Merge branch 'main' into lg-guardrail-llm

It is used internally and should not be recommended for building tools intended for Agent consumption

docs/concepts/agents.mdx

@@ -255,7 +255,11 @@ custom_agent = Agent(
 - `response_template`: Formats agent responses
 
 <Note>
-When using custom templates, you can use variables like `{role}`, `{goal}`, and `{input}` in your templates. These will be automatically populated during execution.
+When using custom templates, ensure that both `system_template` and `prompt_template` are defined. The `response_template` is optional but recommended for consistent output formatting.
+</Note>  
+
+<Note>
+When using custom templates, you can use variables like `{role}`, `{goal}`, and `{backstory}` in your templates. These will be automatically populated during execution.
 </Note>
 
 ## Agent Tools

docs/concepts/tasks.mdx

@@ -322,6 +322,10 @@ blog_task = Task(
    - On success: it returns a tuple of `(bool, Any)`. For example: `(True, validated_result)` 
    - On Failure: it returns a tuple of `(bool, str)`. For example: `(False, "Error message explain the failure")`
 
+### TaskGuardrail
+
+The `TaskGuardrail` class offers a robust mechanism for validating task outputs
+
 ### Error Handling Best Practices
 
 1. **Structured Error Responses**:
@@ -750,6 +754,8 @@ Task guardrails provide a powerful way to validate, transform, or filter task ou
 
 ### Basic Usage
 
+#### Define your own logic to validate
+
 ```python Code
 from typing import Tuple, Union
 from crewai import Task
@@ -769,6 +775,57 @@ task = Task(
 )
 ```
 
+#### Leverage a no-code approach for validation
+
+```python Code
+from crewai import Task
+
+task = Task(
+    description="Generate JSON data",
+    expected_output="Valid JSON object",
+    guardrail="Ensure the response is a valid JSON object"
+)
+```
+
+#### Using YAML
+
+```yaml
+research_task:
+  ...
+  guardrail: make sure each bullet contains a minimum of 100 words
+  ...
+```
+
+```python Code
+@CrewBase
+class InternalCrew:
+    agents_config = "config/agents.yaml"
+    tasks_config = "config/tasks.yaml"
+
+    ...
+    @task
+    def research_task(self):
+        return Task(config=self.tasks_config["research_task"])  # type: ignore[index]
+    ...
+```
+
+
+#### Use custom models for code generation
+
+```python Code
+from crewai import Task
+from crewai.llm import LLM
+
+task = Task(
+    description="Generate JSON data",
+    expected_output="Valid JSON object",
+    guardrail=TaskGuardrail(
+        description="Ensure the response is a valid JSON object",
+        llm=LLM(model="gpt-4o-mini"),
+    )
+)
+```
+
 ### How Guardrails Work
 
 1. **Optional Attribute**: Guardrails are an optional attribute at the task level, allowing you to add validation only where needed.

