV2.py\ndeleted file mode 100644\nindex 1ff42705f4d..00000000000\n--- a/g4f/Provider/nexra/NexraChatGptV2.py\n+++ /dev/null\n@@ -1,92 +0,0 @@\n-from __future__ import annotations\n-\n-import json\n-import requests\n-\n-from ...typing import CreateResult, Messages\n-from ..base_provider import ProviderModelMixin, AbstractProvider\n-from ..helper import format_prompt\n-\n-class NexraChatGptV2(AbstractProvider, ProviderModelMixin):\n-    label = \"Nexra ChatGPT v2\"\n-    url = \"https://nexra.aryahcr.cc/documentation/chatgpt/en\"\n-    api_endpoint = \"https://nexra.aryahcr.cc/api/chat/complements\"\n-    working = True\n-    supports_stream = True\n-    \n-    default_model = 'chatgpt'\n-    models = [default_model]\n-    model_aliases = {\"gpt-4\": \"chatgpt\"}\n-\n-    @classmethod\n-    def get_model(cls, model: str) -> str:\n-        if model in cls.models:\n-            return model\n-        elif model in cls.model_aliases:\n-            return cls.model_aliases[model]\n-        else:\n-            return cls.default_model\n-            \n-    @classmethod\n-    def create_completion(\n-        cls,\n-        model: str,\n-        messages: Messages,\n-        stream: bool,\n-        proxy: str = None,\n-        markdown: bool = False,\n-        **kwargs\n-    ) -> CreateResult:\n-        model = cls.get_model(model)\n-\n-        headers = {\n-            'Content-Type': 'application/json'\n-        }\n-        \n-        data = {\n-            \"messages\": [\n-                {\n-                    \"role\": \"user\",\n-                    \"content\": format_prompt(messages)\n-                }\n-            ],\n-            \"stream\": stream,\n-            \"markdown\": markdown,\n-            \"model\": model\n-        }\n-        \n-        response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream)\n-\n-        if stream:\n-            return cls.process_streaming_response(response)\n-        else:\n-            return cls.process_non_streaming_response(response)\n-\n-    @classmethod\n-    def process_non_streaming_response(cls, response):\n-        if response.status_code == 200:\n-            try:\n-                content = response.text.lstrip('\u001e')\n-                data = json.loads(content)\n-                return data.get('message', '')\n-            except json.JSONDecodeError:\n-                return \"Error: Unable to decode JSON response\"\n-        else:\n-            return f\"Error: {response.status_code}\"\n-\n-    @classmethod\n-    def process_streaming_response(cls, response):\n-        full_message = \"\"\n-        for line in response.iter_lines(decode_unicode=True):\n-            if line:\n-                try:\n-                    line = line.lstrip('\u001e')\n-                    data = json.loads(line)\n-                    if data.get('finish'):\n-                        break\n-                    message = data.get('message', '')\n-                    if message:\n-                        yield message[len(full_message):]\n-                        full_message = message\n-                except json.JSONDecodeError:\n-                    pass\ndiff --git a/g4f/Provider/nexra/NexraChatGptWeb.py b/g4f/Provider/nexra/NexraChatGptWeb.py\ndeleted file mode 100644\nindex f82694d459a..00000000000\n--- a/g4f/Provider/nexra/NexraChatGptWeb.py\n+++ /dev/null\n@@ -1,64 +0,0 @@\n-from __future__ import annotations\n-\n-import json\n-import requests\n-\n-from ...typing import CreateResult, Messages\n-from ..base_provider import ProviderModelMixin, AbstractProvider\n-from ..helper import format_prompt\n-\n-class NexraChatGptWeb(AbstractProvider, ProviderModelMixin):\n-    label = \"Nexra ChatGPT Web\"\n-    url = \"https://nexra.aryahcr.cc/documentation/chatgpt/en\"\n-    working = True\n-    \n-    default_model = \"gptweb\"\n-    models = [default_model]\n-    model_aliases = {\"gpt-4\": \"gptweb\"}\n-    api_endpoints = {\"gptweb\": \"https://nexra.aryahcr.cc/api/chat/gptweb\"}\n-\n-    @classmethod\n-    def get_model(cls, model: str) -> str:\n-        if model in cls.models:\n-            return model\n-        elif model in cls.model_aliases:\n-            return cls.model_aliases[model]\n-        else:\n-            return cls.default_model\n-            \n-    @classmethod\n-    def create_completion(\n-        cls,\n-        model: str,\n-        messages: Messages,\n-        proxy: str = None,\n-        markdown: bool = False,\n-        **kwargs\n-    ) -> CreateResult:\n-        model = cls.get_model(model)\n-        api_endpoint = cls.api_endpoints.get(model, cls.api_endpoints[cls.default_model])\n-\n-        headers = {\n-            'Content-Type': 'application/json'\n-        }\n-        \n-        data = {\n-            \"prompt\": format_prompt(messages),\n-            \"markdown\": markdown\n-        }\n-        \n-        response = requests.post(api_endpoint, headers=headers, json=data)\n-\n-        return cls.process_response(response)\n-\n-    @classmethod\n-    def process_response(cls, response):\n-        if response.status_code == 200:\n-            try:\n-                content = response.text.lstrip('_')\n-                json_response = json.loads(content)\n-                return json_response.get('gpt', '')\n-            except json.JSONDecodeError:\n-                return \"Error: Unable to decode JSON response\"\n-        else:\n-            return f\"Error: {response.status_code}\"\ndiff --git a/g4f/Provider/nexra/__init__.py b/g4f/Provider/nexra/__init__.py\nindex 6121fdc00ec..bebc1fb6f55 100644\n--- a/g4f/Provider/nexra/__init__.py\n+++ b/g4f/Provider/nexra/__init__.py\n@@ -1,9 +1,6 @@\n from .NexraBing                import NexraBing\n from .NexraBlackbox            import NexraBlackbox\n from .NexraChatGPT             import NexraChatGPT\n-from .NexraChatGPT4o           import NexraChatGPT4o\n-from .NexraChatGptV2           import NexraChatGptV2\n-from .NexraChatGptWeb          import NexraChatGptWeb\n from .NexraDallE               import NexraDallE\n from .NexraDallE2              import NexraDallE2\n from .NexraEmi                 import NexraEmi\ndiff --git a/g4f/__init__.py b/g4f/__init__.py\nindex ddd79fdb0e6..d77fe76097a 100644\n--- a/g4f/__init__.py\n+++ b/g4f/__init__.py\n@@ -4,6 +4,7 @@\n \n from . import debug, version\n from .models import Model\n+from .client import Client, AsyncClient\n from .typing import Messages, CreateResult, AsyncResult, Union\n from .errors import StreamNotSupportedError, ModelNotAllowedError\n from .cookies import get_cookies, set_cookies\ndiff --git a/g4f/api/__init__.py b/g4f/api/__init__.py\nindex 83df469a835..754a48f1cf0 100644\n--- a/g4f/api/__init__.py\n+++ b/g4f/api/__init__.py\n@@ -14,17 +14,18 @@\n from fastapi.encoders import jsonable_encoder\n from fastapi.middleware.cors import CORSMiddleware\n from pydantic import BaseModel\n-from typing import Union, Optional\n+from typing import Union, Optional, Iterator\n \n import g4f\n import g4f.debug\n-from g4f.client import Client\n+from g4f.client import Client, ChatCompletion, ChatCompletionChunk, ImagesResponse\n from g4f.typing import Messages\n from g4f.cookies import read_cookie_files\n \n-def create_app():\n+def create_app(g4f_api_key: str = None):\n     app = FastAPI()\n-    api = Api(app)\n+\n+    # Add CORS middleware\n     app.add_middleware(\n         CORSMiddleware,\n         allow_origin_regex=\".*\",\n@@ -32,18 +33,19 @@ def create_app():\n         allow_methods=[\"*\"],\n         allow_headers=[\"*\"],\n     )\n+\n+    api = Api(app, g4f_api_key=g4f_api_key)\n     api.register_routes()\n     api.register_authorization()\n     api.register_validation_exception_handler()\n+\n+    # Read cookie files if not ignored\n     if not AppConfig.ignore_cookie_files:\n         read_cookie_files()\n-    return app\n \n-def create_app_debug():\n-    g4f.debug.logging = True\n-    return create_app()\n+    return app\n \n-class ChatCompletionsForm(BaseModel):\n+class ChatCompletionsConfig(BaseModel):\n     messages: Messages\n     model: str\n     provider: Optional[str] = None\n@@ -55,15 +57,12 @@ class ChatCompletionsForm(BaseModel):\n     web_search: Optional[bool] = None\n     proxy: Optional[str] = None\n \n-class ImagesGenerateForm(BaseModel):\n-    model: Optional[str] = None\n-    provider: Optional[str] = None\n+class ImageGenerationConfig(BaseModel):\n     prompt: str\n-    response_format: Optional[str] = None\n-    api_key: Optional[str] = None\n-    proxy: Optional[str] = None\n+    model: Optional[str] = None\n+    response_format: str = \"url\"\n \n-class AppConfig():\n+class AppConfig:\n     ignored_providers: Optional[list[str]] = None\n     g4f_api_key: Optional[str] = None\n     ignore_cookie_files: bool = False\n@@ -74,16 +73,23 @@ def set_config(cls, **data):\n         for key, value in data.items():\n             setattr(cls, key, value)\n \n+list_ignored_providers: list[str] = None\n+\n+def set_list_ignored_providers(ignored: list[str]):\n+    global list_ignored_providers\n+    list_ignored_providers = ignored\n+\n class Api:\n-    def __init__(self, app: FastAPI) -> None:\n+    def __init__(self, app: FastAPI, g4f_api_key=None) -> None:\n         self.app = app\n         self.client = Client()\n+        self.g4f_api_key = g4f_api_key\n         self.get_g4f_api_key = APIKeyHeader(name=\"g4f-api-key\")\n \n     def register_authorization(self):\n         @self.app.middleware(\"http\")\n         async def authorization(request: Request, call_next):\n-            if AppConfig.g4f_api_key and request.url.path in [\"/v1/chat/completions\", \"/v1/completions\"]:\n+            if self.g4f_api_key and request.url.path in [\"/v1/chat/completions\", \"/v1/completions\", \"/v1/images/generate\"]:\n                 try:\n                     user_g4f_api_key = await self.get_g4f_api_key(request)\n                 except HTTPException as e:\n@@ -92,22 +98,26 @@ async def authorization(request: Request, call_next):\n                             status_code=HTTP_401_UNAUTHORIZED,\n                             content=jsonable_encoder({\"detail\": \"G4F API key required\"}),\n                         )\n-                if not secrets.compare_digest(AppConfig.g4f_api_key, user_g4f_api_key):\n+                if not secrets.compare_digest(self.g4f_api_key, user_g4f_api_key):\n                     return JSONResponse(\n                         status_code=HTTP_403_FORBIDDEN,\n                         content=jsonable_encoder({\"detail\": \"Invalid G4F API key\"}),\n                     )\n-            return await call_next(request)\n+\n+            response = await call_next(request)\n+            return response\n \n     def register_validation_exception_handler(self):\n         @self.app.exception_handler(RequestValidationError)\n         async def validation_exception_handler(request: Request, exc: RequestValidationError):\n             details = exc.errors()\n-            modified_details = [{\n-                \"loc\": error[\"loc\"],\n-                \"message\": error[\"msg\"],\n-                \"type\": error[\"type\"],\n-            } for error in details]\n+            modified_details = []\n+            for error in details:\n+                modified_details.append({\n+                    \"loc\": error[\"loc\"],\n+                    \"message\": error[\"msg\"],\n+                    \"type\": error[\"type\"],\n+                })\n             return JSONResponse(\n                 status_code=HTTP_422_UNPROCESSABLE_ENTITY,\n                 content=jsonable_encoder({\"detail\": modified_details}),\n@@ -121,25 +131,23 @@ async def read_root():\n         @self.app.get(\"/v1\")\n         async def read_root_v1():\n             return HTMLResponse('g4f API: Go to '\n-                                '<a href=\"/v1/chat/completions\">chat/completions</a> '\n-                                'or <a href=\"/v1/models\">models</a>.')\n+                                '<a href=\"/v1/chat/completions\">chat/completions</a>, '\n+                                '<a href=\"/v1/models\">models</a>, or '\n+                                '<a href=\"/v1/images/generate\">images/generate</a>.')\n \n         @self.app.get(\"/v1/models\")\n         async def models():\n-            model_list = {\n-                model: g4f.models.ModelUtils.convert[model]\n+            model_list = dict(\n+                (model, g4f.models.ModelUtils.convert[model])\n                 for model in g4f.Model.__all__()\n-            }\n+            )\n             model_list = [{\n                 'id': model_id,\n                 'object': 'model',\n                 'created': 0,\n                 'owned_by': model.base_provider\n             } for model_id, model in model_list.items()]\n-            return JSONResponse({\n-                \"object\": \"list\",\n-                \"data\": model_list,\n-            })\n+            return JSONResponse(model_list)\n \n         @self.app.get(\"/v1/models/{model_name}\")\n         async def model_info(model_name: str):\n@@ -155,7 +163,7 @@ async def model_info(model_name: str):\n                 return JSONResponse({\"error\": \"The model does not exist.