docs: add file upload support documentation for flows

- Add 'File Inputs' section to flows.mdx documenting: - Using crewai-files types (ImageFile, PDFFile, etc.) in flow state - CrewAI Platform (AMP) automatic file upload dropzone rendering - API usage with URL string coercion via Pydantic - Update files.mdx with: - Example of file types in flow state - Note about CrewAI Platform integration for flows Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
fix: preserve method return value as flow output for @human_feedback with emit
2026-04-24 20:02:38 +00:00 · 2026-03-27 00:45:31 -07:00 · 2026-03-25 22:51:44 -07:00
27 changed files with 138 additions and 3041 deletions
--- a/.github/workflows/docs-broken-links.yml
+++ b/.github/workflows/docs-broken-links.yml
@@ -23,7 +23,7 @@ jobs:
      - name: Set up Node
        uses: actions/setup-node@v4
        with:
-          node-version: "22"
+          node-version: "latest"

      - name: Install Mintlify CLI
        run: npm i -g mintlify
--- a/docs/ar/changelog.mdx
+++ b/docs/ar/changelog.mdx
@@ -4,86 +4,6 @@ description: "تحديثات المنتج والتحسينات وإصلاحات
 icon: "clock"
 mode: "wide"
 ---
-<Update label="27 مارس 2026">
-  ## v1.13.0rc1
-
-  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0rc1)
-
-  ## ما الذي تغير
-
-  ### الوثائق
-  - تحديث سجل التغييرات والإصدار لـ v1.13.0a2
-
-  ## المساهمون
-
-  @greysonlalonde
-
-</Update>
-
-<Update label="27 مارس 2026">
-  ## v1.13.0a2
-
-  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0a2)
-
-  ## ما الذي تغير
-
-  ### الميزات
-  - تحديث تلقائي لمستودع اختبار النشر أثناء الإصدار
-  - تحسين مرونة إصدار المؤسسات وتجربة المستخدم
-
-  ### الوثائق
-  - تحديث سجل التغييرات والإصدار للإصدار v1.13.0a1
-
-  ## المساهمون
-
-  @greysonlalonde
-
-</Update>
-
-<Update label="27 مارس 2026">
-  ## v1.13.0a1
-
-  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0a1)
-
-  ## ما الذي تغير
-
-  ### إصلاحات الأخطاء
-  - إصلاح الروابط المعطلة في سير العمل الوثائقي عن طريق تثبيت Node على LTS 22
-  - مسح ذاكرة التخزين المؤقت لـ uv للحزم المنشورة حديثًا في الإصدار المؤسسي
-
-  ### الوثائق
-  - إضافة مصفوفة شاملة لأذونات RBAC ودليل النشر
-  - تحديث سجل التغييرات والإصدار للإصدار v1.12.2
-
-  ## المساهمون
-
-  @greysonlalonde, @iris-clawd, @joaomdmoura
-
-</Update>
-
-<Update label="25 مارس 2026">
-  ## v1.12.2
-
-  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.12.2)
-
-  ## ما الذي تغير
-
-  ### الميزات
-  - إضافة مرحلة إصدار المؤسسات إلى إصدار أدوات المطورين
-
-  ### إصلاحات الأخطاء
-  - الحفاظ على قيمة إرجاع الطريقة كإخراج تدفق لـ @human_feedback مع emit
-
-  ### الوثائق
-  - تحديث سجل التغييرات والإصدار لـ v1.12.1
-  - مراجعة سياسة الأمان وتعليمات الإبلاغ
-
-  ## المساهمون
-
-  @alex-clawd, @greysonlalonde, @joaomdmoura, @theCyberTech
-
-</Update>
-
 <Update label="25 مارس 2026">
  ## v1.12.1

--- a/docs/docs.json
+++ b/docs/docs.json
--- a/docs/en/changelog.mdx
+++ b/docs/en/changelog.mdx
@@ -4,86 +4,6 @@ description: "Product updates, improvements, and bug fixes for CrewAI"
 icon: "clock"
 mode: "wide"
 ---
-<Update label="Mar 27, 2026">
-  ## v1.13.0rc1
-
-  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0rc1)
-
-  ## What's Changed
-
-  ### Documentation
-  - Update changelog and version for v1.13.0a2
-
-  ## Contributors
-
-  @greysonlalonde
-
-</Update>
-
-<Update label="Mar 27, 2026">
-  ## v1.13.0a2
-
-  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0a2)
-
-  ## What's Changed
-
-  ### Features
-  - Auto-update deployment test repo during release
-  - Improve enterprise release resilience and UX
-
-  ### Documentation
-  - Update changelog and version for v1.13.0a1
-
-  ## Contributors
-
-  @greysonlalonde
-
-</Update>
-
-<Update label="Mar 27, 2026">
-  ## v1.13.0a1
-
-  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0a1)
-
-  ## What's Changed
-
-  ### Bug Fixes
-  - Fix broken links in documentation workflow by pinning Node to LTS 22
-  - Bust the uv cache for freshly published packages in enterprise release
-
-  ### Documentation
-  - Add comprehensive RBAC permissions matrix and deployment guide
-  - Update changelog and version for v1.12.2
-
-  ## Contributors
-
-  @greysonlalonde, @iris-clawd, @joaomdmoura
-
-</Update>
-
-<Update label="Mar 25, 2026">
-  ## v1.12.2
-
-  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.12.2)
-
-  ## What's Changed
-
-  ### Features
-  - Add enterprise release phase to devtools release
-
-  ### Bug Fixes
-  - Preserve method return value as flow output for @human_feedback with emit
-
-  ### Documentation
-  - Update changelog and version for v1.12.1
-  - Revise security policy and reporting instructions
-
-  ## Contributors
-
-  @alex-clawd, @greysonlalonde, @joaomdmoura, @theCyberTech
-
-</Update>
-
 <Update label="Mar 25, 2026">
  ## v1.12.1

--- a/docs/en/concepts/files.mdx
+++ b/docs/en/concepts/files.mdx
@@ -134,6 +134,29 @@ result = flow.kickoff(
 )
 ```

+You can also define file types directly in your flow state for structured file handling:
+
+```python
+from pydantic import BaseModel
+from crewai.flow.flow import Flow, start
+from crewai_files import ImageFile, PDFFile
+
+class DocumentState(BaseModel):
+    document: PDFFile
+    cover_image: ImageFile
+    title: str = ""
+
+class DocumentFlow(Flow[DocumentState]):
+    @start()
+    def process(self):
+        content = self.state.document.read()
+        return {"processed": True}
+```
+
+<Note type="info" title="CrewAI Platform Integration">
+When deploying flows to the CrewAI Platform (AMP), file fields in your state automatically render as file upload dropzones in the UI. For API usage, you can pass URL strings directly and Pydantic coerces them to file objects automatically. See [Flows - File Inputs](/en/concepts/flows#file-inputs) for details.
+</Note>
+
 ### With Standalone Agents

 Pass files directly to agent kickoff:
--- a/docs/en/concepts/flows.mdx
+++ b/docs/en/concepts/flows.mdx
@@ -341,6 +341,69 @@ flow.kickoff()

 By providing both unstructured and structured state management options, CrewAI Flows empowers developers to build AI workflows that are both flexible and robust, catering to a wide range of application requirements.

+## File Inputs
+
+Flows support file inputs through the `crewai-files` package, enabling you to build workflows that process images, PDFs, and other file types. When you use file types like `ImageFile` or `PDFFile` in your flow state, they integrate seamlessly with both local development and the CrewAI Platform.