docs/concepts/tools.mdx

@@ -190,48 +190,6 @@ def my_tool(question: str) -> str:
     return "Result from your custom tool"
 ```
 
-### Structured Tools
-
-The `StructuredTool` class wraps functions as tools, providing flexibility and validation while reducing boilerplate. It supports custom schemas and dynamic logic for seamless integration of complex functionalities.
-
-#### Example:
-Using `StructuredTool.from_function`, you can wrap a function that interacts with an external API or system, providing a structured interface. This enables robust validation and consistent execution, making it easier to integrate complex functionalities into your applications as demonstrated in the following example:
-
-```python
-from crewai.tools.structured_tool import CrewStructuredTool
-from pydantic import BaseModel
-
-# Define the schema for the tool's input using Pydantic
-class APICallInput(BaseModel):
-    endpoint: str
-    parameters: dict
-
-# Wrapper function to execute the API call
-def tool_wrapper(*args, **kwargs):
-    # Here, you would typically call the API using the parameters
-    # For demonstration, we'll return a placeholder string
-    return f"Call the API at {kwargs['endpoint']} with parameters {kwargs['parameters']}"
-
-# Create and return the structured tool
-def create_structured_tool():
-    return CrewStructuredTool.from_function(
-        name='Wrapper API',
-        description="A tool to wrap API calls with structured input.",
-        args_schema=APICallInput,
-        func=tool_wrapper,
-    )
-
-# Example usage
-structured_tool = create_structured_tool()
-
-# Execute the tool with structured input
-result = structured_tool._run(**{
-    "endpoint": "https://example.com/api",
-    "parameters": {"key1": "value1", "key2": "value2"}
-})
-print(result)  # Output: Call the API at https://example.com/api with parameters {'key1': 'value1', 'key2': 'value2'}
-```
-
 ### Custom Caching Mechanism
 
 <Tip>

docs/docs.json

@@ -180,6 +180,42 @@
           }
         ]
       },
+      {
+        "tab": "Enterprise",
+        "groups": [
+          {
+            "group": "Getting Started",
+            "pages": [
+              "enterprise/introduction"
+            ]
+          },
+          {
+            "group": "How-To Guides",
+            "pages": [
+              "enterprise/guides/build-crew",
+              "enterprise/guides/deploy-crew",
+              "enterprise/guides/kickoff-crew",
+              "enterprise/guides/update-crew",
+              "enterprise/guides/use-crew-api",
+              "enterprise/guides/enable-crew-studio"
+            ]
+          },
+          {
+            "group": "Features",
+            "pages": [
+              "enterprise/features/tool-repository",
+              "enterprise/features/webhook-streaming",
+              "enterprise/features/traces"
+            ]
+          },
+          {
+            "group": "Resources",
+            "pages": [
+              "enterprise/resources/frequently-asked-questions"
+            ]
+          }
+        ]
+      },
       {
         "tab": "Examples",
         "groups": [

docs/enterprise/features/tool-repository.mdx

@@ -0,0 +1,106 @@
+---
+title: Tool Repository
+description: "Using the Tool Repository to manage your tools"
+icon: "toolbox"
+---
+
+## Overview
+
+The Tool Repository is a package manager for CrewAI tools. It allows users to publish, install, and manage tools that integrate with CrewAI crews and flows.
+
+Tools can be:
+
+- **Private**: accessible only within your organization (default)
+- **Public**: accessible to all CrewAI users if published with the `--public` flag
+
+The repository is not a version control system. Use Git to track code changes and enable collaboration.
+
+## Prerequisites
+
+Before using the Tool Repository, ensure you have:
+
+- A [CrewAI Enterprise](https://app.crewai.com) account
+- [CrewAI CLI](https://docs.crewai.com/concepts/cli#cli) installed
+- [Git](https://git-scm.com) installed and configured
+- Access permissions to publish or install tools in your CrewAI Enterprise organization
+
+## Installing Tools
+
+To install a tool:
+
+```bash
+crewai tool install <tool-name>
+```
+
+This installs the tool and adds it to `pyproject.toml`.
+
+## Creating and Publishing Tools
+
+To create a new tool project:
+
+```bash
+crewai tool create <tool-name>
+```
+
+This generates a scaffolded tool project locally.
+
+After making changes, initialize a Git repository and commit the code:
+
+```bash
+git init
+git add .
+git commit -m "Initial version"
+```
+
+To publish the tool:
+
+```bash
+crewai tool publish
+```
+
+By default, tools are published as private. To make a tool public:
+
+```bash
+crewai tool publish --public
+```
+
+For more details on how to build tools, see [Creating your own tools](https://docs.crewai.com/concepts/tools#creating-your-own-tools).
+
+## Updating Tools
+
+To update a published tool:
+
+1. Modify the tool locally
+2. Update the version in `pyproject.toml` (e.g., from `0.1.0` to `0.1.1`)
+3. Commit the changes and publish
+
+```bash
+git commit -m "Update version to 0.1.1"
+crewai tool publish
+```
+
+## Deleting Tools
+
+To delete a tool:
+
+1. Go to [CrewAI Enterprise](https://app.crewai.com)
+2. Navigate to **Tools**
+3. Select the tool
+4. Click **Delete**
+
+<Warning>
+Deletion is permanent. Deleted tools cannot be restored or re-installed.
+</Warning>
+
+## Security Checks
+
+Every published version undergoes automated security checks, and are only available to install after they pass. 
+
+You can check the security check status of a tool at:
+
+`CrewAI Enterprise > Tools > Your Tool > Versions`
+
+
+<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+  Contact our support team for assistance with API integration or troubleshooting.
+</Card>

docs/enterprise/features/traces.mdx

@@ -0,0 +1,146 @@
+---
+title: Traces
+description: "Using Traces to monitor your Crews"
+icon: "timeline"
+---
+
+## Overview
+
+Traces provide comprehensive visibility into your crew executions, helping you monitor performance, debug issues, and optimize your AI agent workflows.
+
+## What are Traces?
+
+Traces in CrewAI Enterprise are detailed execution records that capture every aspect of your crew's operation, from initial inputs to final outputs. They record:
+
+- Agent thoughts and reasoning
+- Task execution details
+- Tool usage and outputs
+- Token consumption metrics
+- Execution times
+- Cost estimates
+
+<Frame>
+  ![Traces Overview](/images/enterprise/traces-overview.png)
+</Frame>
+
+## Accessing Traces
+
+<Steps>
+  <Step title="Navigate to the Traces Tab">
+    Once in your CrewAI Enterprise dashboard, click on the **Traces** to view all execution records.
+  </Step>
+  
+  <Step title="Select an Execution">
+    You'll see a list of all crew executions, sorted by date. Click on any execution to view its detailed trace.
+  </Step>
+</Steps>
+
+## Understanding the Trace Interface
+
+The trace interface is divided into several sections, each providing different insights into your crew's execution:
+
+### 1. Execution Summary
+
+The top section displays high-level metrics about the execution:
+
+- **Total Tokens**: Number of tokens consumed across all tasks
+- **Prompt Tokens**: Tokens used in prompts to the LLM
+- **Completion Tokens**: Tokens generated in LLM responses
+- **Requests**: Number of API calls made
+- **Execution Time**: Total duration of the crew run
+- **Estimated Cost**: Approximate cost based on token usage
+
+<Frame>
+  ![Execution Summary](/images/enterprise/trace-summary.png)
+</Frame>
+
+### 2. Tasks & Agents
+
+This section shows all tasks and agents that were part of the crew execution:
+
+- Task name and agent assignment
+- Agents and LLMs used for each task
+- Status (completed/failed)
+- Individual execution time of the task
+
+<Frame>
+  ![Task List](/images/enterprise/trace-tasks.png)
+</Frame>
+
+### 3. Final Output
+
+Displays the final result produced by the crew after all tasks are completed.
+
+<Frame>
+  ![Final Output](/images/enterprise/final-output.png)
+</Frame>
+
+### 4. Execution Timeline
+
+A visual representation of when each task started and ended, helping you identify bottlenecks or parallel execution patterns.
+
+<Frame>
+  ![Execution Timeline](/images/enterprise/trace-timeline.png)
+</Frame>
+
+### 5. Detailed Task View
+
+When you click on a specific task in the timeline or task list, you'll see:
+
+<Frame>
+  ![Detailed Task View](/images/enterprise/trace-detailed-task.png)
+</Frame>
+
+- **Task Key**: Unique identifier for the task
+- **Task ID**: Technical identifier in the system
+- **Status**: Current state (completed/running/failed)
+- **Agent**: Which agent performed the task
+- **LLM**: Language model used for this task
+- **Start/End Time**: When the task began and completed
+- **Execution Time**: Duration of this specific task
+- **Task Description**: What the agent was instructed to do
+- **Expected Output**: What output format was requested
+- **Input**: Any input provided to this task from previous tasks
+- **Output**: The actual result produced by the agent
+
+
+## Using Traces for Debugging
+
+Traces are invaluable for troubleshooting issues with your crews:
+
+<Steps>
+  <Step title="Identify Failure Points">
+    When a crew execution doesn't produce the expected results, examine the trace to find where things went wrong. Look for:
+    
+    - Failed tasks
+    - Unexpected agent decisions
+    - Tool usage errors
+    - Misinterpreted instructions
+
+    <Frame>
+      ![Failure Points](/images/enterprise/failure.png)
+    </Frame>
+  </Step>
+  
+  <Step title="Optimize Performance">
+    Use execution metrics to identify performance bottlenecks:
+    
+    - Tasks that took longer than expected
+    - Excessive token usage
+    - Redundant tool operations
+    - Unnecessary API calls
+  </Step>
+  
+  <Step title="Improve Cost Efficiency">
+    Analyze token usage and cost estimates to optimize your crew's efficiency:
+    
+    - Consider using smaller models for simpler tasks
+    - Refine prompts to be more concise
+    - Cache frequently accessed information
+    - Structure tasks to minimize redundant operations
+  </Step>
+</Steps>
+
+<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+  Contact our support team for assistance with trace analysis or any other CrewAI Enterprise features.
+</Card>

docs/enterprise/features/webhook-streaming.mdx

@@ -0,0 +1,82 @@
+---
+title: Webhook Streaming
+description: "Using Webhook Streaming to stream events to your webhook"
+icon: "webhook"
+---
+
+## Overview
+
+Enterprise Event Streaming lets you receive real-time webhook updates about your crews and flows deployed to 
+CrewAI Enterprise, such as model calls, tool usage, and flow steps.
+
+## Usage
+
+When using the Kickoff API, include a `webhooks` object to your request, for example:
+
+```json
+{
+  "inputs": {"foo": "bar"},
+  "webhooks": {
+    "events": ["crew_kickoff_started", "llm_call_started"],
+    "url": "https://your.endpoint/webhook",
+    "realtime": false,
+    "authentication": {
+      "strategy": "bearer",
+      "token": "my-secret-token"
+    }
+  }
+}
+```
+
+If `realtime` is set to `true`, each event is delivered individually and immediately, at the cost of crew/flow performance.
+
+## Webhook Format
+
+Each webhook sends a list of events:
+
+```json
+{
+  "events": [
+    {
+      "id": "event-id",
+      "execution_id": "crew-run-id",
+      "timestamp": "2025-02-16T10:58:44.965Z",
+      "type": "llm_call_started",
+      "data": {
+        "model": "gpt-4",
+        "messages": [
+          {"role": "system", "content": "You are an assistant."},
+          {"role": "user", "content": "Summarize this article."}
+        ]
+      }
+    }
+  ]
+}
+```
+
+The `data` object structure varies by event type. Refer to the [event list](https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events) on GitHub.
+
+As requests are sent over HTTP, the order of events can't be guaranteed. If you need ordering, use the `timestamp` field.
+
+## Supported Events
+
+CrewAI supports both system events and custom events in Enterprise Event Streaming. These events are sent to your configured webhook endpoint during crew and flow execution.
+
+- `crew_kickoff_started`
+- `crew_step_started`
+- `crew_step_completed`
+- `crew_execution_completed`
+- `llm_call_started`
+- `llm_call_completed`
+- `tool_usage_started`
+- `tool_usage_completed`
+- `crew_test_failed`
+- *...and others*
+
+Event names match the internal event bus. See [GitHub source](https://github.com/crewAIInc/crewAI/tree/main/src/crewai/utilities/events) for the full list.
+
+You can emit your own custom events, and they will be delivered through the webhook stream alongside system events.
+
+<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+  Contact our support team for assistance with webhook integration or troubleshooting.
+</Card>

docs/enterprise/guides/build-crew.mdx

@@ -0,0 +1,43 @@
+---
+title: "Build Crew"
+description: "A Crew is a group of agents that work together to complete a task."
+icon: "people-arrows"
+---
+
+<Tip>
+[CrewAI Enterprise](https://app.crewai.com) streamlines the process of **creating**, **deploying**, and **managing** your AI agents in production environments.
+</Tip>
+
+## Getting Started
+
+<iframe 
+    width="100%"
+    height="400"
+    src="https://www.youtube.com/embed/d1Yp8eeknDk?si=tIxnTRI5UlyCp3z_" 
+    title="Building Crews with CrewAI CLI" 
+    frameborder="0"
+    style={{ borderRadius: '10px' }}
+    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+    allowfullscreen
+></iframe>
+
+### Installation and Setup
+
+<Card title="Follow Standard Installation" icon="wrench" href="/installation">
+  Follow our standard installation guide to set up CrewAI CLI and create your first project.
+</Card>
+
+### Building Your Crew
+
+<Card title="Quickstart Tutorial" icon="rocket" href="/quickstart">
+  Follow our quickstart guide to create your first agent crew using YAML configuration.
+</Card>
+
+## Support and Resources
+
+For Enterprise-specific support or questions, contact our dedicated support team at [support@crewai.com](mailto:support@crewai.com).
+
+
+<Card title="Schedule a Demo" icon="calendar" href="mailto:support@crewai.com">
+  Book time with our team to learn more about Enterprise features and how they can benefit your organization.
+</Card>

docs/enterprise/guides/deploy-crew.mdx

@@ -0,0 +1,216 @@
+---
+title: "Deploy Crew"
+description: "Deploy your local CrewAI project to the Enterprise platform"
+icon: "cloud-arrow-up"
+---
+
+## Option 1: CLI Deployment
+
+<Tip>
+This video tutorial walks you through the process of deploying your locally developed CrewAI project to the CrewAI Enterprise platform, 
+transforming it into a production-ready API endpoint.
+</Tip>
+
+<iframe 
+    width="100%"
+    height="400"
+    src="https://www.youtube.com/embed/3EqSV-CYDZA" 
+    title="Deploying a Crew to CrewAI Enterprise" 
+    frameborder="0"
+    style={{ borderRadius: '10px' }}
