Supporting no-code Guardrail creation (#2636)

* feat: support to define a guardrail task no-code

* feat: add auto-discovery for Guardrail code execution mode

* feat: handle malformed or invalid response from CodeInterpreterTool

* feat: allow to set unsafe_mode from Guardrail task

* feat: renaming GuardrailTask to TaskGuardrail

* feat: ensure guardrail is callable while initializing Task

* feat: remove Docker availability check from TaskGuardrail

The CodeInterpreterTool already ensures compliance with this requirement.

* refactor: replace if/raise with assert

For this use case `assert` is more appropriate choice

* test: remove useless or duplicated test

* fix: attempt to fix type-checker

* feat: support to define a task guardrail using YAML config

* refactor: simplify TaskGuardrail to use LLM for validation, no code generation

* docs: update TaskGuardrail doc strings

* refactor: drop task paramenter from TaskGuardrail

This parameter was used to get the model from the `task.agent` which is a quite bit redudant since we could propagate the llm directly

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.