+
+<Note type="info" title="Optional Dependency">
+File support requires the optional `crewai-files` package. Install it with:
+
+```bash
+uv add 'crewai[file-processing]'
+```
+</Note>
+
+### Using File Types in Flow State
+
+You can include file types directly in your structured flow state:
+
+```python
+from pydantic import BaseModel
+from crewai.flow.flow import Flow, start
+from crewai_files import ImageFile, PDFFile
+
+class DocumentProcessingState(BaseModel):
+    document: PDFFile        # Renders as file upload in CrewAI Platform
+    cover_image: ImageFile   # Renders as image upload
+    title: str = ""          # Renders as text input
+
+class DocumentFlow(Flow[DocumentProcessingState]):
+    @start()
+    def process_document(self):
+        # Access the file - works with URLs, paths, or uploaded files
+        content = self.state.document.read()
+        # Or pass to an agent with VisionTool, etc.
+        return {"processed": True}
+```
+
+### CrewAI Platform Integration
+
+When you deploy a flow to the CrewAI Platform (AMP), file fields in your state automatically render as file upload dropzones in the UI. This makes it easy to build user-facing applications that accept file uploads without any additional frontend work.
+
+| State Field Type | Platform UI Rendering |
+|:-----------------|:----------------------|
+| `ImageFile` | Image upload dropzone |
+| `PDFFile` | PDF upload dropzone |
+| `AudioFile` | Audio upload dropzone |
+| `VideoFile` | Video upload dropzone |
+| `TextFile` | Text file upload dropzone |
+| `str`, `int`, etc. | Standard form inputs |
+
+### API Usage
+
+When calling your flow via API, you can pass URL strings directly for file fields. Pydantic automatically coerces URLs into the appropriate file type:
+
+```python
+# API request body - URLs are automatically converted to file objects
+{
+    "document": "https://example.com/report.pdf",
+    "cover_image": "https://example.com/cover.png",
+    "title": "Q4 Report"
+}
+```
+
+For more details on file types, sources, and provider support, see the [Files documentation](/en/concepts/files).
+
 ## Flow Persistence

 The @persist decorator enables automatic state persistence in CrewAI Flows, allowing you to maintain flow state across restarts or different workflow executions. This decorator can be applied at either the class level or method level, providing flexibility in how you manage state persistence.
--- a/docs/en/enterprise/features/rbac.mdx
+++ b/docs/en/enterprise/features/rbac.mdx
@@ -7,13 +7,11 @@ mode: "wide"

 ## Overview

-RBAC in CrewAI AMP enables secure, scalable access management through two layers:
-
-1. **Feature permissions** — control what each role can do across the platform (manage, read, or no access)
-2. **Entity-level permissions** — fine-grained access on individual automations, environment variables, LLM connections, and Git repositories
+RBAC in CrewAI AMP enables secure, scalable access management through a combination of organization‑level roles and automation‑level visibility controls.

 <Frame>
  <img src="/images/enterprise/users_and_roles.png" alt="RBAC overview in CrewAI AMP" />
+
 </Frame>

 ## Users and Roles
@@ -41,13 +39,6 @@ You can configure users and roles in Settings → Roles.
  </Step>
 </Steps>

-### Predefined Roles
-
-| Role       | Description                                                                 |
-| :--------- | :-------------------------------------------------------------------------- |
-| **Owner**  | Full access to all features and settings. Cannot be restricted.             |
-| **Member** | Read access to most features, manage access to Studio projects. Cannot modify organization or default settings. |
-
 ### Configuration summary

 | Area                  | Where to configure                 | Options                                 |
@@ -55,80 +46,23 @@ You can configure users and roles in Settings → Roles.
 | Users & Roles         | Settings → Roles                   | Predefined: Owner, Member; Custom roles |
 | Automation visibility | Automation → Settings → Visibility | Private; Whitelist users/roles          |

---
+## Automation‑level Access Control

-## Feature Permissions Matrix
+In addition to organization‑wide roles, CrewAI Automations support fine‑grained visibility settings that let you restrict access to specific automations by user or role.

-Every role has a permission level for each feature area. The three levels are:
-
- **Manage** — full read/write access (create, edit, delete)
- **Read** — view-only access
- **No access** — feature is hidden/inaccessible
-
-| Feature                   | Owner   | Member (default) | Description                                                     |
-| :------------------------ | :------ | :--------------- | :-------------------------------------------------------------- |
-| `usage_dashboards`        | Manage  | Read             | View usage metrics and analytics                                |
-| `crews_dashboards`        | Manage  | Read             | View deployment dashboards, access automation details           |
-| `invitations`             | Manage  | Read             | Invite new members to the organization                          |
-| `training_ui`             | Manage  | Read             | Access training/fine-tuning interfaces                          |
-| `tools`                   | Manage  | Read             | Create and manage tools                                         |
-| `agents`                  | Manage  | Read             | Create and manage agents                                        |
-| `environment_variables`   | Manage  | Read             | Create and manage environment variables                         |
-| `llm_connections`         | Manage  | Read             | Configure LLM provider connections                              |
-| `default_settings`        | Manage  | No access        | Modify organization-wide default settings                       |
-| `organization_settings`   | Manage  | No access        | Manage billing, plans, and organization configuration           |
-| `studio_projects`         | Manage  | Manage           | Create and edit projects in Studio                              |
-
-<Tip>
-  When creating a custom role, you can set each feature independently to **Manage**, **Read**, or **No access** to match your team's needs.
-</Tip>
-
---
-
-## Deploying from GitHub or Zip
-
-One of the most common RBAC questions is: _"What permissions does a team member need to deploy?"_
-
-### Deploy from GitHub
-
-To deploy an automation from a GitHub repository, a user needs:
-
-1. **`crews_dashboards`**: at least `Read` — required to access the automations dashboard where deployments are created
-2. **Git repository access** (if entity-level RBAC for Git repositories is enabled): the user's role must be granted access to the specific Git repository via entity-level permissions
-3. **`studio_projects`: `Manage`** — if building the crew in Studio before deploying
-
-### Deploy from Zip
-
-To deploy an automation from a Zip file upload, a user needs:
-
-1. **`crews_dashboards`**: at least `Read` — required to access the automations dashboard
-2. **Zip deployments enabled**: the organization must not have disabled zip deployments in organization settings
-
-### Quick Reference: Minimum Permissions for Deployment
-
-| Action               | Required feature permissions          | Additional requirements                          |
-| :------------------- | :------------------------------------ | :----------------------------------------------- |
-| Deploy from GitHub   | `crews_dashboards: Read`              | Git repo entity access (if Git RBAC is enabled)  |
-| Deploy from Zip      | `crews_dashboards: Read`              | Zip deployments must be enabled at the org level |
-| Build in Studio      | `studio_projects: Manage`             | —                                                |
-| Configure LLM keys   | `llm_connections: Manage`             | —                                                |
-| Set environment vars  | `environment_variables: Manage`       | Entity-level access (if entity RBAC is enabled)  |
-
---
-
-## Automation‑level Access Control (Entity Permissions)
-
-In addition to organization‑wide roles, CrewAI supports fine‑grained entity-level permissions that restrict access to individual resources.
-
-### Automation Visibility
-
-Automations support visibility settings that restrict access by user or role. This is useful for:
+This is useful for:

 - Keeping sensitive or experimental automations private
 - Managing visibility across large teams or external collaborators
 - Testing automations in isolated contexts

-Deployments can be configured as private, meaning only whitelisted users and roles will be able to interact with them.
