minor bug fixes

backend/app/routes/ai_summary.py

@@ -9,6 +9,7 @@ from sqlalchemy import select
 from typing import List
 from uuid import UUID
 import logging
+import os
 
 from app.db import get_db
 from app.security import get_current_user
@@ -53,22 +54,35 @@ async def list_reports_for_summary(
     result = await db.execute(query)
     reports = result.scalars().all()
     
-    response = []
+    response: List[ReportForSummary] = []
     for report in reports:
-        # Build preview URL based on file path
-        preview_url = f"/api/reports/{report.id}/file"
+        # Skip reports whose underlying file is missing on disk
+        if not report.file_path or not os.path.exists(report.file_path):
+            logger.warning(
+                "AI Summary: skipping report %s (%s) because file is missing at %s",
+                report.id,
+                report.filename,
+                report.file_path,
+            )
+            continue
+
+        # Build preview URL based on AI summary file endpoint
+        # Note: this route is defined on the /api/ai router (see get_report_file below)
+        preview_url = f"/api/ai/reports/{report.id}/file"
         
-        response.append(ReportForSummary(
-            id=report.id,
-            filename=report.filename,
-            category=report.category,
-            doc_type=report.doc_type,
-            report_date=report.report_date,
-            uploaded_at=report.uploaded_at,
-            file_path=report.file_path,
-            file_type=report.file_type,
-            preview_url=preview_url
-        ))
+        response.append(
+            ReportForSummary(
+                id=report.id,
+                filename=report.filename,
+                category=report.category,
+                doc_type=report.doc_type,
+                report_date=report.report_date,
+                uploaded_at=report.uploaded_at,
+                file_path=report.file_path,
+                file_type=report.file_type,
+                preview_url=preview_url,
+            )
+        )
     
     return response
 
@@ -99,20 +113,25 @@ async def get_report_file(
     if not os.path.exists(report.file_path):
         raise HTTPException(status_code=404, detail="File not found on disk")
     
-    # Determine media type
+    # Determine media type. Note: in the new pipeline `file_type` is stored
+    # without the leading dot (e.g. "pdf"), while older records may still
+    # include the dot (".pdf"), so we normalize.
     media_types = {
-        '.pdf': 'application/pdf',
-        '.png': 'image/png',
-        '.jpg': 'image/jpeg',
-        '.jpeg': 'image/jpeg',
-        '.tiff': 'image/tiff'
+        'pdf': 'application/pdf',
+        'png': 'image/png',
+        'jpg': 'image/jpeg',
+        'jpeg': 'image/jpeg',
+        'tiff': 'image/tiff',
     }
-    media_type = media_types.get(report.file_type, 'application/octet-stream')
+    normalized_type = (report.file_type or '').lstrip('.').lower()
+    media_type = media_types.get(normalized_type, 'application/octet-stream')
     
+    # Return inline so the browser renders in an <iframe> instead of forcing download
     return FileResponse(
         report.file_path,
         media_type=media_type,
-        filename=report.filename
+        filename=report.filename,
+        content_disposition_type="inline",
     )
 
 

backend/app/services/rag_service.py

@@ -33,6 +33,7 @@ class RAGService:
         self._client = None
         self._collection = None
         self._embedding_model = None
+        self._embedding_available = True  # Disable gracefully on failure
     
     def _get_client(self):
         """Lazy initialization of ChromaDB client."""
@@ -61,9 +62,21 @@ class RAGService:
     
