fix model runtime quota

Fix issue with incorrect port number in app_base_url due to NAT networks (#6653 )
2026-01-23 13:35:35 +08:00 · 2024-08-12 17:09:09 +08:00 · 2024-08-12 15:57:53 +08:00 · 2024-08-12 12:26:12 +08:00 · 2024-08-12 11:28:26 +08:00 · 2024-08-12 11:25:10 +08:00
267 changed files with 9302 additions and 2226 deletions
--- a/README.md
+++ b/README.md
@ -4,7 +4,7 @@
  <a href="https://cloud.dify.ai">Dify Cloud</a> ·
  <a href="https://docs.dify.ai/getting-started/install-self-hosted">Self-hosting</a> ·
  <a href="https://docs.dify.ai">Documentation</a> ·
-  <a href="https://cal.com/guchenhe/60-min-meeting">Enterprise inquiry</a>
+  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">Enterprise inquiry</a>
 </p>

 <p align="center">
@ -38,6 +38,7 @@
  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
  <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
  <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
+  <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
 </p>


@ -151,7 +152,7 @@ Quickly get Dify running in your environment with this [starter guide](#quick-st
 Use our [documentation](https://docs.dify.ai) for further references and more in-depth instructions.

 - **Dify for enterprise / organizations</br>**
-We provide additional enterprise-centric features. [Schedule a meeting with us](https://cal.com/guchenhe/30min) or [send us an email](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) to discuss enterprise needs. </br>
+We provide additional enterprise-centric features. [Log your questions for us through this chatbot](https://udify.app/chat/22L1zSxg6yW1cWQg) or [send us an email](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) to discuss enterprise needs. </br>
  > For startups and small businesses using AWS, check out [Dify Premium on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) and deploy it to your own AWS VPC with one-click. It's an affordable AMI offering with the option to create apps with custom logo and branding.


@ -220,23 +221,6 @@ At the same time, please consider supporting Dify by sharing it on social media
 * [Discord](https://discord.gg/FngNHpbcY7). Best for: sharing your applications and hanging out with the community.
 * [Twitter](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.

-Or, schedule a meeting directly with a team member:
-
-<table>
-  <tr>
-    <th>Point of Contact</th>
-    <th>Purpose</th>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/guchenhe/15min' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/9ebcd111-1205-4d71-83d5-948d70b809f5' alt='Git-Hub-README-Button-3x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>Business enquiries & product feedback</td>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/pinkbanana' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/d1edd00a-d7e4-4513-be6c-e57038e143fd' alt='Git-Hub-README-Button-2x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>Contributions, issues & feature requests</td>
-  </tr>
-</table>
-
 ## Star history

 [![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
--- a/README_AR.md
+++ b/README_AR.md
@ -4,7 +4,7 @@
  <a href="https://cloud.dify.ai">Dify Cloud</a> ·
  <a href="https://docs.dify.ai/getting-started/install-self-hosted">الاستضافة الذاتية</a> ·
  <a href="https://docs.dify.ai">التوثيق</a> ·
-  <a href="https://cal.com/guchenhe/60-min-meeting">استفسارات الشركات</a>
+  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">استفسار الشركات (للإنجليزية فقط)</a>
 </p>

 <p align="center">
@ -38,6 +38,7 @@
  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
  <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
  <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
+  <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
 </p>

 <div style="text-align: right;">
@ -203,23 +204,6 @@ docker compose up -d
 * [Discord](https://discord.gg/FngNHpbcY7). الأفضل لـ: مشاركة تطبيقاتك والترفيه مع المجتمع.
 * [تويتر](https://twitter.com/dify_ai). الأفضل لـ: مشاركة تطبيقاتك والترفيه مع المجتمع.

-أو، قم بجدولة اجتماع مباشرة مع أحد أعضاء الفريق:
-
-<table>
-  <tr>
-    <th>نقطة الاتصال</th>
-    <th>الغرض</th>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/guchenhe/15min' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/9ebcd111-1205-4d71-83d5-948d70b809f5' alt='Git-Hub-README-Button-3x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>استفسارات الأعمال واقتراحات حول المنتج</td>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/pinkbanana' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/d1edd00a-d7e4-4513-be6c-e57038e143fd' alt='Git-Hub-README-Button-2x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>المساهمات والمشكلات وطلبات الميزات</td>
-  </tr>
-</table>
-
 ## تاريخ النجمة

 [![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
--- a/README_CN.md
+++ b/README_CN.md
@ -4,7 +4,7 @@
  <a href="https://cloud.dify.ai">Dify 云服务</a> ·
  <a href="https://docs.dify.ai/getting-started/install-self-hosted">自托管</a> ·
  <a href="https://docs.dify.ai">文档</a> ·
-  <a href="https://cal.com/guchenhe/dify-demo">预约演示</a>
+  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">（需用英文）常见问题解答 / 联系团队</a>
 </div>

 <p align="center">
@ -29,14 +29,16 @@
 </p>

 <div align="center">
-  <a href="./README.md"><img alt="上个月的提交次数" src="https://img.shields.io/badge/英文-d9d9d9"></a>
-  <a href="./README_CN.md"><img alt="上个月的提交次数" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
-  <a href="./README_JA.md"><img alt="上个月的提交次数" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
-  <a href="./README_ES.md"><img alt="上个月的提交次数" src="https://img.shields.io/badge/西班牙语-d9d9d9"></a>
-  <a href="./README_KL.md"><img alt="上个月的提交次数" src="https://img.shields.io/badge/法语-d9d9d9"></a>
-  <a href="./README_FR.md"><img alt="上个月的提交次数" src="https://img.shields.io/badge/克林贡语-d9d9d9"></a>
-  <a href="./README_KR.md"><img alt="上个月的提交次数" src="https://img.shields.io/badge/韓國語-d9d9d9"></a>
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
+  <a href="./README_CN.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
+  <a href="./README_JA.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
+  <a href="./README_ES.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
+  <a href="./README_FR.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README_KL.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
+  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
  <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
+  <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
 </div>


@ -156,7 +158,7 @@ Dify 是一个开源的 LLM 应用开发平台。其直观的界面结合了 AI
 使用我们的[文档](https://docs.dify.ai)进行进一步的参考和更深入的说明。

 - **面向企业/组织的 Dify</br>**
-我们提供额外的面向企业的功能。[与我们安排会议](https://cal.com/guchenhe/30min)或[给我们发送电子邮件](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry)讨论企业需求。 </br>
+我们提供额外的面向企业的功能。[给我们发送电子邮件](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry)讨论企业需求。 </br>
  > 对于使用 AWS 的初创公司和中小型企业，请查看 [AWS Marketplace 上的 Dify 高级版](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6)，并使用一键部署到您自己的 AWS VPC。它是一个价格实惠的 AMI 产品，提供了使用自定义徽标和品牌创建应用程序的选项。

 ## 保持领先
--- a/README_ES.md
+++ b/README_ES.md
@ -4,7 +4,7 @@
  <a href="https://cloud.dify.ai">Dify Cloud</a> ·
  <a href="https://docs.dify.ai/getting-started/install-self-hosted">Auto-alojamiento</a> ·
  <a href="https://docs.dify.ai">Documentación</a> ·
-  <a href="https://cal.com/guchenhe/dify-demo">Programar demostración</a>
+  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">Consultas empresariales (en inglés)</a>
 </p>

 <p align="center">
@ -29,14 +29,16 @@
 </p>

 <p align="center">
-  <a href="./README.md"><img alt="Actividad de Commits el último mes" src="https://img.shields.io/badge/Inglés-d9d9d9"></a>
-  <a href="./README_CN.md"><img alt="Actividad de Commits el último mes" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
-  <a href="./README_JA.md"><img alt="Actividad de Commits el último mes" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
-  <a href="./README_ES.md"><img alt="Actividad de Commits el último mes" src="https://img.shields.io/badge/Español-d9d9d9"></a>
-  <a href="./README_KL.md"><img alt="Actividad de Commits el último mes" src="https://img.shields.io/badge/Français-d9d9d9"></a>
-  <a href="./README_FR.md"><img alt="Actividad de Commits el último mes" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
-  <a href="./README_KR.md"><img alt="Actividad de Commits el último mes" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
+  <a href="./README_CN.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
+  <a href="./README_JA.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
+  <a href="./README_ES.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
+  <a href="./README_FR.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README_KL.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
+  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
  <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
+  <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
 </p>

 #
@ -156,7 +158,7 @@ Pon rápidamente Dify en funcionamiento en tu entorno con esta [guía de inicio
 Usa nuestra [documentación](https://docs.dify.ai) para más referencias e instrucciones más detalladas.

 - **Dify para Empresas / Organizaciones</br>**
-Proporcionamos características adicionales centradas en la empresa. [Programa una reunión con nosotros](https://cal.com/guchenhe/30min) o [envíanos un correo electrónico](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) para discutir las necesidades empresariales. </br>
+Proporcionamos características adicionales centradas en la empresa. [Envíanos un correo electrónico](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) para discutir las necesidades empresariales. </br>
  > Para startups y pequeñas empresas que utilizan AWS, echa un vistazo a [Dify Premium en AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) e impleméntalo en tu propio VPC de AWS con un clic. Es una AMI asequible que ofrece la opción de crear aplicaciones con logotipo y marca personalizados.


@ -228,23 +230,6 @@ Al mismo tiempo, considera apoyar a Dify compartiéndolo en redes sociales y en
 * [Discord](https://discord.gg/FngNHpbcY7). Lo mejor para: compartir tus aplicaciones y pasar el rato con la comunidad.
 * [Twitter](https://twitter.com/dify_ai). Lo mejor para: compartir tus aplicaciones y pasar el rato con la comunidad.

-O, programa una reunión directamente con un miembro del equipo:
-
-<table>
-  <tr>
-    <th>Punto de Contacto</th>
-    <th>Propósito</th>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/guchenhe/15min' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/9ebcd111-1205-4d71-83d5-948d70b809f5' alt='Git-Hub-README-Button-3x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>Consultas comerciales y retroalimentación del producto</td>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/pinkbanana' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/d1edd00a-d7e4-4513-be6c-e57038e143fd' alt='Git-Hub-README-Button-2x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>Contribuciones, problemas y solicitudes de características</td>
-  </tr>
-</table>
-
 ## Historial de Estrellas

 [![Gráfico de Historial de Estrellas](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
--- a/README_FR.md
+++ b/README_FR.md
@ -4,7 +4,7 @@
  <a href="https://cloud.dify.ai">Dify Cloud</a> ·
  <a href="https://docs.dify.ai/getting-started/install-self-hosted">Auto-hébergement</a> ·
  <a href="https://docs.dify.ai">Documentation</a> ·
-  <a href="https://cal.com/guchenhe/dify-demo">Planifier une démo</a>
+  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">Demande d’entreprise (en anglais seulement)</a>
 </p>

 <p align="center">
@ -29,14 +29,16 @@
 </p>

 <p align="center">
-  <a href="./README.md"><img alt="Commits le mois dernier" src="https://img.shields.io/badge/Anglais-d9d9d9"></a>
-  <a href="./README_CN.md"><img alt="Commits le mois dernier" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
-  <a href="./README_JA.md"><img alt="Commits le mois dernier" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
-  <a href="./README_ES.md"><img alt="Commits le mois dernier" src="https://img.shields.io/badge/Español-d9d9d9"></a>
-  <a href="./README_KL.md"><img alt="Commits le mois dernier" src="https://img.shields.io/badge/Français-d9d9d9"></a>
-  <a href="./README_FR.md"><img alt="Commits le mois dernier" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
-  <a href="./README_KR.md"><img alt="Commits le mois dernier" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
+  <a href="./README_CN.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
+  <a href="./README_JA.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
+  <a href="./README_ES.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
+  <a href="./README_FR.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README_KL.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
+  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
  <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
+  <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
 </p>

 #
@ -156,7 +158,7 @@ Lancez rapidement Dify dans votre environnement avec ce [guide de démarrage](#q
 Utilisez notre [documentation](https://docs.dify.ai) pour plus de références et des instructions plus détaillées.

 - **Dify pour les entreprises / organisations</br>**
-Nous proposons des fonctionnalités supplémentaires adaptées aux entreprises. [Planifiez une réunion avec nous](https://cal.com/guchenhe/30min) ou [envoyez-nous un e-mail](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) pour discuter des besoins de l'entreprise. </br>
+Nous proposons des fonctionnalités supplémentaires adaptées aux entreprises. [Envoyez-nous un e-mail](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) pour discuter des besoins de l'entreprise. </br>
  > Pour les startups et les petites entreprises utilisant AWS, consultez [Dify Premium sur AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) et déployez-le dans votre propre VPC AWS en un clic. C'est une offre AMI abordable avec la possibilité de créer des applications avec un logo et une marque personnalisés.


@ -226,23 +228,6 @@ Dans le même temps, veuillez envisager de soutenir Dify en le partageant sur le
 * [Discord](https://discord.gg/FngNHpbcY7). Meilleur pour: partager vos applications et passer du temps avec la communauté.
 * [Twitter](https://twitter.com/dify_ai). Meilleur pour: partager vos applications et passer du temps avec la communauté.

-Ou, planifiez directement une réunion avec un membre de l'équipe:
-
-<table>
-  <tr>
-    <th>Point de contact</th>
-    <th>Objectif</th>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/guchenhe/15min' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/9ebcd111-1205-4d71-83d5-948d70b809f5' alt='Git-Hub-README-Button-3x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>Demandes commerciales & retours produit</td>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/pinkbanana' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/d1edd00a-d7e4-4513-be6c-e57038e143fd' alt='Git-Hub-README-Button-2x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>Contributions, problèmes & demandes de fonctionnalités</td>
-  </tr>
-</table>
-
 ## Historique des étoiles

 [![Graphique de l'historique des étoiles](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
--- a/README_JA.md
+++ b/README_JA.md
@ -4,7 +4,7 @@
  <a href="https://cloud.dify.ai">Dify Cloud</a> ·
  <a href="https://docs.dify.ai/getting-started/install-self-hosted">セルフホスティング</a> ·
  <a href="https://docs.dify.ai">ドキュメント</a> ·
-  <a href="https://cal.com/guchenhe/dify-demo">デモの予約</a>
+  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">企業のお問い合わせ（英語のみ）</a>
 </p>

 <p align="center">
@ -29,14 +29,16 @@
 </p>

 <p align="center">
-  <a href="./README.md"><img alt="先月のコミット" src="https://img.shields.io/badge/English-d9d9d9"></a>
-  <a href="./README_CN.md"><img alt="先月のコミット" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
-  <a href="./README_JA.md"><img alt="先月のコミット" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
-  <a href="./README_ES.md"><img alt="先月のコミット" src="https://img.shields.io/badge/Español-d9d9d9"></a>
-  <a href="./README_KL.md"><img alt="先月のコミット" src="https://img.shields.io/badge/Français-d9d9d9"></a>
-  <a href="./README_FR.md"><img alt="先月のコミット" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
-  <a href="./README_KR.md"><img alt="先月のコミット" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
+  <a href="./README_CN.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
+  <a href="./README_JA.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
+  <a href="./README_ES.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
+  <a href="./README_FR.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README_KL.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
+  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
  <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
+  <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
 </p>

 #
@ -155,7 +157,7 @@ DifyはオープンソースのLLMアプリケーション開発プラットフ
 詳しくは[ドキュメント](https://docs.dify.ai)をご覧ください。

 - **企業/組織向けのDify</br>**
-企業中心の機能を提供しています。[こちらからミーティングを予約](https://cal.com/guchenhe/30min)したり、[メールを送信](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry)して企業のニーズについて相談してください。 </br>
+企業中心の機能を提供しています。[メールを送信](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry)して企業のニーズについて相談してください。 </br>
  > AWSを使用しているスタートアップ企業や中小企業の場合は、[AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6)のDify Premiumをチェックして、ワンクリックで自分のAWS VPCにデプロイできます。さらに、手頃な価格のAMIオファリングどして、ロゴやブランディングをカスタマイズしてアプリケーションを作成するオプションがあります。


@ -225,28 +227,6 @@ docker compose up -d
 * [Discord](https://discord.gg/FngNHpbcY7). 主に: アプリケーションの共有やコミュニティとの交流。
 * [Twitter](https://twitter.com/dify_ai). 主に: アプリケーションの共有やコミュニティとの交流。

-または、直接チームメンバーとミーティングをスケジュール：
-
-<table>
-  <tr>
-    <th>連絡先</th>
-    <th>目的</th>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com
-
-/guchenhe/30min'>ミーティング</a></td>
-    <td>無料の30分間のミーティングをスケジュール</td>
-  </tr>
-  <tr>
-    <td><a href='https://github.com/langgenius/dify/issues'>技術サポート</a></td>
-    <td>技術的な問題やサポートに関する質問</td>
-  </tr>
-  <tr>
-    <td><a href='mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry'>営業担当</a></td>
-    <td>法人ライセンスに関するお問い合わせ</td>
-  </tr>
-</table>


 ## ライセンス
--- a/README_KL.md
+++ b/README_KL.md
@ -4,7 +4,7 @@
  <a href="https://cloud.dify.ai">Dify Cloud</a> ·
  <a href="https://docs.dify.ai/getting-started/install-self-hosted">Self-hosting</a> ·
  <a href="https://docs.dify.ai">Documentation</a> ·
-  <a href="https://cal.com/guchenhe/dify-demo">Schedule demo</a>
+  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">Commercial enquiries</a>
 </p>

 <p align="center">
@ -29,14 +29,16 @@
 </p>

 <p align="center">
-  <a href="./README.md"><img alt="Commits last month" src="https://img.shields.io/badge/English-d9d9d9"></a>
-  <a href="./README_CN.md"><img alt="Commits last month" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
-  <a href="./README_JA.md"><img alt="Commits last month" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
-  <a href="./README_ES.md"><img alt="Commits last month" src="https://img.shields.io/badge/Español-d9d9d9"></a>
-  <a href="./README_KL.md"><img alt="Commits last month" src="https://img.shields.io/badge/Français-d9d9d9"></a>
-  <a href="./README_FR.md"><img alt="Commits last month" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
-  <a href="./README_KR.md"><img alt="Commits last month" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
+  <a href="./README_CN.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
+  <a href="./README_JA.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
+  <a href="./README_ES.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
+  <a href="./README_FR.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README_KL.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
+  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
  <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
+  <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
 </p>

 #
@ -156,7 +158,7 @@ Quickly get Dify running in your environment with this [starter guide](#quick-st
 Use our [documentation](https://docs.dify.ai) for further references and more in-depth instructions.

 - **Dify for Enterprise / Organizations</br>**
-We provide additional enterprise-centric features. [Schedule a meeting with us](https://cal.com/guchenhe/30min) or [send us an email](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) to discuss enterprise needs. </br>
+We provide additional enterprise-centric features. [Send us an email](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) to discuss enterprise needs. </br>
  > For startups and small businesses using AWS, check out [Dify Premium on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) and deploy it to your own AWS VPC with one-click. It's an affordable AMI offering with the option to create apps with custom logo and branding.