\"})\n \n         @self.app.post(\"/v1/chat/completions\")\n-        async def chat_completions(config: ChatCompletionsForm, request: Request = None, provider: str = None):\n+        async def chat_completions(config: ChatCompletionsConfig, request: Request = None, provider: str = None):\n             try:\n                 config.provider = provider if config.provider is None else config.provider\n                 if config.api_key is None and request is not None:\n@@ -164,17 +172,27 @@ async def chat_completions(config: ChatCompletionsForm, request: Request = None,\n                         auth_header = auth_header.split(None, 1)[-1]\n                         if auth_header and auth_header != \"Bearer\":\n                             config.api_key = auth_header\n-                # Use the asynchronous create method and await it\n-                response = await self.client.chat.completions.async_create(\n+\n+                # Create the completion response\n+                response = self.client.chat.completions.create(\n                     **{\n                         **AppConfig.defaults,\n                         **config.dict(exclude_none=True),\n                     },\n                     ignored=AppConfig.ignored_providers\n                 )\n-                if not config.stream:\n+\n+                # Check if the response is synchronous or asynchronous\n+                if isinstance(response, ChatCompletion):\n+                    # Synchronous response\n                     return JSONResponse(response.to_json())\n \n+                if not config.stream:\n+                    # If the response is an iterator but not streaming, collect the result\n+                    response_list = list(response) if isinstance(response, Iterator) else [response]\n+                    return JSONResponse(response_list[0].to_json())\n+\n+                # Streaming response\n                 async def streaming():\n                     try:\n                         async for chunk in response:\n@@ -185,41 +203,38 @@ async def streaming():\n                         logging.exception(e)\n                         yield f'data: {format_exception(e, config)}\\n\\n'\n                     yield \"data: [DONE]\\n\\n\"\n+\n                 return StreamingResponse(streaming(), media_type=\"text/event-stream\")\n \n             except Exception as e:\n                 logging.exception(e)\n                 return Response(content=format_exception(e, config), status_code=500, media_type=\"application/json\")\n \n-        @self.app.post(\"/v1/completions\")\n-        async def completions():\n-            return Response(content=json.dumps({'info': 'Not working yet.'}, indent=4), media_type=\"application/json\")\n-\n-        @self.app.post(\"/v1/images/generations\")\n-        async def images_generate(config: ImagesGenerateForm, request: Request = None, provider: str = None):\n+        @self.app.post(\"/v1/images/generate\")\n+        async def generate_image(config: ImageGenerationConfig):\n             try:\n-                config.provider = provider if config.provider is None else config.provider\n-                if config.api_key is None and request is not None:\n-                    auth_header = request.headers.get(\"Authorization\")\n-                    if auth_header is not None:\n-                        auth_header = auth_header.split(None, 1)[-1]\n-                        if auth_header and auth_header != \"Bearer\":\n-                            config.api_key = auth_header\n-                # Use the asynchronous generate method and await it\n-                response = await self.client.images.async_generate(\n-                    **config.dict(exclude_none=True),\n+                response: ImagesResponse = await self.client.images.async_generate(\n+                    prompt=config.prompt,\n+                    model=config.model,\n+                    response_format=config.response_format\n                 )\n-                return JSONResponse(response.to_json())\n+                # Convert Image objects to dictionaries\n+                response_data = [image.to_dict() for image in response.data]\n+                return JSONResponse({\"data\": response_data})\n             except Exception as e:\n                 logging.exception(e)\n                 return Response(content=format_exception(e, config), status_code=500, media_type=\"application/json\")\n \n-def format_exception(e: Exception, config: ChatCompletionsForm) -> str:\n+        @self.app.post(\"/v1/completions\")\n+        async def completions():\n+            return Response(content=json.dumps({'info': 'Not working yet.'}, indent=4), media_type=\"application/json\")\n+\n+def format_exception(e: Exception, config: Union[ChatCompletionsConfig, ImageGenerationConfig]) -> str:\n     last_provider = g4f.get_last_provider(True)\n     return json.dumps({\n         \"error\": {\"message\": f\"{e.__class__.__name__}: {e}\"},\n-        \"model\": last_provider.get(\"model\") if last_provider else config.model,\n-        \"provider\": last_provider.get(\"name\") if last_provider else config.provider\n+        \"model\": last_provider.get(\"model\") if last_provider else getattr(config, 'model', None),\n+        \"provider\": last_provider.get(\"name\") if last_provider else getattr(config, 'provider', None)\n     })\n \n def run_api(\n@@ -228,18 +243,22 @@ def run_api(\n     bind: str = None,\n     debug: bool = False,\n     workers: int = None,\n-    use_colors: bool = None\n+    use_colors: bool = None,\n+    g4f_api_key: str = None\n ) -> None:\n     print(f'Starting server... [g4f v-{g4f.version.utils.current_version}]' + (\" (debug)\" if debug else \"\"))\n     if use_colors is None:\n         use_colors = debug\n     if bind is not None:\n         host, port = bind.split(\":\")\n+    if debug:\n+        g4f.debug.logging = True\n     uvicorn.run(\n-        f\"g4f.api:create_app{'_debug' if debug else ''}\",\n-        host=host, port=int(port),\n-        workers=workers,\n-        use_colors=use_colors,\n-        factory=True,\n+        \"g4f.api:create_app\", \n+        host=host, \n+        port=int(port), \n+        workers=workers, \n+        use_colors=use_colors, \n+        factory=True, \n         reload=debug\n     )\ndiff --git a/g4f/client/__init__.py b/g4f/client/__init__.py\nindex 9fb3551e29f..d1e7e298458 100644\n--- a/g4f/client/__init__.py\n+++ b/g4f/client/__init__.py\n@@ -1,2 +1,2 @@\n from .stubs import ChatCompletion, ChatCompletionChunk, ImagesResponse\n-from .client import Client\n+from .client import Client, AsyncClient\ndiff --git a/g4f/client/client.py b/g4f/client/client.py\nindex 41238df5ef1..8e19521326f 100644\n--- a/g4f/client/client.py\n+++ b/g4f/client/client.py\n@@ -140,6 +140,29 @@ def images(self) -> Images:\n     async def async_images(self) -> Images:\n         return self._images\n \n+# For backwards compatibility and legacy purposes, use Client instead\n+class AsyncClient(Client):\n+    \"\"\"Legacy AsyncClient that redirects to the main Client class.\n+    This class exists for backwards compatibility.\"\"\"\n+    \n+    def __init__(self, *args, **kwargs):\n+        import warnings\n+        warnings.warn(\n+            \"AsyncClient is deprecated and will be removed in a future version. \"\n+            \"Use Client instead, which now supports both sync and async operations.\",\n+            DeprecationWarning,\n+            stacklevel=2\n+        )\n+        super().__init__(*args, **kwargs)\n+\n+    async def chat_complete(self, *args, **kwargs):\n+        \"\"\"Legacy method that redirects to async_create\"\"\"\n+        return await self.chat.completions.async_create(*args, **kwargs)\n+\n+    async def create_image(self, *args, **kwargs):\n+        \"\"\"Legacy method that redirects to async_generate\"\"\"\n+        return await self.images.async_generate(*args, **kwargs)\n+\n class Completions:\n     def __init__(self, client: Client, provider: ProviderType = None):\n         self.client: Client = client\n@@ -508,3 +531,4 @@ def _save_image(self, image: 'PILImage') -> str:\n     async def create_variation(self, image: Union[str, bytes], model: str = None, response_format: str = \"url\", **kwargs):\n         # Existing implementation, adjust if you want to support b64_json here as well\n         pass\n+\ndiff --git a/g4f/gui/client/index.html b/g4f/gui/client/index.html\nindex 1a660062ce2..7e8ef09cb0c 100644\n--- a/g4f/gui/client/index.html\n+++ b/g4f/gui/client/index.html\n@@ -224,28 +224,35 @@ <h3>Settings</h3>\n                 </div>\n             </div>\n             <div class=\"buttons\">\n-                <div class=\"field\">\n-                    <select name=\"model\" id=\"model\">\n-                        <option value=\"\">Model: Default</option>\n-                        <option value=\"gpt-4\">gpt-4</option>\n-                        <option value=\"gpt-3.5-turbo\">gpt-3.5-turbo</option>\n-                        <option value=\"llama-3-70b-chat\">llama-3-70b-chat</option>\n-                        <option value=\"llama-3.1-70b\">llama-3.1-70b</option>\n-                        <option value=\"gemini-pro\">gemini-pro</option>\n-                        <option value=\"\">----</option>\n-                    </select>\n-                    <select name=\"model2\" id=\"model2\" class=\"hidden\"></select>\n-                </div>\n-                <div class=\"field\">\n-                    <select name=\"provider\" id=\"provider\">\n-                        <option value=\"\">Provider: Auto</option>\n-                        <option value=\"Bing\">Bing</option>\n-                        <option value=\"OpenaiChat\">OpenAI ChatGPT</option>\n-                        <option value=\"Gemini\">Gemini</option>\n-                        <option value=\"Liaobots\">Liaobots</option>\n-                        <option value=\"MetaAI\">Meta AI</option>\n-                        <option value=\"You\">You</option>\n-                        <option value=\"\">----</option>\n+               <div class=\"field\">\n+                  <select name=\"model\" id=\"model\">\n+                     <option value=\"\">Model: Default</option>\n+                     <option value=\"gpt-4\">gpt-4</option>\n+                     <option value=\"gpt-4o\">gpt-4o</option>\n+                     <option value=\"gpt-4o-mini\">gpt-4o-mini</option>\n+                     <option value=\"llama-3.1-70b\">llama-3.1-70b</option>\n+                     <option value=\"llama-3.1-70b\">llama-3.1-405b</option>\n+                     <option value=\"llama-3.1-70b\">mixtral-8x7b</option>\n+                     <option value=\"gemini-pro\">gemini-pro</option>\n+                     <option value=\"gemini-flash\">gemini-flash</option>\n+                     <option value=\"claude-3-haiku\">claude-3-haiku</option>\n+                     <option value=\"claude-3.5-sonnet\">claude-3.5-sonnet</option>\n+                     <option value=\"\">----</option>\n+                  </select>\n+                  <select name=\"model2\" id=\"model2\" class=\"hidden\"></select>\n+               </div>\n+               <div class=\"field\">\n+                  <select name=\"provider\" id=\"provider\">\n+                     <option value=\"\">Provider: Auto</option>\n+                     <option value=\"OpenaiChat\">OpenAI ChatGPT</option>\n+                     <option value=\"Gemini\">Gemini</option>\n+                     <option value=\"MetaAI\">Meta AI</option>\n+                     <option value=\"DeepInfraChat\">DeepInfraChat</option>\n+                     <option value=\"Blackbox\">Blackbox</option>\n+                     <option value=\"HuggingChat\">HuggingChat</option>\n+                     <option value=\"DDG\">DDG</option>\n+                     <option value=\"Pizzagpt\">Pizzagpt</option>\n+                     <option value=\"\">----</option>\n                     </select>\n                 </div>\n             </div>\ndiff --git a/g4f/gui/client/static/js/chat.v1.js b/g4f/gui/client/static/js/chat.v1.js\nindex d5a1ffaa852..42ddb129e4c 100644\n--- a/g4f/gui/client/static/js/chat.v1.js\n+++ b/g4f/gui/client/static/js/chat.v1.js\n@@ -338,6 +338,14 @@ const prepare_messages = (messages, message_index = -1) => {\n         messages = messages.filter((_, index) => message_index >= index);\n     }\n \n+    let new_messages = [];\n+    if (systemPrompt?.value) {\n+        new_messages.push({\n+            \"role\": \"system\",\n+            \"content\": systemPrompt.value\n+        });\n+    }\n+\n     // Remove history, if it's selected\n     if (document.getElementById('history')?.checked) {\n         if (message_index == null) {\n@@ -347,13 +355,6 @@ const prepare_messages = (messages, message_index = -1) => {\n         }\n     }\n \n-    let new_messages = [];\n-    if (systemPrompt?.value) {\n-        new_messages.push({\n-            \"role\": \"system\",\n-            \"content\": systemPrompt.value\n-        });\n-    }\n     messages.forEach((new_message) => {\n         // Include only not regenerated messages\n         if (new_message && !new_message.regenerate) {\n@@ -366,6 +367,7 @@ const prepare_messages = (messages, message_index = -1) => {\n     return new_messages;\n }\n \n+\n async function add_message_chunk(message) {\n     if (message.type == \"conversation\") {\n         console.info(\"Conversation used:\", message.conversation)\ndiff --git a/g4f/gui/server/api.py b/g4f/gui/server/api.py\nindex 57f3eaa192c..7aac650ab36 100644\n--- a/g4f/gui/server/api.py\n+++ b/g4f/gui/server/api.py\n@@ -2,12 +2,11 @@\n \n import logging\n import os\n-import os.path\n import uuid\n import asyncio\n import time\n from aiohttp import ClientSession\n-from typing import Iterator, Optional\n+from typing import Iterator, Optional, AsyncIterator, Union\n from flask import send_from_directory\n \n from g4f import version, models\n@@ -20,21 +19,20 @@\n from g4f.providers.base_provider import ProviderModelMixin, FinishReason\n from g4f.providers.conversation import BaseConversation\n \n-conversations: dict[dict[str, BaseConversation]] = {}\n+# Define the directory for generated images\n images_dir = \"./generated_images\"\n \n+# Function to ensure the images directory exists\n+def ensure_images_dir():\n+    if not os.path.exists(images_dir):\n+        os.makedirs(images_dir)\n+\n+conversations: dict[dict[str, BaseConversation]] = {}\n+\n \n class Api:\n     @staticmethod\n     def get_models() -> list[str]:\n-        \"\"\"\n-        Return a list of all models.\n-\n-        Fetches and returns a list of all available models in the system.\n-\n-        Returns:\n-            List[str]: A list of model names.\n-        \"\"\"\n         return models._all_models\n \n     @staticmethod\n@@ -82,9 +80,6 @@ def get_image_models() -> list[dict]:\n \n     @staticmethod\n     def get_providers() -> list[str]:\n-        \"\"\"\n-        Return a list of all working providers.