feat(ChatKnowledge): Support Financial Report Analysis (#1702)
Co-authored-by: hzh97 <2976151305@qq.com> Co-authored-by: Fangyin Cheng <staneyffer@gmail.com> Co-authored-by: licunxing <864255598@qq.com>main
Aries-ckt
1 year ago
committed by
GitHub
parent
22e0680a6a
commit
167d972093
@ -0,0 +1,3 @@ |
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USE dbgpt; |
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ALTER TABLE knowledge_space |
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ADD COLUMN `domain_type` varchar(50) null comment 'space domain type' after `vector_type`; |
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@ -0,0 +1,396 @@ |
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-- Full SQL of v0.5.9, please not modify this file(It must be same as the file in the release package) |
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|
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CREATE |
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DATABASE IF NOT EXISTS dbgpt; |
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use dbgpt; |
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|
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-- For alembic migration tool |
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CREATE TABLE IF NOT EXISTS `alembic_version` |
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( |
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version_num VARCHAR(32) NOT NULL, |
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CONSTRAINT alembic_version_pkc PRIMARY KEY (version_num) |
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) DEFAULT CHARSET=utf8mb4 ; |
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|
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CREATE TABLE IF NOT EXISTS `knowledge_space` |
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( |
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`id` int NOT NULL AUTO_INCREMENT COMMENT 'auto increment id', |
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`name` varchar(100) NOT NULL COMMENT 'knowledge space name', |
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`vector_type` varchar(50) NOT NULL COMMENT 'vector type', |
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`desc` varchar(500) NOT NULL COMMENT 'description', |
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`owner` varchar(100) DEFAULT NULL COMMENT 'owner', |
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`context` TEXT DEFAULT NULL COMMENT 'context argument', |
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`gmt_created` TIMESTAMP DEFAULT CURRENT_TIMESTAMP COMMENT 'created time', |
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`gmt_modified` TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT 'update time', |
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PRIMARY KEY (`id`), |
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KEY `idx_name` (`name`) COMMENT 'index:idx_name' |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT='knowledge space table'; |
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|
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CREATE TABLE IF NOT EXISTS `knowledge_document` |
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( |
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`id` int NOT NULL AUTO_INCREMENT COMMENT 'auto increment id', |
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`doc_name` varchar(100) NOT NULL COMMENT 'document path name', |
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`doc_type` varchar(50) NOT NULL COMMENT 'doc type', |
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`space` varchar(50) NOT NULL COMMENT 'knowledge space', |
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`chunk_size` int NOT NULL COMMENT 'chunk size', |
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`last_sync` TIMESTAMP DEFAULT CURRENT_TIMESTAMP COMMENT 'last sync time', |
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`status` varchar(50) NOT NULL COMMENT 'status TODO,RUNNING,FAILED,FINISHED', |
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`content` LONGTEXT NOT NULL COMMENT 'knowledge embedding sync result', |
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`result` TEXT NULL COMMENT 'knowledge content', |
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`vector_ids` LONGTEXT NULL COMMENT 'vector_ids', |
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`summary` LONGTEXT NULL COMMENT 'knowledge summary', |
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`gmt_created` TIMESTAMP DEFAULT CURRENT_TIMESTAMP COMMENT 'created time', |
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`gmt_modified` TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT 'update time', |
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PRIMARY KEY (`id`), |
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KEY `idx_doc_name` (`doc_name`) COMMENT 'index:idx_doc_name' |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT='knowledge document table'; |
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|
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CREATE TABLE IF NOT EXISTS `document_chunk` |
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( |
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`id` int NOT NULL AUTO_INCREMENT COMMENT 'auto increment id', |
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`doc_name` varchar(100) NOT NULL COMMENT 'document path name', |
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`doc_type` varchar(50) NOT NULL COMMENT 'doc type', |
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`document_id` int NOT NULL COMMENT 'document parent id', |
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`content` longtext NOT NULL COMMENT 'chunk content', |