@ -228,23 +230,6 @@ At the same time, please consider supporting Dify by sharing it on social media
 * [Discord](https://discord.gg/FngNHpbcY7). Best for: sharing your applications and hanging out with the community.
 * [Twitter](https://twitter.com/dify_ai). Best for: sharing your applications and hanging out with the community.

-Or, schedule a meeting directly with a team member:
-
-<table>
-  <tr>
-    <th>Point of Contact</th>
-    <th>Purpose</th>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/guchenhe/15min' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/9ebcd111-1205-4d71-83d5-948d70b809f5' alt='Git-Hub-README-Button-3x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>Business enquiries & product feedback</td>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/pinkbanana' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/d1edd00a-d7e4-4513-be6c-e57038e143fd' alt='Git-Hub-README-Button-2x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>Contributions, issues & feature requests</td>
-  </tr>
-</table>
-
 ## Star History

 [![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
--- a/README_KR.md
+++ b/README_KR.md
@ -4,7 +4,7 @@
  <a href="https://cloud.dify.ai">Dify 클라우드</a> ·
  <a href="https://docs.dify.ai/getting-started/install-self-hosted">셀프-호스팅</a> ·
  <a href="https://docs.dify.ai">문서</a> ·
-  <a href="https://cal.com/guchenhe/60-min-meeting">기업 문의</a>
+  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">기업 문의 (영어만 가능)</a>
 </p>

 <p align="center">
@ -35,8 +35,10 @@
  <a href="./README_ES.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
  <a href="./README_FR.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
  <a href="./README_KL.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
-  <a href="./README_KR.md"><img alt="한국어 README" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
  <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
+  <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>

 </p>

@ -149,7 +151,7 @@
  추가 참조 및 더 심층적인 지침은 [문서](https://docs.dify.ai)를 사용하세요.

 - **기업 / 조직을 위한 Dify</br>**
-  우리는 추가적인 기업 중심 기능을 제공합니다. 당사와 [미팅일정](https://cal.com/guchenhe/30min)을 잡거나  [이메일 보내기](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry)를 통해 기업 요구 사항을 논의하십시오. </br>
+  우리는 추가적인 기업 중심 기능을 제공합니다. 잡거나  [이메일 보내기](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry)를 통해 기업 요구 사항을 논의하십시오. </br>
  > AWS를 사용하는 스타트업 및 중소기업의 경우 [AWS Marketplace에서 Dify Premium](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6)을 확인하고 한 번의 클릭으로 자체 AWS VPC에 배포하십시오. 맞춤형 로고와 브랜딩이 포함된 앱을 생성할 수 있는 옵션이 포함된 저렴한 AMI 제품입니다.


@ -218,22 +220,6 @@ Dify를 Kubernetes에 배포하고 프리미엄 스케일링 설정을 구성했
 * [디스코드](https://discord.gg/FngNHpbcY7). 애플리케이션 공유 및 커뮤니티와 소통하기에 적합합니다.
 * [트위터](https://twitter.com/dify_ai). 애플리케이션 공유 및 커뮤니티와 소통하기에 적합합니다.

-또는 팀원과 직접 미팅을 예약하세요:
-
-<table>
-  <tr>
-    <th>연락처</th>
-    <th>목적</th>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/guchenhe/15min' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/9ebcd111-1205-4d71-83d5-948d70b809f5' alt='Git-Hub-README-Button-3x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>비즈니스 문의 및 제품 피드백</td>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/pinkbanana' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/d1edd00a-d7e4-4513-be6c-e57038e143fd' alt='Git-Hub-README-Button-2x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>기여, 이슈 및 기능 요청</td>
-  </tr>
-</table>

 ## Star 히스토리

--- a/README_TR.md
+++ b/README_TR.md
@ -4,7 +4,7 @@
  <a href="https://cloud.dify.ai">Dify Bulut</a> ·
  <a href="https://docs.dify.ai/getting-started/install-self-hosted">Kendi Sunucunuzda Barındırma</a> ·
  <a href="https://docs.dify.ai">Dokümantasyon</a> ·
-  <a href="https://cal.com/guchenhe/60-min-meeting">Kurumsal Sorgu</a>
+  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">Yalnızca İngilizce: Kurumsal Sorgulama</a>
 </p>

 <p align="center">
@ -38,6 +38,7 @@
  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
  <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
  <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
+  <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
 </p>


@ -155,7 +156,7 @@ Bu [başlangıç kılavuzu](#quick-start) ile Dify'ı kendi ortamınızda hızl
 Daha fazla referans ve detaylı talimatlar için [dokümantasyonumuzu](https://docs.dify.ai) kullanın.

 - **Kurumlar / organizasyonlar için Dify</br>**
-Ek kurumsal odaklı özellikler sunuyoruz. Kurumsal ihtiyaçları görüşmek için [bizimle bir toplantı planlayın](https://cal.com/guchenhe/30min) veya [bize bir e-posta gönderin](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry). </br>
+Ek kurumsal odaklı özellikler sunuyoruz. Kurumsal ihtiyaçları görüşmek için [bize bir e-posta gönderin](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry). </br>
  > AWS kullanan startuplar ve küçük işletmeler için, [AWS Marketplace'deki Dify Premium'a](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) göz atın ve tek tıklamayla kendi AWS VPC'nize dağıtın. Bu, özel logo ve marka ile uygulamalar oluşturma seçeneğine sahip uygun fiyatlı bir AMI teklifdir.

 ## Güncel Kalma
@ -223,23 +224,6 @@ Aynı zamanda, lütfen Dify'ı sosyal medyada, etkinliklerde ve konferanslarda p
 * [Discord](https://discord.gg/FngNHpbcY7). En uygun: uygulamalarınızı paylaşmak ve toplulukla vakit geçirmek için.
 * [Twitter](https://twitter.com/dify_ai). En uygun: uygulamalarınızı paylaşmak ve toplulukla vakit geçirmek için.

-Veya doğrudan bir ekip üyesiyle toplantı planlayın:
-
-<table>
-  <tr>
-    <th>İletişim Noktası</th>
-    <th>Amaç</th>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/guchenhe/15min' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/9ebcd111-1205-4d71-83d5-948d70b809f5' alt='Git-Hub-README-Button-3x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>İş sorgulamaları & ürün geri bildirimleri</td>
-  </tr>
-  <tr>
-    <td><a href='https://cal.com/pinkbanana' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/d1edd00a-d7e4-4513-be6c-e57038e143fd' alt='Git-Hub-README-Button-2x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
-    <td>Katkılar, sorunlar & özellik istekleri</td>
-  </tr>
-</table>
-
 ## Star history

 [![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
--- a/README_VI.md
+++ b/README_VI.md
@ -0,0 +1,251 @@
+![cover-v5-optimized](https://github.com/langgenius/dify/assets/13230914/f9e19af5-61ba-4119-b926-d10c4c06ebab)
+
+<p align="center">
+  <a href="https://cloud.dify.ai">Dify Cloud</a> ·
+  <a href="https://docs.dify.ai/getting-started/install-self-hosted">Tự triển khai</a> ·
+  <a href="https://docs.dify.ai">Tài liệu</a> ·
+  <a href="https://udify.app/chat/22L1zSxg6yW1cWQg">Yêu cầu doanh nghiệp</a>
+</p>
+
+<p align="center">
+    <a href="https://dify.ai" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/Product-F04438"></a>
+    <a href="https://dify.ai/pricing" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/free-pricing?logo=free&color=%20%23155EEF&label=pricing&labelColor=%20%23528bff"></a>
+    <a href="https://discord.gg/FngNHpbcY7" target="_blank">
+        <img src="https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb"
+            alt="chat trên Discord"></a>
+    <a href="https://twitter.com/intent/follow?screen_name=dify_ai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/dify_ai?logo=X&color=%20%23f5f5f5"
+            alt="theo dõi trên Twitter"></a>
+    <a href="https://hub.docker.com/u/langgenius" target="_blank">
+        <img alt="Docker Pulls" src="https://img.shields.io/docker/pulls/langgenius/dify-web?labelColor=%20%23FDB062&color=%20%23f79009"></a>
+    <a href="https://github.com/langgenius/dify/graphs/commit-activity" target="_blank">
+        <img alt="Commits tháng trước" src="https://img.shields.io/github/commit-activity/m/langgenius/dify?labelColor=%20%2332b583&color=%20%2312b76a"></a>
+    <a href="https://github.com/langgenius/dify/" target="_blank">
+        <img alt="Vấn đề đã đóng" src="https://img.shields.io/github/issues-search?query=repo%3Alanggenius%2Fdify%20is%3Aclosed&label=issues%20closed&labelColor=%20%237d89b0&color=%20%235d6b98"></a>
+    <a href="https://github.com/langgenius/dify/discussions/" target="_blank">
+        <img alt="Bài thảo luận" src="https://img.shields.io/github/discussions/langgenius/dify?labelColor=%20%239b8afb&color=%20%237a5af8"></a>
+</p>
+
+<p align="center">
+  <a href="./README.md"><img alt="README in English" src="https://img.shields.io/badge/English-d9d9d9"></a>
+  <a href="./README_CN.md"><img alt="简体中文版自述文件" src="https://img.shields.io/badge/简体中文-d9d9d9"></a>
+  <a href="./README_JA.md"><img alt="日本語のREADME" src="https://img.shields.io/badge/日本語-d9d9d9"></a>
+  <a href="./README_ES.md"><img alt="README en Español" src="https://img.shields.io/badge/Español-d9d9d9"></a>
+  <a href="./README_FR.md"><img alt="README en Français" src="https://img.shields.io/badge/Français-d9d9d9"></a>
+  <a href="./README_KL.md"><img alt="README tlhIngan Hol" src="https://img.shields.io/badge/Klingon-d9d9d9"></a>
+  <a href="./README_KR.md"><img alt="README in Korean" src="https://img.shields.io/badge/한국어-d9d9d9"></a>
+  <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
+  <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
+  <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
+</p>
+
+
+Dify là một nền tảng phát triển ứng dụng LLM mã nguồn mở. Giao diện trực quan kết hợp quy trình làm việc AI, mô hình RAG, khả năng tác nhân, quản lý mô hình, tính năng quan sát và hơn thế nữa, cho phép bạn nhanh chóng chuyển từ nguyên mẫu sang sản phẩm. Đây là danh sách các tính năng cốt lõi:
+</br> </br>
+
+**1. Quy trình làm việc**: 
+  Xây dựng và kiểm tra các quy trình làm việc AI mạnh mẽ trên một canvas trực quan, tận dụng tất cả các tính năng sau đây và hơn thế nữa.
+
+
+  https://github.com/langgenius/dify/assets/13230914/356df23e-1604-483d-80a6-9517ece318aa
+
+
+
+**2. Hỗ trợ mô hình toàn diện**: 
+  Tích hợp liền mạch với hàng trăm mô hình LLM độc quyền / mã nguồn mở từ hàng chục nhà cung cấp suy luận và giải pháp tự lưu trữ, bao gồm GPT, Mistral, Llama3, và bất kỳ mô hình tương thích API OpenAI nào. Danh sách đầy đủ các nhà cung cấp mô hình được hỗ trợ có thể được tìm thấy [tại đây](https://docs.dify.ai/getting-started/readme/model-providers).
+
+![providers-v5](https://github.com/langgenius/dify/assets/13230914/5a17bdbe-097a-4100-8363-40255b70f6e3)
+
+
+**3. IDE Prompt**: 
+  Giao diện trực quan để tạo prompt, so sánh hiệu suất mô hình và thêm các tính năng bổ sung như chuyển văn bản thành giọng nói cho một ứng dụng dựa trên trò chuyện. 
+
+**4. Mô hình RAG**: 
+  Khả năng RAG mở rộng bao gồm mọi thứ từ nhập tài liệu đến truy xuất, với hỗ trợ sẵn có cho việc trích xuất văn bản từ PDF, PPT và các định dạng tài liệu phổ biến khác.
+
+**5. Khả năng tác nhân**: 
+  Bạn có thể định nghĩa các tác nhân dựa trên LLM Function Calling hoặc ReAct, và thêm các công cụ được xây dựng sẵn hoặc tùy chỉnh cho tác nhân. Dify cung cấp hơn 50 công cụ tích hợp sẵn cho các tác nhân AI, như Google Search, DALL·E, Stable Diffusion và WolframAlpha.
+
+**6. LLMOps**: 
+  Giám sát và phân tích nhật ký và hiệu suất ứng dụng theo thời gian. Bạn có thể liên tục cải thiện prompt, bộ dữ liệu và mô hình dựa trên dữ liệu sản xuất và chú thích.
+
+**7. Backend-as-a-Service**: 
+  Tất cả các dịch vụ của Dify đều đi kèm với các API tương ứng, vì vậy bạn có thể dễ dàng tích hợp Dify vào logic kinh doanh của riêng mình.
+
+
+## So sánh tính năng
+<table style="width: 100%;">
+  <tr>
+    <th align="center">Tính năng</th>
+    <th align="center">Dify.AI</th>
+    <th align="center">LangChain</th>
+    <th align="center">Flowise</th>
+    <th align="center">OpenAI Assistants API</th>
+  </tr>
+  <tr>
+    <td align="center">Phương pháp lập trình</td>
+    <td align="center">Hướng API + Ứng dụng</td>
+    <td align="center">Mã Python</td>
+    <td align="center">Hướng ứng dụng</td>
+    <td align="center">Hướng API</td>
+  </tr>
+  <tr>
+    <td align="center">LLMs được hỗ trợ</td>
+    <td align="center">Đa dạng phong phú</td>
+    <td align="center">Đa dạng phong phú</td>
+    <td align="center">Đa dạng phong phú</td>
+    <td align="center">Chỉ OpenAI</td>
+  </tr>
+  <tr>
+    <td align="center">RAG Engine</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+  </tr>
+  <tr>
+    <td align="center">Agent</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">✅</td>
+  </tr>
+  <tr>
+    <td align="center">Quy trình làm việc</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+  </tr>
+  <tr>
+    <td align="center">Khả năng quan sát</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">❌</td>
+  </tr>
+  <tr>
+    <td align="center">Tính năng doanh nghiệp (SSO/Kiểm soát truy cập)</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+    <td align="center">❌</td>
+    <td align="center">❌</td>
+  </tr>
+  <tr>
+    <td align="center">Triển khai cục bộ</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">✅</td>
+    <td align="center">❌</td>
+  </tr>
+</table>
+
+## Sử dụng Dify
+
+- **Cloud </br>**
+Chúng tôi lưu trữ dịch vụ [Dify Cloud](https://dify.ai) cho bất kỳ ai muốn thử mà không cần cài đặt. Nó cung cấp tất cả các khả năng của phiên bản tự triển khai và bao gồm 200 lượt gọi GPT-4 miễn phí trong gói sandbox.
+
+- **Tự triển khai Dify Community Edition</br>**
+Nhanh chóng chạy Dify trong môi trường của bạn với [hướng dẫn bắt đầu](#quick-start) này.
+Sử dụng [tài liệu](https://docs.dify.ai) của chúng tôi để tham khảo thêm và nhận hướng dẫn chi tiết hơn.
+
+- **Dify cho doanh nghiệp / tổ chức</br>**
+Chúng tôi cung cấp các tính năng bổ sung tập trung vào doanh nghiệp. [Lên lịch cuộc họp với chúng tôi](https://cal.com/guchenhe/30min) hoặc [gửi email cho chúng tôi](mailto:business@dify.ai?subject=[GitHub]Business%20License%20Inquiry) để thảo luận về nhu cầu doanh nghiệp. </br>
+  > Đối với các công ty khởi nghiệp và doanh nghiệp nhỏ sử dụng AWS, hãy xem [Dify Premium trên AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-t22mebxzwjhu6) và triển khai nó vào AWS VPC của riêng bạn chỉ với một cú nhấp chuột. Đây là một AMI giá cả phải chăng với tùy chọn tạo ứng dụng với logo và thương hiệu tùy chỉnh.
+
+
+## Luôn cập nhật
+
+Yêu thích Dify trên GitHub và được thông báo ngay lập tức về các bản phát hành mới.
+
+![star-us](https://github.com/langgenius/dify/assets/13230914/b823edc1-6388-4e25-ad45-2f6b187adbb4)
+
+
+
+## Bắt đầu nhanh
+> Trước khi cài đặt Dify, hãy đảm bảo máy của bạn đáp ứng các yêu cầu hệ thống tối thiểu sau:
+> 
+>- CPU >= 2 Core
+>- RAM >= 4GB
+
+</br>
+
+Cách dễ nhất để khởi động máy chủ Dify là chạy tệp [docker-compose.yml](docker/docker-compose.yaml) của chúng tôi. Trước khi chạy lệnh cài đặt, hãy đảm bảo rằng [Docker](https://docs.docker.com/get-docker/) và [Docker Compose](https://docs.docker.com/compose/install/) đã được cài đặt trên máy của bạn:
+
+```bash
+cd docker
+cp .env.example .env
+docker compose up -d
+```
+
+Sau khi chạy, bạn có thể truy cập bảng điều khiển Dify trong trình duyệt của bạn tại [http://localhost/install](http://localhost/install) và bắt đầu quá trình khởi tạo.
+
+> Nếu bạn muốn đóng góp cho Dify hoặc phát triển thêm, hãy tham khảo [hướng dẫn triển khai từ mã nguồn](https://docs.dify.ai/getting-started/install-self-hosted/local-source-code) của chúng tôi
+
+## Các bước tiếp theo
+
+Nếu bạn cần tùy chỉnh cấu hình, vui lòng tham khảo các nhận xét trong tệp [.env.example](docker/.env.example) của chúng tôi và cập nhật các giá trị tương ứng trong tệp `.env` của bạn. Ngoài ra, bạn có thể cần điều chỉnh tệp `docker-compose.yaml`, chẳng hạn như thay đổi phiên bản hình ảnh, ánh xạ cổng hoặc gắn kết khối lượng, dựa trên môi trường triển khai cụ thể và yêu cầu của bạn. Sau khi thực hiện bất kỳ thay đổi nào, vui lòng chạy lại `docker-compose up -d`. Bạn có thể tìm thấy danh sách đầy đủ các biến môi trường có sẵn [tại đây](https://docs.dify.ai/getting-started/install-self-hosted/environments).
+
+Nếu bạn muốn cấu hình một cài đặt có độ sẵn sàng cao, có các [Helm Charts](https://helm.sh/) và tệp YAML do cộng đồng đóng góp cho phép Dify được triển khai trên Kubernetes.
+
+- [Helm Chart bởi @LeoQuote](https://github.com/douban/charts/tree/master/charts/dify)
+- [Helm Chart bởi @BorisPolonsky](https://github.com/BorisPolonsky/dify-helm)
+- [Tệp YAML bởi @Winson-030](https://github.com/Winson-030/dify-kubernetes)
+
+#### Sử dụng Terraform để Triển khai
+
+##### Azure Global
+Triển khai Dify lên Azure chỉ với một cú nhấp chuột bằng cách sử dụng [terraform](https://www.terraform.io/).
+- [Azure Terraform bởi @nikawang](https://github.com/nikawang/dify-azure-terraform)
+
+## Đóng góp
+
+Đối với những người muốn đóng góp mã, xem [Hướng dẫn Đóng góp](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) của chúng tôi. 
+Đồng thời, vui lòng xem xét hỗ trợ Dify bằng cách chia sẻ nó trên mạng xã hội và tại các sự kiện và hội nghị.
+
+
+> Chúng tôi đang tìm kiếm người đóng góp để giúp dịch Dify sang các ngôn ngữ khác ngoài tiếng Trung hoặc tiếng Anh. Nếu bạn quan tâm đến việc giúp đỡ, vui lòng xem [README i18n](https://github.com/langgenius/dify/blob/main/web/i18n/README.md) để biết thêm thông tin và để lại bình luận cho chúng tôi trong kênh `global-users` của [Máy chủ Cộng đồng Discord](https://discord.gg/8Tpq4AcN9c) của chúng tôi.
+
+**Người đóng góp**
+
+<a href="https://github.com/langgenius/dify/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langgenius/dify" />
+</a>
+
+## Cộng đồng & liên hệ
+
+* [Thảo luận GitHub](https://github.com/langgenius/dify/discussions). Tốt nhất cho: chia sẻ phản hồi và đặt câu hỏi.
+* [Vấn đề GitHub](https://github.com/langgenius/dify/issues). Tốt nhất cho: lỗi bạn gặp phải khi sử dụng Dify.AI và đề xuất tính năng. Xem [Hướng dẫn Đóng góp](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) của chúng tôi.
+* [Discord](https://discord.gg/FngNHpbcY7). Tốt nhất cho: chia sẻ ứng dụng của bạn và giao lưu với cộng đồng.
+* [Twitter](https://twitter.com/dify_ai). Tốt nhất cho: chia sẻ ứng dụng của bạn và giao lưu với cộng đồng.
+
+Hoặc, lên lịch cuộc họp trực tiếp với một thành viên trong nhóm:
+
+<table>
+  <tr>
+    <th>Điểm liên hệ</th>
+    <th>Mục đích</th>
+  </tr>
+  <tr>
+    <td><a href='https://cal.com/guchenhe/15min' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/9ebcd111-1205-4d71-83d5-948d70b809f5' alt='Git-Hub-README-Button-3x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
+    <td>Yêu cầu kinh doanh & phản hồi sản phẩm</td>
+  </tr>
+  <tr>
+    <td><a href='https://cal.com/pinkbanana' target='_blank'><img class="schedule-button" src='https://github.com/langgenius/dify/assets/13230914/d1edd00a-d7e4-4513-be6c-e57038e143fd' alt='Git-Hub-README-Button-2x' style="width: 180px; height: auto; object-fit: contain;"/></a></td>
+    <td>Đóng góp, vấn đề & yêu cầu tính năng</td>
+  </tr>
+</table>
+
+## Lịch sử Yêu thích
+
+[![Biểu đồ Lịch sử Yêu thích](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)
+
+## Tiết lộ bảo mật
+
+Để bảo vệ quyền riêng tư của bạn, vui lòng tránh đăng các vấn đề bảo mật trên GitHub. Thay vào đó, hãy gửi câu hỏi của bạn đến security@dify.ai và chúng tôi sẽ cung cấp cho bạn câu trả lời chi tiết hơn.
+
+## Giấy phép
+
+Kho lưu trữ này có sẵn theo [Giấy phép Mã nguồn Mở Dify](LICENSE), về cơ bản là Apache 2.0 với một vài hạn chế bổ sung.
--- a/api/Dockerfile
+++ b/api/Dockerfile
@ -12,6 +12,7 @@ ENV POETRY_CACHE_DIR=/tmp/poetry_cache
 ENV POETRY_NO_INTERACTION=1
 ENV POETRY_VIRTUALENVS_IN_PROJECT=true
 ENV POETRY_VIRTUALENVS_CREATE=true
+ENV POETRY_REQUESTS_TIMEOUT=15

