fix: reuse parent run_id in nested streaming and fix test context isolation

Co-Authored-By: João <joao@crewai.com>

docs/ar/changelog.mdx

@@ -4,6 +4,29 @@ description: "تحديثات المنتج والتحسينات وإصلاحات
 icon: "clock"
 mode: "wide"
 ---
+<Update label="9 أبريل 2026">
+  ## v1.14.2a1
+
+  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.2a1)
+
+  ## ما الذي تغير
+
+  ### إصلاحات الأخطاء
+  - إصلاح إصدار حدث flow_finished بعد استئناف HITL
+  - إصلاح إصدار التشفير إلى 46.0.7 لمعالجة CVE-2026-39892
+
+  ### إعادة هيكلة
+  - إعادة هيكلة لاستخدام I18N_DEFAULT المشترك
+
+  ### الوثائق
+  - تحديث سجل التغييرات والإصدار لـ v1.14.1
+
+  ## المساهمون
+
+  @greysonlalonde
+
+</Update>
+
 <Update label="9 أبريل 2026">
   ## v1.14.1
 

docs/en/changelog.mdx

@@ -4,6 +4,29 @@ description: "Product updates, improvements, and bug fixes for CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="Apr 09, 2026">
+  ## v1.14.2a1
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.2a1)
+
+  ## What's Changed
+
+  ### Bug Fixes
+  - Fix emission of flow_finished event after HITL resume
+  - Fix cryptography version to 46.0.7 to address CVE-2026-39892
+
+  ### Refactoring
+  - Refactor to use shared I18N_DEFAULT singleton
+
+  ### Documentation
+  - Update changelog and version for v1.14.1
+
+  ## Contributors
+
+  @greysonlalonde
+
+</Update>
+
 <Update label="Apr 09, 2026">
   ## v1.14.1
 

docs/ko/changelog.mdx

@@ -4,6 +4,29 @@ description: "CrewAI의 제품 업데이트, 개선 사항 및 버그 수정"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="2026년 4월 9일">
+  ## v1.14.2a1
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.14.2a1)
+
+  ## 변경 사항
+
+  ### 버그 수정
+  - HITL 재개 후 flow_finished 이벤트 방출 수정
+  - CVE-2026-39892 문제를 해결하기 위해 암호화 버전을 46.0.7로 수정
+
+  ### 리팩토링
+  - 공유 I18N_DEFAULT 싱글톤을 사용하도록 리팩토링
+
+  ### 문서
+  - v1.14.1에 대한 변경 로그 및 버전 업데이트
+
+  ## 기여자
+
+  @greysonlalonde
+
+</Update>
+
 <Update label="2026년 4월 9일">
   ## v1.14.1
 

docs/pt-BR/changelog.mdx

@@ -4,6 +4,29 @@ description: "Atualizações de produto, melhorias e correções do CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="09 abr 2026">
+  ## v1.14.2a1
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.2a1)
+
+  ## O que Mudou
+
+  ### Correções de Bugs
+  - Corrigir a emissão do evento flow_finished após a retomada do HITL
+  - Corrigir a versão da criptografia para 46.0.7 para resolver o CVE-2026-39892
+
+  ### Refatoração
+  - Refatorar para usar o singleton I18N_DEFAULT compartilhado
+
+  ### Documentação
+  - Atualizar o changelog e a versão para v1.14.1
+
+  ## Contribuidores
+
+  @greysonlalonde
+
+</Update>
+
 <Update label="09 abr 2026">
   ## v1.14.1
 

lib/crewai-files/src/crewai_files/__init__.py

@@ -152,4 +152,4 @@ __all__ = [
     "wrap_file_source",
 ]
 
-__version__ = "1.14.1"
+__version__ = "1.14.2a1"

lib/crewai-tools/pyproject.toml

@@ -10,7 +10,7 @@ requires-python = ">=3.10, <3.14"
 dependencies = [
     "pytube~=15.0.0",
     "requests~=2.32.5",
-    "crewai==1.14.1",
+    "crewai==1.14.2a1",
     "tiktoken~=0.8.0",
     "beautifulsoup4~=4.13.4",
     "python-docx~=1.2.0",

lib/crewai-tools/src/crewai_tools/__init__.py

@@ -305,4 +305,4 @@ __all__ = [
     "ZapierActionTools",
 ]
 
-__version__ = "1.14.1"
+__version__ = "1.14.2a1"

lib/crewai/pyproject.toml

@@ -55,7 +55,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
 tools = [
-    "crewai-tools==1.14.1",
+    "crewai-tools==1.14.2a1",
 ]
 embeddings = [
     "tiktoken~=0.8.0"

lib/crewai/src/crewai/__init__.py

@@ -46,7 +46,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
 
 _suppress_pydantic_deprecation_warnings()
 
-__version__ = "1.14.1"
+__version__ = "1.14.2a1"
 _telemetry_submitted = False
 
 

lib/crewai/src/crewai/agent/core.py

@@ -98,6 +98,7 @@ from crewai.utilities.converter import Converter, ConverterError
 from crewai.utilities.env import get_env_context
 from crewai.utilities.guardrail import process_guardrail
 from crewai.utilities.guardrail_types import GuardrailCallable, GuardrailType
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.llm_utils import create_llm
 from crewai.utilities.prompts import Prompts, StandardPromptResult, SystemPromptResult
 from crewai.utilities.pydantic_schema_utils import generate_model_description
@@ -499,8 +500,8 @@ class Agent(BaseAgent):
             self.tools_handler.last_used_tool = None
 
         task_prompt = task.prompt()
-        task_prompt = build_task_prompt_with_schema(task, task_prompt, self.i18n)
-        task_prompt = format_task_with_context(task_prompt, context, self.i18n)
+        task_prompt = build_task_prompt_with_schema(task, task_prompt)
+        task_prompt = format_task_with_context(task_prompt, context)
         return self._retrieve_memory_context(task, task_prompt)
 
     def _finalize_task_prompt(
@@ -562,7 +563,7 @@ class Agent(BaseAgent):
                         m.format() for m in matches
                     )
             if memory.strip() != "":
-                task_prompt += self.i18n.slice("memory").format(memory=memory)
+                task_prompt += I18N_DEFAULT.slice("memory").format(memory=memory)
 
             crewai_event_bus.emit(
                 self,
@@ -968,14 +969,13 @@ class Agent(BaseAgent):
             agent=self,
             has_tools=len(raw_tools) > 0,
             use_native_tool_calling=use_native_tool_calling,
-            i18n=self.i18n,
             use_system_prompt=self.use_system_prompt,
             system_template=self.system_template,
             prompt_template=self.prompt_template,
             response_template=self.response_template,
         ).task_execution()
 
-        stop_words = [self.i18n.slice("observation")]
+        stop_words = [I18N_DEFAULT.slice("observation")]
         if self.response_template:
             stop_words.append(
                 self.response_template.split("{{ .Response }}")[1].strip()
@@ -1017,7 +1017,6 @@ class Agent(BaseAgent):
             self.agent_executor = self.executor_class(
                 llm=self.llm,
                 task=task,
-                i18n=self.i18n,
                 agent=self,
                 crew=self.crew,
                 tools=parsed_tools,
@@ -1262,10 +1261,10 @@ class Agent(BaseAgent):
                 from_agent=self,
             ),
         )
-        query = self.i18n.slice("knowledge_search_query").format(
+        query = I18N_DEFAULT.slice("knowledge_search_query").format(
             task_prompt=task_prompt
         )
-        rewriter_prompt = self.i18n.slice("knowledge_search_query_system_prompt")
+        rewriter_prompt = I18N_DEFAULT.slice("knowledge_search_query_system_prompt")
         if not isinstance(self.llm, BaseLLM):
             self._logger.log(
                 "warning",
@@ -1384,7 +1383,6 @@ class Agent(BaseAgent):
             request_within_rpm_limit=rpm_limit_fn,
             callbacks=[TokenCalcHandler(self._token_process)],
             response_model=response_format,
-            i18n=self.i18n,
         )
 
         all_files: dict[str, Any] = {}
@@ -1420,7 +1418,7 @@ class Agent(BaseAgent):
                         m.format() for m in matches
                     )
                 if memory_block:
-                    formatted_messages += "\n\n" + self.i18n.slice("memory").format(
+                    formatted_messages += "\n\n" + I18N_DEFAULT.slice("memory").format(
                         memory=memory_block
                     )
                 crewai_event_bus.emit(
@@ -1624,7 +1622,7 @@ class Agent(BaseAgent):
             try:
                 model_schema = generate_model_description(response_format)
                 schema = json.dumps(model_schema, indent=2)
-                instructions = self.i18n.slice("formatted_task_instructions").format(
+                instructions = I18N_DEFAULT.slice("formatted_task_instructions").format(
                     output_format=schema
                 )
 

lib/crewai/src/crewai/agent/utils.py

@@ -24,7 +24,6 @@ if TYPE_CHECKING:
     from crewai.agent.core import Agent
     from crewai.task import Task
     from crewai.tools.base_tool import BaseTool
-    from crewai.utilities.i18n import I18N
 
 
 def handle_reasoning(agent: Agent, task: Task) -> None:
@@ -59,46 +58,50 @@ def handle_reasoning(agent: Agent, task: Task) -> None:
         agent._logger.log("error", f"Error during planning: {e!s}")
 
 
-def build_task_prompt_with_schema(task: Task, task_prompt: str, i18n: I18N) -> str:
+def build_task_prompt_with_schema(task: Task, task_prompt: str) -> str:
     """Build task prompt with JSON/Pydantic schema instructions if applicable.
 
     Args:
         task: The task being executed.
         task_prompt: The initial task prompt.
-        i18n: Internationalization instance.
 
     Returns:
         The task prompt potentially augmented with schema instructions.
     """
+    from crewai.utilities.i18n import I18N_DEFAULT
+
     if (task.output_json or task.output_pydantic) and not task.response_model:
         if task.output_json:
             schema_dict = generate_model_description(task.output_json)
             schema = json.dumps(schema_dict["json_schema"]["schema"], indent=2)
-            task_prompt += "\n" + i18n.slice("formatted_task_instructions").format(
-                output_format=schema
-            )
+            task_prompt += "\n" + I18N_DEFAULT.slice(
+                "formatted_task_instructions"
+            ).format(output_format=schema)
         elif task.output_pydantic:
             schema_dict = generate_model_description(task.output_pydantic)
             schema = json.dumps(schema_dict["json_schema"]["schema"], indent=2)
-            task_prompt += "\n" + i18n.slice("formatted_task_instructions").format(
-                output_format=schema
-            )
+            task_prompt += "\n" + I18N_DEFAULT.slice(
+                "formatted_task_instructions"
+            ).format(output_format=schema)
     return task_prompt
 
 
-def format_task_with_context(task_prompt: str, context: str | None, i18n: I18N) -> str:
+def format_task_with_context(task_prompt: str, context: str | None) -> str:
     """Format task prompt with context if provided.
 
     Args:
         task_prompt: The task prompt.
         context: Optional context string.
-        i18n: Internationalization instance.
 
