Update test workflow to use custom test runner for 'fast' pattern and…#599
Update test workflow to use custom test runner for 'fast' pattern and…#599MervinPraison merged 2 commits intomainfrom
Conversation
… refine guardrail functionality in Task class - Changed the test command in the GitHub Actions workflow to run a specific test runner script with a 'fast' pattern. - Introduced guardrail functionality in the Task class to validate task outputs, including error handling and retry logic for guardrail validation failures. - Enhanced the initialization of guardrail parameters and ensured proper type checking for guardrail functions.
❌ Deploy Preview for praisonai failed.
|
WalkthroughThis update introduces a guardrails system to PraisonAI Agents, enabling validation and modification of task outputs using either function-based or LLM-based guardrails. The changes add new modules, public APIs, documentation, example scripts, and tests to demonstrate, validate, and document the guardrail functionality, while updating workflows and public exports accordingly. Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant Agent
participant Task
participant Guardrail
participant LLM (optional)
User->>Agent: Create Agent (with/without guardrail)
Agent->>Task: Create Task (with guardrail config)
User->>Agent: Run Task with input
Agent->>Task: Execute Task
Task->>Guardrail: Validate output
alt Function-based guardrail
Guardrail-->>Task: Return (pass/fail, result/error)
else LLM-based guardrail
Guardrail->>LLM: Send validation prompt
LLM-->>Guardrail: Respond (PASS/FAIL)
Guardrail-->>Task: Return (pass/fail, result/error)
end
alt Guardrail passes
Task->>Agent: Continue execution
else Guardrail fails and retries remain
Task->>Task: Increment retry, re-run callback
else Guardrail fails and retries exhausted
Task-->>Agent: Raise exception
end
Agent-->>User: Return result or error
Suggested labels
Poem
✨ Finishing Touches
Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out. 🪧 TipsChatThere are 3 ways to chat with CodeRabbit:
SupportNeed help? Create a ticket on our support page for assistance with any issues or questions. Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments. CodeRabbit Commands (Invoked using PR comments)
Other keywords and placeholders
CodeRabbit Configuration File (
|
![gemini-code-assist[bot]](https://avatars.githubusercontent.com/in/956858?s=60&v=4){kind=small}
There was a problem hiding this comment.
Hello @MervinPraison, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
Summary of Changes
Hello team, Gemini here with a summary of this pull request from MervinPraison. This PR focuses on two main areas: updating the test workflow and significantly enhancing the Task class with new guardrail functionality.
The test workflow update, as indicated by the title and description, involves changing the GitHub Actions command to use a custom test runner with a 'fast' pattern. While the specific workflow file changes aren't included in the patch content provided, the intent is clear.
The major part of this PR introduces a robust guardrail system into the Task class. This allows for validation of task outputs using either custom Python functions or natural language descriptions processed by an LLM. The implementation includes error handling and a retry mechanism for tasks that fail guardrail validation, enhancing the reliability and safety of agent workflows. The PR also adds new examples and tests to demonstrate and verify this new functionality.
Highlights
- Guardrail Functionality in Task Class: Introduces a
guardrailparameter to theTaskclass, allowing validation of task outputs. - Support for Function and LLM Guardrails: Guardrails can be provided as a callable Python function or a string description for LLM-based validation.
- Configurable Retries for Validation Failures: Adds
max_retriesandretry_countparameters toTaskto handle retries when a guardrail check fails. - Guardrail Result Structure: Introduces a
GuardrailResultclass to standardize the output of guardrail checks, indicating success/failure and providing error details or a modified result. - LLM Guardrail Implementation: Adds an
LLMGuardrailclass that uses an LLM to evaluate task output against a natural language description. - Guardrail Setup and Type Checking: Includes logic in the
Taskclass to set up the appropriate guardrail function (_guardrail_fn) and perform basic type checking for callable guardrails. - New Examples and Tests: Adds several new files (
agent_guardrails_example.py,guardrails_example.py,simple_guardrail_test.py,test_guardrails.py) to demonstrate and test the new guardrail features. - Documentation Update: Adds a comprehensive
CLAUDE.mdfile detailing the project architecture, including the new Guardrails system. - Test Workflow Update (Based on Title/Description): Updates the GitHub Actions workflow to use a custom test runner with a 'fast' pattern (details not visible in provided patches).
Changelog
Click here to see the changelog
- src/praisonai-agents/.cursorrules
- Removed a large block of detailed technical overview text related to workflow loops and task resetting (lines 9-150).
- src/praisonai-agents/CLAUDE.md
- Added a new Markdown file providing a detailed overview of the project architecture, development commands, and patterns, including a section on Guardrails.
- src/praisonai-agents/agent_guardrails_example.py
- Added a new example script demonstrating how to use a function-based guardrail directly with an Agent.
- src/praisonai-agents/guardrails_example.py
- Added a new example script demonstrating both function-based and string-based (LLM) guardrails on a Task, including simulating pass/fail scenarios and showing backward compatibility.
- src/praisonai-agents/praisonaiagents/init.py
- Imported
GuardrailResultandLLMGuardrailfrom the newguardrailsmodule (line 15). - Added
GuardrailResultandLLMGuardrailto the__all__list for export (lines 60-61).
- Imported
- src/praisonai-agents/praisonaiagents/guardrails/init.py
- Added a new
__init__.pyfile to create theguardrailspackage. - Imports
GuardrailResultandLLMGuardrailfrom their respective files.
- Added a new
- src/praisonai-agents/praisonaiagents/guardrails/guardrail_result.py
- Added a new file defining the
GuardrailResultPydantic model (lines 13-18). - Added a class method
from_tupleto convert a(bool, Any)result into aGuardrailResultobject (lines 20-43).