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`meta_info` varchar(200) NOT NULL COMMENT 'metadata info', |
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`gmt_created` timestamp NULL DEFAULT CURRENT_TIMESTAMP COMMENT 'created time', |
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`gmt_modified` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT 'update time', |
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PRIMARY KEY (`id`), |
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KEY `idx_document_id` (`document_id`) COMMENT 'index:document_id' |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT='knowledge document chunk detail'; |
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CREATE TABLE IF NOT EXISTS `connect_config` |
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( |
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`id` int NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`db_type` varchar(255) NOT NULL COMMENT 'db type', |
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`db_name` varchar(255) NOT NULL COMMENT 'db name', |
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`db_path` varchar(255) DEFAULT NULL COMMENT 'file db path', |
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`db_host` varchar(255) DEFAULT NULL COMMENT 'db connect host(not file db)', |
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`db_port` varchar(255) DEFAULT NULL COMMENT 'db cnnect port(not file db)', |
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`db_user` varchar(255) DEFAULT NULL COMMENT 'db user', |
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`db_pwd` varchar(255) DEFAULT NULL COMMENT 'db password', |
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`comment` text COMMENT 'db comment', |
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`sys_code` varchar(128) DEFAULT NULL COMMENT 'System code', |
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PRIMARY KEY (`id`), |
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UNIQUE KEY `uk_db` (`db_name`), |
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KEY `idx_q_db_type` (`db_type`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT 'Connection confi'; |
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CREATE TABLE IF NOT EXISTS `chat_history` |
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( |
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`id` int NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`conv_uid` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL COMMENT 'Conversation record unique id', |
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`chat_mode` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL COMMENT 'Conversation scene mode', |
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`summary` longtext COLLATE utf8mb4_unicode_ci NOT NULL COMMENT 'Conversation record summary', |
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`user_name` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'interlocutor', |
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`messages` text COLLATE utf8mb4_unicode_ci COMMENT 'Conversation details', |
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`message_ids` text COLLATE utf8mb4_unicode_ci COMMENT 'Message id list, split by comma', |
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`sys_code` varchar(128) DEFAULT NULL COMMENT 'System code', |
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`gmt_created` timestamp NULL DEFAULT CURRENT_TIMESTAMP COMMENT 'created time', |
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`gmt_modified` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT 'update time', |
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UNIQUE KEY `conv_uid` (`conv_uid`), |
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PRIMARY KEY (`id`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci COMMENT 'Chat history'; |
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CREATE TABLE IF NOT EXISTS `chat_history_message` |
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( |
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`id` int NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`conv_uid` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL COMMENT 'Conversation record unique id', |
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`index` int NOT NULL COMMENT 'Message index', |
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`round_index` int NOT NULL COMMENT 'Round of conversation', |
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`message_detail` text COLLATE utf8mb4_unicode_ci COMMENT 'Message details, json format', |
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`gmt_created` timestamp NULL DEFAULT CURRENT_TIMESTAMP COMMENT 'created time', |
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`gmt_modified` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT 'update time', |
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UNIQUE KEY `message_uid_index` (`conv_uid`, `index`), |
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PRIMARY KEY (`id`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci COMMENT 'Chat history message'; |
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CREATE TABLE IF NOT EXISTS `chat_feed_back` |
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( |
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`id` bigint(20) NOT NULL AUTO_INCREMENT, |
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`conv_uid` varchar(128) DEFAULT NULL COMMENT 'Conversation ID', |
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`conv_index` int(4) DEFAULT NULL COMMENT 'Round of conversation', |
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`score` int(1) DEFAULT NULL COMMENT 'Score of user', |