     Returns:
         The task prompt formatted with context if provided.
     """
+    from crewai.utilities.i18n import I18N_DEFAULT
+
     if context:
-        return i18n.slice("task_with_context").format(task=task_prompt, context=context)
+        return I18N_DEFAULT.slice("task_with_context").format(
+            task=task_prompt, context=context
+        )
     return task_prompt
 
 

lib/crewai/src/crewai/agents/agent_adapters/langgraph/langgraph_adapter.py

@@ -33,6 +33,7 @@ from crewai.tools.base_tool import BaseTool
 from crewai.types.callback import SerializableCallable
 from crewai.utilities import Logger
 from crewai.utilities.converter import Converter
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.import_utils import require
 
 
@@ -186,7 +187,7 @@ class LangGraphAgentAdapter(BaseAgentAdapter):
             task_prompt = task.prompt() if hasattr(task, "prompt") else str(task)
 
             if context:
-                task_prompt = self.i18n.slice("task_with_context").format(
+                task_prompt = I18N_DEFAULT.slice("task_with_context").format(
                     task=task_prompt, context=context
                 )
 

lib/crewai/src/crewai/agents/agent_adapters/openai_agents/openai_adapter.py

@@ -32,6 +32,7 @@ from crewai.events.types.agent_events import (
 from crewai.tools import BaseTool
 from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.utilities import Logger
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.import_utils import require
 
 
@@ -133,7 +134,7 @@ class OpenAIAgentAdapter(BaseAgentAdapter):
         try:
             task_prompt: str = task.prompt()
             if context:
-                task_prompt = self.i18n.slice("task_with_context").format(
+                task_prompt = I18N_DEFAULT.slice("task_with_context").format(
                     task=task_prompt, context=context
                 )
             crewai_event_bus.emit(

lib/crewai/src/crewai/agents/agent_adapters/openai_agents/structured_output_converter.py

@@ -8,7 +8,7 @@ import json
 from typing import Any
 
 from crewai.agents.agent_adapters.base_converter_adapter import BaseConverterAdapter
-from crewai.utilities.i18n import get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 
 
 class OpenAIConverterAdapter(BaseConverterAdapter):
@@ -59,10 +59,8 @@ class OpenAIConverterAdapter(BaseConverterAdapter):
         if not self._output_format:
             return base_prompt
 
-        output_schema: str = (
-            get_i18n()
-            .slice("formatted_task_instructions")
-            .format(output_format=json.dumps(self._schema, indent=2))
+        output_schema: str = I18N_DEFAULT.slice("formatted_task_instructions").format(
+            output_format=json.dumps(self._schema, indent=2)
         )
 
         return f"{base_prompt}\n\n{output_schema}"

lib/crewai/src/crewai/agents/agent_builder/base_agent.py

@@ -43,7 +43,6 @@ from crewai.state.checkpoint_config import CheckpointConfig, _coerce_checkpoint
 from crewai.tools.base_tool import BaseTool, Tool
 from crewai.types.callback import SerializableCallable
 from crewai.utilities.config import process_config
-from crewai.utilities.i18n import I18N, get_i18n
 from crewai.utilities.logger import Logger
 from crewai.utilities.rpm_controller import RPMController
 from crewai.utilities.string_utils import interpolate_only
@@ -179,7 +178,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
         agent_executor: An instance of the CrewAgentExecutor class.
         llm (Any): Language model that will run the agent.
         crew (Any): Crew to which the agent belongs.
-        i18n (I18N): Internationalization settings.
+
         cache_handler ([CacheHandler]): An instance of the CacheHandler class.
         tools_handler ([ToolsHandler]): An instance of the ToolsHandler class.
         max_tokens: Maximum number of tokens for the agent to generate in a response.
@@ -269,9 +268,6 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
             _serialize_crew_ref, return_type=str | None, when_used="always"
         ),
     ] = Field(default=None, description="Crew to which the agent belongs.")
-    i18n: I18N = Field(
-        default_factory=get_i18n, description="Internationalization settings."
-    )
     cache_handler: CacheHandler | None = Field(
         default=None, description="An instance of the CacheHandler class."
     )

lib/crewai/src/crewai/agents/agent_builder/base_agent_executor.py

@@ -14,7 +14,6 @@ if TYPE_CHECKING:
     from crewai.agents.agent_builder.base_agent import BaseAgent
     from crewai.crew import Crew
     from crewai.task import Task
-    from crewai.utilities.i18n import I18N
 
 
 class BaseAgentExecutor(BaseModel):
@@ -28,7 +27,6 @@ class BaseAgentExecutor(BaseModel):
     max_iter: int = Field(default=25)
     messages: list[LLMMessage] = Field(default_factory=list)
     _resuming: bool = PrivateAttr(default=False)
-    _i18n: I18N | None = PrivateAttr(default=None)
 
     def _save_to_memory(self, output: AgentFinish) -> None:
         """Save task result to unified memory (memory or crew._memory)."""

lib/crewai/src/crewai/agents/crew_agent_executor.py

@@ -67,7 +67,7 @@ from crewai.utilities.agent_utils import (
 )
 from crewai.utilities.constants import TRAINING_DATA_FILE
 from crewai.utilities.file_store import aget_all_files, get_all_files
-from crewai.utilities.i18n import I18N, get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.printer import PRINTER
 from crewai.utilities.string_utils import sanitize_tool_name
 from crewai.utilities.token_counter_callback import TokenCalcHandler
@@ -135,9 +135,8 @@ class CrewAgentExecutor(BaseAgentExecutor):
 
     model_config = ConfigDict(arbitrary_types_allowed=True, populate_by_name=True)
 
-    def __init__(self, i18n: I18N | None = None, **kwargs: Any) -> None:
+    def __init__(self, **kwargs: Any) -> None:
         super().__init__(**kwargs)
-        self._i18n = i18n or get_i18n()
         if not self.before_llm_call_hooks:
             self.before_llm_call_hooks.extend(get_before_llm_call_hooks())
         if not self.after_llm_call_hooks:
@@ -328,7 +327,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
                     formatted_answer = handle_max_iterations_exceeded(
                         formatted_answer,
                         printer=PRINTER,
-                        i18n=self._i18n,
                         messages=self.messages,
                         llm=cast("BaseLLM", self.llm),
                         callbacks=self.callbacks,
@@ -401,7 +399,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
                         agent_action=formatted_answer,
                         fingerprint_context=fingerprint_context,
                         tools=self.tools,
-                        i18n=self._i18n,
                         agent_key=self.agent.key if self.agent else None,
                         agent_role=self.agent.role if self.agent else None,
                         tools_handler=self.tools_handler,
@@ -438,7 +435,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
                         messages=self.messages,
                         llm=cast("BaseLLM", self.llm),
                         callbacks=self.callbacks,
-                        i18n=self._i18n,
                         verbose=self.agent.verbose,
                     )
                     continue
@@ -484,7 +480,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
                     formatted_answer = handle_max_iterations_exceeded(
                         None,
                         printer=PRINTER,
-                        i18n=self._i18n,
                         messages=self.messages,
                         llm=cast("BaseLLM", self.llm),
                         callbacks=self.callbacks,
@@ -575,7 +570,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
                         messages=self.messages,
                         llm=cast("BaseLLM", self.llm),
                         callbacks=self.callbacks,
-                        i18n=self._i18n,
                         verbose=self.agent.verbose,
                     )
                     continue
@@ -771,7 +765,7 @@ class CrewAgentExecutor(BaseAgentExecutor):
                     if tool_finish:
                         return tool_finish
 
-                reasoning_prompt = self._i18n.slice("post_tool_reasoning")
+                reasoning_prompt = I18N_DEFAULT.slice("post_tool_reasoning")
                 reasoning_message: LLMMessage = {
                     "role": "user",
                     "content": reasoning_prompt,
@@ -795,7 +789,7 @@ class CrewAgentExecutor(BaseAgentExecutor):
         if tool_finish:
             return tool_finish
 
-        reasoning_prompt = self._i18n.slice("post_tool_reasoning")
+        reasoning_prompt = I18N_DEFAULT.slice("post_tool_reasoning")
         reasoning_message = {
             "role": "user",
             "content": reasoning_prompt,
@@ -1170,7 +1164,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
                     formatted_answer = handle_max_iterations_exceeded(
                         formatted_answer,
                         printer=PRINTER,
-                        i18n=self._i18n,
                         messages=self.messages,
                         llm=cast("BaseLLM", self.llm),
                         callbacks=self.callbacks,
@@ -1242,7 +1235,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
                         agent_action=formatted_answer,
                         fingerprint_context=fingerprint_context,
                         tools=self.tools,
-                        i18n=self._i18n,
                         agent_key=self.agent.key if self.agent else None,
                         agent_role=self.agent.role if self.agent else None,
                         tools_handler=self.tools_handler,
@@ -1278,7 +1270,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
                         messages=self.messages,
                         llm=cast("BaseLLM", self.llm),
                         callbacks=self.callbacks,
-                        i18n=self._i18n,
                         verbose=self.agent.verbose,
                     )
                     continue
@@ -1318,7 +1309,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
                     formatted_answer = handle_max_iterations_exceeded(
                         None,
                         printer=PRINTER,
-                        i18n=self._i18n,
                         messages=self.messages,
                         llm=cast("BaseLLM", self.llm),
                         callbacks=self.callbacks,
@@ -1408,7 +1398,6 @@ class CrewAgentExecutor(BaseAgentExecutor):
                         messages=self.messages,
                         llm=cast("BaseLLM", self.llm),
                         callbacks=self.callbacks,
-                        i18n=self._i18n,
                         verbose=self.agent.verbose,
                     )
                     continue
@@ -1467,7 +1456,7 @@ class CrewAgentExecutor(BaseAgentExecutor):
             Updated action or final answer.
         """
         # Special case for add_image_tool
-        add_image_tool = self._i18n.tools("add_image")
+        add_image_tool = I18N_DEFAULT.tools("add_image")
         if (
             isinstance(add_image_tool, dict)
             and formatted_answer.tool.casefold().strip()
@@ -1673,5 +1662,5 @@ class CrewAgentExecutor(BaseAgentExecutor):
             Formatted message dict.
         """
         return format_message_for_llm(
-            self._i18n.slice("feedback_instructions").format(feedback=feedback)
+            I18N_DEFAULT.slice("feedback_instructions").format(feedback=feedback)
         )

lib/crewai/src/crewai/agents/parser.py

@@ -19,10 +19,7 @@ from crewai.agents.constants import (
     MISSING_ACTION_INPUT_AFTER_ACTION_ERROR_MESSAGE,
     UNABLE_TO_REPAIR_JSON_RESULTS,
 )
-from crewai.utilities.i18n import get_i18n
-
-
-_I18N = get_i18n()
+from crewai.utilities.i18n import I18N_DEFAULT as _I18N
 
 
 @dataclass

lib/crewai/src/crewai/agents/planner_observer.py

@@ -23,7 +23,7 @@ from crewai.events.types.observation_events import (
     StepObservationStartedEvent,
 )
 from crewai.utilities.agent_utils import extract_task_section
-from crewai.utilities.i18n import I18N, get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.llm_utils import create_llm
 from crewai.utilities.planning_types import StepObservation, TodoItem
 from crewai.utilities.types import LLMMessage
@@ -64,7 +64,6 @@ class PlannerObserver:
         self.task = task
         self.kickoff_input = kickoff_input
         self.llm = self._resolve_llm()
-        self._i18n: I18N = get_i18n()
 
     def _resolve_llm(self) -> Any:
         """Resolve which LLM to use for observation/planning.
@@ -246,7 +245,7 @@ class PlannerObserver:
             task_desc = extract_task_section(self.kickoff_input)
             task_goal = "Complete the task successfully"
 
-        system_prompt = self._i18n.retrieve("planning", "observation_system_prompt")
+        system_prompt = I18N_DEFAULT.retrieve("planning", "observation_system_prompt")
 
         # Build context of what's been done
         completed_summary = ""
@@ -273,7 +272,9 @@ class PlannerObserver:
                 remaining_lines
             )
 
-        user_prompt = self._i18n.retrieve("planning", "observation_user_prompt").format(
+        user_prompt = I18N_DEFAULT.retrieve(
+            "planning", "observation_user_prompt"
+        ).format(
             task_description=task_desc,
             task_goal=task_goal,
             completed_summary=completed_summary,

lib/crewai/src/crewai/agents/step_executor.py

@@ -38,7 +38,7 @@ from crewai.utilities.agent_utils import (
     process_llm_response,
     setup_native_tools,
 )
-from crewai.utilities.i18n import I18N, get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.planning_types import TodoItem
 from crewai.utilities.printer import PRINTER
 from crewai.utilities.step_execution_context import StepExecutionContext, StepResult
@@ -81,7 +81,7 @@ class StepExecutor:
         function_calling_llm: Optional separate LLM for function calling.
         request_within_rpm_limit: Optional RPM limit function.
         callbacks: Optional list of callbacks.
-        i18n: Optional i18n instance.
+
     """
 
     def __init__(
@@ -96,7 +96,6 @@ class StepExecutor:
         function_calling_llm: BaseLLM | None = None,
         request_within_rpm_limit: Callable[[], bool] | None = None,
         callbacks: list[Any] | None = None,
-        i18n: I18N | None = None,
     ) -> None:
         self.llm = llm
         self.tools = tools
@@ -108,7 +107,6 @@ class StepExecutor:
         self.function_calling_llm = function_calling_llm
         self.request_within_rpm_limit = request_within_rpm_limit
         self.callbacks = callbacks or []
-        self._i18n: I18N = i18n or get_i18n()
 
         # Native tool support — set up once
         self._use_native_tools = check_native_tool_support(
@@ -221,14 +219,14 @@ class StepExecutor:
         tools_section = ""
         if self.tools and not self._use_native_tools:
             tool_names = ", ".join(sanitize_tool_name(t.name) for t in self.tools)
-            tools_section = self._i18n.retrieve(
+            tools_section = I18N_DEFAULT.retrieve(
                 "planning", "step_executor_tools_section"
             ).format(tool_names=tool_names)
         elif self.tools:
             tool_names = ", ".join(sanitize_tool_name(t.name) for t in self.tools)
             tools_section = f"\n\nAvailable tools: {tool_names}"
 