+    allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture"
+    allowfullscreen
+></iframe>
+
+## Prerequisites
+
+Before starting the deployment process, make sure you have:
+
+- A CrewAI project built locally ([follow our quickstart guide](/quickstart) if you haven't created one yet)
+- Your code pushed to a GitHub repository
+- The latest version of the CrewAI CLI installed (`uv tool install crewai`)
+
+<Note>
+For a quick reference project, you can clone our example repository at [github.com/tonykipkemboi/crewai-latest-ai-development](https://github.com/tonykipkemboi/crewai-latest-ai-development).
+</Note>
+
+
+
+### Step 1: Authenticate with the Enterprise Platform
+
+First, you need to authenticate your CLI with the CrewAI Enterprise platform:
+
+```bash
+# If you already have a CrewAI Enterprise account
+crewai login
+
+# If you're creating a new account
+crewai signup
+```
+
+When you run either command, the CLI will:
+1. Display a URL and a unique device code
+2. Open your browser to the authentication page
+3. Prompt you to confirm the device
+4. Complete the authentication process
+
+Upon successful authentication, you'll see a confirmation message in your terminal!
+
+### Step 2: Create a Deployment
+
+From your project directory, run:
+
+```bash
+crewai deploy create
+```
+
+This command will:
+1. Detect your GitHub repository information
+2. Identify environment variables in your local `.env` file
+3. Securely transfer these variables to the Enterprise platform
+4. Create a new deployment with a unique identifier
+
+On successful creation, you'll see a message like:
+```shell
+Deployment created successfully!
+Name: your_project_name
+Deployment ID: 01234567-89ab-cdef-0123-456789abcdef
+Current Status: Deploy Enqueued
+```
+
+### Step 3: Monitor Deployment Progress
+
+Track the deployment status with:
+
+```bash
+crewai deploy status
+```
+
+For detailed logs of the build process:
+
+```bash
+crewai deploy logs
+```
+
+<Tip>
+The first deployment typically takes 10-15 minutes as it builds the container images. Subsequent deployments are much faster.
+</Tip>
+
+### Additional CLI Commands
+
+The CrewAI CLI offers several commands to manage your deployments:
+
+```bash
+# List all your deployments
+crewai deploy list
+
+# Get the status of your deployment
+crewai deploy status
+
+# View the logs of your deployment
+crewai deploy logs
+
+# Push updates after code changes
+crewai deploy push
+
+# Remove a deployment
+crewai deploy remove <deployment_id>
+```
+
+## Option 2: Deploy Directly via Web Interface
+
+You can also deploy your crews directly through the CrewAI Enterprise web interface by connecting your GitHub account. This approach doesn't require using the CLI on your local machine.
+
+### Step 1: Pushing to GitHub
+
+First, you need to push your crew to a GitHub repository. If you haven't created a crew yet, you can [follow this tutorial](/quickstart).
+
+### Step 2: Connecting GitHub to CrewAI Enterprise
+
+1. Log in to [CrewAI Enterprise](https://app.crewai.com)
+2. Click on the button "Connect GitHub" 
+
+<Frame>
+  ![Connect GitHub Button](/images/enterprise/connect-github.png)
+</Frame>
+
+### Step 3: Select the Repository
+
+After connecting your GitHub account, you'll be able to select which repository to deploy:
+
+<Frame>
+  ![Select Repository](/images/enterprise/select-repo.png)
+</Frame>
+
+### Step 4: Set Environment Variables
+
+Before deploying, you'll need to set up your environment variables to connect to your LLM provider or other services:
+
+1. You can add variables individually or in bulk
+2. Enter your environment variables in `KEY=VALUE` format (one per line)
+
+<Frame>
+  ![Set Environment Variables](/images/enterprise/set-env-variables.png)
+</Frame>
+
+### Step 5: Deploy Your Crew
+
+1. Click the "Deploy" button to start the deployment process
+2. You can monitor the progress through the progress bar
+3. The first deployment typically takes around 10-15 minutes; subsequent deployments will be faster
+
+<Frame>
+  ![Deploy Progress](/images/enterprise/deploy-progress.png)
+</Frame>
+
+Once deployment is complete, you'll see:
+- Your crew's unique URL
+- A Bearer token to protect your crew API
+- A "Delete" button if you need to remove the deployment
+
+### Interact with Your Deployed Crew
+
+Once deployment is complete, you can access your crew through:
+
+1. **REST API**: The platform generates a unique HTTPS endpoint with these key routes:
+   - `/inputs`: Lists the required input parameters
+   - `/kickoff`: Initiates an execution with provided inputs
+   - `/status/{kickoff_id}`: Checks the execution status
+
+2. **Web Interface**: Visit [app.crewai.com](https://app.crewai.com) to access:
+   - **Status tab**: View deployment information, API endpoint details, and authentication token
+   - **Run tab**: Visual representation of your crew's structure
+   - **Executions tab**: History of all executions
+   - **Metrics tab**: Performance analytics
+   - **Traces tab**: Detailed execution insights
+
+### Trigger an Execution
+
+From the Enterprise dashboard, you can:
+
+1. Click on your crew's name to open its details
+2. Select "Trigger Crew" from the management interface
+3. Enter the required inputs in the modal that appears
+4. Monitor progress as the execution moves through the pipeline
+
+## Monitoring and Analytics
+
+The Enterprise platform provides comprehensive observability features:
+
+- **Execution Management**: Track active and completed runs
+- **Traces**: Detailed breakdowns of each execution
+- **Metrics**: Token usage, execution times, and costs
+- **Timeline View**: Visual representation of task sequences
+
+## Advanced Features
+
+The Enterprise platform also offers:
+
+- **Environment Variables Management**: Securely store and manage API keys
+- **LLM Connections**: Configure integrations with various LLM providers
+- **Custom Tools Repository**: Create, share, and install tools
+- **Crew Studio**: Build crews through a chat interface without writing code
+
+<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+  Contact our support team for assistance with deployment issues or questions about the Enterprise platform.
+</Card>

docs/enterprise/guides/enable-crew-studio.mdx

@@ -0,0 +1,166 @@
+---
+title: "Enable Crew Studio"
+description: "Enabling Crew Studio on CrewAI Enterprise"
+icon: "comments"
+---
+
+<Tip>
+Crew Studio is a powerful **no-code/low-code** tool that allows you to quickly scaffold or build Crews through a conversational interface. 
+</Tip>
+
+## What is Crew Studio?
+
+Crew Studio is an innovative way to create AI agent crews without writing code. 
+
+<Frame>
+  ![Crew Studio Interface](/images/enterprise/crew-studio-interface.png)
+</Frame>
+
+With Crew Studio, you can:
+
+- Chat with the Crew Assistant to describe your problem
+- Automatically generate agents and tasks
+- Select appropriate tools
+- Configure necessary inputs
+- Generate downloadable code for customization
+- Deploy directly to the CrewAI Enterprise platform
+
+## Configuration Steps
+
+Before you can start using Crew Studio, you need to configure your LLM connections:
+
+<Steps>
+  <Step title="Set Up LLM Connection">
+    Go to the **LLM Connections** tab in your CrewAI Enterprise dashboard and create a new LLM connection.
+
+    <Note>
+      Feel free to use any LLM provider you want that is supported by CrewAI.
+    </Note>
+    
+    Configure your LLM connection:
+    
+    - Enter a `Connection Name` (e.g., `OpenAI`)
+    - Select your model provider: `openai` or `azure`
+    - Select models you'd like to use in your Studio-generated Crews
+      - We recommend at least `gpt-4o`, `o1-mini`, and `gpt-4o-mini`
+    - Add your API key as an environment variable:
+      - For OpenAI: Add `OPENAI_API_KEY` with your API key
+      - For Azure OpenAI: Refer to [this article](https://blog.crewai.com/configuring-azure-openai-with-crewai-a-comprehensive-guide/) for configuration details
+    - Click `Add Connection` to save your configuration
+    
+    <Frame>
+      ![LLM Connection Configuration](/images/enterprise/llm-connection-config.png)
+    </Frame>
+  </Step>
+  
+  <Step title="Verify Connection Added">
+    Once you complete the setup, you'll see your new connection added to the list of available connections.
+    
+    <Frame>
+      ![Connection Added](/images/enterprise/connection-added.png)
+    </Frame>
+  </Step>
+  
+  <Step title="Configure LLM Defaults">
+    In the main menu, go to **Settings → Defaults** and configure the LLM Defaults settings:
+    
+    - Select default models for agents and other components
+    - Set default configurations for Crew Studio
+    
+    Click `Save Settings` to apply your changes.
+    
+    <Frame>
+      ![LLM Defaults Configuration](/images/enterprise/llm-defaults.png)
+    </Frame>
+  </Step>
+</Steps>
+
+## Using Crew Studio
+
+Now that you've configured your LLM connection and default settings, you're ready to start using Crew Studio!
+
+<Steps>
+  <Step title="Access Studio">
+    Navigate to the **Studio** section in your CrewAI Enterprise dashboard.
+  </Step>
+  
+  <Step title="Start a Conversation">
+    Start a conversation with the Crew Assistant by describing the problem you want to solve:
+    
+    ```md
+    I need a crew that can research the latest AI developments and create a summary report.
+    ```
+    
+    The Crew Assistant will ask clarifying questions to better understand your requirements.
+  </Step>
+  
+  <Step title="Review Generated Crew">
+    Review the generated crew configuration, including:
+    
+    - Agents and their roles
+    - Tasks to be performed
+    - Required inputs
+    - Tools to be used
+    
+    This is your opportunity to refine the configuration before proceeding.
+  </Step>
+  
+  <Step title="Deploy or Download">
+    Once you're satisfied with the configuration, you can:
+    
+    - Download the generated code for local customization
+    - Deploy the crew directly to the CrewAI Enterprise platform
+    - Modify the configuration and regenerate the crew
+  </Step>
+  
+  <Step title="Test Your Crew">
+    After deployment, test your crew with sample inputs to ensure it performs as expected.
+  </Step>
+</Steps>
+
+<Tip>
+For best results, provide clear, detailed descriptions of what you want your crew to accomplish. Include specific inputs and expected outputs in your description.
+</Tip>
+
+## Example Workflow
+
+Here's a typical workflow for creating a crew with Crew Studio:
+
+<Steps>
+  <Step title="Describe Your Problem">
+    Start by describing your problem:
+    
+    ```md
+    I need a crew that can analyze financial news and provide investment recommendations
+    ```
+  </Step>
+  
+  <Step title="Answer Questions">
+    Respond to clarifying questions from the Crew Assistant to refine your requirements.
+  </Step>
+  
+  <Step title="Review the Plan">
+    Review the generated crew plan, which might include:
+    
+    - A Research Agent to gather financial news
+    - An Analysis Agent to interpret the data
+    - A Recommendations Agent to provide investment advice
+  </Step>
+  
+  <Step title="Approve or Modify">
+    Approve the plan or request changes if necessary.
+  </Step>
+  
+  <Step title="Download or Deploy">
+    Download the code for customization or deploy directly to the platform.
+  </Step>
+  
+  <Step title="Test and Refine">
+    Test your crew with sample inputs and refine as needed.
+  </Step>
+</Steps>
+
+<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+  Contact our support team for assistance with Crew Studio or any other CrewAI Enterprise features.
+</Card>
+

docs/enterprise/guides/kickoff-crew.mdx

@@ -0,0 +1,186 @@
+---
+title: "Kickoff Crew"
+description: "Kickoff a Crew on CrewAI Enterprise"
+icon: "flag-checkered"
+---
+
+# Kickoff a Crew on CrewAI Enterprise
+
+Once you've deployed your crew to the CrewAI Enterprise platform, you can kickoff executions through the web interface or the API. This guide covers both approaches.
+
+## Method 1: Using the Web Interface
+
+### Step 1: Navigate to Your Deployed Crew
+
+1. Log in to [CrewAI Enterprise](https://app.crewai.com)
+2. Click on the crew name from your projects list
+3. You'll be taken to the crew's detail page
+
+<Frame>
+  ![Crew Dashboard](/images/enterprise/crew-dashboard.png)
+</Frame>
+
+### Step 2: Initiate Execution
+
+From your crew's detail page, you have two options to kickoff an execution:
+
+#### Option A: Quick Kickoff
+
+1. Click the `Kickoff` link in the Test Endpoints section
+2. Enter the required input parameters for your crew in the JSON editor
+3. Click the `Send Request` button
+
+<Frame>
+  ![Kickoff Endpoint](/images/enterprise/kickoff-endpoint.png)
+</Frame>
+
+#### Option B: Using the Visual Interface
+
+1. Click the `Run` tab in the crew detail page
+2. Enter the required inputs in the form fields
+3. Click the `Run Crew` button
+
+<Frame>
+  ![Run Crew](/images/enterprise/run-crew.png)
+</Frame>
+
+### Step 3: Monitor Execution Progress
+
+After initiating the execution:
+
+1. You'll receive a response containing a `kickoff_id` - **copy this ID**
+2. This ID is essential for tracking your execution
+
+<Frame>
+  ![Copy Task ID](/images/enterprise/copy-task-id.png)
+</Frame>
+
+### Step 4: Check Execution Status
+
+To monitor the progress of your execution:
+
+1. Click the "Status" endpoint in the Test Endpoints section
+2. Paste the `kickoff_id` into the designated field
+3. Click the "Get Status" button
+
+<Frame>
+  ![Get Status](/images/enterprise/get-status.png)
+</Frame>
+
+The status response will show:
+- Current execution state (`running`, `completed`, etc.)
+- Details about which tasks are in progress
+- Any outputs produced so far
+
+### Step 5: View Final Results
+
+Once execution is complete:
+
+1. The status will change to `completed`
+2. You can view the full execution results and outputs
+3. For a more detailed view, check the `Executions` tab in the crew detail page
+
+## Method 2: Using the API
+
+You can also kickoff crews programmatically using the CrewAI Enterprise REST API.
+
+### Authentication
+
+All API requests require a bearer token for authentication:
+
+```bash
+curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
+```
+
+Your bearer token is available on the Status tab of your crew's detail page.
+
+### Checking Crew Health
+
+Before executing operations, you can verify that your crew is running properly:
+
+```bash
+curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
+```
+
+A successful response will return a message indicating the crew is operational:
+
+```
+Healthy%
+```
+
+### Step 1: Retrieve Required Inputs
+
+First, determine what inputs your crew requires:
+
+```bash
+curl -X GET \
+  -H "Authorization: Bearer YOUR_CREW_TOKEN" \
+  https://your-crew-url.crewai.com/inputs
+```
+
+The response will be a JSON object containing an array of required input parameters, for example:
+
+```json
+{"inputs":["topic","current_year"]}
+```
+
+This example shows that this particular crew requires two inputs: `topic` and `current_year`.
