mirror of
https://github.com/Mintplex-Labs/anything-llm.git
synced 2024-11-15 02:50:10 +01:00
d072875e43
* Add piperTTS in-browser text-to-speech * update vite config * Add voice default + change prod public URL * uncheck file * Error handling bump package for better quality and voices * bump package * Remove pre-packed WASM - will not support offline first solution for docker * attach TTSProvider telem
858 lines
20 KiB
JavaScript
858 lines
20 KiB
JavaScript
const KEY_MAPPING = {
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LLMProvider: {
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envKey: "LLM_PROVIDER",
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checks: [isNotEmpty, supportedLLM],
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},
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// OpenAI Settings
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OpenAiKey: {
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envKey: "OPEN_AI_KEY",
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checks: [isNotEmpty, validOpenAIKey],
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},
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OpenAiModelPref: {
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envKey: "OPEN_MODEL_PREF",
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checks: [isNotEmpty],
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},
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// Azure OpenAI Settings
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AzureOpenAiEndpoint: {
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envKey: "AZURE_OPENAI_ENDPOINT",
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checks: [isNotEmpty],
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},
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AzureOpenAiTokenLimit: {
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envKey: "AZURE_OPENAI_TOKEN_LIMIT",
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checks: [validOpenAiTokenLimit],
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},
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AzureOpenAiKey: {
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envKey: "AZURE_OPENAI_KEY",
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checks: [isNotEmpty],
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},
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AzureOpenAiModelPref: {
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envKey: "OPEN_MODEL_PREF",
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checks: [isNotEmpty],
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},
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AzureOpenAiEmbeddingModelPref: {
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envKey: "EMBEDDING_MODEL_PREF",
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checks: [isNotEmpty],
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},
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// Anthropic Settings
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AnthropicApiKey: {
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envKey: "ANTHROPIC_API_KEY",
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checks: [isNotEmpty, validAnthropicApiKey],
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},
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AnthropicModelPref: {
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envKey: "ANTHROPIC_MODEL_PREF",
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checks: [isNotEmpty, validAnthropicModel],
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},
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GeminiLLMApiKey: {
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envKey: "GEMINI_API_KEY",
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checks: [isNotEmpty],
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},
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GeminiLLMModelPref: {
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envKey: "GEMINI_LLM_MODEL_PREF",
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checks: [isNotEmpty, validGeminiModel],
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},
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GeminiSafetySetting: {
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envKey: "GEMINI_SAFETY_SETTING",
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checks: [validGeminiSafetySetting],
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},
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// LMStudio Settings
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LMStudioBasePath: {
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envKey: "LMSTUDIO_BASE_PATH",
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checks: [isNotEmpty, validLLMExternalBasePath, validDockerizedUrl],
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},
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LMStudioModelPref: {
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envKey: "LMSTUDIO_MODEL_PREF",
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checks: [],
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},
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LMStudioTokenLimit: {
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envKey: "LMSTUDIO_MODEL_TOKEN_LIMIT",
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checks: [nonZero],
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},
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// LocalAI Settings
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LocalAiBasePath: {
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envKey: "LOCAL_AI_BASE_PATH",
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checks: [isNotEmpty, validLLMExternalBasePath, validDockerizedUrl],
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},
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LocalAiModelPref: {
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envKey: "LOCAL_AI_MODEL_PREF",
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checks: [],
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},
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LocalAiTokenLimit: {
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envKey: "LOCAL_AI_MODEL_TOKEN_LIMIT",
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checks: [nonZero],
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},
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LocalAiApiKey: {
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envKey: "LOCAL_AI_API_KEY",
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checks: [],
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},
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OllamaLLMBasePath: {
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envKey: "OLLAMA_BASE_PATH",
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checks: [isNotEmpty, validOllamaLLMBasePath, validDockerizedUrl],
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},
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OllamaLLMModelPref: {
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envKey: "OLLAMA_MODEL_PREF",
