docs: add flow plot visualization example to documentation (#2668)

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

docs/changelog.mdx

@@ -4,6 +4,36 @@ description: View the latest updates and changes to CrewAI
 icon: timeline
 ---
 
+<Update label="2025-04-07" description="v0.114.0">
+  ## Release Highlights
+  <Frame>
+    <img src="/images/v01140.png" />
+  </Frame>
+
+  **New Features & Enhancements**
+  - Agents as an atomic unit. (`Agent(...).kickoff()`)
+  - Support for [Custom LLM implementations](https://docs.crewai.com/guides/advanced/custom-llm).
+  - Integrated External Memory and [Opik observability](https://docs.crewai.com/how-to/opik-observability).
+  - Enhanced YAML extraction.
+  - Multimodal agent validation.
+  - Added Secure fingerprints for agents and crews.
+
+  **Core Improvements & Fixes**
+  - Improved serialization, agent copying, and Python compatibility.
+  - Added wildcard support to `emit()`
+  - Added support for additional router calls and context window adjustments.
+  - Fixed typing issues, validation, and import statements.
+  - Improved method performance.
+  - Enhanced agent task handling, event emissions, and memory management.
+  - Fixed CLI issues, conditional tasks, cloning behavior, and tool outputs.
+
+  **Documentation & Guides**
+  - Improved documentation structure, theme, and organization.
+  - Added guides for Local NVIDIA NIM with WSL2, W&B Weave, and Arize Phoenix.
+  - Updated tool configuration examples, prompts, and observability docs.
+  - Guide on using singular agents within Flows.
+</Update>
+
 <Update label="2025-03-17" description="v0.108.0">
   **Features**
   - Converted tabs to spaces in `crew.py` template

docs/concepts/flows.mdx

@@ -790,6 +790,9 @@ Visualizing your AI workflows can provide valuable insights into the structure a
 
 Plots in CrewAI are graphical representations of your AI workflows. They display the various tasks, their connections, and the flow of data between them. This visualization helps in understanding the sequence of operations, identifying bottlenecks, and ensuring that the workflow logic aligns with your expectations.
 
+![Example of a Flow Plot](/images/flow_plot_example.png)
+*An example visualization of a simple flow with start method, sequential steps, and directional execution.*
+
 ### How to Generate a Plot
 
 CrewAI provides two convenient methods to generate plots of your flows:

docs/concepts/knowledge.mdx

@@ -42,6 +42,16 @@ CrewAI supports various types of knowledge sources out of the box:
 | `collection_name`          | **str**                              | No       | Name of the collection where the knowledge will be stored. Used to identify different sets of knowledge. Defaults to "knowledge" if not provided.     |
 | `storage`                  | **Optional[KnowledgeStorage]**       | No       | Custom storage configuration for managing how the knowledge is stored and retrieved. If not provided, a default storage will be created.              |
 
+
+<Tip>
+Unlike retrieval from a vector database using a tool, agents preloaded with knowledge will not need a retrieval persona or task.
+Simply add the relevant knowledge sources your agent or crew needs to function.
+
+Knowledge sources can be added at the agent or crew level.
+Crew level knowledge sources will be used by **all agents** in the crew.
+Agent level knowledge sources will be used by the **specific agent** that is preloaded with the knowledge.
+</Tip>
+
 ## Quickstart Example
 
 <Tip>
@@ -146,6 +156,26 @@ result = crew.kickoff(
 )
 ```
 
+## Knowledge Configuration
+
+You can configure the knowledge configuration for the crew or agent.
+
+```python Code
+from crewai.knowledge.knowledge_config import KnowledgeConfig
+
+knowledge_config = KnowledgeConfig(results_limit=10, score_threshold=0.5)
+
+agent = Agent(
+    ...
+    knowledge_config=knowledge_config
+)
+```
+
+<Tip>
+  `results_limit`: is the number of relevant documents to return. Default is 3.
+  `score_threshold`: is the minimum score for a document to be considered relevant. Default is 0.35.
+</Tip>
+
 ## More Examples
 
 Here are examples of how to use different types of knowledge sources:

docs/concepts/llamaindex-tools.mdx

@@ -1,71 +0,0 @@
----
-title: Using LlamaIndex Tools
-description: Learn how to integrate LlamaIndex tools with CrewAI agents to enhance search-based queries and more.
-icon: toolbox
----
-
-## Using LlamaIndex Tools
-
-<Info>
-    CrewAI seamlessly integrates with LlamaIndex’s comprehensive toolkit for RAG (Retrieval-Augmented Generation) and agentic pipelines, enabling advanced search-based queries and more. 
-</Info>
-
-Here are the available built-in tools offered by LlamaIndex.
-
-```python Code
-from crewai import Agent
-from crewai_tools import LlamaIndexTool
-
-# Example 1: Initialize from FunctionTool
-from llama_index.core.tools import FunctionTool
-
-your_python_function = lambda ...: ...
-og_tool = FunctionTool.from_defaults(
-    your_python_function, 
-    name="<name>", 
-    description='<description>'
-)
-tool = LlamaIndexTool.from_tool(og_tool)
-
-# Example 2: Initialize from LlamaHub Tools
-from llama_index.tools.wolfram_alpha import WolframAlphaToolSpec
-wolfram_spec = WolframAlphaToolSpec(app_id="<app_id>")
-wolfram_tools = wolfram_spec.to_tool_list()
-tools = [LlamaIndexTool.from_tool(t) for t in wolfram_tools]
-
-# Example 3: Initialize Tool from a LlamaIndex Query Engine
-query_engine = index.as_query_engine()
-query_tool = LlamaIndexTool.from_query_engine(
-    query_engine,
-    name="Uber 2019 10K Query Tool",
-    description="Use this tool to lookup the 2019 Uber 10K Annual Report"
-)
-
-# Create and assign the tools to an agent
-agent = Agent(
-    role='Research Analyst',
-    goal='Provide up-to-date market analysis',
-    backstory='An expert analyst with a keen eye for market trends.',
-    tools=[tool, *tools, query_tool]
-)
-
-# rest of the code ...
-```
-
-## Steps to Get Started
-
-To effectively use the LlamaIndexTool, follow these steps:
-
-<Steps>
-    <Step title="Package Installation">
-    Make sure that `crewai[tools]` package is installed in your Python environment:
-    <CodeGroup>
-        ```shell Terminal
-        pip install 'crewai[tools]'
-        ```
-    </CodeGroup>
-    </Step>
-    <Step title="Install and Use LlamaIndex">
-    Follow the LlamaIndex documentation [LlamaIndex Documentation](https://docs.llamaindex.ai/) to set up a RAG/agent pipeline.
-    </Step>
-</Steps>

docs/docs.json

@@ -8,25 +8,27 @@
     "dark": "#C94C3C"
   },
   "favicon": "favicon.svg",
+  "contextual": {
+    "options": ["copy", "view", "chatgpt", "claude"]
+  },
   "navigation": {
     "tabs": [
       {
-        "tab": "Get Started",
+        "tab": "Documentation",
         "groups": [
           {
             "group": "Get Started",
             "pages": [
               "introduction",
               "installation",
-              "quickstart",
-              "changelog"
+              "quickstart"
             ]
           },
           {
             "group": "Guides",
             "pages": [
               {
-                "group": "Concepts",
+                "group": "Strategy",
                 "pages": [
                   "guides/concepts/evaluating-use-cases"
                 ]
@@ -79,41 +81,6 @@
               "concepts/event-listener"
             ]
           },
-          {
-            "group": "How to Guides",
-            "pages": [
-              "how-to/create-custom-tools",
-              "how-to/sequential-process",
-              "how-to/hierarchical-process",
-              "how-to/custom-manager-agent",
-              "how-to/llm-connections",
-              "how-to/customizing-agents",
-              "how-to/multimodal-agents",
-              "how-to/coding-agents",
-              "how-to/force-tool-output-as-result",
-              "how-to/human-input-on-execution",
-              "how-to/kickoff-async",
-              "how-to/kickoff-for-each",
-              "how-to/replay-tasks-from-latest-crew-kickoff",
-              "how-to/conditional-tasks",
-              "how-to/langchain-tools",
-              "how-to/llamaindex-tools"
-            ]
-          },
-          {
-            "group": "Agent Monitoring & Observability",
-            "pages": [
-              "how-to/agentops-observability",
-              "how-to/arize-phoenix-observability",
-              "how-to/langfuse-observability",
-              "how-to/langtrace-observability",
-              "how-to/mlflow-observability",
-              "how-to/openlit-observability",
-              "how-to/opik-observability",
-              "how-to/portkey-observability",
-              "how-to/weave-integration"
-            ]
-          },
           {
             "group": "Tools",
             "pages": [
@@ -141,6 +108,7 @@
               "tools/hyperbrowserloadtool",
               "tools/linkupsearchtool",
               "tools/llamaindextool",
+              "tools/langchaintool",
               "tools/serperdevtool",
               "tools/s3readertool",
               "tools/s3writertool",
@@ -170,6 +138,40 @@
               "tools/youtubevideosearchtool"
             ]
           },
+          {
+            "group": "Agent Monitoring & Observability",
+            "pages": [
+              "how-to/agentops-observability",
+              "how-to/arize-phoenix-observability",
+              "how-to/langfuse-observability",
+              "how-to/langtrace-observability",
+              "how-to/mlflow-observability",
+              "how-to/openlit-observability",
+              "how-to/opik-observability",
+              "how-to/portkey-observability",
+              "how-to/weave-integration"
+            ]
+          },
+          {
+            "group": "Learn",
+            "pages": [
+              "how-to/conditional-tasks",
+              "how-to/coding-agents",
+              "how-to/create-custom-tools",
+              "how-to/custom-llm",
+              "how-to/custom-manager-agent",
+              "how-to/customizing-agents",
+              "how-to/force-tool-output-as-result",
+              "how-to/hierarchical-process",
+              "how-to/human-input-on-execution",
+              "how-to/kickoff-async",
+              "how-to/kickoff-for-each",
+              "how-to/llm-connections",
+              "how-to/multimodal-agents",
+              "how-to/replay-tasks-from-latest-crew-kickoff",
+              "how-to/sequential-process"
+            ]
+          },
           {
             "group": "Telemetry",
             "pages": [
@@ -188,19 +190,35 @@
             ]
           }
         ]
+      },
+      {
+        "tab": "Releases",
+        "groups": [
+          {
+            "group": "Releases",
+            "pages": [
+              "changelog"
+            ]
+          }
+        ]
       }
     ],
     "global": {
       "anchors": [
         {
-          "anchor": "Community",
+          "anchor": "Website",
+          "href": "https://crewai.com",
+          "icon": "globe"
+        },
+        {
+          "anchor": "Forum",
           "href": "https://community.crewai.com",
           "icon": "discourse"
         },
         {
-          "anchor": "Tutorials",
-          "href": "https://www.youtube.com/@crewAIInc",
-          "icon": "youtube"
+          "anchor": "Get Help",
+          "href": "mailto:support@crewai.com",
+          "icon": "headset"
         }
       ]
     }
@@ -214,6 +232,12 @@
     "strict": false
   },
   "navbar": {
+    "links": [
+      {
+        "label": "Start Free Trial",
+        "href": "https://app.crewai.com"
+      }
+    ],
     "primary": {
       "type": "github",
       "href": "https://github.com/crewAIInc/crewAI"
@@ -223,7 +247,12 @@
     "prompt": "Search CrewAI docs"
   },
   "seo": {
-    "indexing": "navigable"
+    "indexing": "all"
+  },
+  "errors": {
+    "404": {
+      "redirect": true
+    }
   },
   "footer": {
     "socials": {

docs/how-to/custom-llm.mdx

@@ -1,9 +1,13 @@
-# Custom LLM Implementations
+---
+title: Custom LLM Implementation
+description: Learn how to create custom LLM implementations in CrewAI.
+icon: code
+---
+
+## Custom LLM Implementations
 
 CrewAI now supports custom LLM implementations through the `BaseLLM` abstract base class. This allows you to create your own LLM implementations that don't rely on litellm's authentication mechanism.
 
-## Using Custom LLM Implementations
-
 To create a custom LLM implementation, you need to:
 
 1. Inherit from the `BaseLLM` abstract base class

docs/how-to/custom-manager-agent.mdx

@@ -1,5 +1,5 @@
 ---
-title: Create Your Own Manager Agent
+title: Custom Manager Agent
 description: Learn how to set a custom agent as the manager in CrewAI, providing more control over task management and coordination.
 icon: user-shield
 ---

docs/how-to/replay-tasks-from-latest-crew-kickoff.mdx

@@ -20,10 +20,8 @@ Here's an example of how to replay from a task:
 To use the replay feature, follow these steps:
 
 <Steps>
-   <Step title="Open your terminal or command prompt.">
-   </Step>
-   <Step title="Navigate to the directory where your CrewAI project is located.">
-   </Step>
+   <Step title="Open your terminal or command prompt."></Step>
+   <Step title="Navigate to the directory where your CrewAI project is located."></Step>
    <Step title="Run the following commands:">
       To view the latest kickoff task_ids use:
 

docs/quickstart.mdx

@@ -336,9 +336,22 @@ email_summarizer_task:
       - research_task
 ```
 
-## Deploying Your Project
+## Deploying Your Crew
 
-The easiest way to deploy your crew is through [CrewAI Enterprise](http://app.crewai.com), where you can deploy your crew in a few clicks.
+The easiest way to deploy your crew to production is through [CrewAI Enterprise](http://app.crewai.com).
+
+Watch this video tutorial for a step-by-step demonstration of deploying your crew to [CrewAI Enterprise](http://app.crewai.com) using the CLI.
+
+<iframe
+  width="100%"
+  height="400"
+  src="https://www.youtube.com/embed/3EqSV-CYDZA"
+  title="CrewAI Deployment Guide"
+  frameborder="0"
+  style={{ borderRadius: '10px' }}
+  allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+  allowfullscreen
+></iframe>
 
 <CardGroup cols={2}>
   <Card

docs/tools/langchaintool.mdx

@@ -1,10 +1,10 @@
 ---
-title: Using LangChain Tools
-description: Learn how to integrate LangChain tools with CrewAI agents to enhance search-based queries and more.
+title: LangChain Tool
+description: The `LangChainTool` is a wrapper for LangChain tools and query engines.
 icon: link
 ---
 
-## Using LangChain Tools
+## `LangChainTool`
 
 <Info>
     CrewAI seamlessly integrates with LangChain's comprehensive [list of tools](https://python.langchain.com/docs/integrations/tools/), all of which can be used with CrewAI.

src/crewai/agent.py

@@ -114,6 +114,14 @@ class Agent(BaseAgent):
         default=None,
         description="Embedder configuration for the agent.",
     )
+    agent_knowledge_context: Optional[str] = Field(
+        default=None,
+        description="Knowledge context for the agent.",
+    )
+    crew_knowledge_context: Optional[str] = Field(
+        default=None,
+        description="Knowledge context for the crew.",
+    )
 
     @model_validator(mode="after")
     def post_init_setup(self):
@@ -177,7 +185,7 @@ class Agent(BaseAgent):
         self,
         task: Task,
         context: Optional[str] = None,
-        tools: Optional[List[BaseTool]] = None,
+        tools: Optional[List[BaseTool]] = None
     ) -> str:
         """Execute a task with the agent.
 
@@ -188,6 +196,11 @@ class Agent(BaseAgent):
 
         Returns:
             Output of the agent
+
+        Raises:
+            TimeoutError: If execution exceeds the maximum execution time.
+            ValueError: If the max execution time is not a positive integer.
+            RuntimeError: If the agent execution fails for other reasons.
         """
         if self.tools_handler:
             self.tools_handler.last_used_tool = {}  # type: ignore # Incompatible types in assignment (expression has type "dict[Never, Never]", variable has type "ToolCalling")
@@ -229,22 +242,30 @@ class Agent(BaseAgent):
             memory = contextual_memory.build_context_for_task(task, context)
             if memory.strip() != "":
                 task_prompt += self.i18n.slice("memory").format(memory=memory)
-
+        knowledge_config = (
+            self.knowledge_config.model_dump() if self.knowledge_config else {}
+        )
         if self.knowledge:
-            agent_knowledge_snippets = self.knowledge.query([task.prompt()])
+            agent_knowledge_snippets = self.knowledge.query(
+                [task.prompt()], **knowledge_config
+            )
             if agent_knowledge_snippets:
-                agent_knowledge_context = extract_knowledge_context(
+                self.agent_knowledge_context = extract_knowledge_context(
                     agent_knowledge_snippets
                 )
-                if agent_knowledge_context:
-                    task_prompt += agent_knowledge_context
+                if self.agent_knowledge_context:
+                    task_prompt += self.agent_knowledge_context
 
         if self.crew:
-            knowledge_snippets = self.crew.query_knowledge([task.prompt()])
+            knowledge_snippets = self.crew.query_knowledge(
+                [task.prompt()], **knowledge_config
+            )
             if knowledge_snippets:
-                crew_knowledge_context = extract_knowledge_context(knowledge_snippets)
-                if crew_knowledge_context:
-                    task_prompt += crew_knowledge_context
+                self.crew_knowledge_context = extract_knowledge_context(
+                    knowledge_snippets
+                )
+                if self.crew_knowledge_context:
+                    task_prompt += self.crew_knowledge_context
 
         tools = tools or self.tools or []
         self.create_agent_executor(tools=tools, task=task)
@@ -264,14 +285,26 @@ class Agent(BaseAgent):
                     task=task,
                 ),
             )
-            result = self.agent_executor.invoke(
-                {
-                    "input": task_prompt,
-                    "tool_names": self.agent_executor.tools_names,
-                    "tools": self.agent_executor.tools_description,
-                    "ask_for_human_input": task.human_input,
-                }
-            )["output"]
+
+            # Determine execution method based on timeout setting
+            if self.max_execution_time is not None:
+                if not isinstance(self.max_execution_time, int) or self.max_execution_time <= 0:
+                    raise ValueError("Max Execution time must be a positive integer greater than zero")
+                result = self._execute_with_timeout(task_prompt, task, self.max_execution_time)
+            else:
+                result = self._execute_without_timeout(task_prompt, task)
+                
+        except TimeoutError as e:
+            # Propagate TimeoutError without retry
+            crewai_event_bus.emit(
+                self,
+                event=AgentExecutionErrorEvent(
+                    agent=self,
+                    task=task,
+                    error=str(e),
+                ),
+            )
+            raise e
         except Exception as e:
             if e.__class__.__module__.startswith("litellm"):
                 # Do not retry on litellm errors
@@ -312,6 +345,66 @@ class Agent(BaseAgent):
         )
         return result
 
+    def _execute_with_timeout(
+        self,
+        task_prompt: str,
+        task: Task,
+        timeout: int
+    ) -> str:
+        """Execute a task with a timeout.
+        
+        Args:
+            task_prompt: The prompt to send to the agent.
+            task: The task being executed.
+            timeout: Maximum execution time in seconds.
+            
+        Returns:
+            The output of the agent.
+            
+        Raises:
+            TimeoutError: If execution exceeds the timeout.
+            RuntimeError: If execution fails for other reasons.
+        """
+        import concurrent.futures
+        with concurrent.futures.ThreadPoolExecutor() as executor:
+            future = executor.submit(
+                self._execute_without_timeout,
+                task_prompt=task_prompt,
+                task=task
+            )
+            
+            try:
+                return future.result(timeout=timeout)
+            except concurrent.futures.TimeoutError:
+                future.cancel()
+                raise TimeoutError(f"Task '{task.description}' execution timed out after {timeout} seconds. Consider increasing max_execution_time or optimizing the task.")
+            except Exception as e:
+                future.cancel()
+                raise RuntimeError(f"Task execution failed: {str(e)}")
+
+    def _execute_without_timeout(
+        self,
+        task_prompt: str,
+        task: Task
+    ) -> str:
+        """Execute a task without a timeout.
+        
+        Args:
+            task_prompt: The prompt to send to the agent.
+            task: The task being executed.
+            
+        Returns:
+            The output of the agent.
+        """
+        return self.agent_executor.invoke(
+            {
+                "input": task_prompt,
+                "tool_names": self.agent_executor.tools_names,
+                "tools": self.agent_executor.tools_description,
+                "ask_for_human_input": task.human_input,
+            }
+        )["output"]
+
     def create_agent_executor(
         self, tools: Optional[List[BaseTool]] = None, task=None
     ) -> None:

src/crewai/agents/agent_builder/base_agent.py

@@ -19,6 +19,7 @@ from crewai.agents.agent_builder.utilities.base_token_process import TokenProces
 from crewai.agents.cache.cache_handler import CacheHandler
 from crewai.agents.tools_handler import ToolsHandler
 from crewai.knowledge.knowledge import Knowledge
+from crewai.knowledge.knowledge_config import KnowledgeConfig
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.security.security_config import SecurityConfig
 from crewai.tools.base_tool import BaseTool, Tool
@@ -155,6 +156,10 @@ class BaseAgent(ABC, BaseModel):
     adapted_agent: bool = Field(
         default=False, description="Whether the agent is adapted"
     )
+    knowledge_config: Optional[KnowledgeConfig] = Field(
+        default=None,
+        description="Knowledge configuration for the agent such as limits and threshold",
+    )
 
     @model_validator(mode="before")
     @classmethod

src/crewai/cli/tools/main.py

@@ -117,7 +117,9 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
 
         published_handle = publish_response.json()["handle"]
         console.print(
-            f"Successfully published {published_handle} ({project_version}).\nInstall it in other projects with crewai tool install {published_handle}",
+            f"Successfully published `{published_handle}` ({project_version}).\n\n"
+            + "⚠️ Security checks are running in the background. Your tool will be available once these are complete.\n"
+            + f"You can monitor the status or access your tool here:\nhttps://app.crewai.com/crewai_plus/tools/{published_handle}",
             style="bold green",
         )
 
@@ -153,8 +155,12 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
         login_response_json = login_response.json()
 
         settings = Settings()
-        settings.tool_repository_username = login_response_json["credential"]["username"]
-        settings.tool_repository_password = login_response_json["credential"]["password"]
+        settings.tool_repository_username = login_response_json["credential"][
+            "username"
+        ]
+        settings.tool_repository_password = login_response_json["credential"][
+            "password"
+        ]
         settings.dump()
 
         console.print(
@@ -179,7 +185,7 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
             capture_output=False,
             env=self._build_env_with_credentials(repository_handle),
             text=True,
-            check=True
+            check=True,
         )
 
         if add_package_result.stderr:
@@ -204,7 +210,11 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
         settings = Settings()
 
         env = os.environ.copy()
-        env[f"UV_INDEX_{repository_handle}_USERNAME"] = str(settings.tool_repository_username or "")
-        env[f"UV_INDEX_{repository_handle}_PASSWORD"] = str(settings.tool_repository_password or "")
+        env[f"UV_INDEX_{repository_handle}_USERNAME"] = str(
+            settings.tool_repository_username or ""
+        )
+        env[f"UV_INDEX_{repository_handle}_PASSWORD"] = str(
+            settings.tool_repository_password or ""
+        )
 
         return env

src/crewai/crew.py

@@ -304,9 +304,7 @@ class Crew(BaseModel):
         """Initialize private memory attributes."""
         self._external_memory = (
             # External memory doesn’t support a default value since it was designed to be managed entirely externally
-            self.external_memory.set_crew(self)
-            if self.external_memory
-            else None
+            self.external_memory.set_crew(self) if self.external_memory else None
         )
 
         self._long_term_memory = self.long_term_memory
@@ -1136,9 +1134,13 @@ class Crew(BaseModel):
         result = self._execute_tasks(self.tasks, start_index, True)
         return result
 