\n-        \"\"\"\n         return {\n             provider.__name__: (\n                 provider.label if hasattr(provider, \"label\") else provider.__name__\n@@ -99,12 +94,6 @@ def get_providers() -> list[str]:\n \n     @staticmethod\n     def get_version():\n-        \"\"\"\n-        Returns the current and latest version of the application.\n-\n-        Returns:\n-            dict: A dictionary containing the current and latest version.\n-        \"\"\"\n         try:\n             current_version = version.utils.current_version\n         except VersionNotFoundError:\n@@ -115,18 +104,10 @@ def get_version():\n         }\n \n     def serve_images(self, name):\n+        ensure_images_dir()\n         return send_from_directory(os.path.abspath(images_dir), name)\n \n     def _prepare_conversation_kwargs(self, json_data: dict, kwargs: dict):\n-        \"\"\"\n-        Prepares arguments for chat completion based on the request data.\n-\n-        Reads the request and prepares the necessary arguments for handling \n-        a chat completion request.\n-\n-        Returns:\n-            dict: Arguments prepared for chat completion.\n-        \"\"\"\n         model = json_data.get('model') or models.default\n         provider = json_data.get('provider')\n         messages = json_data['messages']\n@@ -134,7 +115,7 @@ def _prepare_conversation_kwargs(self, json_data: dict, kwargs: dict):\n         if api_key is not None:\n             kwargs[\"api_key\"] = api_key\n         if json_data.get('web_search'):\n-            if provider in (\"Bing\", \"HuggingChat\"):\n+            if provider:\n                 kwargs['web_search'] = True\n             else:\n                 from .internet import get_search_message\n@@ -159,13 +140,11 @@ def _create_response_stream(self, kwargs: dict, conversation_id: str, provider:\n             result = ChatCompletion.create(**kwargs)\n             first = True\n             if isinstance(result, ImageResponse):\n-                # \u042f\u043a\u0449\u043e \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442 \u0454 ImageResponse, \u043e\u0431\u0440\u043e\u0431\u043b\u044f\u0454\u043c\u043e \u0439\u043e\u0433\u043e \u044f\u043a \u043e\u0434\u0438\u043d\u043e\u0447\u043d\u0438\u0439 \u0435\u043b\u0435\u043c\u0435\u043d\u0442\n                 if first:\n                     first = False\n                     yield self._format_json(\"provider\", get_last_provider(True))\n                 yield self._format_json(\"content\", str(result))\n             else:\n-                # \u042f\u043a\u0449\u043e \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442 \u0454 \u0456\u0442\u0435\u0440\u0430\u0431\u0435\u043b\u044c\u043d\u0438\u043c, \u043e\u0431\u0440\u043e\u0431\u043b\u044f\u0454\u043c\u043e \u0439\u043e\u0433\u043e \u044f\u043a \u0440\u0430\u043d\u0456\u0448\u0435\n                 for chunk in result:\n                     if first:\n                         first = False\n@@ -181,7 +160,6 @@ def _create_response_stream(self, kwargs: dict, conversation_id: str, provider:\n                     elif isinstance(chunk, ImagePreview):\n                         yield self._format_json(\"preview\", chunk.to_string())\n                     elif isinstance(chunk, ImageResponse):\n-                        # \u041e\u0431\u0440\u043e\u0431\u043a\u0430 ImageResponse\n                         images = asyncio.run(self._copy_images(chunk.get_list(), chunk.options.get(\"cookies\")))\n                         yield self._format_json(\"content\", str(ImageResponse(images, chunk.alt)))\n                     elif not isinstance(chunk, FinishReason):\n@@ -190,8 +168,8 @@ def _create_response_stream(self, kwargs: dict, conversation_id: str, provider:\n             logging.exception(e)\n             yield self._format_json('error', get_error_message(e))\n \n-    # \u0414\u043e\u0434\u0430\u0439\u0442\u0435 \u0446\u0435\u0439 \u043c\u0435\u0442\u043e\u0434 \u0434\u043e \u043a\u043b\u0430\u0441\u0443 Api\n     async def _copy_images(self, images: list[str], cookies: Optional[Cookies] = None):\n+        ensure_images_dir()\n         async with ClientSession(\n             connector=get_connector(None, os.environ.get(\"G4F_PROXY\")),\n             cookies=cookies\n@@ -212,16 +190,6 @@ async def copy_image(image):\n             return await asyncio.gather(*[copy_image(image) for image in images])\n \n     def _format_json(self, response_type: str, content):\n-        \"\"\"\n-        Formats and returns a JSON response.\n-\n-        Args:\n-            response_type (str): The type of the response.\n-            content: The content to be included in the response.\n-\n-        Returns:\n-            str: A JSON formatted string.\n-        \"\"\"\n         return {\n             'type': response_type,\n             response_type: content\n@@ -229,15 +197,6 @@ def _format_json(self, response_type: str, content):\n \n \n def get_error_message(exception: Exception) -> str:\n-    \"\"\"\n-    Generates a formatted error message from an exception.\n-\n-    Args:\n-        exception (Exception): The exception to format.\n-\n-    Returns:\n-        str: A formatted error message string.\n-    \"\"\"\n     message = f\"{type(exception).__name__}: {exception}\"\n     provider = get_last_provider()\n     if provider is None:\ndiff --git a/g4f/gui/server/website.py b/g4f/gui/server/website.py\nindex 5e633674847..3cabcdf3e44 100644\n--- a/g4f/gui/server/website.py\n+++ b/g4f/gui/server/website.py\n@@ -27,6 +27,10 @@ def redirect_home():\n                 'function': redirect_home,\n                 'methods': ['GET', 'POST']\n             },\n+            '/images/': {\n+                'function': redirect_home,\n+                'methods': ['GET', 'POST']\n+            },\n         }\n \n     def _chat(self, conversation_id):\n@@ -35,4 +39,4 @@ def _chat(self, conversation_id):\n         return render_template('index.html', chat_id=conversation_id)\n \n     def _index(self):\n-        return render_template('index.html', chat_id=str(uuid.uuid4()))\n\\ No newline at end of file\n+        return render_template('index.html', chat_id=str(uuid.uuid4()))\ndiff --git a/g4f/models.py b/g4f/models.py\nindex 1cea644783e..32a12d10057 100644\n--- a/g4f/models.py\n+++ b/g4f/models.py\n@@ -23,7 +23,6 @@\n     DDG,\n     DeepInfra,\n     DeepInfraChat,\n-    DeepInfraImage,\n     Editee,\n     Free2GPT,\n     FreeChatgpt,\n@@ -31,6 +30,7 @@\n     FreeNetfly,\n     Gemini,\n     GeminiPro,\n+    GizAI,\n     GigaChat,\n     GPROChat,\n     HuggingChat,\n@@ -42,9 +42,6 @@\n     NexraBing,\n     NexraBlackbox,\n     NexraChatGPT,\n-    NexraChatGPT4o,\n-    NexraChatGptV2,\n-    NexraChatGptWeb,\n     NexraDallE,\n     NexraDallE2,\n     NexraEmi,\n@@ -87,6 +84,8 @@ def __all__() -> list[str]:\n         \"\"\"Returns a list of all model names.\"\"\"\n         return _all_models\n \n+\n+### Default ###\n default = Model(\n     name          = \"\",\n     base_provider = \"\",\n@@ -113,6 +112,8 @@ def __all__() -> list[str]:\n     ])\n )\n \n+\n+\n ############\n ### Text ###\n ############\n@@ -136,13 +137,13 @@ def __all__() -> list[str]:\n gpt_4o = Model(\n     name          = 'gpt-4o',\n     base_provider = 'OpenAI',\n-    best_provider = IterListProvider([NexraChatGPT4o, Blackbox, ChatGptEs, AmigoChat, DarkAI, Editee, Liaobots, Airforce, OpenaiChat])\n+    best_provider = IterListProvider([NexraChatGPT, Blackbox, ChatGptEs, AmigoChat, DarkAI, Editee, GizAI, Airforce, Liaobots, OpenaiChat])\n )\n \n gpt_4o_mini = Model(\n     name          = 'gpt-4o-mini',\n     base_provider = 'OpenAI',\n-    best_provider = IterListProvider([DDG, ChatGptEs, FreeNetfly, Pizzagpt, MagickPen, AmigoChat, RubiksAI, Liaobots, Airforce, ChatgptFree, Koala, OpenaiChat, ChatGpt])\n+    best_provider = IterListProvider([DDG, ChatGptEs, FreeNetfly, Pizzagpt, MagickPen, AmigoChat, RubiksAI, Liaobots, Airforce, GizAI, ChatgptFree, Koala, OpenaiChat, ChatGpt])\n )\n \n gpt_4_turbo = Model(\n@@ -154,7 +155,7 @@ def __all__() -> list[str]:\n gpt_4 = Model(\n     name          = 'gpt-4',\n     base_provider = 'OpenAI',\n-    best_provider = IterListProvider([Chatgpt4Online, Ai4Chat, NexraBing, NexraChatGPT, NexraChatGptV2, NexraChatGptWeb, Airforce, Bing, OpenaiChat, gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider])\n+    best_provider = IterListProvider([Chatgpt4Online, Ai4Chat, NexraBing, NexraChatGPT, Airforce, Bing, OpenaiChat, gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider])\n )\n \n # o1\n@@ -167,7 +168,7 @@ def __all__() -> list[str]:\n o1_mini = Model(\n     name          = 'o1-mini',\n     base_provider = 'OpenAI',\n-    best_provider = AmigoChat\n+    best_provider = IterListProvider([AmigoChat, GizAI])\n )\n \n \n@@ -216,13 +217,13 @@ def __all__() -> list[str]:\n llama_3_1_8b = Model(\n     name          = \"llama-3.1-8b\",\n     base_provider = \"Meta Llama\",\n-    best_provider = IterListProvider([Blackbox, DeepInfraChat, ChatHub, Cloudflare, Airforce, PerplexityLabs])\n+    best_provider = IterListProvider([Blackbox, DeepInfraChat, ChatHub, Cloudflare, Airforce, GizAI, PerplexityLabs])\n )\n \n llama_3_1_70b = Model(\n     name          = \"llama-3.1-70b\",\n     base_provider = \"Meta Llama\",\n-    best_provider = IterListProvider([DDG, HuggingChat, Blackbox, FreeGpt, TeachAnything, Free2GPT, DeepInfraChat, DarkAI, Airforce, AiMathGPT, RubiksAI, HuggingFace, PerplexityLabs])\n+    best_provider = IterListProvider([DDG, HuggingChat, Blackbox, FreeGpt, TeachAnything, Free2GPT, DeepInfraChat, DarkAI, Airforce, AiMathGPT, RubiksAI, GizAI, HuggingFace, PerplexityLabs])\n )\n \n llama_3_1_405b = Model(\n@@ -299,7 +300,7 @@ def __all__() -> list[str]:\n mistral_large = Model(\n     name          = \"mistral-large\",\n     base_provider = \"Mistral\",\n-    best_provider = Editee\n+    best_provider = IterListProvider([Editee, GizAI])\n )\n \n \n@@ -347,13 +348,13 @@ def __all__() -> list[str]:\n gemini_pro = Model(\n     name          = 'gemini-pro',\n     base_provider = 'Google DeepMind',\n-    best_provider = IterListProvider([GeminiPro, Blackbox, AIChatFree, GPROChat, NexraGeminiPro, AmigoChat, Editee, Liaobots, Airforce])\n+    best_provider = IterListProvider([GeminiPro, Blackbox, AIChatFree, GPROChat, NexraGeminiPro, AmigoChat, Editee, GizAI, Airforce, Liaobots])\n )\n \n gemini_flash = Model(\n     name          = 'gemini-flash',\n     base_provider = 'Google DeepMind',\n-    best_provider = IterListProvider([Blackbox, Liaobots, Airforce])\n+    best_provider = IterListProvider([Blackbox, GizAI, Airforce, Liaobots])\n )\n \n gemini = Model(\n@@ -424,14 +425,14 @@ def __all__() -> list[str]:\n claude_3_haiku = Model(\n     name          = 'claude-3-haiku',\n     base_provider = 'Anthropic',\n-    best_provider = IterListProvider([DDG, Airforce, Liaobots])\n+    best_provider = IterListProvider([DDG, Airforce, GizAI, Liaobots])\n )\n \n # claude 3.5\n claude_3_5_sonnet = Model(\n     name          = 'claude-3.5-sonnet',\n     base_provider = 'Anthropic',\n-    best_provider = IterListProvider([Blackbox, Editee, AmigoChat, Airforce, Liaobots])\n+    best_provider = IterListProvider([Blackbox, Editee, AmigoChat, Airforce, GizAI, Liaobots])\n )\n \n \n@@ -753,14 +754,14 @@ def __all__() -> list[str]:\n sdxl = Model(\n     name = 'sdxl',\n     base_provider = 'Stability AI',\n-    best_provider = IterListProvider([ReplicateHome, DeepInfraImage])\n+    best_provider = IterListProvider([ReplicateHome])\n     \n )\n \n sd_1_5 = Model(\n     name = 'sd-1.5',\n     base_provider = 'Stability AI',\n-    best_provider = NexraSD15\n+    best_provider = IterListProvider([NexraSD15, GizAI])\n     \n )\n \n@@ -771,6 +772,13 @@ def __all__() -> list[str]:\n     \n )\n \n+sd_3_5 = Model(\n+    name = 'sd-3.5',\n+    base_provider = 'Stability AI',\n+    best_provider = GizAI\n+    \n+)\n+\n ### Playground ###\n playground_v2_5 = Model(\n     name = 'playground-v2.5',\n@@ -791,7 +799,7 @@ def __all__() -> list[str]:\n flux_pro = Model(\n     name = 'flux-pro',\n     base_provider = 'Flux AI',\n-    best_provider = IterListProvider([AmigoChat, NexraFluxPro])\n+    best_provider = IterListProvider([NexraFluxPro, AmigoChat])\n     \n )\n \n@@ -840,7 +848,7 @@ def __all__() -> list[str]:\n flux_schnell = Model(\n     name = 'flux-schnell',\n     base_provider = 'Flux AI',\n-    best_provider = ReplicateHome\n+    best_provider = IterListProvider([ReplicateHome, GizAI])\n     \n )\n \n@@ -1123,6 +1131,7 @@ class ModelUtils:\n 'sdxl-turbo': sdxl_turbo,\n 'sd-1.5': sd_1_5,\n 'sd-3': sd_3,\n+'sd-3.5': sd_3_5,\n         \n         \n ### Playground ###\n\n```\n"},{"assistant_initiates":false,"asst_text":"M\u1ea1ng m\u00e1y t\u00ednh l\u00e0 m\u1ed9t ph\u1ea7n kh\u00f4ng th\u1ec3 thi\u1ebfu trong th\u1eddi \u0111\u1ea1i s\u1ed1 h\u00f3a ng\u00e0y nay. Trong s\u1ed1 c\u00e1c lo\u1ea1i m\u1ea1ng ph\u1ed5 bi\u1ebfn, m\u1ea1ng LAN \u0111\u00f3ng vai tr\u00f2 quan tr\u1ecdng trong nhi\u1ec1u \u1ee9ng d\u1ee5ng th\u1ef1c t\u1ebf. M\u1ea1ng LAN, vi\u1ebft t\u1eaft c\u1ee7a c\u1ee5m t\u1eeb \"Local Area Network\", l\u00e0 m\u1ea1ng c\u1ee5c b\u1ed9 th\u01b0\u1eddng \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng \u0111\u1ec3 k\u1ebft n\u1ed1i c\u00e1c thi\u1ebft b\u1ecb trong m\u1ed9t khu v\u1ef1c \u0111\u1ecba l\u00fd nh\u1ecf nh\u01b0 v\u0103n ph\u00f2ng, tr\u01b0\u1eddng h\u1ecdc ho\u1eb7c nh\u00e0 ri\u00eang.\n\nM\u1ea1ng LAN cho ph\u00e9p c\u00e1c thi\u1ebft b\u1ecb giao ti\u1ebfp v\u00e0 chia s\u1ebb t\u00e0i nguy\u00ean v\u1edbi nhau m\u1ed9t c\u00e1ch hi\u1ec7u qu\u1ea3. Nh\u1edd c\u00f3 m\u1ea1ng LAN, ng\u01b0\u1eddi d\u00f9ng c\u00f3 th\u1ec3 chia s\u1ebb t\u1eadp tin, t\u00e0i li\u1ec7u, m\u00e1y in, v\u00e0 th\u1eadm ch\u00ed c\u1ea3 k\u1ebft n\u1ed1i internet. \u0110i\u1ec1u n\u00e0y kh\u00f4ng ch\u1ec9 gi\u00fap ti\u1ebft ki\u1ec7m chi ph\u00ed m\u00e0 c\u00f2n t\u1ea1o \u0111i\u1ec1u ki\u1ec7n cho s\u1ef1 h\u1ee3p t\u00e1c v\u00e0 l\u00e0m vi\u1ec7c nh\u00f3m tr\u1edf n\u00ean d\u1ec5 d\u00e0ng v\u00e0 linh ho\u1ea1t h\u01a1n.