-        return self._i18n.retrieve("planning", "step_executor_system_prompt").format(
+        return I18N_DEFAULT.retrieve("planning", "step_executor_system_prompt").format(
             role=role,
             backstory=backstory,
             goal=goal,
@@ -247,7 +245,7 @@ class StepExecutor:
             task_section = extract_task_section(context.task_description)
             if task_section:
                 parts.append(
-                    self._i18n.retrieve(
+                    I18N_DEFAULT.retrieve(
                         "planning", "step_executor_task_context"
                     ).format(
                         task_context=task_section,
@@ -255,14 +253,16 @@ class StepExecutor:
                 )
 
         parts.append(
-            self._i18n.retrieve("planning", "step_executor_user_prompt").format(
+            I18N_DEFAULT.retrieve("planning", "step_executor_user_prompt").format(
                 step_description=todo.description,
             )
         )
 
         if todo.tool_to_use:
             parts.append(
-                self._i18n.retrieve("planning", "step_executor_suggested_tool").format(
+                I18N_DEFAULT.retrieve(
+                    "planning", "step_executor_suggested_tool"
+                ).format(
                     tool_to_use=todo.tool_to_use,
                 )
             )
@@ -270,16 +270,16 @@ class StepExecutor:
         # Include dependency results (final results only, no traces)
         if context.dependency_results:
             parts.append(
-                self._i18n.retrieve("planning", "step_executor_context_header")
+                I18N_DEFAULT.retrieve("planning", "step_executor_context_header")
             )
             for step_num, result in sorted(context.dependency_results.items()):
                 parts.append(
-                    self._i18n.retrieve(
+                    I18N_DEFAULT.retrieve(
                         "planning", "step_executor_context_entry"
                     ).format(step_number=step_num, result=result)
                 )
 
-        parts.append(self._i18n.retrieve("planning", "step_executor_complete_step"))
+        parts.append(I18N_DEFAULT.retrieve("planning", "step_executor_complete_step"))
 
         return "\n".join(parts)
 
@@ -375,7 +375,6 @@ class StepExecutor:
                 agent_action=formatted,
                 fingerprint_context=fingerprint_context,
                 tools=self.tools,
-                i18n=self._i18n,
                 agent_key=self.agent.key if self.agent else None,
                 agent_role=self.agent.role if self.agent else None,
                 tools_handler=self.tools_handler,

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]==1.14.1"
+    "crewai[tools]==1.14.2a1"
 ]
 
 [project.scripts]

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]==1.14.1"
+    "crewai[tools]==1.14.2a1"
 ]
 
 [project.scripts]

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]==1.14.1"
+    "crewai[tools]==1.14.2a1"
 ]
 
 [tool.crewai]

lib/crewai/src/crewai/events/types/llm_events.py

@@ -87,6 +87,7 @@ class LLMStreamChunkEvent(LLMEventBase):
     tool_call: ToolCall | None = None
     call_type: LLMCallType | None = None
     response_id: str | None = None
+    run_id: str | None = None
 
 
 class LLMThinkingChunkEvent(LLMEventBase):

lib/crewai/src/crewai/experimental/agent_executor.py

@@ -91,7 +91,7 @@ from crewai.utilities.agent_utils import (
     track_delegation_if_needed,
 )
 from crewai.utilities.constants import TRAINING_DATA_FILE
-from crewai.utilities.i18n import I18N, get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.planning_types import (
     PlanStep,
     StepObservation,
@@ -189,7 +189,6 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
     )
     callbacks: list[Any] = Field(default_factory=list, exclude=True)
     response_model: type[BaseModel] | None = Field(default=None, exclude=True)
-    i18n: I18N | None = Field(default=None, exclude=True)
     log_error_after: int = Field(default=3, exclude=True)
     before_llm_call_hooks: list[BeforeLLMCallHookType | BeforeLLMCallHookCallable] = (
         Field(default_factory=list, exclude=True)
@@ -198,7 +197,6 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
         default_factory=list, exclude=True
     )
 
-    _i18n: I18N = PrivateAttr(default_factory=get_i18n)
     _console: Console = PrivateAttr(default_factory=Console)
     _last_parser_error: OutputParserError | None = PrivateAttr(default=None)
     _last_context_error: Exception | None = PrivateAttr(default=None)
@@ -214,7 +212,6 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
     @model_validator(mode="after")
     def _setup_executor(self) -> Self:
         """Configure executor after Pydantic field initialization."""
-        self._i18n = self.i18n or get_i18n()
         self.before_llm_call_hooks.extend(get_before_llm_call_hooks())
         self.after_llm_call_hooks.extend(get_after_llm_call_hooks())
 
@@ -363,7 +360,6 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
                 function_calling_llm=self.function_calling_llm,
                 request_within_rpm_limit=self.request_within_rpm_limit,
                 callbacks=self.callbacks,
-                i18n=self._i18n,
             )
         return self._step_executor
 
@@ -1203,7 +1199,6 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
         formatted_answer = handle_max_iterations_exceeded(
             formatted_answer=None,
             printer=PRINTER,
-            i18n=self._i18n,
             messages=list(self.state.messages),
             llm=self.llm,
             callbacks=self.callbacks,
@@ -1430,7 +1425,6 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
                 agent_action=action,
                 fingerprint_context=fingerprint_context,
                 tools=self.tools,
-                i18n=self._i18n,
                 agent_key=self.agent.key if self.agent else None,
                 agent_role=self.agent.role if self.agent else None,
                 tools_handler=self.tools_handler,
@@ -1450,7 +1444,7 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
             action.result = str(e)
             self._append_message_to_state(action.text)
 
-            reasoning_prompt = self._i18n.slice("post_tool_reasoning")
+            reasoning_prompt = I18N_DEFAULT.slice("post_tool_reasoning")
             reasoning_message: LLMMessage = {
                 "role": "user",
                 "content": reasoning_prompt,
@@ -1471,7 +1465,7 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
             self.state.is_finished = True
             return "tool_result_is_final"
 
-        reasoning_prompt = self._i18n.slice("post_tool_reasoning")
+        reasoning_prompt = I18N_DEFAULT.slice("post_tool_reasoning")
         reasoning_message_post: LLMMessage = {
             "role": "user",
             "content": reasoning_prompt,
@@ -2222,10 +2216,10 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
         # Build synthesis prompt
         role = self.agent.role if self.agent else "Assistant"
 
-        system_prompt = self._i18n.retrieve(
+        system_prompt = I18N_DEFAULT.retrieve(
             "planning", "synthesis_system_prompt"
         ).format(role=role)
-        user_prompt = self._i18n.retrieve("planning", "synthesis_user_prompt").format(
+        user_prompt = I18N_DEFAULT.retrieve("planning", "synthesis_user_prompt").format(
             task_description=task_description,
             combined_steps=combined_steps,
         )
@@ -2472,7 +2466,7 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
             self.task.description if self.task else getattr(self, "_kickoff_input", "")
         )
 
-        enhancement = self._i18n.retrieve(
+        enhancement = I18N_DEFAULT.retrieve(
             "planning", "replan_enhancement_prompt"
         ).format(previous_context=previous_context)
 
@@ -2535,7 +2529,6 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
             messages=self.state.messages,
             llm=self.llm,
             callbacks=self.callbacks,
-            i18n=self._i18n,
             verbose=self.agent.verbose,
         )
 
@@ -2746,7 +2739,7 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):  # type: ignor
         Returns:
             Updated action or final answer.
         """
-        add_image_tool = self._i18n.tools("add_image")
+        add_image_tool = I18N_DEFAULT.tools("add_image")
         if (
             isinstance(add_image_tool, dict)
             and formatted_answer.tool.casefold().strip()

lib/crewai/src/crewai/flow/flow.py

@@ -1455,6 +1455,25 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
                 "No pending feedback context. Use from_pending() to restore a paused flow."
             )
 
+        if get_current_parent_id() is None:
+            reset_emission_counter()
+            reset_last_event_id()
+
+        if not self.suppress_flow_events:
+            future = crewai_event_bus.emit(
+                self,
+                FlowStartedEvent(
+                    type="flow_started",
+                    flow_name=self.name or self.__class__.__name__,
+                    inputs=None,
+                ),
+            )
+            if future and isinstance(future, Future):
+                try:
+                    await asyncio.wrap_future(future)
+                except Exception:
+                    logger.warning("FlowStartedEvent handler failed", exc_info=True)
+
         context = self._pending_feedback_context
         emit = context.emit
         default_outcome = context.default_outcome
@@ -1594,16 +1613,39 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
 
         final_result = self._method_outputs[-1] if self._method_outputs else result
 
-        # Emit flow finished
-        crewai_event_bus.emit(
-            self,
-            FlowFinishedEvent(
-                type="flow_finished",
-                flow_name=self.name or self.__class__.__name__,
-                result=final_result,
-                state=self._state,
-            ),
-        )
+        if self._event_futures:
+            await asyncio.gather(
+                *[
+                    asyncio.wrap_future(f)
+                    for f in self._event_futures
+                    if isinstance(f, Future)
+                ]
+            )
+            self._event_futures.clear()
+
+        if not self.suppress_flow_events:
+            future = crewai_event_bus.emit(
+                self,
+                FlowFinishedEvent(
+                    type="flow_finished",
+                    flow_name=self.name or self.__class__.__name__,
+                    result=final_result,
+                    state=self._copy_and_serialize_state(),
+                ),
+            )
+            if future and isinstance(future, Future):
+                try:
+                    await asyncio.wrap_future(future)
+                except Exception:
+                    logger.warning("FlowFinishedEvent handler failed", exc_info=True)
+
+            trace_listener = TraceCollectionListener()
+            if trace_listener.batch_manager.batch_owner_type == "flow":
+                if trace_listener.first_time_handler.is_first_time:
+                    trace_listener.first_time_handler.mark_events_collected()
+                    trace_listener.first_time_handler.handle_execution_completion()
+                else:
+                    trace_listener.batch_manager.finalize_batch()
 
         return final_result
 
@@ -3194,7 +3236,7 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
 
         from crewai.llm import LLM
         from crewai.llms.base_llm import BaseLLM as BaseLLMClass
-        from crewai.utilities.i18n import get_i18n
+        from crewai.utilities.i18n import I18N_DEFAULT
 
         llm_instance: BaseLLMClass
         if isinstance(llm, str):
@@ -3214,9 +3256,7 @@ class Flow(BaseModel, Generic[T], metaclass=FlowMeta):
                 description=f"The outcome that best matches the feedback. Must be one of: {', '.join(outcomes)}"
             )
 
-        # Load prompt from translations (using cached instance)
-        i18n = get_i18n()
-        prompt_template = i18n.slice("human_feedback_collapse")
+        prompt_template = I18N_DEFAULT.slice("human_feedback_collapse")
 
         prompt = prompt_template.format(
             feedback=feedback,

lib/crewai/src/crewai/flow/human_feedback.py

@@ -350,9 +350,9 @@ def human_feedback(
 
         def _get_hitl_prompt(key: str) -> str:
             """Read a HITL prompt from the i18n translations."""
-            from crewai.utilities.i18n import get_i18n
+            from crewai.utilities.i18n import I18N_DEFAULT
 
-            return get_i18n().slice(key)
+            return I18N_DEFAULT.slice(key)
 
         def _resolve_llm_instance() -> Any:
             """Resolve the ``llm`` parameter to a BaseLLM instance.

lib/crewai/src/crewai/lite_agent.py

@@ -89,7 +89,7 @@ from crewai.utilities.converter import (
 )
 from crewai.utilities.guardrail import process_guardrail
 from crewai.utilities.guardrail_types import GuardrailCallable, GuardrailType
-from crewai.utilities.i18n import I18N, get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.llm_utils import create_llm
 from crewai.utilities.printer import PRINTER
 from crewai.utilities.pydantic_schema_utils import generate_model_description
@@ -227,9 +227,6 @@ class LiteAgent(FlowTrackable, BaseModel):
         default=None,
         description="Callback to check if the request is within the RPM8 limit",
     )
-    i18n: I18N = Field(
-        default_factory=get_i18n, description="Internationalization settings."
-    )
     response_format: type[BaseModel] | None = Field(
         default=None, description="Pydantic model for structured output"
     )
@@ -571,7 +568,7 @@ class LiteAgent(FlowTrackable, BaseModel):
                     f"- {m.record.content}" for m in matches
                 )
             if memory_block:
-                formatted = self.i18n.slice("memory").format(memory=memory_block)
+                formatted = I18N_DEFAULT.slice("memory").format(memory=memory_block)
                 if self._messages and self._messages[0].get("role") == "system":
                     existing_content = self._messages[0].get("content", "")
                     if not isinstance(existing_content, str):
@@ -644,7 +641,7 @@ class LiteAgent(FlowTrackable, BaseModel):
             try:
                 model_schema = generate_model_description(active_response_format)
                 schema = json.dumps(model_schema, indent=2)
-                instructions = self.i18n.slice("formatted_task_instructions").format(
+                instructions = I18N_DEFAULT.slice("formatted_task_instructions").format(
                     output_format=schema
                 )
 