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`ques_type` varchar(32) DEFAULT NULL COMMENT 'User question category', |
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`question` longtext DEFAULT NULL COMMENT 'User question', |
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`knowledge_space` varchar(128) DEFAULT NULL COMMENT 'Knowledge space name', |
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`messages` longtext DEFAULT NULL COMMENT 'The details of user feedback', |
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`user_name` varchar(128) DEFAULT NULL COMMENT 'User name', |
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`gmt_created` timestamp NULL DEFAULT CURRENT_TIMESTAMP COMMENT 'created time', |
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`gmt_modified` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT 'update time', |
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PRIMARY KEY (`id`), |
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UNIQUE KEY `uk_conv` (`conv_uid`,`conv_index`), |
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KEY `idx_conv` (`conv_uid`,`conv_index`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT='User feedback table'; |
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CREATE TABLE IF NOT EXISTS `my_plugin` |
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( |
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`id` int NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`tenant` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'user tenant', |
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`user_code` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL COMMENT 'user code', |
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`user_name` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'user name', |
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`name` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL COMMENT 'plugin name', |
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`file_name` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL COMMENT 'plugin package file name', |
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`type` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'plugin type', |
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`version` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'plugin version', |
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`use_count` int DEFAULT NULL COMMENT 'plugin total use count', |
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`succ_count` int DEFAULT NULL COMMENT 'plugin total success count', |
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`sys_code` varchar(128) DEFAULT NULL COMMENT 'System code', |
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`gmt_created` TIMESTAMP DEFAULT CURRENT_TIMESTAMP COMMENT 'plugin install time', |
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PRIMARY KEY (`id`), |
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UNIQUE KEY `name` (`name`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci COMMENT='User plugin table'; |
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CREATE TABLE IF NOT EXISTS `plugin_hub` |
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( |
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`id` int NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`name` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL COMMENT 'plugin name', |
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`description` varchar(255) COLLATE utf8mb4_unicode_ci NOT NULL COMMENT 'plugin description', |
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`author` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'plugin author', |
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`email` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'plugin author email', |
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`type` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'plugin type', |
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`version` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'plugin version', |
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`storage_channel` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'plugin storage channel', |
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`storage_url` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'plugin download url', |
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`download_param` varchar(255) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'plugin download param', |
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`gmt_created` TIMESTAMP DEFAULT CURRENT_TIMESTAMP COMMENT 'plugin upload time', |
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`installed` int DEFAULT NULL COMMENT 'plugin already installed count', |
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PRIMARY KEY (`id`), |
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UNIQUE KEY `name` (`name`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci COMMENT='Plugin Hub table'; |
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CREATE TABLE IF NOT EXISTS `prompt_manage` |
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( |
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`id` int(11) NOT NULL AUTO_INCREMENT, |
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`chat_scene` varchar(100) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'Chat scene', |
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`sub_chat_scene` varchar(100) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'Sub chat scene', |
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`prompt_type` varchar(100) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'Prompt type: common or private', |
