Improve CV parsing and profile editor flow

deploy/README.md

@@ -52,6 +52,8 @@ AUTH_ADMIN_EMAIL=you@example.com
 AUTH_ADMIN_PASSWORD=replace_with_strong_password
 APP_PUBLIC_BASE_URL=https://your-domain.example
 AI_SERVICE_BASE_URL=http://ai-service:8001
+OLLAMA_BASE_URL=http://ollama:11434
+OLLAMA_MODEL=qwen2.5:7b
 EMAIL_FOLLOWUPREMINDERS_ENABLED=true
 EMAIL_FOLLOWUPREMINDERS_UPCOMINGDAYS=2
 # Optional backward-compatible alias if older config still references the previous name:
@@ -87,7 +89,8 @@ If this app is going to be a real production service on Ubuntu:
 2. Gitea Actions runs tests
 3. if green, workflow uploads repo to server
 4. `deploy/deploy.sh` links `/opt/job-tracker/shared/.env` into the repo checkout, then runs `docker compose build && docker compose up -d`
-5. workflow checks service status after deployment
+5. if `OLLAMA_MODEL` is set, the deploy script waits for Ollama, pulls the configured model if missing, then restarts `ai-service` so hybrid CV classification can use it
+6. workflow checks service status after deployment
 
 ## Post-deploy verification you should also do manually the first time
 - confirm reverse proxy routes to the frontend correctly
@@ -96,3 +99,4 @@ If this app is going to be a real production service on Ubuntu:
 - confirm AI service container is reachable from backend
 - confirm reminder and admin/system pages load
 - verify follow-up reminder emails are enabled only when intended and that links open the correct job/tab
+hat links open the correct job/tab

deploy/deploy.sh

@@ -45,6 +45,11 @@ build_with_recovery
 # Force recreation so updated port mappings, env vars, and container config always apply on deploy.
 compose up -d --force-recreate --remove-orphans
 
+if [ -n "${OLLAMA_MODEL:-}" ]; then
+  echo "Post-deploy Ollama warmup enabled for model: ${OLLAMA_MODEL}"
+  ./scripts/start-ollama-cv.sh
+fi
+
 sleep 5
 compose ps