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checks: [],
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},
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OllamaLLMTokenLimit: {
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envKey: "OLLAMA_MODEL_TOKEN_LIMIT",
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checks: [nonZero],
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},
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OllamaLLMPerformanceMode: {
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envKey: "OLLAMA_PERFORMANCE_MODE",
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checks: [],
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},
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OllamaLLMKeepAliveSeconds: {
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envKey: "OLLAMA_KEEP_ALIVE_TIMEOUT",
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checks: [isInteger],
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},
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// Mistral AI API Settings
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MistralApiKey: {
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envKey: "MISTRAL_API_KEY",
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checks: [isNotEmpty],
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},
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MistralModelPref: {
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envKey: "MISTRAL_MODEL_PREF",
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checks: [isNotEmpty],
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},
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// Native LLM Settings
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NativeLLMModelPref: {
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envKey: "NATIVE_LLM_MODEL_PREF",
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checks: [isDownloadedModel],
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},
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NativeLLMTokenLimit: {
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envKey: "NATIVE_LLM_MODEL_TOKEN_LIMIT",
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checks: [nonZero],
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},
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// Hugging Face LLM Inference Settings
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HuggingFaceLLMEndpoint: {
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envKey: "HUGGING_FACE_LLM_ENDPOINT",
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checks: [isNotEmpty, isValidURL, validHuggingFaceEndpoint],
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},
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HuggingFaceLLMAccessToken: {
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envKey: "HUGGING_FACE_LLM_API_KEY",
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checks: [isNotEmpty],
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},
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HuggingFaceLLMTokenLimit: {
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envKey: "HUGGING_FACE_LLM_TOKEN_LIMIT",
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checks: [nonZero],
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},
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// KoboldCPP Settings
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KoboldCPPBasePath: {
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envKey: "KOBOLD_CPP_BASE_PATH",
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checks: [isNotEmpty, isValidURL],
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},
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KoboldCPPModelPref: {
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envKey: "KOBOLD_CPP_MODEL_PREF",
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checks: [isNotEmpty],
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},
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KoboldCPPTokenLimit: {
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envKey: "KOBOLD_CPP_MODEL_TOKEN_LIMIT",
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checks: [nonZero],
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},
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// Text Generation Web UI Settings
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TextGenWebUIBasePath: {
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envKey: "TEXT_GEN_WEB_UI_BASE_PATH",
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checks: [isValidURL],
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},
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TextGenWebUITokenLimit: {
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envKey: "TEXT_GEN_WEB_UI_MODEL_TOKEN_LIMIT",
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checks: [nonZero],
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},
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TextGenWebUIAPIKey: {
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envKey: "TEXT_GEN_WEB_UI_API_KEY",
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checks: [],
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},
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// LiteLLM Settings
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LiteLLMModelPref: {
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envKey: "LITE_LLM_MODEL_PREF",
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checks: [isNotEmpty],
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},
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LiteLLMTokenLimit: {
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envKey: "LITE_LLM_MODEL_TOKEN_LIMIT",
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checks: [nonZero],
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},
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LiteLLMBasePath: {
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envKey: "LITE_LLM_BASE_PATH",
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checks: [isValidURL],
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},
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LiteLLMApiKey: {
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envKey: "LITE_LLM_API_KEY",
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checks: [],
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},
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// Generic OpenAI InferenceSettings
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GenericOpenAiBasePath: {
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envKey: "GENERIC_OPEN_AI_BASE_PATH",
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checks: [isValidURL],
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},
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GenericOpenAiModelPref: {
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envKey: "GENERIC_OPEN_AI_MODEL_PREF",
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checks: [isNotEmpty],
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},