\n\nM\u1ed9t trong nh\u1eefng \u01b0u \u0111i\u1ec3m n\u1ed5i b\u1eadt c\u1ee7a m\u1ea1ng LAN l\u00e0 t\u1ed1c \u0111\u1ed9 truy\u1ec1n t\u1ea3i d\u1eef li\u1ec7u cao, \u0111i\u1ec1u n\u00e0y cho ph\u00e9p c\u00e1c \u1ee9ng d\u1ee5ng v\u00e0 d\u1ecbch v\u1ee5 ch\u1ea1y m\u01b0\u1ee3t m\u00e0 h\u01a1n. Th\u00f4ng th\u01b0\u1eddng, m\u1ea1ng LAN s\u1eed d\u1ee5ng c\u00f4ng ngh\u1ec7 Ethernet ho\u1eb7c Wi-Fi \u0111\u1ec3 k\u1ebft n\u1ed1i c\u00e1c thi\u1ebft b\u1ecb trong c\u00f9ng m\u1ed9t h\u1ec7 th\u1ed1ng m\u1ea1ng. Ethernet, v\u1edbi d\u00e2y c\u00e1p v\u1eadt l\u00fd, cung c\u1ea5p k\u1ebft n\u1ed1i \u1ed5n \u0111\u1ecbnh v\u00e0 nhanh ch\u00f3ng trong khi Wi-Fi l\u1ea1i cung c\u1ea5p t\u00ednh linh ho\u1ea1t cao khi kh\u00f4ng c\u1ea7n s\u1eed d\u1ee5ng \u0111\u1ebfn d\u00e2y c\u00e1p.\n\nVi\u1ec7c tri\u1ec3n khai v\u00e0 qu\u1ea3n l\u00fd m\u1ea1ng LAN c\u0169ng kh\u00e1 \u0111\u01a1n gi\u1ea3n, v\u00e0 chi ph\u00ed \u0111\u1ea7u t\u01b0 ban \u0111\u1ea7u th\u01b0\u1eddng kh\u00f4ng qu\u00e1 cao, \u0111i\u1ec1u n\u00e0y khi\u1ebfn cho m\u1ea1ng LAN tr\u1edf th\u00e0nh l\u1ef1a ch\u1ecdn h\u00e0ng \u0111\u1ea7u cho c\u00e1c t\u1ed5 ch\u1ee9c v\u00e0 doanh nghi\u1ec7p \u1edf m\u1ecdi quy m\u00f4. V\u00ec v\u1eady, hi\u1ec3u v\u00e0 v\u1eadn d\u1ee5ng t\u1ed1i \u01b0u m\u1ea1ng LAN l\u00e0 m\u1ed9t k\u1ef9 n\u0103ng c\u00f4ng ngh\u1ec7 th\u00f4ng tin quan tr\u1ecdng cho m\u1ed7i c\u00e1 nh\u00e2n trong k\u1ef7 nguy\u00ean s\u1ed1.","behavior":"degenerate_repetition","conversation_hash":"c3323892cbbfda0961f5a83110543cb6","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-4o-2024-08-06","n_chars":1988,"n_turns_in_conversation":1,"n_words":414,"source_row_offset":10732,"source_shard":"turns-00052.parquet","timestamp":"Fri, 15 Nov 2024 05:54:45 GMT","turn_id":"ef1ed9482413aa04a25a7ca3","turn_index":0,"user_text":"Write a educational passage in Vietnamese that could appear in a textbook, giving some paragraphs or pharse that related to this question and answer set:\nC\u00e2u h\u1ecfi: M\u1ea1ng LAN l\u00e0 vi\u1ebft t\u1eaft c\u1ee7a c\u1ee5m t\u1eeb n\u00e0o?\nA. Local Arian Network.\nB. Local Arean Network.\nC. Local Area .\nD. Local Area Network.\n\u0110\u00e1p \u00e1n \u0111\u00fang: Local Area Network\nNotes that:\n1. Remember that the multichoice question above must not be included in the paragraphs or phrase\n2. You can not take an example same as the question\n3. Explain detail like in the actual textbook\n4. All instructions must be given in general form"},{"assistant_initiates":false,"asst_text":"```json\n{\"reviews\":[{\"line\":72,\"body\":\"Remove the comment `# Add any other necessary parameters` from the code. This comment does not provide any value to the code and should be eliminated.\"},{\"line\":157,\"body\":\"Remove the comment `# Add any other necessary parameters` from the code. Comments like these are unnecessary and can be misleading.\"}]}\n```","behavior":"degenerate_repetition","conversation_hash":"903512672365175cafd1366fd3775a4e","conversation_redacted":false,"conversation_toxic":false,"country":"Panama","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"English","model":"gpt-4o-mini-2024-07-18","n_chars":3288,"n_turns_in_conversation":1,"n_words":422,"source_row_offset":10733,"source_shard":"turns-00052.parquet","timestamp":"Fri, 15 Nov 2024 05:54:47 GMT","turn_id":"027eef65879ad36592184266","turn_index":0,"user_text":"Your task is to review pull requests. Instructions:\n- Provide the response in following JSON format: {\"reviews\": [{\"line\": <line_number>, \"body\": \"<review comment>\"}]}\n- Do not give positive comments or compliments.\n- Provide comments and suggestions ONLY if there is something to improve, otherwise \"reviews\" should be an empty array.\n- Write the comment in GitHub Markdown format.\n- Use the given description only for the overall context and only comment the code.\n- IMPORTANT: NEVER suggest adding comments to the code.\n\nReview the following code diff in the file \"docs/client.md\" and take the pull request title and description into account when writing the response.\n  \nPull request title: [pull] main from xtekky:main\nPull request description:\n---\nSee Commits and Changes for more details.\n\n-----\nCreated by [<img src=\"https://prod.download/pull-18h-svg\" valign=\"bottom\"/> **pull[bot]**](https://github.com/wei/pull)\n\n_Can you help keep this open source service alive? **[\ud83d\udc96 Please sponsor : )](https://prod.download/pull-pr-sponsor)**_\n---\n\nEach line is prefixed by its number. Code to review:\n```\n7:    - [Getting Started](#getting-started)\n8:    - [Switching to G4F Client](#switching-to-g4f-client)\n9:    - [Initializing the Client](#initializing-the-client)\n10:+   - [Creating Chat Completions](#creating-chat-completions)\n11:    - [Configuration](#configuration)\n12:    - [Usage Examples](#usage-examples)\n13:    - [Text Completions](#text-completions)\n57:     # Add any other necessary parameters\n58: )\n59: ```\n60:+\n61:+## Creating Chat Completions\n62:+**Here\u2019s an improved example of creating chat completions:**\n63:+```python\n64:+response = client.chat.completions.create(\n65:+    model=\"gpt-3.5-turbo\",\n66:+    messages=[\n67:+        {\n68:+            \"role\": \"user\",\n69:+            \"content\": \"Say this is a test\"\n70:+        }\n71:+    ]\n72:+    # Add any other necessary parameters\n73:+)\n74:+```\n75:+\n76:+**This example:**\n77:+   - Asks a specific question `Say this is a test`\n78:+   - Configures various parameters like temperature and max_tokens for more control over the output\n79:+   - Disables streaming for a complete response\n80:+\n81:+You can adjust these parameters based on your specific needs.\n82:  \n83: \n84: ## Configuration\n152: client = Client()\n153: \n154: response = client.images.generate(\n-    model=\"dall-e-3\",\n155:+    model=\"flux\",\n156:     prompt=\"a white siamese cat\"\n157:     # Add any other necessary parameters\n158: )\n162: print(f\"Generated image URL: {image_url}\")\n163: ```\n164: \n165:+\n166:+#### Base64 Response Format\n167:+```python\n168:+from g4f.client import Client\n169:+\n170:+client = Client()\n171:+\n172:+response = client.images.generate(\n173:+    model=\"flux\",\n174:+    prompt=\"a white siamese cat\",\n175:+    response_format=\"b64_json\"\n176:+)\n177:+\n178:+base64_text = response.data[0].b64_json\n179:+print(base64_text)\n180:+```\n181:+\n182:   \n183: \n184: ### Creating Image Variations\n```\n"},{"assistant_initiates":false,"asst_text":"\u5bf9\u4e0d\u8d77\uff0c\u6211\u4e0d\u80fd\u5b8c\u6574\u7ffb\u8bd1\u8fd9\u4e48\u957f\u7684\u6587\u672c\u3002\u4e0d\u8fc7\uff0c\u6211\u53ef\u4ee5\u5c1d\u8bd5\u4e3a\u60a8\u603b\u7ed3\u6216\u63d0\u70bc\u5176\u4e2d\u7684\u5173\u952e\u70b9\u3002\u60a8\u5e0c\u671b\u6211\u600e\u4e48\u505a\u5462\uff1f","behavior":"degenerate_repetition","conversation_hash":"c2ce60e985e8c36cd8ed56286e5fb5c1","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":"Chinese","model":"gpt-4o-2024-08-06","n_chars":25664,"n_turns_in_conversation":10,"n_words":3772,"source_row_offset":10734,"source_shard":"turns-00052.parquet","timestamp":"Fri, 15 Nov 2024 05:54:48 GMT","turn_id":"a083c3e8779595b13889972b","turn_index":0,"user_text":"109\n\u0418\u0421\u0422\u041e\u0420\u0418\u042f 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\n\u043e\u0433\u0440\u0430\u043d\u0438\u0447\u0435\u043d\u043d\u044b\u0445 \u0441\u043f\u0435\u0446\u0438\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u043c\u0438 \u0440\u0430\u043c\u043a\u0430\u043c\u0438 \u0438 \u2026 \u043e\u0442\u0440\u0430\u0436\u0430\u044e\u0449\u0438\u0445 \u043e\u0441\u043d\u043e\u0432\u043d\u044b\u0435 \u0441\u0444\u0435-\n\u0440\u044b \u0436\u0438\u0437\u043d\u0435\u0434\u0435\u044f\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438 \u0447\u0435\u043b\u043e\u0432\u0435\u043a\u0430\u00bb [6, \u0441. 134]. \u0423\u0447\u0435\u0431\u043d\u044b\u0435 \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u043d\u0438\u043a\u0438 \u043f\u0440\u0435\u0434\u043d\u0430-\n\u0437\u043d\u0430\u0447\u0435\u043d\u044b \u00ab\u0434\u043b\u044f \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0438\u043d\u043e\u0441\u0442\u0440\u0430\u043d\u043d\u043e\u043c\u0443 \u044f\u0437\u044b\u043a\u0443 \u043f\u043e\u0441\u0440\u0435\u0434\u0441\u0442\u0432\u043e\u043c \u0437\u0430\u0443\u0447\u0438\u0432\u0430\u043d\u0438\u044f \u0444\u0440\u0430\u0437 \n(\u0430 \u0442\u0430\u043a\u0436\u0435 \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u044b\u0445 \u0441\u043b\u043e\u0432, \u0441\u043b\u043e\u0432\u043e\u0441\u043e\u0447\u0435\u0442\u0430\u043d\u0438\u0439 \u0438 \u0444\u0440\u0430\u0433\u043c\u0435\u043d\u0442\u043e\u0432 \u0441\u0432\u044f\u0437\u043d\u043e\u0433\u043e \u0442\u0435\u043a\u0441\u0442\u0430), \n\u0447\u0430\u0441\u0442\u043e \u0440\u0430\u0441\u043f\u043e\u043b\u043e\u0436\u0435\u043d\u043d\u044b\u0445 \u0432 \u0444\u043e\u0440\u043c\u0435 \u0434\u0438\u0430\u043b\u043e\u0433\u0430 \u0438\u043b\u0438 \u043c\u043e\u043d\u043e\u043b\u043e\u0433\u0430\u00bb [7, \u0441. 134]. \n\u0420\u0430\u0441\u0441\u043c\u043e\u0442\u0440\u0438\u043c \u0443\u0447\u0435\u0431\u043d\u0438\u043a \u041f. \u0416\u0434\u0430\u043d\u043e\u0432\u0430 1772 \u0433., \u0432 \u043a\u043e\u0442\u043e\u0440\u043e\u043c \u043d\u0430 \u0441\u0442\u0440. 112 \u2013 162 \n\u043d\u0430\u0445\u043e\u0434\u044f\u0442\u0441\u044f \u00abFamiliar Phrases / \u0423\u043f\u043e\u0442\u0440\u0435\u0431\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0440\u0435\u0447\u0438\u00bb (\u0432\u0441\u0435\u0433\u043e 22 \u0440\u0430\u0437\u0434\u0435\u043b\u0430), \n\u043d\u0430 \u0441\u0442\u0440. 163 \u2013 299 \u2013 \u00abFamiliar Dialogues / \u0423\u043f\u043e\u0442\u0440\u0435\u0431\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0435 \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u044b\u00bb (37 \n\u043e\u0431\u044a\u0435\u043c\u043d\u044b\u0445, \u043e\u0442 \u043e\u0434\u043d\u043e\u0439 \u0434\u043e \u0448\u0435\u0441\u0442\u0438 \u0441\u0442\u0440\u0430\u043d\u0438\u0446, \u0434\u0438\u0430\u043b\u043e\u0433\u043e\u0432). \u0422\u0435\u043c\u0430\u0442\u0438\u043a\u0430 \u0434\u0438\u0430\u043b\u043e\u0433\u043e\u0432 \u043e\u0445-\n\u0432\u0430\u0442\u044b\u0432\u0430\u0435\u0442 \u043f\u0440\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u0438 \u0432\u0441\u0435 \u0441\u0444\u0435\u0440\u044b \u043f\u043e\u0432\u0441\u0435\u0434\u043d\u0435\u0432\u043d\u043e\u0439 \u0436\u0438\u0437\u043d\u0438 \u0447\u0435\u043b\u043e\u0432\u0435\u043a\u0430: \u043e\u0431\u0449\u0435\u043d\u0438\u0435 \n\u0434\u043e\u043c\u0430 \u0441 \u0447\u043b\u0435\u043d\u0430\u043c\u0438 \u0441\u0435\u043c\u044c\u0438, \u0433\u043e\u0441\u0442\u044f\u043c\u0438 \u0438 \u0441\u043b\u0443\u0433\u0430\u043c\u0438: Dialogue (\u0434\u0430\u043b\u0435\u0435 \u2013 D) 2 \u00abBefore \nGoing to Bed and After One is in Bed / \u0418\u0434\u0443\u0447\u0438 \u0441\u043f\u0430\u0442\u044c \u0438 \u0431\u0443\u0434\u0443\u0447\u0438 \u043d\u0430 \u043f\u043e\u0441\u0442\u0435\u043b\u0438\u00bb; D \n6 \u00abTo Make a Visit in the Morning / \u041f\u043e\u0441\u0435\u0442\u0438\u0442\u044c \u043a\u043e\u0433\u043e \u043f\u043e \u0443\u0442\u0440\u0443\u00bb; D 7 \u00abTo Breakfast \n/ \u0417\u0430\u0432\u0442\u0440\u0430\u043a\u0430\u0442\u044c\u00bb; D 8 \u00abBefore Dinner / \u041f\u0435\u0440\u0435\u0434 \u043e\u0431\u0435\u0434\u043e\u043c\u00bb \u0438 \u0434\u0440.; \u043e\u0431\u0449\u0435\u043d\u0438\u0435 \u0432 \u0434\u0440\u0443\u0436\u0435-\n\u0441\u043a\u043e\u043c \u043a\u0440\u0443\u0433\u0443: D 23 \u00abBetween two friends /\u041c\u0435\u0436\u0434\u0443 \u043f\u0440\u0438\u044f\u0442\u0435\u043b\u044f\u043c\u0438\u00bb; \u043e\u0431\u0449\u0435\u043d\u0438\u0435 \u0432\u043d\u0435 \n\u0434\u043e\u043c\u0430 \u0441 \u043b\u044e\u0434\u044c\u043c\u0438 \u0441\u0432\u043e\u0435\u0433\u043e \u043a\u0440\u0443\u0433\u0430 : D 1 \u00abTo Salute and Inquire after One\u2019s Health \n/ \u041f\u043e\u0437\u0434\u0440\u0430\u0432\u0438\u0442\u044c \u043a\u043e\u0433\u043e \u0438 \u0441\u043f\u0440\u0430\u0448\u0438\u0432\u0430\u0442\u044c \u043e \u0437\u0434\u0440\u0430\u0432\u0438\u0438\u00bb ; D 17 \u00abTo Retire or to Take \nOne\u2019s Leave / \u0420\u0430\u0441\u0441\u0442\u0430\u0432\u0430\u0442\u044c\u0441\u044f \u0438\u043b\u0438 \u043f\u0440\u043e\u0449\u0430\u0442\u044c\u0441\u044f\u00bb ; D 20 \u00abOf news / \u041e \u043d\u043e\u0432\u043e\u0441\u0442\u044f\u0445\u00bb; \nD 24 \u00abTo Write a Letter / \u041f\u0438\u0441\u0430\u0442\u044c \u043f\u0438\u0441\u044c\u043c\u043e\u00bb; D 26 \u00abTo Play at Cards /\u0418\u0433\u0440\u0430\u0442\u044c \u0432 \n\u043a\u0430\u0440\u0442\u044b\u00bb; D 35 \u00abOf Christening, Wedding and Burial / \u041e \u043a\u0440\u0435\u0441\u0442\u0438\u043d\u0430\u0445, \u0441\u0432\u0430\u0434\u044c\u0431\u0435 \u0438 \n\u043f\u043e\u0445\u043e\u0440\u043e\u043d\u0430\u0445\u00bb; \u043e\u0431\u0449\u0435\u043d\u0438\u0435 \u0441 \u0442\u0435\u043c\u0438, \u043a\u0442\u043e \u043e\u043a\u0430\u0437\u044b\u0432\u0430\u0435\u0442 \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u0435 \u0443\u0441\u043b\u0443\u0433\u0438 \u2013 \u0434\u0438\u0430\u043b\u043e\u0433\u0438 \n\u0441 \u043f\u043e\u0440\u0442\u043d\u044b\u043c, \u0441\u0443\u043a\u043e\u043d\u0449\u0438\u043a\u043e\u043c, \u0431\u0430\u0448\u043c\u0430\u0447\u043d\u0438\u043a\u043e\u043c, \u043a\u043e\u043d\u044e\u0448\u0438\u043c, \u0432\u0440\u0430\u0447\u043e\u043c, \u043b\u0435\u043a\u0430\u0440\u0435\u043c; D 21 \n\u00abBetween a Sick body, a Physician and a Surgeon / \u041c\u0435\u0436\u0434\u0443 \u0431\u043e\u043b\u044c\u043d\u044b\u043c, \u0434\u043e\u043a\u0442\u043e\u0440\u043e\u043c \n\u0438 \u043b\u0435\u043a\u0430\u0440\u0435\u043c\u00bb. \u041a\u0440\u043e\u043c\u0435 \u0442\u043e\u0433\u043e, \u0432 \u0434\u0438\u0430\u043b\u043e\u0433\u0430\u0445 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d \u0446\u0435\u043b\u044b\u0439 \u0441\u043f\u0435\u043a\u0442\u0440 \u0440\u0430\u0437\u043d\u043e\u043e\u0431\u0440\u0430\u0437-\n\u043d\u044b\u0445 \u0441\u043f\u043e\u0441\u043e\u0431\u043e\u0432 \u0432\u0440\u0435\u043c\u044f\u043f\u0440\u0435\u043f\u0440\u043e\u0432\u043e\u0436\u0434\u0435\u043d\u0438\u044f: D 27 \u00abTo Go to Bathe or to Swim / \n\u0418\u0434\u0442\u0438 \u043a\u0443\u043f\u0430\u0442\u044c\u0441\u044f \u0438\u043b\u0438 \u043f\u043b\u0430\u0432\u0430\u0442\u044c\u00bb; D 29 \u00abGoing Upon a Journey / \u041e\u0442\u043f\u0440\u0430\u0432\u043b\u044f\u0442\u044c\u0441\u044f \n\u0432 \u0434\u043e\u0440\u043e\u0433\u0443\u00bb; D 31 \u00abTo Hire a Boat / \u041d\u0430\u043d\u0438\u043c\u0430\u0442\u044c \u0431\u043e\u0442\u00bb \u0438 \u0434\u0440\u0443\u0433\u0438\u0435. \u0412\u043e\u043e\u0431\u0440\u0430\u0436\u0430\u0435\u043c\u043e\u043c\u0443 \n/ \u0438\u0434\u0435\u0430\u043b\u044c\u043d\u043e\u043c\u0443 \u00ab\u0433\u0435\u0440\u043e\u044e\u00bb \u043f\u0440\u0435\u0434\u043b\u0430\u0433\u0430\u0435\u0442\u0441\u044f \u0442\u0430\u043a\u0436\u0435 \u043e\u0442\u043f\u0440\u0430\u0432\u0438\u0442\u044c\u0441\u044f \u0432 \u0434\u0435\u0440\u0435\u0432\u043d\u044e \u0438 \u0432\u044b-\n\u0431\u0440\u0430\u0442\u044c \u0442\u0430\u043c \u0437\u0430\u043d\u044f\u0442\u0438\u0435 \u043f\u043e \u0434\u0443\u0448\u0435 \u0438\u0437 \u0440\u044f\u0434\u0430 \u043f\u0435\u0440\u0435\u0447\u0438\u0441\u043b\u0435\u043d\u043d\u044b\u0445, \u0442\u043e \u0435\u0441\u0442\u044c \u0441\u043e\u043e\u0442\u0432\u0435\u0442\u0441\u0442\u0432\u0443-\n\u044e\u0449\u0438\u0445 \u044d\u0442\u0430\u043b\u043e\u043d\u0443 \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u043e\u0432: D 32 \u00abOf Country Diversions, of Sports, especially \nof Hunting and Fishing / \u041e \u0434\u0435\u0440\u0435\u0432\u0435\u043d\u0441\u043a\u0438\u0445 \u0437\u0430\u0431\u0430\u0432\u0430\u0445 \u0438\u043b\u0438 \u0432\u0435\u0441\u0435\u043b\u043e\u0441\u0442\u044f\u0445, \u0430 \u043e\u0441\u043e\u0431\u043b\u0438\u0432\u043e \n\u043e \u0437\u0432\u0435\u0440\u0438\u043d\u043e\u0439 \u0438 \u0440\u044b\u0431\u043d\u043e\u0439 \u043b\u043e\u0432\u043b\u0435\u00bb; D 36 \u00abTo Desire One to Sing / \u041f\u0440\u043e\u0441\u0438\u0442\u044c \u043a\u043e\u0433\u043e \n\u043f\u0435\u0442\u044c\u00bb; D 37 \u00ab\u0410t Jumping and Running / \u041f\u0440\u044b\u0433\u0430\u0442\u044c \u0438 \u0431\u0435\u0433\u0430\u0442\u044c\u00bb. \u0412 \u0434\u0438\u0430\u043b\u043e\u0433\u0430\u0445 32 \u0438 34 \n\u0440\u0430\u0441\u0441\u043c\u0430\u0442\u0440\u0438\u0432\u0430\u044e\u0442\u0441\u044f \u0441\u0438\u0442\u0443\u0430\u0446\u0438\u0438 \u043a\u0443\u043b\u044c\u0442\u0443\u0440\u043d\u043e\u0433\u043e \u0434\u043e\u0441\u0443\u0433\u0430, \u0430 \u0438\u043c\u0435\u043d\u043d\u043e \u043f\u043e\u043a\u0443\u043f\u043a\u0438 \u043a\u043d\u0438\u0433 \u0438 \n\u043f\u043e\u0441\u0435\u0449\u0435\u043d\u0438\u044f \u0442\u0435\u0430\u0442\u0440\u0430 (\u00abTo Buy Books / \u041f\u043e\u043a\u0443\u043f\u0430\u0442\u044c \u043a\u043d\u0438\u0433\u0438\u00bb \u0438 \u00abTo Go to See a Play / \n\u0418\u0434\u0442\u0438 \u0432 \u043a\u043e\u043c\u0435\u0434\u0438\u044e\u00bb) [6]. \u041f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u043d\u044b\u0439 \u0432 \u0432\u0438\u0434\u0435 \u0441\u0446\u0435\u043d\u043e\u043a \u043c\u0430\u0442\u0435\u0440\u0438\u0430\u043b \u043e\u0442\u043b\u0438\u0447\u0430\u043b\u0441\u044f \n113\n114\n\u0431\u043e\u043b\u044c\u0448\u0438\u043c \u0440\u0430\u0437\u043d\u043e\u043e\u0431\u0440\u0430\u0437\u0438\u0435\u043c, \u0431\u044b\u043b \u043b\u0435\u0433\u0447\u0435 \u0434\u043b\u044f \u0432\u043e\u0441\u043f\u0440\u0438\u044f\u0442\u0438\u044f \u0438 \u0437\u0430\u043f\u043e\u043c\u0438\u043d\u0430\u043d\u0438\u044f. \n\u0422\u0435\u043c\u0430\u0442\u0438\u043a\u0430 \u0434\u0438\u0430\u043b\u043e\u0433\u043e\u0432 \u0438\u0437 \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u0430 \u041f. \u0416\u0434\u0430\u043d\u043e\u0432\u0430 1772 \u0433. \u0432 \u0437\u043d\u0430\u0447\u0438\u0442\u0435\u043b\u044c\u043d\u043e\u0439 \u0441\u0442\u0435-\n\u043f\u0435\u043d\u0438 \u0441\u043e\u0432\u043f\u0430\u0434\u0430\u0435\u0442 \u0441 \u0442\u0435\u043c\u0430\u0442\u0438\u043a\u043e\u0439 \u0434\u0438\u0430\u043b\u043e\u0433\u043e\u0432 \u0432 \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u0430\u0445 \u0434\u0440\u0443\u0433\u0438\u0445 \u0438\u043d\u043e\u0441\u0442\u0440\u0430\u043d\u043d\u044b\u0445 \n\u044f\u0437\u044b\u043a\u043e\u0432. \u0413.\u0410. \u041b\u0435\u0432\u0447\u0435\u043d\u043a\u043e [7] \u043e\u0442\u043c\u0435\u0447\u0430\u0435\u0442, \u0447\u0442\u043e \u0438\u0434\u0435\u043e\u0433\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u0435, \u0441\u043e\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u043d\u044b\u0435 \u043f\u043e \n\u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u043c\u0443 \u043f\u0440\u0438\u043d\u0446\u0438\u043f\u0443 \u0441\u043b\u043e\u0432\u0430\u0440\u0438 \u043d\u0435\u0438\u0437\u043c\u0435\u043d\u043d\u043e \u043e\u0431\u043b\u0430\u0434\u0430\u043b\u0438 \u044d\u043a\u0441\u043f\u043b\u0438\u0446\u0438\u0442\u043d\u043e\u0439 \u0438\u0434\u0435\u043e-\n\u043b\u043e\u0433\u0438\u0447\u0435\u0441\u043a\u043e\u0439 \u043d\u0430\u043f\u0440\u0430\u0432\u043b\u0435\u043d\u043d\u043e\u0441\u0442\u044c\u044e, \u043e\u0442\u0440\u0430\u0436\u0430\u044f \u043a\u0430\u0440\u0442\u0438\u043d\u0443 \u043c\u0438\u0440\u0430 \u0441\u043e\u0441\u0442\u0430\u0432\u0438\u0442\u0435\u043b\u044f \u0441\u043b\u043e\u0432\u0430\u0440\u044f. \n\u041d\u0430 \u0431\u043e\u043b\u0435\u0435 \u0440\u0430\u043d\u043d\u0438\u0445 \u044d\u0442\u0430\u043f\u0430\u0445, \u00ab\u043f\u043e \u043d\u0430\u0431\u043b\u044e\u0434\u0435\u043d\u0438\u044e \u041d. \u0412. \u0414\u0443\u0431\u044b\u043d\u0438\u043d\u043e\u0439, \u0432\u043e \u043c\u043d\u043e\u0433\u0438\u0445 \u0438\u0434\u0435\u043e-\n\u0433\u0440\u0430\u0444\u0438\u0447\u0435\u0441\u043a\u0438\u0445 \u0441\u043b\u043e\u0432\u0430\u0440\u044f\u0445, \u0438\u0437\u0434\u0430\u043d\u043d\u044b\u0445 \u0432 \u0420\u043e\u0441\u0441\u0438\u0438 \u0432 \u0425VIII \u0432., \u0440\u0443\u0431\u0440\u0438\u043a\u0430\u0442\u043e\u0440\u044b-\u0442\u0435\u043c\u044b \n\u0440\u0430\u0441\u043f\u043e\u043b\u0430\u0433\u0430\u043b\u0438\u0441\u044c \u0432 \u0442\u043e\u0439 \u043f\u043e\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u043d\u043e\u0441\u0442\u0438, \u0432 \u043a\u043e\u0442\u043e\u0440\u043e\u0439 \u043e\u043d\u0438 \u0438\u0437\u043b\u043e\u0436\u0435\u043d\u044b \u0432 \u043f\u0435\u0440-\n\u0432\u043e\u0439 \u0433\u043b\u0430\u0432\u0435 \u0432\u0435\u0442\u0445\u043e\u0437\u0430\u0432\u0435\u0442\u043d\u043e\u0439 \u00ab\u041a\u043d\u0438\u0433\u0438 \u0411\u044b\u0442\u0438\u044f\u00bb (\u0411\u043e\u0433, \u043d\u0435\u0431\u043e, \u0441\u0442\u0438\u0445\u0438\u0438, \u0440\u0430\u0441\u0442\u0435\u043d\u0438\u044f, \u0436\u0438-\n\u0432\u043e\u0442\u043d\u044b\u0435, \u0447\u0435\u043b\u043e\u0432\u0435\u043a)\u00bb [6, \u0441.148]. \u041e\u0442\u043c\u0435\u0442\u0438\u043c, \u043e\u0434\u043d\u0430\u043a\u043e, \u0447\u0442\u043e \u0432 \u0440\u0430\u0441\u0441\u043c\u0430\u0442\u0440\u0438\u0432\u0430\u0435\u043c\u044b\u0445 \u043d\u0430\u043c\u0438 \n\u0443\u0447\u0435\u0431\u043d\u0438\u043a\u0430\u0445 \u0440\u0430\u0441\u043f\u043e\u043b\u043e\u0436\u0435\u043d\u0438\u0435 \u0442\u0435\u043c-\u0440\u0443\u0431\u0440\u0438\u043a\u0430\u0442\u043e\u0440\u043e\u0432 \u043e\u043f\u0438\u0441\u044b\u0432\u0430\u0435\u0442 \u0438\u0434\u0435\u0430\u043b\u044c\u043d\u044b\u0439 \u0440\u0430\u0441\u043f\u043e-\n\u0440\u044f\u0434\u043e\u043a \u0434\u043d\u044f \u0441\u0432\u0435\u0442\u0441\u043a\u043e\u0433\u043e \u0447\u0435\u043b\u043e\u0432\u0435\u043a\u0430 \u0441\u043e \u0432\u0441\u0435\u043c\u0438 \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u044b\u043c\u0438 \u0432\u0430\u0440\u0438\u0430\u0446\u0438\u044f\u043c\u0438. \u0412\u043e\u043f\u0440\u043e\u0441\u044b \n\u0440\u0435\u043b\u0438\u0433\u0438\u0438 \u0438 \u043c\u0438\u0440\u043e\u0437\u0434\u0430\u043d\u0438\u044f, \u0445\u0430\u0440\u0430\u043a\u0442\u0435\u0440\u043d\u044b\u0435 \u0434\u043b\u044f \u0431\u043e\u043b\u0435\u0435 \u0440\u0430\u043d\u043d\u0438\u0445 \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u043d\u0438\u043a\u043e\u0432, \u043f\u043e\u0447-\n\u0442\u0438 \u0441\u043e\u0432\u0441\u0435\u043c \u043d\u0435 \u043f\u0440\u0438\u0441\u0443\u0442\u0441\u0442\u0432\u0443\u044e\u0442 \u0441\u0440\u0435\u0434\u0438 \u0442\u0435\u043c \u0434\u0438\u0430\u043b\u043e\u0433\u043e\u0432 \u0432 \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u0430\u0445 \u0430\u043d\u0433\u043b\u0438\u0439\u0441\u043a\u043e\u0433\u043e \n\u044f\u0437\u044b\u043a\u0430, \u043d\u0435\u043e\u0431\u0445\u043e\u0434\u0438\u043c\u044b\u0435 \u043e\u0431\u0440\u044f\u0434\u044b, \u0432 \u0442\u043e\u043c \u0447\u0438\u0441\u043b\u0435 \u0438 \u0440\u0435\u043b\u0438\u0433\u0438\u043e\u0437\u043d\u044b\u0435 \u0442\u0430\u0438\u043d\u0441\u0442\u0432\u0430, \u0432\u044b\u0442\u0435\u0441\u043d\u0435-\n\u043d\u044b \u043d\u0430 \u043f\u0435\u0440\u0438\u0444\u0435\u0440\u0438\u044e \u0438 \u0442\u0440\u0430\u043a\u0442\u0443\u044e\u0442\u0441\u044f \u043a\u0430\u043a \u0441\u0432\u0435\u0442\u0441\u043a\u0438\u0435 \u0440\u0438\u0442\u0443\u0430\u043b\u044b: \u0441\u043c, \u043d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0434\u0438\u0430-\n\u043b\u043e\u0433 35 \u0438\u0437 \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u0430 \u041f. \u0416\u0434\u0430\u043d\u043e\u0432\u0430 \u00abOf Christening, Wedding and Burial / \u041e \u043a\u0440\u0435-\n\u0441\u0442\u0438\u043d\u0430\u0445, \u0441\u0432\u0430\u0434\u044c\u0431\u0435 \u0438 \u043f\u043e\u0445\u043e\u0440\u043e\u043d\u0430\u0445\u00bb. \u041d\u0435\u0441\u043e\u043c\u043d\u0435\u043d\u043d\u044b\u043c \u0432\u0438\u0434\u0438\u0442\u0441\u044f \u0432\u043b\u0438\u044f\u043d\u0438\u0435 \u0438\u0434\u0435\u043e\u043b\u043e\u0433\u0438\u0438 \n\u041f\u0440\u043e\u0441\u0432\u0435\u0449\u0435\u043d\u0438\u044f \u0438 \u043f\u0440\u043e\u043f\u0430\u0433\u0430\u043d\u0434\u0430 \u0437\u0430\u043f\u0430\u0434\u043d\u043e\u0433\u043e \u00ab\u0433\u0430\u043b\u0430\u043d\u0442\u043d\u043e\u0433\u043e\u00bb \u0441\u0442\u0438\u043b\u044f \u0436\u0438\u0437\u043d\u0438.\n\u0421\u043a\u043b\u0430\u0434\u044b\u0432\u0430\u044f\u0441\u044c \u0432 \u0435\u0434\u0438\u043d\u044b\u0439 \u043c\u0435\u0442\u0430\u0442\u0435\u043a\u0441\u0442, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043c\u043e\u0436\u043d\u043e \u0443\u0441\u043b\u043e\u0432\u043d\u043e \u043e\u0431\u043e\u0437\u043d\u0430\u0447\u0438\u0442\u044c \n\u043a\u0430\u043a \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u0435 \u043e\u0431\u0440\u0430\u0437\u0430 \u0436\u0438\u0437\u043d\u0438 \u043f\u0440\u043e\u0433\u0440\u0435\u0441\u0441\u0438\u0432\u043d\u043e\u0433\u043e \u0447\u0435\u043b\u043e\u0432\u0435\u043a\u0430 XVIII \u0432\u0435\u043a\u0430, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \n\u0437\u043d\u0430\u0435\u0442, \u043a\u0430\u043a \u0441\u0435\u0431\u044f \u0432\u0435\u0441\u0442\u0438 \u0438 \u0447\u0442\u043e \u0441\u043a\u0430\u0437\u0430\u0442\u044c \u0432 \u0440\u0430\u0437\u043d\u044b\u0445 \u0441\u0438\u0442\u0443\u0430\u0446\u0438\u044f\u0445, \u043f\u0443\u0442\u0435\u0448\u0435\u0441\u0442\u0432\u0443\u0435\u0442, \u0438\u043d-\n\u0442\u0435\u0440\u0435\u0441\u0443\u0435\u0442\u0441\u044f \u043d\u043e\u0432\u043e\u0441\u0442\u044f\u043c\u0438 \u0438 \u043a\u0443\u043b\u044c\u0442\u0443\u0440\u043e\u0439; \u0434\u0438\u0430\u043b\u043e\u0433\u0438 \u0437\u043d\u0430\u043a\u043e\u043c\u044f\u0442 \u0443\u0447\u0435\u043d\u0438\u043a\u043e\u0432 \u0441 \u0440\u0430\u0437\u043d\u044b\u043c\u0438 \n\u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u043c\u0438 \u0438 \u0441\u0442\u0438\u043b\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u043c\u0438 \u0441\u043b\u043e\u044f\u043c\u0438 \u043b\u0435\u043a\u0441\u0438\u043a\u0438, \u0433\u0440\u0430\u043c\u043c\u0430\u0442\u0438\u043a\u0438 \u0438 \u0440\u0430\u0437\u0433\u043e-\n\u0432\u043e\u0440\u043d\u044b\u043c\u0438 \u043c\u043e\u0434\u0435\u043b\u044f\u043c\u0438. \u0421\u0435\u0433\u043e\u0434\u043d\u044f \u043e\u043d\u0438 \u0447\u0438\u0442\u0430\u044e\u0442\u0441\u044f \u043a\u0430\u043a \u0443\u0432\u043b\u0435\u043a\u0430\u0442\u0435\u043b\u044c\u043d\u044b\u0439 \u0440\u0430\u0441\u0441\u043a\u0430\u0437 \u043e \n\u043f\u0440\u043e\u0448\u043b\u043e\u043c, \u0432 \u043a\u043e\u0442\u043e\u0440\u043e\u043c \u0432\u0441\u0435 \u0434\u0435\u0442\u0430\u043b\u0438 \u0434\u043e\u0441\u0442\u043e\u0432\u0435\u0440\u043d\u044b. \u041f\u0440\u0438\u0432\u0435\u0434\u0435\u043c \u0432 \u043a\u0430\u0447\u0435\u0441\u0442\u0432\u0435 \u043f\u0440\u0438\u043c\u0435\u0440\u0430 \n\u0414\u0438\u0430\u043b\u043e\u0433 VI \u201cTo make a Visit in the Morning / \u041f\u043e\u0441\u0435\u0442\u0438\u0442\u044c \u043a\u043e\u0433\u043e \u043f\u043e\u0443\u0442\u0440\u0443\u201d:\nWho is there? \u041a\u0442\u043e \u0442\u0430\u043c?\nA Friend, open the Door. \u041f\u0440\u0438\u044f\u0442\u0435\u043b\u044c, \u043e\u0442\u0432\u043e\u0440\u0438 \u0434\u0432\u0435\u0440\u044c.\nWhere is your Master? \u0413\u0434\u0435 \u0442\u0432\u043e\u0439 \u0433\u043e\u0441\u043f\u043e\u0434\u0438\u043d?\nHe\u2019s in Bed. \u041e\u043d \u0432 \u043f\u043e\u0441\u0442\u0435\u043b\u0438.\nIs he asleep still? \u0415\u0449\u0435 \u043e\u043d \u0441\u043f\u0438\u0442? \nNo, Sir, he\u2019s Awake. \u041d\u0435\u0442, \u0441\u0443\u0434\u0430\u0440\u044c, \u043e\u043d \u043f\u0440\u043e\u0441\u043d\u0443\u043b\u0441\u044f.\nIs he up? Is he stirring? \u0412\u0441\u0442\u0430\u043b \u043b\u0438 \u043e\u043d? \u0412\u0441\u0442\u0430\u0435\u0442 \u043b\u0438 \u043e\u043d?\nNot yet, will you be pleased to step \u041d\u0435\u0442 \u0435\u0449\u0435; \u043d\u0435 \u0438\u0437\u0432\u043e\u043b\u0438\u0442\u0435 \u043b\u0438 \u0432\u043e\u0439\u0442\u0438\ninto his Chamber? \u043a \u043d\u0435\u043c\u0443 \u0432 \u043a\u043e\u043c\u043d\u0430\u0442\u0443?