fix: capture tool name/input before _handle_agent_action in ReAct loops

_handle_agent_action can convert AgentAction to AgentFinish (when result_as_answer=True). Accessing .tool and .tool_input on AgentFinish would raise AttributeError. Now we capture the values beforehand. Co-Authored-By: João <joao@crewai.com>
feat: add agent loop detection middleware (#4682 )
2026-03-05 03:18:14 +00:00 · 2026-03-03 03:36:08 +00:00 · 2026-03-03 03:33:33 +00:00 · 2026-03-02 18:04:28 -05:00 · 2026-03-02 14:27:56 -05:00 · 2026-03-02 09:27:54 -05:00
39 changed files with 1765 additions and 444 deletions
--- a/docs/en/changelog.mdx
+++ b/docs/en/changelog.mdx
@@ -4,6 +4,106 @@ description: "Product updates, improvements, and bug fixes for CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="Feb 27, 2026">
+  ## v1.10.1a1
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.10.1a1)
+
+  ## What's Changed
+
+  ### Features
+  - Implement asynchronous invocation support in step callback methods
+  - Implement lazy loading for heavy dependencies in Memory module
+
+  ### Documentation
+  - Update changelog and version for v1.10.0
+
+  ### Refactoring
+  - Refactor step callback methods to support asynchronous invocation
+  - Refactor to implement lazy loading for heavy dependencies in Memory module
+
+  ### Bug Fixes
+  - Fix branch for release notes
+
+  ## Contributors
+
+  @greysonlalonde, @joaomdmoura
+
+</Update>
+
+<Update label="Feb 27, 2026">
+  ## v1.10.1a1
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.10.1a1)
+
+  ## What's Changed
+
+  ### Refactoring
+  - Refactor step callback methods to support asynchronous invocation
+  - Implement lazy loading for heavy dependencies in Memory module
+
+  ### Documentation
+  - Update changelog and version for v1.10.0
+
+  ### Bug Fixes
+  - Make branch for release notes
+
+  ## Contributors
+
+  @greysonlalonde, @joaomdmoura
+
+</Update>
+
+<Update label="Feb 26, 2026">
+  ## v1.10.0
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.10.0)
+
+  ## What's Changed
+
+  ### Features
+  - Enhance MCP tool resolution and related events
+  - Update lancedb version and add lance-namespace packages
+  - Enhance JSON argument parsing and validation in CrewAgentExecutor and BaseTool
+  - Migrate CLI HTTP client from requests to httpx
+  - Add versioned documentation
+  - Add yanked detection for version notes
+  - Implement user input handling in Flows
+  - Enhance HITL self-loop functionality in human feedback integration tests
+  - Add started_event_id and set in eventbus
+  - Auto update tools.specs
+
+  ### Bug Fixes
+  - Validate tool kwargs even when empty to prevent cryptic TypeError
+  - Preserve null types in tool parameter schemas for LLM
+  - Map output_pydantic/output_json to native structured output
+  - Ensure callbacks are ran/awaited if promise
+  - Capture method name in exception context
+  - Preserve enum type in router result; improve types
+  - Fix cyclic flows silently breaking when persistence ID is passed in inputs
+  - Correct CLI flag format from --skip-provider to --skip_provider
+  - Ensure OpenAI tool call stream is finalized
+  - Resolve complex schema $ref pointers in MCP tools
+  - Enforce additionalProperties=false in schemas
+  - Reject reserved script names for crew folders
+  - Resolve race condition in guardrail event emission test
+
+  ### Documentation
+  - Add litellm dependency note for non-native LLM providers
+  - Clarify NL2SQL security model and hardening guidance
+  - Add 96 missing actions across 9 integrations
+
+  ### Refactoring
+  - Refactor crew to provider
+  - Extract HITL to provider pattern
+  - Improve hook typing and registration
+
+  ## Contributors
+
+  @dependabot[bot], @github-actions[bot], @github-code-quality[bot], @greysonlalonde, @heitorado, @hobostay, @joaomdmoura, @johnvan7, @jonathansampson, @lorenzejay, @lucasgomide, @mattatcha, @mplachta, @nicoferdi96, @theCyberTech, @thiagomoretto, @vinibrsl
+
+</Update>
+
 <Update label="Jan 26, 2026">
  ## v1.9.0

--- a/docs/en/tools/automation/composiotool.mdx
+++ b/docs/en/tools/automation/composiotool.mdx
@@ -18,77 +18,46 @@ Composio is an integration platform that allows you to connect your AI agents to
 To incorporate Composio tools into your project, follow the instructions below:

 ```shell
-pip install composio-crewai
+pip install composio composio-crewai
 pip install crewai
 ```

-After the installation is complete, either run `composio login` or export your composio API key as `COMPOSIO_API_KEY`. Get your Composio API key from [here](https://app.composio.dev)
+After the installation is complete, set your Composio API key as `COMPOSIO_API_KEY`. Get your Composio API key from [here](https://platform.composio.dev)

 ## Example

 The following example demonstrates how to initialize the tool and execute a github action:

-1. Initialize Composio toolset
+1. Initialize Composio with CrewAI Provider

 ```python Code
-from composio_crewai import ComposioToolSet, App, Action
+from composio_crewai import ComposioProvider
+from composio import Composio
 from crewai import Agent, Task, Crew

-toolset = ComposioToolSet()
+composio = Composio(provider=ComposioProvider())
 ```

-2. Connect your GitHub account
+2. Create a new Composio Session and retrieve the tools
 <CodeGroup>
-```shell CLI
-composio add github
-```
-```python Code
-request = toolset.initiate_connection(app=App.GITHUB)
-print(f"Open this URL to authenticate: {request.redirectUrl}")
+```python
+session = composio.create(
+    user_id="your-user-id",
+    toolkits=["gmail", "github"] # optional, default is all toolkits
+)
+tools = session.tools()
 ```
+Read more about sessions and user management [here](https://docs.composio.dev/docs/configuring-sessions)
 </CodeGroup>

-3. Get Tools
+3. Authenticating users manually

- Retrieving all the tools from an app (not recommended for production):
+Composio automatically authenticates the users during the agent chat session. However, you can also authenticate the user manually by calling the `authorize` method.
 ```python Code
-tools = toolset.get_tools(apps=[App.GITHUB])
+connection_request = session.authorize("github")
+print(f"Open this URL to authenticate: {connection_request.redirect_url}")
 ```

- Filtering tools based on tags:
-```python Code
-tag = "users"
-
-filtered_action_enums = toolset.find_actions_by_tags(
-    App.GITHUB,
-    tags=[tag], 
-)
-
-tools = toolset.get_tools(actions=filtered_action_enums)
-```
-
- Filtering tools based on use case:
-```python Code
-use_case = "Star a repository on GitHub"
-
-filtered_action_enums = toolset.find_actions_by_use_case(
-    App.GITHUB, use_case=use_case, advanced=False
-)
-
-tools = toolset.get_tools(actions=filtered_action_enums)
-```
-<Tip>Set `advanced` to True to get actions for complex use cases</Tip>
-
- Using specific tools:
-
-In this demo, we will use the `GITHUB_STAR_A_REPOSITORY_FOR_THE_AUTHENTICATED_USER` action from the GitHub app.
-```python Code
-tools = toolset.get_tools(
-    actions=[Action.GITHUB_STAR_A_REPOSITORY_FOR_THE_AUTHENTICATED_USER]
-)
-```
-Learn more about filtering actions [here](https://docs.composio.dev/patterns/tools/use-tools/use-specific-actions)
-
 4. Define agent

 ```python Code
@@ -116,4 +85,4 @@ crew = Crew(agents=[crewai_agent], tasks=[task])
 crew.kickoff()
 ```

-* More detailed list of tools can be found [here](https://app.composio.dev)
+* More detailed list of tools can be found [here](https://docs.composio.dev/toolkits)
--- a/docs/ko/changelog.mdx
+++ b/docs/ko/changelog.mdx
@@ -4,6 +4,106 @@ description: "CrewAI의 제품 업데이트, 개선 사항 및 버그 수정"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="2026년 2월 27일">
+  ## v1.10.1a1
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.10.1a1)
+
+  ## 변경 사항
+
+  ### 기능
+  - 단계 콜백 메서드에서 비동기 호출 지원 구현
+  - 메모리 모듈의 무거운 의존성에 대한 지연 로딩 구현
+
+  ### 문서
+  - v1.10.0에 대한 변경 로그 및 버전 업데이트
+
+  ### 리팩토링
+  - 비동기 호출을 지원하기 위해 단계 콜백 메서드 리팩토링
+  - 메모리 모듈의 무거운 의존성에 대한 지연 로딩을 구현하기 위해 리팩토링
+
+  ### 버그 수정
+  - 릴리스 노트의 분기 수정
+
+  ## 기여자
+
+  @greysonlalonde, @joaomdmoura
+
+</Update>
+
+<Update label="2026년 2월 27일">
+  ## v1.10.1a1
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.10.1a1)
+
+  ## 변경 사항
+
+  ### 리팩토링
+  - 비동기 호출을 지원하기 위해 단계 콜백 메서드 리팩토링
+  - 메모리 모듈의 무거운 의존성에 대해 지연 로딩 구현
+
+  ### 문서화
+  - v1.10.0에 대한 변경 로그 및 버전 업데이트
+
+  ### 버그 수정
+  - 릴리스 노트를 위한 브랜치 생성
+
+  ## 기여자
+
+  @greysonlalonde, @joaomdmoura
+
+</Update>
+
+<Update label="2026년 2월 26일">
+  ## v1.10.0
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.10.0)
+
+  ## 변경 사항
+
+  ### 기능
+  - MCP 도구 해상도 및 관련 이벤트 개선
+  - lancedb 버전 업데이트 및 lance-namespace 패키지 추가
+  - CrewAgentExecutor 및 BaseTool에서 JSON 인수 파싱 및 검증 개선
+  - CLI HTTP 클라이언트를 requests에서 httpx로 마이그레이션
+  - 버전화된 문서 추가
+  - 버전 노트에 대한 yanked 감지 추가
+  - Flows에서 사용자 입력 처리 구현
+  - 인간 피드백 통합 테스트에서 HITL 자기 루프 기능 개선
+  - eventbus에 started_event_id 추가 및 설정
+  - tools.specs 자동 업데이트
+
+  ### 버그 수정
+  - 빈 경우에도 도구 kwargs를 검증하여 모호한 TypeError 방지
+  - LLM을 위한 도구 매개변수 스키마에서 null 타입 유지
+  - output_pydantic/output_json을 네이티브 구조화된 출력으로 매핑
+  - 약속이 있는 경우 콜백이 실행/대기되도록 보장
+  - 예외 컨텍스트에서 메서드 이름 캡처
+  - 라우터 결과에서 enum 타입 유지; 타입 개선
+  - 입력으로 지속성 ID가 전달될 때 조용히 깨지는 순환 흐름 수정
+  - CLI 플래그 형식을 --skip-provider에서 --skip_provider로 수정
+  - OpenAI 도구 호출 스트림이 완료되도록 보장
+  - MCP 도구에서 복잡한 스키마 $ref 포인터 해결
+  - 스키마에서 additionalProperties=false 강제 적용
+  - 크루 폴더에 대해 예약된 스크립트 이름 거부
+  - 가드레일 이벤트 방출 테스트에서 경쟁 조건 해결
+
+  ### 문서
+  - 비네이티브 LLM 공급자를 위한 litellm 종속성 노트 추가
+  - NL2SQL 보안 모델 및 강화 지침 명확화
+  - 9개 통합에서 96개의 누락된 작업 추가
+
+  ### 리팩토링
+  - crew를 provider로 리팩토링
+  - HITL을 provider 패턴으로 추출
+  - 훅 타이핑 및 등록 개선
+
+  ## 기여자
+
+  @dependabot[bot], @github-actions[bot], @github-code-quality[bot], @greysonlalonde, @heitorado, @hobostay, @joaomdmoura, @johnvan7, @jonathansampson, @lorenzejay, @lucasgomide, @mattatcha, @mplachta, @nicoferdi96, @theCyberTech, @thiagomoretto, @vinibrsl
+
+</Update>
+
 <Update label="2026년 1월 26일">
  ## v1.9.0

--- a/docs/ko/tools/automation/composiotool.mdx
+++ b/docs/ko/tools/automation/composiotool.mdx
@@ -18,77 +18,46 @@ Composio는 AI 에이전트를 250개 이상의 도구와 연결할 수 있는
 Composio 도구를 프로젝트에 통합하려면 아래 지침을 따르세요:

 ```shell
-pip install composio-crewai
+pip install composio composio-crewai
 pip install crewai
 ```

-설치가 완료된 후, `composio login`을 실행하거나 Composio API 키를 `COMPOSIO_API_KEY`로 export하세요. Composio API 키는 [여기](https://app.composio.dev)에서 받을 수 있습니다.
+설치가 완료되면 Composio API 키를 `COMPOSIO_API_KEY`로 설정하세요. Composio API 키는 [여기](https://platform.composio.dev)에서 받을 수 있습니다.

 ## 예시

-다음 예시는 도구를 초기화하고 github action을 실행하는 방법을 보여줍니다:
+다음 예시는 도구를 초기화하고 GitHub 액션을 실행하는 방법을 보여줍니다:

-1. Composio 도구 세트 초기화
+1. CrewAI Provider와 함께 Composio 초기화

 ```python Code
-from composio_crewai import ComposioToolSet, App, Action
+from composio_crewai import ComposioProvider
+from composio import Composio
 from crewai import Agent, Task, Crew

-toolset = ComposioToolSet()
+composio = Composio(provider=ComposioProvider())
 ```

-2. GitHub 계정 연결
+2. 새 Composio 세션을 만들고 도구 가져오기
 <CodeGroup>
-```shell CLI
-composio add github
-```
-```python Code
-request = toolset.initiate_connection(app=App.GITHUB)
-print(f"Open this URL to authenticate: {request.redirectUrl}")
+```python
+session = composio.create(
+    user_id="your-user-id",
+    toolkits=["gmail", "github"] # optional, default is all toolkits
+)
+tools = session.tools()
 ```
+세션 및 사용자 관리에 대한 자세한 내용은 [여기](https://docs.composio.dev/docs/configuring-sessions)를 참고하세요.
 </CodeGroup>