+Deployments can be configured as private, meaning only whitelisted users and roles will be able to:
+
+- View the deployment
+- Run it or interact with its API
+- Access its logs, metrics, and settings
+
+The organization owner always has access, regardless of visibility settings.

 You can configure automation‑level access control in Automation → Settings → Visibility tab.

@@ -165,92 +99,9 @@ You can configure automation‑level access control in Automation → Settings

 <Frame>
  <img src="/images/enterprise/visibility.png" alt="Automation Visibility settings in CrewAI AMP" />
+
 </Frame>

-### Deployment Permission Types
-
-When granting entity-level access to a specific automation, you can assign these permission types:
-
-| Permission           | What it allows                                      |
-| :------------------- | :-------------------------------------------------- |
-| `run`                | Execute the automation and use its API               |
-| `traces`             | View execution traces and logs                       |
-| `manage_settings`    | Edit, redeploy, rollback, or delete the automation   |
-| `human_in_the_loop`  | Respond to human-in-the-loop (HITL) requests         |
-| `full_access`        | All of the above                                     |
-
-### Entity-level RBAC for Other Resources
-
-When entity-level RBAC is enabled, access to these resources can also be controlled per user or role:
-
-| Resource               | Controlled by                    | Description                                           |
-| :--------------------- | :------------------------------- | :---------------------------------------------------- |
-| Environment variables  | Entity RBAC feature flag         | Restrict which roles/users can view or manage specific env vars |
-| LLM connections        | Entity RBAC feature flag         | Restrict access to specific LLM provider configurations |
-| Git repositories       | Git repositories RBAC org setting | Restrict which roles/users can access specific connected repos |
-
---
-
-## Common Role Patterns
-
-While CrewAI ships with Owner and Member roles, most teams benefit from creating custom roles. Here are common patterns:
-
-### Developer Role
-
-A role for team members who build and deploy automations but don't manage organization settings.
-
-| Feature                   | Permission |
-| :------------------------ | :--------- |
-| `usage_dashboards`        | Read       |
-| `crews_dashboards`        | Manage     |
-| `invitations`             | Read       |
-| `training_ui`             | Read       |
-| `tools`                   | Manage     |
-| `agents`                  | Manage     |
-| `environment_variables`   | Manage     |
-| `llm_connections`         | Read       |
-| `default_settings`        | No access  |
-| `organization_settings`   | No access  |
-| `studio_projects`         | Manage     |
-
-### Viewer / Stakeholder Role
-
-A role for non-technical stakeholders who need to monitor automations and view results.
-
-| Feature                   | Permission |
-| :------------------------ | :--------- |
-| `usage_dashboards`        | Read       |
-| `crews_dashboards`        | Read       |
-| `invitations`             | No access  |
-| `training_ui`             | Read       |
-| `tools`                   | Read       |
-| `agents`                  | Read       |
-| `environment_variables`   | No access  |
-| `llm_connections`         | No access  |
-| `default_settings`        | No access  |
-| `organization_settings`   | No access  |
-| `studio_projects`         | Read       |
-
-### Ops / Platform Admin Role
-
-A role for platform operators who manage infrastructure settings but may not build agents.
-
-| Feature                   | Permission |
-| :------------------------ | :--------- |
-| `usage_dashboards`        | Manage     |
-| `crews_dashboards`        | Manage     |
-| `invitations`             | Manage     |
-| `training_ui`             | Read       |
-| `tools`                   | Read       |
-| `agents`                  | Read       |
-| `environment_variables`   | Manage     |
-| `llm_connections`         | Manage     |
-| `default_settings`        | Manage     |
-| `organization_settings`   | Read       |
-| `studio_projects`         | Read       |
-
---
-
 <Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
  Contact our support team for assistance with RBAC questions.
 </Card>
--- a/docs/ko/changelog.mdx
+++ b/docs/ko/changelog.mdx
@@ -4,86 +4,6 @@ description: "CrewAI의 제품 업데이트, 개선 사항 및 버그 수정"
 icon: "clock"
 mode: "wide"
 ---
-<Update label="2026년 3월 27일">
-  ## v1.13.0rc1
-
-  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0rc1)
-
-  ## 변경 사항
-
-  ### 문서
-  - v1.13.0a2의 변경 로그 및 버전 업데이트
-
-  ## 기여자
-
-  @greysonlalonde
-
-</Update>
-
-<Update label="2026년 3월 27일">
-  ## v1.13.0a2
-
-  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0a2)
-
-  ## 변경 사항
-
-  ### 기능
-  - 릴리스 중 자동 업데이트 배포 테스트 리포지토리
-  - 기업 릴리스의 복원력 및 사용자 경험 개선
-
-  ### 문서
-  - v1.13.0a1에 대한 변경 로그 및 버전 업데이트
-
-  ## 기여자
-
-  @greysonlalonde
-
-</Update>
-
-<Update label="2026년 3월 27일">
-  ## v1.13.0a1
-
-  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0a1)
-
-  ## 변경 사항
-
-  ### 버그 수정
-  - Node를 LTS 22로 고정하여 문서 작업 흐름의 끊어진 링크 수정
-  - 기업 릴리스에서 새로 게시된 패키지의 uv 캐시 초기화
-
-  ### 문서
-  - 포괄적인 RBAC 권한 매트릭스 및 배포 가이드 추가
-  - v1.12.2에 대한 변경 로그 및 버전 업데이트
-
-  ## 기여자
-
-  @greysonlalonde, @iris-clawd, @joaomdmoura
-
-</Update>
-
-<Update label="2026년 3월 25일">
-  ## v1.12.2
-
-  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.12.2)
-
-  ## 변경 사항
-
-  ### 기능
-  - devtools 릴리스에 기업 릴리스 단계 추가
-
-  ### 버그 수정
-  - @human_feedback과 함께 emit을 사용할 때 메서드 반환 값을 흐름 출력으로 유지
-
-  ### 문서
-  - v1.12.1에 대한 변경 로그 및 버전 업데이트
-  - 보안 정책 및 보고 지침 수정
-
-  ## 기여자
-
-  @alex-clawd, @greysonlalonde, @joaomdmoura, @theCyberTech
-
-</Update>
-
 <Update label="2026년 3월 25일">
  ## v1.12.1

--- a/docs/pt-BR/changelog.mdx
+++ b/docs/pt-BR/changelog.mdx
@@ -4,86 +4,6 @@ description: "Atualizações de produto, melhorias e correções do CrewAI"
 icon: "clock"
 mode: "wide"
 ---
-<Update label="27 mar 2026">
-  ## v1.13.0rc1
-
-  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0rc1)
-
-  ## O que Mudou
-
-  ### Documentação
-  - Atualizar changelog e versão para v1.13.0a2
-
-  ## Contribuidores
-
-  @greysonlalonde
-
-</Update>
-
-<Update label="27 mar 2026">
-  ## v1.13.0a2
-
-  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0a2)
-
-  ## O que Mudou
-
-  ### Recursos
-  - Repositório de teste de implantação de autoatualização durante o lançamento
-  - Melhorar a resiliência e a experiência do usuário na versão empresarial
-
-  ### Documentação
-  - Atualizar changelog e versão para v1.13.0a1
-
-  ## Contribuidores
-
-  @greysonlalonde
-
-</Update>
-
-<Update label="27 mar 2026">
-  ## v1.13.0a1
-
-  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.13.0a1)
-
-  ## O que Mudou
-
-  ### Correções de Bugs
-  - Corrigir links quebrados no fluxo de documentação fixando o Node na LTS 22
-  - Limpar o cache uv para pacotes recém-publicados na versão empresarial
-
-  ### Documentação
-  - Adicionar uma matriz abrangente de permissões RBAC e guia de implantação
-  - Atualizar o changelog e a versão para v1.12.2
-
-  ## Contributors
-
-  @greysonlalonde, @iris-clawd, @joaomdmoura
