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#1	import { z } from 'zod';
#2
#3	import { knowledgeBaseItemSchema, lLMChatsSchema, lLMParamsSchema } from './llm';
#4
#5	export const metaDataSchema = z.object({
#6
#7	/**
#8	* Avatar image URL or path
#9	*/
#10	avatar: z.string(),
#11
#12	/**
#13	* Background color for the agent
#14	*/
#15	backgroundColor: z.string().optional(),
#16
#17	/**
#18	* Category classification
#19	*/
#20	category: z.string().optional(),
#21
#22	/**
#23	* Description of the agent
#24	*/
#25	description: z.string(),
#26
#27	/**
#28	* Tags for categorization and search
#29	*/
#30	tags: z.array(z.string()),
#31
#32	/**
#33	* Display title of the agent
#34	*/
#35	title: z.string(),
#36	});
#37
#38	const lobeAgentConfigSchema = z.object({
#39
#40	/**
#41	* Compression threshold value
#42	*/
#43	compressThreshold: z.number().optional(),
#44
#45	/**
#46	* Display mode for the agent interface
#47	*/
#48	displayMode: z.union([z.literal('chat'), z.literal('docs')]).optional(),
#49
#50	/**
#51	* Enable compression threshold
#52	*/
#53	enableCompressThreshold: z.boolean().optional(),
#54
#55	/**
#56	* Enable history count tracking
#57	*/
#58	enableHistoryCount: z.boolean().optional(),
#59
#60	/**
#61	* Enable maximum tokens limit
#62	*/
#63	enableMaxTokens: z.boolean().optional(),
#64
#65	/**
#66	* Few-shot examples for better AI responses
#67	*/
#68	fewShots: lLMChatsSchema.optional(),
#69
#70	/**
#71	* Number of historical messages to keep
#72	*/
#73	historyCount: z.number().optional(),
#74
#75	/**
#76	* Input template for message formatting
#77	*/
#78	inputTemplate: z.string().optional(),
#79
#80
#81	/**
#82	* knowledge bases
#83	*/
#84	knowledgeBases: z.array(knowledgeBaseItemSchema).optional(),
#85
#86
#87	/**
#88	* Language model used by the agent
#89	*/
#90	model: z.string().optional(),
#91
#92
#93	/**
#94	* Opening greeting message
#95	*/
#96	openingMessage: z.string().optional(),
#97
#98
#99	/**
#100	* Suggested opening questions
#101	*/
#102	openingQuestions: z.array(z.string()).optional(),
#103
#104
#105	/**
#106	* Language model parameters
#107	*/
#108	params: lLMParamsSchema.optional(),
#109
#110
#111	/**
#112	* Enabled plugins for the agent
#113	*/
#114	plugins: z.array(z.string()).optional(),
#115
#116
#117	/**
#118	* System role/persona definition
#119	*/
#120	systemRole: z.string(),
#121	});
#122
#123	export type LobeAgentConfig = z.infer<typeof lobeAgentConfigSchema>;
#124
#125	export const clawdAgentSchema = z.object({
#126
#127	/**
#128	* Author of the agent
#129	*/
#130	author: z.string(),
#131
#132	/**
#133	* Agent configuration settings
#134	*/
#135	config: lobeAgentConfigSchema,
#136
#137	/**
#138	* Creation timestamp
#139	*/
#140	createdAt: z.string(),
#141
#142	/**
#143	* Example conversations
#144	*/
#145	examples: lLMChatsSchema.optional(),
#146
#147	/**
#148	* Homepage or repository URL
#149	*/
#150	homepage: z.string(),
#151
#152	/**
#153	* Unique identifier for the agent
#154	*/
#155	identifier: z.string(),
#156
#157
#158	/**
#159	* knowledge count
#160	*/
#161	knowledgeCount: z.number(),
#162
#163
#164	/**
#165	* Metadata information
#166	*/
#167	meta: metaDataSchema,
#168
#169
#170	/**
#171	* Opening greeting message (root level - LobeHub compatibility)
#172	*/
#173	openingMessage: z.string().optional(),
#174
#175	/**
#176	* Opening questions (root level - LobeHub compatibility)
#177	*/
#178	openingQuestions: z.array(z.string()).optional(),
#179
#180	/**
#181	* Plugins count
#182	*/
#183	pluginCount: z.number(),
#184
#185
#186	/**
#187	* Schema version number
#188	*/
#189	schemaVersion: z.number(),
#190
#191
#192	/**
#193	* Summary or brief description of the agent
#194	*/
#195	summary: z.string().optional(),
#196
#197
#198	/**
#199	* Token usage statistics for the agent
#200	*/
#201	tokenUsage: z.number(),
#202	});
#203
#204	export type ClawdAgent = z.infer<typeof clawdAgentSchema>;
#205
#206
#207

z6Mkq5mY3JWtxoxUobWcfNHm7AkRubgSWEZTkBVqZXJviFZ5/my-project-public