WIP quickstart env

server/models/systemSettings.js

@@ -205,9 +205,11 @@ const SystemSettings = {
   },
   currentSettings: async function () {
     const { hasVectorCachedFiles } = require("../utils/files");
-    const llmProvider = process.env.LLM_PROVIDER;
-    const vectorDB = process.env.VECTOR_DB;
-    const embeddingEngine = process.env.EMBEDDING_ENGINE ?? "native";
+    const { getStartupDefaults } = require("../utils/boot/defaults");
+    const defaults = getStartupDefaults();
+    const llmProvider = process.env.LLM_PROVIDER ?? defaults.llmProvider;
+    const vectorDB = process.env.VECTOR_DB ?? defaults.vectorDB;
+    const embeddingEngine = process.env.EMBEDDING_ENGINE ?? defaults.embeddingEngine;
     return {
       // --------------------------------------------------------
       // General Settings

server/utils/boot/defaults.js

@@ -0,0 +1,48 @@
+const { supportedLLM } = require("../helpers/updateENV");
+const { getProcessEnvValue } = require("../helpers");
+const LLM_PROVIDER_DEFAULT = null;
+const VECTOR_DB_DEFAULT = null;
+const EMBEDDING_ENGINE_DEFAULT = "native";
+
+function getStartupDefaults() {
+    validateLLMQuickSetup();
+   
+    return {
+        llmProvider: process.env.LLM_PROVIDER ?? LLM_PROVIDER_DEFAULT,
+        vectorDB: process.env.VECTOR_DB ?? VECTOR_DB_DEFAULT,
+        embeddingEngine: process.env.EMBEDDING_ENGINE ?? EMBEDDING_ENGINE_DEFAULT,
+    };
+}
+
+function validateLLMQuickSetup() {
+    try {
+        if(!!process.env.LLM_PROVIDER) return;
+        if(!process.env.LLM_QUICKSETUP) return;
+        
+        const quickSetupString = process.env.LLM_QUICKSETUP;
+        let [provider, model] = [quickSetupString.slice(0, quickSetupString.indexOf(':')), quickSetupString.slice(quickSetupString.indexOf(':') + 1)];
+        if(!provider || !model) throw new Error("Invalid LLM quick setup string. Format: provider:model_tag. eg: dmr:ai/qwen3:4B-UD-Q4_K_XL");
+        
+        // Aliases for quick setup
+        switch(provider) {
+            case "dmr":
+                provider = "docker-model-runner";
+                break;
+            default:
+                break;
+        }
+
+        if(supportedLLM(provider) !== null) throw new Error(`Invalid LLM provider: ${provider}`);
+        process.env.LLM_PROVIDER = provider;
+        const expectedModelPrefKey = getProcessEnvValue(provider);
+        if (model && expectedModelPrefKey) process.env[expectedModelPrefKey] = model;
+    } catch (error) {
+        console.error("Error validating LLM quick setup: " + error.message);
+    } finally {
+        if(process.env.LLM_QUICKSETUP) delete process.env.LLM_QUICKSETUP;
+    }
+}
+
+module.exports = {
+    getStartupDefaults,
+}

server/utils/helpers/index.js

@@ -487,6 +487,79 @@ function getBaseLLMProviderModel({ provider = null } = {}) {
   }
 }
 
+function getProcessEnvValue(provider, defaultValue = null) {
+  switch (provider) {
+    case "openai":
+      return 'OPEN_MODEL_PREF';
+    case "azure":
+      return 'OPEN_MODEL_PREF';
+    case "anthropic":
+      return 'ANTHROPIC_MODEL_PREF';
+    case "gemini":
+      return 'GEMINI_LLM_MODEL_PREF';
+    case "lmstudio":
+      return 'LMSTUDIO_MODEL_PREF';
+    case "localai":
+      return 'LOCAL_AI_MODEL_PREF';
+    case "ollama":
+      return 'OLLAMA_MODEL_PREF';
+    case "togetherai":
+      return 'TOGETHER_AI_MODEL_PREF';
+    case "fireworksai":
+      return 'FIREWORKS_AI_LLM_MODEL_PREF';
+    case "perplexity":
+      return 'PERPLEXITY_MODEL_PREF';
+    case "openrouter":
+      return 'OPENROUTER_MODEL_PREF';
+    case "mistral":
+      return 'MISTRAL_MODEL_PREF';
+    case "huggingface":
+      return defaultValue;
+    case "groq":
+      return 'GROQ_MODEL_PREF';
+    case "koboldcpp":
+      return 'KOBOLD_CPP_MODEL_PREF';
+    case "textgenwebui":
+      return defaultValue;
+    case "cohere":
+      return 'COHERE_MODEL_PREF';
+    case "litellm":
+      return 'LITE_LLM_MODEL_PREF';
+    case "generic-openai":
+      return 'GENERIC_OPEN_AI_MODEL_PREF';
+    case "bedrock":
+      return 'AWS_BEDROCK_LLM_MODEL_PREFERENCE';
+    case "deepseek":
+      return 'DEEPSEEK_MODEL_PREF';
+    case "apipie":
+      return 'APIPIE_LLM_MODEL_PREF';
+    case "novita":
+      return 'NOVITA_LLM_MODEL_PREF';
+    case "xai":
+      return 'XAI_LLM_MODEL_PREF';
+    case "nvidia-nim":
+      return 'NVIDIA_NIM_LLM_MODEL_PREF';
+    case "ppio":
+      return 'PPIO_MODEL_PREF';
+    case "dpais":
+      return 'DPAIS_LLM_MODEL_PREF';
+    case "moonshotai":
+      return 'MOONSHOT_AI_MODEL_PREF';
+    case "cometapi":
+      return 'COMETAPI_LLM_MODEL_PREF';
+    case "foundry":
+      return 'FOUNDRY_MODEL_PREF';
+    case "zai":
+      return 'ZAI_MODEL_PREF';
+    case "giteeai":
+      return 'GITEE_AI_MODEL_PREF';
+    case "docker-model-runner":
+      return 'DOCKER_MODEL_RUNNER_LLM_MODEL_PREF';
+    default:
+      return defaultValue;
+  }
+}
+
 // Some models have lower restrictions on chars that can be encoded in a single pass
 // and by default we assume it can handle 1,000 chars, but some models use work with smaller
 // chars so here we can override that value when embedding information.
@@ -537,6 +610,7 @@ module.exports = {
   getVectorDbClass,
   getLLMProviderClass,
   getBaseLLMProviderModel,
+  getProcessEnvValue,
   getLLMProvider,
   toChunks,
   humanFileSize,

server/utils/helpers/updateENV.js

@@ -1302,4 +1302,5 @@ function dumpENV() {
 module.exports = {
   dumpENV,
   updateENV,
+  supportedLLM,
 };