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`prompt_name` varchar(256) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'prompt name', |
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`content` longtext COLLATE utf8mb4_unicode_ci COMMENT 'Prompt content', |
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`input_variables` varchar(1024) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'Prompt input variables(split by comma))', |
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`model` varchar(128) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'Prompt model name(we can use different models for different prompt)', |
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`prompt_language` varchar(32) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'Prompt language(eg:en, zh-cn)', |
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`prompt_format` varchar(32) COLLATE utf8mb4_unicode_ci DEFAULT 'f-string' COMMENT 'Prompt format(eg: f-string, jinja2)', |
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`prompt_desc` varchar(512) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'Prompt description', |
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`user_name` varchar(128) COLLATE utf8mb4_unicode_ci DEFAULT NULL COMMENT 'User name', |
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`sys_code` varchar(128) DEFAULT NULL COMMENT 'System code', |
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`gmt_created` timestamp NULL DEFAULT CURRENT_TIMESTAMP COMMENT 'created time', |
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`gmt_modified` timestamp NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT 'update time', |
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PRIMARY KEY (`id`), |
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UNIQUE KEY `prompt_name_uiq` (`prompt_name`, `sys_code`, `prompt_language`, `model`), |
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KEY `gmt_created_idx` (`gmt_created`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci COMMENT='Prompt management table'; |
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CREATE TABLE IF NOT EXISTS `gpts_conversations` ( |
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`id` int(11) NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`conv_id` varchar(255) NOT NULL COMMENT 'The unique id of the conversation record', |
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`user_goal` text NOT NULL COMMENT 'User''s goals content', |
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`gpts_name` varchar(255) NOT NULL COMMENT 'The gpts name', |
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`state` varchar(255) DEFAULT NULL COMMENT 'The gpts state', |
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`max_auto_reply_round` int(11) NOT NULL COMMENT 'max auto reply round', |
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`auto_reply_count` int(11) NOT NULL COMMENT 'auto reply count', |
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`user_code` varchar(255) DEFAULT NULL COMMENT 'user code', |
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`sys_code` varchar(255) DEFAULT NULL COMMENT 'system app ', |
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`created_at` datetime DEFAULT NULL COMMENT 'create time', |
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`updated_at` datetime DEFAULT NULL COMMENT 'last update time', |
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`team_mode` varchar(255) NULL COMMENT 'agent team work mode', |
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PRIMARY KEY (`id`), |
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UNIQUE KEY `uk_gpts_conversations` (`conv_id`), |
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KEY `idx_gpts_name` (`gpts_name`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT="gpt conversations"; |
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CREATE TABLE IF NOT EXISTS `gpts_instance` ( |
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`id` int(11) NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`gpts_name` varchar(255) NOT NULL COMMENT 'Current AI assistant name', |
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`gpts_describe` varchar(2255) NOT NULL COMMENT 'Current AI assistant describe', |
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`resource_db` text COMMENT 'List of structured database names contained in the current gpts', |
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`resource_internet` text COMMENT 'Is it possible to retrieve information from the internet', |
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`resource_knowledge` text COMMENT 'List of unstructured database names contained in the current gpts', |
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`gpts_agents` varchar(1000) DEFAULT NULL COMMENT 'List of agents names contained in the current gpts', |
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`gpts_models` varchar(1000) DEFAULT NULL COMMENT 'List of llm model names contained in the current gpts', |
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`language` varchar(100) DEFAULT NULL COMMENT 'gpts language', |
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`user_code` varchar(255) NOT NULL COMMENT 'user code', |
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`sys_code` varchar(255) DEFAULT NULL COMMENT 'system app code', |
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`created_at` datetime DEFAULT NULL COMMENT 'create time', |
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`updated_at` datetime DEFAULT NULL COMMENT 'last update time', |
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`team_mode` varchar(255) NOT NULL COMMENT 'Team work mode', |