@@ -793,7 +790,9 @@ class LiteAgent(FlowTrackable, BaseModel):
         base_prompt = ""
         if self._parsed_tools:
             # Use the prompt template for agents with tools
-            base_prompt = self.i18n.slice("lite_agent_system_prompt_with_tools").format(
+            base_prompt = I18N_DEFAULT.slice(
+                "lite_agent_system_prompt_with_tools"
+            ).format(
                 role=self.role,
                 backstory=self.backstory,
                 goal=self.goal,
@@ -802,7 +801,7 @@ class LiteAgent(FlowTrackable, BaseModel):
             )
         else:
             # Use the prompt template for agents without tools
-            base_prompt = self.i18n.slice(
+            base_prompt = I18N_DEFAULT.slice(
                 "lite_agent_system_prompt_without_tools"
             ).format(
                 role=self.role,
@@ -814,7 +813,7 @@ class LiteAgent(FlowTrackable, BaseModel):
         if active_response_format:
             model_description = generate_model_description(active_response_format)
             schema_json = json.dumps(model_description, indent=2)
-            base_prompt += self.i18n.slice("lite_agent_response_format").format(
+            base_prompt += I18N_DEFAULT.slice("lite_agent_response_format").format(
                 response_format=schema_json
             )
 
@@ -875,7 +874,6 @@ class LiteAgent(FlowTrackable, BaseModel):
                     formatted_answer = handle_max_iterations_exceeded(
                         formatted_answer,
                         printer=PRINTER,
-                        i18n=self.i18n,
                         messages=self._messages,
                         llm=cast(LLM, self.llm),
                         callbacks=self._callbacks,
@@ -914,7 +912,6 @@ class LiteAgent(FlowTrackable, BaseModel):
                         tool_result = execute_tool_and_check_finality(
                             agent_action=formatted_answer,
                             tools=self._parsed_tools,
-                            i18n=self.i18n,
                             agent_key=self.key,
                             agent_role=self.role,
                             agent=self.original_agent,
@@ -956,7 +953,6 @@ class LiteAgent(FlowTrackable, BaseModel):
                         messages=self._messages,
                         llm=cast(LLM, self.llm),
                         callbacks=self._callbacks,
-                        i18n=self.i18n,
                         verbose=self.verbose,
                     )
                     continue

lib/crewai/src/crewai/llm.py

@@ -38,6 +38,7 @@ from crewai.llms.base_llm import (
     get_current_call_id,
     llm_call_context,
 )
+from crewai.utilities.streaming import get_current_stream_run_id
 from crewai.llms.constants import (
     ANTHROPIC_MODELS,
     AZURE_MODELS,
@@ -790,6 +791,7 @@ class LLM(BaseLLM):
                             call_type=LLMCallType.LLM_CALL,
                             response_id=response_id,
                             call_id=get_current_call_id(),
+                            run_id=get_current_stream_run_id(),
                         ),
                     )
             # --- 4) Fallback to non-streaming if no content received
@@ -1003,6 +1005,7 @@ class LLM(BaseLLM):
                     call_type=LLMCallType.TOOL_CALL,
                     response_id=response_id,
                     call_id=get_current_call_id(),
+                    run_id=get_current_stream_run_id(),
                 ),
             )
 
@@ -1456,6 +1459,7 @@ class LLM(BaseLLM):
                             from_agent=from_agent,
                             response_id=response_id,
                             call_id=get_current_call_id(),
+                            run_id=get_current_stream_run_id(),
                         ),
                     )
 

lib/crewai/src/crewai/llms/base_llm.py

@@ -36,6 +36,7 @@ from crewai.events.types.llm_events import (
     LLMStreamChunkEvent,
     LLMThinkingChunkEvent,
 )
+from crewai.utilities.streaming import get_current_stream_run_id
 from crewai.events.types.tool_usage_events import (
     ToolUsageErrorEvent,
     ToolUsageFinishedEvent,
@@ -527,6 +528,7 @@ class BaseLLM(BaseModel, ABC):
                 call_type=call_type,
                 response_id=response_id,
                 call_id=get_current_call_id(),
+                run_id=get_current_stream_run_id(),
             ),
         )
 

lib/crewai/src/crewai/memory/analyze.py

@@ -9,7 +9,7 @@ from typing import Any
 from pydantic import BaseModel, ConfigDict, Field
 
 from crewai.memory.types import MemoryRecord, ScopeInfo
-from crewai.utilities.i18n import get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 
 
 _logger = logging.getLogger(__name__)
@@ -149,7 +149,7 @@ def _get_prompt(key: str) -> str:
     Returns:
         The prompt string.
     """
-    return get_i18n().memory(key)
+    return I18N_DEFAULT.memory(key)
 
 
 def extract_memories_from_content(content: str, llm: Any) -> list[str]:

lib/crewai/src/crewai/task.py

@@ -80,7 +80,7 @@ from crewai.utilities.guardrail_types import (
     GuardrailType,
     GuardrailsType,
 )
-from crewai.utilities.i18n import I18N, get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.printer import PRINTER
 from crewai.utilities.string_utils import interpolate_only
 
@@ -115,7 +115,6 @@ class Task(BaseModel):
     used_tools: int = 0
     tools_errors: int = 0
     delegations: int = 0
-    i18n: I18N = Field(default_factory=get_i18n)
     name: str | None = Field(default=None)
     prompt_context: str | None = None
     description: str = Field(description="Description of the actual task.")
@@ -896,7 +895,7 @@ class Task(BaseModel):
 
         tasks_slices = [description]
 
-        output = self.i18n.slice("expected_output").format(
+        output = I18N_DEFAULT.slice("expected_output").format(
             expected_output=self.expected_output
         )
         tasks_slices = [description, output]
@@ -968,7 +967,7 @@ Follow these guidelines:
                 raise ValueError(f"Error interpolating output_file path: {e!s}") from e
 
         if inputs.get("crew_chat_messages"):
-            conversation_instruction = self.i18n.slice(
+            conversation_instruction = I18N_DEFAULT.slice(
                 "conversation_history_instruction"
             )
 
@@ -1219,7 +1218,7 @@ Follow these guidelines:
                 self.retry_count += 1
                 current_retry_count = self.retry_count
 
-            context = self.i18n.errors("validation_error").format(
+            context = I18N_DEFAULT.errors("validation_error").format(
                 guardrail_result_error=guardrail_result.error,
                 task_output=task_output.raw,
             )
@@ -1316,7 +1315,7 @@ Follow these guidelines:
                 self.retry_count += 1
                 current_retry_count = self.retry_count
 
-            context = self.i18n.errors("validation_error").format(
+            context = I18N_DEFAULT.errors("validation_error").format(
                 guardrail_result_error=guardrail_result.error,
                 task_output=task_output.raw,
             )

lib/crewai/src/crewai/telemetry/telemetry.py

@@ -52,6 +52,7 @@ from crewai.telemetry.utils import (
     add_crew_attributes,
     close_span,
 )
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.logger_utils import suppress_warnings
 from crewai.utilities.string_utils import sanitize_tool_name
 
@@ -314,7 +315,7 @@ class Telemetry:
                                 "verbose?": agent.verbose,
                                 "max_iter": agent.max_iter,
                                 "max_rpm": agent.max_rpm,
-                                "i18n": agent.i18n.prompt_file,
+                                "i18n": I18N_DEFAULT.prompt_file,
                                 "function_calling_llm": (
                                     getattr(
                                         getattr(agent, "function_calling_llm", None),
@@ -844,7 +845,7 @@ class Telemetry:
                             "verbose?": agent.verbose,
                             "max_iter": agent.max_iter,
                             "max_rpm": agent.max_rpm,
-                            "i18n": agent.i18n.prompt_file,
+                            "i18n": I18N_DEFAULT.prompt_file,
                             "llm": agent.llm.model
                             if isinstance(agent.llm, BaseLLM)
                             else str(agent.llm),

lib/crewai/src/crewai/tools/agent_tools/add_image_tool.py

@@ -3,10 +3,7 @@ from typing import Any
 from pydantic import BaseModel, Field
 
 from crewai.tools.base_tool import BaseTool
-from crewai.utilities import I18N
-
-
-i18n = I18N()
+from crewai.utilities.i18n import I18N_DEFAULT
 
 
 class AddImageToolSchema(BaseModel):
@@ -19,9 +16,9 @@ class AddImageToolSchema(BaseModel):
 class AddImageTool(BaseTool):
     """Tool for adding images to the content"""
 
-    name: str = Field(default_factory=lambda: i18n.tools("add_image")["name"])  # type: ignore[index]
+    name: str = Field(default_factory=lambda: I18N_DEFAULT.tools("add_image")["name"])  # type: ignore[index]
     description: str = Field(
-        default_factory=lambda: i18n.tools("add_image")["description"]  # type: ignore[index]
+        default_factory=lambda: I18N_DEFAULT.tools("add_image")["description"]  # type: ignore[index]
     )
     args_schema: type[BaseModel] = AddImageToolSchema
 
@@ -31,7 +28,7 @@ class AddImageTool(BaseTool):
         action: str | None = None,
         **kwargs: Any,
     ) -> dict[str, Any]:
-        action = action or i18n.tools("add_image")["default_action"]  # type: ignore
+        action = action or I18N_DEFAULT.tools("add_image")["default_action"]  # type: ignore
         content = [
             {"type": "text", "text": action},
             {

lib/crewai/src/crewai/tools/agent_tools/agent_tools.py

@@ -5,21 +5,19 @@ from typing import TYPE_CHECKING
 
 from crewai.tools.agent_tools.ask_question_tool import AskQuestionTool
 from crewai.tools.agent_tools.delegate_work_tool import DelegateWorkTool
-from crewai.utilities.i18n import get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 
 
 if TYPE_CHECKING:
     from crewai.agents.agent_builder.base_agent import BaseAgent
     from crewai.tools.base_tool import BaseTool
-    from crewai.utilities.i18n import I18N
 
 
 class AgentTools:
     """Manager class for agent-related tools"""
 
-    def __init__(self, agents: Sequence[BaseAgent], i18n: I18N | None = None) -> None:
+    def __init__(self, agents: Sequence[BaseAgent]) -> None:
         self.agents = agents
-        self.i18n = i18n if i18n is not None else get_i18n()
 
     def tools(self) -> list[BaseTool]:
         """Get all available agent tools"""
@@ -27,14 +25,12 @@ class AgentTools:
 
         delegate_tool = DelegateWorkTool(
             agents=self.agents,
-            i18n=self.i18n,
-            description=self.i18n.tools("delegate_work").format(coworkers=coworkers),  # type: ignore
+            description=I18N_DEFAULT.tools("delegate_work").format(coworkers=coworkers),  # type: ignore
         )
 
         ask_tool = AskQuestionTool(
             agents=self.agents,
-            i18n=self.i18n,
-            description=self.i18n.tools("ask_question").format(coworkers=coworkers),  # type: ignore
+            description=I18N_DEFAULT.tools("ask_question").format(coworkers=coworkers),  # type: ignore
         )
 
         return [delegate_tool, ask_tool]

lib/crewai/src/crewai/tools/agent_tools/base_agent_tools.py

@@ -6,7 +6,7 @@ from pydantic import Field
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.task import Task
 from crewai.tools.base_tool import BaseTool
-from crewai.utilities.i18n import I18N, get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 
 
 logger = logging.getLogger(__name__)
@@ -16,9 +16,6 @@ class BaseAgentTool(BaseTool):
     """Base class for agent-related tools"""
 
     agents: list[BaseAgent] = Field(description="List of available agents")
-    i18n: I18N = Field(
-        default_factory=get_i18n, description="Internationalization settings"
-    )
 
     def sanitize_agent_name(self, name: str) -> str:
         """
@@ -93,7 +90,7 @@ class BaseAgentTool(BaseTool):
             )
         except (AttributeError, ValueError) as e:
             # Handle specific exceptions that might occur during role name processing
-            return self.i18n.errors("agent_tool_unexisting_coworker").format(
+            return I18N_DEFAULT.errors("agent_tool_unexisting_coworker").format(
                 coworkers="\n".join(
                     [
                         f"- {self.sanitize_agent_name(agent.role)}"
@@ -105,7 +102,7 @@ class BaseAgentTool(BaseTool):
 