+
+### Step 2: Kickoff Execution
+
+Initiate execution by providing the required inputs:
+
+```bash
+curl -X POST \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer YOUR_CREW_TOKEN" \
+  -d '{"inputs": {"topic": "AI Agent Frameworks", "current_year": "2025"}}' \
+  https://your-crew-url.crewai.com/kickoff
+```
+
+The response will include a `kickoff_id` that you'll need for tracking:
+
+```json
+{"kickoff_id":"abcd1234-5678-90ef-ghij-klmnopqrstuv"}
+```
+
+### Step 3: Check Execution Status
+
+Monitor the execution progress using the kickoff_id:
+
+```bash
+curl -X GET \
+  -H "Authorization: Bearer YOUR_CREW_TOKEN" \
+  https://your-crew-url.crewai.com/status/abcd1234-5678-90ef-ghij-klmnopqrstuv
+```
+
+## Handling Executions
+
+### Long-Running Executions
+
+For executions that may take a long time:
+
+1. Consider implementing a polling mechanism to check status periodically
+2. Use webhooks (if available) for notification when execution completes
+3. Implement error handling for potential timeouts
+
+### Execution Context
+
+The execution context includes:
+
+- Inputs provided at kickoff
+- Environment variables configured during deployment
+- Any state maintained between tasks
+
+### Debugging Failed Executions
+
+If an execution fails:
+
+1. Check the "Executions" tab for detailed logs
+2. Review the "Traces" tab for step-by-step execution details
+3. Look for LLM responses and tool usage in the trace details
+
+<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+  Contact our support team for assistance with execution issues or questions about the Enterprise platform.
+</Card>
+

docs/enterprise/guides/update-crew.mdx

@@ -0,0 +1,89 @@
+---
+title: "Update Crew"
+description: "Updating a Crew on CrewAI Enterprise"
+icon: "pencil"
+---
+
+<Note>
+After deploying your crew to CrewAI Enterprise, you may need to make updates to the code, security settings, or configuration. 
+This guide explains how to perform these common update operations.
+</Note>
+
+## Why Update Your Crew?
+
+CrewAI won't automatically pick up GitHub updates by default, so you'll need to manually trigger updates, unless you checked the `Auto-update` option when deploying your crew.
+
+There are several reasons you might want to update your crew deployment:
+- You want to update the code with a latest commit you pushed to GitHub
+- You want to reset the bearer token for security reasons
+- You want to update environment variables
+
+## 1. Updating Your Crew Code for a Latest Commit
+
+When you've pushed new commits to your GitHub repository and want to update your deployment:
+
+1. Navigate to your crew in the CrewAI Enterprise platform
+2. Click on the `Re-deploy` button on your crew details page
+
+<Frame>
+  ![Re-deploy Button](/images/enterprise/redeploy-button.png)
+</Frame>
+
+This will trigger an update that you can track using the progress bar. The system will pull the latest code from your repository and rebuild your deployment.
+
+## 2. Resetting Bearer Token
+
+If you need to generate a new bearer token (for example, if you suspect the current token might have been compromised):
+
+1. Navigate to your crew in the CrewAI Enterprise platform
+2. Find the `Bearer Token` section
+3. Click the `Reset` button next to your current token
+
+<Frame>
+  ![Reset Token](/images/enterprise/reset-token.png)
+</Frame>
+
+<Warning>
+Resetting your bearer token will invalidate the previous token immediately. Make sure to update any applications or scripts that are using the old token.
+</Warning>
+
+## 3. Updating Environment Variables
+
+To update the environment variables for your crew:
+
+1. First access the deployment page by clicking on your crew's name
+
+<Frame>
+  ![Environment Variables Button](/images/enterprise/env-vars-button.png)
+</Frame>
+
+2. Locate the `Environment Variables` section (you will need to click the `Settings` icon to access it)
+3. Edit the existing variables or add new ones in the fields provided
+4. Click the `Update` button next to each variable you modify
+
+<Frame>
+  ![Update Environment Variables](/images/enterprise/update-env-vars.png)
+</Frame>
+
+5. Finally, click the `Update Deployment` button at the bottom of the page to apply the changes
+
+<Note>
+Updating environment variables will trigger a new deployment, but this will only update the environment configuration and not the code itself.
+</Note>
+
+## After Updating
+
+After performing any update:
+
+1. The system will rebuild and redeploy your crew
+2. You can monitor the deployment progress in real-time
+3. Once complete, test your crew to ensure the changes are working as expected
+
+<Tip>
+If you encounter any issues after updating, you can view deployment logs in the platform or contact support for assistance.
+</Tip>
+
+<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+  Contact our support team for assistance with updating your crew or troubleshooting deployment issues.
+</Card>
+

docs/enterprise/guides/use-crew-api.mdx

@@ -0,0 +1,319 @@
+---
+title: "Trigger Deployed Crew API"
+description: "Using your deployed crew's API on CrewAI Enterprise"
+icon: "arrow-up-right-from-square"
+---
+
+Once you have deployed your crew to CrewAI Enterprise, it automatically becomes available as a REST API. This guide explains how to interact with your crew programmatically.
+
+## API Basics
+
+Your deployed crew exposes several endpoints that allow you to:
+1. Discover required inputs
+2. Start crew executions
+3. Monitor execution status
+4. Receive results
+
+### Authentication
+
+All API requests require a bearer token for authentication, which is generated when you deploy your crew:
+
+```bash
+curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com/...
+```
+
+<Tip>
+You can find your bearer token in the Status tab of your crew's detail page in the CrewAI Enterprise dashboard.
+</Tip>
+
+<Frame>
+  ![Bearer Token](/images/enterprise/bearer-token.png)
+</Frame>
+
+## Available Endpoints
+
+Your crew API provides three main endpoints:
+
+| Endpoint | Method | Description |
+|----------|--------|-------------|
+| `/inputs` | GET | Lists all required inputs for crew execution |
+| `/kickoff` | POST | Starts a crew execution with provided inputs |
+| `/status/{kickoff_id}` | GET | Retrieves the status and results of an execution |
+
+## GET /inputs
+
+The inputs endpoint allows you to discover what parameters your crew requires:
+
+```bash
+curl -X GET \
+  -H "Authorization: Bearer YOUR_CREW_TOKEN" \
+  https://your-crew-url.crewai.com/inputs
+```
+
+### Response
+
+```json
+{
+  "inputs": ["budget", "interests", "duration", "age"]
+}
+```
+
+This response indicates that your crew expects four input parameters: `budget`, `interests`, `duration`, and `age`.
+
+## POST /kickoff
+
+The kickoff endpoint starts a new crew execution:
+
+```bash
+curl -X POST \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer YOUR_CREW_TOKEN" \
+  -d '{
+    "inputs": {
+      "budget": "1000 USD",
+      "interests": "games, tech, ai, relaxing hikes, amazing food",
+      "duration": "7 days",
+      "age": "35"
+    }
+  }' \
+  https://your-crew-url.crewai.com/kickoff
+```
+
+### Request Parameters
+
+| Parameter | Type | Required | Description |
+|-----------|------|----------|-------------|
+| `inputs` | Object | Yes | Key-value pairs of all required inputs |
+| `meta` | Object | No | Additional metadata to pass to the crew |
+| `taskWebhookUrl` | String | No | Callback URL executed after each task |
+| `stepWebhookUrl` | String | No | Callback URL executed after each agent thought |
+| `crewWebhookUrl` | String | No | Callback URL executed when the crew finishes |
+
+### Example with Webhooks
+
+```json
+{
+  "inputs": {
+    "budget": "1000 USD",
+    "interests": "games, tech, ai, relaxing hikes, amazing food",
+    "duration": "7 days",
+    "age": "35"
+  },
+  "meta": {
+    "requestId": "user-request-12345",
+    "source": "mobile-app"
+  },
+  "taskWebhookUrl": "https://your-server.com/webhooks/task",
+  "stepWebhookUrl": "https://your-server.com/webhooks/step",
+  "crewWebhookUrl": "https://your-server.com/webhooks/crew"
+}
+```
+
+### Response
+
+```json
+{
+  "kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv"
+}
+```
+
+The `kickoff_id` is used to track and retrieve the execution results.
+
+## GET /status/{kickoff_id}
+
+The status endpoint allows you to check the progress and results of a crew execution:
+
+```bash
+curl -X GET \
+  -H "Authorization: Bearer YOUR_CREW_TOKEN" \
+  https://your-crew-url.crewai.com/status/abcd1234-5678-90ef-ghij-klmnopqrstuv
+```
+
+### Response Structure
+
+The response structure will vary depending on the execution state:
+
+#### In Progress
+
+```json
+{
+  "status": "running",
+  "current_task": "research_task",
+  "progress": {
+    "completed_tasks": 0,
+    "total_tasks": 2
+  }
+}
+```
+
+#### Completed
+
+```json
+{
+  "status": "completed",
+  "result": {
+    "output": "Comprehensive travel itinerary...",
+    "tasks": [
+      {
+        "task_id": "research_task",
+        "output": "Research findings...",
+        "agent": "Researcher",
+        "execution_time": 45.2
+      },
+      {
+        "task_id": "planning_task",
+        "output": "7-day itinerary plan...",
+        "agent": "Trip Planner",
+        "execution_time": 62.8
+      }
+    ]
+  },
+  "execution_time": 108.5
+}
+```
+
+## Webhook Integration
+
+When you provide webhook URLs in your kickoff request, the system will make POST requests to those URLs at specific points in the execution:
+
+### taskWebhookUrl
+
+Called when each task completes:
+
+```json
+{
+  "kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv",
+  "task_id": "research_task",
+  "status": "completed",
+  "output": "Research findings...",
+  "agent": "Researcher",
+  "execution_time": 45.2
+}
+```
+
+### stepWebhookUrl
+
+Called after each agent thought or action:
+
+```json
+{
+  "kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv",
+  "task_id": "research_task",
+  "agent": "Researcher",
+  "step_type": "thought",
+  "content": "I should first search for popular destinations that match these interests..."
+}
+```
+
+### crewWebhookUrl
+
+Called when the entire crew execution completes:
+
+```json
+{
+  "kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv",
+  "status": "completed",
+  "result": {
+    "output": "Comprehensive travel itinerary...",
+    "tasks": [
+      {
+        "task_id": "research_task",
+        "output": "Research findings...",
+        "agent": "Researcher",
+        "execution_time": 45.2
+      },
+      {
+        "task_id": "planning_task",
+        "output": "7-day itinerary plan...",
+        "agent": "Trip Planner",
+        "execution_time": 62.8
+      }
+    ]
+  },
+  "execution_time": 108.5,
+  "meta": {
+    "requestId": "user-request-12345",
+    "source": "mobile-app"
+  }
+}
+```
+
+## Best Practices
+
+### Handling Long-Running Executions
+
+Crew executions can take anywhere from seconds to minutes depending on their complexity. Consider these approaches:
+
+1. **Webhooks (Recommended)**: Set up webhook endpoints to receive notifications when the execution completes
+2. **Polling**: Implement a polling mechanism with exponential backoff
+3. **Client-Side Timeout**: Set appropriate timeouts for your API requests
+
+### Error Handling
+
+The API may return various error codes:
+
+| Code | Description | Recommended Action |
+|------|-------------|-------------------|
+| 401 | Unauthorized | Check your bearer token |
+| 404 | Not Found | Verify your crew URL and kickoff_id |
+| 422 | Validation Error | Ensure all required inputs are provided |
+| 500 | Server Error | Contact support with the error details |
+
+### Sample Code
+
+Here's a complete Python example for interacting with your crew API:
+
+```python
+import requests
+import time
+
+# Configuration
+CREW_URL = "https://your-crew-url.crewai.com"
+BEARER_TOKEN = "your-crew-token"
+HEADERS = {
+    "Authorization": f"Bearer {BEARER_TOKEN}",
+    "Content-Type": "application/json"
+}
+
+# 1. Get required inputs
+response = requests.get(f"{CREW_URL}/inputs", headers=HEADERS)
+required_inputs = response.json()["inputs"]
+print(f"Required inputs: {required_inputs}")
+
+# 2. Start crew execution
+payload = {
+    "inputs": {
+        "budget": "1000 USD",
+        "interests": "games, tech, ai, relaxing hikes, amazing food",
+        "duration": "7 days",
+        "age": "35"
+    }
+}
+
+response = requests.post(f"{CREW_URL}/kickoff", headers=HEADERS, json=payload)
+kickoff_id = response.json()["kickoff_id"]
+print(f"Execution started with ID: {kickoff_id}")
+
+# 3. Poll for results
+MAX_RETRIES = 30
+POLL_INTERVAL = 10  # seconds
+for i in range(MAX_RETRIES):
+    print(f"Checking status (attempt {i+1}/{MAX_RETRIES})...")
+    response = requests.get(f"{CREW_URL}/status/{kickoff_id}", headers=HEADERS)
+    data = response.json()
+    
+    if data["status"] == "completed":
+        print("Execution completed!")
+        print(f"Result: {data['result']['output']}")
+        break
+    elif data["status"] == "error":
+        print(f"Execution failed: {data.get('error', 'Unknown error')}")
+        break
+    else:
+        print(f"Status: {data['status']}, waiting {POLL_INTERVAL} seconds...")
+        time.sleep(POLL_INTERVAL)
+```
+
+<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+  Contact our support team for assistance with API integration or troubleshooting.
+</Card>

docs/enterprise/introduction.mdx

@@ -0,0 +1,67 @@
+---
+title: "CrewAI Enterprise"
+description: "Deploy, monitor, and scale your AI agent workflows"
+icon: "globe"
+---
+
+## Introduction
+
+CrewAI Enterprise provides a platform for deploying, monitoring, and scaling your crews and agents in a production environment.
+
+CrewAI Enterprise extends the power of the open-source framework with features designed for production deployments, collaboration, and scalability. Deploy your crews to a managed infrastructure and monitor their execution in real-time.
+
+## Key Features
+
+<CardGroup cols={2}>
+  <Card title="Crew Deployments" icon="rocket">
+    Deploy your crews to a managed infrastructure with a few clicks
+  </Card>
+  <Card title="API Access" icon="code">
+    Access your deployed crews via REST API for integration with existing systems
+  </Card>
+  <Card title="Observability" icon="chart-line">
+    Monitor your crews with detailed execution traces and logs
+  </Card>
+  <Card title="Tool Repository" icon="toolbox">
+    Publish and install tools to enhance your crews' capabilities
+  </Card>
+  <Card title="Webhook Streaming" icon="webhook">
+    Stream real-time events and updates to your systems
+  </Card>
+  <Card title="Crew Studio" icon="paintbrush">
+    Create and customize crews using a no-code/low-code interface
+  </Card>
+</CardGroup>
+
+## Deployment Options
+
+<CardGroup cols={3}>
+  <Card title="GitHub Integration" icon="github">
+    Connect directly to your GitHub repositories to deploy code
+  </Card>
+  <Card title="Crew Studio" icon="palette">
