import { InputVarType } from '@/app/components/workflow/types'; import { PromptRole } from '@/models/debug'; import { PipelineInputVarType } from '@/models/pipeline'; import { AgentStrategy } from '@/types/app'; import { DatasetAttr } from '@/types/feature'; import pkg from '../package.json'; const getBooleanConfig = ( envVar: string | undefined, dataAttrKey: DatasetAttr, defaultValue: boolean = true, ) => { if (envVar !== undefined && envVar !== '') return envVar === 'true'; const attrValue = globalThis.document?.body?.getAttribute(dataAttrKey); if (attrValue !== undefined && attrValue !== '') return attrValue === 'true'; return defaultValue; }; const getNumberConfig = ( envVar: string | undefined, dataAttrKey: DatasetAttr, defaultValue: number, ) => { if (envVar) { const parsed = Number.parseInt(envVar); if (!Number.isNaN(parsed) && parsed > 0) return parsed; } const attrValue = globalThis.document?.body?.getAttribute(dataAttrKey); if (attrValue) { const parsed = Number.parseInt(attrValue); if (!Number.isNaN(parsed) && parsed > 0) return parsed; } return defaultValue; }; const getStringConfig = ( envVar: string | undefined, dataAttrKey: DatasetAttr, defaultValue: string, ) => { if (envVar) return envVar; const attrValue = globalThis.document?.body?.getAttribute(dataAttrKey); if (attrValue) return attrValue; return defaultValue; }; export const API_PREFIX = getStringConfig( process.env.NEXT_PUBLIC_API_PREFIX, DatasetAttr.DATA_API_PREFIX, 'http://localhost:5001/console/api', ); export const PUBLIC_API_PREFIX = getStringConfig( process.env.NEXT_PUBLIC_PUBLIC_API_PREFIX, DatasetAttr.DATA_PUBLIC_API_PREFIX, 'http://localhost:5001/api', ); export const MARKETPLACE_API_PREFIX = getStringConfig( process.env.NEXT_PUBLIC_MARKETPLACE_API_PREFIX, DatasetAttr.DATA_MARKETPLACE_API_PREFIX, 'http://localhost:5002/api', ); export const MARKETPLACE_URL_PREFIX = getStringConfig( process.env.NEXT_PUBLIC_MARKETPLACE_URL_PREFIX, DatasetAttr.DATA_MARKETPLACE_URL_PREFIX, '', ); const EDITION = getStringConfig( process.env.NEXT_PUBLIC_EDITION, DatasetAttr.DATA_PUBLIC_EDITION, 'SELF_HOSTED', ); export const IS_CE_EDITION = EDITION === 'SELF_HOSTED'; export const IS_CLOUD_EDITION = EDITION === 'CLOUD'; export const SUPPORT_MAIL_LOGIN = !!( process.env.NEXT_PUBLIC_SUPPORT_MAIL_LOGIN || globalThis.document?.body?.getAttribute('data-public-support-mail-login') ); export const TONE_LIST = [ { id: 1, name: 'Creative', config: { temperature: 0.8, top_p: 0.9, presence_penalty: 0.1, frequency_penalty: 0.1, }, }, { id: 2, name: 'Balanced', config: { temperature: 0.5, top_p: 0.85, presence_penalty: 0.2, frequency_penalty: 0.3, }, }, { id: 3, name: 'Precise', config: { temperature: 0.2, top_p: 0.75, presence_penalty: 0.5, frequency_penalty: 0.5, }, }, { id: 4, name: 'Custom', }, ]; export const DEFAULT_CHAT_PROMPT_CONFIG = { prompt: [ { role: PromptRole.system, text: '', }, ], }; export const DEFAULT_COMPLETION_PROMPT_CONFIG = { prompt: { text: '', }, conversation_histories_role: { user_prefix: '', assistant_prefix: '', }, }; export const getMaxToken = (modelId: string) => { return modelId === 'gpt-4' || modelId === 'gpt-3.5-turbo-16k' ? 8000 : 4000; }; export const LOCALE_COOKIE_NAME = 'locale'; export const DEFAULT_VALUE_MAX_LEN = 48; export const DEFAULT_PARAGRAPH_VALUE_MAX_LEN = 1000; export const zhRegex = /^[\u4E00-\u9FA5]$/m; export const emojiRegex = /^[\uD800-\uDBFF][\uDC00-\uDFFF]$/m; export const emailRegex = /^[\w.!