-    def query_knowledge(self, query: List[str]) -> Union[List[Dict[str, Any]], None]:
+    def query_knowledge(
+        self, query: List[str], results_limit: int = 3, score_threshold: float = 0.35
+    ) -> Union[List[Dict[str, Any]], None]:
         if self.knowledge:
-            return self.knowledge.query(query)
+            return self.knowledge.query(
+                query, results_limit=results_limit, score_threshold=score_threshold
+            )
         return None
 
     def fetch_inputs(self) -> Set[str]:
@@ -1220,9 +1222,13 @@ class Crew(BaseModel):
         copied_data = self.model_dump(exclude=exclude)
         copied_data = {k: v for k, v in copied_data.items() if v is not None}
         if self.short_term_memory:
-            copied_data["short_term_memory"] = self.short_term_memory.model_copy(deep=True)
+            copied_data["short_term_memory"] = self.short_term_memory.model_copy(
+                deep=True
+            )
         if self.long_term_memory:
-            copied_data["long_term_memory"] = self.long_term_memory.model_copy(deep=True)
+            copied_data["long_term_memory"] = self.long_term_memory.model_copy(
+                deep=True
+            )
         if self.entity_memory:
             copied_data["entity_memory"] = self.entity_memory.model_copy(deep=True)
         if self.external_memory:
@@ -1230,7 +1236,6 @@ class Crew(BaseModel):
         if self.user_memory:
             copied_data["user_memory"] = self.user_memory.model_copy(deep=True)
 
-
         copied_data.pop("agents", None)
         copied_data.pop("tasks", None)
 
@@ -1403,7 +1408,10 @@ class Crew(BaseModel):
             "short": (getattr(self, "_short_term_memory", None), "short term"),
             "entity": (getattr(self, "_entity_memory", None), "entity"),
             "knowledge": (getattr(self, "knowledge", None), "knowledge"),
-            "kickoff_outputs": (getattr(self, "_task_output_handler", None), "task output"),
+            "kickoff_outputs": (
+                getattr(self, "_task_output_handler", None),
+                "task output",
+            ),
             "external": (getattr(self, "_external_memory", None), "external"),
         }
 

src/crewai/knowledge/knowledge.py

@@ -43,7 +43,9 @@ class Knowledge(BaseModel):
         self.storage.initialize_knowledge_storage()
         self._add_sources()
 
-    def query(self, query: List[str], limit: int = 3) -> List[Dict[str, Any]]:
+    def query(
+        self, query: List[str], results_limit: int = 3, score_threshold: float = 0.35
+    ) -> List[Dict[str, Any]]:
         """
         Query across all knowledge sources to find the most relevant information.
         Returns the top_k most relevant chunks.
@@ -56,7 +58,8 @@ class Knowledge(BaseModel):
 
         results = self.storage.search(
             query,
-            limit,
+            limit=results_limit,
+            score_threshold=score_threshold,
         )
         return results
 

src/crewai/knowledge/knowledge_config.py

@@ -0,0 +1,16 @@
+from pydantic import BaseModel, Field
+
+
+class KnowledgeConfig(BaseModel):
+    """Configuration for knowledge retrieval.
+
+    Args:
+        results_limit (int): The number of relevant documents to return.
+        score_threshold (float): The minimum score for a document to be considered relevant.
+    """
+
+    results_limit: int = Field(default=3, description="The number of results to return")
+    score_threshold: float = Field(
+        default=0.35,
+        description="The minimum score for a result to be considered relevant",
+    )

src/crewai/knowledge/storage/knowledge_storage.py

@@ -4,7 +4,7 @@ import io
 import logging
 import os
 import shutil
-from typing import Any, Dict, List, Optional, Union, cast
+from typing import Any, Dict, List, Optional, Union
 
 import chromadb
 import chromadb.errors

tests/agent_test.py

@@ -10,6 +10,8 @@ from crewai import Agent, Crew, Task
 from crewai.agents.cache import CacheHandler
 from crewai.agents.crew_agent_executor import AgentFinish, CrewAgentExecutor
 from crewai.agents.parser import CrewAgentParser, OutputParserException
+from crewai.knowledge.knowledge import Knowledge
+from crewai.knowledge.knowledge_config import KnowledgeConfig
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
 from crewai.llm import LLM
@@ -259,7 +261,9 @@ def test_cache_hitting():
     def handle_tool_end(source, event):
         received_events.append(event)
 
-    with (patch.object(CacheHandler, "read") as read,):
+    with (
+        patch.object(CacheHandler, "read") as read,
+    ):
         read.return_value = "0"
         task = Task(
             description="What is 2 times 6? Ignore correctness and just return the result of the multiplication tool, you must use the tool.",
@@ -1611,6 +1615,78 @@ def test_agent_with_knowledge_sources():
         assert "red" in result.raw.lower()
 
 
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_agent_with_knowledge_sources_with_query_limit_and_score_threshold():
+    content = "Brandon's favorite color is red and he likes Mexican food."
+    string_source = StringKnowledgeSource(content=content)
+    knowledge_config = KnowledgeConfig(results_limit=10, score_threshold=0.5)
+    with patch(
+        "crewai.knowledge.storage.knowledge_storage.KnowledgeStorage"
+    ) as MockKnowledge:
+        mock_knowledge_instance = MockKnowledge.return_value
+        mock_knowledge_instance.sources = [string_source]
+        mock_knowledge_instance.query.return_value = [{"content": content}]
+        with patch.object(Knowledge, "query") as mock_knowledge_query:
+            agent = Agent(
+                role="Information Agent",
+                goal="Provide information based on knowledge sources",
+                backstory="You have access to specific knowledge sources.",
+                llm=LLM(model="gpt-4o-mini"),
+                knowledge_sources=[string_source],
+                knowledge_config=knowledge_config,
+            )
+            task = Task(
+                description="What is Brandon's favorite color?",
+                expected_output="Brandon's favorite color.",
+                agent=agent,
+            )
+            crew = Crew(agents=[agent], tasks=[task])
+            crew.kickoff()
+
+            assert agent.knowledge is not None
+            mock_knowledge_query.assert_called_once_with(
+                [task.prompt()],
+                **knowledge_config.model_dump(),
+            )
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_agent_with_knowledge_sources_with_query_limit_and_score_threshold_default():
+    content = "Brandon's favorite color is red and he likes Mexican food."
+    string_source = StringKnowledgeSource(content=content)
+    knowledge_config = KnowledgeConfig()
+    with patch(
+        "crewai.knowledge.storage.knowledge_storage.KnowledgeStorage"
+    ) as MockKnowledge:
+        mock_knowledge_instance = MockKnowledge.return_value
+        mock_knowledge_instance.sources = [string_source]
+        mock_knowledge_instance.query.return_value = [{"content": content}]
+        with patch.object(Knowledge, "query") as mock_knowledge_query:
+            string_source = StringKnowledgeSource(content=content)
+            knowledge_config = KnowledgeConfig()
+            agent = Agent(
+                role="Information Agent",
+                goal="Provide information based on knowledge sources",
+                backstory="You have access to specific knowledge sources.",
+                llm=LLM(model="gpt-4o-mini"),
+                knowledge_sources=[string_source],
+                knowledge_config=knowledge_config,
+            )
+            task = Task(
+                description="What is Brandon's favorite color?",
+                expected_output="Brandon's favorite color.",
+                agent=agent,
+            )
+            crew = Crew(agents=[agent], tasks=[task])
+            crew.kickoff()
+
+            assert agent.knowledge is not None
+            mock_knowledge_query.assert_called_once_with(
+                [task.prompt()],
+                **knowledge_config.model_dump(),
+            )
+
+
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_agent_with_knowledge_sources_extensive_role():
     content = "Brandon's favorite color is red and he likes Mexican food."

tests/cassettes/test_agent_with_knowledge_sources_with_query_limit_and_score_threshold.yaml

@@ -0,0 +1,330 @@
+interactions:
+- request:
+    body: '{"input": ["Brandon''s favorite color is red and he likes Mexican food."],
+      "model": "text-embedding-3-small", "encoding_format": "base64"}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '137'
+      content-type:
+      - application/json
+      host:
+      - api.openai.com
+      user-agent:
+      - OpenAI/Python 1.68.2
+      x-stainless-arch:
+      - arm64
+      x-stainless-async:
+      - 'false'
+      x-stainless-lang:
+      - python
+      x-stainless-os:
+      - MacOS
+      x-stainless-package-version:
+      - 1.68.2
+      x-stainless-read-timeout:
+      - '600'
+      x-stainless-retry-count:
+      - '0'
+      x-stainless-runtime:
+      - CPython
+      x-stainless-runtime-version:
+      - 3.12.9
+    method: POST
+    uri: https://api.openai.com/v1/embeddings
+  response:
+    body:
+      string: !!binary |
+        H4sIAAAAAAAAA1SaWw+yPtfmz59Pced/yrwR2bV9zhAQ2UkRFHEymYAiOxHZtEDfvN99ovdkNicm
+        YiNpu1bXdf1W//Nff/7802V1fp/++feff17VOP3z377PHumU/vPvP//9X3/+/Pnzn7/P/29k3mb5
+        41G9i9/w34/V+5Ev//z7D/9/nvzfQf/+889JZZQeb+UOCJHjaQqtRQfv1mXUaf0OTfTuHjx+CvAU
+        CWC/KEik3pNeZScAwr5Zzkgne4Gqd6jX2+oDW3BxGx8nMkfrxaq0GM2PNaV5G6QZM0P1joRJl32W
+        BVuXtTPPo02jZhRX8gjWdj7MgDz2D+wRexhoUHsaTN9P0RfLw5itFrmbCgzCHVFOdx/wQte1qJvK
+        FxH556YeT0pqoJ0RTNhqPwiskhTe0T7qIpzrwS4arGS24D4uc6y90d4VpMq+wy7hntS8mG297p2B
+        QNrwZ5pV1p4RZ6vPEHEPDtuWVA0L/w451CylgPUZBhFvXaQWWqXwwKobdNmavrcCyvDk4aRDezby
+        2c5Hym33obtXgLKlioYGKUfZovrOBtkSu6cOQbHw6POcJoyE+vmMxtegUst+HNh2ZImhpFTNsJ4V
+        73p1XlWO8NsSscGvH7asThqCqtoe6anKt+6SsI0K91Ef0UtGS5dIB8DD3QV2vtwaybB8lksCj5K7
+        pTjWccSrU5igG+hfVOuSRl+4sPGhtJ4Qtfr4w4g0EQcaRfCgnrKxXVFD8hnSZ6jTk5PN9ax4JxU5
+        T/5MsnTwskU6ARNOHnCJYHpsoPbgFfDzsRYaLe9dPbfLoiDTls800h+6vjruXYDSGiGs3fJFXw5Z
+        2APLfh+ok3y2YDvrfQvLm3/x5fPervlV0QUUF5c33aFAzQRua0JwHeCKb5/FGITQVzsgc1KIg6vA
+        Mmo+Xg5CiY/80LSf2UqSFwdOKDHoMVyBvk6jq0DzTRTs1uUHLFui9ciAyYGq8fHOhDqzzoCpgkE9
+        Ta/q9aW/VnRO/IR6zaVjs8DvQ9Q/byvOji+YzUV7ztGHji4+b4t7LZqHuwO9+NRR9aZ0YFFWKQF8
+        oXu+5D2rgfee2RlmG3/CO+mFXbq0SgJ35cGm+JxKjEnnY6vsjlOI9+aSsPUqdSNMj3FBD3qdMHHA
+        UgCXpjj46xaeI6GBnAZtrfZJOLMKLKg6VrDCz5jaF6K6/LjWGpwt36FHS430JTwlHtrvYIL3q03d
+        JUkWDWVaEtKLvglq9sj4HiRDHtFo3yjuyGe2D/nPY8ER4xwmtq/AQtvoptF7rdiAX9jdgRtn7+Bn
+        tJEZJc2GgD4yNZz3YBjWu3ziAaFrhXenYwImk8wNpOrj/M13t+Y7wz/D3/57Lz0b2K1kHixsVceP
+        ztUy8VYyH90e/AbvXU+sGZ8aDnKhc6LWu9nVPJp3CYqztfBbYCn6DDf9CG16+VBf9VswK6seI7h7
+        nqirt5POrDOr4LC/ExoMssgmx6EzlCfv+s2fnS5e3vIM9VeX0YDfaUxs04EHhXb/4KPzJoC1ac2j
+        jeltac5xgc5gd++B3PYI22Bmw1g9KgFZx+cdGynQMv7ilz7yDuFKkP351LMfTiYsJQCpLhIpWguN
+        76FsiVd6cLRJX4LU5qEFOUQdt3OBGCfJHX7PD/x7H+9L1xThHJQYF+HiUrWYe6DvogzvTlKvM6OP
+        EijuT5i01wcF7Pg6QvgK4pZ6vlzo82dzCmBAD4zuU7MfFvypHbRLREZku91ma5+PBfjGjz8e7mbN
+        sFByKDkcInrs5Iv+oVDhoTppJTYI17LVHD4qvBBo4NB9lmyRDuYMt0bqkQWbJZteYsaBUpZNvFf7
+        Su+cVQ5gr6YI+7u3A0Sev83KJowLXyzuwGV7N5jR68Zc6iWPoB71O63gwiqEtU9sR3wq2yG0nPZE
+        ja7fuKuzmQ10PnUctriPysROHCtogQ3D+JPs3O1a1AGULo+SauHJ0XlpX8ZI350yeqCtmjFn4T0w
+        SHyDz/xqg+2xnU3UZWJP7VURXHaDlgBHg8P00NhvfTy2rgqPRM1pvKIjmPwodNDU8neq2ydTZ2O7
+        C1F5qFKKX8PFHRZvXGFV81eaBMou4wcOjzLwbk/qpxe1/uyMoEAmCc4Yl4GQrZzstsgq+Qe9D4cZ
+        LFkbJCg6NjG9Wy8pWzj/3cBY7VSaymuf0eK2jnBXmRE+bZkJlqdp+NAf6gFbh9saPQ/d7Q6siTtg
+        HG1ubDtLnA8/1fuK/TpfXVbO7gijGR7pQ3e2EVPA2qJ170v+FosWWEPf6iBRgI6dku7Z0ianM2Jl
+        scWq4R/Z9qkd2l98YU3isD7z7UuBtw4V9Hbef+pZu2wEEE/3DCdFdXDF6j7NMOmftg99uXDFME1T
+        MCX6SA/OvAGTcm4tlJ1uFoHzsdQZvxHu8BQ+eurtkiXrcuobMLzW2Tf+TCZka+8or+FpYqypDhBU
+        5eahY3a54ftLBzULDTuF0f3t4X2N7+4QGrsUifHG8We0fdXzbCoOQHjzJlwbKFk/umYDMQsqmunt
+        0RUDj2ko+/QP6ofSW19xoDVQUHHuw289YJf3MiM+vwQ+f5Xf9Xw3OwIT3eNwcu59sDruWUBjOQ/f
+        /FPd+V0FDZKlWPrG71Nf1UJvYOyh2R+rUxQxL88D0KnUoeq8sfTV3+cBME6Pid5uPnDXZBOk6Fyf
+        ZRxe02wQd6LdweOknzHu4zYj42WV0P5QddSbjzv3qydMEMutia3sHgOmk0CDnZ5gjO1HEwm9kUsg
+        7R47cu6j7bBWwVlDfsy9sNHXls5jXV+R6sYt3hdSyJZQdAo4dvGeWtHJGeYUpzEUkpzhg3UT6l5c
+        +hVAw4rxJeUfmejpQYAe7+6CdUM4ZGPt2wW4RvRBTtK2rCdD9yE8lUGK3fdJjNa++ljoKDsbsnkN
+        F53pZyeF72U806h3OnfVpwqiOx8+fbEH2F1lv65QNhUrPp6FYGChsUuQ44QG+XyWpu72qOHhmi4W
+        tqSLrI8lfOXwu/4EWcF+WPwK3OHNF2y8++UP90gq6LuCgdXyqkXisl5N+DS3D38cDjOb2LrpQYap
+        R+1XvGckOz8lKB7gGVtNyA9MLeYO1uSe/I1/sm/kM4Q0FPAh4LfR3JwXH+7ulYbNfa6yZdqPBZyK
+        k0b4Q5zrM4hUAscBB/7mUXRgtsU2hJvLcaDhV691b0uDCJ2G2lcS2YqEX/1Q93NMFi0wIuZTJYQf
+        73yhd1Tm7Lee8Fffn2G0YyR5OTMEiiz81cNzNXkWKOjJwLio9IHXmm6Gh06JCVceLPbyo9BCttTY
+        9EGHhz562zGGhnn1iOQLA1jj65BCw5NaelNnkTGzLGcknMDNp+c0ASztKgWN+mZPeLtvXbYTdx0q
+        J5Zh4/OqgNhc5xWl92tMHca9I4L7xEPcqzDopdvfwGLnxxGQ15nhOMWSPj60xoROc8uwNRhwWC9Z
+        pwFXwzufhMctYKdJilFrhyN1JbQOS+ExCV5KMaA4JUUtkkYkcHekId1J23KYPlc8Q6F+nbHpiAYT
+        /H0cgqbY7nF2/SzDeidTAcXus6exvKsznvVVBWzcaVitLu+azP2OQ3nQ3vFR35rDSuswAN/zi6bc
+        0XZnTnvwEOXrlSyXThyW4v7wIS5eDwJvAj98/VGOXpVWUvVkDBnLrZhAr4MTTQ63NXv1JTThZz8D
+        ejZOlc7sgFNgs9SCr4xwBMOK3AQw8bDHTnhQ3fmcOxVQRVvyW+cdZrNw23RQTsuQXvdvEnXCTezg
+        V/9jXyyFYU7eUwC+649x0A/Z2F6bEH52UovvrviKmGQ0AZQjJPn0W8+WROs0eNPGJ/7uV0ZO4baH
+        7MnLOEorLZtruvGgbGw0uie3sl5W89Er6fFc0KvCDpHYEHuGj6zoaWC/FzDSOMqha60ZvcX3ldEw
+        TRN48Z83ImSSP7ztfeijDzftyLwXm2hpa0GFtVFb1Lrtp3q2XC+AN5+38a1Gu2HN1spCfpC5fu1F
+        Klubq05A9zIdvFPfE2P35xIgpQptvAOew8b+Up1RoEUJWVq31L/+xwKdOjk+SIcxG7/+BT6FmMM7
+        3f/UyzbaqlAe8RG7toOG1RtTC87BpyXKc5gzej51K5DTOiTrz3+MrtlC7Xzf0MygOViFneEgTWMG
+        EU/PdqDQxyr4xruvnP2rK1YCSGDPVkbk1dOjNS83IXynuUV2TjYPrBJYgooP4b/1XAbjwB0IspIX
+        wvjrJxfjcW+g/RjI3/zeEsG1ABUqTNAeopppx5CgQx2bRA53Z33xo9SCX/9CQ6fh9NkQtg5U+qnx
+        pcVadfbYvVV4lOwtdV3dHOayuvLwr5442DAah3uoAilsYuqm2Y0xv0g4aDTWilWeXob+5yerbRHS
+        3OMXtvRjl8DoNu588P0/oVlOZyTprMWHT5jUc1xsW8QB80z3NYb6Kk2tBQzz4vmgrZuaeGNooe/+
+        4Hs7hvo69zsICkuT8eGCz7qwSS0Ic1F442P08CIWJ0n+mx/OT3iumXB8KNAk4Zna25HLuqYJKyV/
+        uRXWb29uIHxnqYg7jDmOv/p5xYHTgs/HWbB52PYubV2nAr1xCjEOoxIsFSYQds1B9cEwCvqH65Cn
+        tLkAqblbeMZW2ZxBe3R3hKvzVV/VxvLh6SjVON9fpYg8thcffuOF7le+yJazUUL4He+DMDjWq9AK
+        Ofz6bep/kBmtgfoJwM+P//QSAcPowcpUF2oNZ6zz2+nSwmePI+p847G/eKIJvzzG59zsOKzFsYOQ
+        K7dbrOW2Fq3skRH48rueujh/RYufcwJMQ2nxV0n9AJ7TLgI8vh8G9oZr/eUxZwOs9v74t77MQWMb
+        cFrhAf/4AlnDdwJrkifY9rpZnwu1smBwMix6KRxVF+JFVmFgCasv3MpXtBYPJ4Bf/uR/84P1nlZ7
+        sDrZIba//n972BYB7ByXYrtGZT13ecYB4zNp1N33VT3xaOBgkjCf2l//skRPysHPTmmpcxzLaN4e
+        hgA+5DjA9qrE7rLDyAdAgwrWpdsH9N94Adc0EPGVxRMYXwKRBN1PMVXdwIrGSpzv6PIIbGorh4e+
+        3MP1DrlPevOVIi7ZOp24EH6su4rdp+nqc7o1eoBs74AzdXPK1s/q3OGzmAm9G45c08tbXuGrkUey
+        kblRX81LoMIg2kRkMa4gm8N+nuFq+hrWw/RabzNPWxEHjDPeqWKRfeshgXypxv6WB9eMNRFvIWJ0
+        2pff2GB94EpBT7uoaGRvJDAE6NSDn5/An6TUZ/JZUmgZqkj9n59Mt0YHvTeqMW5QFTFOnnv0KE3g
+        S9JFdsku6EOIL3dINet4ZswwPsbPj1Kz6gX2V/898tsWm5F20lnwVjsISTQS5uAh+/kLkBi+hfeL
+        a4P1Jdkqsh8f8ounaO2yJYeeax+wh5ZTti2ESoDILDVqA61gLdjLCrw/1AjnXaNFQmqqFpJkofzq
+        rXMtPLJDAwf7qpNNGJVs1Squh0shSr5eTWRgnZYoP/5Hf/V9eegnBzk93JJlSSx3+3EH86/+TJxs
+        0sePw2k/v4F97TW7rDrZBuTX8UT98HgBf+P9wlcXapy2a0Q9PQhhnM0FtnxhYKstqykiUS8RepR0
+        ff6ej+jnv9WrEGWdwB9D+OODNnu9o+X1MM8wf9kVVu3rJluaUuNQuz1wVP2spfv14xU0p8ih2lfv
+        j/1pGuH7cYmw7WIXTOZ+10FWVlsif/VmZa3JqHz1IE6Q2mdTzXcK+PmPmzpfmdjbaovW07mmh1sf
+        slwB+wKi+pLjQ35p3JHgYYXvQr3R5+x8shliwwBBWkzU6U6gZkpshYB1Jv7LE8lbEO+wjo869SWv
+        05dVkRQYO+aLajei12xrEg+ixEM07tddLcZJkENjy084v6V3MJfVk4dKTxu6S/U4E19GKoDlnYXY
+        GODodibRq59/95tOWQZi9887hMcW+BsBnrKuv1Qxep42nE8bpGX0OSUdsvqT9NX7N3196dMK3jGT
+        8Y8v0vvF4+DcKcDnC/rK2NVYC9gmUYXNuW3qsTnLPuT4QvnL36gZWjkgVnHF8VDw0ZJ06Rn89OXh
+        y5/nYotm8KwH2R+Ss66z80hWeLZvnb9aj0O09pJigVbYW2TzfG/qL//t4fvVfDCWudFlfc8F4Fuv
+        /RmUj+FvfP/48zGTXH3eo0aA3SFofHFNunruPlao6PcbwCY7qpFgrQGBJ0f18cXakujzOy/uZPTp
+        MVVeTOQbKf/xJh8Yu1GfnFtC/uphR65EMCpVpaLwg2O6D8I3G7n7cIfh5xhT9cu/tk2pwb/n704o
+        5ZrlUOb++m9POIvscxpzD/C6N/scM69s9kdlhPFbcrGfjL07J+uphfkwQiIAS3HZrAQxOoXPHtuq
+        ttdZ6ZxS2NCtgs3XfaOz1H+EEE/jiUZZsNX71wOkcHFaAWP+1X39b5LA5elCbHCtNyyf10xgfUQT
+        tsL2FgkuYHf441Xu+3TNVuUSeSDMjS3+zg9M9ypa4Tk71PjohoW7dNtUhd4hWKm1nwFgr7zI4U9f
+        eN/6Roqu5cBV0yvy+vLHJXx/PAhvpMV6L6VsNHZlBcUYOfiIPM9d3pakKi+xWagfd+eBedIgKXUV
+        E+zue60WY1LeUX1fH4Trmiqa72OmAtDGM7WGjZqtvixX8DQQ++cHojZLzhWyLmSlh52oAvLVI1Ai
+        RPXnznZqwQTOGZJBOn737wAYy9UZXomI/K6Sg4wqh2sMPvsV+Eyyxay5pHsJSmEb00MPqD5yZnqH
+        h13n+gVYAp0gq+GQ8nzr2KrkOXsqr7KFocZdsEfXSm+8/XGEsekH2NIClQnNoUrhV/9hz8nL7Dt/
+        Dfn87OIo0P1sCuaUh6Of8Pi51FM04scpgYdOinE4LZa7ts1gQOsyrth5C3B4r9E5h29gyT48qaK+
+        wh0KfvoIm6P7AsupWCowjKNMjU451bM1cw388lYfda4W8T//8tO3qL40NZ3C4QzltkMkXa5DvV7e
+        xgjD7WVHrbCVo/Vz5Xl4dYMdPnz546/fBNVrfiLsNDZsLTTY/+XBzlu418365DyABK32pQDPOuOC
+        HUGPdRWwffOBvn75E7D3fuRvP2TOft+V3/ltPOOdvrinZw7H10elKh7e+qwr8vyXJ+jLuxx+fAea
+        B9X20bc/Jy7r0wT1W+KoSUI4rHC3DWBQrTr2PmQEM51LE3KPgFDHPmn1ll7VCpW9EhDu64f7Je16
+        CPJDSv/y09/+QXIa8U14V+53fh3gdq5B/Uxn2boeNPJ3v3+8aL7HjgbsVvH9zVqGNVPNWkWFC3yM
+        maeDWZ3SBB57y8YPN1RdsT4ad3iuY5kweZ3YlHnajMjj8PDrxlwZKVgWKN/8JLydsmGcH64FvvyG
+        2l7yqIXJPDXw16+5uJ445C03E7Sl1egPYVHojNJGQy3sK7LVYkVfvL0yg/FWX+h+cT9gDo6z+ePZ
+        1PsQD/A7fbgrWtH09FLWjT7LmRKD24frCT9fB33clpICnVug4PjC37J5rG0Cw3MXUHVBU0buZKqg
+        9pAbIn/95dZpUAKNIvz2x6gwEJl/8Art04akzwyB1VkOFij8JvKRKZbRXDMmwFLv9vj2kMdo2Vyu
+        IXwKZw5rEoEDO5eage7lOyVojsmwGn53/ulzwmXRC3Q/fbbi7o3d8fqu57MUWCiWGxMb57cyrPHE
+        J3Cjdi+q7kUjEz+N3/x4Az7qzjZjiHox9Iz3RL/nq1v20tGAuXUx8SGWnJpwsttA8VE1VK0uh0E0
+        9WsFke0fiJArn+jbLwgB7qwdVvFwcLfpLr//rV93NfV0QZ96CF3zEGMHZCoQxtkq4MtZL1g7GLo7
+        f/UUcJos80EkGy7jnrWKmizkCbt4G7AU94uHCpBSAvNyD2axGTiYB82dgAFag6iatQY3jZZh/Cgs
+        9u0H8gicu+2X56g1PxmbHF6r4ogvQjOBbhaDFZqmusEnutHB+uuH3o2Vo4ar9+58wKqCEsOzsMtX
+        jM03q+pQrfYMHxVniZaW0zuknfPNr75m7CxGBrSLM4+vn2pwl3Qrj8BiRYKdahrc6ZhgCwqaUmNL
+        /zRg+PYf//qLxxBw0fzrXzqiUdCQShyjXz+tpM6QUe/L9+kkXToI1nuGL1qc6uu9VgVk1G6HHRO/
+        f/mz/vgNdpX247L+eWrR1WogVpOyAV9+3EKBozw2/L0BmKy+O0iiTsJJHL0yui0YD6XLsyTAdh71
+        Mj9mH/7zuxXwX//68+d//G4YtN0jf30vBkz5Mv3H/7kq8B/if4xt+nr9vYZAxrTI//n3/76B8M9n
+        6NrP9D+nrsnf4z///rMV/t41+GfqpvT1/z7/1/dV//Wv/wUAAP//AwBcfFVx4CAAAA==
+    headers:
+      CF-RAY:
+      - 931fcf607c16eb34-SJC
+      Connection:
+      - keep-alive
+      Content-Encoding:
+      - gzip
+      Content-Type:
+      - application/json
+      Date:
+      - Thu, 17 Apr 2025 23:47:53 GMT
+      Server:
+      - cloudflare
+      Set-Cookie:
+      - __cf_bm=CncSMPCav.9EJL3emmM0sTqugx5GN6_Oy8JPFBssVho-1744933673-1.0.1.1-Q1XMvHbQdrfEWkkCYeeNHwFdZ1NpjAGJ_0jOUYIk_APelFe7nCanjW_xlOj12b3JQql9.iWQDiHvCeYJDTWkdxnNiMQOEiFMYHX5YZXUuJs;
+        path=/; expires=Fri, 18-Apr-25 00:17:53 GMT; domain=.api.openai.com; HttpOnly;
+        Secure; SameSite=None
+      - _cfuvid=unfPTYCpF5COtm5PuZDuaJqlhefP0iibfjsXHc9lKq0-1744933673515-0.0.1.1-604800000;
+        path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
+      Transfer-Encoding:
+      - chunked
+      X-Content-Type-Options:
+      - nosniff
+      access-control-allow-origin:
+      - '*'
+      access-control-expose-headers:
+      - X-Request-ID
+      alt-svc:
+      - h3=":443"; ma=86400
+      cf-cache-status:
+      - DYNAMIC
+      openai-model:
+      - text-embedding-3-small
+      openai-organization:
+      - crewai-iuxna1
+      openai-processing-ms:
+      - '75'
+      openai-version:
+      - '2020-10-01'
+      strict-transport-security:
+      - max-age=31536000; includeSubDomains; preload
+      via:
+      - envoy-router-8687b6cbdb-4qpmr
+      x-envoy-upstream-service-time:
+      - '46'
+      x-ratelimit-limit-requests:
+      - '10000'
+      x-ratelimit-limit-tokens:
+      - '10000000'
+      x-ratelimit-remaining-requests:
+      - '9999'
+      x-ratelimit-remaining-tokens:
+      - '9999986'
+      x-ratelimit-reset-requests:
+      - 6ms
+      x-ratelimit-reset-tokens:
+      - 0s
+      x-request-id:
+      - req_b8c884a7fe2bd4732903ecbdc632576d
+    status:
+      code: 200
+      message: OK
+- request:
+    body: '{"messages": [{"role": "system", "content": "You are Information Agent.
+      You have access to specific knowledge sources.\nYour personal goal is: Provide
+      information based on knowledge sources\nTo give my best complete final answer
+      to the task respond using the exact following format:\n\nThought: I now can
+      give a great answer\nFinal Answer: Your final answer must be the great and the
+      most complete as possible, it must be outcome described.\n\nI MUST use these
+      formats, my job depends on it!"}, {"role": "user", "content": "\nCurrent Task:
+      What is Brandon''s favorite color?\n\nThis is the expected criteria for your
+      final answer: Brandon''s favorite color.\nyou MUST return the actual complete
+      content as the final answer, not a summary.\n\nBegin! This is VERY important
+      to you, use the tools available and give your best Final Answer, your job depends
+      on it!\n\nThought:"}], "model": "gpt-4o-mini", "stop": ["\nObservation:"]}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '926'
+      content-type:
+      - application/json
+      host:
+      - api.openai.com
+      user-agent:
+      - OpenAI/Python 1.68.2
+      x-stainless-arch:
+      - arm64
+      x-stainless-async:
+      - 'false'
+      x-stainless-lang:
+      - python
+      x-stainless-os:
+      - MacOS
+      x-stainless-package-version:
+      - 1.68.2
+      x-stainless-raw-response:
+      - 'true'
+      x-stainless-read-timeout:
+      - '600.0'
+      x-stainless-retry-count:
+      - '0'
+      x-stainless-runtime:
+      - CPython
+      x-stainless-runtime-version:
+      - 3.12.9
+    method: POST
+    uri: https://api.openai.com/v1/chat/completions
+  response:
+    body:
+      string: !!binary |
+        H4sIAAAAAAAAAwAAAP//jJNNi9swEIbv+RWDLr0ki/NBvm5NYUsplFK29NAuZiKNnWlkjVaSk02X
+        /PdiJxtn2y30YrCeecfvvCM/9QAUG7UEpTeYdOXtYPXp7vbLw7evm4ePmObvt/jrsVgVn9/5dbhj
+        1W8Usv5JOj2rbrRU3lJicSesA2GiputwNpksxuPpbNyCSgzZRlb6NJjIoGLHg1E2mgyy2WA4P6s3
+        wpqiWsL3HgDAU/tsfDpDj2oJWf/5pKIYsSS1vBQBqCC2OVEYI8eELql+B7W4RK61/gGc7EGjg5J3
+        BAhlYxvQxT0FgB/ulh1aeNu+L2EV0BlxbyIUuJPAiUCLlQAcwUkCX68ta3sAI7quyCUywA72bMge
+        AHfIFteWYOtkb8mUBFHqoCneXPsLVNQRm4xcbe0VQOckYZNxm8z9mRwvWVgpfZB1/EOqCnYcN3kg
+        jOKauWMSr1p67AHct5nXL2JUPkjlU55kS+3nhtP5qZ/qVt3R0fQMkyS0V6rFpP9Kv9xQQrbxamtK
+        o96Q6aTdirE2LFegdzX1325e632anF35P+07oDX5RCb3gQzrlxN3ZYGaP+FfZZeUW8MqUtixpjwx
+        hWYThgqs7el+qniIiaq8YFdS8IFPl7TweTZejOajUbbIVO/Y+w0AAP//AwA4a1/QsgMAAA==
+    headers:
+      CF-RAY:
+      - 931fcf649bdbed40-SJC
+      Connection:
+      - keep-alive
+      Content-Encoding:
+      - gzip
+      Content-Type:
+      - application/json
+      Date:
+      - Thu, 17 Apr 2025 23:47:54 GMT
+      Server:
+      - cloudflare
+      Set-Cookie:
+      - __cf_bm=8vySwO0xqpm0u93_1_rXQwTeEIWa2ei3_CD5sAdoo3o-1744933674-1.0.1.1-iqZDpH5poOUp4Rcnhfrb0N2Z0c2662RBiPEcx_gefNW.m3tBA3qyFa8tmFv7PitH8u9vyYK7jxUwy4lPiSi830QWNbTMgCMTbrJ7iaUV7hY;
+        path=/; expires=Fri, 18-Apr-25 00:17:54 GMT; domain=.api.openai.com; HttpOnly;
+        Secure; SameSite=None
+      - _cfuvid=IXAyT8eWpFERM53ngcYNmaqhocfGbOHWSoe7SFNdoGI-1744933674288-0.0.1.1-604800000;
+        path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
+      Transfer-Encoding:
+      - chunked
+      X-Content-Type-Options:
+      - nosniff
+      access-control-expose-headers:
+      - X-Request-ID
+      alt-svc:
+      - h3=":443"; ma=86400
+      cf-cache-status:
+      - DYNAMIC
+      openai-organization:
+      - crewai-iuxna1
+      openai-processing-ms:
+      - '489'
+      openai-version:
+      - '2020-10-01'
+      strict-transport-security:
+      - max-age=31536000; includeSubDomains; preload
+      x-ratelimit-limit-requests:
+      - '30000'
+      x-ratelimit-limit-tokens:
+      - '150000000'
+      x-ratelimit-remaining-requests:
+      - '29999'
+      x-ratelimit-remaining-tokens:
+      - '149999801'
+      x-ratelimit-reset-requests:
+      - 2ms
+      x-ratelimit-reset-tokens:
+      - 0s
+      x-request-id:
+      - req_151f9d0b786f2022f249ee20ea108b43
+    status:
+      code: 200
+      message: OK
+version: 1