- Added a new file defining the
- src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py
- Added a new file defining the
LLMGuardrailclass (lines 14-88). - Implements LLM-based validation using a natural language description and an LLM instance.
- Constructs a validation prompt and parses the LLM's 'PASS'/'FAIL' response.
- Added a new file defining the
- src/praisonai-agents/praisonaiagents/task/task.py
- Imported necessary types and the
inspectmodule for type checking (lines 3-4). - Added
guardrail,max_retries, andretry_countparameters to theTaskconstructor (lines 45-47). - Initialized new guardrail-related attributes (
guardrail,max_retries,retry_count,_guardrail_fn) (lines 87-90). - Added
_setup_guardrailmethod to initialize_guardrail_fnbased on theguardrailparameter, including type validation for callable guardrails and creatingLLMGuardrailfor string inputs (lines 155-200). - Modified
execute_callbackto process the guardrail after task output generation (lines 247-277). - Added logic in
execute_callbackto check guardrail result, incrementretry_counton failure, raise an exception ifmax_retriesis reached, and potentially updatetask_outputif the guardrail returns a modified result (lines 250-271). - Added
_process_guardrailhelper method to call the configured guardrail function and convert its output toGuardrailResult(lines 427-455).
- Imported necessary types and the
- src/praisonai-agents/sequence.py
- Added a new example script demonstrating a sequential agent using an MCP tool.
- src/praisonai-agents/simple_guardrail_test.py
- Added a new test script with simple unit tests for
GuardrailResult, function guardrail logic, and LLM guardrail logic using a mock LLM.
- Added a new test script with simple unit tests for
- src/praisonai-agents/test_guardrails.py
- Added a new test script with integrated tests for function-based and string-based LLM guardrails within the Task context, using a mock LLM.
Using Gemini Code Assist
The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.
Invoking Gemini
You can request assistance from Gemini at any point in your pull request via creating an issue comment (i.e. comment on the pull request page) using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands.
| Feature | Command | Description |
|---|---|---|
| Code Review | /gemini review |
Performs a code review for the current pull request in its current state. |
| Pull Request Summary | /gemini summary |
Provides a summary of the current pull request in its current state. |
| Comment | @gemini-code-assist | Responds in comments when explicitly tagged, both in issue comments and review comments. |
| Help | /gemini help |
Displays a list of available commands. |
Customization
To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.
Limitations & Feedback
Gemini Code Assist is currently in preview and may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments to provide feedback.
You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.
Output flows, a stream,
Guardrails check, a watchful gleam.
Pass or fail the test,
Retry, give it your best,
Ensure the agent's dream.
Footnotes
-
Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩
PR Reviewer Guide 🔍Here are some key observations to aid the review process:
|
PR Code Suggestions ✨No code suggestions found for the PR. |
CI Feedback 🧐(Feedback updated until commit 4089c45)A test triggered by this PR failed. Here is an AI-generated analysis of the failure:
|
There was a problem hiding this comment.
Code Review
This pull request introduces a robust guardrail system for task output validation, which is a fantastic addition to PraisonAI Agents. It supports both custom function guardrails and LLM-based guardrails, complete with retry mechanisms. The code is generally well-written, and the inclusion of examples and tests is appreciated.
I have a few suggestions regarding the error handling strategy in LLMGuardrail, a type hint validation detail in Task._setup_guardrail, and a potential duplicate example file. Addressing these would further strengthen this feature.
I'm using PEP 8 as the general style guide for Python in this review.
Summary of Findings
- LLMGuardrail Error Handling: The
LLMGuardraildefaults to a "fail-open" behavior (validation passes) if it encounters internal issues (e.g., LLM unavailable, unclear response). This might be risky for critical guardrails and could benefit from being configurable. - Type Hint Validation in Task: The validation logic for a guardrail function's return type annotation
Tuple[bool, Union[str, TaskOutput]]inTask._setup_guardrailmay not correctly identify this specific Union type. Simpler checks or a more robust Union check could be considered. - Duplicate Example File: The
guardrails_example.pyscript appears in two locations (src/praisonai-agents/andsrc/praisonai-agents/tests/). Consolidating to one, likely in thetests/directory, would improve maintainability. - Documentation Detail (CLAUDE.md): In
CLAUDE.md, line 204 specifiesUse conda activate praisonai-agents. While fine for a specific setup, a more general instruction for activating virtual environments might be considered if Claude's setup isn't guaranteed to use this exact environment name. (Severity: low, not commented directly) - Test Redundancy: The
test_guardrail_resultfunction is duplicated insimple_guardrail_test.pyandtest_guardrails.py. This is minor. (Severity: low, not commented directly)
Merge Readiness
The pull request introduces valuable guardrail functionality and is largely in good shape. However, I recommend addressing the medium-severity issues identified—particularly regarding the LLMGuardrail's error handling behavior and the type hint validation—before merging. These changes will enhance the robustness and maintainability of the new feature. As an AI, I am not authorized to approve pull requests; please ensure further review and approval from team members.
