Fixes missing prompt template or system template

[Vidit-Ostwal]

Fixes #2402

Built on top of #2403,
Changed the structure of files and added test cases in the test_agent itself.

[joaomdmoura]

Disclaimer: This review was made by a crew of AI Agents.

Code Review Comment for PR #2408

Overview

This PR addresses issue #2402, enhancing the handling of templates within the crewAI framework. The primary goal is to bolster the system's resilience when encountering missing templates.

1. src/crewai/utilities/prompts.py

Positive Changes

• The error handling for missing templates has been significantly improved.
• There is now a fallback mechanism to a default format which enhances user experience.
• The separation of template handling logic has been improved, promoting better readability.

Issues Identified

1. Redundant Conditions:

   • The condition if not system_template or not prompt_template could lead to unexpected behavior. A more nuanced condition could improve clarity.

   Suggestion: Implement a more detailed check for critical vs. optional templates to tighten the logic and prevent potential edge cases.

2. Missing Input Validation:

   • The current implementation lacks validation for the format of the templates, which can allow erroneous types to be accepted without feedback.

3. Incomplete Error Handling:

   • The current implementation does not provide clear error messages for cases involving malformed templates, which can hinder debugging.

Suggested Code Improvement

def _build_prompt(
        self,
        components,
        system_template=None,
        prompt_template=None,
        response_template=None,
    ) -> str:
        # Input validations should be added here.
        # Example code for validation
        if system_template and not isinstance(system_template, str):
            raise ValueError("system_template must be a string")

2. Tests

Positive Aspects

• Good test coverage for new functionalities and different template scenarios.
• Clear assertions to validate expected behavior of the system.

Issues Identified

1. Duplicate Test Cases:

   • Similar tests are found across multiple files, which may lead to maintenance challenges.

2. Inconsistent Test Organization:

   • Tests should be organized logically to improve clarity and reduce redundant code.

3. Missing Edge Cases:

   • Some potential template combinations were not adequately tested, which could introduce unforeseen issues.

Suggested Test Improvement

@pytest.mark.parametrize("templates", [
    {"system_template": "Example Template"},
    {"prompt_template": "Prompt Template"},
])
def test_agent_template_combinations(templates):
    # Test various template combinations with clear assertions.

General Recommendations

1. Code Organization:

   • Consolidate all template-related tests into a dedicated file for better maintainability.
   • Move utility functions into a dedicated module if necessary.

2. Error Handling:

   • Improve logging mechanisms for template processing errors for enhanced traceability.
   • Consider introducing custom exceptions to clarify errors related to template handling.

3. Testing:

   • Integrate property-based tests and edge case scenarios to fully validate template handling logic.
   • Consider adding integration tests that utilize real-world template examples for comprehensive test coverage.

4. Documentation:

   • Enhance documentation regarding valid and invalid template formats, including the fallback behavior of the system.
   • Include warning notes about the necessity for input validation.

Impact Analysis

• Positive: The changes enhance the reliability and robustness of template handling.
• Neutral: Minor performance overhead from additional checks, though generally acceptable.
• Risk: Potential issues with backward compatibility; thorough testing recommended to ensure existing functionality remains unaffected.

The changes made in this PR are a step in the right direction towards improving the resilience of template handling within crewAI. Adhering to the suggested improvements will further solidify the implementation and mitigate risks in future enhancements.