mirror of
https://github.com/Mintplex-Labs/anything-llm.git
synced 2024-11-09 00:10:10 +01:00
633f425206
* WIP openrouter integration * add OpenRouter options to onboarding flow and data handling * add todo to fix headers for rankings * OpenRouter LLM support complete * Fix hanging response stream with OpenRouter update tagline update comment * update timeout comment * wait for first chunk to start timer * sort OpenRouter models by organization * uppercase first letter of organization * sort grouped models by org --------- Co-authored-by: timothycarambat <rambat1010@gmail.com>
346 lines
12 KiB
JavaScript
346 lines
12 KiB
JavaScript
process.env.NODE_ENV === "development"
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? require("dotenv").config({ path: `.env.${process.env.NODE_ENV}` })
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: require("dotenv").config();
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const prisma = require("../utils/prisma");
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const SystemSettings = {
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supportedFields: [
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"multi_user_mode",
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"users_can_delete_workspaces",
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"limit_user_messages",
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"message_limit",
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"logo_filename",
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"telemetry_id",
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"footer_data",
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"support_email",
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],
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validations: {
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footer_data: (updates) => {
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try {
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const array = JSON.parse(updates);
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return JSON.stringify(array.slice(0, 3)); // max of 3 items in footer.
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} catch (e) {
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console.error(`Failed to run validation function on footer_data`);
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return JSON.stringify([]);
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}
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},
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},
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currentSettings: async function () {
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const llmProvider = process.env.LLM_PROVIDER;
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const vectorDB = process.env.VECTOR_DB;
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return {
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RequiresAuth: !!process.env.AUTH_TOKEN,
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AuthToken: !!process.env.AUTH_TOKEN,
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JWTSecret: !!process.env.JWT_SECRET,
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StorageDir: process.env.STORAGE_DIR,
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MultiUserMode: await this.isMultiUserMode(),
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VectorDB: vectorDB,
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HasExistingEmbeddings: await this.hasEmbeddings(),
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EmbeddingEngine: process.env.EMBEDDING_ENGINE,
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EmbeddingBasePath: process.env.EMBEDDING_BASE_PATH,
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EmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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EmbeddingModelMaxChunkLength:
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process.env.EMBEDDING_MODEL_MAX_CHUNK_LENGTH,
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LocalAiApiKey: !!process.env.LOCAL_AI_API_KEY,
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...(vectorDB === "pinecone"
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? {
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PineConeKey: !!process.env.PINECONE_API_KEY,
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PineConeIndex: process.env.PINECONE_INDEX,
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}
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: {}),
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...(vectorDB === "chroma"
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? {
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ChromaEndpoint: process.env.CHROMA_ENDPOINT,
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ChromaApiHeader: process.env.CHROMA_API_HEADER,
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ChromaApiKey: !!process.env.CHROMA_API_KEY,
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}
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: {}),
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...(vectorDB === "weaviate"
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? {
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WeaviateEndpoint: process.env.WEAVIATE_ENDPOINT,
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WeaviateApiKey: process.env.WEAVIATE_API_KEY,
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}
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: {}),
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...(vectorDB === "qdrant"
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? {
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QdrantEndpoint: process.env.QDRANT_ENDPOINT,
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QdrantApiKey: process.env.QDRANT_API_KEY,
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}
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: {}),
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...(vectorDB === "milvus"
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? {
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MilvusAddress: process.env.MILVUS_ADDRESS,
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MilvusUsername: process.env.MILVUS_USERNAME,
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MilvusPassword: !!process.env.MILVUS_PASSWORD,
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}
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: {}),
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...(vectorDB === "zilliz"
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? {
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ZillizEndpoint: process.env.ZILLIZ_ENDPOINT,
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ZillizApiToken: process.env.ZILLIZ_API_TOKEN,
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}
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: {}),
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...(vectorDB === "astra"
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? {
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AstraDBApplicationToken: process?.env?.ASTRA_DB_APPLICATION_TOKEN,
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AstraDBEndpoint: process?.env?.ASTRA_DB_ENDPOINT,
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}
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: {}),
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LLMProvider: llmProvider,
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...(llmProvider === "openai"
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? {
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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OpenAiModelPref: process.env.OPEN_MODEL_PREF || "gpt-3.5-turbo",
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}
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: {}),
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...(llmProvider === "azure"
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? {
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiModelPref: process.env.OPEN_MODEL_PREF,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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AzureOpenAiTokenLimit: process.env.AZURE_OPENAI_TOKEN_LIMIT || 4096,
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}
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: {}),
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...(llmProvider === "anthropic"
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? {
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AnthropicApiKey: !!process.env.ANTHROPIC_API_KEY,
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AnthropicModelPref: process.env.ANTHROPIC_MODEL_PREF || "claude-2",
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// For embedding credentials when Anthropic is selected.
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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}
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: {}),
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...(llmProvider === "gemini"
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? {
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GeminiLLMApiKey: !!process.env.GEMINI_API_KEY,
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GeminiLLMModelPref:
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process.env.GEMINI_LLM_MODEL_PREF || "gemini-pro",
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// For embedding credentials when Gemini is selected.