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`is_sustainable` tinyint(1) NOT NULL COMMENT 'Applications for sustainable dialogue', |
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PRIMARY KEY (`id`), |
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UNIQUE KEY `uk_gpts` (`gpts_name`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT="gpts instance"; |
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CREATE TABLE `gpts_messages` ( |
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`id` int(11) NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`conv_id` varchar(255) NOT NULL COMMENT 'The unique id of the conversation record', |
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`sender` varchar(255) NOT NULL COMMENT 'Who speaking in the current conversation turn', |
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`receiver` varchar(255) NOT NULL COMMENT 'Who receive message in the current conversation turn', |
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`model_name` varchar(255) DEFAULT NULL COMMENT 'message generate model', |
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`rounds` int(11) NOT NULL COMMENT 'dialogue turns', |
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`content` text COMMENT 'Content of the speech', |
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`current_goal` text COMMENT 'The target corresponding to the current message', |
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`context` text COMMENT 'Current conversation context', |
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`review_info` text COMMENT 'Current conversation review info', |
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`action_report` text COMMENT 'Current conversation action report', |
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`role` varchar(255) DEFAULT NULL COMMENT 'The role of the current message content', |
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`created_at` datetime DEFAULT NULL COMMENT 'create time', |
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`updated_at` datetime DEFAULT NULL COMMENT 'last update time', |
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PRIMARY KEY (`id`), |
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KEY `idx_q_messages` (`conv_id`,`rounds`,`sender`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT="gpts message"; |
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CREATE TABLE `gpts_plans` ( |
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`id` int(11) NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`conv_id` varchar(255) NOT NULL COMMENT 'The unique id of the conversation record', |
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`sub_task_num` int(11) NOT NULL COMMENT 'Subtask number', |
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`sub_task_title` varchar(255) NOT NULL COMMENT 'subtask title', |
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`sub_task_content` text NOT NULL COMMENT 'subtask content', |
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`sub_task_agent` varchar(255) DEFAULT NULL COMMENT 'Available agents corresponding to subtasks', |
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`resource_name` varchar(255) DEFAULT NULL COMMENT 'resource name', |
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`rely` varchar(255) DEFAULT NULL COMMENT 'Subtask dependencies，like: 1,2,3', |
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`agent_model` varchar(255) DEFAULT NULL COMMENT 'LLM model used by subtask processing agents', |
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`retry_times` int(11) DEFAULT NULL COMMENT 'number of retries', |
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`max_retry_times` int(11) DEFAULT NULL COMMENT 'Maximum number of retries', |
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`state` varchar(255) DEFAULT NULL COMMENT 'subtask status', |
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`result` longtext COMMENT 'subtask result', |
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`created_at` datetime DEFAULT NULL COMMENT 'create time', |
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`updated_at` datetime DEFAULT NULL COMMENT 'last update time', |
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PRIMARY KEY (`id`), |
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UNIQUE KEY `uk_sub_task` (`conv_id`,`sub_task_num`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT="gpt plan"; |
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|
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-- dbgpt.dbgpt_serve_flow definition |
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CREATE TABLE `dbgpt_serve_flow` ( |
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`id` int NOT NULL AUTO_INCREMENT COMMENT 'Auto increment id', |
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`uid` varchar(128) NOT NULL COMMENT 'Unique id', |
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`dag_id` varchar(128) DEFAULT NULL COMMENT 'DAG id', |
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`name` varchar(128) DEFAULT NULL COMMENT 'Flow name', |
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`flow_data` text COMMENT 'Flow data, JSON format', |
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`user_name` varchar(128) DEFAULT NULL COMMENT 'User name', |
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`sys_code` varchar(128) DEFAULT NULL COMMENT 'System code', |
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`gmt_created` datetime DEFAULT NULL COMMENT 'Record creation time', |
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`gmt_modified` datetime DEFAULT NULL COMMENT 'Record update time', |
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`flow_category` varchar(64) DEFAULT NULL COMMENT 'Flow category', |