\n\u0423\u0447\u0435\u0431\u043d\u044b\u0435 \u0430\u043d\u0433\u043b\u043e-\u0440\u0443\u0441\u0441\u043a\u0438\u0435 \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u043d\u0438\u043a\u0438 XVIII \u2013 \u043d\u0430\u0447\u0430\u043b\u0430 XIX \u0432\u0435\u043a\u043e\u0432 \n115\nHow now! Are you in bed still? \u0427\u0442\u043e \u044d\u0442\u043e? \u0412\u044b \u0435\u0449\u0435 \u0432 \u043f\u043e\u0441\u0442\u0435\u043b\u0438?\nI went to bed so late last night that \u042f \u0432\u0447\u0435\u0440\u0430\u0441\u044c \u043b\u0435\u0433 \u0441\u043f\u0430\u0442\u044c \u0441\u0442\u043e\u043b\u044c \nI could not get up betimes, or early. \u043f\u043e\u0437\u0434\u043d\u043e, \u0447\u0442\u043e \u043d\u0435 \u043c\u043e\u0433 \u0432\u0441\u0442\u0430\u0442\u044c \n \u0440\u0430\u043d\u043e. \nWhat did you do after supper? \u0427\u0442\u043e \u0432\u044b \u043f\u043e\u0441\u043b\u0435 \u0443\u0436\u0438\u043d\u0430 \u0434\u0435\u043b\u0430\u043b\u0438?\nHow did you spend the Evening? \u041a\u0430\u043a \u043f\u0440\u043e\u0432\u043e\u0434\u0438\u043b\u0438 \u0432\u044b \u0432\u0435\u0447\u0435\u0440?\nWe play\u2019d at cards, or we went to Cards. \u041c\u044b \u0438\u0433\u0440\u0430\u043b\u0438 \u0432 \u043a\u0430\u0440\u0442\u044b; \n \u0438\u043b\u0438 \u043c\u044b \u0441\u0435\u043b\u0438 \u0438\u0433\u0440\u0430\u0442\u044c \u0432 \u043a\u0430\u0440\u0442\u044b.\nWhat game did you play at? \u0412 \u043a\u0430\u043a\u0443\u044e \u0438\u0433\u0440\u0443 \u0432\u044b \u0437\u0430\u0431\u0430\u0432\u043b\u044f\u043b\u0438\u0441\u044c?\nAt Picket. \u0412 \u043f\u0438\u043a\u0435\u0442. \nTis a game very much at Fashion. \u042d\u0442\u0430 \u0438\u0433\u0440\u0430 \u0432 \u0432\u0435\u043b\u0438\u043a\u043e\u0439 \u043c\u043e\u0434\u0435.\nAfter that we went to the Ball. \u041f\u043e\u0441\u043b\u0435 \u0441\u0435\u0433\u043e \u043c\u044b \u043f\u043e\u0448\u043b\u0438 \u043d\u0430 \u0431\u0430\u043b.\nHow long were you there? \u041a\u0430\u043a \u0434\u043e\u043b\u0433\u043e \u0432\u044b \u0442\u0430\u043c \u0431\u044b\u043b\u0438?\nTill twelve o\u2019clock at night. \u0414\u043e \u043f\u043e\u043b\u0443\u043d\u043e\u0447\u0438.\nAt what time did you go to bed? \u0412 \u043a\u043e\u0442\u043e\u0440\u043e\u043c \u0447\u0430\u0441\u0443 \u0432\u044b \u043b\u0435\u0433\u043b\u0438 \n \u0441\u043f\u0430\u0442\u044c?\nAt one o\u2019clock in the Morning. \u0412 \u0447\u0430\u0441 \u043f\u043e \u043f\u043e\u043b\u0443\u043d\u043e\u0447\u0438.\nI don\u2019t wonder at your riseing so late. \u042f \u043d\u0435 \u0443\u0434\u0438\u0432\u043b\u044f\u044e\u0441\u044c, \u0447\u0442\u043e \u0432\u044b \u0442\u0430\u043a \n \u043f\u043e\u0437\u0434\u043d\u043e \u0432\u0441\u0442\u0430\u0435\u0442\u0435. \n [5, \u0441. 185 \u2013187] \n\u041c\u044b \u043f\u043e\u043b\u0443\u0447\u0430\u0435\u043c \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u044e \u043e \u043c\u043d\u043e\u0433\u0438\u0445 \u0431\u044b\u0442\u043e\u0432\u044b\u0445 \u043f\u043e\u0434\u0440\u043e\u0431\u043d\u043e\u0441\u0442\u044f\u0445 \u0436\u0438\u0437\u043d\u0438 \u043b\u044e-\n\u0434\u0435\u0439 \u0438\u0441\u0441\u043b\u0435\u0434\u0443\u0435\u043c\u043e\u0433\u043e \u043f\u0435\u0440\u0438\u043e\u0434\u0430 (\u043e\u0434\u0435\u0436\u0434\u0430, \u0442\u0443\u0430\u043b\u0435\u0442, \u0435\u0434\u0430, \u0436\u0438\u043b\u0438\u0449\u0435, \u0446\u0435\u043d\u044b \u043d\u0430 \u0442\u043e\u0432\u0430\u0440\u044b \u0438 \n\u0443\u0441\u043b\u0443\u0433\u0438, \u0438 \u0434\u0440.). \u0413.\u041b\u0435\u0432\u0447\u0435\u043d\u043a\u043e \u043d\u0430\u0437\u044b\u0432\u0430\u0435\u0442 \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u043d\u0438\u043a \u043f\u0440\u043e\u0434\u0443\u043a\u0442\u043e\u043c \u044d\u043f\u043e\u0445\u0438, \u043d\u043e \u0442\u0430\u043a\u0436\u0435 \n\u0438 \u0435\u0435 \u0441\u0432\u0438\u0434\u0435\u0442\u0435\u043b\u0435\u043c, \u043f\u043e\u0441\u043a\u043e\u043b\u044c\u043a\u0443 \u043e\u043d \u00ab\u0437\u0430\u043f\u0435\u0447\u0430\u0442\u043b\u0435\u0432\u0430\u0435\u0442 \u0431\u044b\u0442\u043e\u0432\u044b\u0435 \u0444\u0430\u043a\u0442\u044b, \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e, \n\u0431\u043e\u043b\u0435\u0435 \u043d\u0438\u0433\u0434\u0435 \u043d\u0435 \u0443\u043f\u043e\u043c\u044f\u043d\u0443\u0442\u044b\u0435\u00bb [6, \u0441.151]. \n\u0421\u043b\u0435\u0434\u0443\u044e\u0449\u0438\u0439 \u043f\u0440\u0438\u043c\u0435\u0440 \u2013 \u043e\u0442\u0440\u044b\u0432\u043e\u043a \u0438\u0437 \u0414\u0438\u0430\u043b\u043e\u0433\u0430 4 \u00abTo Dress Oneself / \u041e\u0434\u0435\u0432\u0430\u0442\u044c\u0441\u044f\u00bb \n\u0438\u0437 \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u0430 \u041f. \u0416\u0434\u0430\u043d\u043e\u0432\u0430 1772 \u0433. \nBoy, light a candle. \u041c\u0430\u043b\u044b\u0439, \u0437\u0430\u0441\u0432\u0435\u0442\u0438 \u0441\u0432\u0435\u0447\u0443.\nPray reach or give me my breeches, \u041f\u043e\u0436\u0430\u043b\u0443\u0439, \u0434\u043e\u0441\u0442\u0430\u043d\u044c\u0442\u0435 \u0438\u043b\u0438 \nMorning gown, stockings\u2026 \u043f\u043e\u0434\u0430\u0439\u0442\u0435 \u043c\u043d\u0435 \u0448\u0442\u0430\u043d\u044b, \n\u0448\u043b\u0430\u0444\u0440\u043e\u043a, \u0447\u0443\u043b\u043a\u0438\u2026 \nSilk stockings or Worsted stockings? \u0428\u0435\u043b\u043a\u043e\u0432\u044b\u0435 \u0438\u043b\u0438 \u0433\u0430\u0440\u0443\u0441\u043d\u044b\u0435?\nThread\u2026 \u041d\u0438\u0442\u044f\u043d\u044b\u0435\u2026\nComb my Wig or Perriwig. \u041f\u0440\u0438\u0447\u0435\u0448\u0438 \u0433\u043e\u043b\u043e\u0432\u0443, \u043f\u0440\u0438\u0447\u0435\u0448\u0438 \n\u043f\u0430\u0440\u0438\u043a\nThe Combs are not clean. \u0413\u0440\u0435\u0431\u043d\u0438 \u043d\u0435\u0447\u0438\u0441\u0442\u044b\u0435. \n \u041e.\u0413. \u0421\u0438\u0434\u043e\u0440\u043e\u0432\u0430\n116\nWill you have a Horn-comb or \u041a\u0430\u043a\u043e\u0439 \u0433\u0440\u0435\u0431\u0435\u043d\u044c \u0432\u0430\u043c \u043f\u043e\u0434\u0430\u0442\u044c,\na Box-comb?... \u0440\u043e\u0433\u043e\u0432\u044b\u0439 \u0438\u043b\u0438 \u0431\u0443\u043a\u043e\u0432\u044b\u0439? [5, \n\u0441.181\u2013182].\n\u0414\u0430\u043b\u0435\u0435 \u043e\u0431\u0441\u0443\u0436\u0434\u0430\u044e\u0442\u0441\u044f \u0442\u0430\u043a\u0438\u0435 \u0434\u0435\u0442\u0430\u043b\u0438 \u043c\u0443\u0436\u0441\u043a\u043e\u0433\u043e \u0442\u0443\u0430\u043b\u0435\u0442\u0430, \u043a\u0430\u043a \u0440\u0443\u0431\u0430\u0448\u043a\u0430 (\u043a\u043e\u0442\u043e-\n\u0440\u0430\u044f \u043c\u043e\u0433\u043b\u0430 \u0431\u044b\u0442\u044c \u00ab\u0447\u0438\u0441\u0442\u0430, \u0433\u0440\u044f\u0437\u043d\u0430 \u0438\u043b\u0438 \u043d\u0430\u0433\u0440\u0435\u0442\u0430\u00bb), \u043d\u0430\u0434\u0443\u0448\u0435\u043d\u043d\u044b\u0439 \u043f\u043b\u0430\u0442\u043e\u043a, \u0433\u0430\u043b\u0441\u0442\u0443\u043a, \n\u00ab\u043c\u0430\u043d\u0436\u0435\u0442\u043d\u044b\u0435 \u043d\u0430\u043a\u043b\u0430\u0434\u043a\u0438, \u0438\u043b\u0438 \u043c\u0430\u043d\u0438\u0448\u043a\u0438\u00bb, \u043f\u0435\u0440\u0447\u0430\u0442\u043a\u0438, \u0448\u043b\u044f\u043f\u0430, \u0448\u043f\u0430\u0433\u0430, \u0430 \u0442\u0430\u043a\u0436\u0435 \n\u043a\u0430\u043c\u0437\u043e\u043b \u0438 \u0435\u043f\u0430\u043d\u0447\u0430. \u0412 \u0440\u044f\u0434\u0435 \u0441\u043b\u0443\u0447\u0430\u0435\u0432 \u043d\u0430\u043f\u0440\u044f\u043c\u0443\u044e \u043e\u0431\u0441\u0443\u0436\u0434\u0430\u044e\u0442\u0441\u044f \u0432\u043e\u043f\u0440\u043e\u0441\u044b \u043c\u043e\u0434\u044b: \n\u00ab\u0413\u0430\u043b\u0441\u0442\u0443\u043a \u0441 \u043a\u0440\u0443\u0436\u0435\u0432\u043e\u043c \u043d\u0435 \u0432 \u043c\u0430\u043d\u0435\u0440\u0435\u00bb, \u00ab\u0414\u043b\u044f \u0447\u0435\u0433\u043e \u0432\u044b \u043a\u0430\u043c\u0437\u043e\u043b\u0430 \u0441\u0432\u043e\u0435\u0433\u043e \u043d\u0435 \u0437\u0430\u0441\u0442\u0435\u0433\u043d\u0435-\n\u0442\u0435? \u2013 \u042f \u043b\u044e\u0431\u043b\u044e \u0445\u043e\u0434\u0438\u0442\u044c \u0440\u0430\u0437\u0441\u0442\u0435\u0433\u043d\u0443\u0432\u0448\u0438 \u0433\u0440\u0443\u0434\u044c. \u042d\u0442\u043e \u0432 \u043c\u043e\u0434\u0435\u00bb [5, \u0441. 183].\n\u0410\u043d\u0430\u043b\u0438\u0437 \u0434\u0438\u0430\u043b\u043e\u0433\u043e\u0432 \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0442 \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u043e \u043d\u0430\u0431\u043b\u044e\u0434\u0435\u043d\u0438\u0439 \u0441\u043e\u0446\u0438\u043e\u043a\u0443\u043b\u044c-\n\u0442\u0443\u0440\u043d\u043e\u0433\u043e \u0445\u0430\u0440\u0430\u043a\u0442\u0435\u0440\u0430. \u041d\u0430\u043b\u0438\u0446\u043e \u0440\u0430\u0437\u043d\u0438\u0446\u0430 \u043c\u0435\u0436\u0434\u0443 \u0441\u043e\u0432\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u043c\u0438 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438-\n\u044f\u043c\u0438 \u043e \u0432\u0435\u0436\u043b\u0438\u0432\u043e\u0441\u0442\u0438 \u0438 \u044d\u0442\u0438\u043a\u0435\u0442\u0435 \u0438 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u044f\u043c\u0438, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u043f\u0440\u0438\u0441\u0443\u0442\u0441\u0442\u0432\u0443\u044e\u0442 \n\u0432 \u0430\u043d\u0430\u043b\u0438\u0437\u0438\u0440\u0443\u0435\u043c\u044b\u0445 \u0434\u0438\u0430\u043b\u043e\u0433\u0430\u0445, \u0430 \u0442\u0430\u043a\u0436\u0435 \u043c\u0435\u0436\u0434\u0443 \u0442\u0435\u043c, \u0447\u0442\u043e \u0441\u043b\u0435\u0434\u0443\u0435\u0442 / \u043d\u0435 \u0441\u043b\u0435\u0434\u0443\u0435\u0442 \n\u0432\u043a\u043b\u044e\u0447\u0430\u0442\u044c \u0432 \u0443\u0447\u0435\u0431\u043d\u043e\u0435 \u043f\u043e\u0441\u043e\u0431\u0438\u0435. \u0422\u0430\u043a, \u0432 \u0441\u043e\u0432\u0440\u0435\u043c\u0435\u043d\u043d\u043e\u043c \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u0435 \u0438\u043b\u0438 \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440-\n\u043d\u0438\u043a\u0435 \u0435\u0434\u0432\u0430 \u043b\u0438 \u0431\u0443\u0434\u0443\u0442 \u043e\u0431\u0441\u0443\u0436\u0434\u0430\u0442\u044c\u0441\u044f \u0432\u043e\u043f\u0440\u043e\u0441\u044b \u0441\u0432\u0435\u0436\u0435\u0441\u0442\u0438 \u0440\u0443\u0431\u0430\u0448\u0435\u043a \u0438\u043b\u0438 \u0434\u044b\u0440\u043e\u043a \u043d\u0430 \n\u0447\u0443\u043b\u043a\u0430\u0445. \u041e\u0431\u0441\u0443\u0436\u0434\u0435\u043d\u0438\u0435 \u0432\u043e\u0437\u0440\u0430\u0441\u0442\u0430 \u0447\u0435\u043b\u043e\u0432\u0435\u043a\u0430, \u0438\u043d\u0442\u0438\u043c\u043d\u044b\u0445 \u043e\u0442\u043d\u043e\u0448\u0435\u043d\u0438\u0439 \u0438 \u043d\u0435\u043a\u043e\u0442\u043e-\n\u0440\u044b\u0435 \u0434\u0440\u0443\u0433\u0438\u0435 \u0434\u0435\u0442\u0430\u043b\u0438, \u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u043d\u0435 \u0432\u0445\u043e\u0434\u044f\u0442 \u0432 \u0441\u0444\u0435\u0440\u0443 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d\u0438\u0439 \u0441\u043e\u0432\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u0445 \n\u0443\u0447\u0435\u0431\u043d\u0438\u043a\u043e\u0432, \u043f\u043e\u0441\u0442\u043e\u044f\u043d\u043d\u043e \u043f\u0440\u0438\u0441\u0443\u0442\u0441\u0442\u0432\u0443\u044e\u0442 \u0432 \u043f\u043e\u0441\u043e\u0431\u0438\u044f\u0445 \u043a\u043e\u043d\u0446\u0430 \u0425VIII \u2013 \u043d\u0430\u0447\u0430\u043b\u0430 \u0425I\u0425 \n\u0432\u0435\u043a\u0430. \u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440, \u0432 \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u0435 \u041f. \u0416\u0434\u0430\u043d\u043e\u0432\u0430 \u043d\u0430\u0445\u043e\u0434\u0438\u043c: \u00ab\u041e \u0447\u0435\u043c \u0432\u0430\u0448 \u0434\u0432\u043e\u044e\u0440\u043e\u0434\u043d\u044b\u0439 \n\u0431\u0440\u0430\u0442\u0435\u0446 \u043f\u0435\u0447\u0430\u043b\u0438\u0442\u0441\u044f? \u2013 \u041c\u0430\u0442\u044c \u0443 \u043d\u0435\u0433\u043e \u0443\u043c\u0435\u0440\u043b\u0430. \u2013 \u2026\u0418\u0442\u0430\u043a, 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\u0414\u0438\u0430\u043b\u043e\u0433 \n10 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 \u0441\u043e\u0431\u043e\u0439 \u0431\u0435\u0441\u0435\u0434\u0443 \u0440\u0443\u0441\u0441\u043a\u043e\u0433\u043e \u0438 \u0430\u043d\u0433\u043b\u0438\u0439\u0441\u043a\u043e\u0433\u043e \u043a\u0443\u043f\u0446\u043e\u0432, \u0438 \u043d\u0435\u043e\u0431\u0445\u043e\u0434\u0438-\n\u043c\u043e\u0441\u0442\u044c \u0437\u043d\u0430\u043d\u0438\u044f \u0440\u0443\u0441\u0441\u043a\u043e\u0433\u043e \u043e\u0431\u044a\u044f\u0441\u043d\u044f\u0435\u0442\u0441\u044f \u044d\u043a\u043e\u043d\u043e\u043c\u0438\u0447\u0435\u0441\u043a\u0438\u043c\u0438 \u0442\u0440\u0435\u0431\u043e\u0432\u0430\u043d\u0438\u044f\u043c\u0438: \u00ab\u0418\u0431\u043e \n\u0441\u0435\u0439 \u044f\u0437\u044b\u043a (\u0440\u0443\u0441\u0441\u043a\u0438\u0439) \u0432\u0435\u0441\u044c\u043c\u0430 \u043d\u0443\u0436\u0435\u043d \u0432 \u0441\u0435\u043c \u0433\u043e\u0441\u0443\u0434\u0430\u0440\u0441\u0442\u0432\u0435, \u0438 \u0431\u0435\u0437 \u043d\u0435\u0433\u043e \u0432\u0435\u0441\u044c\u043c\u0430 \u0442\u0440\u0443\u0434\u043d\u043e \n\u0437\u0434\u0435\u0441\u044c \u0436\u0438\u0442\u044c. \u0412\u0441\u0435 \u0440\u043e\u0441\u0441\u0438\u0439\u0441\u043a\u0438\u0435 \u043a\u0443\u043f\u0446\u044b \u043f\u043e \u0431\u043e\u043b\u044c\u0448\u0435\u0439 \u0447\u0430\u0441\u0442\u0438 \u0433\u043e\u0432\u043e\u0440\u044f\u0442 \u043f\u043e-\u0440\u0443\u0441\u0441\u043a\u0438; \u043e\u0434-\n\u043d\u0438\u043c \u0441\u043b\u043e\u0432\u043e\u043c, \u0432\u0441\u0435 \u0437\u0434\u0435\u0441\u044c \u043f\u0440\u043e\u0438\u0437\u0432\u043e\u0434\u0438\u0442\u0441\u044f \u043d\u0430 \u0440\u043e\u0441\u0441\u0438\u0439\u0441\u043a\u043e\u043c \u044f\u0437\u044b\u043a\u0435. \u0421\u043b\u0435\u0434\u043e\u0432\u0430\u0442\u0435\u043b\u044c\u043d\u043e, \u0438 \n\u0438\u043d\u043e\u0441\u0442\u0440\u0430\u043d\u0446\u0430\u043c \u043d\u0435\u043e\u0431\u0445\u043e\u0434\u0438\u043c\u043e, \u043d\u0430\u0434\u043e\u0431\u043d\u043e \u0443\u0447\u0438\u0442\u044c\u0441\u044f \u043f\u043e-\u0440\u0443\u0441\u0441\u043a\u0438. \u2013 \u042f \u0442\u043e\u043c\u0443 \u0432\u0435\u0440\u044e, \u043d\u043e \u043e\u043d \n\u0432\u0435\u0441\u044c\u043c\u0430 \u0442\u0440\u0443\u0434\u043d\u044b\u0439 \u044f\u0437\u044b\u043a. \u042f \u0434\u0443\u043c\u0430\u044e, \u0447\u0442\u043e \u0430\u043d\u0433\u043b\u0438\u0441\u043a\u0438\u0439 \u044f\u0437\u044b\u043a \u043d\u0435 \u0442\u0430\u043a \u0442\u0440\u0443\u0434\u0435\u043d \u2026 \u0442\u043e\u043b\u044c\u043a\u043e \n\u043f\u0440\u043e\u0438\u0437\u043d\u043e\u0448\u0435\u043d\u0438\u0435 \u0440\u043e\u0441\u0441\u0438\u0439\u0441\u043a\u043e\u0433\u043e \u044f\u0437\u044b\u043a\u0430 \u043f\u0440\u0438\u044f\u0442\u043d\u0435\u0435 \u0430\u043d\u0433\u043b\u0438\u0441\u043a\u0430\u0433\u043e\u2026 \u2013 \u041e\u0434\u043d\u0430\u043a\u043e \u0436\u0435 \u043e\u043d \n\u043d\u0435 \u0441\u0442\u043e\u043b\u044c \u0438\u0437\u043e\u0431\u0438\u043b\u0435\u043d \u0438 \u043d\u0435 \u0442\u0430\u043a \u0432\u0430\u0436\u0435\u043d. \u2013 \u0412\u044b \u0432 \u044d\u0442\u043e\u043c \u043e\u0448\u0438\u0431\u0430\u0435\u0442\u0435\u0441\u044c, \u0430 \u043e\u043d \u0434\u0435\u0439\u0441\u0442\u0432\u0438-\n\u0442\u0435\u043b\u044c\u043d\u043e \u043d\u0438\u043a\u0430\u043a\u043e\u043c\u0443 \u044f\u0437\u044b\u043a\u0443 \u043d\u0438 \u0432 \u0447\u0435\u043c \u043d\u0435 \u0443\u0441\u0442\u0443\u043f\u0430\u0435\u0442\u00bb [5, \u0441. 