tests/cassettes/test_agent_with_knowledge_sources_with_query_limit_and_score_threshold_default.yaml

@@ -0,0 +1,330 @@
+interactions:
+- request:
+    body: '{"input": ["Brandon''s favorite color is red and he likes Mexican food."],
+      "model": "text-embedding-3-small", "encoding_format": "base64"}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '137'
+      content-type:
+      - application/json
+      host:
+      - api.openai.com
+      user-agent:
+      - OpenAI/Python 1.68.2
+      x-stainless-arch:
+      - arm64
+      x-stainless-async:
+      - 'false'
+      x-stainless-lang:
+      - python
+      x-stainless-os:
+      - MacOS
+      x-stainless-package-version:
+      - 1.68.2
+      x-stainless-read-timeout:
+      - '600'
+      x-stainless-retry-count:
+      - '0'
+      x-stainless-runtime:
+      - CPython
+      x-stainless-runtime-version:
+      - 3.12.9
+    method: POST
+    uri: https://api.openai.com/v1/embeddings
+  response:
+    body:
+      string: !!binary |
+        H4sIAAAAAAAAA1SaWw+yPtfmz59Pced/yrwR2bV9zhAQ2UkRFHEymYAiOxHZtEDfvN99ovdkNicm
+        YiNpu1bXdf1W//Nff/7802V1fp/++feff17VOP3z377PHumU/vPvP//9X3/+/Pnzn7/P/29k3mb5
+        41G9i9/w34/V+5Ev//z7D/9/nvzfQf/+889JZZQeb+UOCJHjaQqtRQfv1mXUaf0OTfTuHjx+CvAU
+        CWC/KEik3pNeZScAwr5Zzkgne4Gqd6jX2+oDW3BxGx8nMkfrxaq0GM2PNaV5G6QZM0P1joRJl32W
+        BVuXtTPPo02jZhRX8gjWdj7MgDz2D+wRexhoUHsaTN9P0RfLw5itFrmbCgzCHVFOdx/wQte1qJvK
+        FxH556YeT0pqoJ0RTNhqPwiskhTe0T7qIpzrwS4arGS24D4uc6y90d4VpMq+wy7hntS8mG297p2B
+        QNrwZ5pV1p4RZ6vPEHEPDtuWVA0L/w451CylgPUZBhFvXaQWWqXwwKobdNmavrcCyvDk4aRDezby
+        2c5Hym33obtXgLKlioYGKUfZovrOBtkSu6cOQbHw6POcJoyE+vmMxtegUst+HNh2ZImhpFTNsJ4V
+        73p1XlWO8NsSscGvH7asThqCqtoe6anKt+6SsI0K91Ef0UtGS5dIB8DD3QV2vtwaybB8lksCj5K7
+        pTjWccSrU5igG+hfVOuSRl+4sPGhtJ4Qtfr4w4g0EQcaRfCgnrKxXVFD8hnSZ6jTk5PN9ax4JxU5
+        T/5MsnTwskU6ARNOHnCJYHpsoPbgFfDzsRYaLe9dPbfLoiDTls800h+6vjruXYDSGiGs3fJFXw5Z
+        2APLfh+ok3y2YDvrfQvLm3/x5fPervlV0QUUF5c33aFAzQRua0JwHeCKb5/FGITQVzsgc1KIg6vA
+        Mmo+Xg5CiY/80LSf2UqSFwdOKDHoMVyBvk6jq0DzTRTs1uUHLFui9ciAyYGq8fHOhDqzzoCpgkE9
+        Ta/q9aW/VnRO/IR6zaVjs8DvQ9Q/byvOji+YzUV7ztGHji4+b4t7LZqHuwO9+NRR9aZ0YFFWKQF8
+        oXu+5D2rgfee2RlmG3/CO+mFXbq0SgJ35cGm+JxKjEnnY6vsjlOI9+aSsPUqdSNMj3FBD3qdMHHA
+        UgCXpjj46xaeI6GBnAZtrfZJOLMKLKg6VrDCz5jaF6K6/LjWGpwt36FHS430JTwlHtrvYIL3q03d
+        JUkWDWVaEtKLvglq9sj4HiRDHtFo3yjuyGe2D/nPY8ER4xwmtq/AQtvoptF7rdiAX9jdgRtn7+Bn
+        tJEZJc2GgD4yNZz3YBjWu3ziAaFrhXenYwImk8wNpOrj/M13t+Y7wz/D3/57Lz0b2K1kHixsVceP
+        ztUy8VYyH90e/AbvXU+sGZ8aDnKhc6LWu9nVPJp3CYqztfBbYCn6DDf9CG16+VBf9VswK6seI7h7
+        nqirt5POrDOr4LC/ExoMssgmx6EzlCfv+s2fnS5e3vIM9VeX0YDfaUxs04EHhXb/4KPzJoC1ac2j
+        jeltac5xgc5gd++B3PYI22Bmw1g9KgFZx+cdGynQMv7ilz7yDuFKkP351LMfTiYsJQCpLhIpWguN
+        76FsiVd6cLRJX4LU5qEFOUQdt3OBGCfJHX7PD/x7H+9L1xThHJQYF+HiUrWYe6DvogzvTlKvM6OP
+        EijuT5i01wcF7Pg6QvgK4pZ6vlzo82dzCmBAD4zuU7MfFvypHbRLREZku91ma5+PBfjGjz8e7mbN
+        sFByKDkcInrs5Iv+oVDhoTppJTYI17LVHD4qvBBo4NB9lmyRDuYMt0bqkQWbJZteYsaBUpZNvFf7
+        Su+cVQ5gr6YI+7u3A0Sev83KJowLXyzuwGV7N5jR68Zc6iWPoB71O63gwiqEtU9sR3wq2yG0nPZE
+        ja7fuKuzmQ10PnUctriPysROHCtogQ3D+JPs3O1a1AGULo+SauHJ0XlpX8ZI350yeqCtmjFn4T0w
+        SHyDz/xqg+2xnU3UZWJP7VURXHaDlgBHg8P00NhvfTy2rgqPRM1pvKIjmPwodNDU8neq2ydTZ2O7
+        C1F5qFKKX8PFHRZvXGFV81eaBMou4wcOjzLwbk/qpxe1/uyMoEAmCc4Yl4GQrZzstsgq+Qe9D4cZ
+        LFkbJCg6NjG9Wy8pWzj/3cBY7VSaymuf0eK2jnBXmRE+bZkJlqdp+NAf6gFbh9saPQ/d7Q6siTtg
+        HG1ubDtLnA8/1fuK/TpfXVbO7gijGR7pQ3e2EVPA2qJ170v+FosWWEPf6iBRgI6dku7Z0ianM2Jl
+        scWq4R/Z9qkd2l98YU3isD7z7UuBtw4V9Hbef+pZu2wEEE/3DCdFdXDF6j7NMOmftg99uXDFME1T
+        MCX6SA/OvAGTcm4tlJ1uFoHzsdQZvxHu8BQ+eurtkiXrcuobMLzW2Tf+TCZka+8or+FpYqypDhBU
+        5eahY3a54ftLBzULDTuF0f3t4X2N7+4QGrsUifHG8We0fdXzbCoOQHjzJlwbKFk/umYDMQsqmunt
+        0RUDj2ko+/QP6ofSW19xoDVQUHHuw289YJf3MiM+vwQ+f5Xf9Xw3OwIT3eNwcu59sDruWUBjOQ/f
+        /FPd+V0FDZKlWPrG71Nf1UJvYOyh2R+rUxQxL88D0KnUoeq8sfTV3+cBME6Pid5uPnDXZBOk6Fyf
+        ZRxe02wQd6LdweOknzHu4zYj42WV0P5QddSbjzv3qydMEMutia3sHgOmk0CDnZ5gjO1HEwm9kUsg
+        7R47cu6j7bBWwVlDfsy9sNHXls5jXV+R6sYt3hdSyJZQdAo4dvGeWtHJGeYUpzEUkpzhg3UT6l5c
+        +hVAw4rxJeUfmejpQYAe7+6CdUM4ZGPt2wW4RvRBTtK2rCdD9yE8lUGK3fdJjNa++ljoKDsbsnkN
+        F53pZyeF72U806h3OnfVpwqiOx8+fbEH2F1lv65QNhUrPp6FYGChsUuQ44QG+XyWpu72qOHhmi4W
+        tqSLrI8lfOXwu/4EWcF+WPwK3OHNF2y8++UP90gq6LuCgdXyqkXisl5N+DS3D38cDjOb2LrpQYap
+        R+1XvGckOz8lKB7gGVtNyA9MLeYO1uSe/I1/sm/kM4Q0FPAh4LfR3JwXH+7ulYbNfa6yZdqPBZyK
+        k0b4Q5zrM4hUAscBB/7mUXRgtsU2hJvLcaDhV691b0uDCJ2G2lcS2YqEX/1Q93NMFi0wIuZTJYQf
+        73yhd1Tm7Lee8Fffn2G0YyR5OTMEiiz81cNzNXkWKOjJwLio9IHXmm6Gh06JCVceLPbyo9BCttTY
+        9EGHhz562zGGhnn1iOQLA1jj65BCw5NaelNnkTGzLGcknMDNp+c0ASztKgWN+mZPeLtvXbYTdx0q
+        J5Zh4/OqgNhc5xWl92tMHca9I4L7xEPcqzDopdvfwGLnxxGQ15nhOMWSPj60xoROc8uwNRhwWC9Z
+        pwFXwzufhMctYKdJilFrhyN1JbQOS+ExCV5KMaA4JUUtkkYkcHekId1J23KYPlc8Q6F+nbHpiAYT
+        /H0cgqbY7nF2/SzDeidTAcXus6exvKsznvVVBWzcaVitLu+azP2OQ3nQ3vFR35rDSuswAN/zi6bc
+        0XZnTnvwEOXrlSyXThyW4v7wIS5eDwJvAj98/VGOXpVWUvVkDBnLrZhAr4MTTQ63NXv1JTThZz8D
+        ejZOlc7sgFNgs9SCr4xwBMOK3AQw8bDHTnhQ3fmcOxVQRVvyW+cdZrNw23RQTsuQXvdvEnXCTezg
+        V/9jXyyFYU7eUwC+649x0A/Z2F6bEH52UovvrviKmGQ0AZQjJPn0W8+WROs0eNPGJ/7uV0ZO4baH
+        7MnLOEorLZtruvGgbGw0uie3sl5W89Er6fFc0KvCDpHYEHuGj6zoaWC/FzDSOMqha60ZvcX3ldEw
+        TRN48Z83ImSSP7ztfeijDzftyLwXm2hpa0GFtVFb1Lrtp3q2XC+AN5+38a1Gu2HN1spCfpC5fu1F
+        Klubq05A9zIdvFPfE2P35xIgpQptvAOew8b+Up1RoEUJWVq31L/+xwKdOjk+SIcxG7/+BT6FmMM7
+        3f/UyzbaqlAe8RG7toOG1RtTC87BpyXKc5gzej51K5DTOiTrz3+MrtlC7Xzf0MygOViFneEgTWMG
+        EU/PdqDQxyr4xruvnP2rK1YCSGDPVkbk1dOjNS83IXynuUV2TjYPrBJYgooP4b/1XAbjwB0IspIX
+        wvjrJxfjcW+g/RjI3/zeEsG1ABUqTNAeopppx5CgQx2bRA53Z33xo9SCX/9CQ6fh9NkQtg5U+qnx
+        pcVadfbYvVV4lOwtdV3dHOayuvLwr5442DAah3uoAilsYuqm2Y0xv0g4aDTWilWeXob+5yerbRHS
+        3OMXtvRjl8DoNu588P0/oVlOZyTprMWHT5jUc1xsW8QB80z3NYb6Kk2tBQzz4vmgrZuaeGNooe/+
+        4Hs7hvo69zsICkuT8eGCz7qwSS0Ic1F442P08CIWJ0n+mx/OT3iumXB8KNAk4Zna25HLuqYJKyV/
+        uRXWb29uIHxnqYg7jDmOv/p5xYHTgs/HWbB52PYubV2nAr1xCjEOoxIsFSYQds1B9cEwCvqH65Cn
+        tLkAqblbeMZW2ZxBe3R3hKvzVV/VxvLh6SjVON9fpYg8thcffuOF7le+yJazUUL4He+DMDjWq9AK
+        Ofz6bep/kBmtgfoJwM+P//QSAcPowcpUF2oNZ6zz2+nSwmePI+p847G/eKIJvzzG59zsOKzFsYOQ
+        K7dbrOW2Fq3skRH48rueujh/RYufcwJMQ2nxV0n9AJ7TLgI8vh8G9oZr/eUxZwOs9v74t77MQWMb
+        cFrhAf/4AlnDdwJrkifY9rpZnwu1smBwMix6KRxVF+JFVmFgCasv3MpXtBYPJ4Bf/uR/84P1nlZ7
+        sDrZIba//n972BYB7ByXYrtGZT13ecYB4zNp1N33VT3xaOBgkjCf2l//skRPysHPTmmpcxzLaN4e
+        hgA+5DjA9qrE7rLDyAdAgwrWpdsH9N94Adc0EPGVxRMYXwKRBN1PMVXdwIrGSpzv6PIIbGorh4e+
+        3MP1DrlPevOVIi7ZOp24EH6su4rdp+nqc7o1eoBs74AzdXPK1s/q3OGzmAm9G45c08tbXuGrkUey
+        kblRX81LoMIg2kRkMa4gm8N+nuFq+hrWw/RabzNPWxEHjDPeqWKRfeshgXypxv6WB9eMNRFvIWJ0
+        2pff2GB94EpBT7uoaGRvJDAE6NSDn5/An6TUZ/JZUmgZqkj9n59Mt0YHvTeqMW5QFTFOnnv0KE3g
+        S9JFdsku6EOIL3dINet4ZswwPsbPj1Kz6gX2V/898tsWm5F20lnwVjsISTQS5uAh+/kLkBi+hfeL
+        a4P1Jdkqsh8f8ounaO2yJYeeax+wh5ZTti2ESoDILDVqA61gLdjLCrw/1AjnXaNFQmqqFpJkofzq
+        rXMtPLJDAwf7qpNNGJVs1Squh0shSr5eTWRgnZYoP/5Hf/V9eegnBzk93JJlSSx3+3EH86/+TJxs
+        0sePw2k/v4F97TW7rDrZBuTX8UT98HgBf+P9wlcXapy2a0Q9PQhhnM0FtnxhYKstqykiUS8RepR0
+        ff6ej+jnv9WrEGWdwB9D+OODNnu9o+X1MM8wf9kVVu3rJluaUuNQuz1wVP2spfv14xU0p8ih2lfv
+        j/1pGuH7cYmw7WIXTOZ+10FWVlsif/VmZa3JqHz1IE6Q2mdTzXcK+PmPmzpfmdjbaovW07mmh1sf
+        slwB+wKi+pLjQ35p3JHgYYXvQr3R5+x8shliwwBBWkzU6U6gZkpshYB1Jv7LE8lbEO+wjo869SWv
+        05dVkRQYO+aLajei12xrEg+ixEM07tddLcZJkENjy084v6V3MJfVk4dKTxu6S/U4E19GKoDlnYXY
+        GODodibRq59/95tOWQZi9887hMcW+BsBnrKuv1Qxep42nE8bpGX0OSUdsvqT9NX7N3196dMK3jGT
+        8Y8v0vvF4+DcKcDnC/rK2NVYC9gmUYXNuW3qsTnLPuT4QvnL36gZWjkgVnHF8VDw0ZJ06Rn89OXh
+        y5/nYotm8KwH2R+Ss66z80hWeLZvnb9aj0O09pJigVbYW2TzfG/qL//t4fvVfDCWudFlfc8F4Fuv
+        /RmUj+FvfP/48zGTXH3eo0aA3SFofHFNunruPlao6PcbwCY7qpFgrQGBJ0f18cXakujzOy/uZPTp
+        MVVeTOQbKf/xJh8Yu1GfnFtC/uphR65EMCpVpaLwg2O6D8I3G7n7cIfh5xhT9cu/tk2pwb/n704o
+        5ZrlUOb++m9POIvscxpzD/C6N/scM69s9kdlhPFbcrGfjL07J+uphfkwQiIAS3HZrAQxOoXPHtuq
+        ttdZ6ZxS2NCtgs3XfaOz1H+EEE/jiUZZsNX71wOkcHFaAWP+1X39b5LA5elCbHCtNyyf10xgfUQT
+        tsL2FgkuYHf441Xu+3TNVuUSeSDMjS3+zg9M9ypa4Tk71PjohoW7dNtUhd4hWKm1nwFgr7zI4U9f
+        eN/6Roqu5cBV0yvy+vLHJXx/PAhvpMV6L6VsNHZlBcUYOfiIPM9d3pakKi+xWagfd+eBedIgKXUV
+        E+zue60WY1LeUX1fH4Trmiqa72OmAtDGM7WGjZqtvixX8DQQ++cHojZLzhWyLmSlh52oAvLVI1Ai
+        RPXnznZqwQTOGZJBOn737wAYy9UZXomI/K6Sg4wqh2sMPvsV+Eyyxay5pHsJSmEb00MPqD5yZnqH
+        h13n+gVYAp0gq+GQ8nzr2KrkOXsqr7KFocZdsEfXSm+8/XGEsekH2NIClQnNoUrhV/9hz8nL7Dt/
+        Dfn87OIo0P1sCuaUh6Of8Pi51FM04scpgYdOinE4LZa7ts1gQOsyrth5C3B4r9E5h29gyT48qaK+
+        wh0KfvoIm6P7AsupWCowjKNMjU451bM1cw388lYfda4W8T//8tO3qL40NZ3C4QzltkMkXa5DvV7e
+        xgjD7WVHrbCVo/Vz5Xl4dYMdPnz546/fBNVrfiLsNDZsLTTY/+XBzlu418365DyABK32pQDPOuOC
+        HUGPdRWwffOBvn75E7D3fuRvP2TOft+V3/ltPOOdvrinZw7H10elKh7e+qwr8vyXJ+jLuxx+fAea
+        B9X20bc/Jy7r0wT1W+KoSUI4rHC3DWBQrTr2PmQEM51LE3KPgFDHPmn1ll7VCpW9EhDu64f7Je16
+        CPJDSv/y09/+QXIa8U14V+53fh3gdq5B/Uxn2boeNPJ3v3+8aL7HjgbsVvH9zVqGNVPNWkWFC3yM
+        maeDWZ3SBB57y8YPN1RdsT4ad3iuY5kweZ3YlHnajMjj8PDrxlwZKVgWKN/8JLydsmGcH64FvvyG
+        2l7yqIXJPDXw16+5uJ445C03E7Sl1egPYVHojNJGQy3sK7LVYkVfvL0yg/FWX+h+cT9gDo6z+ePZ
+        1PsQD/A7fbgrWtH09FLWjT7LmRKD24frCT9fB33clpICnVug4PjC37J5rG0Cw3MXUHVBU0buZKqg
+        9pAbIn/95dZpUAKNIvz2x6gwEJl/8Art04akzwyB1VkOFij8JvKRKZbRXDMmwFLv9vj2kMdo2Vyu
+        IXwKZw5rEoEDO5eage7lOyVojsmwGn53/ulzwmXRC3Q/fbbi7o3d8fqu57MUWCiWGxMb57cyrPHE
+        J3Cjdi+q7kUjEz+N3/x4Az7qzjZjiHox9Iz3RL/nq1v20tGAuXUx8SGWnJpwsttA8VE1VK0uh0E0
+        9WsFke0fiJArn+jbLwgB7qwdVvFwcLfpLr//rV93NfV0QZ96CF3zEGMHZCoQxtkq4MtZL1g7GLo7
+        f/UUcJos80EkGy7jnrWKmizkCbt4G7AU94uHCpBSAvNyD2axGTiYB82dgAFag6iatQY3jZZh/Cgs
+        9u0H8gicu+2X56g1PxmbHF6r4ogvQjOBbhaDFZqmusEnutHB+uuH3o2Vo4ar9+58wKqCEsOzsMtX
+        jM03q+pQrfYMHxVniZaW0zuknfPNr75m7CxGBrSLM4+vn2pwl3Qrj8BiRYKdahrc6ZhgCwqaUmNL
+        /zRg+PYf//qLxxBw0fzrXzqiUdCQShyjXz+tpM6QUe/L9+kkXToI1nuGL1qc6uu9VgVk1G6HHRO/
+        f/mz/vgNdpX247L+eWrR1WogVpOyAV9+3EKBozw2/L0BmKy+O0iiTsJJHL0yui0YD6XLsyTAdh71
+        Mj9mH/7zuxXwX//68+d//G4YtN0jf30vBkz5Mv3H/7kq8B/if4xt+nr9vYZAxrTI//n3/76B8M9n
+        6NrP9D+nrsnf4z///rMV/t41+GfqpvT1/z7/1/dV//Wv/wUAAP//AwBcfFVx4CAAAA==
+    headers:
+      CF-RAY:
+      - 931fceef786ded38-SJC
+      Connection:
+      - keep-alive
+      Content-Encoding:
+      - gzip
+      Content-Type:
+      - application/json
+      Date:
+      - Thu, 17 Apr 2025 23:47:35 GMT
+      Server:
+      - cloudflare
+      Set-Cookie:
+      - __cf_bm=fj4RMXSXRDQjE2CFC6CGC3dVcJ8cl2Cbu8alijwMHA8-1744933655-1.0.1.1-M3c3AI4XQa.0GJoanNACuOm2aEL4xjqHR1grxIP3olFvq3e0eFHwQTvCF20YwR_OLiMJUH87eNUwgziawMccsxjR9OVZyDr5._5Wts6CrqA;
+        path=/; expires=Fri, 18-Apr-25 00:17:35 GMT; domain=.api.openai.com; HttpOnly;
+        Secure; SameSite=None
+      - _cfuvid=MSkpJsQZtdyIGvrl2mIwy0a_We8H6CIrS7etFgRBl2Y-1744933655703-0.0.1.1-604800000;
+        path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
+      Transfer-Encoding:
+      - chunked
+      X-Content-Type-Options:
+      - nosniff
+      access-control-allow-origin:
+      - '*'
+      access-control-expose-headers:
+      - X-Request-ID
+      alt-svc:
+      - h3=":443"; ma=86400
+      cf-cache-status:
+      - DYNAMIC
+      openai-model:
+      - text-embedding-3-small
+      openai-organization:
+      - crewai-iuxna1
+      openai-processing-ms:
+      - '140'
+      openai-version:
+      - '2020-10-01'
+      strict-transport-security:
+      - max-age=31536000; includeSubDomains; preload
+      via:
+      - envoy-router-84959bbcd5-rzqvq
+      x-envoy-upstream-service-time:
+      - '110'
+      x-ratelimit-limit-requests:
+      - '10000'
+      x-ratelimit-limit-tokens:
+      - '10000000'
+      x-ratelimit-remaining-requests:
+      - '9999'
+      x-ratelimit-remaining-tokens:
+      - '9999986'
+      x-ratelimit-reset-requests:
+      - 6ms
+      x-ratelimit-reset-tokens:
+      - 0s
+      x-request-id:
+      - req_dd3ef61c4765b46ed7db80ddfe261f41
+    status:
+      code: 200
+      message: OK
+- request:
+    body: '{"messages": [{"role": "system", "content": "You are Information Agent.
+      You have access to specific knowledge sources.\nYour personal goal is: Provide
+      information based on knowledge sources\nTo give my best complete final answer
+      to the task respond using the exact following format:\n\nThought: I now can
+      give a great answer\nFinal Answer: Your final answer must be the great and the
+      most complete as possible, it must be outcome described.\n\nI MUST use these
+      formats, my job depends on it!"}, {"role": "user", "content": "\nCurrent Task:
+      What is Brandon''s favorite color?\n\nThis is the expected criteria for your
+      final answer: Brandon''s favorite color.\nyou MUST return the actual complete
+      content as the final answer, not a summary.\n\nBegin! This is VERY important
+      to you, use the tools available and give your best Final Answer, your job depends
+      on it!\n\nThought:"}], "model": "gpt-4o-mini", "stop": ["\nObservation:"]}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      connection:
+      - keep-alive
+      content-length:
+      - '926'
+      content-type:
+      - application/json
+      host:
+      - api.openai.com
+      user-agent:
+      - OpenAI/Python 1.68.2
+      x-stainless-arch:
+      - arm64
+      x-stainless-async:
+      - 'false'
+      x-stainless-lang:
+      - python
+      x-stainless-os:
+      - MacOS
+      x-stainless-package-version:
+      - 1.68.2
+      x-stainless-raw-response:
+      - 'true'
+      x-stainless-read-timeout:
+      - '600.0'
+      x-stainless-retry-count:
+      - '0'
+      x-stainless-runtime:
+      - CPython
+      x-stainless-runtime-version:
+      - 3.12.9
+    method: POST
+    uri: https://api.openai.com/v1/chat/completions
+  response:
+    body:
+      string: !!binary |
+        H4sIAAAAAAAAAwAAAP//jFLBbtswDL37KwhdeokLx0mbOLd2WIAC63YZdthWGIpMO9xkUZDkpEWR
+        fx/kpLG7dUAvBszHR733yOcEQFAlViDUVgbVWp3efv66LvKPRd7Q/f57vtaf7m6ePjze774sv23E
+        JDJ48wtVeGFdKm6txkBsjrByKAPGqdPFfF7MZtdXVz3QcoU60hob0jmnLRlK8yyfp9kinS5P7C2T
+        Qi9W8CMBAHjuv1GnqfBRrCCbvFRa9F42KFbnJgDhWMeKkN6TD9IEMRlAxSag6aXfgeE9KGmgoR2C
+        hCbKBmn8Hh3AT7MmIzXc9P8ruHXSVGwuPNRyx44CgmLNDsjDRnd4OX7GYd15Ga2aTusRII3hIGNU
+        vcGHE3I4W9LcWMcb/xdV1GTIb0uH0rOJ8n1gK3r0kAA89NF1r9IQ1nFrQxn4N/bPTa+Xx3li2NgI
+        LU5g4CD1qL5cTN6YV1YYJGk/Cl8oqbZYDdRhU7KriEdAMnL9r5q3Zh+dk2neM34AlEIbsCqtw4rU
+        a8dDm8N40P9rO6fcCxYe3Y4UloHQxU1UWMtOH89M+CcfsC1rMg066+h4a7Uts1mRL/M8KzKRHJI/
+        AAAA//8DALRhJdF5AwAA
+    headers:
+      CF-Cache-Status:
+      - DYNAMIC
+      CF-RAY:
+      - 931fcef51a67f947-SJC
+      Connection:
+      - keep-alive
+      Content-Encoding:
+      - gzip
+      Content-Type:
+      - application/json
+      Date:
+      - Thu, 17 Apr 2025 23:47:36 GMT
+      Server:
+      - cloudflare
+      Set-Cookie:
+      - __cf_bm=7agwu5JV1OJvEFNhvfvqdgWf.HoMyIni9D85soRl3WE-1744933656-1.0.1.1-dKUwAZnjjuuiswFKWGsxpwHNBJUpjhYlZvfZpyNQIejxEJrXMCppgPvtQ9wa4SKezLmKqftvn_H.bAx_AEFJD2EWm5V6R_uK8.odneErR6A;
+        path=/; expires=Fri, 18-Apr-25 00:17:36 GMT; domain=.api.openai.com; HttpOnly;
+        Secure; SameSite=None
+      - _cfuvid=LdTrzwZYrB6ZyQLY7NdaaHVpDVFvIjYm3arSpNy87wU-1744933656504-0.0.1.1-604800000;
+        path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
+      Transfer-Encoding:
+      - chunked
+      X-Content-Type-Options:
+      - nosniff
+      access-control-expose-headers:
+      - X-Request-ID
+      alt-svc:
+      - h3=":443"; ma=86400
+      openai-organization:
+      - crewai-iuxna1
+      openai-processing-ms:
+      - '540'
+      openai-version:
+      - '2020-10-01'
+      strict-transport-security:
+      - max-age=31536000; includeSubDomains; preload
+      x-ratelimit-limit-requests:
+      - '30000'
+      x-ratelimit-limit-tokens:
+      - '150000000'
+      x-ratelimit-remaining-requests:
+      - '29999'
+      x-ratelimit-remaining-tokens:
+      - '149999802'
+      x-ratelimit-reset-requests:
+      - 2ms
+      x-ratelimit-reset-tokens:
+      - 0s
+      x-request-id:
+      - req_8837be6510731522fd5ac4b75c11d486
+    status:
+      code: 200
+      message: OK
+version: 1