 FROM base AS packages

@ -54,6 +55,9 @@ ENV VIRTUAL_ENV=/app/api/.venv
 COPY --from=packages ${VIRTUAL_ENV} ${VIRTUAL_ENV}
 ENV PATH="${VIRTUAL_ENV}/bin:${PATH}"

+# Download nltk data
+RUN python -c "import nltk; nltk.download('punkt')"
+
 # Copy source code
 COPY . /app/api/

--- a/api/constants/init.py
+++ b/api/constants/init.py
@ -1,2 +1 @@
-# TODO: Update all string in code to use this constant
-HIDDEN_VALUE = '[__HIDDEN__]'
+HIDDEN_VALUE = '[__HIDDEN__]'
--- a/api/constants/languages.py
+++ b/api/constants/languages.py
@ -16,6 +16,7 @@ language_timezone_mapping = {
    'pl-PL': 'Europe/Warsaw',
    'hi-IN': 'Asia/Kolkata',
    'tr-TR': 'Europe/Istanbul',
+    'fa-IR': 'Asia/Tehran',
 }

 languages = list(language_timezone_mapping.keys())
--- a/api/controllers/console/extension.py
+++ b/api/controllers/console/extension.py
@ -1,6 +1,7 @@
 from flask_login import current_user
 from flask_restful import Resource, marshal_with, reqparse

+from constants import HIDDEN_VALUE
 from controllers.console import api
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
@ -89,7 +90,7 @@ class APIBasedExtensionDetailAPI(Resource):
        extension_data_from_db.name = args['name']
        extension_data_from_db.api_endpoint = args['api_endpoint']

-        if args['api_key'] != '[__HIDDEN__]':
+        if args['api_key'] != HIDDEN_VALUE:
            extension_data_from_db.api_key = args['api_key']

        return APIBasedExtensionService.save(extension_data_from_db)
--- a/api/core/app/apps/advanced_chat/app_generator.py
+++ b/api/core/app/apps/advanced_chat/app_generator.py
@ -89,7 +89,8 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
        )

        # get tracing instance
-        trace_manager = TraceQueueManager(app_id=app_model.id)
+        user_id = user.id if isinstance(user, Account) else user.session_id
+        trace_manager = TraceQueueManager(app_model.id, user_id)

        if invoke_from == InvokeFrom.DEBUGGER:
            # always enable retriever resource in debugger mode
--- a/api/core/app/apps/advanced_chat/generate_task_pipeline.py
+++ b/api/core/app/apps/advanced_chat/generate_task_pipeline.py
@ -244,7 +244,11 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
        :return:
        """
        for message in self._queue_manager.listen():
-            if hasattr(message.event, 'metadata') and message.event.metadata.get('is_answer_previous_node', False) and publisher:
+            if (message.event
+                    and hasattr(message.event, 'metadata')
+                    and message.event.metadata
+                    and message.event.metadata.get('is_answer_previous_node', False)
+                    and publisher):
                publisher.publish(message=message)
            elif (hasattr(message.event, 'execution_metadata')
                  and message.event.execution_metadata
--- a/api/core/app/segments/factory.py
+++ b/api/core/app/segments/factory.py
@ -75,8 +75,7 @@ def build_segment(value: Any, /) -> Segment:
        return FloatSegment(value=value)
    if isinstance(value, dict):
        # TODO: Limit the depth of the object
-        obj = {k: build_segment(v) for k, v in value.items()}
-        return ObjectSegment(value=obj)
+        return ObjectSegment(value=value)
    if isinstance(value, list):
        # TODO: Limit the depth of the array
        elements = [build_segment(v) for v in value]
--- a/api/core/app/segments/segments.py
+++ b/api/core/app/segments/segments.py
@ -85,26 +85,20 @@ class FileSegment(Segment):

 class ObjectSegment(Segment):
    value_type: SegmentType = SegmentType.OBJECT
-    value: Mapping[str, Segment]
+    value: Mapping[str, Any]

    @property
    def text(self) -> str:
-        # TODO: Process variables.
        return json.dumps(self.model_dump()['value'], ensure_ascii=False)

    @property
    def log(self) -> str:
-        # TODO: Process variables.
        return json.dumps(self.model_dump()['value'], ensure_ascii=False, indent=2)

    @property
    def markdown(self) -> str:
-        # TODO: Use markdown code block
        return json.dumps(self.model_dump()['value'], ensure_ascii=False, indent=2)

-    def to_object(self):
-        return {k: v.to_object() for k, v in self.value.items()}
-

 class ArraySegment(Segment):
    @property
--- a/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py
+++ b/api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py
@ -48,7 +48,8 @@ from core.model_runtime.entities.message_entities import (
 )
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.utils.encoders import jsonable_encoder
-from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName
+from core.ops.entities.trace_entity import TraceTaskName
+from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
 from core.prompt.utils.prompt_template_parser import PromptTemplateParser
 from events.message_event import message_was_created
--- a/api/core/app/task_pipeline/workflow_cycle_manage.py
+++ b/api/core/app/task_pipeline/workflow_cycle_manage.py
@ -22,7 +22,8 @@ from core.app.entities.task_entities import (
 from core.app.task_pipeline.workflow_iteration_cycle_manage import WorkflowIterationCycleManage
 from core.file.file_obj import FileVar
 from core.model_runtime.utils.encoders import jsonable_encoder
-from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName
+from core.ops.entities.trace_entity import TraceTaskName
+from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
 from core.tools.tool_manager import ToolManager
 from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeType
 from core.workflow.nodes.tool.entities import ToolNodeData
@ -40,6 +41,7 @@ from models.workflow import (
    WorkflowRunStatus,
    WorkflowRunTriggeredFrom,
 )
+from services.workflow_service import WorkflowService


 class WorkflowCycleManage(WorkflowIterationCycleManage):
@ -97,7 +99,6 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):

    def _workflow_run_success(
        self, workflow_run: WorkflowRun,
-        start_at: float,
        total_tokens: int,
        total_steps: int,
        outputs: Optional[str] = None,
@ -107,7 +108,6 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
        """
        Workflow run success
        :param workflow_run: workflow run
-        :param start_at: start time
        :param total_tokens: total tokens
        :param total_steps: total steps
        :param outputs: outputs
@ -116,7 +116,7 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
        """
        workflow_run.status = WorkflowRunStatus.SUCCEEDED.value
        workflow_run.outputs = outputs
-        workflow_run.elapsed_time = time.perf_counter() - start_at
+        workflow_run.elapsed_time = WorkflowService.get_elapsed_time(workflow_run_id=workflow_run.id)
        workflow_run.total_tokens = total_tokens
        workflow_run.total_steps = total_steps
        workflow_run.finished_at = datetime.now(timezone.utc).replace(tzinfo=None)
@ -139,7 +139,6 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):

    def _workflow_run_failed(
        self, workflow_run: WorkflowRun,
-        start_at: float,
        total_tokens: int,
        total_steps: int,
        status: WorkflowRunStatus,
@ -150,7 +149,6 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
        """
        Workflow run failed
        :param workflow_run: workflow run
-        :param start_at: start time
        :param total_tokens: total tokens
        :param total_steps: total steps
        :param status: status
@ -159,7 +157,7 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
        """
        workflow_run.status = status.value
        workflow_run.error = error
-        workflow_run.elapsed_time = time.perf_counter() - start_at
+        workflow_run.elapsed_time = WorkflowService.get_elapsed_time(workflow_run_id=workflow_run.id)
        workflow_run.total_tokens = total_tokens
        workflow_run.total_steps = total_steps
        workflow_run.finished_at = datetime.now(timezone.utc).replace(tzinfo=None)
@ -542,7 +540,6 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
        if isinstance(event, QueueStopEvent):
            workflow_run = self._workflow_run_failed(
                workflow_run=workflow_run,
-                start_at=self._task_state.start_at,
                total_tokens=self._task_state.total_tokens,
                total_steps=self._task_state.total_steps,
                status=WorkflowRunStatus.STOPPED,
@ -565,7 +562,6 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):
        elif isinstance(event, QueueWorkflowFailedEvent):
            workflow_run = self._workflow_run_failed(
                workflow_run=workflow_run,
-                start_at=self._task_state.start_at,
                total_tokens=self._task_state.total_tokens,
                total_steps=self._task_state.total_steps,
                status=WorkflowRunStatus.FAILED,
@ -583,7 +579,6 @@ class WorkflowCycleManage(WorkflowIterationCycleManage):

            workflow_run = self._workflow_run_success(
                workflow_run=workflow_run,
-                start_at=self._task_state.start_at,
                total_tokens=self._task_state.total_tokens,
                total_steps=self._task_state.total_steps,
                outputs=outputs,
--- a/api/core/callback_handler/agent_tool_callback_handler.py
+++ b/api/core/callback_handler/agent_tool_callback_handler.py
@ -4,7 +4,8 @@ from typing import Any, Optional, TextIO, Union

 from pydantic import BaseModel

-from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName
+from core.ops.entities.trace_entity import TraceTaskName
+from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
 from core.tools.entities.tool_entities import ToolInvokeMessage

 _TEXT_COLOR_MAPPING = {
--- a/api/core/entities/provider_configuration.py
+++ b/api/core/entities/provider_configuration.py
@ -8,6 +8,7 @@ from typing import Optional

 from pydantic import BaseModel, ConfigDict

+from constants import HIDDEN_VALUE
 from core.entities.model_entities import ModelStatus, ModelWithProviderEntity, SimpleModelProviderEntity
 from core.entities.provider_entities import (
    CustomConfiguration,
@ -202,7 +203,7 @@ class ProviderConfiguration(BaseModel):
            for key, value in credentials.items():
                if key in provider_credential_secret_variables:
                    # if send [__HIDDEN__] in secret input, it will be same as original value
-                    if value == '[__HIDDEN__]' and key in original_credentials:
+                    if value == HIDDEN_VALUE and key in original_credentials:
                        credentials[key] = encrypter.decrypt_token(self.tenant_id, original_credentials[key])

        credentials = model_provider_factory.provider_credentials_validate(
@ -345,7 +346,7 @@ class ProviderConfiguration(BaseModel):
            for key, value in credentials.items():
                if key in provider_credential_secret_variables:
                    # if send [__HIDDEN__] in secret input, it will be same as original value
-                    if value == '[__HIDDEN__]' and key in original_credentials:
+                    if value == HIDDEN_VALUE and key in original_credentials:
                        credentials[key] = encrypter.decrypt_token(self.tenant_id, original_credentials[key])

        credentials = model_provider_factory.model_credentials_validate(
--- a/api/core/file/message_file_parser.py
+++ b/api/core/file/message_file_parser.py
@ -1,5 +1,7 @@
+import re
 from collections.abc import Mapping, Sequence
 from typing import Any, Union
+from urllib.parse import parse_qs, urlparse

 import requests

@ -186,6 +188,30 @@ class MessageFileParser:
                "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
            }

+            def is_s3_presigned_url(url):
+                try:
+                    parsed_url = urlparse(url)
+                    if 'amazonaws.com' not in parsed_url.netloc:
+                        return False
+                    query_params = parse_qs(parsed_url.query)
+                    required_params = ['Signature', 'Expires']
+                    for param in required_params:
+                        if param not in query_params:
+                            return False
+                    if not query_params['Expires'][0].isdigit():
+                        return False
+                    signature = query_params['Signature'][0]
+                    if not re.match(r'^[A-Za-z0-9+/]+={0,2}$', signature):
+                        return False
+                    return True
+                except Exception:
+                    return False
+
+            if is_s3_presigned_url(url):
+                response = requests.get(url, headers=headers, allow_redirects=True)
+                if response.status_code in {200, 304}:
+                    return True, ""
+
            response = requests.head(url, headers=headers, allow_redirects=True)
            if response.status_code in {200, 304}:
                return True, ""
--- a/api/core/llm_generator/llm_generator.py
+++ b/api/core/llm_generator/llm_generator.py
@ -14,7 +14,8 @@ from core.model_manager import ModelManager
 from core.model_runtime.entities.message_entities import SystemPromptMessage, UserPromptMessage
 from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeError
-from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName
+from core.ops.entities.trace_entity import TraceTaskName
+from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
 from core.ops.utils import measure_time
 from core.prompt.utils.prompt_template_parser import PromptTemplateParser

