Upload folder using huggingface_hub

.vscode/settings.json

@@ -9,5 +9,6 @@
     ],
     "terminal.integrated.env.windows": {
         "PYTHONPATH": "${workspaceFolder}"
-    }
+    },
+    "git.ignoreLimitWarning": true
 }

frontend/package-lock.json

@@ -1380,7 +1380,6 @@
       "version": "2.99.2",
       "resolved": "https://registry.npmjs.org/@supabase/supabase-js/-/supabase-js-2.99.2.tgz",
       "integrity": "sha512-179rn5wq0wBAqqGwAwR7TUGg2NOaP+fkd5FCVbYJXby85fsRNPFoNJN8YRBepqX2tN7JJcnTjqaAMXuNjiyisA==",
-      "license": "MIT",
       "dependencies": {
         "@supabase/auth-js": "2.99.2",
         "@supabase/functions-js": "2.99.2",

frontend/src/App.jsx

@@ -14,6 +14,7 @@ export default function App() {
   const [appState, setAppState] = useState('home');
   const [userName, setUserName] = useState('');
   const [authError, setAuthError] = useState('');
+  const [initialPolicyId, setInitialPolicyId] = useState(null);
 
   useEffect(() => {
     console.log("Current App State:", appState);
@@ -92,11 +93,11 @@ export default function App() {
 
   const toggleTheme = () => setIsDark(!isDark);
 
-  const handleUploadComplete = () => {
+  const handleUploadComplete = (policyId) => {
     // UploadModal already completed the upload — just navigate to dashboard.
-    // Previously we stored the file and passed it to Dboard as a prop, which
-    // caused Dboard's mount effect to call processFile() a second time.
-    console.log("Upload finished! Routing to Dboard...");
+    // We store the received policy_id so Dboard knows which policy to open automatically.
+    console.log("Upload finished! Routing to Dboard with policy:", policyId);
+    setInitialPolicyId(policyId);
     navigateTo('dboard');
   };
 
@@ -107,6 +108,7 @@ export default function App() {
         isDark={isDark}
         toggleTheme={toggleTheme}
         userName={userName}
+        initialPolicyId={initialPolicyId}
         onLogout={() => {
           setUserName('');
           navigateTo('home');

frontend/src/components/Dashboard/Dboard.jsx

@@ -211,6 +211,7 @@ export default function Dboard({ file, isDark: _initDark, userName = 'My Account
     const handleMouseMove = (e) => {
       if (!isResizingRef.current) return;
       e.preventDefault();
+      document.body.style.userSelect = 'none'; // Prevent text selection
       
       const dir = isResizingRef.current;
       setChatDimensions(prev => {
@@ -224,7 +225,10 @@ export default function Dboard({ file, isDark: _initDark, userName = 'My Account
       });
     };
     const handleMouseUp = () => {
-      isResizingRef.current = null;
+      if (isResizingRef.current) {
+        document.body.style.userSelect = '';
+        isResizingRef.current = null;
+      }
     };
     window.addEventListener('mousemove', handleMouseMove);
     window.addEventListener('mouseup', handleMouseUp);

frontend/src/components/Dashboard/UploadModal.jsx

@@ -137,6 +137,7 @@ export default function UploadModal({ onUploadComplete, onCancel }) {
   const [stage,      setStage]      = useState(-1);
   const [dark,       setDark]       = useState(false);
   const [backendMsg, setBackendMsg] = useState('');
+  const [processedPid, setProcessedPid] = useState(null);
 
   const fileRef    = useRef(null);
   const dragCounter = useRef(0);
@@ -185,6 +186,7 @@ export default function UploadModal({ onUploadComplete, onCancel }) {
           body: fd,
         });
         const pid = data.policy_id;
+        setProcessedPid(pid);
         setPct(20);
 
         // Poll for processing status every 2 s
@@ -230,11 +232,11 @@ export default function UploadModal({ onUploadComplete, onCancel }) {
       completedRef.current = true;
       const t1 = setTimeout(() => {
         setStatus('done');
-        setTimeout(() => onCompleteRef.current(file), 800);
+        setTimeout(() => onCompleteRef.current(processedPid), 800);
       }, 250);
       return () => clearTimeout(t1);
     }
-  }, [pct, status, file]); // ← onUploadComplete removed from deps
+  }, [pct, status, processedPid]); // ← onUploadComplete removed from deps
 
   const validateAndPick = useCallback((f) => {
     setError('');

rag_engine/embeddings/jina_embedder.py

@@ -40,13 +40,20 @@ class JinaEmbedder(BaseEmbedder):
         return self._call_api([text])[0]
 
     def embed_documents(self, texts: list[str]) -> list[list[float]]:
-        """Process in batches of 100 (Jina API limit)."""
-        all_embeddings: list[list[float]] = []
+        """Process in batches of 100 (Jina API limit) concurrently."""
+        from concurrent.futures import ThreadPoolExecutor
+        
         batch_size = 100
-
-        for i in range(0, len(texts), batch_size):
-            batch = texts[i : i + batch_size]
-            all_embeddings.extend(self._call_api(batch))
+        batches = [texts[i : i + batch_size] for i in range(0, len(texts), batch_size)]
+        
+        all_embeddings: list[list[float]] = []
+        
+        with ThreadPoolExecutor(max_workers=5) as executor:
+            # map preserves order
+            results = list(executor.map(self._call_api, batches))
+            
+        for r in results:
+            all_embeddings.extend(r)
 
         return all_embeddings
 

rag_engine/vector_store/supabase_store.py

@@ -27,21 +27,28 @@ class SupabaseVectorStore(BaseVectorStore):
     # ------------------------------------------------------------------ #
     @with_retry(max_retries=3, delay=1.0, backoff=2.0)
     def add_chunks(self, chunks: list[tuple[str, list[float], dict]]) -> None:
+        from concurrent.futures import ThreadPoolExecutor
+
         rows = [
             {"content": text, "embedding": vector, "metadata": meta}
             for text, vector, meta in chunks
         ]
         total = (len(rows) + _BATCH_SIZE - 1) // _BATCH_SIZE
-        for i in range(0, len(rows), _BATCH_SIZE):
-            batch = rows[i : i + _BATCH_SIZE]
-            batch_num = i // _BATCH_SIZE + 1
-            logger.info("Inserting batch %d/%d (%d rows) to Supabase...", batch_num, total, len(batch))
+        batches = [rows[i : i + _BATCH_SIZE] for i in range(0, len(rows), _BATCH_SIZE)]
+
+        def _insert_batch(batch_data: tuple[int, list[dict]]):
+            b_num, b_rows = batch_data
+            logger.info("Inserting batch %d/%d (%d rows) to Supabase...", b_num, total, len(b_rows))
             try:
-                res = self._client.table(self._table).insert(batch).execute()
-                logger.info("Batch %d/%d stored successfully (%d rows)", batch_num, total, len(batch))
+                self._client.table(self._table).insert(b_rows).execute()
+                logger.info("Batch %d/%d stored successfully (%d rows)", b_num, total, len(b_rows))
             except Exception as e:
-                logger.error("FAILED to store batch %d/%d: %s", batch_num, total, str(e))
+                logger.error("FAILED to store batch %d/%d: %s", b_num, total, str(e))
                 raise e
+
+        with ThreadPoolExecutor(max_workers=5) as executor:
+            list(executor.map(_insert_batch, [(i + 1, b) for i, b in enumerate(batches)]))
+            
         logger.info("Successfully stored %d chunks in Supabase", len(chunks))
 
     # ------------------------------------------------------------------ #