tests/cassettes/test_task_with_max_execution_time.yaml

@@ -0,0 +1,643 @@
+interactions:
+- request:
+    body: '{"messages": [{"role": "system", "content": "You are Researcher. You''re
+      an expert researcher, specialized in technology, software engineering, AI and
+      startups. You work as a freelancer and are now working on doing research and
+      analysis for a new customer.\nYour personal goal is: Make the best research
+      and analysis on content about AI and AI agents. Use the tool provided to you.\nYou
+      ONLY have access to the following tools, and should NEVER make up tools that
+      are not listed here:\n\nTool Name: what amazing tool\nTool Arguments: {}\nTool
+      Description: My tool\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought:
+      you should always think about what to do\nAction: the action to take, only one
+      name of [what amazing tool], just the name, exactly as it''s written.\nAction
+      Input: the input to the action, just a simple JSON object, enclosed in curly
+      braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce
+      all necessary information is gathered, return the following format:\n\n```\nThought:
+      I now know the final answer\nFinal Answer: the final answer to the original
+      input question\n```"}, {"role": "user", "content": "\nCurrent Task: Give me
+      a list of 5 interesting ideas to explore for an article, what makes them unique
+      and interesting.\n\nThis is the expected criteria for your final answer: Bullet
+      point list of 5 interesting ideas.\nyou MUST return the actual complete content
+      as the final answer, not a summary.\n\nBegin! This is VERY important to you,
+      use the tools available and give your best Final Answer, your job depends on
+      it!\n\nThought:"}], "model": "gpt-4o-mini", "stop": ["\nObservation:"]}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate
+      connection:
+      - keep-alive
+      content-length:
+      - '1666'
+      content-type:
+      - application/json
+      host:
+      - api.openai.com
+      user-agent:
+      - OpenAI/Python 1.68.2
+      x-stainless-arch:
+      - arm64
+      x-stainless-async:
+      - 'false'
+      x-stainless-lang:
+      - python
+      x-stainless-os:
+      - MacOS
+      x-stainless-package-version:
+      - 1.68.2
+      x-stainless-raw-response:
+      - 'true'
+      x-stainless-read-timeout:
+      - '600.0'
+      x-stainless-retry-count:
+      - '0'
+      x-stainless-runtime:
+      - CPython
+      x-stainless-runtime-version:
+      - 3.11.12
+    method: POST
+    uri: https://api.openai.com/v1/chat/completions
+  response:
+    content: "{\n  \"id\": \"chatcmpl-BNNPLDDeGQYegE6neZK6ogJmDOMYs\",\n  \"object\":
+      \"chat.completion\",\n  \"created\": 1744911223,\n  \"model\": \"gpt-4o-mini-2024-07-18\",\n
+      \ \"choices\": [\n    {\n      \"index\": 0,\n      \"message\": {\n        \"role\":
+      \"assistant\",\n        \"content\": \"I need to generate interesting ideas
+      for an article related to AI and AI agents. \\n\\nAction: what amazing tool
+      \ \\nAction Input: {}  \",\n        \"refusal\": null,\n        \"annotations\":
+      []\n      },\n      \"logprobs\": null,\n      \"finish_reason\": \"stop\"\n
+      \   }\n  ],\n  \"usage\": {\n    \"prompt_tokens\": 326,\n    \"completion_tokens\":
+      28,\n    \"total_tokens\": 354,\n    \"prompt_tokens_details\": {\n      \"cached_tokens\":
+      0,\n      \"audio_tokens\": 0\n    },\n    \"completion_tokens_details\": {\n
+      \     \"reasoning_tokens\": 0,\n      \"audio_tokens\": 0,\n      \"accepted_prediction_tokens\":
+      0,\n      \"rejected_prediction_tokens\": 0\n    }\n  },\n  \"service_tier\":
+      \"default\",\n  \"system_fingerprint\": \"fp_0392822090\"\n}\n"
+    headers:
+      CF-RAY:
+      - 931dab4c79581b2e-GRU
+      Connection:
+      - keep-alive
+      Content-Encoding:
+      - gzip
+      Content-Type:
+      - application/json
+      Date:
+      - Thu, 17 Apr 2025 17:33:44 GMT
+      Server:
+      - cloudflare
+      Transfer-Encoding:
+      - chunked
+      X-Content-Type-Options:
+      - nosniff
+      access-control-expose-headers:
+      - X-Request-ID
+      alt-svc:
+      - h3=":443"; ma=86400
+      cf-cache-status:
+      - DYNAMIC
+      openai-organization:
+      - crewai-iuxna1
+      openai-processing-ms:
+      - '736'
+      openai-version:
+      - '2020-10-01'
+      strict-transport-security:
+      - max-age=31536000; includeSubDomains; preload
+      x-ratelimit-limit-requests:
+      - '30000'
+      x-ratelimit-limit-tokens:
+      - '150000000'
+      x-ratelimit-remaining-requests:
+      - '29999'
+      x-ratelimit-remaining-tokens:
+      - '149999620'
+      x-ratelimit-reset-requests:
+      - 2ms
+      x-ratelimit-reset-tokens:
+      - 0s
+      x-request-id:
+      - req_0767caa75d1851f392ea34a68763b1bc
+    http_version: HTTP/1.1
+    status_code: 200
+- request:
+    body: !!binary |
+      CqzaAQokCiIKDHNlcnZpY2UubmFtZRISChBjcmV3QUktdGVsZW1ldHJ5EoLaAQoSChBjcmV3YWku
+      dGVsZW1ldHJ5EpYIChAm+VDVVrKTGFLYrGmqyFN/EgiVIKrLvczC6SoMQ3JldyBDcmVhdGVkMAE5
+      uBnOOYMrNxhBWHDXOYMrNxhKGwoOY3Jld2FpX3ZlcnNpb24SCQoHMC4xMTQuMEobCg5weXRob25f
+      dmVyc2lvbhIJCgczLjExLjEySi4KCGNyZXdfa2V5EiIKIDVlNmVmZmU2ODBhNWQ5N2RjMzg3M2Ix
+      NDgyNWNjZmEzSjEKB2NyZXdfaWQSJgokMzI4MzZhOTctMGIyYi00MTAwLTgxZDYtYmIwZWJjY2I2
+      ZDYyShwKDGNyZXdfcHJvY2VzcxIMCgpzZXF1ZW50aWFsShEKC2NyZXdfbWVtb3J5EgIQAEoaChRj
+      cmV3X251bWJlcl9vZl90YXNrcxICGAFKGwoVY3Jld19udW1iZXJfb2ZfYWdlbnRzEgIYAUo6ChBj
+      cmV3X2ZpbmdlcnByaW50EiYKJGQ5YmEwZDE3LTE5YjMtNGQ5Yi04ZTNmLThiMjNhOGM0YzgyM0o7
+      ChtjcmV3X2ZpbmdlcnByaW50X2NyZWF0ZWRfYXQSHAoaMjAyNS0wNC0xN1QxNDozMzo0My4yMzg4
+      MzhKzQIKC2NyZXdfYWdlbnRzEr0CCroCW3sia2V5IjogIjkyZTdlYjE5MTY2NGM5MzU3ODVlZDdk
+      NDI0MGEyOTRkIiwgImlkIjogImMzMWMwNzRmLTg5Y2YtNGRkNi04ZTY2LWM3NDM1OTc0NmNkMSIs
+      ICJyb2xlIjogIlNjb3JlciIsICJ2ZXJib3NlPyI6IGZhbHNlLCAibWF4X2l0ZXIiOiAyNSwgIm1h
+      eF9ycG0iOiBudWxsLCAiZnVuY3Rpb25fY2FsbGluZ19sbG0iOiAiIiwgImxsbSI6ICJncHQtNG8t
+      bWluaSIsICJkZWxlZ2F0aW9uX2VuYWJsZWQ/IjogZmFsc2UsICJhbGxvd19jb2RlX2V4ZWN1dGlv
+      bj8iOiBmYWxzZSwgIm1heF9yZXRyeV9saW1pdCI6IDIsICJ0b29sc19uYW1lcyI6IFtdfV1K+wEK
+      CmNyZXdfdGFza3MS7AEK6QFbeyJrZXkiOiAiMjdlZjM4Y2M5OWRhNGE4ZGVkNzBlZDQwNmU0NGFi
+      ODYiLCAiaWQiOiAiYTNiODU1ODAtZTVjNC00YmU2LWI0ZmItMDU1NDU2Y2RkZWJkIiwgImFzeW5j
+      X2V4ZWN1dGlvbj8iOiBmYWxzZSwgImh1bWFuX2lucHV0PyI6IGZhbHNlLCAiYWdlbnRfcm9sZSI6
+      ICJTY29yZXIiLCAiYWdlbnRfa2V5IjogIjkyZTdlYjE5MTY2NGM5MzU3ODVlZDdkNDI0MGEyOTRk
+      IiwgInRvb2xzX25hbWVzIjogW119XXoCGAGFAQABAAASgAQKED9XhldOUhgSlcVbrT/HuRwSCCF7
+      8YboEaZnKgxUYXNrIENyZWF0ZWQwATlYmeU5gys3GEHwx+c5gys3GEouCghjcmV3X2tleRIiCiA1
+      ZTZlZmZlNjgwYTVkOTdkYzM4NzNiMTQ4MjVjY2ZhM0oxCgdjcmV3X2lkEiYKJDMyODM2YTk3LTBi
+      MmItNDEwMC04MWQ2LWJiMGViY2NiNmQ2MkouCgh0YXNrX2tleRIiCiAyN2VmMzhjYzk5ZGE0YThk
+      ZWQ3MGVkNDA2ZTQ0YWI4NkoxCgd0YXNrX2lkEiYKJGEzYjg1NTgwLWU1YzQtNGJlNi1iNGZiLTA1
+      NTQ1NmNkZGViZEo6ChBjcmV3X2ZpbmdlcnByaW50EiYKJGQ5YmEwZDE3LTE5YjMtNGQ5Yi04ZTNm
+      LThiMjNhOGM0YzgyM0o6ChB0YXNrX2ZpbmdlcnByaW50EiYKJDc0OTEwMDcxLTM1MWQtNDljNy1h
+      YmZlLTJmMWZhNWUzZTEyYko7Cht0YXNrX2ZpbmdlcnByaW50X2NyZWF0ZWRfYXQSHAoaMjAyNS0w
+      NC0xN1QxNDozMzo0My4yMzg4MDFKOwoRYWdlbnRfZmluZ2VycHJpbnQSJgokYzMyNmIyMWUtYWJh
+      YS00N2ZjLWE0NGQtMzk2NTQ4ZjczZTRiegIYAYUBAAEAABKYCAoQH3AbYnQyty/P5gHiJzrjLxII
+      PR8P3tNCS74qDENyZXcgQ3JlYXRlZDABOYgCyj6DKzcYQSD71D6DKzcYShsKDmNyZXdhaV92ZXJz
+      aW9uEgkKBzAuMTE0LjBKGwoOcHl0aG9uX3ZlcnNpb24SCQoHMy4xMS4xMkouCghjcmV3X2tleRIi
+      CiA1ZTZlZmZlNjgwYTVkOTdkYzM4NzNiMTQ4MjVjY2ZhM0oxCgdjcmV3X2lkEiYKJDBkY2JhOGY4
+      LTdhYzQtNDdmMC04ZWIxLWE0ZTJkODFjOGZkYkoeCgxjcmV3X3Byb2Nlc3MSDgoMaGllcmFyY2hp
+      Y2FsShEKC2NyZXdfbWVtb3J5EgIQAEoaChRjcmV3X251bWJlcl9vZl90YXNrcxICGAFKGwoVY3Jl
+      d19udW1iZXJfb2ZfYWdlbnRzEgIYAUo6ChBjcmV3X2ZpbmdlcnByaW50EiYKJDJiYzYzYWE1LWU5
+      YzYtNDAxNi1hMTdiLWFmZDM5ZWJlYmEwNko7ChtjcmV3X2ZpbmdlcnByaW50X2NyZWF0ZWRfYXQS
+      HAoaMjAyNS0wNC0xN1QxNDozMzo0My4zMjI3OTlKzQIKC2NyZXdfYWdlbnRzEr0CCroCW3sia2V5
+      IjogIjkyZTdlYjE5MTY2NGM5MzU3ODVlZDdkNDI0MGEyOTRkIiwgImlkIjogImYyY2Y4YWRlLTdj
+      YmYtNDkwMS1hODMwLWE3ZDkxODA4NjI3NCIsICJyb2xlIjogIlNjb3JlciIsICJ2ZXJib3NlPyI6
+      IGZhbHNlLCAibWF4X2l0ZXIiOiAyNSwgIm1heF9ycG0iOiBudWxsLCAiZnVuY3Rpb25fY2FsbGlu
+      Z19sbG0iOiAiIiwgImxsbSI6ICJncHQtNG8tbWluaSIsICJkZWxlZ2F0aW9uX2VuYWJsZWQ/Ijog
+      ZmFsc2UsICJhbGxvd19jb2RlX2V4ZWN1dGlvbj8iOiBmYWxzZSwgIm1heF9yZXRyeV9saW1pdCI6
+      IDIsICJ0b29sc19uYW1lcyI6IFtdfV1K+wEKCmNyZXdfdGFza3MS7AEK6QFbeyJrZXkiOiAiMjdl
+      ZjM4Y2M5OWRhNGE4ZGVkNzBlZDQwNmU0NGFiODYiLCAiaWQiOiAiMWY3MTljNTktOTJjMC00NGU1
+      LWFmMjUtNzIwYjE1NWE1Njg1IiwgImFzeW5jX2V4ZWN1dGlvbj8iOiBmYWxzZSwgImh1bWFuX2lu
+      cHV0PyI6IGZhbHNlLCAiYWdlbnRfcm9sZSI6ICJTY29yZXIiLCAiYWdlbnRfa2V5IjogIjkyZTdl
+      YjE5MTY2NGM5MzU3ODVlZDdkNDI0MGEyOTRkIiwgInRvb2xzX25hbWVzIjogW119XXoCGAGFAQAB
+      AAASgAQKEIVZhLW3PhEOxntJYQn8IYkSCDNELyrmM+eYKgxUYXNrIENyZWF0ZWQwATlYr+0+gys3
+      GEGIJO4+gys3GEouCghjcmV3X2tleRIiCiA1ZTZlZmZlNjgwYTVkOTdkYzM4NzNiMTQ4MjVjY2Zh
+      M0oxCgdjcmV3X2lkEiYKJDBkY2JhOGY4LTdhYzQtNDdmMC04ZWIxLWE0ZTJkODFjOGZkYkouCgh0
+      YXNrX2tleRIiCiAyN2VmMzhjYzk5ZGE0YThkZWQ3MGVkNDA2ZTQ0YWI4NkoxCgd0YXNrX2lkEiYK
+      JDFmNzE5YzU5LTkyYzAtNDRlNS1hZjI1LTcyMGIxNTVhNTY4NUo6ChBjcmV3X2ZpbmdlcnByaW50
+      EiYKJDJiYzYzYWE1LWU5YzYtNDAxNi1hMTdiLWFmZDM5ZWJlYmEwNko6ChB0YXNrX2ZpbmdlcnBy
+      aW50EiYKJGJmMDU5YjBiLWFlYmYtNGIzMS04YTc4LTA2ZTlmMjcyZDQ2MEo7Cht0YXNrX2Zpbmdl
+      cnByaW50X2NyZWF0ZWRfYXQSHAoaMjAyNS0wNC0xN1QxNDozMzo0My4zMjI3NTVKOwoRYWdlbnRf
+      ZmluZ2VycHJpbnQSJgokY2IzZWQ2ZGQtNzEzNC00YTc3LThiMjctZWIwZGRkZGZlMjdiegIYAYUB
+      AAEAABKdAQoQ6S1CnqyOxKwRN/Vq7X81HRIIso7ugOmXnjEqClRvb2wgVXNhZ2UwATnAIk4/gys3
+      GEE4YlU/gys3GEobCg5jcmV3YWlfdmVyc2lvbhIJCgcwLjExNC4wSigKCXRvb2xfbmFtZRIbChlE
+      ZWxlZ2F0ZSB3b3JrIHRvIGNvd29ya2VySg4KCGF0dGVtcHRzEgIYAXoCGAGFAQABAAASlggKENaM
+      zYnzHCL03v+Ihe5ZidsSCIXobzKG03Z6KgxDcmV3IENyZWF0ZWQwATlQ8uM/gys3GEFIfOk/gys3
+      GEobCg5jcmV3YWlfdmVyc2lvbhIJCgcwLjExNC4wShsKDnB5dGhvbl92ZXJzaW9uEgkKBzMuMTEu
+      MTJKLgoIY3Jld19rZXkSIgogNWU2ZWZmZTY4MGE1ZDk3ZGMzODczYjE0ODI1Y2NmYTNKMQoHY3Jl
+      d19pZBImCiQ5ZmYzZmU1ZC01YmYyLTRlNzEtODU0ZS05OTAyZGYxYzIxYTRKHAoMY3Jld19wcm9j
+      ZXNzEgwKCnNlcXVlbnRpYWxKEQoLY3Jld19tZW1vcnkSAhAAShoKFGNyZXdfbnVtYmVyX29mX3Rh
+      c2tzEgIYAUobChVjcmV3X251bWJlcl9vZl9hZ2VudHMSAhgBSjoKEGNyZXdfZmluZ2VycHJpbnQS
+      JgokOTkwOTQ1YmUtOTczMS00ZTQxLTg5ZDAtYzEzMjljNGQ3NjQ5SjsKG2NyZXdfZmluZ2VycHJp
+      bnRfY3JlYXRlZF9hdBIcChoyMDI1LTA0LTE3VDE0OjMzOjQzLjM0MTIyM0rNAgoLY3Jld19hZ2Vu
+      dHMSvQIKugJbeyJrZXkiOiAiOTJlN2ViMTkxNjY0YzkzNTc4NWVkN2Q0MjQwYTI5NGQiLCAiaWQi
+      OiAiMGM3NDhlNDgtOGNmNC00ZDJhLWFlYWMtZDY5OTUzMDkwZThmIiwgInJvbGUiOiAiU2NvcmVy
+      IiwgInZlcmJvc2U/IjogZmFsc2UsICJtYXhfaXRlciI6IDI1LCAibWF4X3JwbSI6IG51bGwsICJm
+      dW5jdGlvbl9jYWxsaW5nX2xsbSI6ICIiLCAibGxtIjogImdwdC00by1taW5pIiwgImRlbGVnYXRp
+      b25fZW5hYmxlZD8iOiBmYWxzZSwgImFsbG93X2NvZGVfZXhlY3V0aW9uPyI6IGZhbHNlLCAibWF4
+      X3JldHJ5X2xpbWl0IjogMiwgInRvb2xzX25hbWVzIjogW119XUr7AQoKY3Jld190YXNrcxLsAQrp
+      AVt7ImtleSI6ICIyN2VmMzhjYzk5ZGE0YThkZWQ3MGVkNDA2ZTQ0YWI4NiIsICJpZCI6ICI2NzBj
+      MjdhOS1kYTc3LTRhNTQtYmYxYS1mM2M0YjVlNTcwNDkiLCAiYXN5bmNfZXhlY3V0aW9uPyI6IGZh
+      bHNlLCAiaHVtYW5faW5wdXQ/IjogZmFsc2UsICJhZ2VudF9yb2xlIjogIlNjb3JlciIsICJhZ2Vu
+      dF9rZXkiOiAiOTJlN2ViMTkxNjY0YzkzNTc4NWVkN2Q0MjQwYTI5NGQiLCAidG9vbHNfbmFtZXMi
+      OiBbXX1degIYAYUBAAEAABKABAoQ0PunZB/jswUd8i8ahTz20BIIFtRhrWbDsGIqDFRhc2sgQ3Jl
+      YXRlZDABOejM8z+DKzcYQZAu9D+DKzcYSi4KCGNyZXdfa2V5EiIKIDVlNmVmZmU2ODBhNWQ5N2Rj