| if not self.llm: | ||
| self.logger.warning("No LLM provided for guardrail validation") | ||
| return True, task_output | ||
|
|
||
| # Create validation prompt | ||
| validation_prompt = f""" | ||
| You are a quality assurance validator. Your task is to evaluate the following output against specific criteria. | ||
|
|
||
| Validation Criteria: {self.description} | ||
|
|
||
| Output to Validate: | ||
| {task_output.raw} | ||
|
|
||
| Please evaluate if this output meets the criteria. Respond with: | ||
| 1. "PASS" if the output meets all criteria | ||
| 2. "FAIL: [specific reason]" if the output does not meet criteria | ||
|
|
||
| Your response:""" | ||
|
|
||
| # Get LLM response | ||
| if hasattr(self.llm, 'chat'): | ||
| # For Agent's LLM interface | ||
| response = self.llm.chat(validation_prompt, temperature=0.1) | ||
| elif hasattr(self.llm, 'get_response'): | ||
| # For custom LLM instances | ||
| response = self.llm.get_response(validation_prompt, temperature=0.1) | ||
| elif callable(self.llm): | ||
| # For simple callable LLMs | ||
| response = self.llm(validation_prompt) | ||
| else: | ||
| self.logger.error(f"Unsupported LLM type: {type(self.llm)}") | ||
| return True, task_output | ||
|
|
||
| # Parse response | ||
| response = str(response).strip() | ||
|
|
||
| if response.upper().startswith("PASS"): | ||
| return True, task_output | ||
| elif response.upper().startswith("FAIL"): | ||
| # Extract the reason | ||
| reason = response[5:].strip(": ") | ||
| return False, f"Guardrail validation failed: {reason}" | ||
| else: | ||
| # Unclear response, log and pass through | ||
| self.logger.warning(f"Unclear guardrail response: {response}") | ||
| return True, task_output | ||
|
|
||
| except Exception as e: | ||
| self.logger.error(f"Error in LLM guardrail validation: {str(e)}") | ||
| # On error, pass through the original output | ||
| return True, task_output No newline at end of file |
There was a problem hiding this comment.
The LLMGuardrail currently exhibits a "fail-open" behavior in several scenarios:
- If
self.llmis not provided (line 38-40). - If an unsupported LLM type is encountered (lines 67-69).
- If the LLM's response is unclear (lines 80-83).
- If an exception occurs during the
__call__method (lines 85-88).
In these cases, the guardrail effectively passes (return True, task_output).
While this prevents the guardrail mechanism itself from breaking task execution, it might not be the desired behavior if a guardrail is critical for safety, compliance, or correctness, as potentially problematic output could pass through unchecked.
Could we consider making this behavior configurable? For instance, an option like fail_closed_on_error: bool could allow users to specify that if the guardrail cannot operate reliably, it should result in a validation failure. Alternatively, what are your thoughts on the implications of this fail-open approach for critical guardrails?
| if not ( | ||
| get_origin(return_annotation) is tuple | ||
| and len(return_annotation_args) == 2 | ||
| and return_annotation_args[0] is bool | ||
| and ( | ||
| return_annotation_args[1] is Any | ||
| or return_annotation_args[1] is str | ||
| or return_annotation_args[1] is TaskOutput | ||
| or return_annotation_args[1] == Union[str, TaskOutput] | ||
| ) | ||
| ): | ||
| raise ValueError( | ||
| "If return type is annotated, it must be Tuple[bool, Any]" | ||
| ) |
There was a problem hiding this comment.
The condition return_annotation_args[1] == Union[str, TaskOutput] for validating the guardrail function's return type annotation might not behave as intended. Union[str, TaskOutput] is a typing construct, and return_annotation_args[1] would typically be an actual type like str, TaskOutput, or Any (if the annotation was, for example, Tuple[bool, str]).
If the intent is to check if the second element of the tuple annotation is specifically Union[str, TaskOutput], the check should involve get_origin(return_annotation_args[1]) is Union and then examining get_args(return_annotation_args[1]).
However, the preceding checks for is Any, is str, or is TaskOutput (lines 180-182) already cover many practical cases. Given that Any is accepted, is this specific check for Union[str, TaskOutput] necessary, or could it be simplified/removed to avoid potential misbehavior if a developer actually annotates with Union[str, TaskOutput] expecting this check to validate it correctly?
For example, if the annotation is Tuple[bool, Union[str, TaskOutput]], then return_annotation_args[1] would be typing.Union[str, praisonaiagents.main.TaskOutput]. Comparing this directly with Union[str, TaskOutput] (which is typing.Union) will likely be false.
A more robust check for a union type might look like:
(get_origin(return_annotation_args[1]) is Union and
set(get_args(return_annotation_args[1])) == {str, TaskOutput})But again, consider if this level of specificity is needed given Any is allowed.