         if not agent:
             # No matching agent found after sanitization
-            return self.i18n.errors("agent_tool_unexisting_coworker").format(
+            return I18N_DEFAULT.errors("agent_tool_unexisting_coworker").format(
                 coworkers="\n".join(
                     [
                         f"- {self.sanitize_agent_name(agent.role)}"
@@ -120,8 +117,7 @@ class BaseAgentTool(BaseTool):
             task_with_assigned_agent = Task(
                 description=task,
                 agent=selected_agent,
-                expected_output=selected_agent.i18n.slice("manager_request"),
-                i18n=selected_agent.i18n,
+                expected_output=I18N_DEFAULT.slice("manager_request"),
             )
             logger.debug(
                 f"Created task for agent '{self.sanitize_agent_name(selected_agent.role)}': {task}"
@@ -129,6 +125,6 @@ class BaseAgentTool(BaseTool):
             return selected_agent.execute_task(task_with_assigned_agent, context)
         except Exception as e:
             # Handle task creation or execution errors
-            return self.i18n.errors("agent_tool_execution_error").format(
+            return I18N_DEFAULT.errors("agent_tool_execution_error").format(
                 agent_role=self.sanitize_agent_name(selected_agent.role), error=str(e)
             )

lib/crewai/src/crewai/tools/memory_tools.py

@@ -7,7 +7,7 @@ from typing import Any
 from pydantic import BaseModel, Field
 
 from crewai.tools.base_tool import BaseTool
-from crewai.utilities.i18n import get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 
 
 class RecallMemorySchema(BaseModel):
@@ -114,18 +114,17 @@ def create_memory_tools(memory: Any) -> list[BaseTool]:
     Returns:
         List containing a RecallMemoryTool and, if not read-only, a RememberTool.
     """
-    i18n = get_i18n()
     tools: list[BaseTool] = [
         RecallMemoryTool(
             memory=memory,
-            description=i18n.tools("recall_memory"),
+            description=I18N_DEFAULT.tools("recall_memory"),
         ),
     ]
     if not memory.read_only:
         tools.append(
             RememberTool(
                 memory=memory,
-                description=i18n.tools("save_to_memory"),
+                description=I18N_DEFAULT.tools("save_to_memory"),
             )
         )
     return tools

lib/crewai/src/crewai/tools/tool_usage.py

@@ -28,7 +28,7 @@ from crewai.utilities.agent_utils import (
     render_text_description_and_args,
 )
 from crewai.utilities.converter import Converter
-from crewai.utilities.i18n import I18N, get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.printer import PRINTER
 from crewai.utilities.string_utils import sanitize_tool_name
 
@@ -93,7 +93,6 @@ class ToolUsage:
         action: Any = None,
         fingerprint_context: dict[str, str] | None = None,
     ) -> None:
-        self._i18n: I18N = agent.i18n if agent else get_i18n()
         self._telemetry: Telemetry = Telemetry()
         self._run_attempts: int = 1
         self._max_parsing_attempts: int = 3
@@ -146,7 +145,7 @@ class ToolUsage:
         if (
             isinstance(tool, CrewStructuredTool)
             and sanitize_tool_name(tool.name)
-            == sanitize_tool_name(self._i18n.tools("add_image")["name"])  # type: ignore
+            == sanitize_tool_name(I18N_DEFAULT.tools("add_image")["name"])  # type: ignore
         ):
             try:
                 return self._use(tool_string=tool_string, tool=tool, calling=calling)
@@ -194,7 +193,7 @@ class ToolUsage:
         if (
             isinstance(tool, CrewStructuredTool)
             and sanitize_tool_name(tool.name)
-            == sanitize_tool_name(self._i18n.tools("add_image")["name"])  # type: ignore
+            == sanitize_tool_name(I18N_DEFAULT.tools("add_image")["name"])  # type: ignore
         ):
             try:
                 return await self._ause(
@@ -230,7 +229,7 @@ class ToolUsage:
         """
         if self._check_tool_repeated_usage(calling=calling):
             try:
-                result = self._i18n.errors("task_repeated_usage").format(
+                result = I18N_DEFAULT.errors("task_repeated_usage").format(
                     tool_names=self.tools_names
                 )
                 self._telemetry.tool_repeated_usage(
@@ -415,7 +414,7 @@ class ToolUsage:
                     self._run_attempts += 1
                     if self._run_attempts > self._max_parsing_attempts:
                         self._telemetry.tool_usage_error(llm=self.function_calling_llm)
-                        error_message = self._i18n.errors(
+                        error_message = I18N_DEFAULT.errors(
                             "tool_usage_exception"
                         ).format(
                             error=e,
@@ -423,7 +422,7 @@ class ToolUsage:
                             tool_inputs=tool.description,
                         )
                         result = ToolUsageError(
-                            f"\n{error_message}.\nMoving on then. {self._i18n.slice('format').format(tool_names=self.tools_names)}"
+                            f"\n{error_message}.\nMoving on then. {I18N_DEFAULT.slice('format').format(tool_names=self.tools_names)}"
                         ).message
                         if self.task:
                             self.task.increment_tools_errors()
@@ -461,7 +460,7 @@ class ToolUsage:
         # Repeated usage check happens before event emission - safe to return early
         if self._check_tool_repeated_usage(calling=calling):
             try:
-                result = self._i18n.errors("task_repeated_usage").format(
+                result = I18N_DEFAULT.errors("task_repeated_usage").format(
                     tool_names=self.tools_names
                 )
                 self._telemetry.tool_repeated_usage(
@@ -648,7 +647,7 @@ class ToolUsage:
                     self._run_attempts += 1
                     if self._run_attempts > self._max_parsing_attempts:
                         self._telemetry.tool_usage_error(llm=self.function_calling_llm)
-                        error_message = self._i18n.errors(
+                        error_message = I18N_DEFAULT.errors(
                             "tool_usage_exception"
                         ).format(
                             error=e,
@@ -656,7 +655,7 @@ class ToolUsage:
                             tool_inputs=tool.description,
                         )
                         result = ToolUsageError(
-                            f"\n{error_message}.\nMoving on then. {self._i18n.slice('format').format(tool_names=self.tools_names)}"
+                            f"\n{error_message}.\nMoving on then. {I18N_DEFAULT.slice('format').format(tool_names=self.tools_names)}"
                         ).message
                         if self.task:
                             self.task.increment_tools_errors()
@@ -699,7 +698,7 @@ class ToolUsage:
 
     def _remember_format(self, result: str) -> str:
         result = str(result)
-        result += "\n\n" + self._i18n.slice("tools").format(
+        result += "\n\n" + I18N_DEFAULT.slice("tools").format(
             tools=self.tools_description, tool_names=self.tools_names
         )
         return result
@@ -825,12 +824,12 @@ class ToolUsage:
         except Exception:
             if raise_error:
                 raise
-            return ToolUsageError(f"{self._i18n.errors('tool_arguments_error')}")
+            return ToolUsageError(f"{I18N_DEFAULT.errors('tool_arguments_error')}")
 
         if not isinstance(arguments, dict):
             if raise_error:
                 raise
-            return ToolUsageError(f"{self._i18n.errors('tool_arguments_error')}")
+            return ToolUsageError(f"{I18N_DEFAULT.errors('tool_arguments_error')}")
 
         return ToolCalling(
             tool_name=sanitize_tool_name(tool.name),
@@ -856,7 +855,7 @@ class ToolUsage:
                 if self.agent and self.agent.verbose:
                     PRINTER.print(content=f"\n\n{e}\n", color="red")
                 return ToolUsageError(
-                    f"{self._i18n.errors('tool_usage_error').format(error=e)}\nMoving on then. {self._i18n.slice('format').format(tool_names=self.tools_names)}"
+                    f"{I18N_DEFAULT.errors('tool_usage_error').format(error=e)}\nMoving on then. {I18N_DEFAULT.slice('format').format(tool_names=self.tools_names)}"
                 )
             return self._tool_calling(tool_string)
 

lib/crewai/src/crewai/utilities/agent_utils.py

@@ -31,7 +31,7 @@ from crewai.utilities.errors import AgentRepositoryError
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededError,
 )
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.printer import PRINTER, ColoredText, Printer
 from crewai.utilities.pydantic_schema_utils import generate_model_description
 from crewai.utilities.string_utils import sanitize_tool_name
@@ -254,7 +254,6 @@ def has_reached_max_iterations(iterations: int, max_iterations: int) -> bool:
 def handle_max_iterations_exceeded(
     formatted_answer: AgentAction | AgentFinish | None,
     printer: Printer,
-    i18n: I18N,
     messages: list[LLMMessage],
     llm: LLM | BaseLLM,
     callbacks: list[TokenCalcHandler],
@@ -265,7 +264,6 @@ def handle_max_iterations_exceeded(
     Args:
         formatted_answer: The last formatted answer from the agent.
         printer: Printer instance for output.
-        i18n: I18N instance for internationalization.
         messages: List of messages to send to the LLM.
         llm: The LLM instance to call.
         callbacks: List of callbacks for the LLM call.
@@ -282,10 +280,10 @@ def handle_max_iterations_exceeded(
 
     if formatted_answer and hasattr(formatted_answer, "text"):
         assistant_message = (
-            formatted_answer.text + f"\n{i18n.errors('force_final_answer')}"
+            formatted_answer.text + f"\n{I18N_DEFAULT.errors('force_final_answer')}"
         )
     else:
-        assistant_message = i18n.errors("force_final_answer")
+        assistant_message = I18N_DEFAULT.errors("force_final_answer")
 
     messages.append(format_message_for_llm(assistant_message, role="assistant"))
 
@@ -687,7 +685,6 @@ def handle_context_length(
     messages: list[LLMMessage],
     llm: LLM | BaseLLM,
     callbacks: list[TokenCalcHandler],
-    i18n: I18N,
     verbose: bool = True,
 ) -> None:
     """Handle context length exceeded by either summarizing or raising an error.
@@ -698,7 +695,6 @@ def handle_context_length(
         messages: List of messages to summarize
         llm: LLM instance for summarization
         callbacks: List of callbacks for LLM
-        i18n: I18N instance for messages
 
     Raises:
         SystemExit: If context length is exceeded and user opts not to summarize
@@ -710,7 +706,7 @@ def handle_context_length(
                 color="yellow",
             )
         summarize_messages(
-            messages=messages, llm=llm, callbacks=callbacks, i18n=i18n, verbose=verbose
+            messages=messages, llm=llm, callbacks=callbacks, verbose=verbose
         )
     else:
         if verbose:
@@ -863,7 +859,6 @@ async def _asummarize_chunks(
     chunks: list[list[LLMMessage]],
     llm: LLM | BaseLLM,
     callbacks: list[TokenCalcHandler],
-    i18n: I18N,
 ) -> list[SummaryContent]:
     """Summarize multiple message chunks concurrently using asyncio.
 
@@ -871,7 +866,6 @@ async def _asummarize_chunks(
         chunks: List of message chunks to summarize.
         llm: LLM instance (must support ``acall``).
         callbacks: List of callbacks for the LLM.
-        i18n: I18N instance for prompt templates.
 
     Returns:
         Ordered list of summary contents, one per chunk.
@@ -881,10 +875,10 @@ async def _asummarize_chunks(
         conversation_text = _format_messages_for_summary(chunk)
         summarization_messages = [
             format_message_for_llm(
-                i18n.slice("summarizer_system_message"), role="system"
+                I18N_DEFAULT.slice("summarizer_system_message"), role="system"
             ),
             format_message_for_llm(
-                i18n.slice("summarize_instruction").format(
+                I18N_DEFAULT.slice("summarize_instruction").format(
                     conversation=conversation_text
                 ),
             ),
@@ -901,7 +895,6 @@ def summarize_messages(
     messages: list[LLMMessage],
     llm: LLM | BaseLLM,
     callbacks: list[TokenCalcHandler],
-    i18n: I18N,
     verbose: bool = True,
 ) -> None:
     """Summarize messages to fit within context window.
@@ -917,7 +910,6 @@ def summarize_messages(
         messages: List of messages to summarize (modified in-place)
         llm: LLM instance for summarization
         callbacks: List of callbacks for LLM
-        i18n: I18N instance for messages
         verbose: Whether to print progress.
     """
     # 1. Extract & preserve file attachments from user messages
@@ -953,10 +945,10 @@ def summarize_messages(
             conversation_text = _format_messages_for_summary(chunk)
             summarization_messages = [
                 format_message_for_llm(
-                    i18n.slice("summarizer_system_message"), role="system"
+                    I18N_DEFAULT.slice("summarizer_system_message"), role="system"
                 ),
                 format_message_for_llm(
-                    i18n.slice("summarize_instruction").format(
+                    I18N_DEFAULT.slice("summarize_instruction").format(
                         conversation=conversation_text
                     ),
                 ),
@@ -971,9 +963,7 @@ def summarize_messages(
                 content=f"Summarizing {total_chunks} chunks in parallel...",
                 color="yellow",
             )
-        coro = _asummarize_chunks(
-            chunks=chunks, llm=llm, callbacks=callbacks, i18n=i18n
-        )
+        coro = _asummarize_chunks(chunks=chunks, llm=llm, callbacks=callbacks)
         if is_inside_event_loop():
             ctx = contextvars.copy_context()
             with concurrent.futures.ThreadPoolExecutor(max_workers=1) as pool:
@@ -988,7 +978,7 @@ def summarize_messages(
     messages.extend(system_messages)
 
     summary_message = format_message_for_llm(
-        i18n.slice("summary").format(merged_summary=merged_summary)
+        I18N_DEFAULT.slice("summary").format(merged_summary=merged_summary)
     )
     if preserved_files:
         summary_message["files"] = preserved_files

lib/crewai/src/crewai/utilities/converter.py

@@ -8,7 +8,7 @@ from pydantic import BaseModel, ValidationError
 from typing_extensions import Unpack
 
 from crewai.agents.agent_builder.utilities.base_output_converter import OutputConverter
-from crewai.utilities.i18n import get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.internal_instructor import InternalInstructor
 from crewai.utilities.printer import PRINTER
 from crewai.utilities.pydantic_schema_utils import generate_model_description
@@ -21,7 +21,7 @@ if TYPE_CHECKING:
     from crewai.llms.base_llm import BaseLLM
 