+      Mzg3M2IxNDgyNWNjZmEzSjEKB2NyZXdfaWQSJgokOWZmM2ZlNWQtNWJmMi00ZTcxLTg1NGUtOTkw
+      MmRmMWMyMWE0Si4KCHRhc2tfa2V5EiIKIDI3ZWYzOGNjOTlkYTRhOGRlZDcwZWQ0MDZlNDRhYjg2
+      SjEKB3Rhc2tfaWQSJgokNjcwYzI3YTktZGE3Ny00YTU0LWJmMWEtZjNjNGI1ZTU3MDQ5SjoKEGNy
+      ZXdfZmluZ2VycHJpbnQSJgokOTkwOTQ1YmUtOTczMS00ZTQxLTg5ZDAtYzEzMjljNGQ3NjQ5SjoK
+      EHRhc2tfZmluZ2VycHJpbnQSJgokMjczZmM3YjYtZGJmYS00MzYyLWEwZTEtNzhhNjJjNDY0OTlh
+      SjsKG3Rhc2tfZmluZ2VycHJpbnRfY3JlYXRlZF9hdBIcChoyMDI1LTA0LTE3VDE0OjMzOjQzLjM0
+      MTE5NUo7ChFhZ2VudF9maW5nZXJwcmludBImCiQwNTc3MWI4Ny04ZGIzLTRhZGYtOWJhZC0yNzcw
+      ZjgzYTZiYTN6AhgBhQEAAQAAEpgIChA5RacttE9X5amPuTPHLuYDEgiZ/RIthMTU5yoMQ3JldyBD
+      cmVhdGVkMAE5EC+lQIMrNxhBsJGsQIMrNxhKGwoOY3Jld2FpX3ZlcnNpb24SCQoHMC4xMTQuMEob
+      Cg5weXRob25fdmVyc2lvbhIJCgczLjExLjEySi4KCGNyZXdfa2V5EiIKIDVlNmVmZmU2ODBhNWQ5
+      N2RjMzg3M2IxNDgyNWNjZmEzSjEKB2NyZXdfaWQSJgokMTc5MzYxNTItNDJmMi00YmY3LWIzOTEt
+      ZTU0MDU1ZTY2NGU4Sh4KDGNyZXdfcHJvY2VzcxIOCgxoaWVyYXJjaGljYWxKEQoLY3Jld19tZW1v
+      cnkSAhAAShoKFGNyZXdfbnVtYmVyX29mX3Rhc2tzEgIYAUobChVjcmV3X251bWJlcl9vZl9hZ2Vu
+      dHMSAhgBSjoKEGNyZXdfZmluZ2VycHJpbnQSJgokNjI0ZTI1NjEtMDFkOC00YmNkLWJhMjEtZDcx
+      ZTQ0MTZkNGJiSjsKG2NyZXdfZmluZ2VycHJpbnRfY3JlYXRlZF9hdBIcChoyMDI1LTA0LTE3VDE0
+      OjMzOjQzLjM1Mzg3M0rNAgoLY3Jld19hZ2VudHMSvQIKugJbeyJrZXkiOiAiOTJlN2ViMTkxNjY0
+      YzkzNTc4NWVkN2Q0MjQwYTI5NGQiLCAiaWQiOiAiYTEyMTFiNmYtMzFhMy00MzY4LWI5YzItZDNh
+      NjA1NTZlOTk2IiwgInJvbGUiOiAiU2NvcmVyIiwgInZlcmJvc2U/IjogZmFsc2UsICJtYXhfaXRl
+      ciI6IDI1LCAibWF4X3JwbSI6IG51bGwsICJmdW5jdGlvbl9jYWxsaW5nX2xsbSI6ICIiLCAibGxt
+      IjogImdwdC00by1taW5pIiwgImRlbGVnYXRpb25fZW5hYmxlZD8iOiBmYWxzZSwgImFsbG93X2Nv
+      ZGVfZXhlY3V0aW9uPyI6IGZhbHNlLCAibWF4X3JldHJ5X2xpbWl0IjogMiwgInRvb2xzX25hbWVz
+      IjogW119XUr7AQoKY3Jld190YXNrcxLsAQrpAVt7ImtleSI6ICIyN2VmMzhjYzk5ZGE0YThkZWQ3
+      MGVkNDA2ZTQ0YWI4NiIsICJpZCI6ICI3ZjJjNGIxMi00MjNhLTRmMTctOTZiMS0zZmEyNmUzMDM3
+      MmMiLCAiYXN5bmNfZXhlY3V0aW9uPyI6IGZhbHNlLCAiaHVtYW5faW5wdXQ/IjogZmFsc2UsICJh
+      Z2VudF9yb2xlIjogIlNjb3JlciIsICJhZ2VudF9rZXkiOiAiOTJlN2ViMTkxNjY0YzkzNTc4NWVk
+      N2Q0MjQwYTI5NGQiLCAidG9vbHNfbmFtZXMiOiBbXX1degIYAYUBAAEAABKABAoQG2i2Mf2AK81I
+      gFDuyTZ4hxIIGTCH8bEW9REqDFRhc2sgQ3JlYXRlZDABOajZvECDKzcYQbArvUCDKzcYSi4KCGNy
+      ZXdfa2V5EiIKIDVlNmVmZmU2ODBhNWQ5N2RjMzg3M2IxNDgyNWNjZmEzSjEKB2NyZXdfaWQSJgok
+      MTc5MzYxNTItNDJmMi00YmY3LWIzOTEtZTU0MDU1ZTY2NGU4Si4KCHRhc2tfa2V5EiIKIDI3ZWYz
+      OGNjOTlkYTRhOGRlZDcwZWQ0MDZlNDRhYjg2SjEKB3Rhc2tfaWQSJgokN2YyYzRiMTItNDIzYS00
+      ZjE3LTk2YjEtM2ZhMjZlMzAzNzJjSjoKEGNyZXdfZmluZ2VycHJpbnQSJgokNjI0ZTI1NjEtMDFk
+      OC00YmNkLWJhMjEtZDcxZTQ0MTZkNGJiSjoKEHRhc2tfZmluZ2VycHJpbnQSJgokZjViNmU5YjUt
+      ZjcxMi00YzM3LTkyYjAtMWFjNzQ2ZTYzYWJjSjsKG3Rhc2tfZmluZ2VycHJpbnRfY3JlYXRlZF9h
+      dBIcChoyMDI1LTA0LTE3VDE0OjMzOjQzLjM1Mzg0M0o7ChFhZ2VudF9maW5nZXJwcmludBImCiQ1
+      ZjhkM2YwYS1lODZhLTRiMmUtYWFmMC1jOWMyMDg2N2M1ODR6AhgBhQEAAQAAEpwBChBCoZs2F2Pk
+      GqD1dlo+B0jIEgh/8w+r7HLXDioKVG9vbCBVc2FnZTABOfhQHUGDKzcYQeChJUGDKzcYShsKDmNy
+      ZXdhaV92ZXJzaW9uEgkKBzAuMTE0LjBKJwoJdG9vbF9uYW1lEhoKGEFzayBxdWVzdGlvbiB0byBj
+      b3dvcmtlckoOCghhdHRlbXB0cxICGAF6AhgBhQEAAQAAEpYIChAtKHG1/6WFVXbuKiUU/tulEggA
+      5PFku/BBtSoMQ3JldyBDcmVhdGVkMAE5qOuzQYMrNxhBYNO5QYMrNxhKGwoOY3Jld2FpX3ZlcnNp
+      b24SCQoHMC4xMTQuMEobCg5weXRob25fdmVyc2lvbhIJCgczLjExLjEySi4KCGNyZXdfa2V5EiIK
+      IDVlNmVmZmU2ODBhNWQ5N2RjMzg3M2IxNDgyNWNjZmEzSjEKB2NyZXdfaWQSJgokNWQzODQyMmQt
+      NTk2MC00NGQ0LWFmZjctYWM5MDFiMjU1NzM5ShwKDGNyZXdfcHJvY2VzcxIMCgpzZXF1ZW50aWFs
+      ShEKC2NyZXdfbWVtb3J5EgIQAEoaChRjcmV3X251bWJlcl9vZl90YXNrcxICGAFKGwoVY3Jld19u
+      dW1iZXJfb2ZfYWdlbnRzEgIYAUo6ChBjcmV3X2ZpbmdlcnByaW50EiYKJGZhNWYxODc1LWRiYTQt
+      NDc2MS04ZDk4LTliNzlmNDg2ZTNlY0o7ChtjcmV3X2ZpbmdlcnByaW50X2NyZWF0ZWRfYXQSHAoa
+      MjAyNS0wNC0xN1QxNDozMzo0My4zNzE2MzZKzQIKC2NyZXdfYWdlbnRzEr0CCroCW3sia2V5Ijog
+      IjkyZTdlYjE5MTY2NGM5MzU3ODVlZDdkNDI0MGEyOTRkIiwgImlkIjogIjgwZDg1ZDY3LTg3M2Qt
+      NDFhNi05MzY1LWJkODVjYTc5MGI2MyIsICJyb2xlIjogIlNjb3JlciIsICJ2ZXJib3NlPyI6IGZh
+      bHNlLCAibWF4X2l0ZXIiOiAyNSwgIm1heF9ycG0iOiBudWxsLCAiZnVuY3Rpb25fY2FsbGluZ19s
+      bG0iOiAiIiwgImxsbSI6ICJncHQtNG8tbWluaSIsICJkZWxlZ2F0aW9uX2VuYWJsZWQ/IjogZmFs
+      c2UsICJhbGxvd19jb2RlX2V4ZWN1dGlvbj8iOiBmYWxzZSwgIm1heF9yZXRyeV9saW1pdCI6IDIs
+      ICJ0b29sc19uYW1lcyI6IFtdfV1K+wEKCmNyZXdfdGFza3MS7AEK6QFbeyJrZXkiOiAiMjdlZjM4
+      Y2M5OWRhNGE4ZGVkNzBlZDQwNmU0NGFiODYiLCAiaWQiOiAiZWYwNmQ3NTEtZWY2Yy00YjJiLWI2
+      MTQtMmVhMmU1NGM0MjVlIiwgImFzeW5jX2V4ZWN1dGlvbj8iOiBmYWxzZSwgImh1bWFuX2lucHV0
+      PyI6IGZhbHNlLCAiYWdlbnRfcm9sZSI6ICJTY29yZXIiLCAiYWdlbnRfa2V5IjogIjkyZTdlYjE5
+      MTY2NGM5MzU3ODVlZDdkNDI0MGEyOTRkIiwgInRvb2xzX25hbWVzIjogW119XXoCGAGFAQABAAAS
+      gAQKEJUYH+zYJdlQxAU/SEz07wwSCHIyR0YIxKoQKgxUYXNrIENyZWF0ZWQwATnYg8NBgys3GEFQ
+      7cNBgys3GEouCghjcmV3X2tleRIiCiA1ZTZlZmZlNjgwYTVkOTdkYzM4NzNiMTQ4MjVjY2ZhM0ox
+      CgdjcmV3X2lkEiYKJDVkMzg0MjJkLTU5NjAtNDRkNC1hZmY3LWFjOTAxYjI1NTczOUouCgh0YXNr
+      X2tleRIiCiAyN2VmMzhjYzk5ZGE0YThkZWQ3MGVkNDA2ZTQ0YWI4NkoxCgd0YXNrX2lkEiYKJGVm
+      MDZkNzUxLWVmNmMtNGIyYi1iNjE0LTJlYTJlNTRjNDI1ZUo6ChBjcmV3X2ZpbmdlcnByaW50EiYK
+      JGZhNWYxODc1LWRiYTQtNDc2MS04ZDk4LTliNzlmNDg2ZTNlY0o6ChB0YXNrX2ZpbmdlcnByaW50
+      EiYKJDA1ZTU2ZTIzLWI5YjgtNDIwMy05MWYwLTY2ZmE5MDgzNzYzNUo7Cht0YXNrX2ZpbmdlcnBy
+      aW50X2NyZWF0ZWRfYXQSHAoaMjAyNS0wNC0xN1QxNDozMzo0My4zNzE2MDJKOwoRYWdlbnRfZmlu
+      Z2VycHJpbnQSJgokZGZiMDEzYTItNzg0MC00NDFhLTg1YzMtMzI0OWQ1OGJhNmIzegIYAYUBAAEA
+      ABKWCAoQ67KSQgBBFIpwJAjqKwKTNxIIPHptHAGKIGYqDENyZXcgQ3JlYXRlZDABOeB7T0KDKzcY
+      QVhEVUKDKzcYShsKDmNyZXdhaV92ZXJzaW9uEgkKBzAuMTE0LjBKGwoOcHl0aG9uX3ZlcnNpb24S
+      CQoHMy4xMS4xMkouCghjcmV3X2tleRIiCiA1ZTZlZmZlNjgwYTVkOTdkYzM4NzNiMTQ4MjVjY2Zh
+      M0oxCgdjcmV3X2lkEiYKJDRmOTE0YWZhLTVlMTAtNDU3Ni1hYjJjLWVkZmNlZWQzYTZiYkocCgxj
+      cmV3X3Byb2Nlc3MSDAoKc2VxdWVudGlhbEoRCgtjcmV3X21lbW9yeRICEABKGgoUY3Jld19udW1i
+      ZXJfb2ZfdGFza3MSAhgBShsKFWNyZXdfbnVtYmVyX29mX2FnZW50cxICGAFKOgoQY3Jld19maW5n
+      ZXJwcmludBImCiQzODFkOTIwYi1iMGE1LTRiNGUtYTQ0OS1kZjg5OGNjZjVmZDdKOwobY3Jld19m
+      aW5nZXJwcmludF9jcmVhdGVkX2F0EhwKGjIwMjUtMDQtMTdUMTQ6MzM6NDMuMzgxODc1Ss0CCgtj
+      cmV3X2FnZW50cxK9Agq6Alt7ImtleSI6ICI5MmU3ZWIxOTE2NjRjOTM1Nzg1ZWQ3ZDQyNDBhMjk0
+      ZCIsICJpZCI6ICI5ZjVhZTRmOC02MjkwLTQ5NTUtOGI2OC00YmNjOTM5ZjhhMDkiLCAicm9sZSI6
+      ICJTY29yZXIiLCAidmVyYm9zZT8iOiBmYWxzZSwgIm1heF9pdGVyIjogMjUsICJtYXhfcnBtIjog
+      bnVsbCwgImZ1bmN0aW9uX2NhbGxpbmdfbGxtIjogIiIsICJsbG0iOiAiZ3B0LTRvLW1pbmkiLCAi
+      ZGVsZWdhdGlvbl9lbmFibGVkPyI6IGZhbHNlLCAiYWxsb3dfY29kZV9leGVjdXRpb24/IjogZmFs
+      c2UsICJtYXhfcmV0cnlfbGltaXQiOiAyLCAidG9vbHNfbmFtZXMiOiBbXX1dSvsBCgpjcmV3X3Rh
+      c2tzEuwBCukBW3sia2V5IjogIjI3ZWYzOGNjOTlkYTRhOGRlZDcwZWQ0MDZlNDRhYjg2IiwgImlk
+      IjogIjViODI1OWU3LWI2Y2YtNGJlYi1iYTRiLWY3MDg4Y2E4YWM3NiIsICJhc3luY19leGVjdXRp
+      b24/IjogZmFsc2UsICJodW1hbl9pbnB1dD8iOiBmYWxzZSwgImFnZW50X3JvbGUiOiAiU2NvcmVy
+      IiwgImFnZW50X2tleSI6ICI5MmU3ZWIxOTE2NjRjOTM1Nzg1ZWQ3ZDQyNDBhMjk0ZCIsICJ0b29s
+      c19uYW1lcyI6IFtdfV16AhgBhQEAAQAAEoAEChCDE114uxBCLFPLICeD1DCNEgiFJ3IambqX4yoM
+      VGFzayBDcmVhdGVkMAE5+P9iQoMrNxhBcGljQoMrNxhKLgoIY3Jld19rZXkSIgogNWU2ZWZmZTY4
+      MGE1ZDk3ZGMzODczYjE0ODI1Y2NmYTNKMQoHY3Jld19pZBImCiQ0ZjkxNGFmYS01ZTEwLTQ1NzYt
+      YWIyYy1lZGZjZWVkM2E2YmJKLgoIdGFza19rZXkSIgogMjdlZjM4Y2M5OWRhNGE4ZGVkNzBlZDQw
+      NmU0NGFiODZKMQoHdGFza19pZBImCiQ1YjgyNTllNy1iNmNmLTRiZWItYmE0Yi1mNzA4OGNhOGFj
+      NzZKOgoQY3Jld19maW5nZXJwcmludBImCiQzODFkOTIwYi1iMGE1LTRiNGUtYTQ0OS1kZjg5OGNj
+      ZjVmZDdKOgoQdGFza19maW5nZXJwcmludBImCiRmZWIzZDVjYy0yMzEwLTRhNDgtOWQ5My1jMzQ5
+      MTI0MGU3NTlKOwobdGFza19maW5nZXJwcmludF9jcmVhdGVkX2F0EhwKGjIwMjUtMDQtMTdUMTQ6
+      MzM6NDMuMzgxODQ4SjsKEWFnZW50X2ZpbmdlcnByaW50EiYKJDdhYzY3YTkzLTkwNjctNGJjNC1i
+      NmFmLTcxZWVjZmRjNzEzOHoCGAGFAQABAAASmAgKEGmCIFMw9GayxClAketnXWsSCPvb3mKDZYhn
+      KgxDcmV3IENyZWF0ZWQwATkA88JGgys3GEGAhMpGgys3GEobCg5jcmV3YWlfdmVyc2lvbhIJCgcw
+      LjExNC4wShsKDnB5dGhvbl92ZXJzaW9uEgkKBzMuMTEuMTJKLgoIY3Jld19rZXkSIgogNWU2ZWZm
+      ZTY4MGE1ZDk3ZGMzODczYjE0ODI1Y2NmYTNKMQoHY3Jld19pZBImCiRmNmE1MGVkMy02ODk5LTQ4
+      MTItODVkNy1iNDZlYTQyNzUwN2FKHgoMY3Jld19wcm9jZXNzEg4KDGhpZXJhcmNoaWNhbEoRCgtj
+      cmV3X21lbW9yeRICEABKGgoUY3Jld19udW1iZXJfb2ZfdGFza3MSAhgBShsKFWNyZXdfbnVtYmVy
+      X29mX2FnZW50cxICGAFKOgoQY3Jld19maW5nZXJwcmludBImCiQzYzRlM2VmZS01YmQ0LTRkNDgt
+      YThmNS0yOGY0NDdhNDI0OGRKOwobY3Jld19maW5nZXJwcmludF9jcmVhdGVkX2F0EhwKGjIwMjUt
+      MDQtMTdUMTQ6MzM6NDMuNDU2MDg4Ss0CCgtjcmV3X2FnZW50cxK9Agq6Alt7ImtleSI6ICI5MmU3
+      ZWIxOTE2NjRjOTM1Nzg1ZWQ3ZDQyNDBhMjk0ZCIsICJpZCI6ICJmNzMwNTE0Mi1jOTViLTQ0MmQt
+      YjJiOS1jYTVhN2IzMzZlYjMiLCAicm9sZSI6ICJTY29yZXIiLCAidmVyYm9zZT8iOiBmYWxzZSwg
+      Im1heF9pdGVyIjogMjUsICJtYXhfcnBtIjogbnVsbCwgImZ1bmN0aW9uX2NhbGxpbmdfbGxtIjog
+      IiIsICJsbG0iOiAiZ3B0LTRvLW1pbmkiLCAiZGVsZWdhdGlvbl9lbmFibGVkPyI6IGZhbHNlLCAi
+      YWxsb3dfY29kZV9leGVjdXRpb24/IjogZmFsc2UsICJtYXhfcmV0cnlfbGltaXQiOiAyLCAidG9v
+      bHNfbmFtZXMiOiBbXX1dSvsBCgpjcmV3X3Rhc2tzEuwBCukBW3sia2V5IjogIjI3ZWYzOGNjOTlk
+      YTRhOGRlZDcwZWQ0MDZlNDRhYjg2IiwgImlkIjogIjU5MDRiMDg5LTMzNzYtNDZhMy04NWU1LTRk
+      ZTc0NDQyYTljYyIsICJhc3luY19leGVjdXRpb24/IjogZmFsc2UsICJodW1hbl9pbnB1dD8iOiBm
+      YWxzZSwgImFnZW50X3JvbGUiOiAiU2NvcmVyIiwgImFnZW50X2tleSI6ICI5MmU3ZWIxOTE2NjRj
+      OTM1Nzg1ZWQ3ZDQyNDBhMjk0ZCIsICJ0b29sc19uYW1lcyI6IFtdfV16AhgBhQEAAQAAEoAEChD9
+      DkCz0iVsHA4a1S3+yN8lEgjsMseCiYSvFioMVGFzayBDcmVhdGVkMAE5+ATcRoMrNxhB0F7cRoMr
+      NxhKLgoIY3Jld19rZXkSIgogNWU2ZWZmZTY4MGE1ZDk3ZGMzODczYjE0ODI1Y2NmYTNKMQoHY3Jl
+      d19pZBImCiRmNmE1MGVkMy02ODk5LTQ4MTItODVkNy1iNDZlYTQyNzUwN2FKLgoIdGFza19rZXkS
+      IgogMjdlZjM4Y2M5OWRhNGE4ZGVkNzBlZDQwNmU0NGFiODZKMQoHdGFza19pZBImCiQ1OTA0YjA4
+      OS0zMzc2LTQ2YTMtODVlNS00ZGU3NDQ0MmE5Y2NKOgoQY3Jld19maW5nZXJwcmludBImCiQzYzRl
+      M2VmZS01YmQ0LTRkNDgtYThmNS0yOGY0NDdhNDI0OGRKOgoQdGFza19maW5nZXJwcmludBImCiQ3
+      MjExMmY3OS1iMWU3LTRkYTctYTg4YS00NjU3NTJiZTIwZDdKOwobdGFza19maW5nZXJwcmludF9j
+      cmVhdGVkX2F0EhwKGjIwMjUtMDQtMTdUMTQ6MzM6NDMuNDU2MDU5SjsKEWFnZW50X2ZpbmdlcnBy
+      aW50EiYKJGJiMzQ0NzIxLTE3M2QtNGRmNS1iMWRmLWQ2NjBkZjZlZmVjZnoCGAGFAQABAAASnAEK
+      EOg/b+TBCd7kQOaEdNwvgZoSCGYJctohLuuaKgpUb29sIFVzYWdlMAE58JA0R4MrNxhBqOM9R4Mr
+      NxhKGwoOY3Jld2FpX3ZlcnNpb24SCQoHMC4xMTQuMEonCgl0b29sX25hbWUSGgoYQXNrIHF1ZXN0
+      aW9uIHRvIGNvd29ya2VySg4KCGF0dGVtcHRzEgIYAXoCGAGFAQABAAASlwoKEMn/aYwi4Jc7AohP
+      Y7puRXsSCB83OjVnCZfLKgxDcmV3IENyZWF0ZWQwATlw8dVHgys3GEGA9NtHgys3GEobCg5jcmV3
+      YWlfdmVyc2lvbhIJCgcwLjExNC4wShsKDnB5dGhvbl92ZXJzaW9uEgkKBzMuMTEuMTJKLgoIY3Jl
+      d19rZXkSIgogZDQyNjA4MzNhYjBjMjBiYjQ0OTIyYzc5OWFhOTZiNGFKMQoHY3Jld19pZBImCiQx
+      ZjA0NjU0YS05ODE5LTQ0MTEtOTVlZC1kMmMwMTJlNWU3YjJKHAoMY3Jld19wcm9jZXNzEgwKCnNl
+      cXVlbnRpYWxKEQoLY3Jld19tZW1vcnkSAhAAShoKFGNyZXdfbnVtYmVyX29mX3Rhc2tzEgIYAkob
+      ChVjcmV3X251bWJlcl9vZl9hZ2VudHMSAhgBSjoKEGNyZXdfZmluZ2VycHJpbnQSJgokYjhhYjU0
+      YzEtYjFjZS00OGIyLTlkODMtNDVkNzkyMTkxOWQ0SjsKG2NyZXdfZmluZ2VycHJpbnRfY3JlYXRl
+      ZF9hdBIcChoyMDI1LTA0LTE3VDE0OjMzOjQzLjQ3NDIyN0rlAgoLY3Jld19hZ2VudHMS1QIK0gJb
+      eyJrZXkiOiAiOTJlN2ViMTkxNjY0YzkzNTc4NWVkN2Q0MjQwYTI5NGQiLCAiaWQiOiAiMjg5YzIz
+      NzgtNWUxOC00YzJiLWE1NDMtNzVkOTk5YWUyYWQyIiwgInJvbGUiOiAiU2NvcmVyIiwgInZlcmJv
+      c2U/IjogdHJ1ZSwgIm1heF9pdGVyIjogMjUsICJtYXhfcnBtIjogbnVsbCwgImZ1bmN0aW9uX2Nh
+      bGxpbmdfbGxtIjogImdwdC0zLjUtdHVyYm8tMDEyNSIsICJsbG0iOiAiZ3B0LTQtMDEyNS1wcmV2
+      aWV3IiwgImRlbGVnYXRpb25fZW5hYmxlZD8iOiBmYWxzZSwgImFsbG93X2NvZGVfZXhlY3V0aW9u
+      PyI6IGZhbHNlLCAibWF4X3JldHJ5X2xpbWl0IjogMiwgInRvb2xzX25hbWVzIjogW119XUrkAwoK
+      Y3Jld190YXNrcxLVAwrSA1t7ImtleSI6ICIyN2VmMzhjYzk5ZGE0YThkZWQ3MGVkNDA2ZTQ0YWI4
+      NiIsICJpZCI6ICJiNTAxMWUwNi02YTdmLTQzYWItYWQzNy1mNGI4ODBhMmJlYjgiLCAiYXN5bmNf
+      ZXhlY3V0aW9uPyI6IGZhbHNlLCAiaHVtYW5faW5wdXQ/IjogZmFsc2UsICJhZ2VudF9yb2xlIjog
