aws-samples · amirgholipour · Aug 9, 2026
@@ -1,7 +1,7 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <system_prompt>
     <!-- This is your role. -->
-    <role> You are an intelligent PDF analysis orchestrator. You make all decisions about which tools to use based on content classification. You have full control over the analysis workflow. </role>
+    <role> You are an intelligent document and image analysis orchestrator. You make all decisions about which tools to use based on content classification. You have full control over the analysis workflow. </role>
 
     <!-- These are the rules you must follow for execution. -->
     <execution_rules>
@@ -47,8 +47,12 @@
 
     <!-- These are your workflow steps in precise, mandatory order. -->
     <workflow>
-        <step number="1">When user provides PDF path, call pdf_to_images_converter to convert PDF to images</step>
-        <step number="2">Call classify_pdf_content_tool with the image paths to classify each page</step>
+        <step number="1">
+            <pdf_input>When the user provides a PDF path or S3 URI, call pdf_to_images_converter to convert every PDF page to images.</pdf_input>
+            <image_input>When the user provides a TIFF, TIF, JPEG, JPG, or PNG path or S3 URI, treat it as a single page image and DO NOT call pdf_to_images_converter.</image_input>
+            <supported_formats>Supported inputs are PDF, TIFF, TIF, JPEG, JPG, and PNG.</supported_formats>
+        </step>
+        <step number="2">Call classify_pdf_content_tool with a JSON array of image paths. For a direct image upload, pass a one-item array containing its path or S3 URI.</step>
         <step number="3">Analyze the classification results and decide which specialist tools to use for each page. Check enhancement_recommended field for each page.</step>
         <step number="4">
             <step_logic> For each page, call the appropriate specialist tool(s) based on classification. </step_logic>
@@ -244,4 +248,4 @@
             <reason>Minimal content page — full_text captures the page number. Elements is not necessary when there is no document structure to identify (no headings, no sections, just a page number). Correlator is not called since there is only one specialist result.</reason>
         </example>
     </tool_mapping_examples>
-</system_prompt>
+</system_prompt>
@@ -88,7 +88,7 @@ Browser (React/Vite)
     ├── /api/* ──→ Express server (port 7860), all behind requireAuth
     │                ├── Core routes (all roles)
     │                │   ├── AgentCore WebSocket proxy (chat, SSE to browser)
-    │                │   ├── PDF upload to S3 (mints doc_id)
+    │                │   ├── PDF and image upload to S3 (mints doc_id)
     │                │   ├── Job records (/api/jobs)
     │                │   ├── S3 file operations (manifests, prompts, schemas)
     │                │   ├── CloudWatch Logs Insights queries
@@ -112,7 +112,8 @@ The UI is the read side of the doc/job/subtask hierarchy described in
 | `GET /api/jobs/:jobId`  | One job: computed status, counts, and every subtask with its outcome |
 | `GET /api/jobs?doc_id=` | Every job recorded against one document, newest first                |
 
-`POST /api/upload` mints a `doc_id` per upload and returns it. `POST /api/chat` accepts
+`POST /api/upload` accepts PDF, PNG, JPEG/JPG, and TIFF/TIF files, validates their
+file signatures, mints a `doc_id` per upload, and returns it. `POST /api/chat` accepts
 that `doc_id` and forwards it to the agent, which stamps it onto each specialist call.
 When the agent mints a `job_id` it emits a `job` SSE event, also written to the session
 log as `[job] job_id=… doc_id=…`, so a chat transcript can be traced to its job record.
@@ -147,7 +148,7 @@ ui/
 │   │   └── useUser.js             # User context (role, email) from ID token claims
 │   └── components/
 │       ├── Home.jsx               # Dashboard
-│       ├── Chat.jsx               # Agent chat interface, PDF upload, doc_id
+│       ├── Chat.jsx               # Agent chat interface, PDF/image upload, doc_id
 │       ├── SpecialistEditor.jsx   # Manifest/prompt editor
 │       ├── SpecialistWizard.jsx   # New specialist wizard
 │       ├── Evaluator.jsx          # Test runner