+    Deploy crews created through the no-code Crew Studio interface
+  </Card>
+  <Card title="CLI Deployment" icon="terminal">
+    Use the CrewAI CLI for more advanced deployment workflows
+  </Card>
+</CardGroup>
+
+## Getting Started
+
+<Steps>
+  <Step title="Sign up for an account">
+    Create your account at [app.crewai.com](https://app.crewai.com)
+  </Step>
+  <Step title="Create your first crew">
+    Use code or Crew Studio to create your crew
+  </Step>
+  <Step title="Deploy your crew">
+    Deploy your crew to the Enterprise platform
+  </Step>
+  <Step title="Access your crew">
+    Integrate with your crew via the generated API endpoints
+  </Step>
+</Steps>
+
+For detailed instructions, check out our [deployment guide](/enterprise/guides/deploy-crew) or click the button below to get started.

docs/enterprise/resources/frequently-asked-questions.mdx

@@ -0,0 +1,181 @@
+---
+title: FAQs
+description: "Frequently asked questions about CrewAI Enterprise"
+icon: "code"
+---
+
+<AccordionGroup>
+    <Accordion title="How is task execution handled in the hierarchical process?">
+        In the hierarchical process, a manager agent is automatically created and coordinates the workflow, delegating tasks and validating outcomes for
+        streamlined and effective execution. The manager agent utilizes tools to facilitate task delegation and execution by agents under the manager's guidance.
+        The manager LLM is crucial for the hierarchical process and must be set up correctly for proper function.
+    </Accordion>
+
+    <Accordion title="Where can I get the latest CrewAI documentation?">
+        The most up-to-date documentation for CrewAI is available on our official documentation website; https://docs.crewai.com/
+        <Card href="https://docs.crewai.com/" icon="books">CrewAI Docs</Card>
+    </Accordion>
+
+    <Accordion title="What are the key differences between Hierarchical and Sequential Processes in CrewAI?">
+        #### Hierarchical Process:
+        Tasks are delegated and executed based on a structured chain of command.
+        A manager language model (`manager_llm`) must be specified for the manager agent.
+        Manager agent oversees task execution, planning, delegation, and validation.
+        Tasks are not pre-assigned; the manager allocates tasks to agents based on their capabilities.
+
+        #### Sequential Process:
+        Tasks are executed one after another, ensuring tasks are completed in an orderly progression.
+        Output of one task serves as context for the next.
+        Task execution follows the predefined order in the task list.
+
+        #### Which Process is Better Suited for Complex Projects?
+
+        The hierarchical process is better suited for complex projects because it allows for:
+
+        - **Dynamic task allocation and delegation**: Manager agent can assign tasks based on agent capabilities, allowing for efficient resource utilization.
+        - **Structured validation and oversight**: Manager agent reviews task outputs and ensures task completion, increasing reliability and accuracy.
+        - **Complex task management**: Assigning tools at the agent level allows for precise control over tool availability, facilitating the execution of intricate tasks.
+    </Accordion>
+
+    <Accordion title="What are the benefits of using memory in the CrewAI framework?">
+        - **Adaptive Learning**: Crews become more efficient over time, adapting to new information and refining their approach to tasks.
+        - **Enhanced Personalization**: Memory enables agents to remember user preferences and historical interactions, leading to personalized experiences.
+        - **Improved Problem Solving**: Access to a rich memory store aids agents in making more informed decisions, drawing on past learnings and contextual insights.
+    </Accordion>
+
+    <Accordion title="What is the purpose of setting a maximum RPM limit for an agent?">
+        Setting a maximum RPM limit for an agent prevents the agent from making too many requests to external services, which can help to avoid rate limits and improve performance.
+    </Accordion>
+
+    <Accordion title="What role does human input play in the execution of tasks within a CrewAI crew?">
+        It allows agents to request additional information or clarification when necessary.
+        This feature is crucial in complex decision-making processes or when agents require more details to complete a task effectively.
+
+        To integrate human input into agent execution, set the `human_input` flag in the task definition. When enabled, the agent prompts the user for input before delivering its final answer. 
+        This input can provide extra context, clarify ambiguities, or validate the agent's output.
+    </Accordion>
+
+    <Accordion title="What advanced customization options are available for tailoring and enhancing agent behavior and capabilities in CrewAI?">
+        CrewAI provides a range of advanced customization options to tailor and enhance agent behavior and capabilities:
+        
+        - **Language Model Customization**: Agents can be customized with specific language models (`llm`) and function-calling language models (`function_calling_llm`), offering advanced control over their processing and decision-making abilities.
+
+        - **Performance and Debugging Settings**: Adjust an agent's performance and monitor its operations for efficient task execution.
+
+        - **Verbose Mode**: Enables detailed logging of an agent's actions, useful for debugging and optimization.
+
+        - **RPM Limit**: Sets the maximum number of requests per minute (`max_rpm`).
+
+        - **Maximum Iterations for Task Execution**: The `max_iter` attribute allows users to define the maximum number of iterations an agent can perform for a single task, preventing infinite loops or excessively long executions.
+
+        - **Delegation and Autonomy**: Control an agent's ability to delegate or ask questions, tailoring its autonomy and collaborative dynamics within the CrewAI framework. By default, the `allow_delegation` attribute is set to True, enabling agents to seek assistance or delegate tasks as needed. This default behavior promotes collaborative problem-solving and efficiency within the CrewAI ecosystem. If needed, delegation can be disabled to suit specific operational requirements.
+
+        - **Human Input in Agent Execution**: Human input is critical in several agent execution scenarios, allowing agents to request additional information or clarification when necessary. This feature is especially useful in complex decision-making processes or when agents require more details to complete a task effectively.
+    </Accordion>
+
+    <Accordion title="In what scenarios is human input particularly useful in agent execution?">
+        Human input is particularly useful in agent execution when:
+        - **Agents require additional information or clarification**: When agents encounter ambiguity or incomplete data, human input can provide the necessary context to complete the task effectively.
+        - **Agents need to make complex or sensitive decisions**: Human input can assist agents in ethical or nuanced decision-making, ensuring responsible and informed outcomes.
+        - **Oversight and validation of agent output**: Human input can help validate the results generated by agents, ensuring accuracy and preventing any misinterpretation or errors.
+        - **Customizing agent behavior**: Human input can provide feedback on agent responses, allowing users to refine the agent's behavior and responses over time.
+        - **Identifying and resolving errors or limitations**: Human input can help identify and address any errors or limitations in the agent's capabilities, enabling continuous improvement and optimization.
+    </Accordion>
+
+    <Accordion title="What are the different types of memory that are available in crewAI?">
+        The different types of memory available in CrewAI are:
+        - `short-term memory`
+        - `long-term memory`
+        - `entity memory`
+        - `contextual memory`
+
+        Learn more about the different types of memory here:
+        <Card href="https://docs.crewai.com/concepts/memory" icon="brain">CrewAI Memory</Card>
+    </Accordion>
+
+    <Accordion title="How can I create custom tools for my CrewAI agents?">
+        You can create custom tools by subclassing the `BaseTool` class provided by CrewAI or by using the tool decorator. Subclassing involves defining a new class that inherits from `BaseTool`, specifying the name, description, and the `_run` method for operational logic. The tool decorator allows you to create a `Tool` object directly with the required attributes and a functional logic.
+        Click here for more details:
+        <Card href="https://docs.crewai.com/how-to/create-custom-tools" icon="code">CrewAI Tools</Card>
+    </Accordion>
+
+    <Accordion title="How do I use Output Pydantic in a Task?">
+        To use Output Pydantic in a task, you need to define the expected output of the task as a Pydantic model. Here's an example:
+        <Steps>
+            <Step title="Define a Pydantic model">
+                First, you need to define a Pydantic model. For instance, let's create a simple model for a user:
+
+                ```python
+                from pydantic import BaseModel
+
+                class User(BaseModel):
+                    name: str
+                    age: int
+                ```
+            </Step>
+
+            <Step title="Then, when creating a task, specify the expected output as this Pydantic model:">
+
+                ```python
+                from crewai import Task, Crew, Agent
+
+                # Import the User model
+                from my_models import User
+
+                # Create a task with Output Pydantic
+                task = Task(
+                    description="Create a user with the provided name and age",
+                    expected_output=User,  # This is the Pydantic model
+                    agent=agent,
+                    tools=[tool1, tool2]
+                )
+                ```
+            </Step>
+
+            <Step title="In your agent, make sure to set the output_pydantic attribute to the Pydantic model you're using:">
+
+                ```python
+                from crewai import Agent
+
+                # Import the User model
+                from my_models import User
+
+                # Create an agent with Output Pydantic
+                agent = Agent(
+                    role='User Creator',
+                    goal='Create users',
+                    backstory='I am skilled in creating user accounts',
+                    tools=[tool1, tool2],
+                    output_pydantic=User
+                )
+                ```
+            </Step>
+
+            <Step title="When executing the crew, the output of the task will be a User object:">
+
+                ```python
+                from crewai import Crew
+
+                # Create a crew with the agent and task
+                crew = Crew(agents=[agent], tasks=[task])
+
+                # Kick off the crew
+                result = crew.kickoff()
+
+                # The output of the task will be a User object
+                print(result.tasks[0].output)
+                ``` 
+            </Step>
+        </Steps>
+        Here's a tutorial on how to consistently get structured outputs from your agents:
+            <Frame>
+                <iframe 
+                height="400"
+                width="100%"
+                src="https://www.youtube.com/embed/dNpKQk5uxHw" 
+                title="YouTube video player" frameborder="0" 
+                allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" 
+                allowfullscreen></iframe>
+            </Frame>
+    </Accordion>
+</AccordionGroup>

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.114.0"
+version = "0.117.1"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<3.13"
@@ -11,7 +11,7 @@ dependencies = [
     # Core Dependencies
     "pydantic>=2.4.2",
     "openai>=1.13.3",
-    "litellm==1.60.2",
+    "litellm==1.67.1",
     "instructor>=1.3.3",
     # Text Processing
     "pdfplumber>=0.11.4",
@@ -45,7 +45,7 @@ Documentation = "https://docs.crewai.com"
 Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
-tools = ["crewai-tools~=0.40.1"]
+tools = ["crewai-tools~=0.42.2"]
 embeddings = [
     "tiktoken~=0.7.0"
 ]
@@ -60,7 +60,7 @@ pandas = [
 openpyxl = [
     "openpyxl>=3.1.5",
 ]
-mem0 = ["mem0ai>=0.1.29"]
+mem0 = ["mem0ai>=0.1.94"]
 docling = [
     "docling>=2.12.0",
 ]

src/crewai/__init__.py

@@ -17,7 +17,7 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.114.0"
+__version__ = "0.117.1"
 __all__ = [
     "Agent",
     "Crew",

src/crewai/agents/agent_adapters/langgraph/__init__.py

@@ -0,0 +1 @@
+"""LangGraph adapter for crewAI."""

src/crewai/agents/agent_adapters/openai_agents/__init__.py

@@ -0,0 +1 @@
+"""OpenAI agent adapters for crewAI."""

src/crewai/cli/templates/crew/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.13"
 dependencies = [
-    "crewai[tools]>=0.114.0,<1.0.0"
+    "crewai[tools]>=0.117.1,<1.0.0"
 ]
 
 [project.scripts]

src/crewai/cli/templates/flow/crews/poem_crew/__init__.py

@@ -0,0 +1 @@
+"""Poem crew template."""

src/crewai/cli/templates/flow/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.13"
 dependencies = [
-    "crewai[tools]>=0.114.0,<1.0.0",
+    "crewai[tools]>=0.117.1,<1.0.0",
 ]
 
 [project.scripts]

src/crewai/cli/templates/tool/pyproject.toml

@@ -5,7 +5,7 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<3.13"
 dependencies = [
-    "crewai[tools]>=0.114.0"
+    "crewai[tools]>=0.117.1"
 ]
 
 [tool.crewai]

src/crewai/knowledge/utils/__init__.py

@@ -0,0 +1 @@
+"""Knowledge utilities for crewAI."""

src/crewai/llm.py

@@ -37,6 +37,7 @@ with warnings.catch_warnings():
     warnings.simplefilter("ignore", UserWarning)
     import litellm
     from litellm import Choices
+    from litellm.exceptions import ContextWindowExceededError
     from litellm.litellm_core_utils.get_supported_openai_params import (
         get_supported_openai_params,
     )
@@ -64,7 +65,7 @@ class FilteredStream:
             if (
                 "Give Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new"
                 in s
-                or "LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True`"
+                or "LiteLLM.Info: If you need to debug this error, use `litellm._turn_on_debug()`"
                 in s
             ):
                 return 0
@@ -482,6 +483,7 @@ class LLM(BaseLLM):
                     full_response += chunk_content
 
                     # Emit the chunk event
+                    assert hasattr(crewai_event_bus, "emit")
                     crewai_event_bus.emit(
                         self,
                         event=LLMStreamChunkEvent(chunk=chunk_content),
@@ -597,6 +599,11 @@ class LLM(BaseLLM):