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GenericOpenAiTokenLimit: {
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envKey: "GENERIC_OPEN_AI_MODEL_TOKEN_LIMIT",
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checks: [nonZero],
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},
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GenericOpenAiKey: {
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envKey: "GENERIC_OPEN_AI_API_KEY",
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checks: [],
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},
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GenericOpenAiMaxTokens: {
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envKey: "GENERIC_OPEN_AI_MAX_TOKENS",
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checks: [nonZero],
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},
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// AWS Bedrock LLM InferenceSettings
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AwsBedrockLLMAccessKeyId: {
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envKey: "AWS_BEDROCK_LLM_ACCESS_KEY_ID",
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checks: [isNotEmpty],
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},
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AwsBedrockLLMAccessKey: {
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envKey: "AWS_BEDROCK_LLM_ACCESS_KEY",
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checks: [isNotEmpty],
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},
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AwsBedrockLLMRegion: {
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envKey: "AWS_BEDROCK_LLM_REGION",
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checks: [isNotEmpty],
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},
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AwsBedrockLLMModel: {
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envKey: "AWS_BEDROCK_LLM_MODEL_PREFERENCE",
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checks: [isNotEmpty],
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},
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AwsBedrockLLMTokenLimit: {
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envKey: "AWS_BEDROCK_LLM_MODEL_TOKEN_LIMIT",
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checks: [nonZero],
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},
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EmbeddingEngine: {
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envKey: "EMBEDDING_ENGINE",
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checks: [supportedEmbeddingModel],
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},
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EmbeddingBasePath: {
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envKey: "EMBEDDING_BASE_PATH",
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checks: [isNotEmpty, validDockerizedUrl],
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},
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EmbeddingModelPref: {
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envKey: "EMBEDDING_MODEL_PREF",
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checks: [isNotEmpty],
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},
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EmbeddingModelMaxChunkLength: {
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envKey: "EMBEDDING_MODEL_MAX_CHUNK_LENGTH",
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checks: [nonZero],
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},
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// Generic OpenAI Embedding Settings
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GenericOpenAiEmbeddingApiKey: {
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envKey: "GENERIC_OPEN_AI_EMBEDDING_API_KEY",
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checks: [],
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},
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// Vector Database Selection Settings
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VectorDB: {
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envKey: "VECTOR_DB",
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checks: [isNotEmpty, supportedVectorDB],
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},
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// Chroma Options
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ChromaEndpoint: {
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envKey: "CHROMA_ENDPOINT",
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checks: [isValidURL, validChromaURL, validDockerizedUrl],
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},
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ChromaApiHeader: {
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envKey: "CHROMA_API_HEADER",
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checks: [],
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},
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ChromaApiKey: {
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envKey: "CHROMA_API_KEY",
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checks: [],
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},
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// Weaviate Options
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WeaviateEndpoint: {
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envKey: "WEAVIATE_ENDPOINT",
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checks: [isValidURL, validDockerizedUrl],
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},
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WeaviateApiKey: {
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envKey: "WEAVIATE_API_KEY",
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checks: [],
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},
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// QDrant Options
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QdrantEndpoint: {
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envKey: "QDRANT_ENDPOINT",
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checks: [isValidURL, validDockerizedUrl],
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},
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QdrantApiKey: {
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envKey: "QDRANT_API_KEY",
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checks: [],
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},
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PineConeKey: {
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envKey: "PINECONE_API_KEY",
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checks: [],
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},
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PineConeIndex: {
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envKey: "PINECONE_INDEX",
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checks: [],
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},
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// Milvus Options