#$%&'*+\-/=?^{|}~]+@([\w-]+\.)+[\w-]{2,}$/m; const MAX_ZN_VAR_NAME_LENGTH = 8; const MAX_EN_VAR_VALUE_LENGTH = 30; export const getMaxVarNameLength = (value: string) => { if (zhRegex.test(value)) return MAX_ZN_VAR_NAME_LENGTH; return MAX_EN_VAR_VALUE_LENGTH; }; export const MAX_VAR_KEY_LENGTH = 30; export const MAX_PROMPT_MESSAGE_LENGTH = 10; export const VAR_ITEM_TEMPLATE = { key: '', name: '', type: 'string', max_length: DEFAULT_VALUE_MAX_LEN, required: true, }; export const VAR_ITEM_TEMPLATE_IN_WORKFLOW = { variable: '', label: '', type: InputVarType.textInput, max_length: DEFAULT_VALUE_MAX_LEN, required: true, options: [], }; export const VAR_ITEM_TEMPLATE_IN_PIPELINE = { variable: '', label: '', type: PipelineInputVarType.textInput, max_length: DEFAULT_VALUE_MAX_LEN, required: true, options: [], }; export const appDefaultIconBackground = '#D5F5F6'; export const NEED_REFRESH_APP_LIST_KEY = 'needRefreshAppList'; export const DATASET_DEFAULT = { top_k: 4, score_threshold: 0.8, }; export const APP_PAGE_LIMIT = 10; export const ANNOTATION_DEFAULT = { score_threshold: 0.9, }; export const DEFAULT_AGENT_SETTING = { enabled: false, max_iteration: 10, strategy: AgentStrategy.functionCall, tools: [], }; export const DEFAULT_AGENT_PROMPT = { chat: `Respond to the human as helpfully and accurately as possible. {{instruction}} You have access to the following tools: {{tools}} Use a json blob to specify a tool by providing an {{TOOL_NAME_KEY}} key (tool name) and an {{ACTION_INPUT_KEY}} key (tool input). Valid "{{TOOL_NAME_KEY}}" values: "Final Answer" or {{tool_names}} Provide only ONE action per $JSON_BLOB, as shown: \`\`\` { "{{TOOL_NAME_KEY}}": $TOOL_NAME, "{{ACTION_INPUT_KEY}}": $ACTION_INPUT } \`\`\` Follow this format: Question: input question to answer Thought: consider previous and subsequent steps Action: \`\`\` $JSON_BLOB \`\`\` Observation: action result ... (repeat Thought/Action/Observation N times) Thought: I know what to respond Action: \`\`\` { "{{TOOL_NAME_KEY}}": "Final Answer", "{{ACTION_INPUT_KEY}}": "Final response to human" } \`\`\` Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use tools if necessary. Respond directly if appropriate. Format is Action:\`\`\`$JSON_BLOB\`\`\`then Observation:.`, completion: ` Respond to the human as helpfully and accurately as possible. {{instruction}} You have access to the following tools: {{tools}} Use a json blob to specify a tool by providing an {{TOOL_NAME_KEY}} key (tool name) and an {{ACTION_INPUT_KEY}} key (tool input). Valid "{{TOOL_NAME_KEY}}" values: "Final Answer" or {{tool_names}} Provide only ONE action per $JSON_BLOB, as shown: \`\`\` {{{{ "{{TOOL_NAME_KEY}}": $TOOL_NAME, "{{ACTION_INPUT_KEY}}": $ACTION_INPUT }}}} \`\`\` Follow this format: Question: input question to answer Thought: consider previous and subsequent steps Action: \`\`\` $JSON_BLOB \`\`\` Observation: action result ... (repeat Thought/Action/Observation N times) Thought: I know what to respond Action: \`\`\` {{{{ "{{TOOL_NAME_KEY}}": "Final Answer", "{{ACTION_INPUT_KEY}}": "Final response to human" }}}} \`\`\` Begin! Reminder to ALWAYS respond with a valid json blob of a single action. Use tools if necessary. Respond directly if appropriate. Format is Action:\`\`\`$JSON_BLOB\`\`\`then Observation:. Question: {{query}} Thought: {{agent_scratchpad}} `, }; export const VAR_REGEX = /\{\{(#[a-zA-Z0-9_-]{1,50}(\.