@@ -70,6 +70,30 @@ export function mountCoreRoutes(app, PROJECT_ROOT) {
     const ddbClient = DynamoDBDocumentClient.from(new DynamoDBClient({ region: REGION, credentials }));
     const upload = multer({ storage: multer.memoryStorage(), limits: { fileSize: 50 * 1024 * 1024 } });
 
+    function detectUploadType(buffer) {
+        if (buffer.length >= 5 && buffer.subarray(0, 5).toString() === '%PDF-') {
+            return { contentType: 'application/pdf', fileKind: 'pdf', extensions: ['.pdf'] };
+        }
+        if (buffer.length >= 8 && buffer.subarray(0, 8).equals(Buffer.from([0x89, 0x50, 0x4e, 0x47, 0x0d, 0x0a, 0x1a, 0x0a]))) {
+            return { contentType: 'image/png', fileKind: 'image', extensions: ['.png'] };
+        }
+        if (buffer.length >= 3 && buffer[0] === 0xff && buffer[1] === 0xd8 && buffer[2] === 0xff) {
+            return { contentType: 'image/jpeg', fileKind: 'image', extensions: ['.jpg', '.jpeg'] };
+        }
+        const isClassicTiff = buffer.length >= 4 && (
+            (buffer[0] === 0x49 && buffer[1] === 0x49 && buffer[2] === 0x2a && buffer[3] === 0x00) ||
+            (buffer[0] === 0x4d && buffer[1] === 0x4d && buffer[2] === 0x00 && buffer[3] === 0x2a)
+        );
+        const isBigTiff = buffer.length >= 4 && (
+            (buffer[0] === 0x49 && buffer[1] === 0x49 && buffer[2] === 0x2b && buffer[3] === 0x00) ||
+            (buffer[0] === 0x4d && buffer[1] === 0x4d && buffer[2] === 0x00 && buffer[3] === 0x2b)
+        );
+        if (isClassicTiff || isBigTiff) {
+            return { contentType: 'image/tiff', fileKind: 'image', extensions: ['.tif', '.tiff'] };
+        }
+        return null;
+    }
+
     console.log(`Region: ${REGION}`);
     console.log(`Profile: ${AWS_PROFILE || 'default'}`);
     console.log(`Runtime ARN: ${RUNTIME_ARN ? '✅' : '❌ not set'}`);
@@ -167,9 +191,13 @@ export function mountCoreRoutes(app, PROJECT_ROOT) {
     app.post('/api/upload', upload.single('file'), async (req, res) => {
         if (!req.file) return res.status(400).json({ error: 'No file provided' });
         if (!UPLOAD_BUCKET) return res.status(500).json({ error: 'S3_UPLOAD_BUCKET not configured' });
-        const isPdfMime = req.file.mimetype === 'application/pdf';
-        const isPdfMagic = req.file.buffer.length >= 5 && req.file.buffer.slice(0, 5).toString() === '%PDF-';
-        if (!isPdfMime || !isPdfMagic) return res.status(400).json({ error: 'Only PDF files are accepted' });
+        const detectedType = detectUploadType(req.file.buffer);
+        const extension = req.file.originalname.toLowerCase().match(/\.[^.]+$/)?.[0];
+        if (!detectedType || !detectedType.extensions.includes(extension)) {
+            return res.status(400).json({
+                error: 'Supported formats: PDF, TIFF, TIF, JPEG, JPG, and PNG. File contents must match the extension.',
+            });
+        }
 
         const filename = req.file.originalname.replace(/[^a-zA-Z0-9._-]/g, '_');
         // doc_id is the top level of the job-tracking hierarchy
@@ -182,10 +210,17 @@ export function mountCoreRoutes(app, PROJECT_ROOT) {
                 Bucket: UPLOAD_BUCKET,
                 Key: s3Key,
                 Body: req.file.buffer,
-                ContentType: req.file.mimetype,
+                ContentType: detectedType.contentType,
                 Metadata: { doc_id: docId },
             }));
-            res.json({ s3Uri: `s3://${UPLOAD_BUCKET}/${s3Key}`, docId, filename, size: req.file.size });
+            res.json({
+                s3Uri: `s3://${UPLOAD_BUCKET}/${s3Key}`,
+                docId,
+                filename,
+                size: req.file.size,
+                contentType: detectedType.contentType,
+                fileKind: detectedType.fileKind,
+            });
         } catch (e) {
             res.status(500).json({ error: e.message });
         }