-3. 도구 가져오기
+3. 사용자 수동 인증하기

- 앱에서 모든 도구를 가져오기 (프로덕션 환경에서는 권장하지 않음):
+Composio는 에이전트 채팅 세션 중에 사용자를 자동으로 인증합니다. 하지만 `authorize` 메서드를 호출해 사용자를 수동으로 인증할 수도 있습니다.
 ```python Code
-tools = toolset.get_tools(apps=[App.GITHUB])
+connection_request = session.authorize("github")
+print(f"Open this URL to authenticate: {connection_request.redirect_url}")
 ```

- 태그를 기반으로 도구 필터링:
-```python Code
-tag = "users"
-
-filtered_action_enums = toolset.find_actions_by_tags(
-    App.GITHUB,
-    tags=[tag], 
-)
-
-tools = toolset.get_tools(actions=filtered_action_enums)
-```
-
- 사용 사례를 기반으로 도구 필터링:
-```python Code
-use_case = "Star a repository on GitHub"
-
-filtered_action_enums = toolset.find_actions_by_use_case(
-    App.GITHUB, use_case=use_case, advanced=False
-)
-
-tools = toolset.get_tools(actions=filtered_action_enums)
-```
-<Tip>`advanced`를 True로 설정하면 복잡한 사용 사례를 위한 액션을 가져올 수 있습니다</Tip>
-
- 특정 도구 사용하기:
-
-이 데모에서는 GitHub 앱의 `GITHUB_STAR_A_REPOSITORY_FOR_THE_AUTHENTICATED_USER` 액션을 사용합니다.
-```python Code
-tools = toolset.get_tools(
-    actions=[Action.GITHUB_STAR_A_REPOSITORY_FOR_THE_AUTHENTICATED_USER]
-)
-```
-액션 필터링에 대해 더 자세한 내용을 보려면 [여기](https://docs.composio.dev/patterns/tools/use-tools/use-specific-actions)를 참고하세요.
-
 4. 에이전트 정의

 ```python Code
@@ -116,4 +85,4 @@ crew = Crew(agents=[crewai_agent], tasks=[task])
 crew.kickoff()
 ```

-* 더욱 자세한 도구 리스트는 [여기](https://app.composio.dev)에서 확인하실 수 있습니다.
+* 더욱 자세한 도구 목록은 [여기](https://docs.composio.dev/toolkits)에서 확인할 수 있습니다.
--- a/docs/pt-BR/changelog.mdx
+++ b/docs/pt-BR/changelog.mdx
@@ -4,6 +4,106 @@ description: "Atualizações de produto, melhorias e correções do CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="27 fev 2026">
+  ## v1.10.1a1
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.10.1a1)
+
+  ## O que Mudou
+
+  ### Funcionalidades
+  - Implementar suporte a invocação assíncrona em métodos de callback de etapas
+  - Implementar carregamento sob demanda para dependências pesadas no módulo de Memória
+
+  ### Documentação
+  - Atualizar changelog e versão para v1.10.0
+
+  ### Refatoração
+  - Refatorar métodos de callback de etapas para suportar invocação assíncrona
+  - Refatorar para implementar carregamento sob demanda para dependências pesadas no módulo de Memória
+
+  ### Correções de Bugs
+  - Corrigir branch para notas de lançamento
+
+  ## Contribuidores
+
+  @greysonlalonde, @joaomdmoura
+
+</Update>
+
+<Update label="27 fev 2026">
+  ## v1.10.1a1
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.10.1a1)
+
+  ## O que Mudou
+
+  ### Refatoração
+  - Refatorar métodos de callback de etapas para suportar invocação assíncrona
+  - Implementar carregamento sob demanda para dependências pesadas no módulo de Memória
+
+  ### Documentação
+  - Atualizar changelog e versão para v1.10.0
+
+  ### Correções de Bugs
+  - Criar branch para notas de lançamento
+
+  ## Contribuidores
+
+  @greysonlalonde, @joaomdmoura
+
+</Update>
+
+<Update label="26 fev 2026">
+  ## v1.10.0
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.10.0)
+
+  ## O que Mudou
+
+  ### Recursos
+  - Aprimorar a resolução da ferramenta MCP e eventos relacionados
+  - Atualizar a versão do lancedb e adicionar pacotes lance-namespace
+  - Aprimorar a análise e validação de argumentos JSON no CrewAgentExecutor e BaseTool
+  - Migrar o cliente HTTP da CLI de requests para httpx
+  - Adicionar documentação versionada
+  - Adicionar detecção de versões removidas para notas de versão
+  - Implementar tratamento de entrada do usuário em Flows
+  - Aprimorar a funcionalidade de auto-loop HITL nos testes de integração de feedback humano
+  - Adicionar started_event_id e definir no eventbus
+  - Atualizar automaticamente tools.specs
+
+  ### Correções de Bugs
+  - Validar kwargs da ferramenta mesmo quando vazios para evitar TypeError crípticos
+  - Preservar tipos nulos nos esquemas de parâmetros da ferramenta para LLM
+  - Mapear output_pydantic/output_json para saída estruturada nativa
+  - Garantir que callbacks sejam executados/aguardados se forem promessas
+  - Capturar o nome do método no contexto da exceção
+  - Preservar tipo enum no resultado do roteador; melhorar tipos
+  - Corrigir fluxos cíclicos que quebram silenciosamente quando o ID de persistência é passado nas entradas
+  - Corrigir o formato da flag da CLI de --skip-provider para --skip_provider
+  - Garantir que o fluxo de chamada da ferramenta OpenAI seja finalizado
+  - Resolver ponteiros $ref de esquema complexos nas ferramentas MCP
+  - Impor additionalProperties=false nos esquemas
+  - Rejeitar nomes de scripts reservados para pastas de equipe
+  - Resolver condição de corrida no teste de emissão de eventos de guardrail
+
+  ### Documentação
+  - Adicionar nota de dependência litellm para provedores de LLM não nativos
+  - Esclarecer o modelo de segurança NL2SQL e orientações de fortalecimento
+  - Adicionar 96 ações ausentes em 9 integrações
+
+  ### Refatoração
+  - Refatorar crew para provider
+  - Extrair HITL para padrão de provider
+  - Melhorar tipagem e registro de hooks
+
+  ## Contribuidores
+
+  @dependabot[bot], @github-actions[bot], @github-code-quality[bot], @greysonlalonde, @heitorado, @hobostay, @joaomdmoura, @johnvan7, @jonathansampson, @lorenzejay, @lucasgomide, @mattatcha, @mplachta, @nicoferdi96, @theCyberTech, @thiagomoretto, @vinibrsl
+
+</Update>
+
 <Update label="26 jan 2026">
  ## v1.9.0

--- a/docs/pt-BR/tools/automation/composiotool.mdx
+++ b/docs/pt-BR/tools/automation/composiotool.mdx
@@ -11,84 +11,53 @@ mode: "wide"
 Composio é uma plataforma de integração que permite conectar seus agentes de IA a mais de 250 ferramentas. Os principais recursos incluem:

 - **Autenticação de Nível Empresarial**: Suporte integrado para OAuth, Chaves de API, JWT com atualização automática de token
- **Observabilidade Completa**: Logs detalhados de uso das ferramentas, registros de execução, e muito mais
+- **Observabilidade Completa**: Logs detalhados de uso das ferramentas, carimbos de data/hora de execução e muito mais

 ## Instalação

 Para incorporar as ferramentas Composio em seu projeto, siga as instruções abaixo:

 ```shell
-pip install composio-crewai
+pip install composio composio-crewai
 pip install crewai
 ```

-Após a conclusão da instalação, execute `composio login` ou exporte sua chave de API do composio como `COMPOSIO_API_KEY`. Obtenha sua chave de API Composio [aqui](https://app.composio.dev)
+Após concluir a instalação, defina sua chave de API do Composio como `COMPOSIO_API_KEY`. Obtenha sua chave de API do Composio [aqui](https://platform.composio.dev)

 ## Exemplo

-O exemplo a seguir demonstra como inicializar a ferramenta e executar uma ação do github:
+O exemplo a seguir demonstra como inicializar a ferramenta e executar uma ação do GitHub:

-1. Inicialize o conjunto de ferramentas Composio
+1. Inicialize o Composio com o Provider do CrewAI

 ```python Code
-from composio_crewai import ComposioToolSet, App, Action
+from composio_crewai import ComposioProvider
+from composio import Composio
 from crewai import Agent, Task, Crew

-toolset = ComposioToolSet()
+composio = Composio(provider=ComposioProvider())
 ```

-2. Conecte sua conta do GitHub
+2. Crie uma nova sessão Composio e recupere as ferramentas
 <CodeGroup>
-```shell CLI
-composio add github
-```
-```python Code
-request = toolset.initiate_connection(app=App.GITHUB)
-print(f"Open this URL to authenticate: {request.redirectUrl}")
+```python
+session = composio.create(
+    user_id="your-user-id",
+    toolkits=["gmail", "github"] # optional, default is all toolkits
+)
+tools = session.tools()
 ```
+Leia mais sobre sessões e gerenciamento de usuários [aqui](https://docs.composio.dev/docs/configuring-sessions)
 </CodeGroup>

-3. Obtenha ferramentas
+3. Autenticação manual dos usuários

- Recuperando todas as ferramentas de um app (não recomendado em produção):
+O Composio autentica automaticamente os usuários durante a sessão de chat do agente. No entanto, você também pode autenticar o usuário manualmente chamando o método `authorize`.
 ```python Code
-tools = toolset.get_tools(apps=[App.GITHUB])
+connection_request = session.authorize("github")
+print(f"Open this URL to authenticate: {connection_request.redirect_url}")
 ```

- Filtrando ferramentas com base em tags:
-```python Code
-tag = "users"
-
-filtered_action_enums = toolset.find_actions_by_tags(
-    App.GITHUB,
-    tags=[tag], 
-)
-
-tools = toolset.get_tools(actions=filtered_action_enums)
-```
-
- Filtrando ferramentas com base no caso de uso:
-```python Code
-use_case = "Star a repository on GitHub"
-
-filtered_action_enums = toolset.find_actions_by_use_case(
-    App.GITHUB, use_case=use_case, advanced=False
-)
-
-tools = toolset.get_tools(actions=filtered_action_enums)
-```
-<Tip>Defina `advanced` como True para obter ações para casos de uso complexos</Tip>
-
- Usando ferramentas específicas:
-
-Neste exemplo, usaremos a ação `GITHUB_STAR_A_REPOSITORY_FOR_THE_AUTHENTICATED_USER` do app GitHub.
-```python Code
-tools = toolset.get_tools(
-    actions=[Action.GITHUB_STAR_A_REPOSITORY_FOR_THE_AUTHENTICATED_USER]
-)
-```
-Saiba mais sobre como filtrar ações [aqui](https://docs.composio.dev/patterns/tools/use-tools/use-specific-actions)
-
 4. Defina o agente