| sys.path.insert(0, os.path.abspath('..')) | ||
|
|
||
| from praisonaiagents import Agent, Task, TaskOutput | ||
|
|
||
|
|
||
| def email_validator(task_output: TaskOutput) -> Tuple[bool, Any]: | ||
| """ | ||
| Function-based guardrail to validate email content. | ||
|
|
||
| Args: | ||
| task_output: The task output to validate | ||
|
|
||
| Returns: | ||
| Tuple of (success, result_or_error) | ||
| """ | ||
| content = task_output.raw.lower() | ||
|
|
||
| # Check for required email components | ||
| if "subject:" not in content: | ||
| return False, "Email must include a subject line" | ||
|
|
||
| if "dear" not in content and "hello" not in content: | ||
| return False, "Email must include a proper greeting" | ||
|
|
||
| if len(content) < 50: | ||
| return False, "Email content is too short" | ||
|
|
||
| if "error" in content or "problem" in content: | ||
| return False, "Email should not mention errors or problems" | ||
|
|
||
| return True, task_output | ||
|
|
||
|
|
||
| def main(): | ||
| """Run the guardrails example.""" | ||
| print("PraisonAI Agents - Guardrails Example") | ||
| print("=====================================\n") | ||
|
|
||
| # Create an agent | ||
| agent = Agent( | ||
| name="Email Assistant", | ||
| role="Professional Email Writer", | ||
| goal="Write clear, professional emails", | ||
| backstory="I am an AI assistant specialized in writing professional emails" | ||
| ) | ||
|
|
||
| print("1. Testing Function-based Guardrail") | ||
| print("------------------------------------") | ||
|
|
||
| # Create task with function-based guardrail | ||
| task_with_function_guardrail = Task( | ||
| description="Write a professional email to a client about project completion", | ||
| expected_output="A well-formatted professional email", | ||
| agent=agent, | ||
| guardrail=email_validator, # Function-based guardrail | ||
| max_retries=2 | ||
| ) | ||
|
|
||
| print(f"Task created with function guardrail: {email_validator.__name__}") | ||
| print(f"Max retries: {task_with_function_guardrail.max_retries}") | ||
|
|
||
| # Simulate a task output that should pass | ||
| good_output = TaskOutput( | ||
| description="Email task", | ||
| raw="""Subject: Project Completion Update | ||
|
|
||
| Dear Client, | ||
|
|
||
| I am pleased to inform you that your project has been completed successfully. | ||
| All deliverables have been reviewed and are ready for your review. | ||
| Please let me know if you have any questions. | ||
|
|
||
| Best regards, | ||
| Project Team""", | ||
| agent="Email Assistant" | ||
| ) | ||
|
|
||
| result = task_with_function_guardrail._process_guardrail(good_output) | ||
| print(f"Good email result: {'PASSED' if result.success else 'FAILED'}") | ||
| if not result.success: | ||
| print(f"Error: {result.error}") | ||
|
|
||
| # Simulate a task output that should fail | ||
| bad_output = TaskOutput( | ||
| description="Email task", | ||
| raw="Hi there, there was an error with your project.", | ||
| agent="Email Assistant" | ||
| ) | ||
|
|
||
| result = task_with_function_guardrail._process_guardrail(bad_output) | ||
| print(f"Bad email result: {'PASSED' if result.success else 'FAILED'}") | ||
| if not result.success: | ||
| print(f"Error: {result.error}") | ||
|
|
||
| print("\n2. Testing String-based LLM Guardrail") | ||
| print("-------------------------------------") | ||
|
|
||
| # Create task with string-based guardrail | ||
| task_with_llm_guardrail = Task( | ||
| description="Write a marketing email for a new product launch", | ||
| expected_output="Engaging marketing content", | ||
| agent=agent, | ||
| guardrail="Ensure the content is professional, engaging, includes a clear call-to-action, and is free of errors", | ||
| max_retries=3 | ||
| ) | ||
|
|
||
| print("Task created with LLM-based guardrail") | ||
| print("Guardrail description: 'Ensure the content is professional, engaging, includes a clear call-to-action, and is free of errors'") | ||
| print(f"Max retries: {task_with_llm_guardrail.max_retries}") | ||
|
|
||
| print("\n3. Backward Compatibility") | ||
| print("-------------------------") | ||
|
|
||
| # Create task without guardrail (backward compatible) | ||
| task_without_guardrail = Task( | ||
| description="Write a simple thank you note", | ||
| expected_output="A brief thank you message", | ||
| agent=agent | ||
| ) | ||
|
|
||
| print("Task created without guardrail (backward compatible)") | ||
| print(f"Guardrail function: {task_without_guardrail._guardrail_fn}") | ||
|
|
||
| # Test that it doesn't break existing functionality | ||
| simple_output = TaskOutput( | ||
| description="Thank you task", | ||
| raw="Thank you for your business!", | ||
| agent="Email Assistant" | ||
| ) | ||
|
|
||
| result = task_without_guardrail._process_guardrail(simple_output) | ||
| print(f"No guardrail result: {'PASSED' if result.success else 'FAILED'}") | ||
|
|
||
| print("\n✅ Guardrails example completed successfully!") | ||
| print("\nKey Features Demonstrated:") | ||
| print("- Function-based guardrails with custom validation logic") | ||
| print("- String-based LLM guardrails using natural language") | ||
| print("- Configurable retry mechanism") | ||
| print("- Backward compatibility with existing tasks") | ||
| print("- Integration with TaskOutput validation") | ||
|
|
||
|
|
||
| if __name__ == "__main__": | ||
| main() No newline at end of file |
There was a problem hiding this comment.
This file, src/praisonai-agents/tests/guardrails_example.py, appears to be a duplicate of src/praisonai-agents/guardrails_example.py.
The primary difference is the sys.path.insert(0, os.path.abspath('..')) in this version, suggesting it's intended to be run from the tests directory.
To maintain clarity and avoid redundancy, would it be better to keep only one version of this example? If it's primarily a test/example script, the tests/ directory seems like the more appropriate location. If so, the version in the src/praisonai-agents/ root could be removed.
![coderabbitai[bot]](https://avatars.githubusercontent.com/in/347564?s=60&v=4){kind=small}
There was a problem hiding this comment.
Actionable comments posted: 4
🧹 Nitpick comments (20)
src/praisonai-agents/praisonaiagents/guardrails/__init__.py (1)
1-11: LGTM! Well-structured package initialization.The guardrails package is properly structured with clear imports and public API definition.
Add a final newline to fix the formatting issue:
-__all__ = ["GuardrailResult", "LLMGuardrail"] +__all__ = ["GuardrailResult", "LLMGuardrail"] +🧰 Tools
🪛 Pylint (3.3.7)
[convention] 11-11: Final newline missing
(C0304)
src/praisonai-agents/agent_guardrails_example.py (2)
7-11: Add docstring and improve function validation.The function lacks a docstring and could benefit from more robust validation.