--- a/api/core/model_runtime/model_providers/_position.yaml
+++ b/api/core/model_runtime/model_providers/_position.yaml
@ -36,3 +36,4 @@
 - hunyuan
 - siliconflow
 - perfxcloud
+- zhinao
--- a/api/core/model_runtime/model_providers/bedrock/llm/llm.py
+++ b/api/core/model_runtime/model_providers/bedrock/llm/llm.py
@ -379,8 +379,12 @@ class BedrockLargeLanguageModel(LargeLanguageModel):
                        if not message_content.data.startswith("data:"):
                            # fetch image data from url
                            try:
-                                image_content = requests.get(message_content.data).content
-                                mime_type, _ = mimetypes.guess_type(message_content.data)
+                                url = message_content.data
+                                image_content = requests.get(url).content
+                                if '?' in url:
+                                    url = url.split('?')[0]
+                                mime_type, _ = mimetypes.guess_type(url)
+                                base64_data = base64.b64encode(image_content).decode('utf-8')
                            except Exception as ex:
                                raise ValueError(f"Failed to fetch image data from url {message_content.data}, {ex}")
                        else:
--- a/api/core/model_runtime/model_providers/huggingface_tei/init.py
+++ b/api/core/model_runtime/model_providers/huggingface_tei/init.py
--- a/api/core/model_runtime/model_providers/huggingface_tei/huggingface_tei.py
+++ b/api/core/model_runtime/model_providers/huggingface_tei/huggingface_tei.py
@ -0,0 +1,11 @@
+import logging
+
+from core.model_runtime.model_providers.__base.model_provider import ModelProvider
+
+logger = logging.getLogger(__name__)
+
+
+class HuggingfaceTeiProvider(ModelProvider):
+
+    def validate_provider_credentials(self, credentials: dict) -> None:
+        pass
--- a/api/core/model_runtime/model_providers/huggingface_tei/huggingface_tei.yaml
+++ b/api/core/model_runtime/model_providers/huggingface_tei/huggingface_tei.yaml
@ -0,0 +1,36 @@
+provider: huggingface_tei
+label:
+  en_US: Text Embedding Inference
+description:
+  en_US: A blazing fast inference solution for text embeddings models.
+  zh_Hans: 用于文本嵌入模型的超快速推理解决方案。
+background: "#FFF8DC"
+help:
+  title:
+    en_US: How to deploy Text Embedding Inference
+    zh_Hans: 如何部署 Text Embedding Inference
+  url:
+    en_US: https://github.com/huggingface/text-embeddings-inference
+supported_model_types:
+  - text-embedding
+  - rerank
+configurate_methods:
+  - customizable-model
+model_credential_schema:
+  model:
+    label:
+      en_US: Model Name
+      zh_Hans: 模型名称
+    placeholder:
+      en_US: Enter your model name
+      zh_Hans: 输入模型名称
+  credential_form_schemas:
+    - variable: server_url
+      label:
+        zh_Hans: 服务器URL
+        en_US: Server url
+      type: secret-input
+      required: true
+      placeholder:
+        zh_Hans: 在此输入Text Embedding Inference的服务器地址，如 http://192.168.1.100:8080
+        en_US: Enter the url of your Text Embedding Inference, e.g. http://192.168.1.100:8080
--- a/api/core/model_runtime/model_providers/huggingface_tei/rerank/init.py
+++ b/api/core/model_runtime/model_providers/huggingface_tei/rerank/init.py
--- a/api/core/model_runtime/model_providers/huggingface_tei/rerank/rerank.py
+++ b/api/core/model_runtime/model_providers/huggingface_tei/rerank/rerank.py
@ -0,0 +1,137 @@
+from typing import Optional
+
+import httpx
+
+from core.model_runtime.entities.common_entities import I18nObject
+from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType
+from core.model_runtime.entities.rerank_entities import RerankDocument, RerankResult
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.__base.rerank_model import RerankModel
+from core.model_runtime.model_providers.huggingface_tei.tei_helper import TeiHelper
+
+
+class HuggingfaceTeiRerankModel(RerankModel):
+    """
+    Model class for Text Embedding Inference rerank model.
+    """
+
+    def _invoke(
+        self,
+        model: str,
+        credentials: dict,
+        query: str,
+        docs: list[str],
+        score_threshold: Optional[float] = None,
+        top_n: Optional[int] = None,
+        user: Optional[str] = None,
+    ) -> RerankResult:
+        """
+        Invoke rerank model
+
+        :param model: model name
+        :param credentials: model credentials
+        :param query: search query
+        :param docs: docs for reranking
+        :param score_threshold: score threshold
+        :param top_n: top n
+        :param user: unique user id
+        :return: rerank result
+        """
+        if len(docs) == 0:
+            return RerankResult(model=model, docs=[])
+        server_url = credentials['server_url']
+
+        if server_url.endswith('/'):
+            server_url = server_url[:-1]
+
+        try:
+            results = TeiHelper.invoke_rerank(server_url, query, docs)
+
+            rerank_documents = []
+            for result in results:  
+                rerank_document = RerankDocument(
+                    index=result['index'],
+                    text=result['text'],
+                    score=result['score'],
+                )
+                if score_threshold is None or result['score'] >= score_threshold:
+                    rerank_documents.append(rerank_document)
+                if top_n is not None and len(rerank_documents) >= top_n:
+                    break
+
+            return RerankResult(model=model, docs=rerank_documents)
+        except httpx.HTTPStatusError as e:
+            raise InvokeServerUnavailableError(str(e))  
+
+    def validate_credentials(self, model: str, credentials: dict) -> None:
+        """
+        Validate model credentials
+
+        :param model: model name
+        :param credentials: model credentials
+        :return:
+        """
+        try:
+            server_url = credentials['server_url']
+            extra_args = TeiHelper.get_tei_extra_parameter(server_url, model)
+            if extra_args.model_type != 'reranker':
+                raise CredentialsValidateFailedError('Current model is not a rerank model')
+
+            credentials['context_size'] = extra_args.max_input_length
+
+            self.invoke(
+                model=model,
+                credentials=credentials,
+                query='Whose kasumi',
+                docs=[
+                    'Kasumi is a girl\'s name of Japanese origin meaning "mist".',
+                    'Her music is a kawaii bass, a mix of future bass, pop, and kawaii music ',
+                    'and she leads a team named PopiParty.',
+                ],
+                score_threshold=0.8,
+            )
+        except Exception as ex:
+            raise CredentialsValidateFailedError(str(ex))
+
+    @property
+    def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
+        """
+        Map model invoke error to unified error
+        The key is the error type thrown to the caller
+        The value is the error type thrown by the model,
+        which needs to be converted into a unified error type for the caller.
+
+        :return: Invoke error mapping
+        """
+        return {
+            InvokeConnectionError: [InvokeConnectionError],
+            InvokeServerUnavailableError: [InvokeServerUnavailableError],
+            InvokeRateLimitError: [InvokeRateLimitError],
+            InvokeAuthorizationError: [InvokeAuthorizationError],
+            InvokeBadRequestError: [InvokeBadRequestError, KeyError, ValueError],
+        }
+
+    def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None:
+        """
+        used to define customizable model schema
+        """
+        entity = AIModelEntity(
+            model=model,
+            label=I18nObject(en_US=model),
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_type=ModelType.RERANK,
+            model_properties={
+                ModelPropertyKey.CONTEXT_SIZE: int(credentials.get('context_size', 512)),
+            },
+            parameter_rules=[],
+        )
+
+        return entity
--- a/api/core/model_runtime/model_providers/huggingface_tei/tei_helper.py
+++ b/api/core/model_runtime/model_providers/huggingface_tei/tei_helper.py
@ -0,0 +1,183 @@
+from threading import Lock
+from time import time
+from typing import Optional
+
+import httpx
+from requests.adapters import HTTPAdapter
+from requests.exceptions import ConnectionError, MissingSchema, Timeout
+from requests.sessions import Session
+from yarl import URL
+
+
+class TeiModelExtraParameter:
+    model_type: str
+    max_input_length: int
+    max_client_batch_size: int
+
+    def __init__(self, model_type: str, max_input_length: int, max_client_batch_size: Optional[int] = None) -> None:
+        self.model_type = model_type
+        self.max_input_length = max_input_length
+        self.max_client_batch_size = max_client_batch_size
+
+
+cache = {}
+cache_lock = Lock()
+
+
+class TeiHelper:
+    @staticmethod
+    def get_tei_extra_parameter(server_url: str, model_name: str) -> TeiModelExtraParameter:
+        TeiHelper._clean_cache()
+        with cache_lock:
+            if model_name not in cache:
+                cache[model_name] = {
+                    'expires': time() + 300,
+                    'value': TeiHelper._get_tei_extra_parameter(server_url),
+                }
+            return cache[model_name]['value']
+
+    @staticmethod
+    def _clean_cache() -> None:
+        try:
+            with cache_lock:
+                expired_keys = [model_uid for model_uid, model in cache.items() if model['expires'] < time()]
+                for model_uid in expired_keys:
+                    del cache[model_uid]
+        except RuntimeError as e:
+            pass
+
+    @staticmethod
+    def _get_tei_extra_parameter(server_url: str) -> TeiModelExtraParameter:
+        """
+        get tei model extra parameter like model_type, max_input_length, max_batch_requests
+        """
+
+        url = str(URL(server_url) / 'info')
+
+        # this method is surrounded by a lock, and default requests may hang forever, so we just set a Adapter with max_retries=3
+        session = Session()
+        session.mount('http://', HTTPAdapter(max_retries=3))
+        session.mount('https://', HTTPAdapter(max_retries=3))
+
+        try:
+            response = session.get(url, timeout=10)
+        except (MissingSchema, ConnectionError, Timeout) as e:
+            raise RuntimeError(f'get tei model extra parameter failed, url: {url}, error: {e}')
+        if response.status_code != 200:
+            raise RuntimeError(
+                f'get tei model extra parameter failed, status code: {response.status_code}, response: {response.text}'
+            )
+
+        response_json = response.json()
+
+        model_type = response_json.get('model_type', {})
+        if len(model_type.keys()) < 1:
+            raise RuntimeError('model_type is empty')
+        model_type = list(model_type.keys())[0]
+        if model_type not in ['embedding', 'reranker']:
+            raise RuntimeError(f'invalid model_type: {model_type}')
+        
+        max_input_length = response_json.get('max_input_length', 512)
+        max_client_batch_size = response_json.get('max_client_batch_size', 1)
+
+        return TeiModelExtraParameter(
+            model_type=model_type,
+            max_input_length=max_input_length,
+            max_client_batch_size=max_client_batch_size
+        )
+    
+    @staticmethod
+    def invoke_tokenize(server_url: str, texts: list[str]) -> list[list[dict]]:
+        """
+        Invoke tokenize endpoint
+
+        Example response:
+        [
+            [
+                {
+                    "id": 0,
+                    "text": "<s>",
+                    "special": true,
+                    "start": null,
+                    "stop": null
+                },
+                {
+                    "id": 7704,
+                    "text": "str",
+                    "special": false,
+                    "start": 0,
+                    "stop": 3
+                },
+                < MORE TOKENS >
+            ]
+        ]
+
+        :param server_url: server url
+        :param texts: texts to tokenize
+        """
+        resp = httpx.post(
+            f'{server_url}/tokenize',
+            json={'inputs': texts},
+        )
+        resp.raise_for_status()
+        return resp.json()
+    
+    @staticmethod
+    def invoke_embeddings(server_url: str, texts: list[str]) -> dict:
+        """
+        Invoke embeddings endpoint
+
+        Example response:
+        {
+            "object": "list",
+            "data": [
+                {
+                    "object": "embedding",
+                    "embedding": [...],
+                    "index": 0
+                }
+            ],
+            "model": "MODEL_NAME",
+            "usage": {
+                "prompt_tokens": 3,
+                "total_tokens": 3
+            }
+        }
+
+        :param server_url: server url
+        :param texts: texts to embed
+        """
+        # Use OpenAI compatible API here, which has usage tracking
+        resp = httpx.post(
+            f'{server_url}/v1/embeddings',
+            json={'input': texts},
+        )
+        resp.raise_for_status()
+        return resp.json()
+
+    @staticmethod
+    def invoke_rerank(server_url: str, query: str, docs: list[str]) -> list[dict]:
+        """
+        Invoke rerank endpoint
+
+        Example response:
+        [
+            {
+                "index": 0,
+                "text": "Deep Learning is ...",
+                "score": 0.9950755
+            }
+        ]
+
+        :param server_url: server url
+        :param texts: texts to rerank
+        :param candidates: candidates to rerank
+        """
+        params = {'query': query, 'texts': docs, 'return_text': True}
+
+        response = httpx.post(
+            server_url + '/rerank',
+            json=params,
+        )
+        response.raise_for_status() 
+        return response.json()
--- a/api/core/model_runtime/model_providers/huggingface_tei/text_embedding/init.py
+++ b/api/core/model_runtime/model_providers/huggingface_tei/text_embedding/init.py
--- a/api/core/model_runtime/model_providers/huggingface_tei/text_embedding/text_embedding.py
+++ b/api/core/model_runtime/model_providers/huggingface_tei/text_embedding/text_embedding.py
@ -0,0 +1,204 @@
+import time
+from typing import Optional
+
+from core.model_runtime.entities.common_entities import I18nObject
+from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelPropertyKey, ModelType, PriceType
+from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
+from core.model_runtime.errors.invoke import (
+    InvokeAuthorizationError,
+    InvokeBadRequestError,
+    InvokeConnectionError,
+    InvokeError,
+    InvokeRateLimitError,
+    InvokeServerUnavailableError,
+)
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
+from core.model_runtime.model_providers.huggingface_tei.tei_helper import TeiHelper
+
+
+class HuggingfaceTeiTextEmbeddingModel(TextEmbeddingModel):
+    """
+    Model class for Text Embedding Inference text embedding model.
+    """
+
+    def _invoke(
+        self, model: str, credentials: dict, texts: list[str], user: Optional[str] = None
+    ) -> TextEmbeddingResult:
+        """
+        Invoke text embedding model
+
+        credentials should be like:
+        {
+            'server_url': 'server url',
+            'model_uid': 'model uid',
+        }
+
+        :param model: model name
+        :param credentials: model credentials
+        :param texts: texts to embed
+        :param user: unique user id
+        :return: embeddings result
+        """
+        server_url = credentials['server_url']
+
+        if server_url.endswith('/'):
+            server_url = server_url[:-1]
+
+
+        # get model properties
+        context_size = self._get_context_size(model, credentials)
+        max_chunks = self._get_max_chunks(model, credentials)
+
+        inputs = []
+        indices = []
+        used_tokens = 0
+
+        # get tokenized results from TEI
+        batched_tokenize_result = TeiHelper.invoke_tokenize(server_url, texts)
+
+        for i, (text, tokenize_result) in enumerate(zip(texts, batched_tokenize_result)):
+
+            # Check if the number of tokens is larger than the context size
+            num_tokens = len(tokenize_result)
+
+            if num_tokens >= context_size:
+                # Find the best cutoff point
+                pre_special_token_count = 0
+                for token in tokenize_result:
+                    if token['special']:
+                        pre_special_token_count += 1
+                    else:
+                        break
+                rest_special_token_count = len([token for token in tokenize_result if token['special']]) - pre_special_token_count
+
+                # Calculate the cutoff point, leave 20 extra space to avoid exceeding the limit
+                token_cutoff = context_size - rest_special_token_count - 20
+
+                # Find the cutoff index
+                cutpoint_token = tokenize_result[token_cutoff]
+                cutoff = cutpoint_token['start']
+
+                inputs.append(text[0: cutoff])
+            else:
+                inputs.append(text)
+            indices += [i]
+
+        batched_embeddings = []
+        _iter = range(0, len(inputs), max_chunks)
+
+        try:
+            used_tokens = 0
+            for i in _iter:
+                iter_texts = inputs[i : i + max_chunks]
+                results = TeiHelper.invoke_embeddings(server_url, iter_texts)
+                embeddings = results['data']
+                embeddings = [embedding['embedding'] for embedding in embeddings]
+                batched_embeddings.extend(embeddings)
+
+                usage = results['usage']
+                used_tokens += usage['total_tokens']
+        except RuntimeError as e:
+            raise InvokeServerUnavailableError(str(e))
+
+        usage = self._calc_response_usage(model=model, credentials=credentials, tokens=used_tokens)
+
+        result = TextEmbeddingResult(model=model, embeddings=batched_embeddings, usage=usage)
+
+        return result
+
+    def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int:
+        """
+        Get number of tokens for given prompt messages
+
+        :param model: model name
+        :param credentials: model credentials
+        :param texts: texts to embed
+        :return:
+        """
+        num_tokens = 0
+        server_url = credentials['server_url']
+
+        if server_url.endswith('/'):
+            server_url = server_url[:-1]
+
+        batch_tokens = TeiHelper.invoke_tokenize(server_url, texts)
+        num_tokens = sum(len(tokens) for tokens in batch_tokens)
+        return num_tokens
+
+    def validate_credentials(self, model: str, credentials: dict) -> None:
+        """
+        Validate model credentials
+
+        :param model: model name
+        :param credentials: model credentials
+        :return:
+        """
+        try:
+            server_url = credentials['server_url']
+            extra_args = TeiHelper.get_tei_extra_parameter(server_url, model)
+            print(extra_args)
+            if extra_args.model_type != 'embedding':
+                raise CredentialsValidateFailedError('Current model is not a embedding model')
+
+            credentials['context_size'] = extra_args.max_input_length
+            credentials['max_chunks'] = extra_args.max_client_batch_size
+            self._invoke(model=model, credentials=credentials, texts=['ping'])
+        except Exception as ex:
+            raise CredentialsValidateFailedError(str(ex))
+
+    @property
+    def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
+        return {
+            InvokeConnectionError: [InvokeConnectionError],
+            InvokeServerUnavailableError: [InvokeServerUnavailableError],
+            InvokeRateLimitError: [InvokeRateLimitError],
+            InvokeAuthorizationError: [InvokeAuthorizationError],
+            InvokeBadRequestError: [KeyError],
+        }
+
+    def _calc_response_usage(self, model: str, credentials: dict, tokens: int) -> EmbeddingUsage:
+        """
+        Calculate response usage
+
+        :param model: model name
+        :param credentials: model credentials
+        :param tokens: input tokens
+        :return: usage
+        """
+        # get input price info
+        input_price_info = self.get_price(
+            model=model, credentials=credentials, price_type=PriceType.INPUT, tokens=tokens
+        )
+
+        # transform usage
+        usage = EmbeddingUsage(
+            tokens=tokens,
+            total_tokens=tokens,
+            unit_price=input_price_info.unit_price,
+            price_unit=input_price_info.unit,
+            total_price=input_price_info.total_amount,
+            currency=input_price_info.currency,
+            latency=time.perf_counter() - self.started_at,
+        )
+
+        return usage
+
+    def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None:
+        """
+        used to define customizable model schema
+        """
+
+        entity = AIModelEntity(
+            model=model,
+            label=I18nObject(en_US=model),
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_type=ModelType.TEXT_EMBEDDING,
+            model_properties={
+                ModelPropertyKey.MAX_CHUNKS: int(credentials.get('max_chunks', 1)),
+                ModelPropertyKey.CONTEXT_SIZE: int(credentials.get('context_size', 512)),
+            },
+            parameter_rules=[],
+        )
+
+        return entity
--- a/api/core/model_runtime/model_providers/hunyuan/llm/llm.py
+++ b/api/core/model_runtime/model_providers/hunyuan/llm/llm.py
@ -214,7 +214,7 @@ class HunyuanLargeLanguageModel(LargeLanguageModel):
    def _handle_chat_response(self, credentials, model, prompt_messages, response):
        usage = self._calc_response_usage(model, credentials, response.Usage.PromptTokens,
                                          response.Usage.CompletionTokens)
-        assistant_prompt_message = PromptMessage(role="assistant")
+        assistant_prompt_message = AssistantPromptMessage()
        assistant_prompt_message.content = response.Choices[0].Message.Content
        result = LLMResult(
            model=model,
--- a/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v2-base-multilingual.yaml
+++ b/api/core/model_runtime/model_providers/jina/rerank/jina-reranker-v2-base-multilingual.yaml
@ -1,4 +1,4 @@
 model: jina-reranker-v2-base-multilingual
 model_type: rerank
 model_properties:
-  context_size: 8192
+  context_size: 1024
--- a/api/core/model_runtime/model_providers/ollama/text_embedding/text_embedding.py
+++ b/api/core/model_runtime/model_providers/ollama/text_embedding/text_embedding.py
@ -72,7 +72,7 @@ class OllamaEmbeddingModel(TextEmbeddingModel):
            num_tokens = self._get_num_tokens_by_gpt2(text)