 ```python Code
@@ -116,4 +85,4 @@ crew = Crew(agents=[crewai_agent], tasks=[task])
 crew.kickoff()
 ```

-* Uma lista mais detalhada de ferramentas pode ser encontrada [aqui](https://app.composio.dev)
+* Uma lista mais detalhada de ferramentas pode ser encontrada [aqui](https://docs.composio.dev/toolkits)
--- a/lib/crewai-files/pyproject.toml
+++ b/lib/crewai-files/pyproject.toml
@@ -8,8 +8,8 @@ authors = [
 ]
 requires-python = ">=3.10, <3.14"
 dependencies = [
-    "Pillow~=10.4.0",
-    "pypdf~=4.0.0",
+    "Pillow~=12.1.1",
+    "pypdf~=6.7.4",
    "python-magic>=0.4.27",
    "aiocache~=0.12.3",
    "aiofiles~=24.1.0",
--- 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__ = "1.10.0"
+__version__ = "1.10.1a1"
--- 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==1.10.0",
+    "crewai==1.10.1a1",
    "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
@@ -291,4 +291,4 @@ __all__ = [
    "ZapierActionTools",
 ]

-__version__ = "1.10.0"
+__version__ = "1.10.1a1"
--- a/lib/crewai/pyproject.toml
+++ b/lib/crewai/pyproject.toml
@@ -21,7 +21,7 @@ dependencies = [
    "opentelemetry-exporter-otlp-proto-http~=1.34.0",
    # Data Handling
    "chromadb~=1.1.0",
-    "tokenizers~=0.20.3",
+    "tokenizers>=0.21,<1",
    "openpyxl~=3.1.5",
    # Authentication and Security
    "python-dotenv~=1.1.1",
@@ -53,7 +53,7 @@ Repository = "https://github.com/crewAIInc/crewAI"

 [project.optional-dependencies]
 tools = [
-    "crewai-tools==1.10.0",
+    "crewai-tools==1.10.1a1",
 ]
 embeddings = [
    "tiktoken~=0.8.0"
@@ -66,7 +66,7 @@ openpyxl = [
 ]
 mem0 = ["mem0ai~=0.1.94"]
 docling = [
-    "docling~=2.63.0",
+    "docling~=2.75.0",
 ]
 qdrant = [
    "qdrant-client[fastembed]~=1.14.3",
@@ -88,7 +88,7 @@ bedrock = [
    "boto3~=1.40.45",
 ]
 google-genai = [
-    "google-genai~=1.49.0",
+    "google-genai~=1.65.0",
 ]
 azure-ai-inference = [
    "azure-ai-inference~=1.0.0b9",
--- a/lib/crewai/src/crewai/init.py
+++ b/lib/crewai/src/crewai/init.py
@@ -4,13 +4,13 @@ import urllib.request
 import warnings

 from crewai.agent.core import Agent
+from crewai.agents.loop_detector import LoopDetector
 from crewai.crew import Crew
 from crewai.crews.crew_output import CrewOutput
 from crewai.flow.flow import Flow
 from crewai.knowledge.knowledge import Knowledge
 from crewai.llm import LLM
 from crewai.llms.base_llm import BaseLLM
-from crewai.memory.unified_memory import Memory
 from crewai.process import Process
 from crewai.task import Task
 from crewai.tasks.llm_guardrail import LLMGuardrail
@@ -41,7 +41,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:

 _suppress_pydantic_deprecation_warnings()

-__version__ = "1.10.0"
+__version__ = "1.10.1a1"
 _telemetry_submitted = False


@@ -72,6 +72,25 @@ def _track_install_async() -> None:


 _track_install_async()
+
+_LAZY_IMPORTS: dict[str, tuple[str, str]] = {
+    "Memory": ("crewai.memory.unified_memory", "Memory"),
+}
+
+
+def __getattr__(name: str) -> Any:
+    """Lazily import heavy modules (e.g. Memory → lancedb) on first access."""
+    if name in _LAZY_IMPORTS:
+        module_path, attr = _LAZY_IMPORTS[name]
+        import importlib
+
+        mod = importlib.import_module(module_path)
+        val = getattr(mod, attr)
+        globals()[name] = val
+        return val
+    raise AttributeError(f"module 'crewai' has no attribute {name!r}")
+
+
 __all__ = [
    "LLM",
    "Agent",
@@ -81,6 +100,7 @@ __all__ = [
    "Flow",
    "Knowledge",
    "LLMGuardrail",
+    "LoopDetector",
    "Memory",
    "Process",
    "Task",
--- a/lib/crewai/src/crewai/agents/agent_builder/base_agent.py
+++ b/lib/crewai/src/crewai/agents/agent_builder/base_agent.py
@@ -22,6 +22,7 @@ from typing_extensions import Self
 from crewai.agent.internal.meta import AgentMeta
 from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
 from crewai.agents.cache.cache_handler import CacheHandler
+from crewai.agents.loop_detector import LoopDetector
 from crewai.agents.tools_handler import ToolsHandler
 from crewai.knowledge.knowledge import Knowledge
 from crewai.knowledge.knowledge_config import KnowledgeConfig
@@ -213,6 +214,15 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
            "If not set, falls back to crew memory."
        ),
    )
+    loop_detector: LoopDetector | None = Field(
+        default=None,
+        description=(
+            "Optional loop detection middleware. When set, monitors agent tool calls "
+            "for repetitive patterns and intervenes to break loops. "
+            "Pass a LoopDetector instance to configure window_size, "
+            "repetition_threshold, and on_loop behavior."
+        ),
+    )

    @model_validator(mode="before")
    @classmethod
--- a/lib/crewai/src/crewai/agents/crew_agent_executor.py
+++ b/lib/crewai/src/crewai/agents/crew_agent_executor.py
@@ -17,6 +17,7 @@ from pydantic import BaseModel, GetCoreSchemaHandler, ValidationError
 from pydantic_core import CoreSchema, core_schema

 from crewai.agents.agent_builder.base_agent_executor_mixin import CrewAgentExecutorMixin
+from crewai.agents.loop_detector import LoopDetector
 from crewai.agents.parser import (
    AgentAction,
    AgentFinish,
@@ -156,6 +157,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
        self.messages: list[LLMMessage] = []
        self.iterations = 0
        self.log_error_after = 3
+        self.loop_detector: LoopDetector | None = (
+            agent.loop_detector if agent and hasattr(agent, "loop_detector") else None
+        )
+        if self.loop_detector:
+            self.loop_detector.reset()
        self.before_llm_call_hooks: list[Callable[..., Any]] = []
        self.after_llm_call_hooks: list[Callable[..., Any]] = []
        self.before_llm_call_hooks.extend(get_before_llm_call_hooks())
@@ -410,6 +416,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                            )
                        }

+                    # Capture tool info before _handle_agent_action may
+                    # convert the answer to AgentFinish (result_as_answer).
+                    _tool_name = formatted_answer.tool
+                    _tool_input = formatted_answer.tool_input
+
                    tool_result = execute_tool_and_check_finality(
                        agent_action=formatted_answer,
                        fingerprint_context=fingerprint_context,
@@ -427,6 +438,14 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                        formatted_answer, tool_result
                    )

+                    # Check for repetitive loop patterns
+                    loop_result = self._record_and_check_loop(
+                        _tool_name, _tool_input
+                    )
+                    if loop_result is not None:
+                        formatted_answer = loop_result
+                        break
+
                self._invoke_step_callback(formatted_answer)  # type: ignore[arg-type]
                self._append_message(formatted_answer.text)  # type: ignore[union-attr]

@@ -487,8 +506,8 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
            # No tools available, fall back to simple LLM call
            return self._invoke_loop_native_no_tools()

-        openai_tools, available_functions = convert_tools_to_openai_schema(
-            self.original_tools
+        openai_tools, available_functions, self._tool_name_mapping = (
+            convert_tools_to_openai_schema(self.original_tools)
        )

        while True:
@@ -700,9 +719,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
        if not parsed_calls:
            return None

-        original_tools_by_name: dict[str, Any] = {}
-        for tool in self.original_tools or []:
-            original_tools_by_name[sanitize_tool_name(tool.name)] = tool
+        original_tools_by_name: dict[str, Any] = dict(self._tool_name_mapping)

        if len(parsed_calls) > 1:
            has_result_as_answer_in_batch = any(
@@ -785,6 +802,14 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                    if tool_finish:
                        return tool_finish

+                    # Check for loop after each parallel tool result
+                    loop_result = self._record_and_check_loop(
+                        execution_result["func_name"],
+                        execution_result.get("tool_args", ""),
+                    )
+                    if loop_result is not None:
+                        return loop_result
+
                reasoning_prompt = self._i18n.slice("post_tool_reasoning")
                reasoning_message: LLMMessage = {
                    "role": "user",
@@ -809,6 +834,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
        if tool_finish:
            return tool_finish

+        # Check for loop after sequential tool execution
+        loop_result = self._record_and_check_loop(func_name, func_args)
+        if loop_result is not None:
+            return loop_result
+
        reasoning_prompt = self._i18n.slice("post_tool_reasoning")
        reasoning_message = {
            "role": "user",
@@ -949,10 +979,16 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
        track_delegation_if_needed(func_name, args_dict, self.task)

        structured_tool: CrewStructuredTool | None = None
-        for structured in self.tools or []:
-            if sanitize_tool_name(structured.name) == func_name:
-                structured_tool = structured
-                break
+        if original_tool is not None:
+            for structured in self.tools or []:
+                if getattr(structured, "_original_tool", None) is original_tool:
+                    structured_tool = structured
+                    break
+        if structured_tool is None:
+            for structured in self.tools or []:
+                if sanitize_tool_name(structured.name) == func_name:
+                    structured_tool = structured
+                    break

        hook_blocked = False
        before_hook_context = ToolCallHookContext(
@@ -1064,6 +1100,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
            "result": result,
            "from_cache": from_cache,
            "original_tool": original_tool,
+            "tool_args": func_args,
        }

    def _append_tool_result_and_check_finality(
@@ -1242,6 +1279,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                            )
                        }

+                    # Capture tool info before _handle_agent_action may
+                    # convert the answer to AgentFinish (result_as_answer).
+                    _tool_name = formatted_answer.tool
+                    _tool_input = formatted_answer.tool_input
+
                    tool_result = await aexecute_tool_and_check_finality(
                        agent_action=formatted_answer,
                        fingerprint_context=fingerprint_context,
@@ -1259,7 +1301,15 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                        formatted_answer, tool_result
                    )

-                self._invoke_step_callback(formatted_answer)  # type: ignore[arg-type]
+                    # Check for repetitive loop patterns
+                    loop_result = self._record_and_check_loop(
+                        _tool_name, _tool_input
+                    )
+                    if loop_result is not None:
+                        formatted_answer = loop_result
+                        break
+
+                await self._ainvoke_step_callback(formatted_answer)  # type: ignore[arg-type]
                self._append_message(formatted_answer.text)  # type: ignore[union-attr]

            except OutputParserError as e:
@@ -1312,8 +1362,8 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
        if not self.original_tools:
            return await self._ainvoke_loop_native_no_tools()

-        openai_tools, available_functions = convert_tools_to_openai_schema(
-            self.original_tools
+        openai_tools, available_functions, self._tool_name_mapping = (
+            convert_tools_to_openai_schema(self.original_tools)
        )

        while True:
@@ -1374,7 +1424,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                        output=answer,
                        text=answer,
                    )
-                    self._invoke_step_callback(formatted_answer)
+                    await self._ainvoke_step_callback(formatted_answer)
                    self._append_message(answer)  # Save final answer to messages
                    self._show_logs(formatted_answer)
                    return formatted_answer
@@ -1386,7 +1436,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                        output=answer,
                        text=output_json,
                    )
-                    self._invoke_step_callback(formatted_answer)
+                    await self._ainvoke_step_callback(formatted_answer)
                    self._append_message(output_json)
                    self._show_logs(formatted_answer)
                    return formatted_answer
@@ -1397,7 +1447,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                    output=str(answer),
                    text=str(answer),
                )
-                self._invoke_step_callback(formatted_answer)
+                await self._ainvoke_step_callback(formatted_answer)
                self._append_message(str(answer))  # Save final answer to messages
                self._show_logs(formatted_answer)
                return formatted_answer
@@ -1458,6 +1508,94 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
        self._show_logs(formatted_answer)
        return formatted_answer

+    def _record_and_check_loop(
+        self, tool_name: str, tool_args: str | dict[str, Any]
+    ) -> AgentFinish | None:
+        """Record a tool call and check for repetitive loop patterns.
+
+        If a loop is detected, takes the configured action:
+        - ``inject_reflection``: injects a reflection prompt into messages.
+        - ``stop``: forces the agent to produce a final answer.
+        - callable: calls the user's callback and injects the returned message.
+
+        Args:
+            tool_name: Name of the tool that was called.
+            tool_args: Arguments passed to the tool.
+
+        Returns:
+            ``AgentFinish`` if the loop action is ``stop``,
+            ``None`` otherwise (including when reflection is injected).
+        """
+        if not self.loop_detector:
+            return None
+
+        self.loop_detector.record_tool_call(tool_name, tool_args)
+
+        if not self.loop_detector.is_loop_detected():
+            return None
+
+        repeated_tool = self.loop_detector.get_repeated_tool_info() or tool_name
+        action_taken = (
+            self.loop_detector.on_loop
+            if isinstance(self.loop_detector.on_loop, str)
+            else "callback"
+        )
+
+        # Emit loop detected event
+        from crewai.events.types.loop_events import LoopDetectedEvent
+
+        crewai_event_bus.emit(
+            self.agent,
+            LoopDetectedEvent(
+                agent_role=self.agent.role if self.agent else "unknown",
+                agent_id=str(self.agent.id) if self.agent else None,
+                task_id=str(self.task.id) if self.task else None,
+                repeated_tool=repeated_tool,
+                action_taken=action_taken,
+                iteration=self.iterations,
+                agent=self.agent,
+            ),
+        )
+
+        if self.agent and self.agent.verbose:
+            self._printer.print(
+                content=f"Loop detected: {repeated_tool} called repeatedly. Action: {action_taken}",
+                color="bold_yellow",
+            )
+
+        if self.loop_detector.on_loop == "stop":
+            return handle_max_iterations_exceeded(
+                None,
+                printer=self._printer,