     def _get_embedding_model(self):
         """Lazy initialization of embedding model."""
+        if not self._embedding_available:
+            raise RuntimeError("Embedding model is disabled due to previous initialization failure")
+
         if self._embedding_model is None:
-            from sentence_transformers import SentenceTransformer
-            self._embedding_model = SentenceTransformer(settings.EMBEDDING_MODEL)
+            try:
+                from sentence_transformers import SentenceTransformer
+                logger.info(f"Initializing embedding model: {settings.EMBEDDING_MODEL}")
+                self._embedding_model = SentenceTransformer(settings.EMBEDDING_MODEL)
+            except Exception as e:
+                # If the model can't be loaded (no internet, HF issue, etc.),
+                # disable embeddings so the rest of the app can continue.
+                self._embedding_available = False
+                logger.error(f"Failed to initialize embedding model '{settings.EMBEDDING_MODEL}': {e}")
+                raise RuntimeError("Embedding model initialization failed") from e
+
         return self._embedding_model
     
     def _embed_texts(self, texts: List[str]) -> List[List[float]]:
@@ -82,6 +95,7 @@ class RAGService:
             return [list(e) for e in embeddings]
         except Exception as e:
             logger.error(f"Embedding failed: {e}")
+            # Propagate a clean error so callers can gracefully fall back
             raise ValueError(f"Failed to embed texts: {e}")
     
     async def sync_user_reports(self, user_id: uuid.UUID, db: AsyncSession) -> int:
@@ -269,11 +283,20 @@ class RAGService:
         """
         # First, ensure user data is synced (if db provided)
         if db:
-            await self.sync_user_reports(user_id, db)
-            await self.sync_user_observations(user_id, db)
+            try:
+                await self.sync_user_reports(user_id, db)
+                await self.sync_user_observations(user_id, db)
+            except Exception as e:
+                # If syncing fails (embeddings/model/Chroma issues), log and continue.
+                logger.warning(f"RAG sync failed for user {user_id}: {e}")
         
-        # Query for relevant documents
-        docs = await self.query(user_id, query)
+        try:
+            # Query for relevant documents
+            docs = await self.query(user_id, query)
+        except Exception as e:
+            # If RAG fails (e.g. embeddings unavailable, Chroma issue), fall back
+            logger.warning(f"RAG context unavailable for user {user_id}: {e}")
+            return "No health data available for this user yet."
         
         if not docs:
             return "No health data available for this user yet."

frontend/src/components/AuthShell.jsx

@@ -1,5 +1,6 @@
 import { motion } from 'framer-motion'
 import { Link } from 'react-router-dom'
+import Logo from './ui/Logo'
 import './AuthShell.css'
 
 function AuthShell({ children, title, subtitle, footerText, footerLink, footerLinkText }) {
@@ -13,8 +14,7 @@ function AuthShell({ children, title, subtitle, footerText, footerLink, footerLi
           transition={{ duration: 0.6 }}
         >
           <Link to="/" className="auth-logo">
-            <span className="logo-main">Co-Code</span>
-            <span className="logo-sub">GGW</span>
+            <Logo variant="header" />
           </Link>
         </motion.div>
 

frontend/src/components/AuthShell.tsx

@@ -3,6 +3,7 @@ import { Link } from 'react-router-dom'
 import { ReactNode } from 'react'
 import './AuthShell.css'
 
+
 interface AuthShellProps {
   children: ReactNode
   title: string

frontend/src/components/Hero.tsx

@@ -56,7 +56,7 @@ function Hero() {
           >
             {t('hero.tagline')}
             <br />
-            is <motion.span 
+            <motion.span 
               className="highlight"
               initial={{ scale: 0, opacity: 0 }}
               animate={{ scale: 1, opacity: 1 }}

frontend/src/i18n/locales/en.json

@@ -11,8 +11,8 @@
     "cta": "Get Started"
   },
   "hero": {
-    "tagline": "First priority is",
-    "taglineHighlight": "your health",
+    "tagline": "Your health",
+    "taglineHighlight": "comes first",
     "subtitle": "Track it. Understand it. Prevent it.",
     "description": "Upload your lab reports, get them interpreted, and receive smart reminders for checkups + medicines. Lumea helps you stay preventive—without becoming your doctor.",
     "disclaimer": "Not medical advice. Always consult a licensed clinician for diagnosis/treatment.",