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`description` varchar(512) DEFAULT NULL COMMENT 'Flow description', |
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`state` varchar(32) DEFAULT NULL COMMENT 'Flow state', |
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`error_message` varchar(512) NULL comment 'Error message', |
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`source` varchar(64) DEFAULT NULL COMMENT 'Flow source', |
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`source_url` varchar(512) DEFAULT NULL COMMENT 'Flow source url', |
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`version` varchar(32) DEFAULT NULL COMMENT 'Flow version', |
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`define_type` varchar(32) null comment 'Flow define type(json or python)', |
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`label` varchar(128) DEFAULT NULL COMMENT 'Flow label', |
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`editable` int DEFAULT NULL COMMENT 'Editable, 0: editable, 1: not editable', |
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PRIMARY KEY (`id`), |
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UNIQUE KEY `uk_uid` (`uid`), |
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KEY `ix_dbgpt_serve_flow_sys_code` (`sys_code`), |
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KEY `ix_dbgpt_serve_flow_uid` (`uid`), |
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KEY `ix_dbgpt_serve_flow_dag_id` (`dag_id`), |
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KEY `ix_dbgpt_serve_flow_user_name` (`user_name`), |
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KEY `ix_dbgpt_serve_flow_name` (`name`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci; |
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|
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-- dbgpt.gpts_app definition |
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CREATE TABLE `gpts_app` ( |
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`id` int NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`app_code` varchar(255) NOT NULL COMMENT 'Current AI assistant code', |
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`app_name` varchar(255) NOT NULL COMMENT 'Current AI assistant name', |
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`app_describe` varchar(2255) NOT NULL COMMENT 'Current AI assistant describe', |
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`language` varchar(100) NOT NULL COMMENT 'gpts language', |
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`team_mode` varchar(255) NOT NULL COMMENT 'Team work mode', |
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`team_context` text COMMENT 'The execution logic and team member content that teams with different working modes rely on', |
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`user_code` varchar(255) DEFAULT NULL COMMENT 'user code', |
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`sys_code` varchar(255) DEFAULT NULL COMMENT 'system app code', |
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`created_at` datetime DEFAULT NULL COMMENT 'create time', |
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`updated_at` datetime DEFAULT NULL COMMENT 'last update time', |
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`icon` varchar(1024) DEFAULT NULL COMMENT 'app icon, url', |
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PRIMARY KEY (`id`), |
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UNIQUE KEY `uk_gpts_app` (`app_name`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci; |
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CREATE TABLE `gpts_app_collection` ( |
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`id` int(11) NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`app_code` varchar(255) NOT NULL COMMENT 'Current AI assistant code', |
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`user_code` int(11) NOT NULL COMMENT 'user code', |
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`sys_code` varchar(255) NOT NULL COMMENT 'system app code', |
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`created_at` datetime DEFAULT NULL COMMENT 'create time', |
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`updated_at` datetime DEFAULT NULL COMMENT 'last update time', |
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PRIMARY KEY (`id`), |
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KEY `idx_app_code` (`app_code`), |
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KEY `idx_user_code` (`user_code`) |
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) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT="gpt collections"; |
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|
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-- dbgpt.gpts_app_detail definition |
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CREATE TABLE `gpts_app_detail` ( |
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`id` int NOT NULL AUTO_INCREMENT COMMENT 'autoincrement id', |
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`app_code` varchar(255) NOT NULL COMMENT 'Current AI assistant code', |
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`app_name` varchar(255) NOT NULL COMMENT 'Current AI assistant name', |
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`agent_name` varchar(255) NOT NULL COMMENT ' Agent name', |
||||
`node_id` varchar(255) NOT NULL COMMENT 'Current AI assistant Agent Node id', |
||||
`resources` text COMMENT 'Agent bind resource', |
||||
`prompt_template` text COMMENT 'Agent bind template', |
||||
`llm_strategy` varchar(25) DEFAULT NULL COMMENT 'Agent use llm strategy', |
||||
`llm_strategy_value` text COMMENT 'Agent use llm strategy value', |
||||