+                i18n=self._i18n,
+                messages=self.messages,
+                llm=self.llm,
+                callbacks=self.callbacks,
+                verbose=self.agent.verbose if self.agent else False,
+            )
+
+        # inject_reflection or callable
+        if callable(self.loop_detector.on_loop) and not isinstance(
+            self.loop_detector.on_loop, str
+        ):
+            message_text = self.loop_detector.get_loop_message()
+        else:
+            # Use i18n reflection prompt
+            count = self.loop_detector.repetition_threshold
+            message_text = self._i18n.slice("loop_detected").format(
+                repeated_tool=repeated_tool, count=count
+            )
+
+        loop_message: LLMMessage = {
+            "role": "user",
+            "content": message_text,
+        }
+        self.messages.append(loop_message)
+
+        # Reset detector after intervention to give the agent a fresh window
+        self.loop_detector.reset()
+        return None
+
    def _handle_agent_action(
        self, formatted_answer: AgentAction, tool_result: ToolResult
    ) -> AgentAction | AgentFinish:
@@ -1491,7 +1629,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
    def _invoke_step_callback(
        self, formatted_answer: AgentAction | AgentFinish
    ) -> None:
-        """Invoke step callback.
+        """Invoke step callback (sync context).

        Args:
            formatted_answer: Current agent response.
@@ -1501,6 +1639,19 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
            if inspect.iscoroutine(cb_result):
                asyncio.run(cb_result)

+    async def _ainvoke_step_callback(
+        self, formatted_answer: AgentAction | AgentFinish
+    ) -> None:
+        """Invoke step callback (async context).
+
+        Args:
+            formatted_answer: Current agent response.
+        """
+        if self.step_callback:
+            cb_result = self.step_callback(formatted_answer)
+            if inspect.iscoroutine(cb_result):
+                await cb_result
+
    def _append_message(
        self, text: str, role: Literal["user", "assistant", "system"] = "assistant"
    ) -> None:
--- a/lib/crewai/src/crewai/agents/loop_detector.py
+++ b/lib/crewai/src/crewai/agents/loop_detector.py
@@ -0,0 +1,210 @@
+"""Loop detection for agent execution.
+
+Detects repetitive behavioral patterns in agent tool calls and provides
+configurable intervention strategies to break out of loops.
+
+Example usage:
+
+    from crewai import Agent
+    from crewai.agents.loop_detector import LoopDetector
+
+    # Using default settings (window_size=5, repetition_threshold=3, inject_reflection)
+    agent = Agent(
+        role="Researcher",
+        goal="Find novel insights",
+        backstory="An experienced researcher",
+        loop_detector=LoopDetector(),
+    )
+
+    # Custom configuration
+    agent = Agent(
+        role="Researcher",
+        goal="Find novel insights",
+        backstory="An experienced researcher",
+        loop_detector=LoopDetector(
+            window_size=10,
+            repetition_threshold=4,
+            on_loop="stop",
+        ),
+    )
+
+    # With a custom callback
+    def my_callback(detector: LoopDetector) -> str:
+        return "You are repeating yourself. Try a completely different approach."
+
+    agent = Agent(
+        role="Researcher",
+        goal="Find novel insights",
+        backstory="An experienced researcher",
+        loop_detector=LoopDetector(
+            on_loop=my_callback,
+        ),
+    )
+"""
+
+from __future__ import annotations
+
+from collections import deque
+from collections.abc import Callable
+import json
+import logging
+from typing import Any, Literal
+
+from pydantic import BaseModel, Field
+
+
+logger = logging.getLogger(__name__)
+
+
+class ToolCallRecord(BaseModel):
+    """Record of a single tool call for loop detection."""
+
+    tool_name: str
+    tool_args: str  # Normalized JSON string of arguments
+
+    def __eq__(self, other: object) -> bool:
+        if not isinstance(other, ToolCallRecord):
+            return NotImplemented
+        return self.tool_name == other.tool_name and self.tool_args == other.tool_args
+
+    def __hash__(self) -> int:
+        return hash((self.tool_name, self.tool_args))
+
+
+class LoopDetector(BaseModel):
+    """Detects repetitive behavioral patterns in agent tool calls.
+
+    Monitors a sliding window of recent tool calls and flags when
+    the same tool is called repeatedly with the same arguments,
+    indicating the agent is stuck in a loop.
+
+    Args:
+        window_size: Number of recent tool calls to track in the
+            sliding window. Defaults to 5.
+        repetition_threshold: How many identical tool calls within
+            the window trigger loop detection. Defaults to 3.
+        on_loop: Action to take when a loop is detected.
+            - ``"inject_reflection"`` (default): Inject a meta-prompt
+              asking the agent to try a different approach.
+            - ``"stop"``: Force the agent to produce a final answer.
+            - A callable ``(LoopDetector) -> str``: Custom callback
+              that returns a message to inject into the conversation.
+
+    Example::
+
+        from crewai import Agent
+        from crewai.agents.loop_detector import LoopDetector
+
+        agent = Agent(
+            role="Researcher",
+            goal="Find novel insights about AI",
+            backstory="Senior researcher",
+            loop_detector=LoopDetector(
+                window_size=5,
+                repetition_threshold=3,
+                on_loop="inject_reflection",
+            ),
+        )
+    """
+
+    window_size: int = Field(
+        default=5,
+        ge=2,
+        description="Number of recent tool calls to track in the sliding window.",
+    )
+    repetition_threshold: int = Field(
+        default=3,
+        ge=2,
+        description="How many identical tool calls within the window trigger loop detection.",
+    )
+    on_loop: Literal["inject_reflection", "stop"] | Callable[..., str] = Field(
+        default="inject_reflection",
+        description=(
+            "Action when loop is detected: 'inject_reflection' to inject a reflection prompt, "
+            "'stop' to force final answer, or a callable(LoopDetector) -> str for custom handling."
+        ),
+    )
+    _history: deque[ToolCallRecord] = deque()
+
+    def model_post_init(self, __context: Any) -> None:
+        """Initialize the internal deque with the configured window size."""
+        object.__setattr__(self, "_history", deque(maxlen=self.window_size))
+
+    @staticmethod
+    def _normalize_args(args: str | dict[str, Any]) -> str:
+        """Normalize tool arguments to a canonical JSON string for comparison.
+
+        Args:
+            args: Tool arguments as a string or dict.
+
+        Returns:
+            A normalized JSON string with sorted keys.
+        """
+        if isinstance(args, str):
+            try:
+                parsed = json.loads(args)
+            except (json.JSONDecodeError, TypeError):
+                return args.strip()
+            return json.dumps(parsed, sort_keys=True, default=str)
+        return json.dumps(args, sort_keys=True, default=str)
+
+    def record_tool_call(self, tool_name: str, tool_args: str | dict[str, Any]) -> None:
+        """Record a tool call in the sliding window.
+
+        Args:
+            tool_name: Name of the tool that was called.
+            tool_args: Arguments passed to the tool.
+        """
+        record = ToolCallRecord(
+            tool_name=tool_name,
+            tool_args=self._normalize_args(tool_args),
+        )
+        self._history.append(record)
+
+    def is_loop_detected(self) -> bool:
+        """Check if a repetitive loop pattern is detected.
+
+        Returns:
+            True if any single tool call (same name + same args)
+            appears at least ``repetition_threshold`` times within
+            the current window.
+        """
+        if len(self._history) < self.repetition_threshold:
+            return False
+
+        counts: dict[ToolCallRecord, int] = {}
+        for record in self._history:
+            counts[record] = counts.get(record, 0) + 1
+            if counts[record] >= self.repetition_threshold:
+                return True
+        return False
+
+    def get_loop_message(self) -> str:
+        """Get the intervention message based on the configured ``on_loop`` action.
+
+        Returns:
+            A string message to inject into the agent conversation.
+        """
+        if callable(self.on_loop) and not isinstance(self.on_loop, str):
+            return self.on_loop(self)
+        return ""
+
+    def get_repeated_tool_info(self) -> str | None:
+        """Get information about the repeated tool call, if any.
+
+        Returns:
+            A string describing the repeated tool and args, or None.
+        """
+        if len(self._history) < self.repetition_threshold:
+            return None
+
+        counts: dict[ToolCallRecord, int] = {}
+        for record in self._history:
+            counts[record] = counts.get(record, 0) + 1
+            if counts[record] >= self.repetition_threshold:
+                return f"{record.tool_name}({record.tool_args})"
+        return None
+
+    def reset(self) -> None:
+        """Clear the tool call history."""
+        self._history.clear()
--- a/lib/crewai/src/crewai/cli/plus_api.py
+++ b/lib/crewai/src/crewai/cli/plus_api.py
@@ -22,14 +22,15 @@ class PlusAPI:
    EPHEMERAL_TRACING_RESOURCE = "/crewai_plus/api/v1/tracing/ephemeral"
    INTEGRATIONS_RESOURCE = "/crewai_plus/api/v1/integrations"

-    def __init__(self, api_key: str) -> None:
+    def __init__(self, api_key: str | None = None) -> None:
        self.api_key = api_key
        self.headers = {
-            "Authorization": f"Bearer {api_key}",
            "Content-Type": "application/json",
            "User-Agent": f"CrewAI-CLI/{get_crewai_version()}",
            "X-Crewai-Version": get_crewai_version(),
        }
+        if api_key:
+            self.headers["Authorization"] = f"Bearer {api_key}"
        settings = Settings()
        if settings.org_uuid:
            self.headers["X-Crewai-Organization-Id"] = settings.org_uuid
--- 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]==1.10.0"
+    "crewai[tools]==1.10.1a1"
 ]

 [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]==1.10.0"
+    "crewai[tools]==1.10.1a1"
 ]

 [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]==1.10.0"
+    "crewai[tools]==1.10.1a1"
 ]

 [tool.crewai]
--- a/lib/crewai/src/crewai/events/listeners/tracing/trace_batch_manager.py
+++ b/lib/crewai/src/crewai/events/listeners/tracing/trace_batch_manager.py
@@ -67,7 +67,7 @@ class TraceBatchManager:
                api_key=get_auth_token(),
            )
        except AuthError:
-            self.plus_api = PlusAPI(api_key="")
+            self.plus_api = PlusAPI()
        self.ephemeral_trace_url = None

    def initialize_batch(
--- a/lib/crewai/src/crewai/events/types/loop_events.py
+++ b/lib/crewai/src/crewai/events/types/loop_events.py
@@ -0,0 +1,48 @@
+"""Events related to agent loop detection."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from pydantic import ConfigDict, model_validator
+
+from crewai.events.base_events import BaseEvent
+
+
+class LoopDetectedEvent(BaseEvent):
+    """Event emitted when a repetitive loop pattern is detected in agent behavior.
+
+    Attributes:
+        agent_role: Role of the agent that is looping.
+        repeated_tool: Description of the repeated tool call (name + args).
+        action_taken: The action taken to break the loop.
+        iteration: Current iteration count when the loop was detected.
+    """
+
+    agent_role: str
+    agent_id: str | None = None
+    task_id: str | None = None
+    repeated_tool: str | None = None
+    action_taken: str
+    iteration: int
+    agent: Any | None = None
+    type: str = "loop_detected"
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    @model_validator(mode="after")
+    def set_fingerprint_data(self) -> LoopDetectedEvent:
+        """Set fingerprint data from the agent if available."""
+        if (
+            self.agent
+            and hasattr(self.agent, "fingerprint")
+            and self.agent.fingerprint
+        ):
+            self.source_fingerprint = self.agent.fingerprint.uuid_str
+            self.source_type = "agent"
+            if (
+                hasattr(self.agent.fingerprint, "metadata")
+                and self.agent.fingerprint.metadata
+            ):
+                self.fingerprint_metadata = self.agent.fingerprint.metadata
+        return self
--- a/lib/crewai/src/crewai/experimental/agent_executor.py
+++ b/lib/crewai/src/crewai/experimental/agent_executor.py
@@ -52,6 +52,8 @@ from crewai.hooks.types import (
    BeforeLLMCallHookCallable,
    BeforeLLMCallHookType,
 )
+from crewai.tools.base_tool import BaseTool
+from crewai.tools.structured_tool import CrewStructuredTool
 from crewai.utilities.agent_utils import (
    convert_tools_to_openai_schema,
    enforce_rpm_limit,
@@ -85,8 +87,6 @@ if TYPE_CHECKING:
    from crewai.crew import Crew
    from crewai.llms.base_llm import BaseLLM
    from crewai.task import Task
-    from crewai.tools.base_tool import BaseTool
-    from crewai.tools.structured_tool import CrewStructuredTool
    from crewai.tools.tool_types import ToolResult
    from crewai.utilities.prompts import StandardPromptResult, SystemPromptResult

@@ -321,7 +321,7 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
    def _setup_native_tools(self) -> None:
        """Convert tools to OpenAI schema format for native function calling."""
        if self.original_tools:
-            self._openai_tools, self._available_functions = (
+            self._openai_tools, self._available_functions, self._tool_name_mapping = (
                convert_tools_to_openai_schema(self.original_tools)
            )

@@ -594,21 +594,19 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
    def execute_tool_action(self) -> Literal["tool_completed", "tool_result_is_final"]:
        """Execute the tool action and handle the result."""

+        action = cast(AgentAction, self.state.current_answer)
+
+        fingerprint_context = {}
+        if (
+            self.agent
+            and hasattr(self.agent, "security_config")
+            and hasattr(self.agent.security_config, "fingerprint")
+        ):
+            fingerprint_context = {
+                "agent_fingerprint": str(self.agent.security_config.fingerprint)
+            }
+
        try:
-            action = cast(AgentAction, self.state.current_answer)
-
-            # Extract fingerprint context for tool execution
-            fingerprint_context = {}
-            if (
-                self.agent
-                and hasattr(self.agent, "security_config")
-                and hasattr(self.agent.security_config, "fingerprint")
-            ):
-                fingerprint_context = {
-                    "agent_fingerprint": str(self.agent.security_config.fingerprint)
-                }
-
-            # Execute the tool
            tool_result = execute_tool_and_check_finality(
                agent_action=action,
                fingerprint_context=fingerprint_context,
@@ -622,24 +620,19 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
                function_calling_llm=self.function_calling_llm,
                crew=self.crew,
            )
+        except Exception as e:
+            if self.agent and self.agent.verbose:
+                self._printer.print(
+                    content=f"Error in tool execution: {e}", color="red"
+                )
+            if self.task:
+                self.task.increment_tools_errors()

-            # Handle agent action and append observation to messages