Apply this diff to add documentation:
def validate_content(task_output: TaskOutput) -> Tuple[bool, Any]: + """ + Validate that task output content meets minimum length requirement. + + Args: + task_output: The task output to validate + + Returns: + Tuple of (success, result_or_error_message) + """ if len(task_output.raw) < 50: return False, "Content too short" return True, task_output🧰 Tools
🪛 Pylint (3.3.7)
[convention] 7-7: Missing function or method docstring
(C0116)
13-21: Add main function documentation and remove trailing whitespace.The main function needs documentation and there's trailing whitespace on line 18.
Apply this diff:
def main(): + """Demonstrate function-based guardrails with Agent.""" agent = Agent( name="Writer", guardrail=validate_content - ) + ) result = agent.start("Write a welcome message with 4 words") print(result)🧰 Tools
🪛 Pylint (3.3.7)
[convention] 18-18: Trailing whitespace
(C0303)
[convention] 13-13: Missing function or method docstring
(C0116)
[error] 14-17: Unexpected keyword argument 'guardrail' in constructor call
(E1123)
src/praisonai-agents/guardrails_example.py (3)
9-10: Remove unused imports.The
sysandosimports are unused and should be removed.Apply this diff:
-import sys -import os from typing import Tuple, Any🧰 Tools
🪛 Ruff (0.11.9)
9-9:
sysimported but unusedRemove unused import:
sys(F401)
10-10:
osimported but unusedRemove unused import:
os(F401)
🪛 Pylint (3.3.7)
[warning] 9-9: Unused import sys
(W0611)
[warning] 10-10: Unused import os
(W0611)
113-118: Fix formatting issues.Multiple formatting issues including trailing whitespace and line length violations.
Apply this diff to fix formatting:
task_with_llm_guardrail = Task( description="Write a marketing email for a new product launch", expected_output="Engaging marketing content", agent=agent, - guardrail="Ensure the content is professional, engaging, includes a clear call-to-action, and is free of errors", + guardrail=( + "Ensure the content is professional, engaging, " + "includes a clear call-to-action, and is free of errors" + ), max_retries=3 ) - + print("Task created with LLM-based guardrail") - print("Guardrail description: 'Ensure the content is professional, engaging, includes a clear call-to-action, and is free of errors'") + print( + "Guardrail description: 'Ensure the content is professional, " + "engaging, includes a clear call-to-action, and is free of errors'" + ) print(f"Max retries: {task_with_llm_guardrail.max_retries}") - +🧰 Tools
🪛 Pylint (3.3.7)
[convention] 113-113: Line too long (121/100)
(C0301)
[convention] 116-116: Trailing whitespace
(C0303)
[convention] 118-118: Line too long (138/100)
(C0301)
154-154: Add missing final newline.The file is missing a final newline.
Add a newline at the end of the file.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 154-154: Final newline missing
(C0304)
src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py (4)
9-10: Remove unused imports.The
OptionalandBaseModelimports are unused and should be removed.Apply this diff:
-from typing import Any, Tuple, Union, Optional +from typing import Any, Tuple, Union -from pydantic import BaseModel from ..main import TaskOutput🧰 Tools
🪛 Ruff (0.11.9)
9-9:
typing.Optionalimported but unusedRemove unused import:
typing.Optional(F401)
10-10:
pydantic.BaseModelimported but unusedRemove unused import:
pydantic.BaseModel(F401)
🪛 Pylint (3.3.7)
[error] 10-10: Unable to import 'pydantic'
(E0401)
[warning] 9-9: Unused Optional imported from typing
(W0611)
[warning] 10-10: Unused BaseModel imported from pydantic
(W0611)
74-83: Improve response parsing logic structure.The response parsing logic is correct but could be more readable with clearer structure.
Apply this diff to improve readability:
if response.upper().startswith("PASS"): return True, task_output - elif response.upper().startswith("FAIL"): + if response.upper().startswith("FAIL"): # Extract the reason reason = response[5:].strip(": ") return False, f"Guardrail validation failed: {reason}" - else: - # Unclear response, log and pass through - self.logger.warning(f"Unclear guardrail response: {response}") - return True, task_output + + # Unclear response, log and pass through + self.logger.warning(f"Unclear guardrail response: {response}") + return True, task_output🧰 Tools
🪛 Pylint (3.3.7)
[refactor] 74-83: Unnecessary "elif" after "return", remove the leading "el" from "elif"
(R1705)
[warning] 82-82: Use lazy % formatting in logging functions
(W1203)
85-88: Consider more specific exception handling.Using broad
Exceptioncatching is generally discouraged. Consider catching more specific exceptions.Apply this diff for more specific error handling:
- except Exception as e: + except (AttributeError, TypeError, ValueError) as e: self.logger.error(f"Error in LLM guardrail validation: {str(e)}") # On error, pass through the original output return True, task_output + except Exception as e: + self.logger.error(f"Unexpected error in LLM guardrail validation: {str(e)}") + return True, task_output🧰 Tools
🪛 Pylint (3.3.7)
[convention] 88-88: Final newline missing
(C0304)
[warning] 85-85: Catching too general exception Exception
(W0718)
[warning] 86-86: Use lazy % formatting in logging functions
(W1203)
88-88: Add missing final newline.The file is missing a final newline.