 _JSON_PATTERN: Final[re.Pattern[str]] = re.compile(r"({.*})", re.DOTALL)
-_I18N = get_i18n()
+_I18N = I18N_DEFAULT
 
 
 class ConverterError(Exception):

lib/crewai/src/crewai/utilities/evaluators/task_evaluator.py

@@ -8,7 +8,7 @@ from pydantic import BaseModel, Field
 from crewai.events.event_bus import crewai_event_bus
 from crewai.events.types.task_events import TaskEvaluationEvent
 from crewai.utilities.converter import Converter
-from crewai.utilities.i18n import get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.pydantic_schema_utils import generate_model_description
 from crewai.utilities.training_converter import TrainingConverter
 
@@ -98,11 +98,9 @@ class TaskEvaluator:
 
         if not self.llm.supports_function_calling():  # type: ignore[union-attr]
             schema_dict = generate_model_description(TaskEvaluation)
-            output_schema: str = (
-                get_i18n()
-                .slice("formatted_task_instructions")
-                .format(output_format=json.dumps(schema_dict, indent=2))
-            )
+            output_schema: str = I18N_DEFAULT.slice(
+                "formatted_task_instructions"
+            ).format(output_format=json.dumps(schema_dict, indent=2))
             instructions = f"{instructions}\n\n{output_schema}"
 
         converter = Converter(
@@ -174,11 +172,9 @@ class TaskEvaluator:
 
         if not self.llm.supports_function_calling():  # type: ignore[union-attr]
             schema_dict = generate_model_description(TrainingTaskEvaluation)
-            output_schema: str = (
-                get_i18n()
-                .slice("formatted_task_instructions")
-                .format(output_format=json.dumps(schema_dict, indent=2))
-            )
+            output_schema: str = I18N_DEFAULT.slice(
+                "formatted_task_instructions"
+            ).format(output_format=json.dumps(schema_dict, indent=2))
             instructions = f"{instructions}\n\n{output_schema}"
 
         converter = TrainingConverter(

lib/crewai/src/crewai/utilities/i18n.py

@@ -142,3 +142,6 @@ def get_i18n(prompt_file: str | None = None) -> I18N:
         Cached I18N instance.
     """
     return I18N(prompt_file=prompt_file)
+
+
+I18N_DEFAULT: I18N = get_i18n()

lib/crewai/src/crewai/utilities/prompts.py

@@ -6,7 +6,7 @@ from typing import Any, Literal
 
 from pydantic import BaseModel, Field
 
-from crewai.utilities.i18n import I18N, get_i18n
+from crewai.utilities.i18n import I18N_DEFAULT
 
 
 class StandardPromptResult(BaseModel):
@@ -49,7 +49,6 @@ class Prompts(BaseModel):
         - Need to refactor so that prompt is not tightly coupled to agent.
     """
 
-    i18n: I18N = Field(default_factory=get_i18n)
     has_tools: bool = Field(
         default=False, description="Indicates if the agent has access to tools"
     )
@@ -140,13 +139,13 @@ class Prompts(BaseModel):
         if not system_template or not prompt_template:
             # If any of the required templates are missing, fall back to the default format
             prompt_parts: list[str] = [
-                self.i18n.slice(component) for component in components
+                I18N_DEFAULT.slice(component) for component in components
             ]
             prompt = "".join(prompt_parts)
         else:
             # All templates are provided, use them
             template_parts: list[str] = [
-                self.i18n.slice(component)
+                I18N_DEFAULT.slice(component)
                 for component in components
                 if component != "task"
             ]
@@ -154,7 +153,7 @@ class Prompts(BaseModel):
                 "{{ .System }}", "".join(template_parts)
             )
             prompt = prompt_template.replace(
-                "{{ .Prompt }}", "".join(self.i18n.slice("task"))
+                "{{ .Prompt }}", "".join(I18N_DEFAULT.slice("task"))
             )
             # Handle missing response_template
             if response_template:

lib/crewai/src/crewai/utilities/reasoning_handler.py

@@ -15,6 +15,7 @@ from crewai.events.types.reasoning_events import (
     AgentReasoningStartedEvent,
 )
 from crewai.llm import LLM
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.llm_utils import create_llm
 from crewai.utilities.planning_types import PlanStep
 from crewai.utilities.string_utils import sanitize_tool_name
@@ -481,17 +482,17 @@ class AgentReasoning:
         """Get the system prompt for planning.
 
         Returns:
-            The system prompt, either custom or from i18n.
+            The system prompt, either custom or from I18N_DEFAULT.
         """
         if self.config.system_prompt is not None:
             return self.config.system_prompt
 
         # Try new "planning" section first, fall back to "reasoning" for compatibility
         try:
-            return self.agent.i18n.retrieve("planning", "system_prompt")
+            return I18N_DEFAULT.retrieve("planning", "system_prompt")
         except (KeyError, AttributeError):
             # Fallback to reasoning section for backward compatibility
-            return self.agent.i18n.retrieve("reasoning", "initial_plan").format(
+            return I18N_DEFAULT.retrieve("reasoning", "initial_plan").format(
                 role=self.agent.role,
                 goal=self.agent.goal,
                 backstory=self._get_agent_backstory(),
@@ -527,7 +528,7 @@ class AgentReasoning:
 
         # Try new "planning" section first
         try:
-            return self.agent.i18n.retrieve("planning", "create_plan_prompt").format(
+            return I18N_DEFAULT.retrieve("planning", "create_plan_prompt").format(
                 description=self.description,
                 expected_output=self.expected_output,
                 tools=available_tools,
@@ -535,7 +536,7 @@ class AgentReasoning:
             )
         except (KeyError, AttributeError):
             # Fallback to reasoning section for backward compatibility
-            return self.agent.i18n.retrieve("reasoning", "create_plan_prompt").format(
+            return I18N_DEFAULT.retrieve("reasoning", "create_plan_prompt").format(
                 role=self.agent.role,
                 goal=self.agent.goal,
                 backstory=self._get_agent_backstory(),
@@ -584,12 +585,12 @@ class AgentReasoning:
 
         # Try new "planning" section first
         try:
-            return self.agent.i18n.retrieve("planning", "refine_plan_prompt").format(
+            return I18N_DEFAULT.retrieve("planning", "refine_plan_prompt").format(
                 current_plan=current_plan,
             )
         except (KeyError, AttributeError):
             # Fallback to reasoning section for backward compatibility
-            return self.agent.i18n.retrieve("reasoning", "refine_plan_prompt").format(
+            return I18N_DEFAULT.retrieve("reasoning", "refine_plan_prompt").format(
                 role=self.agent.role,
                 goal=self.agent.goal,
                 backstory=self._get_agent_backstory(),
@@ -642,7 +643,7 @@ def _call_llm_with_reasoning_prompt(
     Returns:
         The LLM response.
     """
-    system_prompt = reasoning_agent.i18n.retrieve("reasoning", plan_type).format(
+    system_prompt = I18N_DEFAULT.retrieve("reasoning", plan_type).format(
         role=reasoning_agent.role,
         goal=reasoning_agent.goal,
         backstory=backstory,

lib/crewai/src/crewai/utilities/streaming.py

@@ -7,6 +7,7 @@ import logging
 import queue
 import threading
 from typing import Any, NamedTuple
+import uuid
 
 from typing_extensions import TypedDict
 
@@ -25,6 +26,17 @@ from crewai.utilities.string_utils import sanitize_tool_name
 
 logger = logging.getLogger(__name__)
 
+# ContextVar that tracks the current streaming run_id.
+# Set by create_streaming_state() so that LLM emit paths can stamp events.
+_current_stream_run_id: contextvars.ContextVar[str | None] = contextvars.ContextVar(
+    "_current_stream_run_id", default=None
+)
+
+
+def get_current_stream_run_id() -> str | None:
+    """Return the active streaming run_id for the current context, if any."""
+    return _current_stream_run_id.get()
+
 
 class TaskInfo(TypedDict):
     """Task context information for streaming."""
@@ -106,6 +118,7 @@ def _create_stream_handler(
     sync_queue: queue.Queue[StreamChunk | None | Exception],
     async_queue: asyncio.Queue[StreamChunk | None | Exception] | None = None,
     loop: asyncio.AbstractEventLoop | None = None,
+    run_id: str | None = None,
 ) -> Callable[[Any, BaseEvent], None]:
     """Create a stream handler function.
 
@@ -114,6 +127,9 @@ def _create_stream_handler(
         sync_queue: Synchronous queue for chunks.
         async_queue: Optional async queue for chunks.
         loop: Optional event loop for async operations.
+        run_id: Unique identifier for this streaming run. When set, the handler
+            only accepts events whose ``run_id`` matches, preventing cross-run
+            chunk contamination in concurrent streaming scenarios.
 
     Returns:
         Handler function that can be registered with the event bus.
@@ -129,6 +145,10 @@ def _create_stream_handler(
         if not isinstance(event, LLMStreamChunkEvent):
             return
 
+        # Filter: only accept events belonging to this streaming run.
+        if run_id is not None and event.run_id is not None and event.run_id != run_id:
+            return
+
         chunk = _create_stream_chunk(event, current_task_info)
 
         if async_queue is not None and loop is not None:
@@ -187,6 +207,16 @@ def create_streaming_state(
 ) -> StreamingState:
     """Create and register streaming state.
 
+    Each call assigns a ``run_id`` that is:
+    * stored in a ``contextvars.ContextVar`` so that downstream LLM emit
+      paths can stamp ``LLMStreamChunkEvent.run_id`` automatically, and
+    * passed to the stream handler so it only accepts events with a
+      matching ``run_id``, preventing cross-run chunk contamination.
+
+    If the current context already carries a ``run_id`` (e.g. a parent
+    flow already created a streaming state), the existing value is reused
+    so that nested streaming (flow → crew) shares the same scope.
+
     Args:
         current_task_info: Task context info.
         result_holder: List to hold the final result.
@@ -195,6 +225,9 @@ def create_streaming_state(
     Returns:
         Initialized StreamingState with registered handler.
     """
+    run_id = _current_stream_run_id.get() or str(uuid.uuid4())
+    _current_stream_run_id.set(run_id)
+
     sync_queue: queue.Queue[StreamChunk | None | Exception] = queue.Queue()
     async_queue: asyncio.Queue[StreamChunk | None | Exception] | None = None
     loop: asyncio.AbstractEventLoop | None = None
@@ -203,7 +236,9 @@ def create_streaming_state(
         async_queue = asyncio.Queue()
         loop = asyncio.get_event_loop()
 
-    handler = _create_stream_handler(current_task_info, sync_queue, async_queue, loop)
+    handler = _create_stream_handler(
+        current_task_info, sync_queue, async_queue, loop, run_id=run_id
+    )
     crewai_event_bus.register_handler(LLMStreamChunkEvent, handler)
 
     return StreamingState(

lib/crewai/src/crewai/utilities/tool_utils.py

@@ -13,7 +13,7 @@ from crewai.security.fingerprint import Fingerprint
 from crewai.tools.structured_tool import CrewStructuredTool
 from crewai.tools.tool_types import ToolResult
 from crewai.tools.tool_usage import ToolUsage, ToolUsageError
-from crewai.utilities.i18n import I18N
+from crewai.utilities.i18n import I18N_DEFAULT
 from crewai.utilities.logger import Logger
 from crewai.utilities.string_utils import sanitize_tool_name
 