-            result = self._handle_agent_action(action, tool_result)
-            self.state.current_answer = result
+            error_observation = f"\nObservation: Error executing tool: {e}"
+            action.text += error_observation
+            action.result = str(e)
+            self._append_message_to_state(action.text)

-            # Invoke step callback if configured
-            self._invoke_step_callback(result)
-
-            # Append result message to conversation state
-            if hasattr(result, "text"):
-                self._append_message_to_state(result.text)
-
-            # Check if tool result became a final answer (result_as_answer flag)
-            if isinstance(result, AgentFinish):
-                self.state.is_finished = True
-                return "tool_result_is_final"
-
-            # Inject post-tool reasoning prompt to enforce analysis
            reasoning_prompt = self._i18n.slice("post_tool_reasoning")
            reasoning_message: LLMMessage = {
                "role": "user",
@@ -649,12 +642,26 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):

            return "tool_completed"

-        except Exception as e:
-            error_text = Text()
-            error_text.append("❌ Error in tool execution: ", style="red bold")
-            error_text.append(str(e), style="red")
-            self._console.print(error_text)
-            raise
+        result = self._handle_agent_action(action, tool_result)
+        self.state.current_answer = result
+
+        self._invoke_step_callback(result)
+
+        if hasattr(result, "text"):
+            self._append_message_to_state(result.text)
+
+        if isinstance(result, AgentFinish):
+            self.state.is_finished = True
+            return "tool_result_is_final"
+
+        reasoning_prompt = self._i18n.slice("post_tool_reasoning")
+        reasoning_message: LLMMessage = {
+            "role": "user",
+            "content": reasoning_prompt,
+        }
+        self.state.messages.append(reasoning_message)
+
+        return "tool_completed"

    @listen("native_tool_calls")
    def execute_native_tool(
@@ -728,7 +735,20 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
                )
                for future in as_completed(future_to_idx):
                    idx = future_to_idx[future]
-                    ordered_results[idx] = future.result()
+                    try:
+                        ordered_results[idx] = future.result()
+                    except Exception as e:
+                        tool_call = runnable_tool_calls[idx]
+                        info = extract_tool_call_info(tool_call)
+                        call_id = info[0] if info else "unknown"
+                        func_name = info[1] if info else "unknown"
+                        ordered_results[idx] = {
+                            "call_id": call_id,
+                            "func_name": func_name,
+                            "result": f"Error executing tool: {e}",
+                            "from_cache": False,
+                            "original_tool": None,
+                        }
                execution_results = [
                    result for result in ordered_results if result is not None
                ]
@@ -824,11 +844,17 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
                continue
            _, func_name, _ = info

-            original_tool = None
-            for tool in self.original_tools or []:
-                if sanitize_tool_name(tool.name) == func_name:
-                    original_tool = tool
-                    break
+            mapping = getattr(self, "_tool_name_mapping", None)
+            original_tool: BaseTool | None = None
+            if mapping and func_name in mapping:
+                mapped = mapping[func_name]
+                if isinstance(mapped, BaseTool):
+                    original_tool = mapped
+            if original_tool is None:
+                for tool in self.original_tools or []:
+                    if sanitize_tool_name(tool.name) == func_name:
+                        original_tool = tool
+                        break

            if not original_tool:
                continue
@@ -844,7 +870,18 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
        """Execute a single native tool call and return metadata/result."""
        info = extract_tool_call_info(tool_call)
        if not info:
-            raise ValueError("Invalid native tool call format")
+            call_id = (
+                getattr(tool_call, "id", None)
+                or (tool_call.get("id") if isinstance(tool_call, dict) else None)
+                or "unknown"
+            )
+            return {
+                "call_id": call_id,
+                "func_name": "unknown",
+                "result": "Error: Invalid native tool call format",
+                "from_cache": False,
+                "original_tool": None,
+            }

        call_id, func_name, func_args = info

@@ -856,12 +893,17 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
        # Get agent_key for event tracking
        agent_key = getattr(self.agent, "key", "unknown") if self.agent else "unknown"

-        # Find original tool by matching sanitized name (needed for cache_function and result_as_answer)
-        original_tool = None
-        for tool in self.original_tools or []:
-            if sanitize_tool_name(tool.name) == func_name:
-                original_tool = tool
-                break
+        original_tool: BaseTool | None = None
+        mapping = getattr(self, "_tool_name_mapping", None)
+        if mapping and func_name in mapping:
+            mapped = mapping[func_name]
+            if isinstance(mapped, BaseTool):
+                original_tool = mapped
+        if original_tool is None:
+            for tool in self.original_tools or []:
+                if sanitize_tool_name(tool.name) == func_name:
+                    original_tool = tool
+                    break

        # Check if tool has reached max usage count
        max_usage_reached = False
@@ -904,10 +946,16 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
        track_delegation_if_needed(func_name, args_dict, self.task)

        structured_tool: CrewStructuredTool | None = None
-        for structured in self.tools or []:
-            if sanitize_tool_name(structured.name) == func_name:
-                structured_tool = structured
-                break
+        if original_tool is not None:
+            for structured in self.tools or []:
+                if getattr(structured, "_original_tool", None) is original_tool:
+                    structured_tool = structured
+                    break
+        if structured_tool is None:
+            for structured in self.tools or []:
+                if sanitize_tool_name(structured.name) == func_name:
+                    structured_tool = structured
+                    break

        hook_blocked = False
        before_hook_context = ToolCallHookContext(
--- a/lib/crewai/src/crewai/flow/flow.py
+++ b/lib/crewai/src/crewai/flow/flow.py
@@ -16,7 +16,7 @@ from collections.abc import (
    Sequence,
    ValuesView,
 )
-from concurrent.futures import Future
+from concurrent.futures import Future, ThreadPoolExecutor
 import copy
 import enum
 import inspect
@@ -1739,7 +1739,12 @@ class Flow(Generic[T], metaclass=FlowMeta):
        async def _run_flow() -> Any:
            return await self.kickoff_async(inputs, input_files)

-        return asyncio.run(_run_flow())
+        try:
+            asyncio.get_running_loop()
+            with ThreadPoolExecutor(max_workers=1) as pool:
+                return pool.submit(asyncio.run, _run_flow()).result()
+        except RuntimeError:
+            return asyncio.run(_run_flow())

    async def kickoff_async(
        self,
--- a/lib/crewai/src/crewai/memory/init.py
+++ b/lib/crewai/src/crewai/memory/init.py
@@ -1,6 +1,14 @@
-"""Memory module: unified Memory with LLM analysis and pluggable storage."""
+"""Memory module: unified Memory with LLM analysis and pluggable storage.
+
+Heavy dependencies are lazily imported so that
+``import crewai`` does not initialise at runtime — critical for
+Celery pre-fork and similar deployment patterns.
+"""
+
+from __future__ import annotations
+
+from typing import Any

-from crewai.memory.encoding_flow import EncodingFlow
 from crewai.memory.memory_scope import MemoryScope, MemorySlice
 from crewai.memory.types import (
    MemoryMatch,
@@ -10,7 +18,24 @@ from crewai.memory.types import (
    embed_text,
    embed_texts,
 )
-from crewai.memory.unified_memory import Memory
+
+_LAZY_IMPORTS: dict[str, tuple[str, str]] = {
+    "Memory": ("crewai.memory.unified_memory", "Memory"),
+    "EncodingFlow": ("crewai.memory.encoding_flow", "EncodingFlow"),
+}
+
+
+def __getattr__(name: str) -> Any:
+    """Lazily import Memory / EncodingFlow to avoid pulling in lancedb at import time."""
+    if name in _LAZY_IMPORTS:
+        import importlib
+
+        module_path, attr = _LAZY_IMPORTS[name]
+        mod = importlib.import_module(module_path)
+        val = getattr(mod, attr)
+        globals()[name] = val
+        return val
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")


 __all__ = [
--- a/lib/crewai/src/crewai/memory/unified_memory.py
+++ b/lib/crewai/src/crewai/memory/unified_memory.py
@@ -21,7 +21,6 @@ from crewai.llms.base_llm import BaseLLM
 from crewai.memory.analyze import extract_memories_from_content
 from crewai.memory.recall_flow import RecallFlow
 from crewai.memory.storage.backend import StorageBackend
-from crewai.memory.storage.lancedb_storage import LanceDBStorage
 from crewai.memory.types import (
    MemoryConfig,
    MemoryMatch,
@@ -148,12 +147,10 @@ class Memory:
            else None
        )

-        # Storage is initialized eagerly (local, no API key needed).
-        self._storage: StorageBackend
-        if storage == "lancedb":
-            self._storage = LanceDBStorage()
-        elif isinstance(storage, str):
-            self._storage = LanceDBStorage(path=storage)
+        if isinstance(storage, str):
+            from crewai.memory.storage.lancedb_storage import LanceDBStorage
+
+            self._storage = LanceDBStorage() if storage == "lancedb" else LanceDBStorage(path=storage)
        else:
            self._storage = storage

--- a/lib/crewai/src/crewai/telemetry/telemetry.py
+++ b/lib/crewai/src/crewai/telemetry/telemetry.py
@@ -173,6 +173,12 @@ class Telemetry:

        self._original_handlers: dict[int, Any] = {}

+        if threading.current_thread() is not threading.main_thread():
+            logger.debug(
+                "Skipping signal handler registration: not running in main thread"
+            )
+            return
+
        self._register_signal_handler(signal.SIGTERM, SigTermEvent, shutdown=True)
        self._register_signal_handler(signal.SIGINT, SigIntEvent, shutdown=True)
        if hasattr(signal, "SIGHUP"):
--- a/lib/crewai/src/crewai/tools/base_tool.py
+++ b/lib/crewai/src/crewai/tools/base_tool.py
@@ -23,7 +23,7 @@ from pydantic import (
 )
 from typing_extensions import TypeIs

-from crewai.tools.structured_tool import CrewStructuredTool
+from crewai.tools.structured_tool import CrewStructuredTool, build_schema_hint
 from crewai.utilities.printer import Printer
 from crewai.utilities.pydantic_schema_utils import generate_model_description
 from crewai.utilities.string_utils import sanitize_tool_name
@@ -167,8 +167,9 @@ class BaseTool(BaseModel, ABC):
                validated = self.args_schema.model_validate(kwargs)
                return validated.model_dump()
            except Exception as e:
+                hint = build_schema_hint(self.args_schema)
                raise ValueError(
-                    f"Tool '{self.name}' arguments validation failed: {e}"
+                    f"Tool '{self.name}' arguments validation failed: {e}{hint}"
                ) from e
        return kwargs

--- a/lib/crewai/src/crewai/tools/structured_tool.py
+++ b/lib/crewai/src/crewai/tools/structured_tool.py
@@ -17,6 +17,27 @@ if TYPE_CHECKING:
    from crewai.tools.base_tool import BaseTool


+def build_schema_hint(args_schema: type[BaseModel]) -> str:
+    """Build a human-readable hint from a Pydantic model's JSON schema.
+
+    Args:
+        args_schema: The Pydantic model class to extract schema from.
+
+    Returns:
+        A formatted string with expected arguments and required fields,
+        or empty string if schema extraction fails.
+    """
+    try:
+        schema = args_schema.model_json_schema()
+        return (
+            f"\nExpected arguments: "
+            f"{json.dumps(schema.get('properties', {}))}"
+            f"\nRequired: {json.dumps(schema.get('required', []))}"
+        )
+    except Exception:
+        return ""
+
+
 class ToolUsageLimitExceededError(Exception):
    """Exception raised when a tool has reached its maximum usage limit."""

@@ -208,7 +229,8 @@ class CrewStructuredTool:
            validated_args = self.args_schema.model_validate(raw_args)
            return validated_args.model_dump()
        except Exception as e:
-            raise ValueError(f"Arguments validation failed: {e}") from e
+            hint = build_schema_hint(self.args_schema)
+            raise ValueError(f"Arguments validation failed: {e}{hint}") from e

    async def ainvoke(
        self,
--- a/lib/crewai/src/crewai/translations/en.json
+++ b/lib/crewai/src/crewai/translations/en.json
@@ -15,6 +15,7 @@
    "native_tools": "",
    "native_task": "\nCurrent Task: {input}",
    "post_tool_reasoning": "Analyze the tool result. If requirements are met, provide the Final Answer. Otherwise, call the next tool. Deliver only the answer without meta-commentary.",
+    "loop_detected": "WARNING: You appear to be repeating the same action ({repeated_tool}). You have called it {count} times with the same arguments. This is not making progress. You MUST try a completely different approach — use a different tool, different arguments, or provide your Final Answer now.",
    "format": "Decide if you need a tool or can provide the final answer. Use one at a time.\nTo use a tool, use:\nThought: [reasoning]\nAction: [name from {tool_names}]\nAction Input: [JSON object]\n\nTo provide the final answer, use:\nThought: [reasoning]\nFinal Answer: [complete response]",
    "final_answer_format": "If you don't need to use any more tools, you must give your best complete final answer, make sure it satisfies the expected criteria, use the EXACT format below:\n\n```\nThought: I now can give a great answer\nFinal Answer: my best complete final answer to the task.\n\n```",
    "format_without_tools": "\nSorry, I didn't use the right format. I MUST either use a tool (among the available ones), OR give my best final answer.\nHere is the expected format I must follow:\n\n```\nQuestion: the input question you must answer\nThought: you should always think about what to do\nAction: the action to take, should be one of [{tool_names}]\nAction Input: the input to the action\nObservation: the result of the action\n```\n This Thought/Action/Action Input/Result process can repeat N times. Once I know the final answer, I must return the following format:\n\n```\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described\n\n```",
--- a/lib/crewai/src/crewai/utilities/agent_utils.py
+++ b/lib/crewai/src/crewai/utilities/agent_utils.py
@@ -139,7 +139,11 @@ def render_text_description_and_args(

 def convert_tools_to_openai_schema(
    tools: Sequence[BaseTool | CrewStructuredTool],
-) -> tuple[list[dict[str, Any]], dict[str, Callable[..., Any]]]:
+) -> tuple[
+    list[dict[str, Any]],
+    dict[str, Callable[..., Any]],
+    dict[str, BaseTool | CrewStructuredTool],
+]:
    """Convert CrewAI tools to OpenAI function calling format.