-
-</Update>
-
-<Update label="25 mar 2026">
-  ## v1.12.2
-
-  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.12.2)
-
-  ## O que Mudou
-
-  ### Recursos
-  - Adicionar fase de lançamento empresarial ao lançamento do devtools
-
-  ### Correções de Bugs
-  - Preservar o valor de retorno do método como saída de fluxo para @human_feedback com emit
-
-  ### Documentação
-  - Atualizar changelog e versão para v1.12.1
-  - Revisar política de segurança e instruções de relatório
-
-  ## Contributors
-
-  @alex-clawd, @greysonlalonde, @joaomdmoura, @theCyberTech
-
-</Update>
-
 <Update label="25 mar 2026">
  ## v1.12.1

--- a/lib/crewai-files/src/crewai_files/init.py
+++ b/lib/crewai-files/src/crewai_files/init.py
@@ -152,4 +152,4 @@ __all__ = [
    "wrap_file_source",
 ]

-__version__ = "1.13.0rc1"
+__version__ = "1.12.1"
--- a/lib/crewai-tools/pyproject.toml
+++ b/lib/crewai-tools/pyproject.toml
@@ -11,7 +11,7 @@ dependencies = [
    "pytube~=15.0.0",
    "requests~=2.32.5",
    "docker~=7.1.0",
-    "crewai==1.13.0rc1",
+    "crewai==1.12.1",
    "tiktoken~=0.8.0",
    "beautifulsoup4~=4.13.4",
    "python-docx~=1.2.0",
--- a/lib/crewai-tools/src/crewai_tools/init.py
+++ b/lib/crewai-tools/src/crewai_tools/init.py
@@ -309,4 +309,4 @@ __all__ = [
    "ZapierActionTools",
 ]

-__version__ = "1.13.0rc1"
+__version__ = "1.12.1"
--- a/lib/crewai/pyproject.toml
+++ b/lib/crewai/pyproject.toml
@@ -54,7 +54,7 @@ Repository = "https://github.com/crewAIInc/crewAI"

 [project.optional-dependencies]
 tools = [
-    "crewai-tools==1.13.0rc1",
+    "crewai-tools==1.12.1",
 ]
 embeddings = [
    "tiktoken~=0.8.0"
--- a/lib/crewai/src/crewai/init.py
+++ b/lib/crewai/src/crewai/init.py
@@ -42,7 +42,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:

 _suppress_pydantic_deprecation_warnings()

-__version__ = "1.13.0rc1"
+__version__ = "1.12.1"
 _telemetry_submitted = False


--- a/lib/crewai/src/crewai/cli/templates/crew/pyproject.toml
+++ b/lib/crewai/src/crewai/cli/templates/crew/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.13.0rc1"
+    "crewai[tools]==1.12.1"
 ]

 [project.scripts]
--- a/lib/crewai/src/crewai/cli/templates/flow/pyproject.toml
+++ b/lib/crewai/src/crewai/cli/templates/flow/pyproject.toml
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.13.0rc1"
+    "crewai[tools]==1.12.1"
 ]

 [project.scripts]
--- a/lib/crewai/src/crewai/cli/templates/tool/pyproject.toml
+++ b/lib/crewai/src/crewai/cli/templates/tool/pyproject.toml
@@ -5,7 +5,7 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.13.0rc1"
+    "crewai[tools]==1.12.1"
 ]

 [tool.crewai]
--- a/lib/crewai/src/crewai/crew.py
+++ b/lib/crewai/src/crewai/crew.py
@@ -1338,18 +1338,7 @@ class Crew(FlowTrackable, BaseModel):
                api = getattr(agent.llm, "api", None)
                supported_types = get_supported_content_types(provider, api)

-            # Text files are always auto-injected (inlined as text), even
-            # when the model does not support multimodal input.
-            text_prefixes = (
-                "text/",
-                "application/json",
-                "application/xml",
-                "application/x-yaml",
-            )
-
            def is_auto_injected(content_type: str) -> bool:
-                if any(content_type.startswith(t) for t in text_prefixes):
-                    return True
                return any(content_type.startswith(t) for t in supported_types)

            # Only add read_file tool if there are files that need it
--- a/lib/crewai/src/crewai/flow/flow.py
+++ b/lib/crewai/src/crewai/flow/flow.py
@@ -883,9 +883,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
        self.human_feedback_history: list[HumanFeedbackResult] = []
        self.last_human_feedback: HumanFeedbackResult | None = None
        self._pending_feedback_context: PendingFeedbackContext | None = None
-        # Per-method stash for real @human_feedback output (keyed by method name)
-        # Used to decouple routing outcome from method return value when emit is set
-        self._human_feedback_method_outputs: dict[str, Any] = {}
+        self._human_feedback_method_output: Any = None  # Stashed real output from @human_feedback with emit
        self.suppress_flow_events: bool = suppress_flow_events

        # User input history (for self.ask())
@@ -2297,12 +2295,10 @@ class Flow(Generic[T], metaclass=FlowMeta):
            # For @human_feedback methods with emit, the result is the collapsed outcome
            # (e.g., "approved") used for routing. But we want the actual method output
            # to be the stored result (for final flow output). Replace the last entry
-            # if a stashed output exists. Dict-based stash is concurrency-safe and
-            # handles None return values (presence in dict = stashed, not value).
-            if method_name in self._human_feedback_method_outputs:
-                self._method_outputs[-1] = self._human_feedback_method_outputs.pop(
-                    method_name
-                )
+            # if a stashed output exists.
+            if self._human_feedback_method_output is not None:
+                self._method_outputs[-1] = self._human_feedback_method_output
+                self._human_feedback_method_output = None

            self._method_execution_counts[method_name] = (
                self._method_execution_counts.get(method_name, 0) + 1
--- a/lib/crewai/src/crewai/flow/human_feedback.py
+++ b/lib/crewai/src/crewai/flow/human_feedback.py
@@ -594,9 +594,8 @@ def human_feedback(
                # Stash the real method output for final flow result when emit is set
                # (result is the collapsed outcome string for routing, but we want to
                # preserve the actual method output as the flow's final result)
-                # Uses per-method dict for concurrency safety and to handle None returns
                if emit:
-                    self._human_feedback_method_outputs[func.__name__] = method_output
+                    self._human_feedback_method_output = method_output

                return result

@@ -625,9 +624,8 @@ def human_feedback(
                # Stash the real method output for final flow result when emit is set
                # (result is the collapsed outcome string for routing, but we want to
                # preserve the actual method output as the flow's final result)
-                # Uses per-method dict for concurrency safety and to handle None returns
                if emit:
-                    self._human_feedback_method_outputs[func.__name__] = method_output
+                    self._human_feedback_method_output = method_output

                return result

--- a/lib/crewai/src/crewai/llm.py
+++ b/lib/crewai/src/crewai/llm.py
@@ -54,10 +54,7 @@ from crewai.utilities.string_utils import sanitize_tool_name


 try:
-    from crewai_files import (
-        aformat_multimodal_content,
-        format_multimodal_content,
-    )
+    from crewai_files import aformat_multimodal_content, format_multimodal_content

    HAS_CREWAI_FILES = True
 except ImportError:
@@ -2042,10 +2039,6 @@ class LLM(BaseLLM):
        For each message with a `files` field, formats the files into
        provider-specific content blocks and updates the message content.