             self._handle_emit_call_events(full_response, LLMCallType.LLM_CALL)
             return full_response
 
+        except ContextWindowExceededError as e:
+            # Catch context window errors from litellm and convert them to our own exception type.
+            # This exception is handled by CrewAgentExecutor._invoke_loop() which can then
+            # decide whether to summarize the content or abort based on the respect_context_window flag.
+            raise LLMContextLengthExceededException(str(e))
         except Exception as e:
             logging.error(f"Error in streaming response: {str(e)}")
             if full_response.strip():
@@ -605,6 +612,7 @@ class LLM(BaseLLM):
                 return full_response
 
             # Emit failed event and re-raise the exception
+            assert hasattr(crewai_event_bus, "emit")
             crewai_event_bus.emit(
                 self,
                 event=LLMCallFailedEvent(error=str(e)),
@@ -627,7 +635,7 @@ class LLM(BaseLLM):
                 current_tool_accumulator.function.arguments += (
                     tool_call.function.arguments
                 )
-
+            assert hasattr(crewai_event_bus, "emit")
             crewai_event_bus.emit(
                 self,
                 event=LLMStreamChunkEvent(
@@ -711,7 +719,16 @@ class LLM(BaseLLM):
             str: The response text
         """
         # --- 1) Make the completion call
-        response = litellm.completion(**params)
+        try:
+            # Attempt to make the completion call, but catch context window errors
+            # and convert them to our own exception type for consistent handling
+            # across the codebase. This allows CrewAgentExecutor to handle context
+            # length issues appropriately.
+            response = litellm.completion(**params)
+        except ContextWindowExceededError as e:
+            # Convert litellm's context window error to our own exception type
+            # for consistent handling in the rest of the codebase
+            raise LLMContextLengthExceededException(str(e))
 
         # --- 2) Extract response message and content
         response_message = cast(Choices, cast(ModelResponse, response).choices)[
@@ -791,6 +808,7 @@ class LLM(BaseLLM):
                     function_name, lambda: None
                 )  # Ensure fn is always a callable
                 logging.error(f"Error executing function '{function_name}': {e}")
+                assert hasattr(crewai_event_bus, "emit")
                 crewai_event_bus.emit(
                     self,
                     event=LLMCallFailedEvent(error=f"Tool execution error: {str(e)}"),
@@ -828,6 +846,7 @@ class LLM(BaseLLM):
             LLMContextLengthExceededException: If input exceeds model's context limit
         """
         # --- 1) Emit call started event
+        assert hasattr(crewai_event_bus, "emit")
         crewai_event_bus.emit(
             self,
             event=LLMCallStartedEvent(
@@ -870,15 +889,18 @@ class LLM(BaseLLM):
                         params, callbacks, available_functions
                     )
 
+            except LLMContextLengthExceededException:
+                # Re-raise LLMContextLengthExceededException as it should be handled
+                # by the CrewAgentExecutor._invoke_loop method, which can then decide
+                # whether to summarize the content or abort based on the respect_context_window flag
+                raise
             except Exception as e:
+                assert hasattr(crewai_event_bus, "emit")
                 crewai_event_bus.emit(
                     self,
                     event=LLMCallFailedEvent(error=str(e)),
                 )
-                if not LLMContextLengthExceededException(
-                    str(e)
-                )._is_context_limit_error(str(e)):
-                    logging.error(f"LiteLLM call failed: {str(e)}")
+                logging.error(f"LiteLLM call failed: {str(e)}")
                 raise
 
     def _handle_emit_call_events(self, response: Any, call_type: LLMCallType):
@@ -888,6 +910,7 @@ class LLM(BaseLLM):
             response (str): The response from the LLM call.
             call_type (str): The type of call, either "tool_call" or "llm_call".
         """
+        assert hasattr(crewai_event_bus, "emit")
         crewai_event_bus.emit(
             self,
             event=LLMCallCompletedEvent(response=response, call_type=call_type),

src/crewai/llms/__init__.py

@@ -0,0 +1 @@
+"""LLM implementations for crewAI."""

src/crewai/llms/third_party/__init__.py

@@ -0,0 +1 @@
+"""Third-party LLM implementations for crewAI."""

src/crewai/memory/storage/__init__.py

@@ -0,0 +1 @@
+"""Memory storage implementations for crewAI."""

src/crewai/memory/storage/mem0_storage.py

@@ -88,7 +88,9 @@ class Mem0Storage(Storage):
             }
 
         if params:
-            self.memory.add(value, **params | {"output_format": "v1.1"})
+            if isinstance(self.memory, MemoryClient):
+                params["output_format"] = "v1.1"
+            self.memory.add(value, **params)
 
     def search(
         self,
@@ -96,7 +98,7 @@ class Mem0Storage(Storage):
         limit: int = 3,
         score_threshold: float = 0.35,
     ) -> List[Any]:
-        params = {"query": query, "limit": limit}
+        params = {"query": query, "limit": limit, "output_format": "v1.1"}
         if user_id := self._get_user_id():
             params["user_id"] = user_id
 
@@ -116,8 +118,11 @@ class Mem0Storage(Storage):
 
         # Discard the filters for now since we create the filters
         # automatically when the crew is created.
+        if isinstance(self.memory, Memory):
+            del params["metadata"], params["output_format"]
+            
         results = self.memory.search(**params)
-        return [r for r in results if r["score"] >= score_threshold]
+        return [r for r in results["results"] if r["score"] >= score_threshold]
 
     def _get_user_id(self) -> str:
         return self._get_config().get("user_id", "")

src/crewai/project/crew_base.py

@@ -8,8 +8,6 @@ from dotenv import load_dotenv
 
 load_dotenv()
 
-logging.basicConfig(level=logging.WARNING)
-
 T = TypeVar("T", bound=type)
 
 """Base decorator for creating crew classes with configuration and function management."""
@@ -248,6 +246,9 @@ def CrewBase(cls: T) -> T:
                     callback_functions[callback]() for callback in callbacks
                 ]
 
+            if guardrail := task_info.get("guardrail"):
+                self.tasks_config[task_name]["guardrail"] = guardrail
+
     # Include base class (qual)name in the wrapper class (qual)name.
     WrappedClass.__name__ = CrewBase.__name__ + "(" + cls.__name__ + ")"
     WrappedClass.__qualname__ = CrewBase.__qualname__ + "(" + cls.__name__ + ")"

src/crewai/task.py

@@ -140,9 +140,9 @@ class Task(BaseModel):
         default=None,
     )
     processed_by_agents: Set[str] = Field(default_factory=set)
-    guardrail: Optional[Callable[[TaskOutput], Tuple[bool, Any]]] = Field(
+    guardrail: Optional[Union[Callable[[TaskOutput], Tuple[bool, Any]], str]] = Field(
         default=None,
-        description="Function to validate task output before proceeding to next task",
+        description="Function or string description of a guardrail to validate task output before proceeding to next task",
     )
     max_retries: int = Field(
         default=3, description="Maximum number of retries when guardrail fails"
@@ -157,8 +157,12 @@ class Task(BaseModel):
 
     @field_validator("guardrail")
     @classmethod
-    def validate_guardrail_function(cls, v: Optional[Callable]) -> Optional[Callable]:
-        """Validate that the guardrail function has the correct signature and behavior.
+    def validate_guardrail_function(
+        cls, v: Optional[str | Callable]
+    ) -> Optional[str | Callable]:
+        """
+        If v is a callable, validate that the guardrail function has the correct signature and behavior.
+        If v is a string, return it as is.
 
         While type hints provide static checking, this validator ensures runtime safety by:
         1. Verifying the function accepts exactly one parameter (the TaskOutput)
@@ -171,16 +175,16 @@ class Task(BaseModel):
         - Clear error messages help users debug guardrail implementation issues
 
         Args:
-            v: The guardrail function to validate
+            v: The guardrail function to validate or a string describing the guardrail task
 
         Returns:
-            The validated guardrail function
+            The validated guardrail function or a string describing the guardrail task
 
         Raises:
             ValueError: If the function signature is invalid or return annotation
                        doesn't match Tuple[bool, Any]
         """
-        if v is not None:
+        if v is not None and callable(v):
             sig = inspect.signature(v)
             positional_args = [
                 param
@@ -211,6 +215,7 @@ class Task(BaseModel):
                     )
         return v
 
+    _guardrail: Optional[Callable] = PrivateAttr(default=None)
     _original_description: Optional[str] = PrivateAttr(default=None)
     _original_expected_output: Optional[str] = PrivateAttr(default=None)
     _original_output_file: Optional[str] = PrivateAttr(default=None)
@@ -231,6 +236,20 @@ class Task(BaseModel):
                 )
         return self
 
+    @model_validator(mode="after")
+    def ensure_guardrail_is_callable(self) -> "Task":
+        if callable(self.guardrail):
+            self._guardrail = self.guardrail
+        elif isinstance(self.guardrail, str):
+            from crewai.tasks.task_guardrail import TaskGuardrail
+
+            assert self.agent is not None
+            self._guardrail = TaskGuardrail(
+                description=self.guardrail, llm=self.agent.llm
+            )
+
+        return self
+
     @field_validator("id", mode="before")
     @classmethod
     def _deny_user_set_id(cls, v: Optional[UUID4]) -> None:
@@ -407,10 +426,8 @@ class Task(BaseModel):
                 output_format=self._get_output_format(),
             )
 
-            if self.guardrail:
-                guardrail_result = GuardrailResult.from_tuple(
-                    self.guardrail(task_output)
-                )
+            if self._guardrail:
+                guardrail_result = self._process_guardrail(task_output)
                 if not guardrail_result.success:
                     if self.retry_count >= self.max_retries:
                         raise Exception(
@@ -464,13 +481,46 @@ class Task(BaseModel):
                     )
                 )
                 self._save_file(content)
-            crewai_event_bus.emit(self, TaskCompletedEvent(output=task_output, task=self))
+            crewai_event_bus.emit(
+                self, TaskCompletedEvent(output=task_output, task=self)
+            )
             return task_output
         except Exception as e:
             self.end_time = datetime.datetime.now()
             crewai_event_bus.emit(self, TaskFailedEvent(error=str(e), task=self))
             raise e  # Re-raise the exception after emitting the event
 
+    def _process_guardrail(self, task_output: TaskOutput) -> GuardrailResult:
+        assert self._guardrail is not None
+
+        from crewai.utilities.events import (
+            TaskGuardrailCompletedEvent,
+            TaskGuardrailStartedEvent,
+        )
+        from crewai.utilities.events.crewai_event_bus import crewai_event_bus
+
+        result = self._guardrail(task_output)
+
+        crewai_event_bus.emit(
+            self,
+            TaskGuardrailStartedEvent(
+                guardrail=self._guardrail, retry_count=self.retry_count
+            ),
+        )
+
+        guardrail_result = GuardrailResult.from_tuple(result)
+
+        crewai_event_bus.emit(
+            self,
+            TaskGuardrailCompletedEvent(
+                success=guardrail_result.success,
+                result=guardrail_result.result,
+                error=guardrail_result.error,
+                retry_count=self.retry_count,
+            ),
+        )
+        return guardrail_result
+
     def prompt(self) -> str:
         """Prompt the task.
 

src/crewai/tasks/task_guardrail.py

@@ -0,0 +1,92 @@
+from typing import Any, Optional, Tuple
+
+from pydantic import BaseModel, Field
+
+from crewai.agent import Agent, LiteAgentOutput
+from crewai.llm import LLM
+from crewai.task import Task
+from crewai.tasks.task_output import TaskOutput
+
+
+class TaskGuardrailResult(BaseModel):
+    valid: bool = Field(
+        description="Whether the task output complies with the guardrail"
+    )
+    feedback: str | None = Field(
+        description="A feedback about the task output if it is not valid",
+        default=None,
+    )
+
+
+class TaskGuardrail:
+    """It validates the output of another task using an LLM.
+
+    This class is used to validate the output from a Task based on specified criteria.
+    It uses an LLM to validate the output and provides a feedback if the output is not valid.
+
+    Args:
+        description (str): The description of the validation criteria.
+        llm (LLM, optional): The language model to use for code generation.
+    """
+
+    def __init__(
+        self,
+        description: str,
+        llm: LLM,
+    ):
+        self.description = description
+
+        self.llm: LLM = llm
+
+    def _validate_output(self, task_output: TaskOutput) -> LiteAgentOutput:
+        agent = Agent(
+            role="Guardrail Agent",
+            goal="Validate the output of the task",
+            backstory="You are a expert at validating the output of a task. By providing effective feedback if the output is not valid.",
+            llm=self.llm,
+        )
+
+        query = f"""
+        Ensure the following task result complies with the given guardrail.
+
+        Task result:
+        {task_output.raw}
+
+        Guardrail:
+        {self.description}
+        
+        Your task:
+        - Confirm if the Task result complies with the guardrail.
+        - If not, provide clear feedback explaining what is wrong (e.g., by how much it violates the rule, or what specific part fails).
+        - Focus only on identifying issues — do not propose corrections.
+        - If the Task result complies with the guardrail, saying that is valid
+        """
+
+        result = agent.kickoff(query, response_format=TaskGuardrailResult)
+
+        return result
+
+    def __call__(self, task_output: TaskOutput) -> Tuple[bool, Any]:
+        """Validates the output of a task based on specified criteria.
+
+        Args:
+            task_output (TaskOutput): The output to be validated.
+
+        Returns:
+            Tuple[bool, Any]: A tuple containing:
+                - bool: True if validation passed, False otherwise
+                - Any: The validation result or error message
+        """
+
+        try:
+            result = self._validate_output(task_output)