@@ -30,7 +30,6 @@ if TYPE_CHECKING:
 async def aexecute_tool_and_check_finality(
     agent_action: AgentAction,
     tools: list[CrewStructuredTool],
-    i18n: I18N,
     agent_key: str | None = None,
     agent_role: str | None = None,
     tools_handler: ToolsHandler | None = None,
@@ -49,7 +48,6 @@ async def aexecute_tool_and_check_finality(
     Args:
         agent_action: The action containing the tool to execute.
         tools: List of available tools.
-        i18n: Internationalization settings.
         agent_key: Optional key for event emission.
         agent_role: Optional role for event emission.
         tools_handler: Optional tools handler for tool execution.
@@ -142,7 +140,7 @@ async def aexecute_tool_and_check_finality(
 
         return ToolResult(modified_result, tool.result_as_answer)
 
-    tool_result = i18n.errors("wrong_tool_name").format(
+    tool_result = I18N_DEFAULT.errors("wrong_tool_name").format(
         tool=sanitized_tool_name,
         tools=", ".join(tool_name_to_tool_map.keys()),
     )
@@ -152,7 +150,6 @@ async def aexecute_tool_and_check_finality(
 def execute_tool_and_check_finality(
     agent_action: AgentAction,
     tools: list[CrewStructuredTool],
-    i18n: I18N,
     agent_key: str | None = None,
     agent_role: str | None = None,
     tools_handler: ToolsHandler | None = None,
@@ -170,7 +167,6 @@ def execute_tool_and_check_finality(
     Args:
         agent_action: The action containing the tool to execute
         tools: List of available tools
-        i18n: Internationalization settings
         agent_key: Optional key for event emission
         agent_role: Optional role for event emission
         tools_handler: Optional tools handler for tool execution
@@ -263,7 +259,7 @@ def execute_tool_and_check_finality(
 
         return ToolResult(modified_result, tool.result_as_answer)
 
-    tool_result = i18n.errors("wrong_tool_name").format(
+    tool_result = I18N_DEFAULT.errors("wrong_tool_name").format(
         tool=sanitized_tool_name,
         tools=", ".join(tool_name_to_tool_map.keys()),
     )

lib/crewai/tests/agents/test_agent.py

@@ -1208,12 +1208,10 @@ def test_llm_call_with_error():
 def test_handle_context_length_exceeds_limit():
     # Import necessary modules
     from crewai.utilities.agent_utils import handle_context_length
-    from crewai.utilities.i18n import I18N
     from crewai.utilities.printer import Printer
 
     # Create mocks for dependencies
     printer = Printer()
-    i18n = I18N()
 
     # Create an agent just for its LLM
     agent = Agent(
@@ -1249,7 +1247,6 @@ def test_handle_context_length_exceeds_limit():
                 messages=messages,
                 llm=llm,
                 callbacks=callbacks,
-                i18n=i18n,
             )
 
         # Verify our patch was called and raised the correct error
@@ -1994,7 +1991,7 @@ def test_litellm_anthropic_error_handling():
 @pytest.mark.vcr()
 def test_get_knowledge_search_query():
     """Test that _get_knowledge_search_query calls the LLM with the correct prompts."""
-    from crewai.utilities.i18n import I18N
+    from crewai.utilities.i18n import I18N_DEFAULT
 
     content = "The capital of France is Paris."
     string_source = StringKnowledgeSource(content=content)
@@ -2013,7 +2010,6 @@ def test_get_knowledge_search_query():
         agent=agent,
     )
 
-    i18n = I18N()
     task_prompt = task.prompt()
 
     with (
@@ -2050,13 +2046,13 @@ def test_get_knowledge_search_query():
             [
                 {
                     "role": "system",
-                    "content": i18n.slice(
+                    "content": I18N_DEFAULT.slice(
                         "knowledge_search_query_system_prompt"
                     ).format(task_prompt=task.description),
                 },
                 {
                     "role": "user",
-                    "content": i18n.slice("knowledge_search_query").format(
+                    "content": I18N_DEFAULT.slice("knowledge_search_query").format(
                         task_prompt=task_prompt
                     ),
                 },

lib/crewai/tests/agents/test_agent_executor.py

@@ -48,8 +48,6 @@ def _build_executor(**kwargs: Any) -> AgentExecutor:
     executor._last_context_error = None
     executor._step_executor = None
     executor._planner_observer = None
-    from crewai.utilities.i18n import get_i18n
-    executor._i18n = kwargs.get("i18n") or get_i18n()
     return executor
 from crewai.agents.planner_observer import PlannerObserver
 from crewai.experimental.agent_executor import (

lib/crewai/tests/test_streaming.py

@@ -861,6 +861,265 @@ class TestStreamingCancellation:
         assert not streaming.is_cancelled
 
 
+class TestStreamingRunIsolation:
+    """Tests for concurrent streaming run isolation (issue #5376).
+
+    The singleton event bus fans out events to all registered handlers.
+    Without run_id scoping, concurrent streaming runs receive each other's
+    chunks.  These tests verify that the run_id filtering prevents
+    cross-run chunk contamination.
+    """
+
+    def test_handler_ignores_events_from_different_run(self) -> None:
+        """A handler with run_id must reject events carrying a different run_id."""
+        import queue as _queue
+
+        from crewai.utilities.streaming import _create_stream_handler, TaskInfo
+
+        task_info: TaskInfo = {
+            "index": 0,
+            "name": "task-a",
+            "id": "tid-a",
+            "agent_role": "Agent",
+            "agent_id": "aid-a",
+        }
+        q: _queue.Queue[StreamChunk | None | Exception] = _queue.Queue()
+        handler = _create_stream_handler(task_info, q, run_id="run-A")
+
+        # Event from a *different* run – must be silently dropped.
+        foreign_event = LLMStreamChunkEvent(
+            chunk="foreign-chunk",
+            call_id="cid",
+            run_id="run-B",
+        )
+        handler(None, foreign_event)
+        assert q.empty(), "Handler must not enqueue events from a different run_id"
+
+        # Event from the *same* run – must be enqueued.
+        own_event = LLMStreamChunkEvent(
+            chunk="own-chunk",
+            call_id="cid",
+            run_id="run-A",
+        )
+        handler(None, own_event)
+        assert not q.empty(), "Handler must enqueue events with matching run_id"
+        item = q.get_nowait()
+        assert item.content == "own-chunk"
+
+    def test_concurrent_streaming_states_do_not_cross_contaminate(self) -> None:
+        """Two streaming states created in separate contexts (simulating
+        concurrent runs) must each receive only their own events, even
+        though both handlers are registered on the same global event bus.
+        """
+        import contextvars
+
+        from crewai.utilities.streaming import (
+            create_streaming_state,
+            _current_stream_run_id,
+            TaskInfo,
+            _unregister_handler,
+        )
+
+        task_a: TaskInfo = {
+            "index": 0,
+            "name": "task-a",
+            "id": "tid-a",
+            "agent_role": "Agent-A",
+            "agent_id": "aid-a",
+        }
+        task_b: TaskInfo = {
+            "index": 1,
+            "name": "task-b",
+            "id": "tid-b",
+            "agent_role": "Agent-B",
+            "agent_id": "aid-b",
+        }
+
+        def _create_in_fresh_context(
+            task_info: TaskInfo,
+        ) -> "StreamingState":
+            """Reset the run_id contextvar and create streaming state."""
+            _current_stream_run_id.set(None)
+            return create_streaming_state(task_info, [])
+
+        # Create each streaming state in a *separate* context so they get
+        # distinct run_ids (simulates truly concurrent runs).
+        state_a = contextvars.copy_context().run(_create_in_fresh_context, task_a)
+        state_b = contextvars.copy_context().run(_create_in_fresh_context, task_b)
+
+        # Extract run_ids from handler closures.
+        def _get_run_id_from_handler(handler: Any) -> str | None:
+            """Extract the run_id captured in the handler closure."""
+            fn = handler
+            if hasattr(fn, "__wrapped__"):
+                fn = fn.__wrapped__
+            for cell in (fn.__closure__ or []):
+                try:
+                    val = cell.cell_contents
+                    if isinstance(val, str) and len(val) == 36 and val.count("-") == 4:
+                        return val
+                except ValueError:
+                    continue
+            return None
+
+        rid_a = _get_run_id_from_handler(state_a.handler)
+        rid_b = _get_run_id_from_handler(state_b.handler)
+        assert rid_a is not None and rid_b is not None
+        assert rid_a != rid_b, "Each streaming state must have a unique run_id"
+
+        # Emit events for run A.
+        for i in range(3):
+            crewai_event_bus.emit(
+                self,
+                LLMStreamChunkEvent(
+                    chunk=f"A-{i}",
+                    call_id="cid-a",
+                    run_id=rid_a,
+                ),
+            )
+
+        # Emit events for run B.
+        for i in range(3):
+            crewai_event_bus.emit(
+                self,
+                LLMStreamChunkEvent(
+                    chunk=f"B-{i}",
+                    call_id="cid-b",
+                    run_id=rid_b,
+                ),
+            )
+
+        # Drain queues.
+        chunks_a = []
+        while not state_a.sync_queue.empty():
+            chunks_a.append(state_a.sync_queue.get_nowait())
+
+        chunks_b = []
+        while not state_b.sync_queue.empty():
+            chunks_b.append(state_b.sync_queue.get_nowait())
+
+        # Verify isolation.
+        contents_a = [c.content for c in chunks_a]
+        contents_b = [c.content for c in chunks_b]
+
+        assert contents_a == ["A-0", "A-1", "A-2"], (
+            f"State A must only contain its own chunks, got {contents_a}"
+        )
+        assert contents_b == ["B-0", "B-1", "B-2"], (
+            f"State B must only contain its own chunks, got {contents_b}"
+        )
+
+        # No cross-contamination.
+        for c in contents_a:
+            assert not c.startswith("B-"), f"Run A received run B chunk: {c}"
+        for c in contents_b:
+            assert not c.startswith("A-"), f"Run B received run A chunk: {c}"
+
+        # Cleanup.
+        _unregister_handler(state_a.handler)
+        _unregister_handler(state_b.handler)
+
+    def test_concurrent_threads_isolated(self) -> None:
+        """Simulate two concurrent streaming runs in separate threads and
+        verify that each collects only its own chunks.
+        """
+        import contextvars
+        import threading
+        import time
+
+        from crewai.utilities.streaming import (
+            create_streaming_state,
+            get_current_stream_run_id,
+            TaskInfo,
+            _unregister_handler,
+        )
+
+        results: dict[str, list[str]] = {"A": [], "B": []}
+        errors: list[Exception] = []
+
+        def run_streaming(label: str, task_info: TaskInfo) -> None:
+            try:
+                state = create_streaming_state(task_info, [])
+                run_id = get_current_stream_run_id()
+                assert run_id is not None
+
+                # Simulate LLM emitting chunks stamped with this run's id.
+                for i in range(5):
+                    crewai_event_bus.emit(
+                        None,
+                        LLMStreamChunkEvent(
+                            chunk=f"{label}-{i}",
+                            call_id=f"cid-{label}",
+                            run_id=run_id,
+                        ),
+                    )
+                    time.sleep(0.005)
+
+                # Drain the queue.
+                while not state.sync_queue.empty():
+                    item = state.sync_queue.get_nowait()
+                    results[label].append(item.content)
+
+                _unregister_handler(state.handler)
+            except Exception as exc:
+                errors.append(exc)
+
+        task_a: TaskInfo = {
+            "index": 0,
+            "name": "task-a",
+            "id": "tid-a",
+            "agent_role": "Agent-A",
+            "agent_id": "aid-a",
+        }
+        task_b: TaskInfo = {
+            "index": 1,
+            "name": "task-b",
+            "id": "tid-b",
+            "agent_role": "Agent-B",
+            "agent_id": "aid-b",
+        }
+
+        t_a = threading.Thread(target=run_streaming, args=("A", task_a))
+        t_b = threading.Thread(target=run_streaming, args=("B", task_b))
+
+        t_a.start()
+        t_b.start()
+        t_a.join(timeout=10)
+        t_b.join(timeout=10)
+
+        assert not errors, f"Threads raised errors: {errors}"
+
+        # Each thread must see only its own chunks.
+        for c in results["A"]:
+            assert c.startswith("A-"), f"Run A received foreign chunk: {c}"
+        for c in results["B"]:
+            assert c.startswith("B-"), f"Run B received foreign chunk: {c}"
+
+        assert len(results["A"]) == 5, (
+            f"Run A expected 5 chunks, got {len(results['A'])}: {results['A']}"
+        )
+        assert len(results["B"]) == 5, (
+            f"Run B expected 5 chunks, got {len(results['B'])}: {results['B']}"
+        )
+
+    def test_run_id_stamped_on_llm_stream_chunk_event(self) -> None:
+        """Verify that LLMStreamChunkEvent accepts and stores run_id."""
+        event = LLMStreamChunkEvent(
+            chunk="test",
+            call_id="cid",
+            run_id="my-run-id",
+        )
+        assert event.run_id == "my-run-id"
+
+    def test_run_id_defaults_to_none(self) -> None:
+        """Verify that run_id defaults to None when not provided."""
+        event = LLMStreamChunkEvent(
+            chunk="test",
+            call_id="cid",
+        )
+        assert event.run_id is None
+
+
 class TestStreamingImports:
     """Tests for correct imports of streaming types."""
 