Add a newline at the end of the file.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 88-88: Final newline missing
(C0304)
src/praisonai-agents/praisonaiagents/guardrails/guardrail_result.py (2)
32-43: Refactor to improve code style.The logic is correct, but the code can be simplified by removing the unnecessary
elseblock after thereturnstatement.Apply this diff to improve readability:
- if success: - return cls( - success=True, - result=data, - error="" - ) - else: - return cls( - success=False, - result=None, - error=str(data) if data else "Guardrail validation failed" - ) + if success: + return cls( + success=True, + result=data, + error="" + ) + return cls( + success=False, + result=None, + error=str(data) if data else "Guardrail validation failed" + )🧰 Tools
🪛 Pylint (3.3.7)
[convention] 43-43: Final newline missing
(C0304)
[refactor] 32-43: Unnecessary "else" after "return", remove the "else" and de-indent the code inside it
(R1705)
1-43: Address formatting issues.The file has several formatting issues that should be cleaned up for consistency.
Please address the following formatting issues:
- Remove trailing whitespace on lines 15, 17, 19, 31
- Add final newline at end of file
- Consider breaking the long line 17 if it exceeds project line length limits
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 15-15: Trailing whitespace
(C0303)
[convention] 17-17: Line too long (108/100)
(C0301)
[convention] 19-19: Trailing whitespace
(C0303)
[convention] 31-31: Trailing whitespace
(C0303)
[convention] 43-43: Final newline missing
(C0304)
[error] 9-9: Unable to import 'pydantic'
(E0401)
[refactor] 32-43: Unnecessary "else" after "return", remove the "else" and de-indent the code inside it
(R1705)
[refactor] 13-13: Too few public methods (1/2)
(R0903)
src/praisonai-agents/test_guardrails.py (3)
6-12: Remove unused imports.The file imports modules that are not used in the code.
Apply this diff to remove unused imports:
-import os import sys import logging from praisonaiagents import Agent, Task, TaskOutput -from praisonaiagents.guardrails import GuardrailResult, LLMGuardrail +from praisonaiagents.guardrails import GuardrailResult from typing import Tuple, Any🧰 Tools
🪛 Ruff (0.11.9)
6-6:
osimported but unusedRemove unused import:
os(F401)
11-11:
praisonaiagents.guardrails.LLMGuardrailimported but unusedRemove unused import:
praisonaiagents.guardrails.LLMGuardrail(F401)
🪛 Pylint (3.3.7)
[convention] 12-12: standard import "typing.Tuple" should be placed before third party imports "praisonaiagents.Agent", "praisonaiagents.guardrails.GuardrailResult"
(C0411)
[warning] 6-6: Unused import os
(W0611)
[warning] 11-11: Unused LLMGuardrail imported from praisonaiagents.guardrails
(W0611)
156-182: Improve exception handling specificity.The current broad exception handling could mask specific issues during testing.
Consider catching more specific exceptions or logging additional context:
- except Exception as e: + except (AssertionError, ImportError, AttributeError) as e: print(f"❌ Test failed: {e}") import traceback traceback.print_exc() return False + except Exception as e: + print(f"❌ Unexpected error: {e}") + import traceback + traceback.print_exc() + return False🧰 Tools
🪛 Pylint (3.3.7)
[convention] 159-159: Trailing whitespace
(C0303)
[convention] 164-164: Trailing whitespace
(C0303)
[convention] 167-167: Trailing whitespace
(C0303)
[convention] 173-173: Trailing whitespace
(C0303)
[convention] 180-180: Trailing whitespace
(C0303)
[convention] 182-182: Final newline missing
(C0304)
[warning] 168-168: Catching too general exception Exception
(W0718)
[convention] 170-170: Import outside toplevel (traceback)
(C0415)
[convention] 181-181: Constant name "success" doesn't conform to UPPER_CASE naming style
(C0103)
1-182: Address formatting issues.The file has extensive trailing whitespace issues that should be cleaned up.
Please clean up trailing whitespace on multiple lines and add a final newline at the end of the file. Consider using an auto-formatter or linter to maintain consistent formatting.
🧰 Tools
🪛 Ruff (0.11.9)
6-6:
osimported but unusedRemove unused import:
os(F401)
11-11:
praisonaiagents.guardrails.LLMGuardrailimported but unusedRemove unused import:
praisonaiagents.guardrails.LLMGuardrail(F401)
🪛 Pylint (3.3.7)
[convention] 18-18: Trailing whitespace
(C0303)
[convention] 26-26: Trailing whitespace
(C0303)
[convention] 30-30: Trailing whitespace
(C0303)
[convention] 34-34: Trailing whitespace
(C0303)
[convention] 42-42: Trailing whitespace
(C0303)
[convention] 49-49: Trailing whitespace
(C0303)
[convention] 53-53: Trailing whitespace
(C0303)
[convention] 56-56: Trailing whitespace
(C0303)
[convention] 60-60: Trailing whitespace
(C0303)
[convention] 64-64: Trailing whitespace
(C0303)
[convention] 71-71: Trailing whitespace
(C0303)
[convention] 86-86: Trailing whitespace
(C0303)
[convention] 92-92: Trailing whitespace
(C0303)
[convention] 97-97: Trailing whitespace
(C0303)
[convention] 101-101: Trailing whitespace
(C0303)
[convention] 109-109: Trailing whitespace