    This function converts CrewAI BaseTool and CrewStructuredTool objects
@@ -152,16 +156,12 @@ def convert_tools_to_openai_schema(
    Returns:
        Tuple containing:
        - List of OpenAI-format tool schema dictionaries
-        - Dict mapping tool names to their callable run() methods
-
-    Example:
-        >>> tools = [CalculatorTool(), SearchTool()]
-        >>> schemas, functions = convert_tools_to_openai_schema(tools)
-        >>> # schemas can be passed to llm.call(tools=schemas)
-        >>> # functions can be passed to llm.call(available_functions=functions)
+        - Dict mapping sanitized tool names to their callable run() methods
+        - Dict mapping sanitized tool names to their original tool objects
    """
    openai_tools: list[dict[str, Any]] = []
    available_functions: dict[str, Callable[..., Any]] = {}
+    tool_name_mapping: dict[str, BaseTool | CrewStructuredTool] = {}

    for tool in tools:
        # Get the JSON schema for tool parameters
@@ -186,6 +186,14 @@ def convert_tools_to_openai_schema(

        sanitized_name = sanitize_tool_name(tool.name)

+        if sanitized_name in available_functions:
+            counter = 2
+            candidate = sanitize_tool_name(f"{sanitized_name}_{counter}")
+            while candidate in available_functions:
+                counter += 1
+                candidate = sanitize_tool_name(f"{sanitized_name}_{counter}")
+            sanitized_name = candidate
+
        schema: dict[str, Any] = {
            "type": "function",
            "function": {
@@ -197,8 +205,9 @@ def convert_tools_to_openai_schema(
        }
        openai_tools.append(schema)
        available_functions[sanitized_name] = tool.run  # type: ignore[union-attr]
+        tool_name_mapping[sanitized_name] = tool

-    return openai_tools, available_functions
+    return openai_tools, available_functions, tool_name_mapping


 def has_reached_max_iterations(iterations: int, max_iterations: int) -> bool:
--- a/lib/crewai/src/crewai/utilities/string_utils.py
+++ b/lib/crewai/src/crewai/utilities/string_utils.py
@@ -2,6 +2,7 @@
 # https://github.com/un33k/python-slugify
 # MIT License

+import hashlib
 import re
 from typing import Any, Final
 import unicodedata
@@ -40,7 +41,9 @@ def sanitize_tool_name(name: str, max_length: int = _MAX_TOOL_NAME_LENGTH) -> st
    name = name.strip("_")

    if len(name) > max_length:
-        name = name[:max_length].rstrip("_")
+        name_hash = hashlib.sha256(name.encode()).hexdigest()[:8]
+        suffix = f"_{name_hash}"
+        name = name[: max_length - len(suffix)].rstrip("_") + suffix

    return name

--- a/lib/crewai/tests/agents/test_loop_detector.py
+++ b/lib/crewai/tests/agents/test_loop_detector.py
@@ -0,0 +1,523 @@
+"""Unit tests for LoopDetector and loop detection integration.
+
+Tests cover:
+- LoopDetector class: tracking, detection, message generation, configuration
+- ToolCallRecord equality and hashing
+- Edge cases: empty history, threshold boundaries, window overflow
+- Integration with CrewAgentExecutor._record_and_check_loop
+- LoopDetectedEvent creation
+"""
+
+from __future__ import annotations
+
+from unittest.mock import MagicMock, Mock, patch
+
+import pytest
+
+from crewai.agents.loop_detector import LoopDetector, ToolCallRecord
+from crewai.events.types.loop_events import LoopDetectedEvent
+
+
+# ---------------------------------------------------------------------------
+# ToolCallRecord
+# ---------------------------------------------------------------------------
+
+class TestToolCallRecord:
+    """Tests for ToolCallRecord model."""
+
+    def test_equality_same_name_and_args(self):
+        a = ToolCallRecord(tool_name="search", tool_args='{"q": "hello"}')
+        b = ToolCallRecord(tool_name="search", tool_args='{"q": "hello"}')
+        assert a == b
+
+    def test_inequality_different_name(self):
+        a = ToolCallRecord(tool_name="search", tool_args='{"q": "hello"}')
+        b = ToolCallRecord(tool_name="fetch", tool_args='{"q": "hello"}')
+        assert a != b
+
+    def test_inequality_different_args(self):
+        a = ToolCallRecord(tool_name="search", tool_args='{"q": "hello"}')
+        b = ToolCallRecord(tool_name="search", tool_args='{"q": "world"}')
+        assert a != b
+
+    def test_hash_same_records(self):
+        a = ToolCallRecord(tool_name="search", tool_args='{"q": "hello"}')
+        b = ToolCallRecord(tool_name="search", tool_args='{"q": "hello"}')
+        assert hash(a) == hash(b)
+
+    def test_hash_different_records(self):
+        a = ToolCallRecord(tool_name="search", tool_args='{"q": "hello"}')
+        b = ToolCallRecord(tool_name="search", tool_args='{"q": "world"}')
+        # Different records should (almost certainly) have different hashes
+        assert hash(a) != hash(b)
+
+    def test_equality_not_implemented_for_other_types(self):
+        a = ToolCallRecord(tool_name="search", tool_args="{}")
+        assert a != "not a record"
+        assert a.__eq__("not a record") is NotImplemented
+
+
+# ---------------------------------------------------------------------------
+# LoopDetector — Initialization
+# ---------------------------------------------------------------------------
+
+class TestLoopDetectorInit:
+    """Tests for LoopDetector initialization and defaults."""
+
+    def test_default_values(self):
+        ld = LoopDetector()
+        assert ld.window_size == 5
+        assert ld.repetition_threshold == 3
+        assert ld.on_loop == "inject_reflection"
+
+    def test_custom_values(self):
+        ld = LoopDetector(window_size=10, repetition_threshold=4, on_loop="stop")
+        assert ld.window_size == 10
+        assert ld.repetition_threshold == 4
+        assert ld.on_loop == "stop"
+
+    def test_callable_on_loop(self):
+        def my_cb(detector: LoopDetector) -> str:
+            return "custom"
+
+        ld = LoopDetector(on_loop=my_cb)
+        assert callable(ld.on_loop)
+
+    def test_window_size_minimum(self):
+        with pytest.raises(Exception):
+            LoopDetector(window_size=1)
+
+    def test_repetition_threshold_minimum(self):
+        with pytest.raises(Exception):
+            LoopDetector(repetition_threshold=1)
+
+
+# ---------------------------------------------------------------------------
+# LoopDetector — Argument Normalization
+# ---------------------------------------------------------------------------
+
+class TestNormalizeArgs:
+    """Tests for LoopDetector._normalize_args static method."""
+
+    def test_dict_sorted_keys(self):
+        result = LoopDetector._normalize_args({"b": 2, "a": 1})
+        assert result == '{"a": 1, "b": 2}'
+
+    def test_json_string_normalized(self):
+        result = LoopDetector._normalize_args('{"b": 2, "a": 1}')
+        assert result == '{"a": 1, "b": 2}'
+
+    def test_plain_string_stripped(self):
+        result = LoopDetector._normalize_args("  hello world  ")
+        assert result == "hello world"
+
+    def test_invalid_json_string(self):
+        result = LoopDetector._normalize_args("not json")
+        assert result == "not json"
+
+    def test_empty_dict(self):
+        result = LoopDetector._normalize_args({})
+        assert result == "{}"
+
+    def test_empty_string(self):
+        result = LoopDetector._normalize_args("")
+        assert result == ""
+
+
+# ---------------------------------------------------------------------------
+# LoopDetector — Recording and Detection
+# ---------------------------------------------------------------------------
+
+class TestLoopDetection:
+    """Tests for loop recording and detection logic."""
+
+    def test_no_loop_below_threshold(self):
+        ld = LoopDetector(repetition_threshold=3)
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("search", {"q": "test"})
+        assert ld.is_loop_detected() is False
+
+    def test_loop_at_threshold(self):
+        ld = LoopDetector(repetition_threshold=3)
+        for _ in range(3):
+            ld.record_tool_call("search", {"q": "test"})
+        assert ld.is_loop_detected() is True
+
+    def test_loop_above_threshold(self):
+        ld = LoopDetector(repetition_threshold=3)
+        for _ in range(5):
+            ld.record_tool_call("search", {"q": "test"})
+        assert ld.is_loop_detected() is True
+
+    def test_no_loop_with_different_tools(self):
+        ld = LoopDetector(repetition_threshold=3)
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("fetch", {"url": "http://example.com"})
+        ld.record_tool_call("read", {"file": "data.txt"})
+        assert ld.is_loop_detected() is False
+
+    def test_no_loop_with_different_args(self):
+        ld = LoopDetector(repetition_threshold=3)
+        ld.record_tool_call("search", {"q": "test1"})
+        ld.record_tool_call("search", {"q": "test2"})
+        ld.record_tool_call("search", {"q": "test3"})
+        assert ld.is_loop_detected() is False
+
+    def test_loop_with_mixed_calls(self):
+        """Loop detected even if other calls are interspersed, as long as
+        threshold is met within the window."""
+        ld = LoopDetector(window_size=5, repetition_threshold=3)
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("fetch", {"url": "http://example.com"})
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("search", {"q": "test"})
+        assert ld.is_loop_detected() is True
+
+    def test_window_overflow_removes_old_calls(self):
+        """Old calls slide out of the window, potentially clearing the loop."""
+        ld = LoopDetector(window_size=3, repetition_threshold=3)
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("search", {"q": "test"})
+        # Now add a different call — this pushes first "search" out when we add
+        # one more different call
+        ld.record_tool_call("fetch", {"url": "http://example.com"})
+        # Only 2 "search" in window at this point, not 3
+        assert ld.is_loop_detected() is False
+
+    def test_loop_with_string_args(self):
+        ld = LoopDetector(repetition_threshold=3)
+        for _ in range(3):
+            ld.record_tool_call("search", '{"q": "test"}')
+        assert ld.is_loop_detected() is True
+
+    def test_loop_with_equivalent_json_args(self):
+        """Args with different key order should be normalized and treated as equal."""
+        ld = LoopDetector(repetition_threshold=3)
+        ld.record_tool_call("search", '{"b": 2, "a": 1}')
+        ld.record_tool_call("search", '{"a": 1, "b": 2}')
+        ld.record_tool_call("search", {"a": 1, "b": 2})
+        assert ld.is_loop_detected() is True
+
+    def test_empty_history(self):
+        ld = LoopDetector()
+        assert ld.is_loop_detected() is False
+
+    def test_single_call(self):
+        ld = LoopDetector()
+        ld.record_tool_call("search", {"q": "test"})
+        assert ld.is_loop_detected() is False
+
+
+# ---------------------------------------------------------------------------
+# LoopDetector — Reset
+# ---------------------------------------------------------------------------
+
+class TestLoopDetectorReset:
+    """Tests for LoopDetector.reset()."""
+
+    def test_reset_clears_history(self):
+        ld = LoopDetector(repetition_threshold=3)
+        for _ in range(3):
+            ld.record_tool_call("search", {"q": "test"})
+        assert ld.is_loop_detected() is True
+        ld.reset()
+        assert ld.is_loop_detected() is False
+
+    def test_reset_allows_fresh_tracking(self):
+        ld = LoopDetector(repetition_threshold=3)
+        for _ in range(3):
+            ld.record_tool_call("search", {"q": "test"})
+        ld.reset()
+        # Now record again — should not trigger until threshold
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("search", {"q": "test"})
+        assert ld.is_loop_detected() is False
+
+
+# ---------------------------------------------------------------------------
+# LoopDetector — Messages and Tool Info
+# ---------------------------------------------------------------------------
+
+class TestLoopDetectorMessages:
+    """Tests for get_loop_message and get_repeated_tool_info."""
+
+    def test_get_loop_message_with_callable(self):
+        def my_callback(detector: LoopDetector) -> str:
+            return "Custom loop message"
+
+        ld = LoopDetector(on_loop=my_callback)
+        assert ld.get_loop_message() == "Custom loop message"
+
+    def test_get_loop_message_inject_reflection_returns_empty(self):
+        ld = LoopDetector(on_loop="inject_reflection")
+        assert ld.get_loop_message() == ""
+
+    def test_get_loop_message_stop_returns_empty(self):
+        ld = LoopDetector(on_loop="stop")
+        assert ld.get_loop_message() == ""
+
+    def test_get_repeated_tool_info_with_loop(self):
+        ld = LoopDetector(repetition_threshold=3)
+        for _ in range(3):
+            ld.record_tool_call("search", {"q": "test"})
+        info = ld.get_repeated_tool_info()
+        assert info is not None
+        assert "search" in info
+
+    def test_get_repeated_tool_info_no_loop(self):
+        ld = LoopDetector(repetition_threshold=3)
+        ld.record_tool_call("search", {"q": "test"})
+        assert ld.get_repeated_tool_info() is None
+
+    def test_get_repeated_tool_info_empty_history(self):
+        ld = LoopDetector()
+        assert ld.get_repeated_tool_info() is None
+
+    def test_callback_receives_detector_instance(self):
+        received = {}
+
+        def my_callback(detector: LoopDetector) -> str:
+            received["detector"] = detector
+            return "msg"
+
+        ld = LoopDetector(on_loop=my_callback)
+        ld.get_loop_message()
+        assert received["detector"] is ld
+
+
+# ---------------------------------------------------------------------------
+# LoopDetectedEvent
+# ---------------------------------------------------------------------------
+
+class TestLoopDetectedEvent:
+    """Tests for the LoopDetectedEvent model."""
+
+    def test_event_creation(self):
+        event = LoopDetectedEvent(
+            agent_role="Researcher",
+            agent_id="agent-1",
+            task_id="task-1",
+            repeated_tool="search({\"q\": \"test\"})",
+            action_taken="inject_reflection",
+            iteration=5,
+        )
+        assert event.agent_role == "Researcher"
+        assert event.repeated_tool == 'search({"q": "test"})'
+        assert event.action_taken == "inject_reflection"
+        assert event.iteration == 5
+        assert event.type == "loop_detected"
+
+    def test_event_with_agent_fingerprint(self):
+        mock_agent = MagicMock()
+        mock_agent.fingerprint.uuid_str = "fp-123"
+        mock_agent.fingerprint.metadata = {"key": "value"}
+
+        event = LoopDetectedEvent(
+            agent_role="Researcher",
+            action_taken="stop",
+            iteration=3,
+            agent=mock_agent,
+        )
+        assert event.source_fingerprint == "fp-123"
+        assert event.fingerprint_metadata == {"key": "value"}
+
+    def test_event_without_agent(self):
+        event = LoopDetectedEvent(
+            agent_role="Researcher",
+            action_taken="inject_reflection",
+            iteration=1,
+        )
+        assert event.agent is None
+        assert event.agent_id is None
+
+
+# ---------------------------------------------------------------------------
+# Integration: CrewAgentExecutor._record_and_check_loop
+# ---------------------------------------------------------------------------
+
+class TestRecordAndCheckLoop:
+    """Tests for the _record_and_check_loop helper on CrewAgentExecutor."""
+
+    @pytest.fixture
+    def _make_executor(self):
+        """Factory that builds a minimal CrewAgentExecutor-like object.
+
+        We import the real class and patch its __init__ so we can
+        test _record_and_check_loop without setting up the full executor.
+        """
+        from crewai.agents.crew_agent_executor import CrewAgentExecutor