+      IlNjb3JlciIsICJhZ2VudF9rZXkiOiAiOTJlN2ViMTkxNjY0YzkzNTc4NWVkN2Q0MjQwYTI5NGQi
+      LCAidG9vbHNfbmFtZXMiOiBbXX0sIHsia2V5IjogIjYwOWRlZTM5MTA4OGNkMWM4N2I4ZmE2NmFh
+      NjdhZGJlIiwgImlkIjogIjRiODE5NjQ5LTYyMjQtNGQ3Mi1hZDFkLTM0ODZhYzBkODQwNSIsICJh
+      c3luY19leGVjdXRpb24/IjogZmFsc2UsICJodW1hbl9pbnB1dD8iOiBmYWxzZSwgImFnZW50X3Jv
+      bGUiOiAiU2NvcmVyIiwgImFnZW50X2tleSI6ICI5MmU3ZWIxOTE2NjRjOTM1Nzg1ZWQ3ZDQyNDBh
+      Mjk0ZCIsICJ0b29sc19uYW1lcyI6IFtdfV16AhgBhQEAAQAAEoAEChCdiwcYoV5twj//vpjaNfMl
+      EghUv7y5H7+dXioMVGFzayBDcmVhdGVkMAE5wN3kR4MrNxhBsDPlR4MrNxhKLgoIY3Jld19rZXkS
+      IgogZDQyNjA4MzNhYjBjMjBiYjQ0OTIyYzc5OWFhOTZiNGFKMQoHY3Jld19pZBImCiQxZjA0NjU0
+      YS05ODE5LTQ0MTEtOTVlZC1kMmMwMTJlNWU3YjJKLgoIdGFza19rZXkSIgogMjdlZjM4Y2M5OWRh
+      NGE4ZGVkNzBlZDQwNmU0NGFiODZKMQoHdGFza19pZBImCiRiNTAxMWUwNi02YTdmLTQzYWItYWQz
+      Ny1mNGI4ODBhMmJlYjhKOgoQY3Jld19maW5nZXJwcmludBImCiRiOGFiNTRjMS1iMWNlLTQ4YjIt
+      OWQ4My00NWQ3OTIxOTE5ZDRKOgoQdGFza19maW5nZXJwcmludBImCiQ3NDcyMTM3Yi0wYzBkLTRi
+      OTEtYTgwYy01YzZkYWQwZmM3YTBKOwobdGFza19maW5nZXJwcmludF9jcmVhdGVkX2F0EhwKGjIw
+      MjUtMDQtMTdUMTQ6MzM6NDMuNDc0MTc1SjsKEWFnZW50X2ZpbmdlcnByaW50EiYKJDVlMWU1Nzdh
+      LWY5N2QtNDA2OS04NzNmLTc1ZjYyMDE0ZWJlNnoCGAGFAQABAAASgAQKEA6OsjCwXi+o2MUfKyS+
+      TmgSCOIWlM7TtxNCKgxUYXNrIENyZWF0ZWQwATmQ915Igys3GEHYaF9Igys3GEouCghjcmV3X2tl
+      eRIiCiBkNDI2MDgzM2FiMGMyMGJiNDQ5MjJjNzk5YWE5NmI0YUoxCgdjcmV3X2lkEiYKJDFmMDQ2
+      NTRhLTk4MTktNDQxMS05NWVkLWQyYzAxMmU1ZTdiMkouCgh0YXNrX2tleRIiCiA2MDlkZWUzOTEw
+      ODhjZDFjODdiOGZhNjZhYTY3YWRiZUoxCgd0YXNrX2lkEiYKJDRiODE5NjQ5LTYyMjQtNGQ3Mi1h
+      ZDFkLTM0ODZhYzBkODQwNUo6ChBjcmV3X2ZpbmdlcnByaW50EiYKJGI4YWI1NGMxLWIxY2UtNDhi
+      Mi05ZDgzLTQ1ZDc5MjE5MTlkNEo6ChB0YXNrX2ZpbmdlcnByaW50EiYKJGYwZWUxMjY2LWExNzIt
+      NDhiMi1iMTM2LTczN2I3YWNkYWYwNko7Cht0YXNrX2ZpbmdlcnByaW50X2NyZWF0ZWRfYXQSHAoa
+      MjAyNS0wNC0xN1QxNDozMzo0My40NzQyMDVKOwoRYWdlbnRfZmluZ2VycHJpbnQSJgokNWUxZTU3
+      N2EtZjk3ZC00MDY5LTg3M2YtNzVmNjIwMTRlYmU2egIYAYUBAAEAABL/CQoQOon8z16iVXeCtEnr
+      visR+hII1ztFvfUBPyAqDENyZXcgQ3JlYXRlZDABOYC2CUmDKzcYQVhjEUmDKzcYShsKDmNyZXdh
+      aV92ZXJzaW9uEgkKBzAuMTE0LjBKGwoOcHl0aG9uX3ZlcnNpb24SCQoHMy4xMS4xMkouCghjcmV3
+      X2tleRIiCiBhOTU0MGNkMGVhYTUzZjY3NTQzN2U5YmQ0ZmE1ZTQ0Y0oxCgdjcmV3X2lkEiYKJDFh
+      MDA5NjZhLTcwYmQtNDc4OS1hZmQxLTY5NjgzMzZjYjc2NkocCgxjcmV3X3Byb2Nlc3MSDAoKc2Vx
+      dWVudGlhbEoRCgtjcmV3X21lbW9yeRICEABKGgoUY3Jld19udW1iZXJfb2ZfdGFza3MSAhgCShsK
+      FWNyZXdfbnVtYmVyX29mX2FnZW50cxICGAFKOgoQY3Jld19maW5nZXJwcmludBImCiRjOGI1ZDUx
+      My0xNzY0LTQyYWQtOGVlYS0wYWU0MDAzZTRmNTRKOwobY3Jld19maW5nZXJwcmludF9jcmVhdGVk
+      X2F0EhwKGjIwMjUtMDQtMTdUMTQ6MzM6NDMuNDk0ODMySs0CCgtjcmV3X2FnZW50cxK9Agq6Alt7
+      ImtleSI6ICI5MmU3ZWIxOTE2NjRjOTM1Nzg1ZWQ3ZDQyNDBhMjk0ZCIsICJpZCI6ICIwZTg1MzFl
+      YS05MmM4LTQzMGQtYmE0Yy1jMmIxYzkwZDBlMWQiLCAicm9sZSI6ICJTY29yZXIiLCAidmVyYm9z
+      ZT8iOiBmYWxzZSwgIm1heF9pdGVyIjogMjUsICJtYXhfcnBtIjogbnVsbCwgImZ1bmN0aW9uX2Nh
+      bGxpbmdfbGxtIjogIiIsICJsbG0iOiAiZ3B0LTRvLW1pbmkiLCAiZGVsZWdhdGlvbl9lbmFibGVk
+      PyI6IGZhbHNlLCAiYWxsb3dfY29kZV9leGVjdXRpb24/IjogZmFsc2UsICJtYXhfcmV0cnlfbGlt
+      aXQiOiAyLCAidG9vbHNfbmFtZXMiOiBbXX1dSuQDCgpjcmV3X3Rhc2tzEtUDCtIDW3sia2V5Ijog
+      IjI3ZWYzOGNjOTlkYTRhOGRlZDcwZWQ0MDZlNDRhYjg2IiwgImlkIjogImI2NWQ1ZGUzLWY5MjAt
+      NDVhZi1hOTgwLTA2NjBkMDU5YzdiZiIsICJhc3luY19leGVjdXRpb24/IjogZmFsc2UsICJodW1h
+      bl9pbnB1dD8iOiBmYWxzZSwgImFnZW50X3JvbGUiOiAiU2NvcmVyIiwgImFnZW50X2tleSI6ICI5
+      MmU3ZWIxOTE2NjRjOTM1Nzg1ZWQ3ZDQyNDBhMjk0ZCIsICJ0b29sc19uYW1lcyI6IFtdfSwgeyJr
+      ZXkiOiAiYjBkMzRhNmY2MjFhN2IzNTgwZDVkMWY0ZTI2NjViOTIiLCAiaWQiOiAiZjk2MDU5NzMt
+      YzYyMi00NzRjLWFhZjktYWJiOWMwZWZhYmQ0IiwgImFzeW5jX2V4ZWN1dGlvbj8iOiBmYWxzZSwg
+      Imh1bWFuX2lucHV0PyI6IGZhbHNlLCAiYWdlbnRfcm9sZSI6ICJTY29yZXIiLCAiYWdlbnRfa2V5
+      IjogIjkyZTdlYjE5MTY2NGM5MzU3ODVlZDdkNDI0MGEyOTRkIiwgInRvb2xzX25hbWVzIjogW119
+      XXoCGAGFAQABAAASgAQKEGysuSY/RpRwwsmMtZmmkLgSCB3RCKVN5vMGKgxUYXNrIENyZWF0ZWQw
+      ATmYyRpJgys3GEFwIxtJgys3GEouCghjcmV3X2tleRIiCiBhOTU0MGNkMGVhYTUzZjY3NTQzN2U5
+      YmQ0ZmE1ZTQ0Y0oxCgdjcmV3X2lkEiYKJDFhMDA5NjZhLTcwYmQtNDc4OS1hZmQxLTY5NjgzMzZj
+      Yjc2NkouCgh0YXNrX2tleRIiCiAyN2VmMzhjYzk5ZGE0YThkZWQ3MGVkNDA2ZTQ0YWI4NkoxCgd0
+      YXNrX2lkEiYKJGI2NWQ1ZGUzLWY5MjAtNDVhZi1hOTgwLTA2NjBkMDU5YzdiZko6ChBjcmV3X2Zp
+      bmdlcnByaW50EiYKJGM4YjVkNTEzLTE3NjQtNDJhZC04ZWVhLTBhZTQwMDNlNGY1NEo6ChB0YXNr
+      X2ZpbmdlcnByaW50EiYKJDZjNDhlMTkxLTViMjEtNDBmNi1iNmQwLWRjMWY3ZmM2YWQzN0o7Cht0
+      YXNrX2ZpbmdlcnByaW50X2NyZWF0ZWRfYXQSHAoaMjAyNS0wNC0xN1QxNDozMzo0My40OTQ3NzdK
+      OwoRYWdlbnRfZmluZ2VycHJpbnQSJgokNTZmYTQ1MTYtM2RiNS00Mjk3LTg3NzUtOTI2MWVhNWI4
+      OWI2egIYAYUBAAEAABKABAoQJRURFvAOz5/5e2bQNRT4ChIIpSiy2tnBCrsqDFRhc2sgQ3JlYXRl
+      ZDABOdgreEmDKzcYQSCdeEmDKzcYSi4KCGNyZXdfa2V5EiIKIGE5NTQwY2QwZWFhNTNmNjc1NDM3
+      ZTliZDRmYTVlNDRjSjEKB2NyZXdfaWQSJgokMWEwMDk2NmEtNzBiZC00Nzg5LWFmZDEtNjk2ODMz
+      NmNiNzY2Si4KCHRhc2tfa2V5EiIKIGIwZDM0YTZmNjIxYTdiMzU4MGQ1ZDFmNGUyNjY1YjkySjEK
+      B3Rhc2tfaWQSJgokZjk2MDU5NzMtYzYyMi00NzRjLWFhZjktYWJiOWMwZWZhYmQ0SjoKEGNyZXdf
+      ZmluZ2VycHJpbnQSJgokYzhiNWQ1MTMtMTc2NC00MmFkLThlZWEtMGFlNDAwM2U0ZjU0SjoKEHRh
+      c2tfZmluZ2VycHJpbnQSJgokMWI0YzI5NTYtMDZkOC00NWNjLWFmYWMtNmZhZDk0MzdkNTZmSjsK
+      G3Rhc2tfZmluZ2VycHJpbnRfY3JlYXRlZF9hdBIcChoyMDI1LTA0LTE3VDE0OjMzOjQzLjQ5NDgw
+      OEo7ChFhZ2VudF9maW5nZXJwcmludBImCiQ1NmZhNDUxNi0zZGI1LTQyOTctODc3NS05MjYxZWE1
+      Yjg5YjZ6AhgBhQEAAQAAEpYIChCt1KD2VBrK6+JIjPGbSQYWEghyEaRdKejivSoMQ3JldyBDcmVh
+      dGVkMAE54Fn7SYMrNxhBMPkBSoMrNxhKGwoOY3Jld2FpX3ZlcnNpb24SCQoHMC4xMTQuMEobCg5w
+      eXRob25fdmVyc2lvbhIJCgczLjExLjEySi4KCGNyZXdfa2V5EiIKIDVlNmVmZmU2ODBhNWQ5N2Rj
+      Mzg3M2IxNDgyNWNjZmEzSjEKB2NyZXdfaWQSJgokMDQ4ZDQ5MzctNmU3OC00OWFkLTllZDMtYzVi
+      MjdlNDgyNThlShwKDGNyZXdfcHJvY2VzcxIMCgpzZXF1ZW50aWFsShEKC2NyZXdfbWVtb3J5EgIQ
+      AEoaChRjcmV3X251bWJlcl9vZl90YXNrcxICGAFKGwoVY3Jld19udW1iZXJfb2ZfYWdlbnRzEgIY
+      AUo6ChBjcmV3X2ZpbmdlcnByaW50EiYKJDIxYjViOWQ3LWVjNTktNDBhYi1iZjY1LTk1NzM2M2Fl
+      ZDRkZEo7ChtjcmV3X2ZpbmdlcnByaW50X2NyZWF0ZWRfYXQSHAoaMjAyNS0wNC0xN1QxNDozMzo0
+      My41MTA0NjZKzQIKC2NyZXdfYWdlbnRzEr0CCroCW3sia2V5IjogIjkyZTdlYjE5MTY2NGM5MzU3
+      ODVlZDdkNDI0MGEyOTRkIiwgImlkIjogImFkN2ExMTJiLWY5NDQtNDViYy05YzE4LWJjOWQzMDE4
+      NjE1OCIsICJyb2xlIjogIlNjb3JlciIsICJ2ZXJib3NlPyI6IGZhbHNlLCAibWF4X2l0ZXIiOiAy
+      NSwgIm1heF9ycG0iOiBudWxsLCAiZnVuY3Rpb25fY2FsbGluZ19sbG0iOiAiIiwgImxsbSI6ICJn
+      cHQtNG8tbWluaSIsICJkZWxlZ2F0aW9uX2VuYWJsZWQ/IjogZmFsc2UsICJhbGxvd19jb2RlX2V4
+      ZWN1dGlvbj8iOiBmYWxzZSwgIm1heF9yZXRyeV9saW1pdCI6IDIsICJ0b29sc19uYW1lcyI6IFtd
+      fV1K+wEKCmNyZXdfdGFza3MS7AEK6QFbeyJrZXkiOiAiMjdlZjM4Y2M5OWRhNGE4ZGVkNzBlZDQw
+      NmU0NGFiODYiLCAiaWQiOiAiZTJmMDI3YzItZWQ2NC00MDU4LThkNzUtNjQ1OWMzYTllYWIwIiwg
+      ImFzeW5jX2V4ZWN1dGlvbj8iOiBmYWxzZSwgImh1bWFuX2lucHV0PyI6IGZhbHNlLCAiYWdlbnRf
+      cm9sZSI6ICJTY29yZXIiLCAiYWdlbnRfa2V5IjogIjkyZTdlYjE5MTY2NGM5MzU3ODVlZDdkNDI0
+      MGEyOTRkIiwgInRvb2xzX25hbWVzIjogW119XXoCGAGFAQABAAASgAQKELdQRmZyaC0pfEDI4tAa
+      vRsSCCE13pISM1wEKgxUYXNrIENyZWF0ZWQwATmwBwpKgys3GEG4WQpKgys3GEouCghjcmV3X2tl
+      eRIiCiA1ZTZlZmZlNjgwYTVkOTdkYzM4NzNiMTQ4MjVjY2ZhM0oxCgdjcmV3X2lkEiYKJDA0OGQ0
+      OTM3LTZlNzgtNDlhZC05ZWQzLWM1YjI3ZTQ4MjU4ZUouCgh0YXNrX2tleRIiCiAyN2VmMzhjYzk5
+      ZGE0YThkZWQ3MGVkNDA2ZTQ0YWI4NkoxCgd0YXNrX2lkEiYKJGUyZjAyN2MyLWVkNjQtNDA1OC04
+      ZDc1LTY0NTljM2E5ZWFiMEo6ChBjcmV3X2ZpbmdlcnByaW50EiYKJDIxYjViOWQ3LWVjNTktNDBh
+      Yi1iZjY1LTk1NzM2M2FlZDRkZEo6ChB0YXNrX2ZpbmdlcnByaW50EiYKJDNmMDU4NDE1LTNkNzUt
+      NDZhNi05OWFjLTIyZmM5OWM4OTBmM0o7Cht0YXNrX2ZpbmdlcnByaW50X2NyZWF0ZWRfYXQSHAoa
+      MjAyNS0wNC0xN1QxNDozMzo0My41MTA0NDBKOwoRYWdlbnRfZmluZ2VycHJpbnQSJgokMjViMTgx
+      NjYtYjk3My00ZDM3LWI0OTUtMTI4YmIyMzQyNjhmegIYAYUBAAEAABKWCAoQuKzLEfp7NclRHh6f
+      Sm2/nxIIucJxIhUlkkwqDENyZXcgQ3JlYXRlZDABOfDOa0qDKzcYQfh/cUqDKzcYShsKDmNyZXdh
+      aV92ZXJzaW9uEgkKBzAuMTE0LjBKGwoOcHl0aG9uX3ZlcnNpb24SCQoHMy4xMS4xMkouCghjcmV3
+      X2tleRIiCiA1ZTZlZmZlNjgwYTVkOTdkYzM4NzNiMTQ4MjVjY2ZhM0oxCgdjcmV3X2lkEiYKJDhl
+      YzE2ZWQ3LTNiYjItNDkxZC04YjYxLTI3MWYxNmZlOGFlMUocCgxjcmV3X3Byb2Nlc3MSDAoKc2Vx
+      dWVudGlhbEoRCgtjcmV3X21lbW9yeRICEABKGgoUY3Jld19udW1iZXJfb2ZfdGFza3MSAhgBShsK
+      FWNyZXdfbnVtYmVyX29mX2FnZW50cxICGAFKOgoQY3Jld19maW5nZXJwcmludBImCiQxN2MxN2Qz
+      NC1mZWZkLTQ1ZTktYWM2NS00ODY2ZTBlNTgwYTBKOwobY3Jld19maW5nZXJwcmludF9jcmVhdGVk
+      X2F0EhwKGjIwMjUtMDQtMTdUMTQ6MzM6NDMuNTE4MDI0Ss0CCgtjcmV3X2FnZW50cxK9Agq6Alt7
+      ImtleSI6ICI5MmU3ZWIxOTE2NjRjOTM1Nzg1ZWQ3ZDQyNDBhMjk0ZCIsICJpZCI6ICJhODk2OTRm
+      ZS1lNjE1LTQzOWItOTQ4MC02MmVmZTRiNGY4ODUiLCAicm9sZSI6ICJTY29yZXIiLCAidmVyYm9z
+      ZT8iOiBmYWxzZSwgIm1heF9pdGVyIjogMjUsICJtYXhfcnBtIjogbnVsbCwgImZ1bmN0aW9uX2Nh
+      bGxpbmdfbGxtIjogIiIsICJsbG0iOiAiZ3B0LTRvLW1pbmkiLCAiZGVsZWdhdGlvbl9lbmFibGVk
+      PyI6IGZhbHNlLCAiYWxsb3dfY29kZV9leGVjdXRpb24/IjogZmFsc2UsICJtYXhfcmV0cnlfbGlt
+      aXQiOiAyLCAidG9vbHNfbmFtZXMiOiBbXX1dSvsBCgpjcmV3X3Rhc2tzEuwBCukBW3sia2V5Ijog
+      IjI3ZWYzOGNjOTlkYTRhOGRlZDcwZWQ0MDZlNDRhYjg2IiwgImlkIjogIjMwYjNmYmQ4LWM0MmMt
+      NDhlYi1hNDdlLTAzNzFlOTFmYTAxYiIsICJhc3luY19leGVjdXRpb24/IjogZmFsc2UsICJodW1h
+      bl9pbnB1dD8iOiBmYWxzZSwgImFnZW50X3JvbGUiOiAiU2NvcmVyIiwgImFnZW50X2tleSI6ICI5
+      MmU3ZWIxOTE2NjRjOTM1Nzg1ZWQ3ZDQyNDBhMjk0ZCIsICJ0b29sc19uYW1lcyI6IFtdfV16AhgB
+      hQEAAQAAEoAEChBSqrS4nl90w/7Z/EGzEvYpEgj54GNjf+XWQyoMVGFzayBDcmVhdGVkMAE5GJ55
+      SoMrNxhBOOx5SoMrNxhKLgoIY3Jld19rZXkSIgogNWU2ZWZmZTY4MGE1ZDk3ZGMzODczYjE0ODI1
+      Y2NmYTNKMQoHY3Jld19pZBImCiQ4ZWMxNmVkNy0zYmIyLTQ5MWQtOGI2MS0yNzFmMTZmZThhZTFK
+      LgoIdGFza19rZXkSIgogMjdlZjM4Y2M5OWRhNGE4ZGVkNzBlZDQwNmU0NGFiODZKMQoHdGFza19p
+      ZBImCiQzMGIzZmJkOC1jNDJjLTQ4ZWItYTQ3ZS0wMzcxZTkxZmEwMWJKOgoQY3Jld19maW5nZXJw
+      cmludBImCiQxN2MxN2QzNC1mZWZkLTQ1ZTktYWM2NS00ODY2ZTBlNTgwYTBKOgoQdGFza19maW5n
+      ZXJwcmludBImCiQ5MGYyODZhZC1lOWQ4LTRkOWUtYjA5MC05YTQyY2I3ZjYzNDhKOwobdGFza19m
+      aW5nZXJwcmludF9jcmVhdGVkX2F0EhwKGjIwMjUtMDQtMTdUMTQ6MzM6NDMuNTE3OTk4SjsKEWFn
+      ZW50X2ZpbmdlcnByaW50EiYKJDhhMTliOTQxLWI4MTgtNDU3MC05NmJjLWZlYWQ4MWNkMjk1NXoC
+      GAGFAQABAAASlggKEFFBQgm1QyQTSqKMpRKbGjwSCCoFcjlB3aOLKgxDcmV3IENyZWF0ZWQwATlY
+      /RVLgys3GEEwLR1Lgys3GEobCg5jcmV3YWlfdmVyc2lvbhIJCgcwLjExNC4wShsKDnB5dGhvbl92
+      ZXJzaW9uEgkKBzMuMTEuMTJKLgoIY3Jld19rZXkSIgogNWU2ZWZmZTY4MGE1ZDk3ZGMzODczYjE0
+      ODI1Y2NmYTNKMQoHY3Jld19pZBImCiQ5NDYyMGE5YS1jMjc1LTRjMjItYjk1OC0zZmZlYWRiOGFl
+      ZGJKHAoMY3Jld19wcm9jZXNzEgwKCnNlcXVlbnRpYWxKEQoLY3Jld19tZW1vcnkSAhAAShoKFGNy
+      ZXdfbnVtYmVyX29mX3Rhc2tzEgIYAUobChVjcmV3X251bWJlcl9vZl9hZ2VudHMSAhgBSjoKEGNy
+      ZXdfZmluZ2VycHJpbnQSJgokNzQzZDgxNDYtZTM0My00Njk0LTljODUtMmVmZWRkMzZhYTlkSjsK
+      G2NyZXdfZmluZ2VycHJpbnRfY3JlYXRlZF9hdBIcChoyMDI1LTA0LTE3VDE0OjMzOjQzLjUyOTAz
+      MkrNAgoLY3Jld19hZ2VudHMSvQIKugJbeyJrZXkiOiAiOTJlN2ViMTkxNjY0YzkzNTc4NWVkN2Q0
+      MjQwYTI5NGQiLCAiaWQiOiAiZWE5NTMyZDktZDczNy00ZTIyLWE3MjItMDg2ODQ4NGViMmY5Iiwg
+      InJvbGUiOiAiU2NvcmVyIiwgInZlcmJvc2U/IjogZmFsc2UsICJtYXhfaXRlciI6IDI1LCAibWF4
+      X3JwbSI6IG51bGwsICJmdW5jdGlvbl9jYWxsaW5nX2xsbSI6ICIiLCAibGxtIjogImdwdC00by1t
+      aW5pIiwgImRlbGVnYXRpb25fZW5hYmxlZD8iOiBmYWxzZSwgImFsbG93X2NvZGVfZXhlY3V0aW9u
+      PyI6IGZhbHNlLCAibWF4X3JldHJ5X2xpbWl0IjogMiwgInRvb2xzX25hbWVzIjogW119XUr7AQoK
+      Y3Jld190YXNrcxLsAQrpAVt7ImtleSI6ICIyN2VmMzhjYzk5ZGE0YThkZWQ3MGVkNDA2ZTQ0YWI4
+      NiIsICJpZCI6ICIyMmUyMjZiNC1kNmI5LTRiMzgtOTQwMi05NDY0NTBhOWExZjUiLCAiYXN5bmNf
+      ZXhlY3V0aW9uPyI6IGZhbHNlLCAiaHVtYW5faW5wdXQ/IjogZmFsc2UsICJhZ2VudF9yb2xlIjog
+      IlNjb3JlciIsICJhZ2VudF9rZXkiOiAiOTJlN2ViMTkxNjY0YzkzNTc4NWVkN2Q0MjQwYTI5NGQi
+      LCAidG9vbHNfbmFtZXMiOiBbXX1degIYAYUBAAEAABKABAoQBNXlZK0H3tATZKP2Uw7bBxII0nvw
+      9UluHcgqDFRhc2sgQ3JlYXRlZDABOXhiJ0uDKzcYQZiwJ0uDKzcYSi4KCGNyZXdfa2V5EiIKIDVl