(C0303)
[convention] 116-116: Trailing whitespace
(C0303)
[convention] 120-120: Trailing whitespace
(C0303)
[convention] 121-121: Trailing whitespace
(C0303)
[convention] 127-127: Trailing whitespace
(C0303)
[convention] 131-131: Trailing whitespace
(C0303)
[convention] 138-138: Trailing whitespace
(C0303)
[convention] 145-145: Trailing whitespace
(C0303)
[convention] 152-152: Trailing whitespace
(C0303)
[convention] 159-159: Trailing whitespace
(C0303)
[convention] 164-164: Trailing whitespace
(C0303)
[convention] 167-167: Trailing whitespace
(C0303)
[convention] 173-173: Trailing whitespace
(C0303)
[convention] 180-180: Trailing whitespace
(C0303)
[convention] 182-182: Final newline missing
(C0304)
[warning] 50-50: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 61-61: Access to a protected member _process_guardrail of a client class
(W0212)
[convention] 73-73: Missing class docstring
(C0115)
[convention] 74-74: Missing function or method docstring
(C0116)
[warning] 74-74: Unused argument 'kwargs'
(W0613)
[refactor] 73-73: Too few public methods (1/2)
(R0903)
[warning] 117-117: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 128-128: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 168-168: Catching too general exception Exception
(W0718)
[convention] 170-170: Import outside toplevel (traceback)
(C0415)
[convention] 181-181: Constant name "success" doesn't conform to UPPER_CASE naming style
(C0103)
[convention] 12-12: standard import "typing.Tuple" should be placed before third party imports "praisonaiagents.Agent", "praisonaiagents.guardrails.GuardrailResult"
(C0411)
[warning] 6-6: Unused import os
(W0611)
[warning] 11-11: Unused LLMGuardrail imported from praisonaiagents.guardrails
(W0611)
src/praisonai-agents/simple_guardrail_test.py (2)
6-12: Remove unused import.The
osmodule is imported but never used.Apply this diff:
import sys -import os from typing import Tuple, Any🧰 Tools
🪛 Ruff (0.11.9)
7-7:
osimported but unusedRemove unused import:
os(F401)
🪛 Pylint (3.3.7)
[warning] 7-7: Unused import os
(W0611)
1-154: Address formatting issues.Similar to the other test file, this has multiple trailing whitespace issues and missing final newline.
Please clean up trailing whitespace throughout the file and add a final newline. Consider using an auto-formatter to maintain consistency.
🧰 Tools
🪛 Ruff (0.11.9)
7-7:
osimported but unusedRemove unused import:
os(F401)
🪛 Pylint (3.3.7)
[convention] 18-18: Trailing whitespace
(C0303)
[convention] 25-25: Trailing whitespace
(C0303)
[convention] 32-32: Trailing whitespace
(C0303)
[convention] 39-39: Trailing whitespace
(C0303)
[convention] 47-47: Trailing whitespace
(C0303)
[convention] 54-54: Trailing whitespace
(C0303)
[convention] 59-59: Trailing whitespace
(C0303)
[convention] 62-62: Trailing whitespace
(C0303)
[convention] 66-66: Trailing whitespace
(C0303)
[convention] 71-71: Trailing whitespace
(C0303)
[convention] 78-78: Trailing whitespace
(C0303)
[convention] 93-93: Trailing whitespace
(C0303)
[convention] 96-96: Trailing whitespace
(C0303)
[convention] 103-103: Trailing whitespace
(C0303)
[convention] 110-110: Trailing whitespace
(C0303)
[convention] 115-115: Trailing whitespace
(C0303)
[convention] 116-116: Trailing whitespace
(C0303)
[convention] 122-122: Trailing whitespace
(C0303)
[convention] 127-127: Trailing whitespace
(C0303)
[convention] 134-134: Trailing whitespace
(C0303)
[convention] 139-139: Trailing whitespace
(C0303)
[convention] 142-142: Trailing whitespace
(C0303)
[convention] 148-148: Trailing whitespace
(C0303)
[convention] 154-154: Final newline missing
(C0304)
[convention] 80-80: Missing class docstring
(C0115)
[convention] 81-81: Missing function or method docstring
(C0116)
[warning] 81-81: Unused argument 'kwargs'
(W0613)
[refactor] 80-80: Too few public methods (1/2)
(R0903)
[warning] 143-143: Catching too general exception Exception
(W0718)
[convention] 145-145: Import outside toplevel (traceback)
(C0415)
[convention] 153-153: Constant name "success" doesn't conform to UPPER_CASE naming style
(C0103)
[warning] 7-7: Unused import os
(W0611)
src/praisonai-agents/CLAUDE.md (1)
96-97: Fix minor language issues.LanguageTool detected some minor grammatical issues that should be corrected.
Apply these fixes:
-- **Knowledge** (`praisonaiagents/knowledge/`): Document processing with chunking - - Chunking strategies via `chonkie` library +- **Knowledge** (`praisonaiagents/knowledge/`): Document processing with chunking + - Chunking strategies via `chonkie` library-The project uses example-driven testing with 100+ test files in `tests/` directory. +The project uses example-driven testing with 100+ test files in the `tests/` directory.🧰 Tools
🪛 LanguageTool
[duplication] ~96-~96: Possible typo: you repeated a word.
Context: .../knowledge/): Document processing with chunking - Chunking strategies viachonkie` library - Em...(ENGLISH_WORD_REPEAT_RULE)
src/praisonai-agents/praisonaiagents/task/task.py (2)
155-200: Clean up trailing whitespaceMultiple lines have trailing whitespace that should be removed.