lib/crewai/tests/tools/test_tool_usage.py

@@ -308,7 +308,6 @@ def test_validate_tool_input_invalid_input():
     mock_agent.key = "test_agent_key"  # Must be a string
     mock_agent.role = "test_agent_role"  # Must be a string
     mock_agent._original_role = "test_agent_role"  # Must be a string
-    mock_agent.i18n = MagicMock()
     mock_agent.verbose = False
 
     # Create mock action with proper string value
@@ -443,7 +442,6 @@ def test_tool_selection_error_event_direct():
     mock_agent = MagicMock()
     mock_agent.key = "test_key"
     mock_agent.role = "test_role"
-    mock_agent.i18n = MagicMock()
     mock_agent.verbose = False
 
     mock_task = MagicMock()
@@ -518,13 +516,6 @@ def test_tool_validate_input_error_event():
     mock_agent.verbose = False
     mock_agent._original_role = "test_role"
 
-    # Mock i18n with error message
-    mock_i18n = MagicMock()
-    mock_i18n.errors.return_value = (
-        "Tool input must be a valid dictionary in JSON or Python literal format"
-    )
-    mock_agent.i18n = mock_i18n
-
     # Mock task and tools handler
     mock_task = MagicMock()
     mock_tools_handler = MagicMock()
@@ -590,7 +581,6 @@ def test_tool_usage_finished_event_with_result():
     mock_agent.key = "test_agent_key"
     mock_agent.role = "test_agent_role"
     mock_agent._original_role = "test_agent_role"
-    mock_agent.i18n = MagicMock()
     mock_agent.verbose = False
 
     # Create mock task
@@ -670,7 +660,6 @@ def test_tool_usage_finished_event_with_cached_result():
     mock_agent.key = "test_agent_key"
     mock_agent.role = "test_agent_role"
     mock_agent._original_role = "test_agent_role"
-    mock_agent.i18n = MagicMock()
     mock_agent.verbose = False
 
     # Create mock task
@@ -761,9 +750,6 @@ def test_tool_error_does_not_emit_finished_event():
     mock_agent._original_role = "test_agent_role"
     mock_agent.verbose = False
     mock_agent.fingerprint = None
-    mock_agent.i18n.tools.return_value = {"name": "Add Image"}
-    mock_agent.i18n.errors.return_value = "Error: {error}"
-    mock_agent.i18n.slice.return_value = "Available tools: {tool_names}"
 
     mock_task = MagicMock()
     mock_task.delegations = 0

lib/crewai/tests/utilities/test_agent_utils.py

@@ -225,16 +225,6 @@ class TestConvertToolsToOpenaiSchema:
         assert max_results_prop["default"] == 10
 
 
-def _make_mock_i18n() -> MagicMock:
-    """Create a mock i18n with the new structured prompt keys."""
-    mock_i18n = MagicMock()
-    mock_i18n.slice.side_effect = lambda key: {
-        "summarizer_system_message": "You are a precise assistant that creates structured summaries.",
-        "summarize_instruction": "Summarize the conversation:\n{conversation}",
-        "summary": "<summary>\n{merged_summary}\n</summary>\nContinue the task.",
-    }.get(key, "")
-    return mock_i18n
-
 class MCPStyleInput(BaseModel):
     """Input schema mimicking an MCP tool with optional fields."""
 
@@ -330,7 +320,7 @@ class TestSummarizeMessages:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         # System message preserved + summary message = 2
@@ -361,7 +351,7 @@ class TestSummarizeMessages:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         assert len(messages) == 1
@@ -387,7 +377,7 @@ class TestSummarizeMessages:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         assert len(messages) == 1
@@ -410,7 +400,7 @@ class TestSummarizeMessages:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         assert id(messages) == original_list_id
@@ -432,7 +422,7 @@ class TestSummarizeMessages:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         assert len(messages) == 2
@@ -456,7 +446,7 @@ class TestSummarizeMessages:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         # Check what was passed to llm.call
@@ -482,7 +472,7 @@ class TestSummarizeMessages:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         assert "The extracted summary content." in messages[0]["content"]
@@ -506,7 +496,7 @@ class TestSummarizeMessages:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         # Verify the conversation text sent to LLM contains tool labels
@@ -528,7 +518,7 @@ class TestSummarizeMessages:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         # No LLM call should have been made
@@ -733,7 +723,7 @@ class TestParallelSummarization:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         # acall should have been awaited once per chunk
@@ -757,7 +747,7 @@ class TestParallelSummarization:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         mock_llm.call.assert_called_once()
@@ -788,7 +778,7 @@ class TestParallelSummarization:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         # The final summary message should have A, B, C in order
@@ -816,7 +806,7 @@ class TestParallelSummarization:
                 chunks=[chunk_a, chunk_b],
                 llm=mock_llm,
                 callbacks=[],
-                i18n=_make_mock_i18n(),
+    
             )
         )
 
@@ -843,7 +833,7 @@ class TestParallelSummarization:
             messages=messages,
             llm=mock_llm,
             callbacks=[],
-            i18n=_make_mock_i18n(),
+
         )
 
         assert mock_llm.acall.await_count == 2
@@ -940,10 +930,8 @@ class TestParallelSummarizationVCR:
     def test_parallel_summarize_openai(self) -> None:
         """Test that parallel summarization with gpt-4o-mini produces a valid summary."""
         from crewai.llm import LLM
-        from crewai.utilities.i18n import I18N
 
         llm = LLM(model="gpt-4o-mini", temperature=0)
-        i18n = I18N()
         messages = _build_long_conversation()
 
         original_system = messages[0]["content"]
@@ -959,7 +947,6 @@ class TestParallelSummarizationVCR:
                 messages=messages,
                 llm=llm,
                 callbacks=[],
-                i18n=i18n,
             )
 
         # System message preserved
@@ -975,10 +962,8 @@ class TestParallelSummarizationVCR:
     def test_parallel_summarize_preserves_files(self) -> None:
         """Test that file references survive parallel summarization."""
         from crewai.llm import LLM
-        from crewai.utilities.i18n import I18N
 
         llm = LLM(model="gpt-4o-mini", temperature=0)
-        i18n = I18N()
         messages = _build_long_conversation()
 
         mock_file = MagicMock()
@@ -989,7 +974,6 @@ class TestParallelSummarizationVCR:
                 messages=messages,
                 llm=llm,
                 callbacks=[],
-                i18n=i18n,
             )
 
         summary_msg = messages[-1]

lib/crewai/tests/utilities/test_structured_planning.py

@@ -147,8 +147,6 @@ class TestAgentReasoningWithMockedLLM:
         agent.backstory = "Test backstory"
         agent.verbose = False
         agent.planning_config = PlanningConfig()
-        agent.i18n = MagicMock()
-        agent.i18n.retrieve.return_value = "Test prompt: {description}"
         # Mock the llm attribute
         agent.llm = MagicMock()
         agent.llm.supports_function_calling.return_value = True

lib/crewai/tests/utilities/test_summarize_integration.py

@@ -14,7 +14,6 @@ from crewai.crew import Crew
 from crewai.llm import LLM
 from crewai.task import Task
 from crewai.utilities.agent_utils import summarize_messages
-from crewai.utilities.i18n import I18N
 
 
 def _build_conversation_messages(
@@ -90,7 +89,7 @@ class TestSummarizeDirectOpenAI:
     def test_summarize_direct_openai(self) -> None:
         """Test summarize_messages with gpt-4o-mini preserves system messages."""
         llm = LLM(model="gpt-4o-mini", temperature=0)
-        i18n = I18N()
+
         messages = _build_conversation_messages(include_system=True)
 
         original_system_content = messages[0]["content"]
@@ -99,7 +98,7 @@ class TestSummarizeDirectOpenAI:
             messages=messages,
             llm=llm,
             callbacks=[],
-            i18n=i18n,
+
         )
 
         # System message should be preserved
@@ -122,14 +121,14 @@ class TestSummarizeDirectAnthropic:
     def test_summarize_direct_anthropic(self) -> None:
         """Test summarize_messages with claude-3-5-haiku."""
         llm = LLM(model="anthropic/claude-3-5-haiku-latest", temperature=0)
-        i18n = I18N()
+
         messages = _build_conversation_messages(include_system=True)
 
         summarize_messages(
             messages=messages,
             llm=llm,
             callbacks=[],
-            i18n=i18n,
+
         )
 
         assert len(messages) >= 2
@@ -148,14 +147,14 @@ class TestSummarizeDirectGemini:
     def test_summarize_direct_gemini(self) -> None:
         """Test summarize_messages with gemini-2.0-flash."""
         llm = LLM(model="gemini/gemini-2.0-flash", temperature=0)
-        i18n = I18N()
+
         messages = _build_conversation_messages(include_system=True)
 
         summarize_messages(
             messages=messages,
             llm=llm,
             callbacks=[],
-            i18n=i18n,
+
         )
 
         assert len(messages) >= 2
@@ -174,14 +173,14 @@ class TestSummarizeDirectAzure:
     def test_summarize_direct_azure(self) -> None:
         """Test summarize_messages with azure/gpt-4o-mini."""
         llm = LLM(model="azure/gpt-4o-mini", temperature=0)
-        i18n = I18N()
+
         messages = _build_conversation_messages(include_system=True)
 
         summarize_messages(
             messages=messages,
             llm=llm,
             callbacks=[],
-            i18n=i18n,
+
         )
 
         assert len(messages) >= 2
@@ -261,7 +260,7 @@ class TestSummarizePreservesFiles:
     def test_summarize_preserves_files_integration(self) -> None:
         """Test that file references survive a real summarization call."""
         llm = LLM(model="gpt-4o-mini", temperature=0)
-        i18n = I18N()
+
         messages = _build_conversation_messages(
             include_system=True, include_files=True
         )
@@ -270,7 +269,7 @@ class TestSummarizePreservesFiles:
             messages=messages,
             llm=llm,
             callbacks=[],
-            i18n=i18n,
+
         )
 
         # System message preserved

lib/devtools/src/crewai_devtools/__init__.py

@@ -1,3 +1,3 @@
 """CrewAI development tools."""
 
-__version__ = "1.14.1"
+__version__ = "1.14.2a1"

pyproject.toml

@@ -161,13 +161,14 @@ info = "Commits must follow Conventional Commits 1.0.0."
 
 
 [tool.uv]
-exclude-newer = "3 days"
+exclude-newer = "2026-04-10"  # pinned for CVE-2026-39892; restore to "3 days" after 2026-04-11
 
 # 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 <1.2.11 has SSRF via image_url token counting (CVE-2026-26013).
 # transformers 4.57.6 has CVE-2026-1839; force 5.4+ (docling 2.84 allows huggingface-hub>=1).
+# cryptography 46.0.6 has CVE-2026-39892; force 46.0.7+.
 override-dependencies = [
     "rich>=13.7.1",
     "onnxruntime<1.24; python_version < '3.11'",
@@ -175,6 +176,7 @@ override-dependencies = [
     "langchain-core>=1.2.11,<2",
     "urllib3>=2.6.3",
     "transformers>=5.4.0; python_version >= '3.10'",
+    "cryptography>=46.0.7",
 ]
 
 [tool.uv.workspace]

uv.lock

@@ -13,8 +13,7 @@ resolution-markers = [
 ]
 
 [options]
-exclude-newer = "2026-04-05T11:09:48.9111Z"
-exclude-newer-span = "P3D"
+exclude-newer = "2026-04-10T16:00:00Z"
 
 [manifest]
 members = [
@@ -24,6 +23,7 @@ members = [
     "crewai-tools",
 ]
 overrides = [
+    { name = "cryptography", specifier = ">=46.0.7" },
     { name = "langchain-core", specifier = ">=1.2.11,<2" },
     { name = "onnxruntime", marker = "python_full_version < '3.11'", specifier = "<1.24" },
     { name = "pillow", specifier = ">=12.1.1" },
@@ -1583,48 +1583,48 @@ provides-extras = ["apify", "beautifulsoup4", "bedrock", "browserbase", "composi
 
 [[package]]
 name = "cryptography"
-version = "46.0.6"
+version = "46.0.7"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "cffi", marker = "platform_python_implementation != 'PyPy'" },
     { name = "typing-extensions", marker = "python_full_version < '3.11'" },
 ]
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