-        Text files (TextFile instances or files with text/* / application/json /
-        application/xml / application/x-yaml content types) are always inlined
-        as text content, even when the model does not support multimodal input.
-
        Args:
            messages: List of messages that may contain file attachments.

@@ -2056,55 +2049,11 @@ class LLM(BaseLLM):
            return messages

        if not self.supports_multimodal():
-            # Inline text files as text; reject non-text files
-            has_non_text = False
-            for msg in messages:
-                files = msg.get("files")
-                if not files:
-                    continue
-
-                text_parts: list[str] = []
-                non_text_files: dict[str, Any] = {}
-                for name, file_input in files.items():
-                    if self._is_text_file(file_input):
-                        try:
-                            content = file_input.read_text()
-                            text_parts.append(
-                                f"--- Content of file '{name}' ---\n{content}"
-                            )
-                        except Exception:
-                            non_text_files[name] = file_input
-                    else:
-                        non_text_files[name] = file_input
-
-                if non_text_files:
-                    has_non_text = True
-
-                if text_parts:
-                    existing_content = msg.get("content", "")
-                    inlined = "\n\n".join(text_parts)
-                    if isinstance(existing_content, str):
-                        msg["content"] = (
-                            f"{existing_content}\n\n{inlined}"
-                            if existing_content
-                            else inlined
-                        )
-                    elif isinstance(existing_content, list):
-                        msg["content"] = [
-                            *existing_content,
-                            self.format_text_content(inlined),
-                        ]
-
-                if non_text_files:
-                    msg["files"] = non_text_files
-                else:
-                    msg.pop("files", None)
-
-            if has_non_text:
+            if any(msg.get("files") for msg in messages):
                raise ValueError(
                    f"Model '{self.model}' does not support multimodal input, "
-                    "but non-text files were provided via 'input_files'. "
-                    "Use a vision-capable model or remove the non-text file inputs."
+                    "but files were provided via 'input_files'. "
+                    "Use a vision-capable model or remove the file inputs."
                )
            return messages

@@ -2141,10 +2090,6 @@ class LLM(BaseLLM):
        For each message with a `files` field, formats the files into
        provider-specific content blocks and updates the message content.

-        Text files (TextFile instances or files with text/* / application/json /
-        application/xml / application/x-yaml content types) are always inlined
-        as text content, even when the model does not support multimodal input.
-
        Args:
            messages: List of messages that may contain file attachments.

@@ -2155,55 +2100,11 @@ class LLM(BaseLLM):
            return messages

        if not self.supports_multimodal():
-            # Inline text files as text; reject non-text files
-            has_non_text = False
-            for msg in messages:
-                files = msg.get("files")
-                if not files:
-                    continue
-
-                text_parts: list[str] = []
-                non_text_files: dict[str, Any] = {}
-                for name, file_input in files.items():
-                    if self._is_text_file(file_input):
-                        try:
-                            content = file_input.read_text()
-                            text_parts.append(
-                                f"--- Content of file '{name}' ---\n{content}"
-                            )
-                        except Exception:
-                            non_text_files[name] = file_input
-                    else:
-                        non_text_files[name] = file_input
-
-                if non_text_files:
-                    has_non_text = True
-
-                if text_parts:
-                    existing_content = msg.get("content", "")
-                    inlined = "\n\n".join(text_parts)
-                    if isinstance(existing_content, str):
-                        msg["content"] = (
-                            f"{existing_content}\n\n{inlined}"
-                            if existing_content
-                            else inlined
-                        )
-                    elif isinstance(existing_content, list):
-                        msg["content"] = [
-                            *existing_content,
-                            self.format_text_content(inlined),
-                        ]
-
-                if non_text_files:
-                    msg["files"] = non_text_files
-                else:
-                    msg.pop("files", None)
-
-            if has_non_text:
+            if any(msg.get("files") for msg in messages):
                raise ValueError(
                    f"Model '{self.model}' does not support multimodal input, "
-                    "but non-text files were provided via 'input_files'. "
-                    "Use a vision-capable model or remove the non-text file inputs."
+                    "but files were provided via 'input_files'. "
+                    "Use a vision-capable model or remove the file inputs."
                )
            return messages

--- a/lib/crewai/src/crewai/llms/base_llm.py
+++ b/lib/crewai/src/crewai/llms/base_llm.py
@@ -37,7 +37,7 @@ from crewai.types.usage_metrics import UsageMetrics


 try:
-    from crewai_files import TextFile, format_multimodal_content
+    from crewai_files import format_multimodal_content

    HAS_CREWAI_FILES = True
 except ImportError:
@@ -635,10 +635,6 @@ class BaseLLM(ABC):
        For each message with a `files` field, formats the files into
        provider-specific content blocks and updates the message content.

-        Text files (TextFile instances or files with text/* / application/json /
-        application/xml / application/x-yaml content types) are always inlined
-        as text content, even when the model does not support multimodal input.
-
        Args:
            messages: List of messages that may contain file attachments.

@@ -648,61 +644,12 @@ class BaseLLM(ABC):
        if not HAS_CREWAI_FILES:
            return messages

-        is_multimodal = self.supports_multimodal()
-
-        if not is_multimodal:
-            # Inline text files as text; reject non-text files
-            has_non_text = False
-            for msg in messages:
-                files = msg.get("files")
-                if not files:
-                    continue
-
-                text_parts: list[str] = []
-                non_text_files: dict[str, Any] = {}
-                for name, file_input in files.items():
-                    if self._is_text_file(file_input):
-                        try:
-                            content = file_input.read_text()
-                            text_parts.append(
-                                f"--- Content of file '{name}' ---\n{content}"
-                            )
-                        except Exception:
-                            # If reading fails, fall back to tool-based access
-                            non_text_files[name] = file_input
-                    else:
-                        non_text_files[name] = file_input
-
-                if non_text_files:
-                    has_non_text = True
-
-                # Append inlined text content to the message
-                if text_parts:
-                    existing_content = msg.get("content", "")
-                    inlined = "\n\n".join(text_parts)
-                    if isinstance(existing_content, str):
-                        msg["content"] = (
-                            f"{existing_content}\n\n{inlined}"
-                            if existing_content
-                            else inlined
-                        )
-                    elif isinstance(existing_content, list):
-                        msg["content"] = [
-                            *existing_content,
-                            self.format_text_content(inlined),
-                        ]
-
-                # Keep only non-text files (for tool-based access)
-                if non_text_files:
-                    msg["files"] = non_text_files
-                else:
-                    msg.pop("files", None)
-
-            if has_non_text:
+        if not self.supports_multimodal():
+            if any(msg.get("files") for msg in messages):
                raise ValueError(
                    f"Model '{self.model}' does not support multimodal input, "
-                    "but non-text files were provided via 'input_files'. "
-                    "Use a vision-capable model or remove the non-text file inputs."
+                    "but files were provided via 'input_files'. "
+                    "Use a vision-capable model or remove the file inputs."