@@ -185,22 +185,32 @@ function MyComposer() {
 // ── S3 Upload Attachment Adapter ──
 
 class S3AttachmentAdapter {
-  accept = 'application/pdf'
+  accept = 'application/pdf,image/png,image/jpeg,image/tiff,.pdf,.png,.jpg,.jpeg,.tif,.tiff'
 
   // Top level of the job-tracking hierarchy (doc_id -> job_id -> subtask_id).
   // The server mints it per upload; we hold the most recent one so subsequent
   // turns can attribute their jobs to the document being discussed.
   lastDocId = ''
 
   async add({ file }) {
-    if (!file.name.toLowerCase().endsWith('.pdf') && file.type !== 'application/pdf') {
-      throw new Error('Only PDF files are supported')
+    const extension = file.name.toLowerCase().match(/\.[^.]+$/)?.[0]
+    const supportedTypes = {
+      '.pdf': 'application/pdf',
+      '.png': 'image/png',
+      '.jpg': 'image/jpeg',
+      '.jpeg': 'image/jpeg',
+      '.tif': 'image/tiff',
+      '.tiff': 'image/tiff',
+    }
+    const contentType = supportedTypes[extension]
+    if (!contentType) {
+      throw new Error('Supported formats: PDF, TIFF, TIF, JPEG, JPG, and PNG')
     }
     return {
       id: crypto.randomUUID(),
-      type: 'document',
+      type: contentType.startsWith('image/') ? 'image' : 'document',
       name: file.name,
-      contentType: 'application/pdf',
+      contentType,
       file,
       status: { type: 'requires-action', reason: 'composer-send' },
     }
@@ -217,13 +227,13 @@ class S3AttachmentAdapter {
 
     if (data.docId) this.lastDocId = data.docId
 
-    // Return the s3 URI as text content so the agent sees it
+    const uploadedKind = data.fileKind === 'image' ? 'image' : 'PDF'
     return {
       ...attachment,
       status: { type: 'complete' },
       content: [{
         type: 'text',
-        text: `Uploaded file: ${data.s3Uri}`,
+        text: `Uploaded ${uploadedKind} ready for analysis: ${data.s3Uri}`,
       }],
     }
   }
@@ -258,10 +268,16 @@ function ChatInner() {
   const adapter = useMemo(() => ({
     async *run({ messages, abortSignal }) {
       const lastUserMsg = [...messages].reverse().find(m => m.role === 'user')
-      const messageText = lastUserMsg?.content
+      const typedText = lastUserMsg?.content
         ?.filter(c => c.type === 'text')
         .map(c => c.text)
         .join('\n') || ''
+      const attachmentText = lastUserMsg?.attachments
+        ?.flatMap(attachment => attachment.content || [])
+        .filter(c => c.type === 'text')
+        .map(c => c.text)
+        .join('\n') || ''
+      const messageText = [typedText, attachmentText].filter(Boolean).join('\n')
 
       const res = await fetch('/api/chat', {
         method: 'POST',
@@ -271,7 +287,7 @@ function ChatInner() {
           session_id: sessionId,
           audit_mode: auditMode,
           dynamic_tokens: dynamicTokens,
-          // Empty until a PDF has been uploaded in this session; the agent
+          // Empty until a document or image has been uploaded in this session; the agent
           // treats an absent doc_id as "not attributable to a document".
           doc_id: attachmentAdapter.lastDocId,
         }),