294\u2013295]. \u0413\u0435\u0440\u043e\u0438 \u0442\u0430\u043a\u0436\u0435 \n\u043e\u0431\u0441\u0443\u0436\u0434\u0430\u044e\u0442 \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e\u0441\u0442\u0438 \u0438\u0437\u0443\u0447\u0435\u043d\u0438\u044f \u0430\u043d\u0433\u043b\u0438\u0439\u0441\u043a\u043e\u0433\u043e \u044f\u0437\u044b\u043a\u0430 \u0440\u0443\u0441\u0441\u043a\u0438\u043c \u0447\u0435\u043b\u043e\u0432\u0435\u043a\u043e\u043c: \n\u00ab\u0415\u0441\u0442\u044c \u043a\u043d\u0438\u0433\u0438 \u043e\u0447\u0435\u043d\u044c \u0445\u043e\u0440\u043e\u0448\u0438, \u043d\u043e \u043a\u0430\u043a\u043e\u0439 \u041b\u0435\u043a\u0441\u0438\u043a\u043e\u043d \u0443\u043f\u043e\u0442\u0440\u0435\u0431\u043b\u044f\u0435\u0442\u0435? \u2013 \u0423 \u043d\u0430\u0441 \u043d\u0435\u0442 \n\u043d\u0438\u043a\u0430\u043a\u043e\u0432\u0430 \u043d\u0430 \u0430\u043d\u0433\u043b\u0438\u043d\u0441\u043a\u043e\u043c \u0441 \u0440\u043e\u0441\u0441\u0438\u0439\u0441\u043a\u0438\u043c; \u0438\u043d\u0430\u0447\u0435 \u0431\u044b \u043c\u044b \u043c\u043e\u0433\u043b\u0438 \u043f\u0440\u0438\u0438\u0441\u043a\u0430\u0442\u044c \u043c\u043d\u043e\u0433\u043e \n\u0441\u043b\u043e\u0432 \u0438 \u0441\u0430\u043c\u0438; \u043e\u0434\u043d\u0430\u043a\u043e \u0436\u0435 \u043c\u044b \u0442\u0435\u043f\u0435\u0440\u044c \u043f\u0440\u0438\u043d\u0443\u0436\u0434\u0435\u043d\u044b \u0438\u043c\u0435\u0442\u044c \u0438\u043c \u0443\u0447\u0438\u0442\u0435\u043b\u044f, \u0438\u043b\u0438 \u043d\u0435 \n\u0441\u043e\u0432\u0435\u0440\u0448\u0435\u043d\u043d\u043e \u0443\u0447\u0438\u0442\u044c\u0441\u044f \u043d\u0430\u0441\u043b\u044b\u0448\u043a\u043e\u044e\u00bb [5, \u0441. 296]. \u0413\u0435\u0440\u043e\u0435\u043c \u0414\u0438\u0430\u043b\u043e\u0433\u0430 11 \u0441\u0442\u0430\u043d\u043e\u0432\u0438\u0442\u0441\u044f \n\u043c\u043e\u043b\u043e\u0434\u043e\u0439 \u0447\u0435\u043b\u043e\u0432\u0435\u043a, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u0440\u043e\u0434\u0438\u043b\u0441\u044f \u0432 \u041c\u043e\u0441\u043a\u0432\u0435, \u0430 \u043f\u043e\u0437\u0436\u0435 \u043f\u0440\u043e\u0432\u0435\u043b \u043f\u043e\u043b\u0442\u043e\u0440\u0430 \u0433\u043e\u0434\u0430 \n\u0432 \u041b\u043e\u043d\u0434\u043e\u043d\u0435, \u0433\u0434\u0435 \u0438 \u0432\u044b\u0443\u0447\u0438\u043b \u0430\u043d\u0433\u043b\u0438\u0439\u0441\u043a\u0438\u0439 \u044f\u0437\u044b\u043a: \u00ab\u0413\u043e\u0432\u043e\u0440\u044e \u043d\u0435 \u043c\u043d\u043e\u0433\u043e, \u0431\u043e\u043b\u044c\u0448\u0435 \u0440\u0430\u0437\u0443-\n\u043c\u0435\u044e, \u043d\u0435\u0436\u0435\u043b\u0438 \u0433\u043e\u0432\u043e\u0440\u044e. \u2013 \u0410\u043d\u0433\u043b\u0438\u0441\u043a\u0438\u0439 \u044f\u0437\u044b\u043a \u0434\u043b\u044f \u0440\u0443\u0441\u0441\u043a\u043e\u0433\u043e \u0447\u0435\u043b\u043e\u0432\u0435\u043a\u0430 \u043e\u0447\u0435\u043d\u044c \u0442\u0440\u0443\u0434\u0435\u043d. \n\u2013 \u0420\u0443\u0441\u0441\u043a\u0438\u0439 \u044f\u0437\u044b\u043a \u0433\u043e\u0440\u0430\u0437\u0434\u043e \u0442\u0440\u0443\u0434\u043d\u0435\u0435 \u0434\u043b\u044f \u0430\u043d\u0433\u043b\u0438\u0447\u0430\u043d\u0438\u043d\u0430. \u2013 \u042f \u0441\u0443\u043c\u043d\u0435\u0432\u0430\u044e\u0441\u044c \u0432 \u044d\u0442\u043e\u043c\u00bb \n[5, \u0441. 294 \u2013 295].\n\u0415\u0449\u0435 \u043e\u0434\u0438\u043d \u043b\u044e\u0431\u043e\u043f\u044b\u0442\u043d\u044b\u0439 \u0444\u0430\u043a\u0442: \u0432 \u0440\u0430\u043d\u043d\u0438\u0445 \u043e\u0442\u0435\u0447\u0435\u0441\u0442\u0432\u0435\u043d\u043d\u044b\u0445 \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u0430\u0445 \u0438\u043d\u043e-\n\u0441\u0442\u0440\u0430\u043d\u043d\u044b\u0445 \u044f\u0437\u044b\u043a\u043e\u0432 \u043d\u0430\u043b\u0438\u0446\u043e \u043d\u0435 \u043f\u0440\u043e\u0441\u0442\u043e \u043f\u0435\u0440\u0435\u043a\u043b\u0438\u0447\u043a\u0430 \u0438\u043b\u0438 \u0447\u0430\u0441\u0442\u0438\u0447\u043d\u043e\u0435 \u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435-\n\u0441\u043a\u043e\u0435 \u0441\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u0435 \u00ab\u0423\u043f\u043e\u0442\u0440\u0435\u0431\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u0440\u0435\u0447\u0435\u0439\u00bb \u0438 \u00ab\u0420\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u043e\u0432\u00bb, \u043d\u043e \u0438 \u043f\u0440\u044f\u043c\u044b\u0435 \n\u0442\u0435\u043a\u0441\u0442\u0443\u0430\u043b\u044c\u043d\u044b\u0435 \u043f\u043e\u0432\u0442\u043e\u0440\u044b. \n\u0420\u0430\u0437\u0434\u0435\u043b \u00abExpressions of kindness\u00bb, \u0430\u043d\u0433\u043b\u0438\u0439\u0441\u043a\u0438\u0439 \u0442\u0435\u043a\u0441\u0442 \u043a\u043e\u0442\u043e\u0440\u043e\u0433\u043e \u043f\u043e\u0447\u0442\u0438 \u043e\u0434\u0438-\n\u043d\u0430\u043a\u043e\u0432 \u0432 \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u0430\u0445 \u0416\u0434\u0430\u043d\u043e\u0432\u0430 \u0438 \u041a\u0440\u044f\u0436\u0435\u0432\u0430 (\u043e\u0442\u043b\u0438\u0447\u0438\u0435 \u043b\u0438\u0448\u044c \u0432 \u043e\u0434\u043d\u043e\u0439 \u0444\u0440\u0430\u0437\u0435), \u0437\u0430-\n\u043c\u0435\u0442\u043d\u043e \u0440\u0430\u0437\u043b\u0438\u0447\u0430\u0435\u0442\u0441\u044f \u0440\u0443\u0441\u0441\u043a\u0438\u043c \u043f\u0435\u0440\u0435\u0432\u043e\u0434\u043e\u043c. \nMy Life \u0416\u0438\u0437\u043d\u044c \u043c\u043e\u044f \u0416\u0438\u0437\u043d\u044c \u043c\u043e\u044f\nMy dear Soul \u0414\u0443\u0448\u0430 \u043c\u043e\u044f \u0414\u0443\u0448\u0430 \u043c\u043e\u044f\n \u041e.\u0413. \u0421\u0438\u0434\u043e\u0440\u043e\u0432\u0430\n118\nMy Love \u041b\u044e\u0431\u0438\u043c\u044b\u0439 \u041b\u044e\u0431\u0438\u043c\u044b\u0439/\u0430\u044f; \u0443\u0442\u0435\u0445\u0430 \u043c\u043e\u044f\nMy little Darling \u0414\u0440\u0430\u0433\u043e\u0446\u0435\u043d\u043d\u044b\u0439 \u0421\u043e\u043a\u0440\u043e\u0432\u0438\u0449\u0435 \u043c\u043e\u0435, \u0434\u043e\u0440\u043e\u0433\u043e\u0439, \n \u0438\u043b\u0438 \u0421\u043e\u043a\u0440\u043e\u0432\u0438\u0449\u0435 \u043c\u043e\u0435 \u0434\u043e\u0440\u043e\u0433\u0430\u044f\nMy little Heart \u0421\u0435\u0440\u0434\u0446\u0435 \u043c\u043e\u0435 \u0421\u0435\u0440\u0434\u0446\u0435 \u043c\u043e\u0435\nMy little honey \u2013 \u0420\u0430\u0434\u043e\u0441\u0442\u044c \u043c\u043e\u044f, \u0421\u0432\u0435\u0442\u0438\u043a \u043c\u043e\u0439 \nSweet Heart \u041a\u0440\u0430\u0441\u0430\u0432\u0435\u0446 \u043c\u043e\u0439 \u2013 \nMy dear Child \u041b\u044e\u0431\u0435\u0437\u043d\u043e\u0435 \u0434\u0438\u0442\u044f\u0442\u043a\u043e \u0414\u043e\u0440\u043e\u0433\u043e\u0439, \u0434\u043e\u0440\u043e\u0433\u0430\u044f, \u0433\u043e\u043b\u0443\u0431\u0447\u0438\u043a, \n \u0433\u043e\u043b\u0443\u0431\u0443\u0448\u043a\u0430\nMy pretty Angel \u0423\u0442\u0435\u0445\u0430 \u043c\u043e\u044f, \u0410\u043d\u0433\u0435\u043b \u043c\u043e\u0439 \n\u0438\u043b\u0438 \u0410\u043d\u0433\u0435\u043b \u043c\u043e\u0439\nMy All \u0412\u0441\u0435 \u043c\u043e\u0435 \u0441\u043e\u043a\u0440\u043e\u0432\u0438\u0449\u0435 \u0412\u0441\u0435 \u043c\u043e\u0435; \u043f\u0440\u0435\u0434\u0440\u0430\u0433\u043e\u0439, \n \u043f\u0440\u0435\u0434\u0440\u0430\u0433\u0430\u044f\n[9, c. 211] [6 \u0441. 113]\n\u0421\u043e\u0432\u043f\u0430\u0434\u0435\u043d\u0438\u044f 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\n\u0423\u0447\u0435\u0431\u043d\u044b\u0435 \u0430\u043d\u0433\u043b\u043e-\u0440\u0443\u0441\u0441\u043a\u0438\u0435 \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u043d\u0438\u043a\u0438 XVIII \u2013 \u043d\u0430\u0447\u0430\u043b\u0430 XIX \u0432\u0435\u043a\u043e\u0432 \n \u041e.\u0413. \u0421\u0438\u0434\u043e\u0440\u043e\u0432\u0430\n\u0438\u0437\u0431\u0435\u0433\u0430\u0435\u0442 \u00ab\u0420\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u043e\u0432\u00bb \u0441\u0432\u0435\u0442\u0441\u043a\u043e\u0433\u043e \u0438 \u043c\u043e\u0440\u0430\u043b\u0438\u0437\u0430\u0442\u043e\u0440\u0441\u043a\u043e\u0433\u043e \u0445\u0430\u0440\u0430\u043a\u0442\u0435\u0440\u0430, \u0441\u043e\u043e\u0431\u0440\u0430\u0437\u0443-\n\u044f\u0441\u044c \u0441 \u0432\u043e\u0437\u0440\u0430\u0441\u0442\u043e\u043c \u0443\u0447\u0435\u043d\u0438\u043a\u043e\u0432 \u043f\u0430\u043d\u0441\u0438\u043e\u043d\u0430. \n\u0422\u0430\u043a\u0438\u043c \u043e\u0431\u0440\u0430\u0437\u043e\u043c, \u0432 \u043a\u043e\u043d\u0446\u0435 XVIII \u2013 \u043d\u0430\u0447\u0430\u043b\u0435 XIX \u0432\u0435\u043a\u043e\u0432 \u0430\u043d\u0433\u043b\u043e-\u0440\u0443\u0441\u0441\u043a\u0438\u0435 \u0440\u0430\u0437\u0433\u043e-\n\u0432\u043e\u0440\u043d\u0438\u043a\u0438, \u0438\u0437\u0434\u0430\u043d\u043d\u044b\u0435 \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u043e \u0438\u043b\u0438 \u0432\u043a\u043b\u044e\u0447\u0435\u043d\u043d\u044b\u0435 \u0432 \u0441\u043e\u0441\u0442\u0430\u0432 \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u043e\u0432 \u0430\u043d\u0433\u043b\u0438\u0439-\n\u0441\u043a\u043e\u0433\u043e \u044f\u0437\u044b\u043a\u0430, \u0430\u043a\u0442\u0438\u0432\u043d\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043b\u0438\u0441\u044c \u0432 \u043f\u0440\u0435\u043f\u043e\u0434\u0430\u0432\u0430\u043d\u0438\u0438 \u0438 \u043e\u0431\u0435\u0441\u043f\u0435\u0447\u0438\u0432\u0430\u043b\u0438 \u043e\u0431-\n\u0443\u0447\u0435\u043d\u0438\u0435 \u043f\u0440\u0430\u043a\u0442\u0438\u043a\u0435 \u044f\u0437\u044b\u043a\u0430. \u0414\u043e\u0441\u0442\u043e\u0432\u0435\u0440\u043d\u043e \u0438\u0437\u0432\u0435\u0441\u0442\u043d\u043e, \u0447\u0442\u043e \u043e\u043d\u0438 \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043b\u0438\u0441\u044c \u0432 \n\u043f\u0440\u0430\u043a\u0442\u0438\u043a\u0435 \u043f\u0440\u0435\u043f\u043e\u0434\u0430\u0432\u0430\u043d\u0438\u044f \u0432 \u041c\u043e\u0440\u0441\u043a\u043e\u043c \u043a\u0430\u0434\u0435\u0442\u0441\u043a\u043e\u043c \u043a\u043e\u0440\u043f\u0443\u0441\u0435 \u0432 \u041f\u0435\u0442\u0435\u0440\u0431\u0443\u0440\u0433\u0435 \u0438 \u0432 \n\u041d\u0438\u043a\u043e\u043b\u0430\u0435\u0432\u0435 \u0438 \u0432 \u0411\u043b\u0430\u0433\u043e\u0440\u043e\u0434\u043d\u043e\u043c \u043f\u0430\u043d\u0441\u0438\u043e\u043d\u0435 \u041c\u043e\u0441\u043a\u043e\u0432\u0441\u043a\u043e\u0433\u043e \u0443\u043d\u0438\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442\u0430. \u0412\u043e \u0432\u0441\u0435\u0445 \n\u0431\u0435\u0437 \u0438\u0441\u043a\u043b\u044e\u0447\u0435\u043d\u0438\u044f \u0441\u043b\u0443\u0447\u0430\u044f\u0445 \u043e\u043d\u0438 \u043d\u0435 \u0442\u043e\u043b\u044c\u043a\u043e \u0438\u0433\u0440\u0430\u043b\u0438 \u0440\u043e\u043b\u044c \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u043e\u0432 \u0430\u043d\u0433\u043b\u0438\u0439\u0441\u043a\u043e\u0433\u043e \n\u044f\u0437\u044b\u043a\u0430, \u043d\u043e \u0442\u0430\u043a\u0436\u0435 \u0432\u044b\u043f\u043e\u043b\u043d\u044f\u043b\u0438 \u0432\u043e\u0441\u043f\u0438\u0442\u0430\u0442\u0435\u043b\u044c\u043d\u0443\u044e \u0438 \u0441\u043e\u0446\u0438\u043e\u043a\u0443\u043b\u044c\u0442\u0443\u0440\u043d\u0443\u044e \u0444\u0443\u043d\u043a\u0446\u0438\u044e, \n\u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u044f\u044f \u0443\u0447\u0435\u043d\u0438\u043a\u0430\u043c \u043c\u043e\u0434\u0435\u043b\u0438 \u043f\u043e\u0432\u0435\u0434\u0435\u043d\u0438\u044f, \u043f\u0440\u0430\u0432\u0438\u043b\u0430 \u044d\u0442\u0438\u043a\u0435\u0442\u0430, \u0437\u043d\u0430\u043a\u043e\u043c\u044f \u0438\u0445 \u0441 \n\u0434\u043e\u0441\u0442\u0438\u0436\u0435\u043d\u0438\u044f\u043c\u0438 \u043a\u0443\u043b\u044c\u0442\u0443\u0440\u044b, \u0441 \u0442\u0435\u043d\u0434\u0435\u043d\u0446\u0438\u044f\u043c\u0438 \u043c\u043e\u0434\u044b \u0438 \u0442.\u0434., \u0430 \u0442\u0430\u043a\u0436\u0435 \u0440\u0435\u043a\u043b\u0430\u043c\u0438\u0440\u0443\u044f \n\u0440\u0443\u0441\u0441\u043a\u0443\u044e \u043a\u0443\u043b\u044c\u0442\u0443\u0440\u0443.