+
+        def _factory(
+            loop_detector: LoopDetector | None = None,
+            verbose: bool = False,
+        ) -> CrewAgentExecutor:
+            executor = object.__new__(CrewAgentExecutor)
+            # Minimal attributes required by _record_and_check_loop
+            executor.loop_detector = loop_detector
+
+            mock_agent = Mock()
+            mock_agent.role = "Test Agent"
+            mock_agent.id = "agent-1"
+            mock_agent.verbose = verbose
+            executor.agent = mock_agent
+
+            mock_task = Mock()
+            mock_task.id = "task-1"
+            executor.task = mock_task
+
+            executor.iterations = 0
+            executor.messages = []
+
+            mock_printer = Mock()
+            executor._printer = mock_printer
+
+            mock_i18n = Mock()
+            mock_i18n.slice.return_value = (
+                "WARNING: You appear to be repeating the same action ({repeated_tool}). "
+                "You have called it {count} times."
+            )
+            executor._i18n = mock_i18n
+
+            mock_llm = Mock()
+            executor.llm = mock_llm
+            executor.callbacks = []
+
+            return executor
+
+        return _factory
+
+    def test_no_loop_detector_returns_none(self, _make_executor):
+        executor = _make_executor(loop_detector=None)
+        result = executor._record_and_check_loop("search", {"q": "test"})
+        assert result is None
+
+    def test_no_loop_detected_returns_none(self, _make_executor):
+        ld = LoopDetector(repetition_threshold=3)
+        executor = _make_executor(loop_detector=ld)
+        # Only 1 call — no loop
+        result = executor._record_and_check_loop("search", {"q": "test"})
+        assert result is None
+
+    @patch("crewai.agents.crew_agent_executor.crewai_event_bus")
+    def test_inject_reflection_appends_message(self, mock_bus, _make_executor):
+        ld = LoopDetector(repetition_threshold=3, on_loop="inject_reflection")
+        executor = _make_executor(loop_detector=ld)
+
+        # Record 2 calls before the 3rd (which triggers detection)
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("search", {"q": "test"})
+
+        result = executor._record_and_check_loop("search", {"q": "test"})
+
+        assert result is None  # inject_reflection does NOT stop
+        assert len(executor.messages) == 1
+        assert "repeating" in executor.messages[0]["content"].lower()
+        # Event should have been emitted
+        mock_bus.emit.assert_called_once()
+
+    @patch("crewai.agents.crew_agent_executor.crewai_event_bus")
+    @patch("crewai.agents.crew_agent_executor.handle_max_iterations_exceeded")
+    def test_stop_returns_agent_finish(
+        self, mock_handle_max, mock_bus, _make_executor
+    ):
+        from crewai.agents.parser import AgentFinish
+
+        mock_handle_max.return_value = AgentFinish(
+            thought="forced", output="Stopped", text="Stopped"
+        )
+
+        ld = LoopDetector(repetition_threshold=3, on_loop="stop")
+        executor = _make_executor(loop_detector=ld)
+
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("search", {"q": "test"})
+
+        result = executor._record_and_check_loop("search", {"q": "test"})
+
+        assert result is not None
+        assert isinstance(result, AgentFinish)
+        mock_handle_max.assert_called_once()
+        mock_bus.emit.assert_called_once()
+
+    @patch("crewai.agents.crew_agent_executor.crewai_event_bus")
+    def test_callable_on_loop_injects_callback_message(
+        self, mock_bus, _make_executor
+    ):
+        def custom_callback(detector: LoopDetector) -> str:
+            return "CUSTOM: Stop repeating yourself!"
+
+        ld = LoopDetector(repetition_threshold=3, on_loop=custom_callback)
+        executor = _make_executor(loop_detector=ld)
+
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("search", {"q": "test"})
+
+        result = executor._record_and_check_loop("search", {"q": "test"})
+
+        assert result is None
+        assert len(executor.messages) == 1
+        assert "CUSTOM: Stop repeating yourself!" in executor.messages[0]["content"]
+
+    @patch("crewai.agents.crew_agent_executor.crewai_event_bus")
+    def test_detection_resets_after_intervention(self, mock_bus, _make_executor):
+        ld = LoopDetector(repetition_threshold=3, on_loop="inject_reflection")
+        executor = _make_executor(loop_detector=ld)
+
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("search", {"q": "test"})
+
+        # 3rd call triggers loop
+        executor._record_and_check_loop("search", {"q": "test"})
+
+        # After intervention, detector should be reset
+        assert ld.is_loop_detected() is False
+
+    @patch("crewai.agents.crew_agent_executor.crewai_event_bus")
+    def test_verbose_prints_message(self, mock_bus, _make_executor):
+        ld = LoopDetector(repetition_threshold=3, on_loop="inject_reflection")
+        executor = _make_executor(loop_detector=ld, verbose=True)
+
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("search", {"q": "test"})
+
+        executor._record_and_check_loop("search", {"q": "test"})
+
+        executor._printer.print.assert_called_once()
+        call_kwargs = executor._printer.print.call_args
+        assert "Loop detected" in call_kwargs.kwargs.get(
+            "content", call_kwargs[1].get("content", "")
+        )
+
+    @patch("crewai.agents.crew_agent_executor.crewai_event_bus")
+    def test_event_contains_correct_data(self, mock_bus, _make_executor):
+        ld = LoopDetector(repetition_threshold=3, on_loop="inject_reflection")
+        executor = _make_executor(loop_detector=ld)
+
+        ld.record_tool_call("search", {"q": "test"})
+        ld.record_tool_call("search", {"q": "test"})
+
+        executor._record_and_check_loop("search", {"q": "test"})
+
+        event = mock_bus.emit.call_args[0][1]
+        assert isinstance(event, LoopDetectedEvent)
+        assert event.agent_role == "Test Agent"
+        assert event.action_taken == "inject_reflection"
+        assert event.iteration == 0  # executor.iterations was 0
+
+
+# ---------------------------------------------------------------------------
+# Public API import
+# ---------------------------------------------------------------------------
+
+class TestPublicImport:
+    """Verify LoopDetector is importable from the public crewai package."""
+
+    def test_import_from_crewai(self):
+        from crewai import LoopDetector as LD
+
+        assert LD is LoopDetector
+
+    def test_in_all(self):
+        import crewai
+
+        assert "LoopDetector" in crewai.__all__
--- a/lib/crewai/tests/agents/test_native_tool_calling.py
+++ b/lib/crewai/tests/agents/test_native_tool_calling.py
@@ -1184,7 +1184,7 @@ class TestNativeToolCallingJsonParseError:
        executor = self._make_executor([tool])

        from crewai.utilities.agent_utils import convert_tools_to_openai_schema
-        _, available_functions = convert_tools_to_openai_schema([tool])
+        _, available_functions, _ = convert_tools_to_openai_schema([tool])

        malformed_json = '{"code": "print("hello")"}'

@@ -1212,7 +1212,7 @@ class TestNativeToolCallingJsonParseError:
        executor = self._make_executor([tool])

        from crewai.utilities.agent_utils import convert_tools_to_openai_schema
-        _, available_functions = convert_tools_to_openai_schema([tool])
+        _, available_functions, _ = convert_tools_to_openai_schema([tool])

        valid_json = '{"code": "print(1)"}'

@@ -1239,7 +1239,7 @@ class TestNativeToolCallingJsonParseError:
        executor = self._make_executor([tool])

        from crewai.utilities.agent_utils import convert_tools_to_openai_schema
-        _, available_functions = convert_tools_to_openai_schema([tool])
+        _, available_functions, _ = convert_tools_to_openai_schema([tool])

        result = executor._execute_single_native_tool_call(
            call_id="call_789",
@@ -1265,7 +1265,7 @@ class TestNativeToolCallingJsonParseError:
        executor = self._make_executor([tool])

        from crewai.utilities.agent_utils import convert_tools_to_openai_schema
-        _, available_functions = convert_tools_to_openai_schema([tool])
+        _, available_functions, _ = convert_tools_to_openai_schema([tool])

        result = executor._execute_single_native_tool_call(
            call_id="call_schema",
--- a/lib/crewai/tests/telemetry/test_telemetry.py
+++ b/lib/crewai/tests/telemetry/test_telemetry.py
@@ -121,3 +121,41 @@ def test_telemetry_singleton_pattern():
        thread.join()

    assert all(instance is telemetry1 for instance in instances)
+
+
+def test_no_signal_handler_traceback_in_non_main_thread():
+    """Signal handler registration should be silently skipped in non-main threads.
+
+    Regression test for https://github.com/crewAIInc/crewAI/issues/4289
+    """
+    errors: list[Exception] = []
+    mock_holder: dict = {}
+
+    def init_in_thread():
+        try:
+            Telemetry._instance = None
+            with (
+                patch.dict(
+                    os.environ,
+                    {"CREWAI_DISABLE_TELEMETRY": "false", "OTEL_SDK_DISABLED": "false"},
+                ),
+                patch("crewai.telemetry.telemetry.TracerProvider"),
+                patch("signal.signal") as mock_signal,
+                patch("crewai.telemetry.telemetry.logger") as mock_logger,
+            ):
+                Telemetry()
+                mock_holder["signal"] = mock_signal
+                mock_holder["logger"] = mock_logger
+        except Exception as exc:
+            errors.append(exc)
+
+    thread = threading.Thread(target=init_in_thread)
+    thread.start()
+    thread.join()
+
+    assert not errors, f"Unexpected error: {errors}"
+    assert mock_holder, "Thread did not execute"
+    mock_holder["signal"].assert_not_called()
+    mock_holder["logger"].debug.assert_any_call(
+        "Skipping signal handler registration: not running in main thread"
+    )
--- a/lib/crewai/tests/utilities/test_agent_utils.py
+++ b/lib/crewai/tests/utilities/test_agent_utils.py
@@ -80,7 +80,7 @@ class TestConvertToolsToOpenaiSchema:
    def test_converts_single_tool(self) -> None:
        """Test converting a single tool to OpenAI schema."""
        tools = [CalculatorTool()]
-        schemas, functions = convert_tools_to_openai_schema(tools)
+        schemas, functions, _ = convert_tools_to_openai_schema(tools)

        assert len(schemas) == 1
        assert len(functions) == 1
@@ -95,7 +95,7 @@ class TestConvertToolsToOpenaiSchema:
    def test_converts_multiple_tools(self) -> None:
        """Test converting multiple tools to OpenAI schema."""
        tools = [CalculatorTool(), SearchTool()]
-        schemas, functions = convert_tools_to_openai_schema(tools)
+        schemas, functions, _ = convert_tools_to_openai_schema(tools)

        assert len(schemas) == 2
        assert len(functions) == 2
@@ -113,7 +113,7 @@ class TestConvertToolsToOpenaiSchema:
    def test_functions_dict_contains_callables(self) -> None:
        """Test that the functions dict maps names to callable run methods."""
        tools = [CalculatorTool(), SearchTool()]
-        schemas, functions = convert_tools_to_openai_schema(tools)
+        schemas, functions, _ = convert_tools_to_openai_schema(tools)

        assert "calculator" in functions
        assert "web_search" in functions
@@ -123,14 +123,14 @@ class TestConvertToolsToOpenaiSchema:
    def test_function_can_be_called(self) -> None:
        """Test that the returned function can be called."""
        tools = [CalculatorTool()]
-        schemas, functions = convert_tools_to_openai_schema(tools)
+        schemas, functions, _ = convert_tools_to_openai_schema(tools)

        result = functions["calculator"](expression="2 + 2")
        assert result == "4"

    def test_empty_tools_list(self) -> None:
        """Test with an empty tools list."""
-        schemas, functions = convert_tools_to_openai_schema([])
+        schemas, functions, _ = convert_tools_to_openai_schema([])

        assert schemas == []
        assert functions == {}
@@ -138,7 +138,7 @@ class TestConvertToolsToOpenaiSchema:
    def test_schema_has_required_fields(self) -> None:
        """Test that the schema includes required fields information."""
        tools = [SearchTool()]
-        schemas, functions = convert_tools_to_openai_schema(tools)
+        schemas, functions, _ = convert_tools_to_openai_schema(tools)

        schema = schemas[0]
        params = schema["function"]["parameters"]
@@ -158,7 +158,7 @@ class TestConvertToolsToOpenaiSchema:
                return "done"

        tools = [MinimalTool()]
-        schemas, functions = convert_tools_to_openai_schema(tools)
+        schemas, functions, _ = convert_tools_to_openai_schema(tools)

        assert len(schemas) == 1
        schema = schemas[0]
@@ -169,7 +169,7 @@ class TestConvertToolsToOpenaiSchema:
    def test_schema_structure_matches_openai_format(self) -> None:
        """Test that the schema structure matches OpenAI's expected format."""
        tools = [CalculatorTool()]
-        schemas, functions = convert_tools_to_openai_schema(tools)
+        schemas, functions, _ = convert_tools_to_openai_schema(tools)

        schema = schemas[0]

@@ -194,7 +194,7 @@ class TestConvertToolsToOpenaiSchema:
    def test_removes_redundant_schema_fields(self) -> None:
        """Test that redundant title and description are removed from parameters."""
        tools = [CalculatorTool()]
-        schemas, functions = convert_tools_to_openai_schema(tools)
+        schemas, functions, _ = convert_tools_to_openai_schema(tools)

        params = schemas[0]["function"]["parameters"]
        # Title should be removed as it's redundant with function name
@@ -203,7 +203,7 @@ class TestConvertToolsToOpenaiSchema:
    def test_preserves_field_descriptions(self) -> None:
        """Test that field descriptions are preserved in the schema."""
        tools = [SearchTool()]
-        schemas, functions = convert_tools_to_openai_schema(tools)
+        schemas, functions, _ = convert_tools_to_openai_schema(tools)

        params = schemas[0]["function"]["parameters"]
        query_prop = params["properties"]["query"]
@@ -215,7 +215,7 @@ class TestConvertToolsToOpenaiSchema:
    def test_preserves_default_values(self) -> None:
        """Test that default values are preserved in the schema."""
        tools = [SearchTool()]
-        schemas, functions = convert_tools_to_openai_schema(tools)
+        schemas, functions, _ = convert_tools_to_openai_schema(tools)

        params = schemas[0]["function"]["parameters"]
        max_results_prop = params["properties"]["max_results"]
@@ -265,7 +265,7 @@ class TestOptionalFieldsPreserveNull:
        """Optional[str] fields should include null in the schema so the LLM
        can send null instead of being forced to guess a value."""
        tools = [MCPStyleTool()]
-        schemas, _ = convert_tools_to_openai_schema(tools)
+        schemas, _, _ = convert_tools_to_openai_schema(tools)

        params = schemas[0]["function"]["parameters"]
        page_id_prop = params["properties"]["page_id"]
@@ -278,7 +278,7 @@ class TestOptionalFieldsPreserveNull:
    def test_optional_literal_allows_null(self) -> None:
        """Optional[Literal[...]] fields should include null."""
        tools = [MCPStyleTool()]
-        schemas, _ = convert_tools_to_openai_schema(tools)
+        schemas, _, _ = convert_tools_to_openai_schema(tools)

        params = schemas[0]["function"]["parameters"]
        filter_prop = params["properties"]["filter_type"]
@@ -290,7 +290,7 @@ class TestOptionalFieldsPreserveNull:
    def test_required_field_stays_non_null(self) -> None:
        """Required fields without Optional should NOT have null."""
        tools = [MCPStyleTool()]