            if num_tokens >= context_size:
-                cutoff = int(len(text) * (np.floor(context_size / num_tokens)))
+                cutoff = int(np.floor(len(text) * (context_size / num_tokens)))
                # if num tokens is larger than context length, only use the start
                inputs.append(text[0: cutoff])
            else:
--- a/api/core/model_runtime/model_providers/openai/llm/_position.yaml
+++ b/api/core/model_runtime/model_providers/openai/llm/_position.yaml
@ -1,6 +1,7 @@
 - gpt-4
 - gpt-4o
 - gpt-4o-2024-05-13
+- gpt-4o-2024-08-06
 - gpt-4o-mini
 - gpt-4o-mini-2024-07-18
 - gpt-4-turbo
--- a/api/core/model_runtime/model_providers/openai/llm/gpt-4o-2024-08-06.yaml
+++ b/api/core/model_runtime/model_providers/openai/llm/gpt-4o-2024-08-06.yaml
@ -0,0 +1,44 @@
+model: gpt-4o-2024-08-06
+label:
+  zh_Hans: gpt-4o-2024-08-06
+  en_US: gpt-4o-2024-08-06
+model_type: llm
+features:
+  - multi-tool-call
+  - agent-thought
+  - stream-tool-call
+  - vision
+model_properties:
+  mode: chat
+  context_size: 128000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: presence_penalty
+    use_template: presence_penalty
+  - name: frequency_penalty
+    use_template: frequency_penalty
+  - name: max_tokens
+    use_template: max_tokens
+    default: 512
+    min: 1
+    max: 16384
+  - name: response_format
+    label:
+      zh_Hans: 回复格式
+      en_US: response_format
+    type: string
+    help:
+      zh_Hans: 指定模型必须输出的格式
+      en_US: specifying the format that the model must output
+    required: false
+    options:
+      - text
+      - json_object
+pricing:
+  input: '2.50'
+  output: '10.00'
+  unit: '0.000001'
+  currency: USD
--- a/api/core/model_runtime/model_providers/openai_api_compatible/text_embedding/text_embedding.py
+++ b/api/core/model_runtime/model_providers/openai_api_compatible/text_embedding/text_embedding.py
@ -76,7 +76,7 @@ class OAICompatEmbeddingModel(_CommonOAI_API_Compat, TextEmbeddingModel):
            num_tokens = self._get_num_tokens_by_gpt2(text)

            if num_tokens >= context_size:
-                cutoff = int(len(text) * (np.floor(context_size / num_tokens)))
+                cutoff = int(np.floor(len(text) * (context_size / num_tokens)))
                # if num tokens is larger than context length, only use the start
                inputs.append(text[0: cutoff])
            else:
--- a/api/core/model_runtime/model_providers/perfxcloud/text_embedding/text_embedding.py
+++ b/api/core/model_runtime/model_providers/perfxcloud/text_embedding/text_embedding.py
@ -79,7 +79,7 @@ class OAICompatEmbeddingModel(_CommonOAI_API_Compat, TextEmbeddingModel):
            num_tokens = self._get_num_tokens_by_gpt2(text)

            if num_tokens >= context_size:
-                cutoff = int(len(text) * (np.floor(context_size / num_tokens)))
+                cutoff = int(np.floor(len(text) * (context_size / num_tokens)))
                # if num tokens is larger than context length, only use the start
                inputs.append(text[0: cutoff])
            else:
--- a/api/core/model_runtime/model_providers/siliconflow/llm/_position.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/_position.yaml
@ -1,8 +1,20 @@
- deepseek-v2-chat
- qwen2-72b-instruct
- qwen2-57b-a14b-instruct
- qwen2-7b-instruct
- yi-1.5-34b-chat
- yi-1.5-9b-chat
- yi-1.5-6b-chat
- glm4-9B-chat
+- Qwen/Qwen2-72B-Instruct
+- Qwen/Qwen2-57B-A14B-Instruct
+- Qwen/Qwen2-7B-Instruct
+- Qwen/Qwen2-1.5B-Instruct
+- 01-ai/Yi-1.5-34B-Chat
+- 01-ai/Yi-1.5-9B-Chat-16K
+- 01-ai/Yi-1.5-6B-Chat
+- THUDM/glm-4-9b-chat
+- deepseek-ai/DeepSeek-V2-Chat
+- deepseek-ai/DeepSeek-Coder-V2-Instruct
+- internlm/internlm2_5-7b-chat
+- google/gemma-2-27b-it
+- google/gemma-2-9b-it
+- meta-llama/Meta-Llama-3-70B-Instruct
+- meta-llama/Meta-Llama-3-8B-Instruct
+- meta-llama/Meta-Llama-3.1-405B-Instruct
+- meta-llama/Meta-Llama-3.1-70B-Instruct
+- meta-llama/Meta-Llama-3.1-8B-Instruct
+- mistralai/Mixtral-8x7B-Instruct-v0.1
+- mistralai/Mistral-7B-Instruct-v0.2
--- a/api/core/model_runtime/model_providers/siliconflow/llm/deepseek-v2-chat.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/deepseek-v2-chat.yaml
@ -1,4 +1,4 @@
-model: deepseek-ai/deepseek-v2-chat
+model: deepseek-ai/DeepSeek-V2-Chat
 label:
  en_US: deepseek-ai/DeepSeek-V2-Chat
 model_type: llm
--- a/api/core/model_runtime/model_providers/siliconflow/llm/gemma-2-27b-it.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/gemma-2-27b-it.yaml
@ -0,0 +1,30 @@
+model: google/gemma-2-27b-it
+label:
+  en_US: google/gemma-2-27b-it
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 8196
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 4096
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: '1.26'
+  output: '1.26'
+  unit: '0.000001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/gemma-2-9b-it.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/gemma-2-9b-it.yaml
@ -0,0 +1,30 @@
+model: google/gemma-2-9b-it
+label:
+  en_US: google/gemma-2-9b-it
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 8196
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 4096
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: '0'
+  output: '0'
+  unit: '0.000001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/glm4-9b-chat.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/glm4-9b-chat.yaml
@ -1,4 +1,4 @@
-model: zhipuai/glm4-9B-chat
+model: THUDM/glm-4-9b-chat
 label:
  en_US: THUDM/glm-4-9b-chat
 model_type: llm
@ -24,7 +24,7 @@ parameter_rules:
  - name: frequency_penalty
    use_template: frequency_penalty
 pricing:
-  input: '0.6'
-  output: '0.6'
+  input: '0'
+  output: '0'
  unit: '0.000001'
  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/internlm2_5-7b-chat.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/internlm2_5-7b-chat.yaml
@ -0,0 +1,30 @@
+model: internlm/internlm2_5-7b-chat
+label:
+  en_US: internlm/internlm2_5-7b-chat
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 32768
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 4096
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: '0'
+  output: '0'
+  unit: '0.000001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3-70b-instruct.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3-70b-instruct.yaml
@ -0,0 +1,30 @@
+model: meta-llama/Meta-Llama-3-70B-Instruct
+label:
+  en_US: meta-llama/Meta-Llama-3-70B-Instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 32768
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 4096
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: '4.13'
+  output: '4.13'
+  unit: '0.000001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3-8b-instruct.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3-8b-instruct.yaml
@ -0,0 +1,30 @@
+model: meta-llama/Meta-Llama-3-8B-Instruct
+label:
+  en_US: meta-llama/Meta-Llama-3-8B-Instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 8192
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 4096
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: '0'
+  output: '0'
+  unit: '0.000001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-405b-instruct.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-405b-instruct.yaml
@ -0,0 +1,30 @@
+model: meta-llama/Meta-Llama-3.1-405B-Instruct
+label:
+  en_US: meta-llama/Meta-Llama-3.1-405B-Instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 32768
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 4096
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: '21'
+  output: '21'
+  unit: '0.000001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-70b-instruct.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-70b-instruct.yaml
@ -0,0 +1,30 @@
+model: meta-llama/Meta-Llama-3.1-70B-Instruct
+label:
+  en_US: meta-llama/Meta-Llama-3.1-70B-Instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 32768
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 4096
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: '4.13'
+  output: '4.13'
+  unit: '0.000001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-8b-instruct.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/meta-mlama-3.1-8b-instruct.yaml
@ -0,0 +1,30 @@
+model: meta-llama/Meta-Llama-3.1-8B-Instruct
+label:
+  en_US: meta-llama/Meta-Llama-3.1-8B-Instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 8192
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 4096
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: '0'
+  output: '0'
+  unit: '0.000001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/mistral-7b-instruct-v0.2.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/mistral-7b-instruct-v0.2.yaml
@ -0,0 +1,30 @@
+model: mistralai/Mistral-7B-Instruct-v0.2
+label:
+  en_US: mistralai/Mistral-7B-Instruct-v0.2
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 32768
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 4096
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: '0'
+  output: '0'
+  unit: '0.000001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/mistral-8x7b-instruct-v0.1.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/mistral-8x7b-instruct-v0.1.yaml
@ -0,0 +1,30 @@
+model: mistralai/Mixtral-8x7B-Instruct-v0.1
+label:
+  en_US: mistralai/Mixtral-8x7B-Instruct-v0.1
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 32768
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 4096
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: '1.26'
+  output: '1.26'
+  unit: '0.000001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-1.5b-instruct.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-1.5b-instruct.yaml
@ -0,0 +1,30 @@
+model: Qwen/Qwen2-1.5B-Instruct
+label:
+  en_US: Qwen/Qwen2-1.5B-Instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 32768
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 4096
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: '0'
+  output: '0'
+  unit: '0.000001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-57b-a14b-instruct.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-57b-a14b-instruct.yaml
@ -1,4 +1,4 @@
-model: alibaba/Qwen2-57B-A14B-Instruct
+model: Qwen/Qwen2-57B-A14B-Instruct
 label:
  en_US: Qwen/Qwen2-57B-A14B-Instruct
 model_type: llm
--- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-72b-instruct.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-72b-instruct.yaml
@ -1,4 +1,4 @@
-model: alibaba/Qwen2-72B-Instruct
+model: Qwen/Qwen2-72B-Instruct
 label:
  en_US: Qwen/Qwen2-72B-Instruct
 model_type: llm
--- a/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-7b-instruct.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/qwen2-7b-instruct.yaml
@ -1,4 +1,4 @@
-model: alibaba/Qwen2-7B-Instruct
+model: Qwen/Qwen2-7B-Instruct
 label:
  en_US: Qwen/Qwen2-7B-Instruct
 model_type: llm
@ -24,7 +24,7 @@ parameter_rules:
  - name: frequency_penalty
    use_template: frequency_penalty
 pricing:
-  input: '0.35'
-  output: '0.35'
+  input: '0'
+  output: '0'
  unit: '0.000001'
  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-6b-chat.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-6b-chat.yaml
@ -24,7 +24,7 @@ parameter_rules:
  - name: frequency_penalty
    use_template: frequency_penalty
 pricing:
-  input: '0.35'
-  output: '0.35'
+  input: '0'
+  output: '0'
  unit: '0.000001'
  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-9b-chat.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/llm/yi-1.5-9b-chat.yaml
@ -1,4 +1,4 @@
-model: 01-ai/Yi-1.5-9B-Chat
+model: 01-ai/Yi-1.5-9B-Chat-16K
 label:
  en_US: 01-ai/Yi-1.5-9B-Chat-16K
 model_type: llm
@ -24,7 +24,7 @@ parameter_rules:
  - name: frequency_penalty
    use_template: frequency_penalty
 pricing:
-  input: '0.42'
-  output: '0.42'
+  input: '0'
+  output: '0'
  unit: '0.000001'
  currency: RMB
--- a/api/core/model_runtime/model_providers/siliconflow/siliconflow.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/siliconflow.yaml
@ -15,6 +15,7 @@ help:
    en_US: https://cloud.siliconflow.cn/keys
 supported_model_types:
  - llm
+  - text-embedding
 configurate_methods:
  - predefined-model
 provider_credential_schema:
--- a/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-large-en-v1.5.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-large-en-v1.5.yaml
@ -0,0 +1,5 @@
+model: BAAI/bge-large-en-v1.5
+model_type: text-embedding
+model_properties:
+  context_size: 512
+  max_chunks: 1
--- a/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-large-zh-v1.5.yaml
+++ b/api/core/model_runtime/model_providers/siliconflow/text_embedding/bge-large-zh-v1.5.yaml
@ -0,0 +1,5 @@
+model: BAAI/bge-large-zh-v1.5
+model_type: text-embedding
+model_properties:
+  context_size: 512
+  max_chunks: 1
--- a/api/core/model_runtime/model_providers/siliconflow/text_embedding/text_embedding.py
+++ b/api/core/model_runtime/model_providers/siliconflow/text_embedding/text_embedding.py
@ -0,0 +1,29 @@
+from typing import Optional
+
+from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult
+from core.model_runtime.model_providers.openai_api_compatible.text_embedding.text_embedding import (
+    OAICompatEmbeddingModel,
+)
+
+
+class SiliconflowTextEmbeddingModel(OAICompatEmbeddingModel):
+    """
+    Model class for Siliconflow text embedding model.
+    """
+    def validate_credentials(self, model: str, credentials: dict) -> None:
+        self._add_custom_parameters(credentials)
+        super().validate_credentials(model, credentials)
+
+    def _invoke(self, model: str, credentials: dict,
+                texts: list[str], user: Optional[str] = None) \
+            -> TextEmbeddingResult:
+        self._add_custom_parameters(credentials)
+        return super()._invoke(model, credentials, texts, user)
+    
+    def get_num_tokens(self, model: str, credentials: dict, texts: list[str]) -> int:
+        self._add_custom_parameters(credentials)
+        return super().get_num_tokens(model, credentials, texts)
+    
+    @classmethod
+    def _add_custom_parameters(cls, credentials: dict) -> None:
+        credentials['endpoint_url'] = 'https://api.siliconflow.cn/v1'
--- a/api/core/model_runtime/model_providers/stepfun/llm/_position.yaml
+++ b/api/core/model_runtime/model_providers/stepfun/llm/_position.yaml
@ -2,5 +2,7 @@
 - step-1-32k
 - step-1-128k
 - step-1-256k
+- step-1-flash
+- step-2-16k
 - step-1v-8k
 - step-1v-32k
--- a/api/core/model_runtime/model_providers/stepfun/llm/step-1-flash.yaml
+++ b/api/core/model_runtime/model_providers/stepfun/llm/step-1-flash.yaml
@ -0,0 +1,25 @@
+model: step-1-flash
+label:
+  zh_Hans: step-1-flash
+  en_US: step-1-flash
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 8000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: max_tokens
+    use_template: max_tokens
+    default: 512
+    min: 1
+    max: 8000
+pricing:
+  input: '0.001'
+  output: '0.004'
+  unit: '0.001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/stepfun/llm/step-1v-32k.yaml
+++ b/api/core/model_runtime/model_providers/stepfun/llm/step-1v-32k.yaml
@ -5,6 +5,9 @@ label:
 model_type: llm
 features:
  - vision
+  - tool-call
+  - multi-tool-call
+  - stream-tool-call
 model_properties:
  mode: chat
  context_size: 32000
--- a/api/core/model_runtime/model_providers/stepfun/llm/step-1v-8k.yaml
+++ b/api/core/model_runtime/model_providers/stepfun/llm/step-1v-8k.yaml
@ -5,6 +5,9 @@ label:
 model_type: llm
 features:
  - vision
+  - tool-call
+  - multi-tool-call
+  - stream-tool-call
 model_properties:
  mode: chat
  context_size: 8192
--- a/api/core/model_runtime/model_providers/stepfun/llm/step-2-16k.yaml
+++ b/api/core/model_runtime/model_providers/stepfun/llm/step-2-16k.yaml
@ -0,0 +1,28 @@
+model: step-2-16k
+label:
+  zh_Hans: step-2-16k
+  en_US: step-2-16k
+model_type: llm
+features:
+  - agent-thought
+  - tool-call
+  - multi-tool-call
+  - stream-tool-call
+model_properties:
+  mode: chat
+  context_size: 16000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: max_tokens
+    use_template: max_tokens
+    default: 1024
+    min: 1
+    max: 16000
+pricing:
+  input: '0.038'
+  output: '0.120'
+  unit: '0.001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/wenxin/llm/ernie_bot.py
+++ b/api/core/model_runtime/model_providers/wenxin/llm/ernie_bot.py
@ -140,8 +140,9 @@ class ErnieBotModel:
        'ernie-lite-8k-0308': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-lite-8k',
        'ernie-character-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-char-8k',
        'ernie-character-8k-0321': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-char-8k',
-        'ernie-4.0-tutbo-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-4.0-turbo-8k',
-        'ernie-4.0-tutbo-8k-preview': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-4.0-turbo-8k-preview',
+        'ernie-4.0-turbo-8k': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-4.0-turbo-8k',
+        'ernie-4.0-turbo-8k-preview': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie-4.0-turbo-8k-preview',
+        'yi_34b_chat': 'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/yi_34b_chat',
    }

    function_calling_supports = [
@ -154,7 +155,8 @@ class ErnieBotModel:
        'ernie-3.5-128k',
        'ernie-4.0-8k',
        'ernie-4.0-turbo-8k',
-        'ernie-4.0-turbo-8k-preview'
+        'ernie-4.0-turbo-8k-preview',
+        'yi_34b_chat'
    ]