                )
            return messages

@@ -733,25 +680,6 @@ class BaseLLM(ABC):

        return messages

-    @staticmethod
-    def _is_text_file(file_input: Any) -> bool:
-        """Check whether a file input is a text file.
-
-        Returns True for TextFile instances or files whose content_type
-        starts with ``text/`` or matches common text-based MIME types
-        (application/json, application/xml, application/x-yaml).
-        """
-        if HAS_CREWAI_FILES and isinstance(file_input, TextFile):
-            return True
-        content_type = getattr(file_input, "content_type", "")
-        if content_type.startswith("text/"):
-            return True
-        return content_type in (
-            "application/json",
-            "application/xml",
-            "application/x-yaml",
-        )
-
    @staticmethod
    def _validate_structured_output(
        response: str,
--- a/lib/crewai/src/crewai/task.py
+++ b/lib/crewai/src/crewai/task.py
@@ -824,18 +824,7 @@ class Task(BaseModel):
                    api: str | None = getattr(self.agent.llm, "api", None)
                    supported_types = get_supported_content_types(provider, api)

-                # Text files are always auto-injected (inlined as text), even
-                # when the model does not support multimodal input.
-                text_prefixes = (
-                    "text/",
-                    "application/json",
-                    "application/xml",
-                    "application/x-yaml",
-                )
-
                def is_auto_injected(content_type: str) -> bool:
-                    if any(content_type.startswith(t) for t in text_prefixes):
-                        return True
                    return any(content_type.startswith(t) for t in supported_types)

                auto_injected_files = {
--- a/lib/crewai/tests/llms/test_multimodal.py
+++ b/lib/crewai/tests/llms/test_multimodal.py
@@ -338,280 +338,6 @@ class TestBaseLLMMultimodal:
        assert result == {"type": "text", "text": "Hello"}


-class TestTextFileInliningNonMultimodal:
-    """Tests for text file inlining on non-multimodal models (issue #5137).
-
-    When a model does not support multimodal input, text files should be
-    inlined as plain text in the message content rather than raising a
-    ValueError.
-    """
-
-    # --- BaseLLM (native provider path) ---
-
-    def test_base_text_file_inlined_on_non_multimodal(self) -> None:
-        """TextFile content is inlined when model is not multimodal (BaseLLM)."""
-        from crewai.llms.base_llm import BaseLLM
-
-        class NonMultimodalLLM(BaseLLM):
-            def call(self, messages, tools=None, callbacks=None):
-                return "test"
-
-        llm = NonMultimodalLLM(model="test-model")
-        assert llm.supports_multimodal() is False
-
-        text_content = b"Hello from a text file!"
-        messages = [
-            {
-                "role": "user",
-                "content": "Analyse this file",
-                "files": {"readme": TextFile(source=text_content)},
-            }
-        ]
-
-        result = llm._process_message_files(messages)
-
-        assert "files" not in result[0]
-        assert "Hello from a text file!" in result[0]["content"]
-        assert "readme" in result[0]["content"]
-
-    def test_base_multiple_text_files_inlined(self) -> None:
-        """Multiple text files are all inlined on non-multimodal model."""
-        from crewai.llms.base_llm import BaseLLM
-
-        class NonMultimodalLLM(BaseLLM):
-            def call(self, messages, tools=None, callbacks=None):
-                return "test"
-
-        llm = NonMultimodalLLM(model="test-model")
-
-        messages = [
-            {
-                "role": "user",
-                "content": "Analyse these files",
-                "files": {
-                    "file1": TextFile(source=b"Content of file 1"),
-                    "file2": TextFile(source=b"Content of file 2"),
-                },
-            }
-        ]
-
-        result = llm._process_message_files(messages)
-
-        assert "files" not in result[0]
-        assert "Content of file 1" in result[0]["content"]
-        assert "Content of file 2" in result[0]["content"]
-
-    def test_base_image_file_still_rejected_on_non_multimodal(self) -> None:
-        """ImageFile still raises ValueError on non-multimodal model."""
-        from crewai.llms.base_llm import BaseLLM
-
-        class NonMultimodalLLM(BaseLLM):
-            def call(self, messages, tools=None, callbacks=None):
-                return "test"
-
-        llm = NonMultimodalLLM(model="test-model")
-
-        messages = [
-            {
-                "role": "user",
-                "content": "Describe this image",
-                "files": {"photo": ImageFile(source=MINIMAL_PNG)},
-            }
-        ]
-
-        with pytest.raises(ValueError, match="non-text files"):
-            llm._process_message_files(messages)
-
-    def test_base_mixed_text_and_image_rejects_but_inlines_text(self) -> None:
-        """Mixed text+image: text is inlined, but error is raised for image."""
-        from crewai.llms.base_llm import BaseLLM
-
-        class NonMultimodalLLM(BaseLLM):
-            def call(self, messages, tools=None, callbacks=None):
-                return "test"
-
-        llm = NonMultimodalLLM(model="test-model")
-
-        messages = [
-            {
-                "role": "user",
-                "content": "Process these",
-                "files": {
-                    "readme": TextFile(source=b"Some text content"),
-                    "photo": ImageFile(source=MINIMAL_PNG),
-                },
-            }
-        ]
-
-        with pytest.raises(ValueError, match="non-text files"):
-            llm._process_message_files(messages)
-
-        # Text file should have been inlined before the error
-        assert "Some text content" in messages[0]["content"]
-
-    def test_base_no_files_no_error(self) -> None:
-        """Messages without files pass through unchanged."""
-        from crewai.llms.base_llm import BaseLLM
-
-        class NonMultimodalLLM(BaseLLM):
-            def call(self, messages, tools=None, callbacks=None):
-                return "test"
-
-        llm = NonMultimodalLLM(model="test-model")
-
-        messages = [
-            {"role": "user", "content": "No files here"},
-        ]
-
-        result = llm._process_message_files(messages)
-        assert result[0]["content"] == "No files here"
-
-    def test_base_text_file_with_empty_existing_content(self) -> None:
-        """TextFile inlined when existing content is empty string."""
-        from crewai.llms.base_llm import BaseLLM
-
-        class NonMultimodalLLM(BaseLLM):
-            def call(self, messages, tools=None, callbacks=None):
-                return "test"
-
-        llm = NonMultimodalLLM(model="test-model")
-
-        messages = [
-            {
-                "role": "user",
-                "content": "",
-                "files": {"doc": TextFile(source=b"File content here")},
-            }
-        ]
-
-        result = llm._process_message_files(messages)
-
-        assert "files" not in result[0]
-        assert "File content here" in result[0]["content"]
-        # Should not start with newlines when existing content is empty
-        assert not result[0]["content"].startswith("\n")
-
-    # --- LiteLLM LLM class ---
-
-    def test_litellm_text_file_inlined_on_non_multimodal(self) -> None:
-        """TextFile content is inlined when litellm model is not multimodal."""
-        llm = LLM(model="gpt-3.5-turbo", is_litellm=True)
-        assert llm.supports_multimodal() is False
-
-        messages = [
-            {
-                "role": "user",
-                "content": "Analyse this file",
-                "files": {"readme": TextFile(source=b"Hello from litellm test")},
-            }
-        ]
-
-        result = llm._process_message_files(messages)
-
-        assert "files" not in result[0]
-        assert "Hello from litellm test" in result[0]["content"]
-
-    def test_litellm_image_file_rejected_on_non_multimodal(self) -> None:
-        """ImageFile raises ValueError on non-multimodal litellm model."""