\n\u041b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430\n1. \u0411\u0438\u0440\u0436\u0430\u043a\u043e\u0432\u0430 \u0415. \u042d. \u0418\u0437 \u0438\u0441\u0442\u043e\u0440\u0438\u0438 \u0440\u0443\u0441\u0441\u043a\u043e-\u0438\u043d\u043e\u044f\u0437\u044b\u0447\u043d\u043e\u0439 \u043b\u0435\u043a\u0441\u0438\u043a\u043e\u0433\u0440\u0430\u0444\u0438\u0438 XVIII \n\u0432. \u00ab\u0420\u0443\u0441\u0441\u043a\u043e-\u0433\u043e\u043b\u043b\u0430\u043d\u0434\u0441\u043a\u0438\u0439 \u043b\u0435\u043a\u0441\u0438\u043a\u043e\u043d\u00bb \u042f\u043a\u043e\u0432\u0430 \u0411\u0440\u044e\u0441\u0430 // \u0421\u043b\u043e\u0432\u0430\u0440\u0438 \u0438 \u0441\u043b\u043e\u0432\u0430\u0440\u043d\u043e\u0435 \u0434\u0435\u043b\u043e \n\u0432 \u0420\u043e\u0441\u0441\u0438\u0438 XVIII \u0432. /\u041e\u0442\u0432. \u0440\u0435\u0434. \u041b. \u041a\u0443\u0442\u0438\u043d\u0430 \u0438 \u0415. \u0411\u0438\u0440\u0436\u0430\u043a\u043e\u0432\u0430. \u041b.: \u041d\u0430\u0443\u043a\u0430, 1980. \u2013 \u0421. \n23\u201338.\n2. \u0411\u0443\u043b\u0438\u0447 \u0421. \u041a. \u041e\u0447\u0435\u0440\u043a \u0438\u0441\u0442\u043e\u0440\u0438\u0438 \u044f\u0437\u044b\u043a\u043e\u0437\u043d\u0430\u043d\u0438\u044f \u0432 \u0420\u043e\u0441\u0441\u0438\u0438. \u0422. 1 (XIII \u0432. \u2013 1825\u0433.). \n\u0421\u041f\u0431.: \u0442\u0438\u043f. \u041c\u0430\u0440\u043a\u0443\u0448\u0435\u0432\u0430, 1904. \u2013 1248 \u0441.\n3. \u0412\u043e\u043c\u043f\u0435\u0440\u0441\u043a\u0438\u0439 \u0412. \u041c. \u0421\u043b\u043e\u0432\u0430\u0440\u0438 \u0425VIII \u0432\u0435\u043a\u0430. \u041c.: \u041d\u0430\u0443\u043a\u0430, 1986. \u2013 136 \u0441.\n4. \u0414\u0443\u0431\u044b\u043d\u0438\u043d\u0430 \u041d. \u0412. \u041f\u0440\u0435\u043f\u043e\u0434\u0430\u0432\u0430\u043d\u0438\u0435 \u0444\u0440\u0430\u043d\u0446\u0443\u0437\u0441\u043a\u043e\u0433\u043e \u044f\u0437\u044b\u043a\u0430 \u0432 XVIII \u0432\u0435\u043a\u0435 \u0438 \n\u041c\u043e\u0441\u043a\u043e\u0432\u0441\u043a\u0438\u0439 \u0443\u043d\u0438\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442 // \u0412\u0435\u0441\u0442\u043d\u0438\u043a \u041c\u0413\u0423. \u0421\u0435\u0440\u0438\u044f19. \u041b\u0438\u043d\u0433\u0432\u0438\u0441\u0442\u0438\u043a\u0430 \u0438 \u043c\u0435\u0436-\n\u043a\u0443\u043b\u044c\u0442\u0443\u0440\u043d\u0430\u044f \u043a\u043e\u043c\u043c\u0443\u043d\u0438\u043a\u0430\u0446\u0438\u044f. \u2013 2004. \u2013 \u2116 3. \u2013 \u0421. 69\u201385.\n5. \u0416\u0434\u0430\u043d\u043e\u0432 \u041f. \u0410\u043d\u0433\u043b\u0438\u043d\u0441\u043a\u0430\u044f \u0433\u0440\u0430\u043c\u043c\u0430\u0442\u0438\u043a\u0430, \u0441\u043e\u0447\u0438\u043d\u0435\u043d\u043d\u0430\u044f \u041c\u043e\u0440\u0441\u043a\u043e\u0433\u043e \n\u0428\u043b\u044f\u0445\u0435\u0442\u043d\u043e\u0433\u043e \u043a\u0430\u0434\u0435\u0442\u0441\u043a\u043e\u0433\u043e \u043a\u043e\u0440\u043f\u0443\u0441\u0430 \u0443\u0447\u0438\u0442\u0435\u043b\u0435\u043c \u041f\u0440\u043e\u0445\u043e\u0440\u043e\u043c \u0416\u0434\u0430\u043d\u043e\u0432\u044b\u043c \u0432 \u043f\u043e\u043b\u044c-\n\u0437\u0443 \u0443\u0447\u0430\u0449\u0435\u0433\u043e\u0441\u044f \u0431\u043b\u0430\u0433\u043e\u0440\u043e\u0434\u043d\u043e\u0433\u043e \u044e\u043d\u043e\u0448\u0435\u0441\u0442\u0432\u0430. \u0421\u041f\u0431.: \u0422\u0438\u043f\u043e\u0433\u0440\u0430\u0444\u0438\u044f \u043f\u0440\u0438 \u041c\u043e\u0440\u0441\u043a\u043e\u043c \n\u0448\u043b\u044f\u0445\u0435\u0442\u043d\u043e\u043c \u043a\u0430\u0434\u0435\u0442\u0441\u043a\u043e\u043c \u043a\u043e\u0440\u043f\u0443\u0441\u0435, 1772. \u2013 304 \u0441.\n6. \u041b\u0435\u0432\u0447\u0435\u043d\u043a\u043e \u0413. \u0410. \u0421\u043b\u043e\u0432\u0430\u0440\u044c-\u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u043d\u0438\u043a \u0432 \u0420\u043e\u0441\u0441\u0438\u0438: \u043a \u0432\u043e\u043f\u0440\u043e\u0441\u0443 \u043e\u0431 \u0438\u0441\u0442\u043e\u0440\u0438\u0438 \n\u0436\u0430\u043d\u0440\u0430 // \u0412\u0435\u0441\u0442\u043d\u0438\u043a \u041c\u0413\u0423. \u0421\u0435\u0440\u0438\u044f 19. \u041b\u0438\u043d\u0433\u0432\u0438\u0441\u0442\u0438\u043a\u0430 \u0438 \u043c\u0435\u0436\u043a\u0443\u043b\u044c\u0442\u0443\u0440\u043d\u0430\u044f \u043a\u043e\u043c\u043c\u0443\u043d\u0438-\n\u043a\u0430\u0446\u0438\u044f. \u2013 2006. \u2013 \u2116 3. \u2013 \u0421. 145\u2013156.\n7. \u041b\u0435\u0432\u0447\u0435\u043d\u043a\u043e \u0413. \u0410. \u0422\u0438\u043f\u043e\u043b\u043e\u0433\u0438\u044f \u0441\u043b\u043e\u0432\u0430\u0440\u0435\u0439-\u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u043d\u0438\u043a\u043e\u0432 \u0432 \u0420\u043e\u0441\u0441\u0438\u0438 // \u0412\u0435\u0441\u0442\u043d\u0438\u043a \n\u041c\u0413\u0423. \u0421\u0435\u0440\u0438\u044f 19. \u041b\u0438\u043d\u0433\u0432\u0438\u0441\u0442\u0438\u043a\u0430 \u0438 \u043c\u0435\u0436\u043a\u0443\u043b\u044c\u0442\u0443\u0440\u043d\u0430\u044f \u043a\u043e\u043c\u043c\u0443\u043d\u0438\u043a\u0430\u0446\u0438\u044f. \u2013 2007. \u2013 \u2116 \n4. \u2013 \u0421. 133 \u2013 142.\n8. \u041a\u0440\u044f\u0436\u0435\u0432 \u0412. \u0410\u043d\u0433\u043b\u0438\u043d\u0441\u043a\u0430\u044f \u0433\u0440\u0430\u043c\u043c\u0430\u0442\u0438\u043a\u0430, \u0437\u0430\u043a\u043b\u044e\u0447\u0430\u044e\u0449\u0430\u044f \u0432 \u0441\u0435\u0431\u0435 \u043a\u0440\u0430\u0442\u043a\u043e \u0432\u0441\u0435 \n\u043f\u0440\u0430\u0432\u0438\u043b\u0430, \u043d\u0443\u0436\u043d\u044b\u0435 \u0434\u043b\u044f \u0438\u0437\u0443\u0447\u0435\u043d\u0438\u044f \u0441\u0435\u043c\u0443 \u044f\u0437\u044b\u043a\u0443, \u0441 \u043f\u0440\u0438\u0432\u043b\u0435\u0447\u0435\u043d\u0438\u0435\u043c \u0443\u043f\u043e\u0442\u0440\u0435\u0431\u0438\u0442\u0435\u043b\u044c-\n\u043d\u044b\u0445 \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u043e\u0432. \u041c., 1795. \u2013 241 c.\n119\n\u0423\u0447\u0435\u0431\u043d\u044b\u0435 \u0430\u043d\u0433\u043b\u043e-\u0440\u0443\u0441\u0441\u043a\u0438\u0435 \u0440\u0430\u0437\u0433\u043e\u0432\u043e\u0440\u043d\u0438\u043a\u0438 XVIII \u2013 \u043d\u0430\u0447\u0430\u043b\u0430 XIX \u0432\u0435\u043a\u043e\u0432 \n9. \u041f\u0435\u0440\u043c\u0441\u043a\u0438\u0439 \u041c. \u041f\u0440\u0430\u043a\u0442\u0438\u0447\u0435\u0441\u043a\u0430\u044f \u0430\u043d\u0433\u043b\u0438\u0441\u043a\u0430\u044f \u0433\u0440\u0430\u043c\u043c\u0430\u0442\u0438\u043a\u0430.\u0421\u041f\u0431.: \u0422\u0438\u043f\u043e\u0433\u0440\u0430\u0444\u0438\u044f \n\u043f\u0440\u0438 \u041c\u043e\u0440\u0441\u043a\u043e\u043c \u0448\u043b\u044f\u0445\u0435\u0442\u043d\u043e\u043c \u043a\u0430\u0434\u0435\u0442\u0441\u043a\u043e\u043c \u043a\u043e\u0440\u043f\u0443\u0441\u0435, 1766. \u2013 192 \u0441.\n10.\u0420\u0443\u0434\u043d\u0435\u0432 \u0414.\u0412. \u041d\u0435\u0438\u0437\u0432\u0435\u0441\u0442\u043d\u044b\u0435 \u0438\u043c\u0435\u043d\u0430 \u0425VIII \u0432\u0435\u043a\u0430: \u041f\u0440\u043e\u0445\u043e\u0440 \u0418\u0432\u0430\u043d\u043e\u0432\u0438\u0447 \u0416\u0434\u0430\u043d\u043e\u0432 \n// \u041b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u043d\u0430\u044f \u043a\u0443\u043b\u044c\u0442\u0443\u0440\u0430 \u0420\u043e\u0441\u0441\u0438\u0438 \u0425VIII \u0432\u0435\u043a\u0430/ \u041f\u043e\u0434 \u0440\u0435\u0434. \u0411\u0443\u0445\u0430\u0440\u043a\u0438\u043d\u0430 \u041f. \u0415. \u0438 \u0434\u0440. \n[\u042d\u043b\u0435\u043a\u0442\u0440\u043e\u043d\u043d\u044b\u0439 \u0440\u0435\u0441\u0443\u0440\u0441]. \u0412\u044b\u043f. 4. \u2013 \u0421\u041f\u0431., 2011. \u2013 \u0421. 262\u2013279. URL: http://18vek.\nspb.ru/sbornik-4.pdf/ (\u0414\u0430\u0442\u0430 \u043e\u0431\u0440\u0430\u0449\u0435\u043d\u0438\u044f 05. 12. 2015)\n11.\u0421\u0438\u0434\u043e\u0440\u043e\u0432\u0430 \u041e. \u0413. \u041f\u0435\u0440\u0432\u044b\u0435 \u0440\u0443\u0441\u0441\u043a\u0438\u0435 \u0443\u0447\u0435\u0431\u043d\u0438\u043a\u0438 \u0430\u043d\u0433\u043b\u0438\u0439\u0441\u043a\u043e\u0433\u043e \u044f\u0437\u044b\u043a\u0430: \u0441\u043e\u0446\u0438\u043e-\n\u043a\u0443\u043b\u044c\u0442\u0443\u0440\u043d\u044b\u0439 \u0430\u0441\u043f\u0435\u043a\u0442 // Albionika. \u0410\u043b\u044c\u043c\u0430\u043d\u0430\u0445 \u0438\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u043d\u0438\u0439 \u0432\u0441\u0435\u043e\u0431\u0449\u0435\u0439 \u0438\u0441\u0442\u043e\u0440\u0438\u0438 \nXVI\u2013XX \u0432\u0432. \u2116 7. \u0421\u0435\u0440\u0438\u044f \u00ab\u0418\u043d\u0442\u0435\u043b\u043b\u0435\u043a\u0442\u0443\u0430\u043b\u044c\u043d\u0430\u044f \u0438\u0441\u0442\u043e\u0440\u0438\u044f\u00bb. \u0412\u044b\u043f. 4. \u0415\u043a\u0430\u0442\u0435\u0440\u0438\u043d\u0431\u0443\u0440\u0433: \n\u0418\u0437\u0434-\u0432\u043e \u0423\u0440\u0413\u0423, 2010. \u2013 \u0421. 67\u201381.\n12.Howatt A.P., Widdowson H.G. A History of English Language Teaching. \nOxford: OUP, 2004, 2nd ed. \u2013 147p.\n120 \u7ffb\u8bd1\u6210\u6c49\u8bed\uff0c\u6700\u540e\u7684\u53c2\u8003\u6587\u732e\u4e0d\u7528\u7ffb\u8bd1"},{"assistant_initiates":false,"asst_text":"\u5f53\u7136\u53ef\u4ee5\u3002\u4ee5\u4e0b\u662f\u539f\u6587\u524d\u4e24\u9875\u7684\u4e2d\u6587\u7ffb\u8bd1\uff1a\n\n---\n\n109\n\u5b66\u4e60\u6559\u6750\u7684\u5386\u53f2\n\u5173\u952e\u8bcd\uff1a\n18\u4e16\u7eaa\uff0c\u5916\u8bed\u5b66\u4e60\uff0c\n\u6559\u6750\uff0c\u82f1\u4fc4\u4f1a\u8bdd\u624b\u518c\u3002\nO.G.\u897f\u591a\u7f57\u5a03\n\n18\u81f319\u4e16\u7eaa\u521d\u7684\u82f1\u4fc4\u4f1a\u8bdd\u624b\u518c\n\n\u672c\u6587\u63a2\u8ba8\u4e86\u9996\u6279\u5728\u4fc4\u7f57\u65af\u51fa\u7248\u7684\u82f1\u4fc4\u4f1a\u8bdd\u624b\u518c\uff0c\u8fd9\u4e9b\u624b\u518c\u65e2\u6709\u4f5c\u4e3a\u72ec\u7acb\u6559\u6750\u51fa\u7248\u7684\uff0c\u4e5f\u6709\u4f5c\u4e3a\u6559\u6750\u4e00\u90e8\u5206\u7684\u3002\u7531\u4e8e\u5176\u6559\u5b66\u529f\u80fd\uff0c\u8fd9\u4e9b\u624b\u518c\u53d1\u6325\u4e86\u6559\u80b2\u548c\u80b2\u4eba\u7684\u4f5c\u7528\uff0c\u5728\u6559\u5b66\u8fc7\u7a0b\u4e2d\u88ab\u5e7f\u6cdb\u4f7f\u7528\uff0c\u8865\u5145\u4e86\u6559\u6750\u7684\u7406\u8bba\u90e8\u5206\u3002\u6587\u7ae0\u5bf9\u6bd4\u5206\u6790\u4e861772\u5e74P.\u65e5\u4e39\u8bfa\u592b\u548c1795\u5e74V.S.\u514b\u91cc\u4e9a\u70ed\u592b\u7684\u82f1\u4fc4\u4f1a\u8bdd\u624b\u518c\u3002\n\n\u9996\u6279\u4e3a\u4fc4\u8bed\u5b66\u751f\u51c6\u5907\u7684\u6d3b\u4f53\u6b27\u6d32\u8bed\u8a00\u6559\u6750\u51fa\u73b0\u572818\u4e16\u7eaa\u3002\u5b83\u4eec\u7684\u51fa\u73b0\u4e0e\u4e16\u4fd7\u7c7b\u578b\u5b66\u6821\u7684\u5efa\u7acb\u3001\u4e0e\u6b27\u6d32\u4eba\u4ea4\u6d41\u9700\u6c42\u7684\u589e\u52a0\uff0c\u4ee5\u53ca\u56fd\u5bb6\u548c\u793e\u4f1a\u7684\u9700\u6c42\u6709\u5173\u3002\n\n18\u4e16\u7eaa\uff0c\u5728\u4fc4\u7f57\u65af\u5f62\u6210\u4e86\u6839\u636e\u5916\u8bed\u6d41\u884c\u7a0b\u5ea6\u800c\u6392\u5217\u7684\u8bed\u8a00\u7b49\u7ea7\u3002\u4e16\u7eaa\u521d\uff0c\u8377\u5170\u8bed\u7684\u638c\u63e1\u662f\u91cd\u8981\u7684\u3002\u6839\u636e\u5f7c\u5f97\u4e00\u4e16\u7684\u547d\u4ee4\uff0c1717\u5e74\u7531J.\u5e03\u9c81\u65af\u7f16\u5199\u7684\u300a\u4fc4\u8377\u5b57\u5178\u300b\u51fa\u7248\uff1b\u76f4\u52301725\u5e74\uff0c\u67098\u672c\u4e66\u4ece\u8377\u5170\u8bed\u7ffb\u8bd1\u6210\u4fc4\u8bed\uff0c\u52301740\u5e74\u53c8\u67094\u672c\uff0c\u4e4b\u540e\u5230\u4e16\u7eaa\u672b\u201c\u4e66\u76ee\u7d22\u5f15\u672a\u8bb0\u5f55\u4efb\u4f55\u8377\u5170\u8bed\u8bd1\u8457\u201d [1, p. 36]\u3002\u968f\u7740\u65f6\u95f4\u7684\u63a8\u79fb\uff0c\u8377\u5170\u8bed\u88ab\u5fb7\u8bed\u53d6\u4ee3\uff0c\u4e0d\u4e45\u540e\u6cd5\u8bed\u5728\u4fc4\u56fd\u516c\u4f17\u4e2d\u83b7\u5f97\u4e86\u4eba\u6c14\u3002\u4ece1730\u5e74\u4ee3\u8d77\uff0c\u51fa\u73b0\u4e86\u5927\u91cf\u4e3a\u4fc4\u56fd\u4eba\u51c6\u5907\u7684\u5fb7\u8bed\u548c\u6cd5\u8bed\u6559\u6750 [\u89c12]\u3002\n\n\u81f3\u4e8e\u82f1\u8bed\uff0c18\u4e16\u7eaa\u5728\u4fc4\u7f57\u65af\u5b83\u4ecd\u662f\u7f55\u89c1\u7684\u8bed\u8a00\u2014\u2014\u8fd9\u4e00\u70b9\u4ece\u82f1\u8bed\u7684\u6559\u5b66\u72b6\u51b5\u53ef\u89c1\u4e00\u6591\u3002\u9996\u5148\uff0c\u6cd5\u8bed\u548c\u5fb7\u8bed\u88ab\u7eb3\u5165\u6587\u6cd5\u5b66\u6821\u548c\u5927\u5b66\u7684\u8bfe\u7a0b\u4e2d\u3002\u6839\u636eS.M.\u7d22\u6d1b\u7ef4\u7ea6\u592b\u7684\u8bb0\u5f55\uff0cN.\u675c\u5e03\u5c3c\u5a1c\u5199\u9053\uff0c\u5728\u5b89\u5a1c\u00b7\u4f0a\u51e1\u8bfa\u592b\u5a1c\u7edf\u6cbb\u65f6\u671f\u6210\u7acb\u7684\u519b\u5b98\u5b66\u6821\u4e2d\uff0c\u201c245\u540d\u4fc4\u7f57\u65af\u5b66\u5458\u4e2d\u53ea\u670918\u4eba\u5b66\u4e60\u4fc4\u8bed\uff0c1\u4eba\u5b66\u4e60\u6cd5\u8bed\uff0c15\u4eba\u5b66\u4e60\u62c9\u4e01\u8bed\uff0c237\u4eba\u5b66\u4e60\u5fb7\u8bed\u201d [4, p. 71]\u300218\u4e16\u7eaa\u4e0b\u534a\u53f6\uff0c\u5728\u83ab\u65af\u79d1\u4e3a\u5927\u5b66\u5165\u5b66\u521b\u7acb\u4e86\u4e00\u4e2a\u540d\u4e3a\u201c\u5b66\u4e60\u65b9\u6cd5\u201d\u7684\u8bfe\u7a0b\uff0c\u7531\u83ab\u65af\u79d1\u5927\u5b66\u7684\u6559\u5e08\u7528\u4fc4\u8bed\u3001\u62c9\u4e01\u8bed\u3001\u5fb7\u8bed\u548c\u6cd5\u8bed\u7f16\u5199\u3002\u8be5\u8bfe\u7a0b\u57281790\u5e74\u8fdb\u884c\u4e86\u8865\u5145\u7248\u518d\u7248\uff0c\u4f46\u5373\u4fbf\u662f\u5728\u65b0\u7684\u7248\u672c\u4e2d\uff0c\u4e5f\u672a\u5305\u542b\u82f1\u8bed\u3002\n\n\u968f\u7740\u5916\u8bed\u88ab\u7eb3\u5165\u8bfe\u7a0b\uff0c\u8bed\u8a00\u6559\u6750\u7684\u9700\u6c42\u51fa\u73b0\u3002\u5728\u8fd9\u65b9\u9762\uff0c\u82f1\u8bed\u518d\u6b21\u843d\u540e\u4e8e\u5176\u4ed6\u8bed\u8a00\u3002S.K.\u5e03\u5229\u5947\u6307\u51fa\uff0c\u201cM. \u4f69\u59c6\u65af\u57fa\u7684\u9996\u90e8\u82f1\u6587\u8bed\u6cd5\u6559\u6750\u2026\u2026\u6bd4\u5fb7\u8bed\u548c\u6cd5\u8bed\u8bed\u6cd5\u665a\u51fa\u7248\u4e8636\u5e74\u201d [2, p. 331]\u3002\u5bf9\u6bd418\u4e16\u7eaa\u4fc4\u56fd\u51fa\u7248\u7684\u5916\u8bed\u6559\u6750\u6e05\u5355\uff0c\u82f1\u8bed\u6559\u6750\u7684\u6559\u5b66\u548c\u5b66\u4e60\u5174\u8da3\u660e\u663e\u4e0d\u5982\u5176\u4ed6\u8bed\u8a00\uff1a\u4f8b\u5982\uff0c\u4ece1749\u5e74\u81f31800\u5e74\u95f4\u51fa\u7248\u7684\u6cd5\u8bed\u6559\u6750\u6e05\u5355\u4e2d\u51fa\u73b0\u4e8633\u4e2a\u6807\u9898 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States","empty_output":false,"evidence_codes":[],"label":"absent","label_present":false,"label_qualified":false,"label_source":"Final dense release","language":"Chinese","model":"gpt-4o-2024-08-06","n_chars":1183,"n_turns_in_conversation":10,"n_words":30,"source_row_offset":10735,"source_shard":"turns-00052.parquet","timestamp":"Fri, 15 Nov 2024 05:54:48 GMT","turn_id":"b792c2e1840c247ba6448f1b","turn_index":1,"user_text":"\u90a3\u5c31\u7ffb\u8bd1\u524d\u4e24\u9875"}],"shard":{"index":52,"name":"turns-00052.parquet","rows":53077}}