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MilvusAddress: {
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envKey: "MILVUS_ADDRESS",
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checks: [isValidURL, validDockerizedUrl],
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},
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MilvusUsername: {
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envKey: "MILVUS_USERNAME",
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checks: [isNotEmpty],
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},
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MilvusPassword: {
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envKey: "MILVUS_PASSWORD",
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checks: [isNotEmpty],
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},
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// Zilliz Cloud Options
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ZillizEndpoint: {
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envKey: "ZILLIZ_ENDPOINT",
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checks: [isValidURL],
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},
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ZillizApiToken: {
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envKey: "ZILLIZ_API_TOKEN",
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checks: [isNotEmpty],
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},
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// Astra DB Options
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AstraDBApplicationToken: {
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envKey: "ASTRA_DB_APPLICATION_TOKEN",
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checks: [isNotEmpty],
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},
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AstraDBEndpoint: {
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envKey: "ASTRA_DB_ENDPOINT",
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checks: [isNotEmpty],
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},
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// Together Ai Options
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TogetherAiApiKey: {
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envKey: "TOGETHER_AI_API_KEY",
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checks: [isNotEmpty],
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},
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TogetherAiModelPref: {
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envKey: "TOGETHER_AI_MODEL_PREF",
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checks: [isNotEmpty],
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},
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// Perplexity Options
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PerplexityApiKey: {
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envKey: "PERPLEXITY_API_KEY",
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checks: [isNotEmpty],
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},
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PerplexityModelPref: {
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envKey: "PERPLEXITY_MODEL_PREF",
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checks: [isNotEmpty],
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},
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// OpenRouter Options
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OpenRouterApiKey: {
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envKey: "OPENROUTER_API_KEY",
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checks: [isNotEmpty],
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},
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OpenRouterModelPref: {
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envKey: "OPENROUTER_MODEL_PREF",
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checks: [isNotEmpty],
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},
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OpenRouterTimeout: {
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envKey: "OPENROUTER_TIMEOUT_MS",
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checks: [],
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},
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// Groq Options
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GroqApiKey: {
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envKey: "GROQ_API_KEY",
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checks: [isNotEmpty],
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},
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GroqModelPref: {
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envKey: "GROQ_MODEL_PREF",
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checks: [isNotEmpty],
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},
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// Cohere Options
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CohereApiKey: {
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envKey: "COHERE_API_KEY",
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checks: [isNotEmpty],
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},
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CohereModelPref: {
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envKey: "COHERE_MODEL_PREF",
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checks: [isNotEmpty],
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},
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// VoyageAi Options
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VoyageAiApiKey: {
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envKey: "VOYAGEAI_API_KEY",
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checks: [isNotEmpty],
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},
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// Whisper (transcription) providers
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WhisperProvider: {
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envKey: "WHISPER_PROVIDER",
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checks: [isNotEmpty, supportedTranscriptionProvider],
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postUpdate: [],
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},
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WhisperModelPref: {
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envKey: "WHISPER_MODEL_PREF",
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checks: [validLocalWhisper],
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postUpdate: [],
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},
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// System Settings
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AuthToken: {
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envKey: "AUTH_TOKEN",
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checks: [requiresForceMode, noRestrictedChars],
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},
