feat: add aclose()/close() and async context manager to streaming outputs

docs/ar/learn/streaming-crew-execution.mdx

@@ -325,6 +325,34 @@ asyncio.run(interactive_research())
 - **تجربة المستخدم**: تقليل زمن الاستجابة المتصور بعرض نتائج تدريجية
 - **لوحات المعلومات الحية**: بناء واجهات مراقبة تعرض حالة تنفيذ الطاقم
 
+## الإلغاء وتنظيف الموارد
+
+يدعم `CrewStreamingOutput` الإلغاء السلس بحيث يتوقف العمل الجاري فوراً عند انقطاع اتصال المستهلك.
+
+### مدير السياق غير المتزامن
+
+```python Code
+streaming = await crew.akickoff(inputs={"topic": "AI"})
+
+async with streaming:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+```
+
+### الإلغاء الصريح
+
+```python Code
+streaming = await crew.akickoff(inputs={"topic": "AI"})
+try:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+finally:
+    await streaming.aclose()  # غير متزامن
+    # streaming.close()       # المكافئ المتزامن
+```
+
+بعد الإلغاء، يكون كل من `streaming.is_cancelled` و `streaming.is_completed` بقيمة `True`. كل من `aclose()` و `close()` متساويان القوة.
+
 ## ملاحظات مهمة
 
 - يفعّل البث تلقائياً بث LLM لجميع الوكلاء في الطاقم

docs/ar/learn/streaming-flow-execution.mdx

@@ -420,6 +420,34 @@ except Exception as e:
         print("Streaming completed but flow encountered an error")
 ```
 
+## الإلغاء وتنظيف الموارد
+
+يدعم `FlowStreamingOutput` الإلغاء السلس بحيث يتوقف العمل الجاري فوراً عند انقطاع اتصال المستهلك.
+
+### مدير السياق غير المتزامن
+
+```python Code
+streaming = await flow.kickoff_async()
+
+async with streaming:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+```
+
+### الإلغاء الصريح
+
+```python Code
+streaming = await flow.kickoff_async()
+try:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+finally:
+    await streaming.aclose()  # غير متزامن
+    # streaming.close()       # المكافئ المتزامن
+```
+
+بعد الإلغاء، يكون كل من `streaming.is_cancelled` و `streaming.is_completed` بقيمة `True`. كل من `aclose()` و `close()` متساويان القوة.
+
 ## ملاحظات مهمة
 
 - يفعّل البث تلقائياً بث LLM لأي أطقم مستخدمة داخل التدفق

docs/en/learn/streaming-crew-execution.mdx

@@ -325,6 +325,34 @@ Streaming is particularly valuable for:
 - **User Experience**: Reduce perceived latency by showing incremental results
 - **Live Dashboards**: Build monitoring interfaces that display crew execution status
 
+## Cancellation and Resource Cleanup
+
+`CrewStreamingOutput` supports graceful cancellation so that in-flight work stops promptly when the consumer disconnects.
+
+### Async Context Manager
+
+```python Code
+streaming = await crew.akickoff(inputs={"topic": "AI"})
+
+async with streaming:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+```
+
+### Explicit Cancellation
+
+```python Code
+streaming = await crew.akickoff(inputs={"topic": "AI"})
+try:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+finally:
+    await streaming.aclose()  # async
+    # streaming.close()       # sync equivalent
+```
+
+After cancellation, `streaming.is_cancelled` and `streaming.is_completed` are both `True`. Both `aclose()` and `close()` are idempotent.
+
 ## Important Notes
 
 - Streaming automatically enables LLM streaming for all agents in the crew

docs/en/learn/streaming-flow-execution.mdx

@@ -420,6 +420,34 @@ except Exception as e:
         print("Streaming completed but flow encountered an error")
 ```
 
+## Cancellation and Resource Cleanup
+
+`FlowStreamingOutput` supports graceful cancellation so that in-flight work stops promptly when the consumer disconnects.
+
+### Async Context Manager
+
+```python Code
+streaming = await flow.kickoff_async()
+
+async with streaming:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+```
+
+### Explicit Cancellation
+
+```python Code
+streaming = await flow.kickoff_async()
+try:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+finally:
+    await streaming.aclose()  # async
+    # streaming.close()       # sync equivalent
+```
+
+After cancellation, `streaming.is_cancelled` and `streaming.is_completed` are both `True`. Both `aclose()` and `close()` are idempotent.
+
 ## Important Notes
 
 - Streaming automatically enables LLM streaming for any crews used within the flow

docs/ko/learn/streaming-crew-execution.mdx

@@ -325,6 +325,34 @@ asyncio.run(interactive_research())
 - **사용자 경험**: 점진적인 결과를 표시하여 체감 지연 시간 감소
 - **라이브 대시보드**: crew 실행 상태를 표시하는 모니터링 인터페이스 구축
 
+## 취소 및 리소스 정리
+
+`CrewStreamingOutput`은 소비자가 연결을 끊을 때 진행 중인 작업을 즉시 중단하는 정상적인 취소를 지원합니다.
+
+### 비동기 컨텍스트 매니저
+
+```python Code
+streaming = await crew.akickoff(inputs={"topic": "AI"})
+
+async with streaming:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+```
+
+### 명시적 취소
+
+```python Code
+streaming = await crew.akickoff(inputs={"topic": "AI"})
+try:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+finally:
+    await streaming.aclose()  # 비동기
+    # streaming.close()       # 동기 버전
+```
+
+취소 후 `streaming.is_cancelled`와 `streaming.is_completed`는 모두 `True`입니다. `aclose()`와 `close()` 모두 멱등성을 가집니다.
+
 ## 중요 사항
 
 - 스트리밍은 crew의 모든 에이전트에 대해 자동으로 LLM 스트리밍을 활성화합니다

docs/pt-BR/learn/streaming-crew-execution.mdx

@@ -325,6 +325,34 @@ O streaming é particularmente valioso para:
 - **Experiência do Usuário**: Reduzir latência percebida mostrando resultados incrementais
 - **Dashboards ao Vivo**: Construir interfaces de monitoramento que exibem status de execução da crew
 
+## Cancelamento e Limpeza de Recursos
+
+`CrewStreamingOutput` suporta cancelamento gracioso para que o trabalho em andamento pare imediatamente quando o consumidor desconecta.
+
+### Gerenciador de Contexto Assíncrono
+
+```python Code
+streaming = await crew.akickoff(inputs={"topic": "AI"})
+
+async with streaming:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+```
+
+### Cancelamento Explícito
+
+```python Code
+streaming = await crew.akickoff(inputs={"topic": "AI"})
+try:
+    async for chunk in streaming:
+        print(chunk.content, end="", flush=True)
+finally:
+    await streaming.aclose()  # assíncrono
+    # streaming.close()       # equivalente síncrono
+```
+
+Após o cancelamento, `streaming.is_cancelled` e `streaming.is_completed` são ambos `True`. Tanto `aclose()` quanto `close()` são idempotentes.
+
 ## Notas Importantes
 
 - O streaming ativa automaticamente o streaming do LLM para todos os agentes na crew