    api_key: str = ''
--- a/api/core/model_runtime/model_providers/wenxin/llm/yi_34b_chat.yaml
+++ b/api/core/model_runtime/model_providers/wenxin/llm/yi_34b_chat.yaml
@ -0,0 +1,30 @@
+model: yi_34b_chat
+label:
+  en_US: yi_34b_chat
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 32000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    min: 0.1
+    max: 1.0
+    default: 0.95
+  - name: top_p
+    use_template: top_p
+    min: 0
+    max: 1.0
+    default: 0.7
+  - name: max_tokens
+    use_template: max_tokens
+    default: 4096
+    min: 2
+    max: 4096
+  - name: presence_penalty
+    use_template: presence_penalty
+    default: 1.0
+    min: 1.0
+    max: 2.0
--- a/api/core/model_runtime/model_providers/zhinao/init.py
+++ b/api/core/model_runtime/model_providers/zhinao/init.py
--- a/api/core/model_runtime/model_providers/zhinao/_assets/icon_l_en.svg
+++ b/api/core/model_runtime/model_providers/zhinao/_assets/icon_l_en.svg
--- a/api/core/model_runtime/model_providers/zhinao/_assets/icon_s_en.svg
+++ b/api/core/model_runtime/model_providers/zhinao/_assets/icon_s_en.svg
--- a/api/core/model_runtime/model_providers/zhinao/llm/360gpt-turbo-responsibility-8k.yaml
+++ b/api/core/model_runtime/model_providers/zhinao/llm/360gpt-turbo-responsibility-8k.yaml
@ -0,0 +1,36 @@
+model: 360gpt-turbo-responsibility-8k
+label:
+  zh_Hans: 360gpt-turbo-responsibility-8k
+  en_US: 360gpt-turbo-responsibility-8k
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 8192
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    min: 0
+    max: 1
+    default: 0.5
+  - name: top_p
+    use_template: top_p
+    min: 0
+    max: 1
+    default: 1
+  - name: max_tokens
+    use_template: max_tokens
+    min: 1
+    max: 8192
+    default: 1024
+  - name: frequency_penalty
+    use_template: frequency_penalty
+    min: -2
+    max: 2
+    default: 0
+  - name: presence_penalty
+    use_template: presence_penalty
+    min: -2
+    max: 2
+    default: 0
--- a/api/core/model_runtime/model_providers/zhinao/llm/360gpt-turbo.yaml
+++ b/api/core/model_runtime/model_providers/zhinao/llm/360gpt-turbo.yaml
@ -0,0 +1,36 @@
+model: 360gpt-turbo
+label:
+  zh_Hans: 360gpt-turbo
+  en_US: 360gpt-turbo
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 2048
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    min: 0
+    max: 1
+    default: 0.5
+  - name: top_p
+    use_template: top_p
+    min: 0
+    max: 1
+    default: 1
+  - name: max_tokens
+    use_template: max_tokens
+    min: 1
+    max: 2048
+    default: 1024
+  - name: frequency_penalty
+    use_template: frequency_penalty
+    min: -2
+    max: 2
+    default: 0
+  - name: presence_penalty
+    use_template: presence_penalty
+    min: -2
+    max: 2
+    default: 0
--- a/api/core/model_runtime/model_providers/zhinao/llm/360gpt2-pro.yaml
+++ b/api/core/model_runtime/model_providers/zhinao/llm/360gpt2-pro.yaml
@ -0,0 +1,36 @@
+model: 360gpt2-pro
+label:
+  zh_Hans: 360gpt2-pro
+  en_US: 360gpt2-pro
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 2048
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    min: 0
+    max: 1
+    default: 0.5
+  - name: top_p
+    use_template: top_p
+    min: 0
+    max: 1
+    default: 1
+  - name: max_tokens
+    use_template: max_tokens
+    min: 1
+    max: 2048
+    default: 1024
+  - name: frequency_penalty
+    use_template: frequency_penalty
+    min: -2
+    max: 2
+    default: 0
+  - name: presence_penalty
+    use_template: presence_penalty
+    min: -2
+    max: 2
+    default: 0
--- a/api/core/model_runtime/model_providers/zhinao/llm/init.py
+++ b/api/core/model_runtime/model_providers/zhinao/llm/init.py
--- a/api/core/model_runtime/model_providers/zhinao/llm/_position.yaml
+++ b/api/core/model_runtime/model_providers/zhinao/llm/_position.yaml
@ -0,0 +1,3 @@
+- 360gpt2-pro
+- 360gpt-turbo
+- 360gpt-turbo-responsibility-8k
--- a/api/core/model_runtime/model_providers/zhinao/llm/llm.py
+++ b/api/core/model_runtime/model_providers/zhinao/llm/llm.py
@ -0,0 +1,25 @@
+from collections.abc import Generator
+from typing import Optional, Union
+
+from core.model_runtime.entities.llm_entities import LLMResult
+from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool
+from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel
+
+
+class ZhinaoLargeLanguageModel(OAIAPICompatLargeLanguageModel):
+    def _invoke(self, model: str, credentials: dict,
+                prompt_messages: list[PromptMessage], model_parameters: dict,
+                tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
+                stream: bool = True, user: Optional[str] = None) \
+            -> Union[LLMResult, Generator]:
+        self._add_custom_parameters(credentials)
+        return super()._invoke(model, credentials, prompt_messages, model_parameters, tools, stop, stream)
+
+    def validate_credentials(self, model: str, credentials: dict) -> None:
+        self._add_custom_parameters(credentials)
+        super().validate_credentials(model, credentials)
+
+    @classmethod
+    def _add_custom_parameters(cls, credentials: dict) -> None:
+        credentials['mode'] = 'chat'
+        credentials['endpoint_url'] = 'https://api.360.cn/v1'
--- a/api/core/model_runtime/model_providers/zhinao/zhinao.py
+++ b/api/core/model_runtime/model_providers/zhinao/zhinao.py
@ -0,0 +1,32 @@
+import logging
+
+from core.model_runtime.entities.model_entities import ModelType
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.__base.model_provider import ModelProvider
+
+logger = logging.getLogger(__name__)
+
+
+class ZhinaoProvider(ModelProvider):
+
+    def validate_provider_credentials(self, credentials: dict) -> None:
+        """
+        Validate provider credentials
+        if validate failed, raise exception
+
+        :param credentials: provider credentials, credentials form defined in `provider_credential_schema`.
+        """
+        try:
+            model_instance = self.get_model_instance(ModelType.LLM)
+
+            # Use `360gpt-turbo` model for validate,
+            # no matter what model you pass in, text completion model or chat model
+            model_instance.validate_credentials(
+                model='360gpt-turbo',
+                credentials=credentials
+            )
+        except CredentialsValidateFailedError as ex:
+            raise ex
+        except Exception as ex:
+            logger.exception(f'{self.get_provider_schema().provider} credentials validate failed')
+            raise ex
--- a/api/core/model_runtime/model_providers/zhinao/zhinao.yaml
+++ b/api/core/model_runtime/model_providers/zhinao/zhinao.yaml
@ -0,0 +1,32 @@
+provider: zhinao
+label:
+  en_US: 360 AI
+  zh_Hans: 360 智脑
+description:
+  en_US: Models provided by 360 AI.
+  zh_Hans: 360 智脑提供的模型。
+icon_small:
+  en_US: icon_s_en.svg
+icon_large:
+  en_US: icon_l_en.svg
+background: "#e3f0ff"
+help:
+  title:
+    en_US: Get your API Key from 360 AI.
+    zh_Hans: 从360 智脑获取 API Key
+  url:
+    en_US: https://ai.360.com/platform/keys
+supported_model_types:
+  - llm
+configurate_methods:
+  - predefined-model
+provider_credential_schema:
+  credential_form_schemas:
+    - variable: api_key
+      label:
+        en_US: API Key
+      type: secret-input
+      required: true
+      placeholder:
+        zh_Hans: 在此输入您的 API Key
+        en_US: Enter your API Key
--- a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-0520.yaml
+++ b/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-0520.yaml
@ -37,3 +37,8 @@ parameter_rules:
    default: 1024
    min: 1
    max: 8192
+pricing:
+  input: '0.1'
+  output: '0.1'
+  unit: '0.001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-air.yaml
+++ b/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-air.yaml
@ -37,3 +37,8 @@ parameter_rules:
    default: 1024
    min: 1
    max: 8192
+pricing:
+  input: '0.001'
+  output: '0.001'
+  unit: '0.001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-airx.yaml
+++ b/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-airx.yaml
@ -37,3 +37,8 @@ parameter_rules:
    default: 1024
    min: 1
    max: 8192
+pricing:
+  input: '0.01'
+  output: '0.01'
+  unit: '0.001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-flash.yaml
+++ b/api/core/model_runtime/model_providers/zhipuai/llm/glm-4-flash.yaml
@ -37,3 +37,8 @@ parameter_rules:
    default: 1024
    min: 1
    max: 8192
+pricing:
+  input: '0.0001'
+  output: '0.0001'
+  unit: '0.001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/zhipuai/llm/glm_4_long.yaml
+++ b/api/core/model_runtime/model_providers/zhipuai/llm/glm_4_long.yaml
@ -0,0 +1,33 @@
+model: glm-4-long
+label:
+  en_US: glm-4-long
+model_type: llm
+features:
+  - multi-tool-call
+  - agent-thought
+  - stream-tool-call
+model_properties:
+  mode: chat
+  context_size: 10240
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    default: 0.95
+    min: 0.0
+    max: 1.0
+    help:
+      zh_Hans: 采样温度，控制输出的随机性，必须为正数取值范围是：(0.0,1.0]，不能等于 0,默认值为 0.95 值越大，会使输出更随机，更具创造性；值越小，输出会更加稳定或确定建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。
+      en_US: Sampling temperature, controls the randomness of the output, must be a positive number. The value range is (0.0,1.0], which cannot be equal to 0. The default value is 0.95. The larger the value, the more random and creative the output will be; the smaller the value, The output will be more stable or certain. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time.
+  - name: top_p
+    use_template: top_p
+    default: 0.7
+    min: 0.0
+    max: 1.0
+    help:
+      zh_Hans: 用温度取样的另一种方法，称为核取样取值范围是：(0.0, 1.0) 开区间，不能等于 0 或 1，默认值为 0.7 模型考虑具有 top_p 概率质量tokens的结果例如：0.1 意味着模型解码器只考虑从前 10% 的概率的候选集中取 tokens 建议您根据应用场景调整 top_p 或 temperature 参数，但不要同时调整两个参数。
+      en_US: Another method of temperature sampling is called kernel sampling. The value range is (0.0, 1.0) open interval, which cannot be equal to 0 or 1. The default value is 0.7. The model considers the results with top_p probability mass tokens. For example 0.1 means The model decoder only considers tokens from the candidate set with the top 10% probability. It is recommended that you adjust the top_p or temperature parameters according to the application scenario, but do not adjust both parameters at the same time.
+  - name: max_tokens
+    use_template: max_tokens
+    default: 1024
+    min: 1
+    max: 4096
--- a/api/core/model_runtime/model_providers/zhipuai/text_embedding/embedding-2.yaml
+++ b/api/core/model_runtime/model_providers/zhipuai/text_embedding/embedding-2.yaml
@ -1,4 +1,8 @@
 model: embedding-2
 model_type: text-embedding
 model_properties:
-  context_size: 512
+  context_size: 8192
+pricing:
+  input: '0.0005'
+  unit: '0.001'
+  currency: RMB
--- a/api/core/model_runtime/model_providers/zhipuai/text_embedding/embedding-3.yaml
+++ b/api/core/model_runtime/model_providers/zhipuai/text_embedding/embedding-3.yaml
@ -0,0 +1,8 @@
+model: embedding-3
+model_type: text-embedding
+model_properties:
+  context_size: 8192
+pricing:
+  input: '0.0005'
+  unit: '0.001'
+  currency: RMB
--- a/api/core/moderation/input_moderation.py
+++ b/api/core/moderation/input_moderation.py
@ -4,7 +4,8 @@ from typing import Optional
 from core.app.app_config.entities import AppConfig
 from core.moderation.base import ModerationAction, ModerationException
 from core.moderation.factory import ModerationFactory
-from core.ops.ops_trace_manager import TraceQueueManager, TraceTask, TraceTaskName
+from core.ops.entities.trace_entity import TraceTaskName
+from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
 from core.ops.utils import measure_time

 logger = logging.getLogger(__name__)
--- a/api/core/ops/entities/trace_entity.py
+++ b/api/core/ops/entities/trace_entity.py
@ -1,4 +1,5 @@
 from datetime import datetime
+from enum import Enum
 from typing import Any, Optional, Union

 from pydantic import BaseModel, ConfigDict, field_validator
@ -105,4 +106,15 @@ trace_info_info_map = {
    'DatasetRetrievalTraceInfo': DatasetRetrievalTraceInfo,
    'ToolTraceInfo': ToolTraceInfo,
    'GenerateNameTraceInfo': GenerateNameTraceInfo,
-}
+}
+
+
+class TraceTaskName(str, Enum):
+    CONVERSATION_TRACE = 'conversation'
+    WORKFLOW_TRACE = 'workflow'
+    MESSAGE_TRACE = 'message'
+    MODERATION_TRACE = 'moderation'
+    SUGGESTED_QUESTION_TRACE = 'suggested_question'
+    DATASET_RETRIEVAL_TRACE = 'dataset_retrieval'
+    TOOL_TRACE = 'tool'
+    GENERATE_NAME_TRACE = 'generate_conversation_name'
--- a/api/core/ops/langfuse_trace/entities/langfuse_trace_entity.py
+++ b/api/core/ops/langfuse_trace/entities/langfuse_trace_entity.py
@ -50,10 +50,11 @@ class LangfuseTrace(BaseModel):
    """
    Langfuse trace model
    """
+
    id: Optional[str] = Field(
        default=None,
        description="The id of the trace can be set, defaults to a random id. Used to link traces to external systems "
-                    "or when creating a distributed trace. Traces are upserted on id.",
+        "or when creating a distributed trace. Traces are upserted on id.",
    )
    name: Optional[str] = Field(
        default=None,
@ -68,7 +69,7 @@ class LangfuseTrace(BaseModel):
    metadata: Optional[dict[str, Any]] = Field(
        default=None,
        description="Additional metadata of the trace. Can be any JSON object. Metadata is merged when being updated "
-                    "via the API.",
+        "via the API.",
    )
    user_id: Optional[str] = Field(
        default=None,
@ -81,22 +82,22 @@ class LangfuseTrace(BaseModel):
    version: Optional[str] = Field(
        default=None,
        description="The version of the trace type. Used to understand how changes to the trace type affect metrics. "
-                    "Useful in debugging.",
+        "Useful in debugging.",
    )
    release: Optional[str] = Field(
        default=None,
        description="The release identifier of the current deployment. Used to understand how changes of different "
-                    "deployments affect metrics. Useful in debugging.",
+        "deployments affect metrics. Useful in debugging.",
    )
    tags: Optional[list[str]] = Field(
        default=None,
        description="Tags are used to categorize or label traces. Traces can be filtered by tags in the UI and GET "
-                    "API. Tags can also be changed in the UI. Tags are merged and never deleted via the API.",
+        "API. Tags can also be changed in the UI. Tags are merged and never deleted via the API.",
    )
    public: Optional[bool] = Field(
        default=None,
        description="You can make a trace public to share it via a public link. This allows others to view the trace "
-                    "without needing to log in or be members of your Langfuse project.",
+        "without needing to log in or be members of your Langfuse project.",
    )

    @field_validator("input", "output")
@ -109,6 +110,7 @@ class LangfuseSpan(BaseModel):
    """
    Langfuse span model
    """
+
    id: Optional[str] = Field(
        default=None,
        description="The id of the span can be set, otherwise a random id is generated. Spans are upserted on id.",
@ -140,17 +142,17 @@ class LangfuseSpan(BaseModel):
    metadata: Optional[dict[str, Any]] = Field(
        default=None,
        description="Additional metadata of the span. Can be any JSON object. Metadata is merged when being updated "
-                    "via the API.",
+        "via the API.",
    )
    level: Optional[str] = Field(
        default=None,
        description="The level of the span. Can be DEBUG, DEFAULT, WARNING or ERROR. Used for sorting/filtering of "
-                    "traces with elevated error levels and for highlighting in the UI.",
+        "traces with elevated error levels and for highlighting in the UI.",
    )
    status_message: Optional[str] = Field(
        default=None,
        description="The status message of the span. Additional field for context of the event. E.g. the error "
-                    "message of an error event.",
+        "message of an error event.",
    )
    input: Optional[Union[str, dict[str, Any], list, None]] = Field(
        default=None, description="The input of the span. Can be any JSON object."
@ -161,7 +163,7 @@ class LangfuseSpan(BaseModel):
    version: Optional[str] = Field(
        default=None,
        description="The version of the span type. Used to understand how changes to the span type affect metrics. "
-                    "Useful in debugging.",
+        "Useful in debugging.",
    )
    parent_observation_id: Optional[str] = Field(
        default=None,
@ -185,10 +187,9 @@ class UnitEnum(str, Enum):
 class GenerationUsage(BaseModel):
    promptTokens: Optional[int] = None
    completionTokens: Optional[int] = None
-    totalTokens: Optional[int] = None
+    total: Optional[int] = None
    input: Optional[int] = None
    output: Optional[int] = None
-    total: Optional[int] = None
    unit: Optional[UnitEnum] = None
    inputCost: Optional[float] = None
    outputCost: Optional[float] = None
@ -224,15 +225,13 @@ class LangfuseGeneration(BaseModel):
    completion_start_time: Optional[datetime | str] = Field(
        default=None,
        description="The time at which the completion started (streaming). Set it to get latency analytics broken "
-                    "down into time until completion started and completion duration.",
+        "down into time until completion started and completion duration.",
    )
    end_time: Optional[datetime | str] = Field(
        default=None,
        description="The time at which the generation ended. Automatically set by generation.end().",
    )
-    model: Optional[str] = Field(
-        default=None, description="The name of the model used for the generation."
-    )
+    model: Optional[str] = Field(default=None, description="The name of the model used for the generation.")
    model_parameters: Optional[dict[str, Any]] = Field(
        default=None,
        description="The parameters of the model used for the generation; can be any key-value pairs.",
@ -248,27 +247,27 @@ class LangfuseGeneration(BaseModel):
    usage: Optional[GenerationUsage] = Field(
        default=None,
        description="The usage object supports the OpenAi structure with tokens and a more generic version with "
-                    "detailed costs and units.",
+        "detailed costs and units.",
    )
    metadata: Optional[dict[str, Any]] = Field(
        default=None,
        description="Additional metadata of the generation. Can be any JSON object. Metadata is merged when being "
-                    "updated via the API.",
+        "updated via the API.",
    )
    level: Optional[LevelEnum] = Field(
        default=None,
        description="The level of the generation. Can be DEBUG, DEFAULT, WARNING or ERROR. Used for sorting/filtering "
-                    "of traces with elevated error levels and for highlighting in the UI.",
+        "of traces with elevated error levels and for highlighting in the UI.",
    )
    status_message: Optional[str] = Field(
        default=None,
        description="The status message of the generation. Additional field for context of the event. E.g. the error "
-                    "message of an error event.",
+        "message of an error event.",
    )
    version: Optional[str] = Field(
        default=None,
        description="The version of the generation type. Used to understand how changes to the span type affect "
-                    "metrics. Useful in debugging.",
+        "metrics. Useful in debugging.",
    )