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JWTSecret: {
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envKey: "JWT_SECRET",
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checks: [requiresForceMode],
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},
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DisableTelemetry: {
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envKey: "DISABLE_TELEMETRY",
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checks: [],
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},
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// Agent Integration ENVs
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AgentGoogleSearchEngineId: {
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envKey: "AGENT_GSE_CTX",
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checks: [],
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},
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AgentGoogleSearchEngineKey: {
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envKey: "AGENT_GSE_KEY",
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checks: [],
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},
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AgentSerperApiKey: {
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envKey: "AGENT_SERPER_DEV_KEY",
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checks: [],
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},
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AgentBingSearchApiKey: {
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envKey: "AGENT_BING_SEARCH_API_KEY",
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checks: [],
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},
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AgentSerplyApiKey: {
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envKey: "AGENT_SERPLY_API_KEY",
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checks: [],
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},
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AgentSearXNGApiUrl: {
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envKey: "AGENT_SEARXNG_API_URL",
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checks: [],
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},
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// TTS/STT Integration ENVS
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TextToSpeechProvider: {
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envKey: "TTS_PROVIDER",
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checks: [supportedTTSProvider],
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},
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// TTS OpenAI
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TTSOpenAIKey: {
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envKey: "TTS_OPEN_AI_KEY",
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checks: [validOpenAIKey],
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},
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TTSOpenAIVoiceModel: {
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envKey: "TTS_OPEN_AI_VOICE_MODEL",
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checks: [],
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},
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// TTS ElevenLabs
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TTSElevenLabsKey: {
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envKey: "TTS_ELEVEN_LABS_KEY",
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checks: [isNotEmpty],
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},
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TTSElevenLabsVoiceModel: {
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envKey: "TTS_ELEVEN_LABS_VOICE_MODEL",
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checks: [],
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},
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// PiperTTS Local
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TTSPiperTTSVoiceModel: {
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envKey: "TTS_PIPER_VOICE_MODEL",
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checks: [],
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},
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};
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function isNotEmpty(input = "") {
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return !input || input.length === 0 ? "Value cannot be empty" : null;
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}
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function nonZero(input = "") {
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if (isNaN(Number(input))) return "Value must be a number";
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return Number(input) <= 0 ? "Value must be greater than zero" : null;
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}
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function isInteger(input = "") {
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if (isNaN(Number(input))) return "Value must be a number";
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return Number(input);
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}
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function isValidURL(input = "") {
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try {
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new URL(input);
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return null;
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} catch (e) {
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return "URL is not a valid URL.";
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}
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}
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function validOpenAIKey(input = "") {
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return input.startsWith("sk-") ? null : "OpenAI Key must start with sk-";
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}
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function validAnthropicApiKey(input = "") {
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return input.startsWith("sk-ant-")
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? null
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: "Anthropic Key must start with sk-ant-";
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}
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function validLLMExternalBasePath(input = "") {
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try {
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new URL(input);
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if (!input.includes("v1")) return "URL must include /v1";
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if (input.split("").slice(-1)?.[0] === "/")
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return "URL cannot end with a slash";
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return null;
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} catch {
