try

src/app/api/analyze/route.ts

@@ -7,15 +7,23 @@ import { processAnimalImage } from '../../../services/animalProcessingService'
 export async function POST(req: NextRequest): Promise<NextResponse> {
   try {
     const formData = await req.formData()
-    const imageFile = formData.get('image') as File
+    const imageFile = formData.get('image')
     
-    if (!imageFile) {
+    // Robust type checking
+    if (!imageFile || !(imageFile instanceof File)) {
       return NextResponse.json(
-        { error: 'No image provided' },
+        { error: 'No valid image provided' },
         { status: 400 }
       )
     }
 
+    // Log file details for debugging
+    console.log('Received file:', {
+      name: imageFile.name,
+      type: imageFile.type,
+      size: imageFile.size
+    })
+
     // Convert image to buffer
     const arrayBuffer = await imageFile.arrayBuffer()
     const buffer = Buffer.from(arrayBuffer)
@@ -42,7 +50,7 @@ export async function POST(req: NextRequest): Promise<NextResponse> {
         buffer,
         visionResult.description,
         visionResult.rawResponse,
-	imageFile.name
+        imageFile.name
       ).catch(console.error)
     }
 

src/services/googleVisionService.ts

@@ -27,19 +27,44 @@ export async function analyzeImage(imageBuffer: Buffer, filename: string): Promi
     
     // Create file from buffer using Blob
     const blob = new Blob([imageBuffer], { type: 'image/jpeg' })
+    
+    // Detailed logging for debugging
+    console.log('Analyzing image:', {
+      filename,
+      bufferLength: imageBuffer.length,
+      blobSize: blob.size,
+      blobType: blob.type
+    })
+
     formData.append('image', blob, filename)
 
+    // Log FormData contents (if possible)
+    for (const [key, value] of formData.entries()) {
+      console.log('FormData entry:', key, value)
+    }
+
     const response = await fetch('/api/analyze', {
       method: 'POST',
       body: formData
     })
 
+    // Log full response for debugging
+    const responseText = await response.text()
+    console.log('Raw response:', responseText)
+
     if (!response.ok) {
-      const error = await response.json()
-      throw new Error(error.error || 'Failed to analyze image')
+      try {
+        const errorData = JSON.parse(responseText)
+        throw new Error(errorData.error || 'Failed to analyze image')
+      } catch {
+        throw new Error(`HTTP error ${response.status}: ${responseText}`)
+      }
     }
 
-    return await response.json()
+    // Parse response
+    const result = JSON.parse(responseText)
+    return result
+
   } catch (error) {
     console.error('Vision analysis error:', error)
     return {