-        llm = LLM(model="gpt-3.5-turbo", is_litellm=True)
-        assert llm.supports_multimodal() is False
-
-        messages = [
-            {
-                "role": "user",
-                "content": "Describe this",
-                "files": {"photo": ImageFile(source=MINIMAL_PNG)},
-            }
-        ]
-
-        with pytest.raises(ValueError, match="non-text files"):
-            llm._process_message_files(messages)
-
-    def test_litellm_json_file_inlined_on_non_multimodal(self) -> None:
-        """JSON file (application/json) is treated as text and inlined."""
-        llm = LLM(model="gpt-3.5-turbo", is_litellm=True)
-        assert llm.supports_multimodal() is False
-
-        json_content = b'{"key": "value"}'
-        messages = [
-            {
-                "role": "user",
-                "content": "Parse this JSON",
-                "files": {"data": TextFile(source=json_content)},
-            }
-        ]
-
-        result = llm._process_message_files(messages)
-
-        assert "files" not in result[0]
-        assert '{"key": "value"}' in result[0]["content"]
-
-    # --- _is_text_file helper ---
-
-    def test_is_text_file_with_text_file_instance(self) -> None:
-        """_is_text_file returns True for TextFile instances."""
-        from crewai.llms.base_llm import BaseLLM
-
-        assert BaseLLM._is_text_file(TextFile(source=b"hello")) is True
-
-    def test_is_text_file_with_image_file_instance(self) -> None:
-        """_is_text_file returns False for ImageFile instances."""
-        from crewai.llms.base_llm import BaseLLM
-
-        assert BaseLLM._is_text_file(ImageFile(source=MINIMAL_PNG)) is False
-
-    def test_is_text_file_with_pdf_file_instance(self) -> None:
-        """_is_text_file returns False for PDFFile instances."""
-        from crewai.llms.base_llm import BaseLLM
-
-        assert BaseLLM._is_text_file(PDFFile(source=MINIMAL_PDF)) is False
-
-    def test_is_text_file_with_text_content_type(self) -> None:
-        """_is_text_file returns True for objects with text/* content_type."""
-        from crewai.llms.base_llm import BaseLLM
-
-        class MockFile:
-            content_type = "text/plain"
-
-        assert BaseLLM._is_text_file(MockFile()) is True
-
-    def test_is_text_file_with_json_content_type(self) -> None:
-        """_is_text_file returns True for application/json content_type."""
-        from crewai.llms.base_llm import BaseLLM
-
-        class MockFile:
-            content_type = "application/json"
-
-        assert BaseLLM._is_text_file(MockFile()) is True
-
-    def test_is_text_file_with_xml_content_type(self) -> None:
-        """_is_text_file returns True for application/xml content_type."""
-        from crewai.llms.base_llm import BaseLLM
-
-        class MockFile:
-            content_type = "application/xml"
-
-        assert BaseLLM._is_text_file(MockFile()) is True
-
-    def test_is_text_file_with_yaml_content_type(self) -> None:
-        """_is_text_file returns True for application/x-yaml content_type."""
-        from crewai.llms.base_llm import BaseLLM
-
-        class MockFile:
-            content_type = "application/x-yaml"
-
-        assert BaseLLM._is_text_file(MockFile()) is True
-
-    def test_is_text_file_with_image_content_type(self) -> None:
-        """_is_text_file returns False for image/* content_type."""
-        from crewai.llms.base_llm import BaseLLM
-
-        class MockFile:
-            content_type = "image/png"
-
-        assert BaseLLM._is_text_file(MockFile()) is False
-
-
 class TestMultipleFilesFormatting:
    """Tests for formatting multiple files at once."""

@@ -646,4 +372,4 @@ class TestMultipleFilesFormatting:

        result = format_multimodal_content({}, llm.model)

-        assert result == []
+        assert result == []
--- a/lib/crewai/tests/test_human_feedback_decorator.py
+++ b/lib/crewai/tests/test_human_feedback_decorator.py
@@ -726,31 +726,3 @@ class TestHumanFeedbackFinalOutputPreservation:
        # _method_outputs should contain the real output
        assert len(flow._method_outputs) == 1
        assert flow._method_outputs[0] == {"data": "real output"}
-
-    @patch("builtins.input", return_value="looks good")
-    @patch("builtins.print")
-    def test_none_return_value_is_preserved(self, mock_print, mock_input):
-        """A method returning None should preserve None as flow output, not the outcome string."""
-
-        class NoneReturnFlow(Flow):
-            @start()
-            @human_feedback(
-                message="Review:",
-                emit=["approved", "rejected"],
-                llm="gpt-4o-mini",
-            )
-            def process(self):
-                # Method does work but returns None (implicit)
-                pass
-
-        flow = NoneReturnFlow()
-
-        with (
-            patch.object(flow, "_request_human_feedback", return_value=""),
-            patch.object(flow, "_collapse_to_outcome", return_value="approved"),
-        ):
-            result = flow.kickoff()
-
-        # Final output should be None (the method's real return), not "approved"
-        assert result is None, f"Expected None, got {result!r}"
-        assert flow.last_human_feedback.outcome == "approved"
--- a/lib/devtools/src/crewai_devtools/init.py
+++ b/lib/devtools/src/crewai_devtools/init.py
@@ -1,3 +1,3 @@
 """CrewAI development tools."""

-__version__ = "1.13.0rc1"
+__version__ = "1.12.1"
--- a/lib/devtools/src/crewai_devtools/cli.py
+++ b/lib/devtools/src/crewai_devtools/cli.py
@@ -156,33 +156,6 @@ def update_version_in_file(file_path: Path, new_version: str) -> bool:
    return False


-def update_pyproject_version(file_path: Path, new_version: str) -> bool:
-    """Update the [project] version field in a pyproject.toml file.
-
-    Args:
-        file_path: Path to pyproject.toml file.
-        new_version: New version string.
-
-    Returns:
-        True if version was updated, False otherwise.
-    """
-    if not file_path.exists():
-        return False
-
-    content = file_path.read_text()
-    new_content = re.sub(
-        r'^(version\s*=\s*")[^"]+(")',
-        rf"\g<1>{new_version}\2",
-        content,
-        count=1,
-        flags=re.MULTILINE,
-    )
-    if new_content != content:
-        file_path.write_text(new_content)
-        return True
-    return False
-
-
 _DEFAULT_WORKSPACE_PACKAGES: Final[list[str]] = [
    "crewai",
    "crewai-tools",
@@ -1072,84 +1045,10 @@ def _update_enterprise_crewai_dep(pyproject_path: Path, version: str) -> bool:
    return False


-_DEPLOYMENT_TEST_REPO: Final[str] = "crewAIInc/crew_deployment_test"
-
 _PYPI_POLL_INTERVAL: Final[int] = 15
 _PYPI_POLL_TIMEOUT: Final[int] = 600


-def _update_deployment_test_repo(version: str, is_prerelease: bool) -> None:
-    """Update the deployment test repo to pin the new crewai version.
-
-    Clones the repo, updates the crewai[tools] pin in pyproject.toml,
-    regenerates the lockfile, commits, and pushes directly to main.
-
-    Args:
-        version: New crewai version string.
-        is_prerelease: Whether this is a pre-release version.