+      NmVmZmU2ODBhNWQ5N2RjMzg3M2IxNDgyNWNjZmEzSjEKB2NyZXdfaWQSJgokOTQ2MjBhOWEtYzI3
+      NS00YzIyLWI5NTgtM2ZmZWFkYjhhZWRiSi4KCHRhc2tfa2V5EiIKIDI3ZWYzOGNjOTlkYTRhOGRl
+      ZDcwZWQ0MDZlNDRhYjg2SjEKB3Rhc2tfaWQSJgokMjJlMjI2YjQtZDZiOS00YjM4LTk0MDItOTQ2
+      NDUwYTlhMWY1SjoKEGNyZXdfZmluZ2VycHJpbnQSJgokNzQzZDgxNDYtZTM0My00Njk0LTljODUt
+      MmVmZWRkMzZhYTlkSjoKEHRhc2tfZmluZ2VycHJpbnQSJgokYjI3M2Q1OTMtYzcxZC00ZWRmLWI0
+      NmMtMTkyMmIxY2ZmZjY1SjsKG3Rhc2tfZmluZ2VycHJpbnRfY3JlYXRlZF9hdBIcChoyMDI1LTA0
+      LTE3VDE0OjMzOjQzLjUyOTAwMko7ChFhZ2VudF9maW5nZXJwcmludBImCiQ5ZWYxZjc4Ny1lZTIz
+      LTRlNGUtOGJkYi04NGJiNjkwZjlkZjV6AhgBhQEAAQAAEpYIChCLERZYyvqc04xX3gWXPO59EggU
+      L4MaGDu+FyoMQ3JldyBDcmVhdGVkMAE54NLGS4MrNxhBeGbNS4MrNxhKGwoOY3Jld2FpX3ZlcnNp
+      b24SCQoHMC4xMTQuMEobCg5weXRob25fdmVyc2lvbhIJCgczLjExLjEySi4KCGNyZXdfa2V5EiIK
+      IDVlNmVmZmU2ODBhNWQ5N2RjMzg3M2IxNDgyNWNjZmEzSjEKB2NyZXdfaWQSJgokZWI4MDdlMzEt
+      MGFiZS00NjQ0LWEwZjEtMDM4N2ZkZTYzYWQ1ShwKDGNyZXdfcHJvY2VzcxIMCgpzZXF1ZW50aWFs
+      ShEKC2NyZXdfbWVtb3J5EgIQAEoaChRjcmV3X251bWJlcl9vZl90YXNrcxICGAFKGwoVY3Jld19u
+      dW1iZXJfb2ZfYWdlbnRzEgIYAUo6ChBjcmV3X2ZpbmdlcnByaW50EiYKJDBkZDRmNDNlLTEzNzEt
+      NDVlNS1iMGNmLWY2ZDE5YTNjNzZkOUo7ChtjcmV3X2ZpbmdlcnByaW50X2NyZWF0ZWRfYXQSHAoa
+      MjAyNS0wNC0xN1QxNDozMzo0My41NDA2MzhKzQIKC2NyZXdfYWdlbnRzEr0CCroCW3sia2V5Ijog
+      IjkyZTdlYjE5MTY2NGM5MzU3ODVlZDdkNDI0MGEyOTRkIiwgImlkIjogImY0ZDM5NzdlLTg4YjAt
+      NDQ2Zi04YzQ5LThkMjc0NDgwOGQ4NiIsICJyb2xlIjogIlNjb3JlciIsICJ2ZXJib3NlPyI6IGZh
+      bHNlLCAibWF4X2l0ZXIiOiAyNSwgIm1heF9ycG0iOiBudWxsLCAiZnVuY3Rpb25fY2FsbGluZ19s
+      bG0iOiAiIiwgImxsbSI6ICJncHQtNG8tbWluaSIsICJkZWxlZ2F0aW9uX2VuYWJsZWQ/IjogZmFs
+      c2UsICJhbGxvd19jb2RlX2V4ZWN1dGlvbj8iOiBmYWxzZSwgIm1heF9yZXRyeV9saW1pdCI6IDIs
+      ICJ0b29sc19uYW1lcyI6IFtdfV1K+wEKCmNyZXdfdGFza3MS7AEK6QFbeyJrZXkiOiAiMjdlZjM4
+      Y2M5OWRhNGE4ZGVkNzBlZDQwNmU0NGFiODYiLCAiaWQiOiAiYjA4MTZmY2QtYjcyMS00YTZkLTk0
+      ODQtNDc4YWM4ZDdkYTg4IiwgImFzeW5jX2V4ZWN1dGlvbj8iOiBmYWxzZSwgImh1bWFuX2lucHV0
+      PyI6IGZhbHNlLCAiYWdlbnRfcm9sZSI6ICJTY29yZXIiLCAiYWdlbnRfa2V5IjogIjkyZTdlYjE5
+      MTY2NGM5MzU3ODVlZDdkNDI0MGEyOTRkIiwgInRvb2xzX25hbWVzIjogW119XXoCGAGFAQABAAAS
+      gAQKEB0emJtWTE8969Cle2pbw8QSCFZbdjoOT655KgxUYXNrIENyZWF0ZWQwATlgt9VLgys3GEFo
+      CdZLgys3GEouCghjcmV3X2tleRIiCiA1ZTZlZmZlNjgwYTVkOTdkYzM4NzNiMTQ4MjVjY2ZhM0ox
+      CgdjcmV3X2lkEiYKJGViODA3ZTMxLTBhYmUtNDY0NC1hMGYxLTAzODdmZGU2M2FkNUouCgh0YXNr
+      X2tleRIiCiAyN2VmMzhjYzk5ZGE0YThkZWQ3MGVkNDA2ZTQ0YWI4NkoxCgd0YXNrX2lkEiYKJGIw
+      ODE2ZmNkLWI3MjEtNGE2ZC05NDg0LTQ3OGFjOGQ3ZGE4OEo6ChBjcmV3X2ZpbmdlcnByaW50EiYK
+      JDBkZDRmNDNlLTEzNzEtNDVlNS1iMGNmLWY2ZDE5YTNjNzZkOUo6ChB0YXNrX2ZpbmdlcnByaW50
+      EiYKJGM1ODIyZGM4LWIyYmYtNDUyZS04YjQ2LWRkNjAyMDNkNTA0Zko7Cht0YXNrX2ZpbmdlcnBy
+      aW50X2NyZWF0ZWRfYXQSHAoaMjAyNS0wNC0xN1QxNDozMzo0My41NDA2MDlKOwoRYWdlbnRfZmlu
+      Z2VycHJpbnQSJgokZjZhMjA0MDYtOTM0Yy00ZjVmLWI1MzMtMDYwMTQwMGUxMTM1egIYAYUBAAEA
+      ABL4BwoQxJQoNY/stf/qihFVNGkp1hII9x5mkc7Cz5AqDENyZXcgQ3JlYXRlZDABOcB+REyDKzcY
+      QYA7SkyDKzcYShsKDmNyZXdhaV92ZXJzaW9uEgkKBzAuMTE0LjBKGwoOcHl0aG9uX3ZlcnNpb24S
+      CQoHMy4xMS4xMkouCghjcmV3X2tleRIiCiA1ZTZlZmZlNjgwYTVkOTdkYzM4NzNiMTQ4MjVjY2Zh
+      M0oxCgdjcmV3X2lkEiYKJDY3NmIxNjlhLTI5YTYtNDVhOC05NmNjLTY4MjMyNzgzYmU3NUoeCgxj
+      cmV3X3Byb2Nlc3MSDgoMaGllcmFyY2hpY2FsShEKC2NyZXdfbWVtb3J5EgIQAEoaChRjcmV3X251
+      bWJlcl9vZl90YXNrcxICGAFKGwoVY3Jld19udW1iZXJfb2ZfYWdlbnRzEgIYAUo6ChBjcmV3X2Zp
+      bmdlcnByaW50EiYKJDMzZDRkZWU1LWIxOTEtNDAzYy04OWEwLTYyNWJiNjVmMmYxOUo7ChtjcmV3
+      X2ZpbmdlcnByaW50X2NyZWF0ZWRfYXQSHAoaMjAyNS0wNC0xN1QxNDozMzo0My41NDg4OThKzQIK
+      C2NyZXdfYWdlbnRzEr0CCroCW3sia2V5IjogIjkyZTdlYjE5MTY2NGM5MzU3ODVlZDdkNDI0MGEy
+      OTRkIiwgImlkIjogImE0Mzc1OWYyLTY0NDEtNDNiMy1hOGRjLWYxYmQzMTU3MDdlZiIsICJyb2xl
+      IjogIlNjb3JlciIsICJ2ZXJib3NlPyI6IGZhbHNlLCAibWF4X2l0ZXIiOiAyNSwgIm1heF9ycG0i
+      OiBudWxsLCAiZnVuY3Rpb25fY2FsbGluZ19sbG0iOiAiIiwgImxsbSI6ICJncHQtNG8tbWluaSIs
+      ICJkZWxlZ2F0aW9uX2VuYWJsZWQ/IjogZmFsc2UsICJhbGxvd19jb2RlX2V4ZWN1dGlvbj8iOiBm
+      YWxzZSwgIm1heF9yZXRyeV9saW1pdCI6IDIsICJ0b29sc19uYW1lcyI6IFtdfV1K2wEKCmNyZXdf
+      dGFza3MSzAEKyQFbeyJrZXkiOiAiMjdlZjM4Y2M5OWRhNGE4ZGVkNzBlZDQwNmU0NGFiODYiLCAi
+      aWQiOiAiMDVmYzk4OWItMDY5Mi00ODAzLTgyMTMtMWQ2ODY5YTYwMTBlIiwgImFzeW5jX2V4ZWN1
+      dGlvbj8iOiBmYWxzZSwgImh1bWFuX2lucHV0PyI6IGZhbHNlLCAiYWdlbnRfcm9sZSI6ICJOb25l
+      IiwgImFnZW50X2tleSI6IG51bGwsICJ0b29sc19uYW1lcyI6IFtdfV16AhgBhQEAAQAAEoAEChDT
+      QOB/rAOBZumhFuP0yYFYEggS6cvMoHzBYioMVGFzayBDcmVhdGVkMAE5cB9dTIMrNxhBeHFdTIMr
+      NxhKLgoIY3Jld19rZXkSIgogNWU2ZWZmZTY4MGE1ZDk3ZGMzODczYjE0ODI1Y2NmYTNKMQoHY3Jl
+      d19pZBImCiQ2NzZiMTY5YS0yOWE2LTQ1YTgtOTZjYy02ODIzMjc4M2JlNzVKLgoIdGFza19rZXkS
+      IgogMjdlZjM4Y2M5OWRhNGE4ZGVkNzBlZDQwNmU0NGFiODZKMQoHdGFza19pZBImCiQwNWZjOTg5
+      Yi0wNjkyLTQ4MDMtODIxMy0xZDY4NjlhNjAxMGVKOgoQY3Jld19maW5nZXJwcmludBImCiQzM2Q0
+      ZGVlNS1iMTkxLTQwM2MtODlhMC02MjViYjY1ZjJmMTlKOgoQdGFza19maW5nZXJwcmludBImCiQ2
+      MGIzYTVkNi04MWUxLTQzOGYtOTE3Yy0yNjU4MzU4NjdmNzZKOwobdGFza19maW5nZXJwcmludF9j
+      cmVhdGVkX2F0EhwKGjIwMjUtMDQtMTdUMTQ6MzM6NDMuNTQ4ODcwSjsKEWFnZW50X2ZpbmdlcnBy
+      aW50EiYKJDgwZjQ2NDkxLWM0YjItNDExNy05MTM2LTZhOTQxZjI5ODBiZHoCGAGFAQABAAASnAEK
+      EObnhSrs8UQiBg/0Bricu2cSCMFW2rX4WlIFKgpUb29sIFVzYWdlMAE5CJ26TIMrNxhBmE/DTIMr
+      NxhKGwoOY3Jld2FpX3ZlcnNpb24SCQoHMC4xMTQuMEonCgl0b29sX25hbWUSGgoYQXNrIHF1ZXN0
+      aW9uIHRvIGNvd29ya2VySg4KCGF0dGVtcHRzEgIYAXoCGAGFAQABAAAS0AoKEBk04hfXjSFQOWWK
+      xJFMHB8SCLGFr6R51/OhKgxDcmV3IENyZWF0ZWQwATl4TzNNgys3GEFIMzlNgys3GEobCg5jcmV3
+      YWlfdmVyc2lvbhIJCgcwLjExNC4wShsKDnB5dGhvbl92ZXJzaW9uEgkKBzMuMTEuMTJKLgoIY3Jl
+      d19rZXkSIgogNzQyNzU3MzEyZWY3YmI0ZWUwYjA2NjJkMWMyZTIxNzlKMQoHY3Jld19pZBImCiQ2
+      MWRiMTdjYi0xODQ3LTRmYzktOWNkMy1hMDY3ZjRkOGExMzRKHAoMY3Jld19wcm9jZXNzEgwKCnNl
+      cXVlbnRpYWxKEQoLY3Jld19tZW1vcnkSAhAAShoKFGNyZXdfbnVtYmVyX29mX3Rhc2tzEgIYAUob
+      ChVjcmV3X251bWJlcl9vZl9hZ2VudHMSAhgCSjoKEGNyZXdfZmluZ2VycHJpbnQSJgokNjQ3OGY2
+      MjItZGVlOC00OWYyLTljMDktOGNiOTBjMjEwYzNjSjsKG2NyZXdfZmluZ2VycHJpbnRfY3JlYXRl
+      ZF9hdBIcChoyMDI1LTA0LTE3VDE0OjMzOjQzLjU2NDI2NEqGBQoLY3Jld19hZ2VudHMS9gQK8wRb
+      eyJrZXkiOiAiODljZjMxMWI0OGI1MjE2OWQ0MmYzOTI1YzViZTFjNWEiLCAiaWQiOiAiM2E3YjUx
+      ZGItYzhhZC00ZDU3LWE1OGUtOGIzY2EyYzIxZTI2IiwgInJvbGUiOiAiTWFuYWdlciIsICJ2ZXJi
+      b3NlPyI6IGZhbHNlLCAibWF4X2l0ZXIiOiAyNSwgIm1heF9ycG0iOiBudWxsLCAiZnVuY3Rpb25f
+      Y2FsbGluZ19sbG0iOiAiIiwgImxsbSI6ICJncHQtNG8tbWluaSIsICJkZWxlZ2F0aW9uX2VuYWJs
+      ZWQ/IjogdHJ1ZSwgImFsbG93X2NvZGVfZXhlY3V0aW9uPyI6IGZhbHNlLCAibWF4X3JldHJ5X2xp
+      bWl0IjogMiwgInRvb2xzX25hbWVzIjogW119LCB7ImtleSI6ICI5MmU3ZWIxOTE2NjRjOTM1Nzg1
+      ZWQ3ZDQyNDBhMjk0ZCIsICJpZCI6ICIxNWZiMjExOC0zOTE0LTQ2ZTctODRkZi05M2E5ZDA0ZWVj
+      M2YiLCAicm9sZSI6ICJTY29yZXIiLCAidmVyYm9zZT8iOiBmYWxzZSwgIm1heF9pdGVyIjogMjUs
+      ICJtYXhfcnBtIjogbnVsbCwgImZ1bmN0aW9uX2NhbGxpbmdfbGxtIjogIiIsICJsbG0iOiAiZ3B0
+      LTRvLW1pbmkiLCAiZGVsZWdhdGlvbl9lbmFibGVkPyI6IHRydWUsICJhbGxvd19jb2RlX2V4ZWN1
+      dGlvbj8iOiBmYWxzZSwgIm1heF9yZXRyeV9saW1pdCI6IDIsICJ0b29sc19uYW1lcyI6IFtdfV1K
+      /AEKCmNyZXdfdGFza3MS7QEK6gFbeyJrZXkiOiAiMjdlZjM4Y2M5OWRhNGE4ZGVkNzBlZDQwNmU0
+      NGFiODYiLCAiaWQiOiAiMzcwNTE2YzQtNWNhMC00NDBjLWE3YTctNWFhMjZiMDQ4MmFmIiwgImFz
+      eW5jX2V4ZWN1dGlvbj8iOiBmYWxzZSwgImh1bWFuX2lucHV0PyI6IGZhbHNlLCAiYWdlbnRfcm9s
+      ZSI6ICJNYW5hZ2VyIiwgImFnZW50X2tleSI6ICI4OWNmMzExYjQ4YjUyMTY5ZDQyZjM5MjVjNWJl
+      MWM1YSIsICJ0b29sc19uYW1lcyI6IFtdfV16AhgBhQEAAQAAEoAEChBGCATWQjaQu6Zpx66QI8ik
+      Egg05IWKCa/6oyoMVGFzayBDcmVhdGVkMAE54CVFTYMrNxhB0HtFTYMrNxhKLgoIY3Jld19rZXkS
+      IgogNzQyNzU3MzEyZWY3YmI0ZWUwYjA2NjJkMWMyZTIxNzlKMQoHY3Jld19pZBImCiQ2MWRiMTdj
+      Yi0xODQ3LTRmYzktOWNkMy1hMDY3ZjRkOGExMzRKLgoIdGFza19rZXkSIgogMjdlZjM4Y2M5OWRh
+      NGE4ZGVkNzBlZDQwNmU0NGFiODZKMQoHdGFza19pZBImCiQzNzA1MTZjNC01Y2EwLTQ0MGMtYTdh
+      Ny01YWEyNmIwNDgyYWZKOgoQY3Jld19maW5nZXJwcmludBImCiQ2NDc4ZjYyMi1kZWU4LTQ5ZjIt
+      OWMwOS04Y2I5MGMyMTBjM2NKOgoQdGFza19maW5nZXJwcmludBImCiQxMWU1ZDRhNi04ODc5LTQx
+      ZDktYWE3ZS04OTdhNDMzMDhlZWVKOwobdGFza19maW5nZXJwcmludF9jcmVhdGVkX2F0EhwKGjIw
+      MjUtMDQtMTdUMTQ6MzM6NDMuNTY0MjMzSjsKEWFnZW50X2ZpbmdlcnByaW50EiYKJGUyMzRlYzA5
+      LTk3MzktNGE3Zi04MDgxLTBhNjJkYzNlNzY1ZHoCGAGFAQABAAASnQEKEFjGvzVUde99Ey+6qDaD
+      oG4SCFWLiXG8McaKKgpUb29sIFVzYWdlMAE5kI2lTYMrNxhBMG2tTYMrNxhKGwoOY3Jld2FpX3Zl
+      cnNpb24SCQoHMC4xMTQuMEooCgl0b29sX25hbWUSGwoZRGVsZWdhdGUgd29yayB0byBjb3dvcmtl
+      ckoOCghhdHRlbXB0cxICGAF6AhgBhQEAAQAAEooIChCB+QR8dk6jPImbeJiKh5UYEgj00bY0zkAX
+      LSoMQ3JldyBDcmVhdGVkMAE5cAkrToMrNxhBKNM1ToMrNxhKGwoOY3Jld2FpX3ZlcnNpb24SCQoH
+      MC4xMTQuMEobCg5weXRob25fdmVyc2lvbhIJCgczLjExLjEySi4KCGNyZXdfa2V5EiIKIDMwM2I4
+      ZWRkNWIwMDg3MTBkNzZhYWY4MjVhNzA5ZTU1SjEKB2NyZXdfaWQSJgokNmUzM2ZiOTItNTZjMC00
+      OTY3LTk1MjItZGQ3ZWFhOWY5NjFlSh4KDGNyZXdfcHJvY2VzcxIOCgxoaWVyYXJjaGljYWxKEQoL
+      Y3Jld19tZW1vcnkSAhAAShoKFGNyZXdfbnVtYmVyX29mX3Rhc2tzEgIYAUobChVjcmV3X251bWJl
+      cl9vZl9hZ2VudHMSAhgBSjoKEGNyZXdfZmluZ2VycHJpbnQSJgokNDY5MjUyODctOTY2OS00MTRl
+      LWEwNzctZGVjNDE2ZTE3NDRlSjsKG2NyZXdfZmluZ2VycHJpbnRfY3JlYXRlZF9hdBIcChoyMDI1
+      LTA0LTE3VDE0OjMzOjQzLjU4MDUyM0rfAgoLY3Jld19hZ2VudHMSzwIKzAJbeyJrZXkiOiAiOTJl
+      N2ViMTkxNjY0YzkzNTc4NWVkN2Q0MjQwYTI5NGQiLCAiaWQiOiAiNzllZTU5MjktNjdlMy00NjNi
+      LTljYjEtMjFlNTdjNjZlNGQ4IiwgInJvbGUiOiAiU2NvcmVyIiwgInZlcmJvc2U/IjogZmFsc2Us
+      ICJtYXhfaXRlciI6IDI1LCAibWF4X3JwbSI6IG51bGwsICJmdW5jdGlvbl9jYWxsaW5nX2xsbSI6
+      ICIiLCAibGxtIjogImdwdC00by1taW5pIiwgImRlbGVnYXRpb25fZW5hYmxlZD8iOiBmYWxzZSwg
+      ImFsbG93X2NvZGVfZXhlY3V0aW9uPyI6IGZhbHNlLCAibWF4X3JldHJ5X2xpbWl0IjogMiwgInRv
+      b2xzX25hbWVzIjogWyJzY29yaW5nX2V4YW1wbGVzIl19XUrbAQoKY3Jld190YXNrcxLMAQrJAVt7
+      ImtleSI6ICJmMzU3NWIwMTNjMjI5NGI3Y2M4ZTgwMzE1NWM4YmE0NiIsICJpZCI6ICJhZTlmMjgz
+      MC1hY2NhLTRiNmQtOGRjNy01MjMzZmZlYmJhM2QiLCAiYXN5bmNfZXhlY3V0aW9uPyI6IGZhbHNl
+      LCAiaHVtYW5faW5wdXQ/IjogZmFsc2UsICJhZ2VudF9yb2xlIjogIk5vbmUiLCAiYWdlbnRfa2V5
+      IjogbnVsbCwgInRvb2xzX25hbWVzIjogW119XXoCGAGFAQABAAASgAQKEHOf6gKzlTQXpW3qTaF+
+      AlQSCIXd9+wt3hyiKgxUYXNrIENyZWF0ZWQwATkws0hOgys3GEE4BUlOgys3GEouCghjcmV3X2tl
+      eRIiCiAzMDNiOGVkZDViMDA4NzEwZDc2YWFmODI1YTcwOWU1NUoxCgdjcmV3X2lkEiYKJDZlMzNm
+      YjkyLTU2YzAtNDk2Ny05NTIyLWRkN2VhYTlmOTYxZUouCgh0YXNrX2tleRIiCiBmMzU3NWIwMTNj
+      MjI5NGI3Y2M4ZTgwMzE1NWM4YmE0NkoxCgd0YXNrX2lkEiYKJGFlOWYyODMwLWFjY2EtNGI2ZC04
+      ZGM3LTUyMzNmZmViYmEzZEo6ChBjcmV3X2ZpbmdlcnByaW50EiYKJDQ2OTI1Mjg3LTk2NjktNDE0
+      ZS1hMDc3LWRlYzQxNmUxNzQ0ZUo6ChB0YXNrX2ZpbmdlcnByaW50EiYKJDU4ZGVjODNjLWFjZTQt
+      NGI1Ni05YzhjLWQyZGQ1YjVlMWYyNUo7Cht0YXNrX2ZpbmdlcnByaW50X2NyZWF0ZWRfYXQSHAoa
+      MjAyNS0wNC0xN1QxNDozMzo0My41ODA0OTNKOwoRYWdlbnRfZmluZ2VycHJpbnQSJgokMGVjNzAw
+      NWEtOGMzOC00N2RlLWI5YzctNjc3ZmFkOTU2ZmMzegIYAYUBAAEAABJpChDdogUTH/ocvPeyU/F2
+      dgcNEghEqOA/7aEsiyoQVG9vbCBVc2FnZSBFcnJvcjABOVBbt06DKzcYQajPvU6DKzcYShsKDmNy
+      ZXdhaV92ZXJzaW9uEgkKBzAuMTE0LjB6AhgBhQEAAQAAEp0BChD7kRw1jX3K2nusXZXPvHyGEghl
+      QFQp8mFhuCoKVG9vbCBVc2FnZTABORCS/E6DKzcYQXDPBE+DKzcYShsKDmNyZXdhaV92ZXJzaW9u
+      EgkKBzAuMTE0LjBKKAoJdG9vbF9uYW1lEhsKGURlbGVnYXRlIHdvcmsgdG8gY293b3JrZXJKDgoI
+      YXR0ZW1wdHMSAhgBegIYAYUBAAEAAA==
+    headers:
+      Accept:
+      - '*/*'
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '27952'
+      Content-Type:
+      - application/x-protobuf
+      User-Agent:
+      - OTel-OTLP-Exporter-Python/1.31.1
+    method: POST
+    uri: https://telemetry.crewai.com:4319/v1/traces
+  response:
+    body:
+      string: "\n\0"
+    headers:
+      Content-Length:
+      - '2'
+      Content-Type:
+      - application/x-protobuf
+      Date:
+      - Thu, 17 Apr 2025 17:33:47 GMT
+    status:
+      code: 200
+      message: OK
+version: 1