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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}
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: {}),
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...(llmProvider === "lmstudio"
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? {
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LMStudioBasePath: process.env.LMSTUDIO_BASE_PATH,
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LMStudioTokenLimit: process.env.LMSTUDIO_MODEL_TOKEN_LIMIT,
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// For embedding credentials when lmstudio is selected.
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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}
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: {}),
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...(llmProvider === "localai"
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? {
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LocalAiBasePath: process.env.LOCAL_AI_BASE_PATH,
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LocalAiModelPref: process.env.LOCAL_AI_MODEL_PREF,
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LocalAiTokenLimit: process.env.LOCAL_AI_MODEL_TOKEN_LIMIT,
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// For embedding credentials when localai is selected.
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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}
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: {}),
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...(llmProvider === "ollama"
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? {
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OllamaLLMBasePath: process.env.OLLAMA_BASE_PATH,
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OllamaLLMModelPref: process.env.OLLAMA_MODEL_PREF,
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OllamaLLMTokenLimit: process.env.OLLAMA_MODEL_TOKEN_LIMIT,
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// For embedding credentials when ollama is selected.
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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}
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: {}),
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...(llmProvider === "togetherai"
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? {
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TogetherAiApiKey: !!process.env.TOGETHER_AI_API_KEY,
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TogetherAiModelPref: process.env.TOGETHER_AI_MODEL_PREF,
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// For embedding credentials when ollama is selected.
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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}
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: {}),
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...(llmProvider === "perplexity"
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? {
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PerplexityApiKey: !!process.env.PERPLEXITY_API_KEY,
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PerplexityModelPref: process.env.PERPLEXITY_MODEL_PREF,
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// For embedding credentials when ollama is selected.
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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}
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: {}),
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...(llmProvider === "openrouter"
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? {
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OpenRouterApiKey: !!process.env.OPENROUTER_API_KEY,
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OpenRouterModelPref: process.env.OPENROUTER_MODEL_PREF,
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// For embedding credentials when ollama is selected.
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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}
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: {}),
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...(llmProvider === "mistral"
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? {
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MistralApiKey: !!process.env.MISTRAL_API_KEY,
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MistralModelPref: process.env.MISTRAL_MODEL_PREF,
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// For embedding credentials when mistral is selected.
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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}
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: {}),
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...(llmProvider === "native"
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? {
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NativeLLMModelPref: process.env.NATIVE_LLM_MODEL_PREF,
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NativeLLMTokenLimit: process.env.NATIVE_LLM_MODEL_TOKEN_LIMIT,
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// For embedding credentials when ollama is selected.
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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}
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: {}),
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...(llmProvider === "huggingface"
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? {
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HuggingFaceLLMEndpoint: process.env.HUGGING_FACE_LLM_ENDPOINT,
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HuggingFaceLLMAccessToken: !!process.env.HUGGING_FACE_LLM_API_KEY,
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HuggingFaceLLMTokenLimit: process.env.HUGGING_FACE_LLM_TOKEN_LIMIT,
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// For embedding credentials when Anthropic is selected.
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OpenAiKey: !!process.env.OPEN_AI_KEY,
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AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
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AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
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AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
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}
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: {}),
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};
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},
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get: async function (clause = {}) {
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try {
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const setting = await prisma.system_settings.findFirst({ where: clause });
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return setting || null;
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} catch (error) {
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console.error(error.message);
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return null;
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}
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},
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where: async function (clause = {}, limit) {
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try {
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const settings = await prisma.system_settings.findMany({
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where: clause,
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take: limit || undefined,
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});
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return settings;
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} catch (error) {
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console.error(error.message);
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return [];
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}
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},
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updateSettings: async function (updates = {}) {
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try {
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const updatePromises = Object.keys(updates)
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.filter((key) => this.supportedFields.includes(key))
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.map((key) => {
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const validatedValue = this.validations.hasOwnProperty(key)
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? this.validations[key](updates[key])
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: updates[key];
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return prisma.system_settings.upsert({
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where: { label: key },
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update: {
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value: validatedValue === null ? null : String(validatedValue),
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},
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create: {
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label: key,
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value: validatedValue === null ? null : String(validatedValue),
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},
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});
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});
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await Promise.all(updatePromises);
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return { success: true, error: null };
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} catch (error) {
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console.error("FAILED TO UPDATE SYSTEM SETTINGS", error.message);
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return { success: false, error: error.message };
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}
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},
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isMultiUserMode: async function () {
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try {
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const setting = await this.get({ label: "multi_user_mode" });
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return setting?.value === "true";
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} catch (error) {
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console.error(error.message);
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return false;
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}
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},
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currentLogoFilename: async function () {
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try {
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const setting = await this.get({ label: "logo_filename" });
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return setting?.value || null;
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} catch (error) {
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console.error(error.message);
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return null;
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}
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},
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canDeleteWorkspaces: async function () {
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try {
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const setting = await this.get({ label: "users_can_delete_workspaces" });
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return setting?.value === "true";
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} catch (error) {
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console.error(error.message);
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return false;
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}
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},
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hasEmbeddings: async function () {
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try {
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const { Document } = require("./documents");
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const count = await Document.count({}, 1);
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return count > 0;
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} catch (error) {
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console.error(error.message);
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return false;
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}
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},
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};
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module.exports.SystemSettings = SystemSettings;
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