-        schemas, _ = convert_tools_to_openai_schema(tools)
+        schemas, _, _ = convert_tools_to_openai_schema(tools)

        params = schemas[0]["function"]["parameters"]
        query_prop = params["properties"]["query"]
@@ -301,7 +301,7 @@ class TestOptionalFieldsPreserveNull:
    def test_all_fields_in_required_for_strict_mode(self) -> None:
        """All fields (including optional) must be in required for strict mode."""
        tools = [MCPStyleTool()]
-        schemas, _ = convert_tools_to_openai_schema(tools)
+        schemas, _, _ = convert_tools_to_openai_schema(tools)

        params = schemas[0]["function"]["parameters"]
        assert "query" in params["required"]
--- a/lib/devtools/src/crewai_devtools/init.py
+++ b/lib/devtools/src/crewai_devtools/init.py
@@ -1,3 +1,3 @@
 """CrewAI development tools."""

-__version__ = "1.10.0"
+__version__ = "1.10.1a1"
--- a/lib/devtools/src/crewai_devtools/cli.py
+++ b/lib/devtools/src/crewai_devtools/cli.py
@@ -200,7 +200,7 @@ def add_docs_version(docs_json_path: Path, version: str) -> bool:

    Args:
        docs_json_path: Path to docs/docs.json.
-        version: Version string (e.g., "1.10.0").
+        version: Version string (e.g., "1.10.1b1").

    Returns:
        True if docs.json was updated, False otherwise.
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -146,9 +146,13 @@ python_functions = "test_*"

 # composio-core pins rich<14 but textual requires rich>=14.
 # onnxruntime 1.24+ dropped Python 3.10 wheels; cap it so qdrant[fastembed] resolves on 3.10.
+# fastembed 0.7.x and docling 2.63 cap pillow<12; the removed APIs don't affect them.
+# langchain-core 0.3.76 has a template-injection vuln (GHSA); force >=0.3.80.
 override-dependencies = [
    "rich>=13.7.1",
    "onnxruntime<1.24; python_version < '3.11'",
+    "pillow>=12.1.1",
+    "langchain-core>=0.3.80,<1",
 ]

 [tool.uv.workspace]
--- a/uv.lock
+++ b/uv.lock
@@ -20,7 +20,9 @@ members = [
    "crewai-tools",
 ]
 overrides = [
+    { name = "langchain-core", specifier = ">=0.3.80,<1" },
    { name = "onnxruntime", marker = "python_full_version < '3.11'", specifier = "<1.24" },
+    { name = "pillow", specifier = ">=12.1.1" },
    { name = "rich", specifier = ">=13.7.1" },
 ]

@@ -1194,8 +1196,8 @@ requires-dist = [
    { name = "click", specifier = "~=8.1.7" },
    { name = "crewai-files", marker = "extra == 'file-processing'", editable = "lib/crewai-files" },
    { name = "crewai-tools", marker = "extra == 'tools'", editable = "lib/crewai-tools" },
-    { name = "docling", marker = "extra == 'docling'", specifier = "~=2.63.0" },
-    { name = "google-genai", marker = "extra == 'google-genai'", specifier = "~=1.49.0" },
+    { name = "docling", marker = "extra == 'docling'", specifier = "~=2.75.0" },
+    { name = "google-genai", marker = "extra == 'google-genai'", specifier = "~=1.65.0" },
    { name = "httpx", specifier = "~=0.28.1" },
    { name = "httpx-auth", marker = "extra == 'a2a'", specifier = "~=0.23.1" },
    { name = "httpx-sse", marker = "extra == 'a2a'", specifier = "~=0.4.0" },
@@ -1225,7 +1227,7 @@ requires-dist = [
    { name = "regex", specifier = "~=2026.1.15" },
    { name = "textual", specifier = ">=7.5.0" },
    { name = "tiktoken", marker = "extra == 'embeddings'", specifier = "~=0.8.0" },
-    { name = "tokenizers", specifier = "~=0.20.3" },
+    { name = "tokenizers", specifier = ">=0.21,<1" },
    { name = "tomli", specifier = "~=2.0.2" },
    { name = "tomli-w", specifier = "~=1.1.0" },
    { name = "uv", specifier = "~=0.9.13" },
@@ -1273,8 +1275,8 @@ requires-dist = [
    { name = "aiocache", specifier = "~=0.12.3" },
    { name = "aiofiles", specifier = "~=24.1.0" },
    { name = "av", specifier = "~=13.0.0" },
-    { name = "pillow", specifier = "~=10.4.0" },
-    { name = "pypdf", specifier = "~=4.0.0" },
+    { name = "pillow", specifier = "~=12.1.1" },
+    { name = "pypdf", specifier = "~=6.7.4" },
    { name = "python-magic", specifier = ">=0.4.27" },
    { name = "tinytag", specifier = "~=1.10.0" },
 ]
@@ -1676,12 +1678,13 @@ wheels = [

 [[package]]
 name = "docling"
-version = "2.63.0"
+version = "2.75.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "accelerate" },
    { name = "beautifulsoup4" },
    { name = "certifi" },
+    { name = "defusedxml" },
    { name = "docling-core", extra = ["chunking"] },
    { name = "docling-ibm-models" },
    { name = "docling-parse" },
@@ -1708,16 +1711,17 @@ dependencies = [
    { name = "tqdm" },
    { name = "typer" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/18/c4/a8b7c66f0902ed4d0bcd87db94d3929539ac5fdff5325978744b30bee6b1/docling-2.63.0.tar.gz", hash = "sha256:5592c25e986ebf58811bcbfdbc8217d1a2074638b5412364968a1f1482994cc8", size = 250895, upload-time = "2025-11-20T14:43:53.131Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/77/0b/8ea363fd3c8bb4facb8d3c37aebfe7ad5265fecc1c6bd40f979d1f6179ba/docling-2.75.0.tar.gz", hash = "sha256:1b0a77766e201e5e2d118e236c006f3814afcea2e13726fb3c7389d666a56622", size = 364929, upload-time = "2026-02-24T20:18:04.896Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/69/fd/e5d23f8f12e18a8ada7d977cb86ae5f964b827ae71a42e3ee9f9e2d7d577/docling-2.63.0-py3-none-any.whl", hash = "sha256:59f39b6cf43f10f8c9e429c90f6973245c4c3752d5a03ca3e1732f6fb2905000", size = 268323, upload-time = "2025-11-20T14:43:51.823Z" },
+    { url = "https://files.pythonhosted.org/packages/b8/85/5c6885547ce5cde33af43201e3b2b04cf2360e6854abc07485f54b8d265d/docling-2.75.0-py3-none-any.whl", hash = "sha256:6e156f0326edb6471fc076e978ac64f902f54aac0da13cf89df456013e377bcc", size = 396243, upload-time = "2026-02-24T20:18:03.57Z" },
 ]

 [[package]]
 name = "docling-core"
-version = "2.63.0"
+version = "2.66.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
+    { name = "defusedxml" },
    { name = "jsonref" },
    { name = "jsonschema" },
    { name = "latex2mathml" },
@@ -1729,9 +1733,9 @@ dependencies = [
    { name = "typer" },
    { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/d3/76/f6a1333c0ce4c20e60358185ff8b7fa92e1e1561a43a6788e7c8aaa9898e/docling_core-2.63.0.tar.gz", hash = "sha256:946cf97f27cb81a2c6507121045a356be91e40b5a06bbaf028ca7036df78b2f1", size = 251016, upload-time = "2026-02-03T14:41:07.158Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/00/ba/0b40f5bb2fff918bea79b0ea843ab3479a5f2c7a4be7009ddd713f0e8ab0/docling_core-2.66.0.tar.gz", hash = "sha256:3bbb85bf3e0106d20e7f3d2801ec40460347c95bcda55862b1fcb9effa4f78ea", size = 256592, upload-time = "2026-02-26T10:46:56.744Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/8b/c4/0c825b46412f088828dd2730d231c745d1ff4b5537eed292e827103eff37/docling_core-2.63.0-py3-none-any.whl", hash = "sha256:8f39167bf17da13225c8a67d23df98c87a74e2ab39762dbf51fab93d9b90de25", size = 238637, upload-time = "2026-02-03T14:41:05.55Z" },
+    { url = "https://files.pythonhosted.org/packages/2a/df/6983118cb33e5ce166592945bb473a2b7c60865a9ba661c1d462cfd2c356/docling_core-2.66.0-py3-none-any.whl", hash = "sha256:5f6cf447ca4f50c27531bd15ea1d16c3a811fbfe22e0107207711561520fb316", size = 241133, upload-time = "2026-02-26T10:46:55.021Z" },
 ]

 [package.optional-dependencies]
@@ -1771,7 +1775,7 @@ wheels = [

 [[package]]
 name = "docling-parse"
-version = "4.7.3"
+version = "5.4.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "docling-core" },
@@ -1780,25 +1784,24 @@ dependencies = [
    { name = "pywin32", marker = "sys_platform == 'win32'" },
    { name = "tabulate" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/bb/7a/653c3b11920113217724fab9b4740f9f8964864f92a2a27590accecec5ac/docling_parse-4.7.3.tar.gz", hash = "sha256:5936e6bcb7969c2a13f38ecc75cada3b0919422dc845e96da4b0b7b3bbc394ce", size = 67646746, upload-time = "2026-01-14T14:18:19.376Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/5c/23/07335df49075c376f1cb1238438234a41989688b70119064ef5b9cf1731e/docling_parse-5.4.0.tar.gz", hash = "sha256:1c48096b21cd23d1ab1d306bf0fdfbc7626ec22d62c51eb08a9ec49a5b58dbc8", size = 55466941, upload-time = "2026-02-24T11:46:56.627Z" }
 wheels = [
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 [[package]]
Author	SHA1	Message	Date
Devin AI	420ed828b7	fix: capture tool name/input before _handle_agent_action in ReAct loops _handle_agent_action can convert AgentAction to AgentFinish (when result_as_answer=True). Accessing .tool and .tool_input on AgentFinish would raise AttributeError. Now we capture the values beforehand. Co-Authored-By: João <joao@crewai.com>	2026-03-03 03:36:08 +00:00
Devin AI	52d36ccaf9	feat: add agent loop detection middleware (#4682 ) - Add LoopDetector class with sliding window tracking, configurable repetition threshold, and intervention strategies (inject_reflection, stop, or custom callback) - Add LoopDetectedEvent for observability via the event bus - Integrate loop detection into all 4 executor loop methods (sync/async ReAct and native tools) - Add loop_detector field to BaseAgent - Export LoopDetector from crewai public API - Add i18n support for loop detection warning message - Add 50 comprehensive unit tests Co-Authored-By: João <joao@crewai.com>	2026-03-03 03:33:33 +00:00
Greyson LaLonde	7972192d55	fix(deps): bump tokenizers lower bound to >=0.21 to avoid broken 0.20.3 Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Build uv cache / build-cache (3.10) (push) Has been cancelled Details Build uv cache / build-cache (3.11) (push) Has been cancelled Details Build uv cache / build-cache (3.12) (push) Has been cancelled Details Build uv cache / build-cache (3.13) (push) Has been cancelled Details Mark stale issues and pull requests / stale (push) Has been cancelled Details	2026-03-02 18:04:28 -05:00
Mike Plachta	b3f8a42321	feat: upgrade gemini genai Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com> Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>	2026-03-02 14:27:56 -05:00
Greyson LaLonde	21224f2bc5	fix: conditionally pass plus header Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Empty strings are considered illegal values for bearer auth in `httpx`.	2026-03-02 09:27:54 -05:00
Giulio Leone	b76022c1e7	fix(telemetry): skip signal handler registration in non-main threads * fix(telemetry): skip signal handler registration in non-main threads When CrewAI is initialized from a non-main thread (e.g. Streamlit, Flask, Django, Jupyter), the telemetry module attempted to register signal handlers which only work in the main thread. This caused multiple noisy ValueError tracebacks to be printed to stderr, confusing users even though the errors were caught and non-fatal. Check `threading.current_thread() is not threading.main_thread()` before attempting signal registration, and skip silently with a debug-level log message instead of printing full tracebacks. Fixes crewAIInc/crewAI#4289 * fix(test): move Telemetry() inside signal.signal mock context Refs: #4649 * fix(telemetry): move signal.signal mock inside thread to wrap Telemetry() construction The patch context now activates inside init_in_thread so the mock is guaranteed to be active before and during Telemetry.__init__, addressing the Copilot review feedback. Refs: #4289 * fix(test): mock logger.debug instead of capsys for deterministic assertion Replace signal.signal-only mock with combined logger + signal mock. Assert logger.debug was called with the skip message and signal.signal was never invoked from the non-main thread. Refs: #4289	2026-03-02 07:42:55 -05:00
Greyson LaLonde	1ac5801578	fix: inject tool errors as observations and resolve name collisions Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Mark stale issues and pull requests / stale (push) Has been cancelled Details	2026-03-01 00:46:04 -05:00
Matt Aitchison	c00a348837	fix: upgrade pypdf 4.x → 6.7.4 to resolve 11 Dependabot alerts Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Build uv cache / build-cache (3.10) (push) Has been cancelled Details Build uv cache / build-cache (3.11) (push) Has been cancelled Details Build uv cache / build-cache (3.12) (push) Has been cancelled Details Build uv cache / build-cache (3.13) (push) Has been cancelled Details pypdf <6.7.4 has multiple DoS vulnerabilities via crafted PDF streams (FlateDecode, LZWDecode, RunLengthDecode, XFA, TreeObject, outlines). Only basic PdfReader/PdfWriter APIs are used in crewai-files, none of which changed in the 5.0 or 6.0 breaking releases.	2026-02-28 17:16:45 -05:00
Matt Aitchison	6c8c6c8e12	fix: resolve critical/high Dependabot security alerts (#4652 ) Upgrade pillow 10.4.0 → 12.1.1 (out-of-bounds write on PSD images), langchain-core 0.3.76 → 0.3.83 (template injection), and urllib3 2.6.1 → 2.6.3 (decompression-bomb bypass on redirects). Bump docling ~=2.63.0 → ~=2.75.0 for pillow 12 compat, and add uv overrides for pillow/langchain-core to unblock transitive pins from fastembed and langchain-apify.	2026-02-28 13:04:35 -06:00
Musthaq Ahamad	3899910aa9	docs: sync Composio tool docs across locales (#4639 ) Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details Mark stale issues and pull requests / stale (push) Has been cancelled Details Build uv cache / build-cache (3.10) (push) Has been cancelled Details Build uv cache / build-cache (3.11) (push) Has been cancelled Details Build uv cache / build-cache (3.12) (push) Has been cancelled Details Build uv cache / build-cache (3.13) (push) Has been cancelled Details * docs: update Composio tool docs across locales Align the Composio automation docs with the new session-based example flow and keep localized pages in sync with the updated English content. Made-with: Cursor * docs: clarify manual user authentication wording Refine the Composio auth section language to reflect session-based automatic auth during agent chat while keeping the manual `authorize` flow explicit. Made-with: Cursor * docs: sync updated Composio auth wording across locales Propagate the latest English wording updates for CrewAI provider initialization and manual user authentication guidance to pt-BR and ko docs. Made-with: Cursor	2026-02-27 13:38:45 -08:00
Greyson LaLonde	757a435ee3	chore: update changelog and version for v1.10.1a1 Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details	2026-02-27 09:58:48 -05:00
Greyson LaLonde	8bfdb188f7	feat: bump versions to 1.10.1a1	2026-02-27 09:44:47 -05:00
João Moura	1bdb9496a3	refactor: update step callback methods to support asynchronous invocation (#4633 ) * refactor: update step callback methods to support asynchronous invocation - Replaced synchronous step callback invocations with asynchronous counterparts in the CrewAgentExecutor class. - Introduced a new async method _ainvoke_step_callback to handle step callbacks in an async context, improving responsiveness and performance in asynchronous workflows. * chore: bump version to 1.10.1b1 across multiple files - Updated version strings from 1.10.1b to 1.10.1b1 in various project files including pyproject.toml and __init__.py files. - Adjusted dependency specifications to reflect the new version in relevant templates and modules.	2026-02-27 07:35:03 -03:00
Joao Moura	979aa26c3d	bump new alpha version	2026-02-27 01:43:33 -08:00
João Moura	514c082882	refactor: implement lazy loading for heavy dependencies in Memory module (#4632 ) Some checks failed CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details Mark stale issues and pull requests / stale (push) Has been cancelled Details - Introduced lazy imports for the Memory and EncodingFlow classes to optimize import time and reduce initial load, particularly beneficial for deployment scenarios like Celery pre-fork. - Updated the Memory class to include new configuration options for aggregation queries, enhancing its functionality. - Adjusted the __getattr__ method in both the crewai and memory modules to support lazy loading of specified attributes.	2026-02-27 03:20:02 -03:00
Greyson LaLonde	c9e8068578	docs: update changelog and version for v1.10.0	2026-02-26 19:14:25 -05:00