`created_at` datetime DEFAULT NULL COMMENT 'create time', |
||||
`updated_at` datetime DEFAULT NULL COMMENT 'last update time', |
||||
PRIMARY KEY (`id`), |
||||
UNIQUE KEY `uk_gpts_app_agent_node` (`app_name`,`agent_name`,`node_id`) |
||||
) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_unicode_ci; |
||||
|
||||
CREATE |
||||
DATABASE IF NOT EXISTS EXAMPLE_1; |
||||
use EXAMPLE_1; |
||||
CREATE TABLE IF NOT EXISTS `users` |
||||
( |
||||
`id` int NOT NULL AUTO_INCREMENT, |
||||
`username` varchar(50) NOT NULL COMMENT '用户名', |
||||
`password` varchar(50) NOT NULL COMMENT '密码', |
||||
`email` varchar(50) NOT NULL COMMENT '邮箱', |
||||
`phone` varchar(20) DEFAULT NULL COMMENT '电话', |
||||
PRIMARY KEY (`id`), |
||||
KEY `idx_username` (`username`) COMMENT '索引：按用户名查询' |
||||
) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT='聊天用户表'; |
||||
|
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_1', 'password_1', 'user_1@example.com', '12345678901'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_2', 'password_2', 'user_2@example.com', '12345678902'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_3', 'password_3', 'user_3@example.com', '12345678903'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_4', 'password_4', 'user_4@example.com', '12345678904'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_5', 'password_5', 'user_5@example.com', '12345678905'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_6', 'password_6', 'user_6@example.com', '12345678906'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_7', 'password_7', 'user_7@example.com', '12345678907'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_8', 'password_8', 'user_8@example.com', '12345678908'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_9', 'password_9', 'user_9@example.com', '12345678909'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_10', 'password_10', 'user_10@example.com', '12345678900'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_11', 'password_11', 'user_11@example.com', '12345678901'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_12', 'password_12', 'user_12@example.com', '12345678902'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_13', 'password_13', 'user_13@example.com', '12345678903'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_14', 'password_14', 'user_14@example.com', '12345678904'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_15', 'password_15', 'user_15@example.com', '12345678905'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_16', 'password_16', 'user_16@example.com', '12345678906'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_17', 'password_17', 'user_17@example.com', '12345678907'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_18', 'password_18', 'user_18@example.com', '12345678908'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_19', 'password_19', 'user_19@example.com', '12345678909'); |
||||
INSERT INTO users (username, password, email, phone) |
||||
VALUES ('user_20', 'password_20', 'user_20@example.com', '12345678900'); |
||||
|
Before Width: | Height: | Size: 118 KiB After Width: | Height: | Size: 118 KiB |
@ -1 +1 @@ |
||||
version = "0.5.9" |
||||
version = "0.5.10" |
||||
|
||||
@ -1,29 +0,0 @@ |
||||
from typing import Dict |
||||
|
||||
from dbgpt.app.scene import BaseChat, ChatScene |
||||
|
||||
|
||||
class ExtractEntity(BaseChat): |
||||
chat_scene: str = ChatScene.ExtractEntity.value() |
||||
|
||||
"""extracting entities by llm""" |
||||
|
||||
def __init__(self, chat_param: Dict): |
||||
""" """ |
||||
chat_param["chat_mode"] = ChatScene.ExtractEntity |
||||
super().__init__( |
||||
chat_param=chat_param, |
||||
) |
||||
|
||||
self.user_input = chat_param["current_user_input"] |
||||
self.extract_mode = chat_param["select_param"] |
||||
|
||||
async def generate_input_values(self): |
||||
input_values = { |
||||
"text": self.user_input, |
||||
} |
||||
return input_values |
||||
|
||||
@property |
||||
def chat_type(self) -> str: |
||||
return ChatScene.ExtractEntity.value |
||||
@ -1,34 +0,0 @@ |
||||
import logging |
||||
from typing import Set |
||||
|
||||
from dbgpt.core.interface.output_parser import BaseOutputParser |
||||
|
||||
logger = logging.getLogger(__name__) |
||||
|
||||
|
||||
class ExtractEntityParser(BaseOutputParser): |
||||
def __init__(self, is_stream_out: bool, **kwargs): |
||||
super().__init__(is_stream_out=is_stream_out, **kwargs) |
||||
|
||||
def parse_prompt_response(self, response, max_length: int = 128) -> Set[str]: |
||||
lowercase = True |
||||
# clean_str = super().parse_prompt_response(response) |
||||
print("clean prompt response:", response) |
||||
|
||||
results = [] |
||||
response = response.strip() # Strip newlines from responses. |
||||
|
||||
if response.startswith("KEYWORDS:"): |
||||
response = response[len("KEYWORDS:") :] |
||||
|
||||
keywords = response.split(",") |
||||
for k in keywords: |
||||
rk = k |
||||
if lowercase: |
||||
rk = rk.lower() |
||||
results.append(rk.strip()) |
||||
|
||||
return set(results) |
||||
|
||||
def parse_view_response(self, speak, data) -> str: |
||||
return data |
||||
@ -1,41 +0,0 @@ |
||||
from dbgpt._private.config import Config |
||||
from dbgpt.app.scene import AppScenePromptTemplateAdapter, ChatScene |
||||
from dbgpt.app.scene.chat_knowledge.extract_entity.out_parser import ExtractEntityParser |
||||
from dbgpt.core import ChatPromptTemplate, HumanPromptTemplate |
||||
|
||||
CFG = Config() |
||||
|
||||
PROMPT_SCENE_DEFINE = """""" |
||||
|
||||
_DEFAULT_TEMPLATE = """ |
||||
"A question is provided below. Given the question, extract up to 10 " |
||||
"keywords from the text. Focus on extracting the keywords that we can use " |
||||
"to best lookup answers to the question. Avoid stopwords.\n" |
||||
"Example:" |
||||
"Text: Alice is Bob's mother." |
||||