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return "Not a valid URL";
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}
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}
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function validOllamaLLMBasePath(input = "") {
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try {
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new URL(input);
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if (input.split("").slice(-1)?.[0] === "/")
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return "URL cannot end with a slash";
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return null;
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} catch {
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return "Not a valid URL";
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}
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}
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function supportedTTSProvider(input = "") {
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const validSelection = [
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"native",
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"openai",
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"elevenlabs",
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"piper_local",
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].includes(input);
|
|
return validSelection ? null : `${input} is not a valid TTS provider.`;
|
|
}
|
|
|
|
function validLocalWhisper(input = "") {
|
|
const validSelection = [
|
|
"Xenova/whisper-small",
|
|
"Xenova/whisper-large",
|
|
].includes(input);
|
|
return validSelection
|
|
? null
|
|
: `${input} is not a valid Whisper model selection.`;
|
|
}
|
|
|
|
function supportedLLM(input = "") {
|
|
const validSelection = [
|
|
"openai",
|
|
"azure",
|
|
"anthropic",
|
|
"gemini",
|
|
"lmstudio",
|
|
"localai",
|
|
"ollama",
|
|
"native",
|
|
"togetherai",
|
|
"mistral",
|
|
"huggingface",
|
|
"perplexity",
|
|
"openrouter",
|
|
"groq",
|
|
"koboldcpp",
|
|
"textgenwebui",
|
|
"cohere",
|
|
"litellm",
|
|
"generic-openai",
|
|
"bedrock",
|
|
].includes(input);
|
|
return validSelection ? null : `${input} is not a valid LLM provider.`;
|
|
}
|
|
|
|
function supportedTranscriptionProvider(input = "") {
|
|
const validSelection = ["openai", "local"].includes(input);
|
|
return validSelection
|
|
? null
|
|
: `${input} is not a valid transcription model provider.`;
|
|
}
|
|
|
|
function validGeminiModel(input = "") {
|
|
const validModels = [
|
|
"gemini-pro",
|
|
"gemini-1.0-pro",
|
|
"gemini-1.5-pro-latest",
|
|
"gemini-1.5-flash-latest",
|
|
"gemini-1.5-pro-exp-0801",
|
|
];
|
|
return validModels.includes(input)
|
|
? null
|
|
: `Invalid Model type. Must be one of ${validModels.join(", ")}.`;
|
|
}
|
|
|
|
function validGeminiSafetySetting(input = "") {
|
|
const validModes = [
|
|
"BLOCK_NONE",
|
|
"BLOCK_ONLY_HIGH",
|
|
"BLOCK_MEDIUM_AND_ABOVE",
|
|
"BLOCK_LOW_AND_ABOVE",
|
|
];
|
|
return validModes.includes(input)
|
|
? null
|
|
: `Invalid Safety setting. Must be one of ${validModes.join(", ")}.`;
|
|
}
|
|
|
|
function validAnthropicModel(input = "") {
|
|
const validModels = [
|
|
"claude-instant-1.2",
|
|
"claude-2.0",
|
|
"claude-2.1",
|
|
"claude-3-opus-20240229",
|
|
"claude-3-sonnet-20240229",
|
|
"claude-3-haiku-20240307",
|
|
"claude-3-5-sonnet-20240620",
|
|
];
|
|
return validModels.includes(input)
|
|
? null
|
|
: `Invalid Model type. Must be one of ${validModels.join(", ")}.`;
|
|
}
|
|
|
|
function supportedEmbeddingModel(input = "") {
|
|
const supported = [
|
|
"openai",
|
|
"azure",
|
|
"localai",
|
|
"native",
|
|
"ollama",
|
|
"lmstudio",
|
|
"cohere",
|
|
"voyageai",
|
|
"litellm",
|
|
"generic-openai",
|
|
];
|
|
return supported.includes(input)
|
|
? null
|
|
: `Invalid Embedding model type. Must be one of ${supported.join(", ")}.`;
|
|
}
|
|
|
|
function supportedVectorDB(input = "") {
|
|
const supported = [
|
|
"chroma",
|
|
"pinecone",
|
|
"lancedb",
|
|
"weaviate",
|
|
"qdrant",
|
|
"milvus",
|
|
"zilliz",
|
|
"astra",
|
|
];
|
|
return supported.includes(input)
|
|
? null
|
|
: `Invalid VectorDB type. Must be one of ${supported.join(", ")}.`;
|
|
}
|
|
|
|
function validChromaURL(input = "") {
|
|
return input.slice(-1) === "/"
|
|
? `Chroma Instance URL should not end in a trailing slash.`
|
|
: null;
|
|
}
|
|
|
|
function validOpenAiTokenLimit(input = "") {
|
|
const tokenLimit = Number(input);
|
|
if (isNaN(tokenLimit)) return "Token limit is not a number";
|
|
if (![4_096, 16_384, 8_192, 32_768, 128_000].includes(tokenLimit))
|
|
return "Invalid OpenAI token limit.";
|
|
return null;
|
|
}
|
|
|
|
function requiresForceMode(_, forceModeEnabled = false) {
|
|
return forceModeEnabled === true ? null : "Cannot set this setting.";
|
|
}
|
|
|
|
function isDownloadedModel(input = "") {
|
|
const fs = require("fs");
|
|
const path = require("path");
|
|
const storageDir = path.resolve(
|
|
process.env.STORAGE_DIR
|
|
? path.resolve(process.env.STORAGE_DIR, "models", "downloaded")
|
|
: path.resolve(__dirname, `../../storage/models/downloaded`)
|
|
);
|
|
if (!fs.existsSync(storageDir)) return false;
|
|
|
|
const files = fs
|
|
.readdirSync(storageDir)
|
|
.filter((file) => file.includes(".gguf"));
|
|
return files.includes(input);
|
|
}
|
|
|
|
async function validDockerizedUrl(input = "") {
|
|
if (process.env.ANYTHING_LLM_RUNTIME !== "docker") return null;
|
|
|
|
try {
|
|
const { isPortInUse, getLocalHosts } = require("./portAvailabilityChecker");
|
|
const localInterfaces = getLocalHosts();
|
|
const url = new URL(input);
|
|
const hostname = url.hostname.toLowerCase();
|
|
const port = parseInt(url.port, 10);
|
|
|
|
// If not a loopback, skip this check.
|
|
if (!localInterfaces.includes(hostname)) return null;
|
|
if (isNaN(port)) return "Invalid URL: Port is not specified or invalid";
|
|
|
|
const isPortAvailableFromDocker = await isPortInUse(port, hostname);
|
|
if (isPortAvailableFromDocker)
|
|
return "Port is not running a reachable service on loopback address from inside the AnythingLLM container. Please use host.docker.internal (for linux use 172.17.0.1), a real machine ip, or domain to connect to your service.";
|
|
} catch (error) {
|
|
console.error(error.message);
|
|
return "An error occurred while validating the URL";
|
|
}
|
|
|
|
return null;
|
|
}
|
|
|
|
function validHuggingFaceEndpoint(input = "") {
|
|
return input.slice(-6) !== ".cloud"
|
|
? `Your HF Endpoint should end in ".cloud"`
|
|
: null;
|
|
}
|
|
|
|
function noRestrictedChars(input = "") {
|
|
const regExp = new RegExp(/^[a-zA-Z0-9_\-!@$%^&*();]+$/);
|
|
return !regExp.test(input)
|
|
? `Your password has restricted characters in it. Allowed symbols are _,-,!,@,$,%,^,&,*,(,),;`
|
|
: null;
|
|
}
|
|
|
|
// This will force update .env variables which for any which reason were not able to be parsed or
|
|
// read from an ENV file as this seems to be a complicating step for many so allowing people to write
|
|
// to the process will at least alleviate that issue. It does not perform comprehensive validity checks or sanity checks
|
|
// and is simply for debugging when the .env not found issue many come across.
