feat: enable client side config

app/api/validate-model/route.ts

@@ -81,6 +81,9 @@ interface ValidateRequest {
     awsAccessKeyId?: string
     awsSecretAccessKey?: string
     awsRegion?: string
+    // Vertex AI specific
+    vertexProject?: string
+    vertexLocation?: string
 }
 
 export async function POST(req: Request) {
@@ -94,6 +97,8 @@ export async function POST(req: Request) {
             awsAccessKeyId,
             awsSecretAccessKey,
             awsRegion,
+            vertexProject,
+            vertexLocation,
         } = body
 
         if (!provider || !modelId) {
@@ -166,23 +171,27 @@ export async function POST(req: Request) {
 
             case "vertexai": {
                 // Vertex AI uses GCP service account authentication via environment variables
-                const vertexProject = process.env.GOOGLE_VERTEX_PROJECT
-                const vertexLocation =
-                    process.env.GOOGLE_VERTEX_LOCATION || "us-central1"
+                // OR client-provided project/location
+                const project =
+                    vertexProject || process.env.GOOGLE_VERTEX_PROJECT
+                const location =
+                    vertexLocation ||
+                    process.env.GOOGLE_VERTEX_LOCATION ||
+                    "us-central1"
 
-                if (!vertexProject) {
+                if (!project) {
                     return NextResponse.json(
                         {
                             valid: false,
-                            error: "GOOGLE_VERTEX_PROJECT environment variable is required",
+                            error: "Project ID is required (set in Settings or via GOOGLE_VERTEX_PROJECT)",
                         },
                         { status: 400 },
                     )
                 }
 
                 const vertex = createVertex({
-                    project: vertexProject,
-                    location: vertexLocation,
+                    project: project,
+                    location: location,
                 })
                 model = vertex(modelId)
                 break

lib/ai-providers.ts

@@ -30,6 +30,9 @@ export interface ClientOverrides {
     awsSecretAccessKey?: string | null
     awsRegion?: string | null
     awsSessionToken?: string | null
+    // Vertex AI config
+    vertexProject?: string | null
+    vertexLocation?: string | null
     // Custom headers (e.g., for EdgeOne cookie auth)
     headers?: Record<string, string>
 }
@@ -684,13 +687,17 @@ export function getAIModel(overrides?: ClientOverrides): ModelConfig {
         case "vertexai": {
             // Google Vertex AI uses GCP service account authentication, not API keys
             // Auth is handled via GOOGLE_APPLICATION_CREDENTIALS env var or GCP default credentials
-            const vertexProject = process.env.GOOGLE_VERTEX_PROJECT
+            // Client-provided Project ID and Location, falling back to server environment variables
+            const vertexProject =
+                overrides?.vertexProject || process.env.GOOGLE_VERTEX_PROJECT
             const vertexLocation =
-                process.env.GOOGLE_VERTEX_LOCATION || "us-central1"
+                overrides?.vertexLocation ||
+                process.env.GOOGLE_VERTEX_LOCATION ||
+                "us-central1"
 
             if (!vertexProject) {
                 throw new Error(
-                    "GOOGLE_VERTEX_PROJECT environment variable is required for vertexai provider.",
+                    "Project ID is required for Vertex AI. Please configure it in Settings or set GOOGLE_VERTEX_PROJECT environment variable.",
                 )
             }
 

lib/types/model-config.ts

@@ -37,6 +37,10 @@ export interface ProviderConfig {
     awsSecretAccessKey?: string
     awsRegion?: string
     awsSessionToken?: string // Optional, for temporary credentials
+    // Vertex AI specific fields
+    vertexProject?: string
+    vertexLocation?: string
+
     models: ModelConfig[]
     validated?: boolean // Has API key been validated
 }
@@ -62,6 +66,10 @@ export interface FlattenedModel {
     awsSecretAccessKey?: string
     awsRegion?: string
     awsSessionToken?: string
+    // Vertex AI specific fields
+    vertexProject?: string
+    vertexLocation?: string
+
     validated?: boolean // Has this model been validated
 }
 
@@ -323,6 +331,10 @@ export function flattenModels(config: MultiModelConfig): FlattenedModel[] {
                 awsSecretAccessKey: provider.awsSecretAccessKey,
                 awsRegion: provider.awsRegion,
                 awsSessionToken: provider.awsSessionToken,
+                // Vertex AI fields
+                vertexProject: provider.vertexProject,
+                vertexLocation: provider.vertexLocation,
+
                 validated: model.validated,
             })
         }