"KEYWORDS:Alice,mother,Bob\n" |
||||
"---------------------\n" |
||||
"{text}\n" |
||||
"---------------------\n" |
||||
"Provide keywords in the following comma-separated format: 'KEYWORDS: <keywords>'\n" |
||||
""" |
||||
PROMPT_RESPONSE = """""" |
||||
|
||||
PROMPT_NEED_NEED_STREAM_OUT = False |
||||
|
||||
prompt = ChatPromptTemplate( |
||||
messages=[ |
||||
# SystemPromptTemplate.from_template(PROMPT_SCENE_DEFINE), |
||||
HumanPromptTemplate.from_template(_DEFAULT_TEMPLATE + PROMPT_RESPONSE), |
||||
] |
||||
) |
||||
|
||||
prompt_adapter = AppScenePromptTemplateAdapter( |
||||
prompt=prompt, |
||||
template_scene=ChatScene.ExtractEntity.value(), |
||||
stream_out=PROMPT_NEED_NEED_STREAM_OUT, |
||||
output_parser=ExtractEntityParser(is_stream_out=PROMPT_NEED_NEED_STREAM_OUT), |
||||
need_historical_messages=False, |
||||
) |
||||
|
||||
CFG.prompt_template_registry.register(prompt_adapter, is_default=True) |
||||
@ -1,29 +0,0 @@ |
||||
from typing import Dict |
||||
|
||||
from dbgpt.app.scene import BaseChat, ChatScene |
||||
|
||||
|
||||
class ExtractTriplet(BaseChat): |
||||
chat_scene: str = ChatScene.ExtractTriplet.value() |
||||
|
||||
"""extracting triplets by llm""" |
||||
|
||||
def __init__(self, chat_param: Dict): |
||||
""" """ |
||||
chat_param["chat_mode"] = ChatScene.ExtractTriplet |
||||
super().__init__( |
||||
chat_param=chat_param, |
||||
) |
||||
|
||||
self.user_input = chat_param["current_user_input"] |
||||
self.extract_mode = chat_param["select_param"] |
||||
|
||||
async def generate_input_values(self): |
||||
input_values = { |
||||
"text": self.user_input, |
||||
} |
||||
return input_values |
||||
|
||||
@property |
||||
def chat_type(self) -> str: |
||||
return ChatScene.ExtractTriplet.value |
||||
@ -1,52 +0,0 @@ |
||||
import logging |
||||
import re |
||||
from typing import List, Tuple |
||||
|
||||
from dbgpt.core.interface.output_parser import BaseOutputParser |
||||
|
||||
logger = logging.getLogger(__name__) |
||||
|
||||
|
||||
class ExtractTripleParser(BaseOutputParser): |
||||
def __init__(self, is_stream_out: bool, **kwargs): |
||||
super().__init__(is_stream_out=is_stream_out, **kwargs) |
||||
|
||||
def parse_prompt_response( |
||||
self, response, max_length: int = 128 |
||||
) -> List[Tuple[str, str, str]]: |
||||
# clean_str = super().parse_prompt_response(response) |
||||
print("clean prompt response:", response) |
||||
|
||||
if response.startswith("Triplets:"): |
||||
response = response[len("Triplets:") :] |
||||
pattern = r"\([^()]+\)" |
||||
response = re.findall(pattern, response) |
||||
# response = response.strip().split("\n") |
||||
print("parse prompt response:", response) |
||||
results = [] |
||||
for text in response: |
||||
if not text or text[0] != "(" or text[-1] != ")": |
||||
# skip empty lines and non-triplets |
||||
continue |
||||
tokens = text[1:-1].split(",") |
||||
if len(tokens) != 3: |
||||
continue |
||||
|
||||
if any(len(s.encode("utf-8")) > max_length for s in tokens): |
||||
# We count byte-length instead of len() for UTF-8 chars, |
||||
# will skip if any of the tokens are too long. |
||||
# This is normally due to a poorly formatted triplet |
||||
# extraction, in more serious KG building cases |
||||
# we'll need NLP models to better extract triplets. |
||||
continue |
||||
|
||||
subject, predicate, obj = map(str.strip, tokens) |
||||
if not subject or not predicate or not obj: |
||||
# skip partial triplets |
||||
continue |
||||
results.append((subject.lower(), predicate.lower(), obj.lower())) |
||||
return results |
||||
|
||||
def parse_view_response(self, speak, data) -> str: |
||||
### tool out data to table view |
||||
return data |
||||
@ -1,51 +0,0 @@ |
||||
from dbgpt._private.config import Config |
||||
from dbgpt.app.scene import AppScenePromptTemplateAdapter, ChatScene |
||||
from dbgpt.app.scene.chat_knowledge.extract_triplet.out_parser import ( |
||||
ExtractTripleParser, |
||||
) |
||||
from dbgpt.core import ChatPromptTemplate, HumanPromptTemplate |
||||
|
||||
CFG = Config() |
||||
|
||||
PROMPT_SCENE_DEFINE = """""" |
||||
|
||||
_DEFAULT_TEMPLATE = """ |
||||
"Some text is provided below. Given the text, extract up to 10" |
||||
"knowledge triplets in the form of (subject, predicate, object). Avoid stopwords.\n" |
||||
"---------------------\n" |
||||
"Example:" |
||||
"Text: Alice is Bob's mother." |
||||
"Triplets:\n(Alice, is mother of, Bob)\n" |
||||
"Text: Philz is a coffee shop founded in Berkeley in 1982.\n" |
||||
"Triplets:\n" |
||||
"(Philz, is, coffee shop)\n" |
||||
"(Philz, founded in, Berkeley)\n" |
||||
"(Philz, founded in, 1982)\n" |
||||
"---------------------\n" |
||||
"Text: {text}\n" |
||||
"Triplets:\n" |
||||
ensure Respond in the following List(Tuple) format: |
||||
'(Stephen Curry, plays for, Golden State Warriors)\n(Stephen Curry, known for, shooting skills)\n(Stephen Curry, attended, Davidson College)\n(Stephen Curry, led, team to success)' |
||||
""" |
||||
PROMPT_RESPONSE = """""" |
||||
|
||||
|
||||
PROMPT_NEED_NEED_STREAM_OUT = False |
||||
|
||||
|
||||
prompt = ChatPromptTemplate( |
||||
messages=[ |
||||
# SystemPromptTemplate.from_template(PROMPT_SCENE_DEFINE), |
||||
HumanPromptTemplate.from_template(_DEFAULT_TEMPLATE + PROMPT_RESPONSE), |
||||
] |
||||
) |
||||
|
||||
prompt_adapter = AppScenePromptTemplateAdapter( |
||||
prompt=prompt, |
||||
template_scene=ChatScene.ExtractTriplet.value(), |
||||
stream_out=PROMPT_NEED_NEED_STREAM_OUT, |
||||
output_parser=ExtractTripleParser(is_stream_out=PROMPT_NEED_NEED_STREAM_OUT), |
||||
need_historical_messages=False, |
||||
) |
||||
|
||||
CFG.prompt_template_registry.register(prompt_adapter, is_default=True) |
||||
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@ -1,4 +1,4 @@ |
||||
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Reference in new issue