-    """
-    console.print(
-        f"\n[bold cyan]Updating {_DEPLOYMENT_TEST_REPO} to {version}[/bold cyan]"
-    )
-
-    with tempfile.TemporaryDirectory() as tmp:
-        repo_dir = Path(tmp) / "crew_deployment_test"
-        run_command(["gh", "repo", "clone", _DEPLOYMENT_TEST_REPO, str(repo_dir)])
-        console.print(f"[green]✓[/green] Cloned {_DEPLOYMENT_TEST_REPO}")
-
-        pyproject = repo_dir / "pyproject.toml"
-        content = pyproject.read_text()
-        new_content = re.sub(
-            r'"crewai\[tools\]==[^"]+"',
-            f'"crewai[tools]=={version}"',
-            content,
-        )
-        if new_content == content:
-            console.print(
-                "[yellow]Warning:[/yellow] No crewai[tools] pin found to update"
-            )
-            return
-        pyproject.write_text(new_content)
-        console.print(f"[green]✓[/green] Updated crewai[tools] pin to {version}")
-
-        lock_cmd = [
-            "uv",
-            "lock",
-            "--refresh-package",
-            "crewai",
-            "--refresh-package",
-            "crewai-tools",
-        ]
-        if is_prerelease:
-            lock_cmd.append("--prerelease=allow")
-
-        max_retries = 10
-        for attempt in range(1, max_retries + 1):
-            try:
-                run_command(lock_cmd, cwd=repo_dir)
-                break
-            except subprocess.CalledProcessError:
-                if attempt == max_retries:
-                    console.print(
-                        f"[red]Error:[/red] uv lock failed after {max_retries} attempts"
-                    )
-                    raise
-                console.print(
-                    f"[yellow]uv lock failed (attempt {attempt}/{max_retries}),"
-                    f" retrying in {_PYPI_POLL_INTERVAL}s...[/yellow]"
-                )
-                time.sleep(_PYPI_POLL_INTERVAL)
-        console.print("[green]✓[/green] Lockfile updated")
-
-        run_command(["git", "add", "pyproject.toml", "uv.lock"], cwd=repo_dir)
-        run_command(
-            ["git", "commit", "-m", f"chore: bump crewai to {version}"],
-            cwd=repo_dir,
-        )
-        run_command(["git", "push"], cwd=repo_dir)
-        console.print(f"[green]✓[/green] Pushed to {_DEPLOYMENT_TEST_REPO}")
-
-
 def _wait_for_pypi(package: str, version: str) -> None:
    """Poll PyPI until a specific package version is available.

@@ -1242,11 +1141,6 @@ def _release_enterprise(version: str, is_prerelease: bool, dry_run: bool) -> Non

            pyproject = pkg_dir / "pyproject.toml"
            if pyproject.exists():
-                if update_pyproject_version(pyproject, version):
-                    console.print(
-                        f"[green]✓[/green] Updated version in: "
-                        f"{pyproject.relative_to(repo_dir)}"
-                    )
                if update_pyproject_dependencies(
                    pyproject, version, extra_packages=list(_ENTERPRISE_EXTRA_PACKAGES)
                ):
@@ -1265,35 +1159,7 @@ def _release_enterprise(version: str, is_prerelease: bool, dry_run: bool) -> Non
        _wait_for_pypi("crewai", version)

        console.print("\nSyncing workspace...")
-        sync_cmd = [
-            "uv",
-            "sync",
-            "--refresh-package",
-            "crewai",
-            "--refresh-package",
-            "crewai-tools",
-            "--refresh-package",
-            "crewai-files",
-        ]
-        if is_prerelease:
-            sync_cmd.append("--prerelease=allow")
-
-        max_retries = 10
-        for attempt in range(1, max_retries + 1):
-            try:
-                run_command(sync_cmd, cwd=repo_dir)
-                break
-            except subprocess.CalledProcessError:
-                if attempt == max_retries:
-                    console.print(
-                        f"[red]Error:[/red] uv sync failed after {max_retries} attempts"
-                    )
-                    raise
-                console.print(
-                    f"[yellow]uv sync failed (attempt {attempt}/{max_retries}),"
-                    f" retrying in {_PYPI_POLL_INTERVAL}s...[/yellow]"
-                )
-                time.sleep(_PYPI_POLL_INTERVAL)
+        run_command(["uv", "sync"], cwd=repo_dir)
        console.print("[green]✓[/green] Workspace synced")

        # --- branch, commit, push, PR ---
@@ -1309,7 +1175,7 @@ def _release_enterprise(version: str, is_prerelease: bool, dry_run: bool) -> Non
        run_command(["git", "push", "-u", "origin", branch_name], cwd=repo_dir)
        console.print("[green]✓[/green] Branch pushed")

-        pr_url = run_command(
+        run_command(
            [
                "gh",
                "pr",
@@ -1326,7 +1192,6 @@ def _release_enterprise(version: str, is_prerelease: bool, dry_run: bool) -> Non
            cwd=repo_dir,
        )
        console.print("[green]✓[/green] Enterprise bump PR created")
-        console.print(f"[cyan]PR URL:[/cyan] {pr_url}")

        _poll_pr_until_merged(branch_name, "enterprise bump PR", repo=enterprise_repo)

@@ -1693,18 +1558,7 @@ def tag(dry_run: bool, no_edit: bool) -> None:
    is_flag=True,
    help="Skip the enterprise release phase",
 )
-@click.option(
-    "--skip-to-enterprise",
-    is_flag=True,
-    help="Skip phases 1 & 2, run only the enterprise release phase",
-)
-def release(
-    version: str,
-    dry_run: bool,
-    no_edit: bool,
-    skip_enterprise: bool,
-    skip_to_enterprise: bool,
-) -> None:
+def release(version: str, dry_run: bool, no_edit: bool, skip_enterprise: bool) -> None:
    """Full release: bump versions, tag, and publish a GitHub release.

    Combines bump and tag into a single workflow. Creates a version bump PR,
@@ -1717,19 +1571,11 @@ def release(
        dry_run: Show what would be done without making changes.
        no_edit: Skip editing release notes.
        skip_enterprise: Skip the enterprise release phase.
-        skip_to_enterprise: Skip phases 1 & 2, run only the enterprise release phase.
    """
    try:
        check_gh_installed()

-        if skip_enterprise and skip_to_enterprise:
-            console.print(
-                "[red]Error:[/red] Cannot use both --skip-enterprise "
-                "and --skip-to-enterprise"
-            )
-            sys.exit(1)
-
-        if not skip_enterprise or skip_to_enterprise:
+        if not skip_enterprise:
            missing: list[str] = []
            if not _ENTERPRISE_REPO:
                missing.append("ENTERPRISE_REPO")
@@ -1748,15 +1594,6 @@ def release(
        cwd = Path.cwd()
        lib_dir = cwd / "lib"

-        is_prerelease = _is_prerelease(version)
-
-        if skip_to_enterprise:
-            _release_enterprise(version, is_prerelease, dry_run)
-            console.print(
-                f"\n[green]✓[/green] Enterprise release [bold]{version}[/bold] complete!"
-            )
-            return
-
        if not dry_run:
            console.print("Checking git status...")
            check_git_clean()
@@ -1850,8 +1687,7 @@ def release(

        if not dry_run:
            _create_tag_and_release(tag_name, release_notes, is_prerelease)
-            _trigger_pypi_publish(tag_name, wait=True)
-            _update_deployment_test_repo(version, is_prerelease)
+            _trigger_pypi_publish(tag_name, wait=not skip_enterprise)

        if not skip_enterprise:
            _release_enterprise(version, is_prerelease, dry_run)