tests/cassettes/test_task_with_max_execution_time_exceeded.yaml

@@ -0,0 +1,81 @@
+interactions:
+- request:
+    body: '{"contents": [{"role": "user", "parts": [{"text": "\nCurrent Task: Give
+      me a list of 5 interesting ideas to explore for an article, what makes them
+      unique and interesting.\n\nThis is the expected criteria for your final answer:
+      Bullet point list of 5 interesting ideas.\nyou MUST return the actual complete
+      content as the final answer, not a summary.\n\nBegin! This is VERY important
+      to you, use the tools available and give your best Final Answer, your job depends
+      on it!\n\nThought:"}]}], "system_instruction": {"parts": [{"text": "You are
+      Researcher. You''re an expert researcher, specialized in technology, software
+      engineering, AI and startups. You work as a freelancer and are now working on
+      doing research and analysis for a new customer.\nYour personal goal is: Make
+      the best research and analysis on content about AI and AI agents. Use the tool
+      provided to you.\nYou ONLY have access to the following tools, and should NEVER
+      make up tools that are not listed here:\n\nTool Name: what amazing tool\nTool
+      Arguments: {}\nTool Description: My tool\n\nIMPORTANT: Use the following format
+      in your response:\n\n```\nThought: you should always think about what to do\nAction:
+      the action to take, only one name of [what amazing tool], just the name, exactly
+      as it''s written.\nAction Input: the input to the action, just a simple JSON
+      object, enclosed in curly braces, using \" to wrap keys and values.\nObservation:
+      the result of the action\n```\n\nOnce all necessary information is gathered,
+      return the following format:\n\n```\nThought: I now know the final answer\nFinal
+      Answer: the final answer to the original input question\n```"}]}, "generationConfig":
+      {"temperature": 0.7, "stop_sequences": ["\nObservation:"]}}'
+    headers:
+      accept:
+      - '*/*'
+      accept-encoding:
+      - gzip, deflate
+      connection:
+      - keep-alive
+      content-length:
+      - '1718'
+      content-type:
+      - application/json
+      host:
+      - generativelanguage.googleapis.com
+      user-agent:
+      - litellm/1.60.2
+    method: POST
+    uri: https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent
+  response:
+    body:
+      string: !!binary |
+        H4sIAAAAAAAC/61STWvbQBC961cMe+klFnJUy8S30JZiaGloTQlEOaylibRktavujtKkxv+9s3Lk
+        rE2PFUha9r2Z9+ZjlwCISppa1ZLQixXc8Q3AbvwGzBpCQwxMV3zZS0dv3MOzi85MIXwOQWLT2qFp
+        aQVrMIg1kIUGDTpWA1Wj9PBgHUgDnFJVGkFu7UBwvea7evwxnXwKsH6nNQwegVp+rdUhV4u6hw5h
+        66Qynqzr0tKU5roiZc0KfreSQHbyjzLNGDNBsDb9wK52pfg1oHsp2WspPk/OFqC4bIeeQuA/feJz
+        r60L8LnXC6ZWgw8QC40WOvmIHlBW7ZgMBqNYdgyLhNJS7EXUxv3xfH/x1nxnNYbOdrZGPdH3E0E8
+        KKN8+50dWxNoPzbfbsQRlU/NF9v0zm7D/GZZml1dLoti8X4+X+RFvszzPJmkR1ExeK7qK5LkBZHH
+        NRCcoutpYx/RfLDDuCB5nh10ooU6IRTLV5wsSX0aezVhUWL/kWWVjjctWkKuX2pFL+OWfbrdiKhH
+        dOZr6lISNfPc5X9SK5anYsnrcA7z+onOq8NgGux4VLN5uphxzbMsuxTJPvkLk2fgU5EDAAA=
+    headers:
+      Alt-Svc:
+      - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
+      Content-Encoding:
+      - gzip
+      Content-Type:
+      - application/json; charset=UTF-8
+      Date:
+      - Thu, 17 Apr 2025 19:00:14 GMT
+      Server:
+      - scaffolding on HTTPServer2
+      Server-Timing:
+      - gfet4t7; dur=1972
+      Transfer-Encoding:
+      - chunked
+      Vary:
+      - Origin
+      - X-Origin
+      - Referer
+      X-Content-Type-Options:
+      - nosniff
+      X-Frame-Options:
+      - SAMEORIGIN
+      X-XSS-Protection:
+      - '0'
+    status:
+      code: 200
+      message: OK
+version: 1

tests/task_test.py

@@ -3,6 +3,7 @@
 import hashlib
 import json
 import os
+import time
 from functools import partial
 from typing import Tuple, Union
 from unittest.mock import MagicMock, patch
@@ -1368,3 +1369,90 @@ def test_interpolate_valid_types():
     assert parsed["optional"] is None
     assert parsed["nested"]["flag"] is True
     assert parsed["nested"]["empty"] is None
+
+
+def test_task_with_no_max_execution_time():
+    researcher = Agent(
+    role="Researcher",
+    goal="Make the best research and analysis on content about AI and AI agents",
+    backstory="You're an expert researcher, specialized in technology, software engineering, AI and startups. You work as a freelancer and is now working on doing research and analysis for a new customer.",
+    allow_delegation=False,
+    max_execution_time=None
+    )
+
+    task = Task(
+        description="Give me a list of 5 interesting ideas to explore for na article, what makes them unique and interesting.",
+        expected_output="Bullet point list of 5 interesting ideas.",
+        agent=researcher,
+    )
+
+    with patch.object(Agent, "_execute_without_timeout", return_value = "ok") as execute:
+        result = task.execute_sync(agent=researcher)
+        assert result.raw == "ok"
+        execute.assert_called_once()
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_task_with_max_execution_time():
+    from crewai.tools import tool
+    """Test that execution raises TimeoutError when max_execution_time is exceeded."""
+
+    @tool("what amazing tool", result_as_answer=True)
+    def my_tool() -> str:
+        "My tool"
+        time.sleep(1)
+        return "okay"
+
+    researcher = Agent(
+        role="Researcher",
+        goal="Make the best research and analysis on content about AI and AI agents. Use the tool provided to you.",
+        backstory=(
+            "You're an expert researcher, specialized in technology, software engineering, AI and startups. "
+            "You work as a freelancer and are now working on doing research and analysis for a new customer."
+        ),
+        allow_delegation=False,
+        tools=[my_tool],
+        max_execution_time=4
+    )
+
+    task = Task(
+        description="Give me a list of 5 interesting ideas to explore for an article, what makes them unique and interesting.",
+        expected_output="Bullet point list of 5 interesting ideas.",
+        agent=researcher,
+    )
+
+    result = task.execute_sync(agent=researcher)
+    assert result.raw == "okay"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_task_with_max_execution_time_exceeded():
+    from crewai.tools import tool
+    """Test that execution raises TimeoutError when max_execution_time is exceeded."""
+
+    @tool("what amazing tool", result_as_answer=True)
+    def my_tool() -> str:
+        "My tool"
+        time.sleep(10)
+        return "okay"
+
+    researcher = Agent(
+        role="Researcher",
+        goal="Make the best research and analysis on content about AI and AI agents. Use the tool provided to you.",
+        backstory=(
+            "You're an expert researcher, specialized in technology, software engineering, AI and startups. "
+            "You work as a freelancer and are now working on doing research and analysis for a new customer."
+        ),
+        allow_delegation=False,
+        tools=[my_tool],
+        max_execution_time=1
+    )
+
+    task = Task(
+        description="Give me a list of 5 interesting ideas to explore for an article, what makes them unique and interesting.",
+        expected_output="Bullet point list of 5 interesting ideas.",
+        agent=researcher,
+    )
+
+    with pytest.raises(TimeoutError):
+        task.execute_sync(agent=researcher)