|
|
async function updateENV(newENVs = {}, force = false, userId = null) {
|
|
let error = "";
|
|
const validKeys = Object.keys(KEY_MAPPING);
|
|
const ENV_KEYS = Object.keys(newENVs).filter(
|
|
(key) => validKeys.includes(key) && !newENVs[key].includes("******") // strip out answers where the value is all asterisks
|
|
);
|
|
const newValues = {};
|
|
|
|
for (const key of ENV_KEYS) {
|
|
const { envKey, checks, postUpdate = [] } = KEY_MAPPING[key];
|
|
const prevValue = process.env[envKey];
|
|
const nextValue = newENVs[key];
|
|
|
|
const errors = await executeValidationChecks(checks, nextValue, force);
|
|
if (errors.length > 0) {
|
|
error += errors.join("\n");
|
|
break;
|
|
}
|
|
|
|
newValues[key] = nextValue;
|
|
process.env[envKey] = nextValue;
|
|
|
|
for (const postUpdateFunc of postUpdate)
|
|
await postUpdateFunc(key, prevValue, nextValue);
|
|
}
|
|
|
|
await logChangesToEventLog(newValues, userId);
|
|
if (process.env.NODE_ENV === "production") dumpENV();
|
|
return { newValues, error: error?.length > 0 ? error : false };
|
|
}
|
|
|
|
async function executeValidationChecks(checks, value, force) {
|
|
const results = await Promise.all(
|
|
checks.map((validator) => validator(value, force))
|
|
);
|
|
return results.filter((err) => typeof err === "string");
|
|
}
|
|
|
|
async function logChangesToEventLog(newValues = {}, userId = null) {
|
|
const { EventLogs } = require("../../models/eventLogs");
|
|
const eventMapping = {
|
|
LLMProvider: "update_llm_provider",
|
|
EmbeddingEngine: "update_embedding_engine",
|
|
VectorDB: "update_vector_db",
|
|
};
|
|
|
|
for (const [key, eventName] of Object.entries(eventMapping)) {
|
|
if (!newValues.hasOwnProperty(key)) continue;
|
|
await EventLogs.logEvent(eventName, {}, userId);
|
|
}
|
|
return;
|
|
}
|
|
|
|
function dumpENV() {
|
|
const fs = require("fs");
|
|
const path = require("path");
|
|
|
|
const frozenEnvs = {};
|
|
const protectedKeys = [
|
|
...Object.values(KEY_MAPPING).map((values) => values.envKey),
|
|
// Manually Add Keys here which are not already defined in KEY_MAPPING
|
|
// and are either managed or manually set ENV key:values.
|
|
"STORAGE_DIR",
|
|
"SERVER_PORT",
|
|
// For persistent data encryption
|
|
"SIG_KEY",
|
|
"SIG_SALT",
|
|
// Password Schema Keys if present.
|
|
"PASSWORDMINCHAR",
|
|
"PASSWORDMAXCHAR",
|
|
"PASSWORDLOWERCASE",
|
|
"PASSWORDUPPERCASE",
|
|
"PASSWORDNUMERIC",
|
|
"PASSWORDSYMBOL",
|
|
"PASSWORDREQUIREMENTS",
|
|
// HTTPS SETUP KEYS
|
|
"ENABLE_HTTPS",
|
|
"HTTPS_CERT_PATH",
|
|
"HTTPS_KEY_PATH",
|
|
];
|
|
|
|
// Simple sanitization of each value to prevent ENV injection via newline or quote escaping.
|
|
function sanitizeValue(value) {
|
|
const offendingChars =
|
|
/[\n\r\t\v\f\u0085\u00a0\u1680\u180e\u2000-\u200a\u2028\u2029\u202f\u205f\u3000"'`#]/;
|
|
const firstOffendingCharIndex = value.search(offendingChars);
|
|
if (firstOffendingCharIndex === -1) return value;
|
|
|
|
return value.substring(0, firstOffendingCharIndex);
|
|
}
|
|
|
|
for (const key of protectedKeys) {
|
|
const envValue = process.env?.[key] || null;
|
|
if (!envValue) continue;
|
|
frozenEnvs[key] = process.env?.[key] || null;
|
|
}
|
|
|
|
var envResult = `# Auto-dump ENV from system call on ${new Date().toTimeString()}\n`;
|
|
envResult += Object.entries(frozenEnvs)
|
|
.map(([key, value]) => `${key}='${sanitizeValue(value)}'`)
|
|
.join("\n");
|
|
|
|
const envPath = path.join(__dirname, "../../.env");
|
|
fs.writeFileSync(envPath, envResult, { encoding: "utf8", flag: "w" });
|
|
return true;
|
|
}
|
|
|
|
module.exports = {
|
|
dumpENV,
|
|
updateENV,
|
|
};
|