    model_config = ConfigDict(protected_namespaces=())
@ -277,4 +276,3 @@ class LangfuseGeneration(BaseModel):
    def ensure_dict(cls, v, info: ValidationInfo):
        field_name = info.field_name
        return validate_input_output(v, field_name)
-
--- a/api/core/ops/langfuse_trace/langfuse_trace.py
+++ b/api/core/ops/langfuse_trace/langfuse_trace.py
@ -16,6 +16,7 @@ from core.ops.entities.trace_entity import (
    ModerationTraceInfo,
    SuggestedQuestionTraceInfo,
    ToolTraceInfo,
+    TraceTaskName,
    WorkflowTraceInfo,
 )
 from core.ops.langfuse_trace.entities.langfuse_trace_entity import (
@ -68,9 +69,9 @@ class LangFuseDataTrace(BaseTraceInstance):
        user_id = trace_info.metadata.get("user_id")
        if trace_info.message_id:
            trace_id = trace_info.message_id
-            name = f"message_{trace_info.message_id}"
+            name = TraceTaskName.MESSAGE_TRACE.value
            trace_data = LangfuseTrace(
-                id=trace_info.message_id,
+                id=trace_id,
                user_id=user_id,
                name=name,
                input=trace_info.workflow_run_inputs,
@ -78,11 +79,13 @@ class LangFuseDataTrace(BaseTraceInstance):
                metadata=trace_info.metadata,
                session_id=trace_info.conversation_id,
                tags=["message", "workflow"],
+                created_at=trace_info.start_time,
+                updated_at=trace_info.end_time,
            )
            self.add_trace(langfuse_trace_data=trace_data)
            workflow_span_data = LangfuseSpan(
-                id=trace_info.workflow_app_log_id if trace_info.workflow_app_log_id else trace_info.workflow_run_id,
-                name=f"workflow_{trace_info.workflow_app_log_id}" if trace_info.workflow_app_log_id else f"workflow_{trace_info.workflow_run_id}",
+                id=(trace_info.workflow_app_log_id if trace_info.workflow_app_log_id else trace_info.workflow_run_id),
+                name=TraceTaskName.WORKFLOW_TRACE.value,
                input=trace_info.workflow_run_inputs,
                output=trace_info.workflow_run_outputs,
                trace_id=trace_id,
@ -97,7 +100,7 @@ class LangFuseDataTrace(BaseTraceInstance):
            trace_data = LangfuseTrace(
                id=trace_id,
                user_id=user_id,
-                name=f"workflow_{trace_info.workflow_app_log_id}" if trace_info.workflow_app_log_id else f"workflow_{trace_info.workflow_run_id}",
+                name=TraceTaskName.WORKFLOW_TRACE.value,
                input=trace_info.workflow_run_inputs,
                output=trace_info.workflow_run_outputs,
                metadata=trace_info.metadata,
@ -134,14 +137,12 @@ class LangFuseDataTrace(BaseTraceInstance):
            node_type = node_execution.node_type
            status = node_execution.status
            if node_type == "llm":
-                inputs = json.loads(node_execution.process_data).get(
-                    "prompts", {}
-                    ) if node_execution.process_data else {}
+                inputs = (
+                    json.loads(node_execution.process_data).get("prompts", {}) if node_execution.process_data else {}
+                )
            else:
                inputs = json.loads(node_execution.inputs) if node_execution.inputs else {}
-            outputs = (
-                json.loads(node_execution.outputs) if node_execution.outputs else {}
-            )
+            outputs = json.loads(node_execution.outputs) if node_execution.outputs else {}
            created_at = node_execution.created_at if node_execution.created_at else datetime.now()
            elapsed_time = node_execution.elapsed_time
            finished_at = created_at + timedelta(seconds=elapsed_time)
@ -163,28 +164,30 @@ class LangFuseDataTrace(BaseTraceInstance):
            if trace_info.message_id:
                span_data = LangfuseSpan(
                    id=node_execution_id,
-                    name=f"{node_name}_{node_execution_id}",
+                    name=node_type,
                    input=inputs,
                    output=outputs,
                    trace_id=trace_id,
                    start_time=created_at,
                    end_time=finished_at,
                    metadata=metadata,
-                    level=LevelEnum.DEFAULT if status == 'succeeded' else LevelEnum.ERROR,
+                    level=(LevelEnum.DEFAULT if status == "succeeded" else LevelEnum.ERROR),
                    status_message=trace_info.error if trace_info.error else "",
-                    parent_observation_id=trace_info.workflow_app_log_id if trace_info.workflow_app_log_id else trace_info.workflow_run_id,
+                    parent_observation_id=(
+                        trace_info.workflow_app_log_id if trace_info.workflow_app_log_id else trace_info.workflow_run_id
+                    ),
                )
            else:
                span_data = LangfuseSpan(
                    id=node_execution_id,
-                    name=f"{node_name}_{node_execution_id}",
+                    name=node_type,
                    input=inputs,
                    output=outputs,
                    trace_id=trace_id,
                    start_time=created_at,
                    end_time=finished_at,
                    metadata=metadata,
-                    level=LevelEnum.DEFAULT if status == 'succeeded' else LevelEnum.ERROR,
+                    level=(LevelEnum.DEFAULT if status == "succeeded" else LevelEnum.ERROR),
                    status_message=trace_info.error if trace_info.error else "",
                )

@ -195,11 +198,11 @@ class LangFuseDataTrace(BaseTraceInstance):
                total_token = metadata.get("total_tokens", 0)
                # add generation
                generation_usage = GenerationUsage(
-                    totalTokens=total_token,
+                    total=total_token,
                )

                node_generation_data = LangfuseGeneration(
-                    name=f"generation_{node_execution_id}",
+                    name="llm",
                    trace_id=trace_id,
                    parent_observation_id=node_execution_id,
                    start_time=created_at,
@ -207,16 +210,14 @@ class LangFuseDataTrace(BaseTraceInstance):
                    input=inputs,
                    output=outputs,
                    metadata=metadata,
-                    level=LevelEnum.DEFAULT if status == 'succeeded' else LevelEnum.ERROR,
+                    level=(LevelEnum.DEFAULT if status == "succeeded" else LevelEnum.ERROR),
                    status_message=trace_info.error if trace_info.error else "",
                    usage=generation_usage,
                )

                self.add_generation(langfuse_generation_data=node_generation_data)

-    def message_trace(
-        self, trace_info: MessageTraceInfo, **kwargs
-    ):
+    def message_trace(self, trace_info: MessageTraceInfo, **kwargs):
        # get message file data
        file_list = trace_info.file_list
        metadata = trace_info.metadata
@ -225,9 +226,9 @@ class LangFuseDataTrace(BaseTraceInstance):

        user_id = message_data.from_account_id
        if message_data.from_end_user_id:
-            end_user_data: EndUser = db.session.query(EndUser).filter(
-                EndUser.id == message_data.from_end_user_id
-            ).first()
+            end_user_data: EndUser = (
+                db.session.query(EndUser).filter(EndUser.id == message_data.from_end_user_id).first()
+            )
            if end_user_data is not None:
                user_id = end_user_data.session_id
                metadata["user_id"] = user_id
@ -235,7 +236,7 @@ class LangFuseDataTrace(BaseTraceInstance):
        trace_data = LangfuseTrace(
            id=message_id,
            user_id=user_id,
-            name=f"message_{message_id}",
+            name=TraceTaskName.MESSAGE_TRACE.value,
            input={
                "message": trace_info.inputs,
                "files": file_list,
@ -258,7 +259,6 @@ class LangFuseDataTrace(BaseTraceInstance):

        # start add span
        generation_usage = GenerationUsage(
-            totalTokens=trace_info.total_tokens,
            input=trace_info.message_tokens,
            output=trace_info.answer_tokens,
            total=trace_info.total_tokens,
@ -267,7 +267,7 @@ class LangFuseDataTrace(BaseTraceInstance):
        )

        langfuse_generation_data = LangfuseGeneration(
-            name=f"generation_{message_id}",
+            name="llm",
            trace_id=message_id,
            start_time=trace_info.start_time,
            end_time=trace_info.end_time,
@ -275,7 +275,7 @@ class LangFuseDataTrace(BaseTraceInstance):
            input=trace_info.inputs,
            output=message_data.answer,
            metadata=metadata,
-            level=LevelEnum.DEFAULT if message_data.status != 'error' else LevelEnum.ERROR,
+            level=(LevelEnum.DEFAULT if message_data.status != "error" else LevelEnum.ERROR),
            status_message=message_data.error if message_data.error else "",
            usage=generation_usage,
        )
@ -284,7 +284,7 @@ class LangFuseDataTrace(BaseTraceInstance):

    def moderation_trace(self, trace_info: ModerationTraceInfo):
        span_data = LangfuseSpan(
-            name="moderation",
+            name=TraceTaskName.MODERATION_TRACE.value,
            input=trace_info.inputs,
            output={
                "action": trace_info.action,
@ -303,22 +303,21 @@ class LangFuseDataTrace(BaseTraceInstance):
    def suggested_question_trace(self, trace_info: SuggestedQuestionTraceInfo):
        message_data = trace_info.message_data
        generation_usage = GenerationUsage(
-            totalTokens=len(str(trace_info.suggested_question)),
+            total=len(str(trace_info.suggested_question)),
            input=len(trace_info.inputs),
            output=len(trace_info.suggested_question),
-            total=len(trace_info.suggested_question),
            unit=UnitEnum.CHARACTERS,
        )

        generation_data = LangfuseGeneration(
-            name="suggested_question",
+            name=TraceTaskName.SUGGESTED_QUESTION_TRACE.value,
            input=trace_info.inputs,
            output=str(trace_info.suggested_question),
            trace_id=trace_info.message_id,
            start_time=trace_info.start_time,
            end_time=trace_info.end_time,
            metadata=trace_info.metadata,
-            level=LevelEnum.DEFAULT if message_data.status != 'error' else LevelEnum.ERROR,
+            level=(LevelEnum.DEFAULT if message_data.status != "error" else LevelEnum.ERROR),
            status_message=message_data.error if message_data.error else "",
            usage=generation_usage,
        )
@ -327,7 +326,7 @@ class LangFuseDataTrace(BaseTraceInstance):

    def dataset_retrieval_trace(self, trace_info: DatasetRetrievalTraceInfo):
        dataset_retrieval_span_data = LangfuseSpan(
-            name="dataset_retrieval",
+            name=TraceTaskName.DATASET_RETRIEVAL_TRACE.value,
            input=trace_info.inputs,
            output={"documents": trace_info.documents},
            trace_id=trace_info.message_id,
@ -347,7 +346,7 @@ class LangFuseDataTrace(BaseTraceInstance):
            start_time=trace_info.start_time,
            end_time=trace_info.end_time,
            metadata=trace_info.metadata,
-            level=LevelEnum.DEFAULT if trace_info.error == "" or trace_info.error is None else LevelEnum.ERROR,
+            level=(LevelEnum.DEFAULT if trace_info.error == "" or trace_info.error is None else LevelEnum.ERROR),
            status_message=trace_info.error,
        )

@ -355,7 +354,7 @@ class LangFuseDataTrace(BaseTraceInstance):

    def generate_name_trace(self, trace_info: GenerateNameTraceInfo):
        name_generation_trace_data = LangfuseTrace(
-            name="generate_name",
+            name=TraceTaskName.GENERATE_NAME_TRACE.value,
            input=trace_info.inputs,
            output=trace_info.outputs,
            user_id=trace_info.tenant_id,
@ -366,7 +365,7 @@ class LangFuseDataTrace(BaseTraceInstance):
        self.add_trace(langfuse_trace_data=name_generation_trace_data)

        name_generation_span_data = LangfuseSpan(
-            name="generate_name",
+            name=TraceTaskName.GENERATE_NAME_TRACE.value,
            input=trace_info.inputs,
            output=trace_info.outputs,
            trace_id=trace_info.conversation_id,
@ -377,9 +376,7 @@ class LangFuseDataTrace(BaseTraceInstance):
        self.add_span(langfuse_span_data=name_generation_span_data)

    def add_trace(self, langfuse_trace_data: Optional[LangfuseTrace] = None):
-        format_trace_data = (
-            filter_none_values(langfuse_trace_data.model_dump()) if langfuse_trace_data else {}
-        )
+        format_trace_data = filter_none_values(langfuse_trace_data.model_dump()) if langfuse_trace_data else {}
        try:
            self.langfuse_client.trace(**format_trace_data)
            logger.debug("LangFuse Trace created successfully")
@ -387,9 +384,7 @@ class LangFuseDataTrace(BaseTraceInstance):
            raise ValueError(f"LangFuse Failed to create trace: {str(e)}")

    def add_span(self, langfuse_span_data: Optional[LangfuseSpan] = None):
-        format_span_data = (
-            filter_none_values(langfuse_span_data.model_dump()) if langfuse_span_data else {}
-        )
+        format_span_data = filter_none_values(langfuse_span_data.model_dump()) if langfuse_span_data else {}
        try:
            self.langfuse_client.span(**format_span_data)
            logger.debug("LangFuse Span created successfully")
@ -397,19 +392,13 @@ class LangFuseDataTrace(BaseTraceInstance):
            raise ValueError(f"LangFuse Failed to create span: {str(e)}")

    def update_span(self, span, langfuse_span_data: Optional[LangfuseSpan] = None):
-        format_span_data = (
-            filter_none_values(langfuse_span_data.model_dump()) if langfuse_span_data else {}
-        )
+        format_span_data = filter_none_values(langfuse_span_data.model_dump()) if langfuse_span_data else {}

        span.end(**format_span_data)

-    def add_generation(
-        self, langfuse_generation_data: Optional[LangfuseGeneration] = None
-    ):
+    def add_generation(self, langfuse_generation_data: Optional[LangfuseGeneration] = None):
        format_generation_data = (
-            filter_none_values(langfuse_generation_data.model_dump())
-            if langfuse_generation_data
-            else {}
+            filter_none_values(langfuse_generation_data.model_dump()) if langfuse_generation_data else {}
        )
        try:
            self.langfuse_client.generation(**format_generation_data)
@ -417,13 +406,9 @@ class LangFuseDataTrace(BaseTraceInstance):
        except Exception as e:
            raise ValueError(f"LangFuse Failed to create generation: {str(e)}")

-    def update_generation(
-        self, generation, langfuse_generation_data: Optional[LangfuseGeneration] = None
-    ):
+    def update_generation(self, generation, langfuse_generation_data: Optional[LangfuseGeneration] = None):
        format_generation_data = (
-            filter_none_values(langfuse_generation_data.model_dump())
-            if langfuse_generation_data
-            else {}
+            filter_none_values(langfuse_generation_data.model_dump()) if langfuse_generation_data else {}
        )

        generation.end(**format_generation_data)
--- a/api/core/ops/langsmith_trace/langsmith_trace.py
+++ b/api/core/ops/langsmith_trace/langsmith_trace.py
@ -15,6 +15,7 @@ from core.ops.entities.trace_entity import (
    ModerationTraceInfo,
    SuggestedQuestionTraceInfo,
    ToolTraceInfo,
+    TraceTaskName,
    WorkflowTraceInfo,
 )
 from core.ops.langsmith_trace.entities.langsmith_trace_entity import (
@ -39,9 +40,7 @@ class LangSmithDataTrace(BaseTraceInstance):
        self.langsmith_key = langsmith_config.api_key
        self.project_name = langsmith_config.project
        self.project_id = None
-        self.langsmith_client = Client(
-            api_key=langsmith_config.api_key, api_url=langsmith_config.endpoint
-        )
+        self.langsmith_client = Client(api_key=langsmith_config.api_key, api_url=langsmith_config.endpoint)
        self.file_base_url = os.getenv("FILES_URL", "http://127.0.0.1:5001")

    def trace(self, trace_info: BaseTraceInfo):
@ -64,7 +63,7 @@ class LangSmithDataTrace(BaseTraceInstance):
        if trace_info.message_id:
            message_run = LangSmithRunModel(
                id=trace_info.message_id,
-                name=f"message_{trace_info.message_id}",
+                name=TraceTaskName.MESSAGE_TRACE.value,
                inputs=trace_info.workflow_run_inputs,
                outputs=trace_info.workflow_run_outputs,
                run_type=LangSmithRunType.chain,
@ -73,8 +72,8 @@ class LangSmithDataTrace(BaseTraceInstance):
                extra={
                    "metadata": trace_info.metadata,
                },
-                tags=["message"],
-                error=trace_info.error
+                tags=["message", "workflow"],
+                error=trace_info.error,
            )
            self.add_run(message_run)

@ -82,7 +81,7 @@ class LangSmithDataTrace(BaseTraceInstance):
            file_list=trace_info.file_list,
            total_tokens=trace_info.total_tokens,
            id=trace_info.workflow_app_log_id if trace_info.workflow_app_log_id else trace_info.workflow_run_id,
-            name=f"workflow_{trace_info.workflow_app_log_id}" if trace_info.workflow_app_log_id else f"workflow_{trace_info.workflow_run_id}",
+            name=TraceTaskName.WORKFLOW_TRACE.value,
            inputs=trace_info.workflow_run_inputs,
            run_type=LangSmithRunType.tool,
            start_time=trace_info.workflow_data.created_at,
@ -126,22 +125,18 @@ class LangSmithDataTrace(BaseTraceInstance):
            node_type = node_execution.node_type
            status = node_execution.status
            if node_type == "llm":
-                inputs = json.loads(node_execution.process_data).get(
-                    "prompts", {}
-                    ) if node_execution.process_data else {}
+                inputs = (
+                    json.loads(node_execution.process_data).get("prompts", {}) if node_execution.process_data else {}
+                )
            else:
                inputs = json.loads(node_execution.inputs) if node_execution.inputs else {}
-            outputs = (
-                json.loads(node_execution.outputs) if node_execution.outputs else {}
-            )
+            outputs = json.loads(node_execution.outputs) if node_execution.outputs else {}
            created_at = node_execution.created_at if node_execution.created_at else datetime.now()
            elapsed_time = node_execution.elapsed_time
            finished_at = created_at + timedelta(seconds=elapsed_time)

            execution_metadata = (
-                json.loads(node_execution.execution_metadata)
-                if node_execution.execution_metadata
-                else {}
+                json.loads(node_execution.execution_metadata) if node_execution.execution_metadata else {}
            )
            node_total_tokens = execution_metadata.get("total_tokens", 0)

@ -168,7 +163,7 @@ class LangSmithDataTrace(BaseTraceInstance):

            langsmith_run = LangSmithRunModel(
                total_tokens=node_total_tokens,
-                name=f"{node_name}_{node_execution_id}",
+                name=node_type,
                inputs=inputs,
                run_type=run_type,
                start_time=created_at,
@ -178,7 +173,9 @@ class LangSmithDataTrace(BaseTraceInstance):
                extra={
                    "metadata": metadata,
                },
-                parent_run_id=trace_info.workflow_app_log_id if trace_info.workflow_app_log_id else trace_info.workflow_run_id,
+                parent_run_id=trace_info.workflow_app_log_id
+                if trace_info.workflow_app_log_id
+                else trace_info.workflow_run_id,
                tags=["node_execution"],
            )