+            assert isinstance(
+                result.pydantic, TaskGuardrailResult
+            ), "The guardrail result is not a valid pydantic model"
+
+            if result.pydantic.valid:
+                return True, task_output.raw
+            else:
+                return False, result.pydantic.feedback
+        except Exception as e:
+            return False, f"Error while validating the task output: {str(e)}"

src/crewai/tools/agent_tools/__init__.py

@@ -0,0 +1 @@
+"""Agent tools for crewAI."""

src/crewai/utilities/evaluators/__init__.py

@@ -0,0 +1 @@
+"""Evaluators for crewAI."""

src/crewai/utilities/events/__init__.py

@@ -9,6 +9,10 @@ from .crew_events import (
     CrewTestCompletedEvent,
     CrewTestFailedEvent,
 )
+from .task_guardrail_events import (
+    TaskGuardrailCompletedEvent,
+    TaskGuardrailStartedEvent,
+)
 from .agent_events import (
     AgentExecutionStartedEvent,
     AgentExecutionCompletedEvent,

src/crewai/utilities/events/event_types.py

@@ -34,6 +34,10 @@ from .task_events import (
     TaskFailedEvent,
     TaskStartedEvent,
 )
+from .task_guardrail_events import (
+    TaskGuardrailCompletedEvent,
+    TaskGuardrailStartedEvent,
+)
 from .tool_usage_events import (
     ToolUsageErrorEvent,
     ToolUsageFinishedEvent,
@@ -68,4 +72,6 @@ EventTypes = Union[
     LLMCallCompletedEvent,
     LLMCallFailedEvent,
     LLMStreamChunkEvent,
+    TaskGuardrailStartedEvent,
+    TaskGuardrailCompletedEvent,
 ]

src/crewai/utilities/events/task_guardrail_events.py

@@ -0,0 +1,38 @@
+from typing import Any, Callable, Optional, Union
+
+from crewai.utilities.events.base_events import BaseEvent
+
+
+class TaskGuardrailStartedEvent(BaseEvent):
+    """Event emitted when a guardrail task starts
+
+    Attributes:
+        guardrail: The guardrail callable or TaskGuardrail instance
+        retry_count: The number of times the guardrail has been retried
+    """
+
+    type: str = "task_guardrail_started"
+    guardrail: Union[str, Callable]
+    retry_count: int
+
+    def __init__(self, **data):
+        from inspect import getsource
+
+        from crewai.tasks.task_guardrail import TaskGuardrail
+
+        super().__init__(**data)
+
+        if isinstance(self.guardrail, TaskGuardrail):
+            self.guardrail = self.guardrail.description.strip()
+        elif isinstance(self.guardrail, Callable):
+            self.guardrail = getsource(self.guardrail).strip()
+
+
+class TaskGuardrailCompletedEvent(BaseEvent):
+    """Event emitted when a guardrail task completes"""
+
+    type: str = "task_guardrail_completed"
+    success: bool
+    result: Any
+    error: Optional[str] = None
+    retry_count: int

src/crewai/utilities/events/utils/__init__.py

@@ -0,0 +1 @@
+"""Event utilities for crewAI."""

src/crewai/utilities/exceptions/__init__.py

@@ -0,0 +1 @@
+"""Exceptions for crewAI."""

src/crewai/utilities/prompts.py

@@ -54,10 +54,12 @@ class Prompts(BaseModel):
         response_template=None,
     ) -> str:
         """Constructs a prompt string from specified components."""
-        if not system_template and not prompt_template:
+        if not system_template or not prompt_template:
+            # If any of the required templates are missing, fall back to the default format
             prompt_parts = [self.i18n.slice(component) for component in components]
             prompt = "".join(prompt_parts)
         else:
+            # All templates are provided, use them
             prompt_parts = [
                 self.i18n.slice(component)
                 for component in components
@@ -67,8 +69,12 @@ class Prompts(BaseModel):
             prompt = prompt_template.replace(
                 "{{ .Prompt }}", "".join(self.i18n.slice("task"))
             )
-            response = response_template.split("{{ .Response }}")[0]
-            prompt = f"{system}\n{prompt}\n{response}"
+            # Handle missing response_template
+            if response_template:
+                response = response_template.split("{{ .Response }}")[0]
+                prompt = f"{system}\n{prompt}\n{response}"
+            else:
+                prompt = f"{system}\n{prompt}"
 
         prompt = (
             prompt.replace("{goal}", self.agent.goal)

tests/agent_test.py

@@ -72,9 +72,54 @@ def test_agent_creation():
     assert agent.role == "test role"
     assert agent.goal == "test goal"
     assert agent.backstory == "test backstory"
-    assert agent.tools == []
+
+def test_agent_with_only_system_template():
+    """Test that an agent with only system_template works without errors."""
+    agent = Agent(
+        role="Test Role",
+        goal="Test Goal",
+        backstory="Test Backstory",
+        allow_delegation=False,
+        system_template="You are a test agent...",
+        # prompt_template is intentionally missing
+    )
+
+    assert agent.role == "Test Role"
+    assert agent.goal == "Test Goal"
+    assert agent.backstory == "Test Backstory"
+
+def test_agent_with_only_prompt_template():
+    """Test that an agent with only system_template works without errors."""
+    agent = Agent(
+        role="Test Role",
+        goal="Test Goal",
+        backstory="Test Backstory",
+        allow_delegation=False,
+        prompt_template="You are a test agent...",
+        # prompt_template is intentionally missing
+    )
+
+    assert agent.role == "Test Role"
+    assert agent.goal == "Test Goal"
+    assert agent.backstory == "Test Backstory"
 
 
+def test_agent_with_missing_response_template():
+    """Test that an agent with system_template and prompt_template but no response_template works without errors."""
+    agent = Agent(
+        role="Test Role",
+        goal="Test Goal",
+        backstory="Test Backstory",
+        allow_delegation=False,
+        system_template="You are a test agent...",
+        prompt_template="This is a test prompt...",
+        # response_template is intentionally missing
+    )
+
+    assert agent.role == "Test Role"
+    assert agent.goal == "Test Goal"
+    assert agent.backstory == "Test Backstory"
+    
 def test_agent_default_values():
     agent = Agent(role="test role", goal="test goal", backstory="test backstory")
     assert agent.llm.model == "gpt-4o-mini"

tests/agents/agent_adapters/__init__.py

@@ -0,0 +1 @@
+"""Tests for agent adapters."""

tests/agents/agent_builder/__init__.py

@@ -0,0 +1 @@
+"""Tests for agent builder."""

tests/cassettes/test_guardrail_emits_events.yaml

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+      - A novel depicting the experiences of German soldiers during World War I, highlighting
+      the horrors of trench warfare.\n\n2. **\"The First World War\" by John Keegan**
+      - A comprehensive overview of the war, analyzing its causes, major battles,
+      and consequences.\n\n3. **\"A World Undone: The Story of the Great War, 1914
+      to 1918\" by G.J. Meyer** - A narrative history that covers the entire conflict
+      with a focus on key events and figures.\n\n4. **\"The Guns of August\" by Barbara
+      W. Tuchman** - An acclaimed work detailing the events leading up to the war
+      and the early stages of combat, emphasizing the decisions of leaders.\n\n5.
+      **\"Goodbye to All That\" by Robert Graves** - An autobiography that captures
+      the experience of trench warfare from a soldier''s perspective, along with the
+      transition to post-war life.\n\n6. **\"With Our Backs to the Wall: Victory and
+      Defeat in 1918\" by David Stevenson** - An analysis of the final year of the
+      war, outlining both the military strategies and the socio-political contexts
+      that shaped the outcome.\n\n7. **\"The Great War: A Combat History of the First
+      World War\" by Peter Hart** - This book provides a battle-by-battle account,
+      using personal diaries and accounts to bring the war''s events to life.\n\n8.
+      **\"The War to End All Wars: The American Military Experience in World War I\"
+      by Edward M. Coffman** - An exploration of American involvement in the war,
+      discussing military strategies and impacts.\n\n9. **\"Over the Top: A Soldier\u2019s
+      Diary of the First World War\" by Arthur Empey** - A firsthand account of trench
+      warfare written by an American volunteer, offering a raw depiction of combat
+      experiences.\n\n10. **\"The First World War: A New Illustrated History\" by
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+      history of the war, accessible for readers of all backgrounds.\n\nThis list
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+      if the output is not valid.\nYour personal goal is: Validate the output of the
+      task\n\nTo give my best complete final answer to the task respond using the
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tests/cli/deploy/__init__.py

@@ -0,0 +1 @@
+"""Tests for CLI deploy."""

tests/config/tasks.yaml

@@ -6,6 +6,7 @@ research_task:
   expected_output: >
     A list with 10 bullet points of the most relevant information about {topic}
   agent: researcher
+  guardrail: ensure each bullet contains its source
 
 reporting_task:
   description: >

tests/llm_test.py

@@ -373,6 +373,45 @@ def get_weather_tool_schema():
         },
     }
 
+def test_context_window_exceeded_error_handling():
+    """Test that litellm.ContextWindowExceededError is converted to LLMContextLengthExceededException."""
+    from litellm.exceptions import ContextWindowExceededError
+
+    from crewai.utilities.exceptions.context_window_exceeding_exception import (
+        LLMContextLengthExceededException,
+    )
+
+    llm = LLM(model="gpt-4")
+
+    # Test non-streaming response
+    with patch("litellm.completion") as mock_completion:
+        mock_completion.side_effect = ContextWindowExceededError(
+            "This model's maximum context length is 8192 tokens. However, your messages resulted in 10000 tokens.",
+            model="gpt-4",
+            llm_provider="openai"
+        )
+
+        with pytest.raises(LLMContextLengthExceededException) as excinfo:
+            llm.call("This is a test message")
+
+        assert "context length exceeded" in str(excinfo.value).lower()
+        assert "8192 tokens" in str(excinfo.value)
+
+    # Test streaming response
+    llm = LLM(model="gpt-4", stream=True)
+    with patch("litellm.completion") as mock_completion:
+        mock_completion.side_effect = ContextWindowExceededError(
+            "This model's maximum context length is 8192 tokens. However, your messages resulted in 10000 tokens.",
+            model="gpt-4",
+            llm_provider="openai"
+        )
+
+        with pytest.raises(LLMContextLengthExceededException) as excinfo:
+            llm.call("This is a test message")
+
+        assert "context length exceeded" in str(excinfo.value).lower()
+        assert "8192 tokens" in str(excinfo.value)
+
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 @pytest.fixture

tests/memory/__init__.py

@@ -0,0 +1 @@
+"""Tests for memory."""

tests/memory/user_memory_test.py

@@ -1,4 +1,3 @@
-
 from unittest.mock import MagicMock, patch
 
 import pytest
@@ -65,4 +64,4 @@ def test_save_and_search(user_memory):
     with patch.object(UserMemory, 'search', return_value=expected_result) as mock_search:
         find = UserMemory.search("test value", score_threshold=0.01)[0]
         mock_search.assert_called_once_with("test value", score_threshold=0.01)
-        assert find == expected_result[0]
+        assert find == expected_result[0]

tests/project_test.py

@@ -1,4 +1,5 @@
 from typing import List
+from unittest.mock import patch
 
 import pytest
 
@@ -142,6 +143,15 @@ def test_agent_function_calling_llm():
     ), "agent's function_calling_llm is incorrect"
 
 
+def test_task_guardrail():
+    crew = InternalCrew()
+    research_task = crew.research_task()
+    assert research_task.guardrail == "ensure each bullet contains its source"
+
+    reporting_task = crew.reporting_task()
+    assert reporting_task.guardrail is None
+
+
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_before_kickoff_modification():
     crew = InternalCrew()

tests/storage/__init__.py

@@ -0,0 +1 @@
+"""Tests for storage."""

tests/storage/test_mem0_storage.py

@@ -15,6 +15,7 @@ from crewai.task import Task
 class MockCrew:
     def __init__(self, memory_config):
         self.memory_config = memory_config
+        self.agents = [MagicMock(role="Test Agent")]
 
 
 @pytest.fixture
@@ -107,11 +108,13 @@ def mem0_storage_with_memory_client_using_config_from_crew(mock_mem0_memory_clie
 
 
 @pytest.fixture
-def mem0_storage_with_memory_client_using_explictly_config(mock_mem0_memory_client):
+def mem0_storage_with_memory_client_using_explictly_config(mock_mem0_memory_client, mock_mem0_memory):
     """Fixture to create a Mem0Storage instance with mocked dependencies"""
 
-    # We need to patch the MemoryClient before it's instantiated
-    with patch.object(MemoryClient, "__new__", return_value=mock_mem0_memory_client):
+    # We need to patch both MemoryClient and Memory to prevent actual initialization
+    with patch.object(MemoryClient, "__new__", return_value=mock_mem0_memory_client), \
+         patch.object(Memory, "__new__", return_value=mock_mem0_memory):
+
         crew = MockCrew(
             memory_config={
                 "provider": "mem0",
@@ -155,3 +158,82 @@ def test_mem0_storage_with_explict_config(
         mem0_storage_with_memory_client_using_explictly_config.memory_config
         == expected_config
     )
+
+
+def test_save_method_with_memory_oss(mem0_storage_with_mocked_config):
+    """Test save method for different memory types"""
+    mem0_storage, _, _ = mem0_storage_with_mocked_config
+    mem0_storage.memory.add = MagicMock()
+    
+    # Test short_term memory type (already set in fixture)
+    test_value = "This is a test memory"
+    test_metadata = {"key": "value"}
+    
+    mem0_storage.save(test_value, test_metadata)
+    
+    mem0_storage.memory.add.assert_called_once_with(
+        test_value,
+        agent_id="Test_Agent",
+        infer=False,
+        metadata={"type": "short_term", "key": "value"},
+    )
+
+
+def test_save_method_with_memory_client(mem0_storage_with_memory_client_using_config_from_crew):
+    """Test save method for different memory types"""
+    mem0_storage = mem0_storage_with_memory_client_using_config_from_crew
+    mem0_storage.memory.add = MagicMock()
+    
+    # Test short_term memory type (already set in fixture)
+    test_value = "This is a test memory"
+    test_metadata = {"key": "value"}
+    
+    mem0_storage.save(test_value, test_metadata)
+    
+    mem0_storage.memory.add.assert_called_once_with(
+        test_value,
+        agent_id="Test_Agent",
+        infer=False,
+        metadata={"type": "short_term", "key": "value"},
+        output_format="v1.1"
+    )
+
+
+def test_search_method_with_memory_oss(mem0_storage_with_mocked_config):
+    """Test search method for different memory types"""
+    mem0_storage, _, _ = mem0_storage_with_mocked_config