\d+)?(\.[a-zA-Z_]\w{0,29}){1,10}#)\}\}/gi; export const resetReg = () => (VAR_REGEX.lastIndex = 0); export const DISABLE_UPLOAD_IMAGE_AS_ICON = process.env.NEXT_PUBLIC_DISABLE_UPLOAD_IMAGE_AS_ICON === 'true'; export const GITHUB_ACCESS_TOKEN = process.env.NEXT_PUBLIC_GITHUB_ACCESS_TOKEN || ''; export const SUPPORT_INSTALL_LOCAL_FILE_EXTENSIONS = '.difypkg,.difybndl'; export const FULL_DOC_PREVIEW_LENGTH = 50; export const JSON_SCHEMA_MAX_DEPTH = 10; export const MAX_TOOLS_NUM = getNumberConfig( process.env.NEXT_PUBLIC_MAX_TOOLS_NUM, DatasetAttr.DATA_PUBLIC_MAX_TOOLS_NUM, 10, ); export const MAX_PARALLEL_LIMIT = getNumberConfig( process.env.NEXT_PUBLIC_MAX_PARALLEL_LIMIT, DatasetAttr.DATA_PUBLIC_MAX_PARALLEL_LIMIT, 10, ); export const TEXT_GENERATION_TIMEOUT_MS = getNumberConfig( process.env.NEXT_PUBLIC_TEXT_GENERATION_TIMEOUT_MS, DatasetAttr.DATA_PUBLIC_TEXT_GENERATION_TIMEOUT_MS, 60000, ); export const LOOP_NODE_MAX_COUNT = getNumberConfig( process.env.NEXT_PUBLIC_LOOP_NODE_MAX_COUNT, DatasetAttr.DATA_PUBLIC_LOOP_NODE_MAX_COUNT, 100, ); export const MAX_ITERATIONS_NUM = getNumberConfig( process.env.NEXT_PUBLIC_MAX_ITERATIONS_NUM, DatasetAttr.DATA_PUBLIC_MAX_ITERATIONS_NUM, 99, ); export const MAX_TREE_DEPTH = getNumberConfig( process.env.NEXT_PUBLIC_MAX_TREE_DEPTH, DatasetAttr.DATA_PUBLIC_MAX_TREE_DEPTH, 50, ); export const ALLOW_UNSAFE_DATA_SCHEME = getBooleanConfig( process.env.NEXT_PUBLIC_ALLOW_UNSAFE_DATA_SCHEME, DatasetAttr.DATA_PUBLIC_ALLOW_UNSAFE_DATA_SCHEME, false, ); export const ENABLE_WEBSITE_JINAREADER = getBooleanConfig( process.env.NEXT_PUBLIC_ENABLE_WEBSITE_JINAREADER, DatasetAttr.DATA_PUBLIC_ENABLE_WEBSITE_JINAREADER, true, ); export const ENABLE_WEBSITE_FIRECRAWL = getBooleanConfig( process.env.NEXT_PUBLIC_ENABLE_WEBSITE_FIRECRAWL, DatasetAttr.DATA_PUBLIC_ENABLE_WEBSITE_FIRECRAWL, true, ); export const ENABLE_WEBSITE_WATERCRAWL = getBooleanConfig( process.env.NEXT_PUBLIC_ENABLE_WEBSITE_WATERCRAWL, DatasetAttr.DATA_PUBLIC_ENABLE_WEBSITE_WATERCRAWL, false, ); export const VALUE_SELECTOR_DELIMITER = '@@@'; export const validPassword = /^(?=.*[a-zA-Z])(?=.*\d)\S{8,}$/; export const ZENDESK_WIDGET_KEY = getStringConfig( process.env.NEXT_PUBLIC_ZENDESK_WIDGET_KEY, DatasetAttr.NEXT_PUBLIC_ZENDESK_WIDGET_KEY, '', ); export const ZENDESK_FIELD_IDS = { ENVIRONMENT: getStringConfig( process.env.NEXT_PUBLIC_ZENDESK_FIELD_ID_ENVIRONMENT, DatasetAttr.NEXT_PUBLIC_ZENDESK_FIELD_ID_ENVIRONMENT, '', ), VERSION: getStringConfig( process.env.NEXT_PUBLIC_ZENDESK_FIELD_ID_VERSION, DatasetAttr.NEXT_PUBLIC_ZENDESK_FIELD_ID_VERSION, '', ), EMAIL: getStringConfig( process.env.NEXT_PUBLIC_ZENDESK_FIELD_ID_EMAIL, DatasetAttr.NEXT_PUBLIC_ZENDESK_FIELD_ID_EMAIL, '', ), WORKSPACE_ID: getStringConfig( process.env.NEXT_PUBLIC_ZENDESK_FIELD_ID_WORKSPACE_ID, DatasetAttr.NEXT_PUBLIC_ZENDESK_FIELD_ID_WORKSPACE_ID, '', ), PLAN: getStringConfig( process.env.NEXT_PUBLIC_ZENDESK_FIELD_ID_PLAN, DatasetAttr.NEXT_PUBLIC_ZENDESK_FIELD_ID_PLAN, '', ), }; export const APP_VERSION = pkg.version; export const RAG_PIPELINE_PREVIEW_CHUNK_NUM = 20; export const PROVIDER_WITH_PRESET_TONE = [ 'langgenius/openai/openai', 'langgenius/azure_openai/azure_openai', ];