@ -198,9 +195,9 @@ class LangSmithDataTrace(BaseTraceInstance):
        metadata["user_id"] = user_id

        if message_data.from_end_user_id:
-            end_user_data: EndUser = db.session.query(EndUser).filter(
-                EndUser.id == message_data.from_end_user_id
-            ).first()
+            end_user_data: EndUser = (
+                db.session.query(EndUser).filter(EndUser.id == message_data.from_end_user_id).first()
+            )
            if end_user_data is not None:
                end_user_id = end_user_data.session_id
                metadata["end_user_id"] = end_user_id
@ -210,7 +207,7 @@ class LangSmithDataTrace(BaseTraceInstance):
            output_tokens=trace_info.answer_tokens,
            total_tokens=trace_info.total_tokens,
            id=message_id,
-            name=f"message_{message_id}",
+            name=TraceTaskName.MESSAGE_TRACE.value,
            inputs=trace_info.inputs,
            run_type=LangSmithRunType.chain,
            start_time=trace_info.start_time,
@ -230,7 +227,7 @@ class LangSmithDataTrace(BaseTraceInstance):
            input_tokens=trace_info.message_tokens,
            output_tokens=trace_info.answer_tokens,
            total_tokens=trace_info.total_tokens,
-            name=f"llm_{message_id}",
+            name="llm",
            inputs=trace_info.inputs,
            run_type=LangSmithRunType.llm,
            start_time=trace_info.start_time,
@ -248,7 +245,7 @@ class LangSmithDataTrace(BaseTraceInstance):

    def moderation_trace(self, trace_info: ModerationTraceInfo):
        langsmith_run = LangSmithRunModel(
-            name="moderation",
+            name=TraceTaskName.MODERATION_TRACE.value,
            inputs=trace_info.inputs,
            outputs={
                "action": trace_info.action,
@ -271,7 +268,7 @@ class LangSmithDataTrace(BaseTraceInstance):
    def suggested_question_trace(self, trace_info: SuggestedQuestionTraceInfo):
        message_data = trace_info.message_data
        suggested_question_run = LangSmithRunModel(
-            name="suggested_question",
+            name=TraceTaskName.SUGGESTED_QUESTION_TRACE.value,
            inputs=trace_info.inputs,
            outputs=trace_info.suggested_question,
            run_type=LangSmithRunType.tool,
@ -288,7 +285,7 @@ class LangSmithDataTrace(BaseTraceInstance):

    def dataset_retrieval_trace(self, trace_info: DatasetRetrievalTraceInfo):
        dataset_retrieval_run = LangSmithRunModel(
-            name="dataset_retrieval",
+            name=TraceTaskName.DATASET_RETRIEVAL_TRACE.value,
            inputs=trace_info.inputs,
            outputs={"documents": trace_info.documents},
            run_type=LangSmithRunType.retriever,
@ -323,7 +320,7 @@ class LangSmithDataTrace(BaseTraceInstance):

    def generate_name_trace(self, trace_info: GenerateNameTraceInfo):
        name_run = LangSmithRunModel(
-            name="generate_name",
+            name=TraceTaskName.GENERATE_NAME_TRACE.value,
            inputs=trace_info.inputs,
            outputs=trace_info.outputs,
            run_type=LangSmithRunType.tool,
--- a/api/core/ops/ops_trace_manager.py
+++ b/api/core/ops/ops_trace_manager.py
@ -5,7 +5,6 @@ import queue
 import threading
 import time
 from datetime import timedelta
-from enum import Enum
 from typing import Any, Optional, Union
 from uuid import UUID

@ -24,6 +23,7 @@ from core.ops.entities.trace_entity import (
    ModerationTraceInfo,
    SuggestedQuestionTraceInfo,
    ToolTraceInfo,
+    TraceTaskName,
    WorkflowTraceInfo,
 )
 from core.ops.langfuse_trace.langfuse_trace import LangFuseDataTrace
@ -253,17 +253,6 @@ class OpsTraceManager:
        return trace_instance(tracing_config).api_check()


-class TraceTaskName(str, Enum):
-    CONVERSATION_TRACE = 'conversation_trace'
-    WORKFLOW_TRACE = 'workflow_trace'
-    MESSAGE_TRACE = 'message_trace'
-    MODERATION_TRACE = 'moderation_trace'
-    SUGGESTED_QUESTION_TRACE = 'suggested_question_trace'
-    DATASET_RETRIEVAL_TRACE = 'dataset_retrieval_trace'
-    TOOL_TRACE = 'tool_trace'
-    GENERATE_NAME_TRACE = 'generate_name_trace'
-
-
 class TraceTask:
    def __init__(
        self,
--- a/api/core/provider_manager.py
+++ b/api/core/provider_manager.py
@ -663,7 +663,7 @@ class ProviderManager:
        # Convert provider_records to dict
        quota_type_to_provider_records_dict = {}
        for provider_record in provider_records:
-            if provider_record.provider_type != ProviderType.SYSTEM.value:
+            if provider_record.provider_type != ProviderType.SYSTEM.value and provider_record.quota_type != ProviderQuotaType.PAID.value:
                continue

            quota_type_to_provider_records_dict[ProviderQuotaType.value_of(provider_record.quota_type)] \
--- a/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector.py
+++ b/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector.py
@ -65,8 +65,15 @@ class AnalyticdbVector(BaseVector):
        AnalyticdbVector._init = True

    def _initialize(self) -> None:
-        self._initialize_vector_database()
-        self._create_namespace_if_not_exists()
+        cache_key = f"vector_indexing_{self.config.instance_id}"
+        lock_name = f"{cache_key}_lock"
+        with redis_client.lock(lock_name, timeout=20):
+            collection_exist_cache_key = f"vector_indexing_{self.config.instance_id}"
+            if redis_client.get(collection_exist_cache_key):
+                return
+            self._initialize_vector_database()
+            self._create_namespace_if_not_exists()
+            redis_client.set(collection_exist_cache_key, 1, ex=3600)

    def _initialize_vector_database(self) -> None:
        from alibabacloud_gpdb20160503 import models as gpdb_20160503_models
@ -285,9 +292,11 @@ class AnalyticdbVector(BaseVector):
        documents = []
        for match in response.body.matches.match:
            if match.score > score_threshold:
+                metadata = json.loads(match.metadata.get("metadata_"))
                doc = Document(
                    page_content=match.metadata.get("page_content"),
-                    metadata=json.loads(match.metadata.get("metadata_")),
+                    vector=match.metadata.get("vector"),
+                    metadata=metadata,
                )
                documents.append(doc)
        return documents
@ -320,7 +329,23 @@ class AnalyticdbVectorFactory(AbstractVectorFactory):
                self.gen_index_struct_dict(VectorType.ANALYTICDB, collection_name)
            )

-        # TODO handle optional params
+        # handle optional params
+        if dify_config.ANALYTICDB_KEY_ID is None:
+            raise ValueError("ANALYTICDB_KEY_ID should not be None")
+        if dify_config.ANALYTICDB_KEY_SECRET is None:
+            raise ValueError("ANALYTICDB_KEY_SECRET should not be None")
+        if dify_config.ANALYTICDB_REGION_ID is None:
+            raise ValueError("ANALYTICDB_REGION_ID should not be None")
+        if dify_config.ANALYTICDB_INSTANCE_ID is None:
+            raise ValueError("ANALYTICDB_INSTANCE_ID should not be None")
+        if dify_config.ANALYTICDB_ACCOUNT is None:
+            raise ValueError("ANALYTICDB_ACCOUNT should not be None")
+        if dify_config.ANALYTICDB_PASSWORD is None:
+            raise ValueError("ANALYTICDB_PASSWORD should not be None")
+        if dify_config.ANALYTICDB_NAMESPACE is None:
+            raise ValueError("ANALYTICDB_NAMESPACE should not be None")
+        if dify_config.ANALYTICDB_NAMESPACE_PASSWORD is None:
+            raise ValueError("ANALYTICDB_NAMESPACE_PASSWORD should not be None")
        return AnalyticdbVector(
            collection_name,
            AnalyticdbConfig(
--- a/api/core/rag/datasource/vdb/myscale/myscale_vector.py
+++ b/api/core/rag/datasource/vdb/myscale/myscale_vector.py
@ -126,13 +126,14 @@ class MyScaleVector(BaseVector):
        where_str = f"WHERE dist < {1 - score_threshold}" if \
            self._metric.upper() == "COSINE" and order == SortOrder.ASC and score_threshold > 0.0 else ""
        sql = f"""
-            SELECT text, metadata, {dist} as dist FROM {self._config.database}.{self._collection_name}
+            SELECT text, vector, metadata, {dist} as dist FROM {self._config.database}.{self._collection_name}
            {where_str} ORDER BY dist {order.value} LIMIT {top_k}
        """
        try:
            return [
                Document(
                    page_content=r["text"],
+                    vector=r['vector'],
                    metadata=r["metadata"],
                )
                for r in self._client.query(sql).named_results()
--- a/api/core/rag/datasource/vdb/opensearch/opensearch_vector.py
+++ b/api/core/rag/datasource/vdb/opensearch/opensearch_vector.py
@ -192,7 +192,9 @@ class OpenSearchVector(BaseVector):
        docs = []
        for hit in response['hits']['hits']:
            metadata = hit['_source'].get(Field.METADATA_KEY.value)
-            doc = Document(page_content=hit['_source'].get(Field.CONTENT_KEY.value), metadata=metadata)
+            vector = hit['_source'].get(Field.VECTOR.value)
+            page_content = hit['_source'].get(Field.CONTENT_KEY.value)
+            doc = Document(page_content=page_content, vector=vector, metadata=metadata)
            docs.append(doc)

        return docs
--- a/api/core/rag/datasource/vdb/oracle/oraclevector.py
+++ b/api/core/rag/datasource/vdb/oracle/oraclevector.py
@ -234,16 +234,16 @@ class OracleVector(BaseVector):
                        entities.append(token)
            with self._get_cursor() as cur:
                cur.execute(
-                    f"select meta, text FROM {self.table_name} WHERE CONTAINS(text, :1, 1) > 0 order by score(1) desc fetch first {top_k} rows only",
+                    f"select meta, text, embedding FROM {self.table_name} WHERE CONTAINS(text, :1, 1) > 0 order by score(1) desc fetch first {top_k} rows only",
                    [" ACCUM ".join(entities)]
                )
                docs = []
                for record in cur:
-                    metadata, text = record
-                    docs.append(Document(page_content=text, metadata=metadata))
+                    metadata, text, embedding = record
+                    docs.append(Document(page_content=text, vector=embedding, metadata=metadata))
            return docs
        else:
-            return [Document(page_content="", metadata="")]
+            return [Document(page_content="", metadata={})]
        return []

    def delete(self) -> None:
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
jyong	3bfb26d571	fix model runtime quota	2024-08-12 17:09:09 +08:00
jyong	ccf4bd8555	fix model runtime quota	2024-08-12 15:57:53 +08:00
mago960806	a68df696ec	Fix issue with incorrect port number in app_base_url due to NAT networks (#6653 )	2024-08-12 12:26:12 +08:00
Chenhe Gu	4b93df5a30	Docs/remove all meeting schedule links (#7177 )	2024-08-12 11:28:26 +08:00
Joel	12dd3c0277	fix: leave chat page show assign to readonly property prolem (#7178 )	2024-08-12 11:25:10 +08:00
Bowen Liang	ccb6ddd840	chore: bump Ruff to 0.5.7 (#7174 )	2024-08-12 10:24:48 +08:00
Nam Vu	c48584fbb1	chore: update localization link in README (#7168 )	2024-08-12 10:19:13 +08:00
ybalbert001	f2cb1fb09f	Fix : Workflow "start" paste url not support s3 pre-signed URL (#6855 ) Co-authored-by: Yuanbo Li <ybalbert@amazon.com>	2024-08-11 16:45:15 +08:00
灰灰	ac60182c91	fix: solving http-request-tool bugs in workflow (#6685 )	2024-08-11 16:32:06 +08:00
k-brahma	700d37be8d	Add explanatory comment to NGINX_ENABLE_CERTBOT_CHALLENGE key in .env.example (#7154 )	2024-08-10 16:58:50 +08:00
crazywoola	8b5761efb2	change secret input to text input in searxng (#7160 )	2024-08-10 16:58:22 +08:00
Nam Vu	ef4d85f5c0	feat: README_VI (#7158 )	2024-08-10 11:48:03 +08:00
Yanyi Liu	5b32f2e0dd	Feat: Add model provider Text Embedding Inference for embedding and rerank (#7132 )	2024-08-09 19:12:13 +08:00
Yanyi Liu	4cbeb6815b	Fix: Wrong cutoff length lead to empty input in openai compatible embedding model. (#7133 )	2024-08-09 19:11:57 +08:00
Kevin9703	2c188a45c8	feat(app/log): Add Referenced Content in Application Logs (#7082 )	2024-08-09 19:06:08 +08:00
Jeff Li	d338f69837	feat: add decode option to json process tools (#7138 )	2024-08-09 19:05:27 +08:00
Nam Vu	7ebad74372	chore: #6515 i18n (#7149 )	2024-08-09 19:05:00 +08:00
Nam Vu	e2a13a9945	chore: #5487 i18n (#7150 )	2024-08-09 19:04:50 +08:00
Jyong	c6b0dc6a29	update dataset embedding model, update document status to be indexing (#7145 )	2024-08-09 16:47:15 +08:00
crazywoola	f667ef98cb	Feat/update tools length (#7141 )	2024-08-09 16:07:37 +08:00
Joe	425174e82f	feat: update ops trace (#7102 )	2024-08-09 15:22:16 +08:00
Joe	7201b56a6d	fix: workflow log run time error (#7130 )	2024-08-09 14:46:31 +08:00
Yi Xiao	34cab0e0b7	Fix: account delete function & confirm issues (#7129 )	2024-08-09 11:37:34 +08:00
Matri	4dfa8eedb8	Feat/tool-D-ID (#6278 )	2024-08-09 11:05:33 +08:00
Nam Vu	633808de06	chore: improve Vietnamese (vi-VN) translations (#7127 )	2024-08-09 10:07:12 +08:00
k-brahma	f4591f97aa	Update i18n/ja-JP/dataset-documents.ts "embeddedSpend" value. (#7124 )	2024-08-09 08:33:18 +08:00
forrestlinfeng	07511dfaf4	update stepfun model (#7118 ) Co-authored-by: chenlinfeng <chenlinfeng@step.ai> Co-authored-by: Tfsh <tianfs_fight@163.com>	2024-08-08 20:40:37 +08:00
小羽	7944ce0594	feat: wenxin add yi-34b-chat (#7117 )	2024-08-08 20:01:21 +08:00
Aero Kang	ad682c394d	fix annotation reply is null (#7103 )	2024-08-08 19:07:50 +08:00
Nam Vu	7210613551	feat: Postgres max connections (#7067 )	2024-08-08 17:25:23 +08:00
orangeclk	83acb53c08	feat: add zhipu embedding-3 (#7100 )	2024-08-08 17:08:46 +08:00
shAlfred	a7162240e6	feat: add text-embedding functon and LLM models to Siliconflow (#7090 )	2024-08-08 17:08:28 +08:00
Jyong	12095f8cd6	extract docx filter comment element (#7092 )	2024-08-08 16:53:29 +08:00
zxhlyh	925f0d2e09	fix: workflow search blocks (#7097 )	2024-08-08 15:33:02 +08:00
Hash Brown	b6d206e095	feat: app icon enhancements (#7095 )	2024-08-08 15:29:11 +08:00
majian	5542ee4d0d	workflow logs support workflow run id filter (#6833 )	2024-08-08 14:54:02 +08:00
zhuhao	4ffa706e4f	feat: add a builtin tool to support regex extraction. (#7081 ) (#7087 )	2024-08-08 14:23:57 +08:00
Jyong	169cde6c3c	add nltk punkt resource (#7063 )	2024-08-08 14:23:22 +08:00
小羽	34a9dbe826	Feat/add 360-zhinao provider (#7069 )	2024-08-08 14:23:08 +08:00
Nam Vu	8e23e24bd5	feat: Poetry requests timeout (#7086 )	2024-08-08 14:17:29 +08:00
orangeclk	f288d367ac	Add price info for zhipu models (#7084 )	2024-08-08 14:17:05 +08:00
Waffle	5e2fa13126	feat: support glm-4-long (#7070 ) Co-authored-by: crazywoola <100913391+crazywoola@users.noreply.github.com>	2024-08-08 10:54:39 +08:00
zxhlyh	1571a8afd4	fix: workflow delete node shortcut (#7076 )	2024-08-08 10:42:08 +08:00
-LAN-	67a2f14cef	fix(api/core/workflow/nodes/tool/tool_node.py): Keep None value in tool params. (#7066 )	2024-08-07 19:36:21 +08:00
Chenhe Gu	a0d5b61c2a	update enterprise inquiry link to point to chatflow (#7064 )	2024-08-07 19:27:54 +08:00
Joe	d7bb422a5c	fix: hunyuan assistant_prompt_message pydantic error (#7062 )	2024-08-07 18:31:40 +08:00
8bitpd	40c6f3c724	fix: add redis lock to AnalyticdbVector init (#6859 ) Co-authored-by: xiaozeyu <xiaozeyu.xzy@alibaba-inc.com>	2024-08-07 17:32:06 +08:00
-LAN-	df8f8c9a2c	feat(api/core/rag/datasource/vdb/analyticdb/analyticdb_vector.py): Checking config before init analyticdb (#7050 )	2024-08-07 17:31:36 +08:00
-LAN-	536c43257b	refactor(*): Update hard-code '[__HIDDEN__]' to the constant. (#7048 )	2024-08-07 17:30:56 +08:00
-LAN-	4e8f6b3603	chore(api/core/app/segments/segments.py): Remove todo tags. (#7052 )	2024-08-07 17:29:35 +08:00
Jyong	80c94f02e9	add vector field for other vectordb (#7051 )	2024-08-07 17:14:03 +08:00
-LAN-	aad02113c6	fix(api/core/app/segments): Allow to contains boolean value in object segment (#7047 )	2024-08-07 16:20:22 +08:00
chenxu9741	72c75b75cf	feat: Add hyperlink parsing to the DOCX document. (#7017 )	2024-08-07 16:01:14 +08:00
Sadegh Ghanbari Shohani	ffa992acf7	Add support for i18n Farsi language (fa-IR) (#7044 )	2024-08-07 15:44:42 +08:00
majian	99b78dd198	feat: add gpt-4o-2024-08-06 (#7046 )	2024-08-07 15:35:57 +08:00
Sangmin Ahn	7f81a86e9e	chore: show non-English characters in exported DSL files (#7042 )	2024-08-07 14:03:15 +08:00
DDDDD12138	4c4f6e362f	chore: lint code to remove unused imports and variables (#7033 )	2024-08-07 13:04:44 +08:00
NFish	1a302ca957	feat: add disabled support to tooltip-plus component (#7036 )	2024-08-07 11:26:47 +08:00
crazywoola	11f9d2f124	doc: correct typos in mdx files (#7029 )	2024-08-07 09:03:45 +08:00
Achim	a93bc83c8d	Provide output data also in json property of workflow tool (#6924 ) (#7027 )	2024-08-07 08:54:51 +08:00
crazywoola	3516989738	fix: typos in wenxin llm (#7021 )	2024-08-06 22:33:03 +08:00
Sa Zhang	26991443ed	fix: Fix incorrect context size for jina-reranker-v2 model (#7006 )	2024-08-06 21:08:29 +08:00
Bryan	eece50acec	fix: tran list issue (#7009 ) Co-authored-by: libing <libing@healink.cn>	2024-08-06 21:01:38 +08:00
Jyong	28d4e5b045	Fix/reranking mode is null (#7012 )	2024-08-06 19:12:04 +08:00
Joel	c110888aee	feat: agent app support generate prompt (#7007 )	2024-08-06 17:43:54 +08:00