+    mock_results = {"results": [{"score": 0.9, "content": "Result 1"}, {"score": 0.4, "content": "Result 2"}]}
+    mem0_storage.memory.search = MagicMock(return_value=mock_results)
+
+    results = mem0_storage.search("test query", limit=5, score_threshold=0.5)
+
+    mem0_storage.memory.search.assert_called_once_with(
+        query="test query", 
+        limit=5, 
+        agent_id="Test_Agent",
+        user_id="test_user"
+    )
+
+    assert len(results) == 1
+    assert results[0]["content"] == "Result 1"
+
+
+def test_search_method_with_memory_client(mem0_storage_with_memory_client_using_config_from_crew):
+    """Test search method for different memory types"""
+    mem0_storage = mem0_storage_with_memory_client_using_config_from_crew
+    mock_results = {"results": [{"score": 0.9, "content": "Result 1"}, {"score": 0.4, "content": "Result 2"}]}
+    mem0_storage.memory.search = MagicMock(return_value=mock_results)
+
+    results = mem0_storage.search("test query", limit=5, score_threshold=0.5)
+
+    mem0_storage.memory.search.assert_called_once_with(
+        query="test query", 
+        limit=5, 
+        agent_id="Test_Agent", 
+        metadata={"type": "short_term"},
+        user_id="test_user",
+        output_format='v1.1'
+    )
+
+    assert len(results) == 1
+    assert results[0]["content"] == "Result 1"

tests/test_task_guardrails.py

@@ -1,11 +1,16 @@
-"""Tests for task guardrails functionality."""
-
-from unittest.mock import Mock
+from unittest.mock import ANY, Mock, patch
 
 import pytest
 
-from crewai.task import Task
+from crewai import Agent, Task
+from crewai.llm import LLM
+from crewai.tasks.task_guardrail import TaskGuardrail
 from crewai.tasks.task_output import TaskOutput
+from crewai.utilities.events import (
+    TaskGuardrailCompletedEvent,
+    TaskGuardrailStartedEvent,
+)
+from crewai.utilities.events.crewai_event_bus import crewai_event_bus
 
 
 def test_task_without_guardrail():
@@ -22,7 +27,7 @@ def test_task_without_guardrail():
     assert result.raw == "test result"
 
 
-def test_task_with_successful_guardrail():
+def test_task_with_successful_guardrail_func():
     """Test that successful guardrail validation passes transformed result."""
 
     def guardrail(result: TaskOutput):
@@ -127,3 +132,138 @@ def test_guardrail_error_in_context():
 
     assert "Task failed guardrail validation" in str(exc_info.value)
     assert "Expected JSON, got string" in str(exc_info.value)
+
+
+@pytest.fixture
+def sample_agent():
+    return Agent(role="Test Agent", goal="Test Goal", backstory="Test Backstory")
+
+
+@pytest.fixture
+def task_output():
+    return TaskOutput(
+        raw="""
+        Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever
+        """,
+        description="Test task",
+        expected_output="Output",
+        agent="Test Agent",
+    )
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_task_guardrail_process_output(task_output):
+    guardrail = TaskGuardrail(
+        description="Ensure the result has less than 10 words", llm=LLM(model="gpt-4o")
+    )
+
+    result = guardrail(task_output)
+    assert result[0] is False
+
+    assert "exceeding the guardrail limit of fewer than" in result[1].lower()
+
+    guardrail = TaskGuardrail(
+        description="Ensure the result has less than 500 words", llm=LLM(model="gpt-4o")
+    )
+
+    result = guardrail(task_output)
+    assert result[0] is True
+    assert result[1] == task_output.raw
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_guardrail_emits_events(sample_agent):
+    started_guardrail = []
+    completed_guardrail = []
+
+    with crewai_event_bus.scoped_handlers():
+
+        @crewai_event_bus.on(TaskGuardrailStartedEvent)
+        def handle_guardrail_started(source, event):
+            started_guardrail.append(
+                {"guardrail": event.guardrail, "retry_count": event.retry_count}
+            )
+
+        @crewai_event_bus.on(TaskGuardrailCompletedEvent)
+        def handle_guardrail_completed(source, event):
+            completed_guardrail.append(
+                {
+                    "success": event.success,
+                    "result": event.result,
+                    "error": event.error,
+                    "retry_count": event.retry_count,
+                }
+            )
+
+        task = Task(
+            description="Gather information about available books on the First World War",
+            agent=sample_agent,
+            expected_output="A list of available books on the First World War",
+            guardrail="Ensure the authors are from Italy",
+        )
+
+        result = task.execute_sync(agent=sample_agent)
+
+        def custom_guardrail(result: TaskOutput):
+            return (True, "good result from callable function")
+
+        task = Task(
+            description="Test task",
+            expected_output="Output",
+            guardrail=custom_guardrail,
+        )
+
+        task.execute_sync(agent=sample_agent)
+
+        expected_started_events = [
+            {"guardrail": "Ensure the authors are from Italy", "retry_count": 0},
+            {"guardrail": "Ensure the authors are from Italy", "retry_count": 1},
+            {
+                "guardrail": """def custom_guardrail(result: TaskOutput):
+            return (True, "good result from callable function")""",
+                "retry_count": 0,
+            },
+        ]
+
+        expected_completed_events = [
+            {
+                "success": False,
+                "result": None,
+                "error": "The task result does not comply with the guardrail because none of "
+                "the listed authors are from Italy. All authors mentioned are from "
+                "different countries, including Germany, the UK, the USA, and others, "
+                "which violates the requirement that authors must be Italian.",
+                "retry_count": 0,
+            },
+            {"success": True, "result": result.raw, "error": None, "retry_count": 1},
+            {
+                "success": True,
+                "result": "good result from callable function",
+                "error": None,
+                "retry_count": 0,
+            },
+        ]
+        assert started_guardrail == expected_started_events
+        assert completed_guardrail == expected_completed_events
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_guardrail_when_an_error_occurs(sample_agent, task_output):
+    with (
+        patch(
+            "crewai.Agent.kickoff",
+            side_effect=Exception("Unexpected error"),
+        ),
+        pytest.raises(
+            Exception,
+            match="Error while validating the task output: Unexpected error",
+        ),
+    ):
+        task = Task(
+            description="Gather information about available books on the First World War",
+            agent=sample_agent,
+            expected_output="A list of available books on the First World War",
+            guardrail="Ensure the authors are from Italy",
+            max_retries=0,
+        )
+        task.execute_sync(agent=sample_agent)

tests/tools/__init__.py

@@ -0,0 +1 @@
+"""Tests for tools."""

tests/utilities/__init__.py

@@ -0,0 +1 @@
+"""Tests for utilities."""

tests/utilities/evaluators/__init__.py

@@ -0,0 +1 @@
+"""Tests for evaluators."""

tests/utilities/events/__init__.py

@@ -0,0 +1 @@
+"""Tests for events."""

uv.lock

@@ -1,32 +1,150 @@
 version = 1
-revision = 1
 requires-python = ">=3.10, <3.13"
 resolution-markers = [
-    "python_full_version < '3.11' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
-    "python_full_version < '3.11' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
-    "python_version < '0'",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
-    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
-    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
-    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
-    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux'",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
-    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
 ]
 
 [[package]]
@@ -334,7 +452,7 @@ name = "build"
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 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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+    { name = "colorama", marker = "os_name == 'nt'" },
     { name = "importlib-metadata", marker = "python_full_version < '3.10.2'" },
     { name = "packaging" },
     { name = "pyproject-hooks" },
@@ -569,7 +687,7 @@ name = "click"
 version = "8.1.8"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "colorama", marker = "sys_platform == 'win32'" },
+    { name = "colorama", marker = "platform_system == 'Windows'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/b9/2e/0090cbf739cee7d23781ad4b89a9894a41538e4fcf4c31dcdd705b78eb8b/click-8.1.8.tar.gz", hash = "sha256:ed53c9d8990d83c2a27deae68e4ee337473f6330c040a31d4225c9574d16096a", size = 226593 }
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@@ -620,7 +738,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.114.0"
+version = "0.117.1"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },
@@ -708,15 +826,15 @@ requires-dist = [
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     { name = "chromadb", specifier = ">=0.5.23" },
     { name = "click", specifier = ">=8.1.7" },
-    { name = "crewai-tools", marker = "extra == 'tools'", specifier = "~=0.40.1" },
+    { name = "crewai-tools", marker = "extra == 'tools'", specifier = "~=0.42.2" },
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-    { name = "litellm", specifier = "==1.60.2" },
-    { name = "mem0ai", marker = "extra == 'mem0'", specifier = ">=0.1.29" },
+    { name = "litellm", specifier = "==1.67.1" },
+    { name = "mem0ai", marker = "extra == 'mem0'", specifier = ">=0.1.94" },
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@@ -735,7 +853,6 @@ requires-dist = [
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 ]
-provides-extras = ["tools", "embeddings", "agentops", "fastembed", "pdfplumber", "pandas", "openpyxl", "mem0", "docling", "aisuite"]
 
 [package.metadata.requires-dev]
 dev = [
@@ -758,7 +875,7 @@ dev = [
 
 [[package]]
 name = "crewai-tools"
-version = "0.40.1"
+version = "0.42.2"
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 dependencies = [
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@@ -773,9 +890,9 @@ dependencies = [
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+    { url = "https://files.pythonhosted.org/packages/4e/43/0f70b95350084e5cb1e1d74e9acb9e18a89ba675b1d579c787c2662baba7/crewai_tools-0.42.2-py3-none-any.whl", hash = "sha256:13727fb68f0efefd21edeb281be3d66ff2f5a3b5029d4e6adef388b11fd5846a", size = 583933 },
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 [[package]]
@@ -2266,7 +2383,7 @@ wheels = [
 
 [[package]]
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-version = "1.60.2"
+version = "1.67.1"
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 [[package]]
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-version = "0.1.29"
+version = "0.1.94"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "openai" },
     { name = "posthog" },
+    { name = "psycopg2-binary" },
     { name = "pydantic" },
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     { name = "qdrant-client" },
     { name = "sqlalchemy" },
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 name = "ptyprocess"
 version = "0.7.0"
@@ -5022,19 +5186,19 @@ dependencies = [
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-    { name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
+    { name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cuda-runtime-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cufft-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-curand-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
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+    { name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
     { name = "sympy" },
-    { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
+    { name = "triton", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
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@@ -5081,7 +5245,7 @@ name = "tqdm"
 version = "4.66.5"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "colorama", marker = "sys_platform == 'win32'" },
+    { name = "colorama", marker = "platform_system == 'Windows'" },
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 sdist = { url = "https://files.pythonhosted.org/packages/58/83/6ba9844a41128c62e810fddddd72473201f3eacde02046066142a2d96cc5/tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad", size = 169504 }
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@@ -5123,7 +5287,7 @@ name = "triton"
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 dependencies = [
-    { name = "filelock", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "filelock", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'linux')" },
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 wheels = [
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+    "python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation == 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation == 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
 ]
 dependencies = [
     { name = "pyyaml", marker = "platform_python_implementation == 'PyPy'" },
@@ -5307,18 +5531,78 @@ name = "vcrpy"
 version = "7.0.0"
 source = { registry = "https://pypi.org/simple" }
 resolution-markers = [
-    "python_full_version < '3.11' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
-    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
-    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
-    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux'",
-    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version < '3.11' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version < '3.11' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version == '3.11.*' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'darwin'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'darwin'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform == 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'darwin')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform == 'linux'",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform == 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system == 'Darwin' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and platform_python_implementation != 'PyPy' and platform_system == 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux'",
+    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and sys_platform != 'darwin') or (python_full_version >= '3.12.4' and platform_python_implementation != 'PyPy' and platform_system != 'Darwin' and platform_system != 'Linux' and sys_platform != 'darwin' and sys_platform != 'linux')",
 ]
 dependencies = [
     { name = "pyyaml", marker = "platform_python_implementation != 'PyPy'" },