- return - + return +- raise ValueError("Guardrail function must accept exactly one parameter (TaskOutput)") - + raise ValueError("Guardrail function must accept exactly one parameter (TaskOutput)") +- - self._guardrail_fn = self.guardrail + + self._guardrail_fn = self.guardrail🧰 Tools
🪛 Pylint (3.3.7)
[convention] 160-160: Trailing whitespace
(C0303)
[convention] 169-169: Line too long (101/100)
(C0301)
[convention] 170-170: Trailing whitespace
(C0303)
[convention] 189-189: Trailing whitespace
(C0303)
[convention] 193-193: Import outside toplevel (guardrails.LLMGuardrail)
(C0415)
427-455: Clean up formatting and use lazy loggingThe method has several formatting issues and should use lazy logging.
def _process_guardrail(self, task_output: TaskOutput): """Process the guardrail validation for a task output. - + Args: task_output: The task output to validate - + Returns: GuardrailResult: The result of the guardrail validation """ from ..guardrails import GuardrailResult - + if not self._guardrail_fn: return GuardrailResult(success=True, result=task_output) - + try: # Call the guardrail function result = self._guardrail_fn(task_output) - + # Convert the result to a GuardrailResult return GuardrailResult.from_tuple(result) - + except Exception as e: - logger.error(f"Task {self.id}: Error in guardrail validation: {e}") + logger.error("Task %s: Error in guardrail validation: %s", self.id, e) # On error, return failure return GuardrailResult( success=False, result=None, error=f"Guardrail validation error: {str(e)}" ) +🧰 Tools
🪛 Pylint (3.3.7)
[convention] 437-437: Trailing whitespace
(C0303)
[convention] 440-440: Trailing whitespace
(C0303)
[convention] 444-444: Trailing whitespace
(C0303)
[convention] 447-447: Trailing whitespace
(C0303)
[convention] 455-455: Final newline missing
(C0304)
[convention] 436-436: Import outside toplevel (guardrails.GuardrailResult)
(C0415)
[warning] 448-448: Catching too general exception Exception
(W0718)
[warning] 449-449: Use lazy % formatting in logging functions
(W1203)
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (14)
.github/workflows/python-package.yml(1 hunks)src/praisonai-agents/.cursorrules(1 hunks)src/praisonai-agents/CLAUDE.md(1 hunks)src/praisonai-agents/agent_guardrails_example.py(1 hunks)src/praisonai-agents/guardrails_example.py(1 hunks)src/praisonai-agents/praisonaiagents/__init__.py(2 hunks)src/praisonai-agents/praisonaiagents/guardrails/__init__.py(1 hunks)src/praisonai-agents/praisonaiagents/guardrails/guardrail_result.py(1 hunks)src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py(1 hunks)src/praisonai-agents/praisonaiagents/task/task.py(6 hunks)src/praisonai-agents/sequence.py(1 hunks)src/praisonai-agents/simple_guardrail_test.py(1 hunks)src/praisonai-agents/test_guardrails.py(1 hunks)src/praisonai-agents/tests/guardrails_example.py(1 hunks)
🧰 Additional context used
🧬 Code Graph Analysis (2)
src/praisonai-agents/praisonaiagents/guardrails/__init__.py (2)
src/praisonai-agents/praisonaiagents/guardrails/guardrail_result.py (1)
GuardrailResult(13-43)src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py (1)
LLMGuardrail(14-88)
src/praisonai-agents/praisonaiagents/__init__.py (2)
src/praisonai-agents/praisonaiagents/guardrails/guardrail_result.py (1)
GuardrailResult(13-43)src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py (1)
LLMGuardrail(14-88)
🪛 Pylint (3.3.7)
src/praisonai-agents/praisonaiagents/guardrails/__init__.py
[convention] 11-11: Final newline missing
(C0304)
src/praisonai-agents/agent_guardrails_example.py
[convention] 18-18: Trailing whitespace
(C0303)
[convention] 1-1: Missing module docstring
(C0114)
[convention] 7-7: Missing function or method docstring
(C0116)
[convention] 13-13: Missing function or method docstring
(C0116)
[error] 14-17: Unexpected keyword argument 'guardrail' in constructor call
(E1123)
[warning] 4-4: Unused Task imported from praisonaiagents
(W0611)
src/praisonai-agents/guardrails_example.py
[convention] 27-27: Trailing whitespace
(C0303)
[convention] 31-31: Trailing whitespace
(C0303)
[convention] 34-34: Trailing whitespace
(C0303)
[convention] 37-37: Trailing whitespace
(C0303)
[convention] 40-40: Trailing whitespace
(C0303)
[convention] 48-48: Trailing whitespace
(C0303)
[convention] 56-56: Trailing whitespace
(C0303)
[convention] 59-59: Trailing whitespace
(C0303)
[convention] 68-68: Trailing whitespace
(C0303)
[convention] 71-71: Trailing whitespace
(C0303)
[convention] 87-87: Trailing whitespace
(C0303)
[convention] 92-92: Trailing whitespace
(C0303)
[convention] 99-99: Trailing whitespace
(C0303)
[convention] 104-104: Trailing whitespace
(C0303)
[convention] 107-107: Trailing whitespace
(C0303)
[convention] 113-113: Line too long (121/100)
(C0301)
[convention] 116-116: Trailing whitespace
(C0303)
[convention] 118-118: Line too long (138/100)
(C0301)
[convention] 120-120: Trailing whitespace
(C0303)
[convention] 123-123: Trailing whitespace
(C0303)
[convention] 130-130: Trailing whitespace
(C0303)
[convention] 133-133: Trailing whitespace
(C0303)
[convention] 140-140: Trailing whitespace
(C0303)
[convention] 143-143: Trailing whitespace
(C0303)
[convention] 154-154: Final newline missing
(C0304)
[warning] 88-88: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 100-100: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 132-132: Access to a protected member _guardrail_fn of a client class
(W0212)
[warning] 141-141: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 9-9: Unused import sys
(W0611)
[warning] 10-10: Unused import os
(W0611)
src/praisonai-agents/tests/guardrails_example.py
[convention] 30-30: Trailing whitespace
(C0303)
[convention] 34-34: Trailing whitespace
(C0303)
[convention] 37-37: Trailing whitespace
(C0303)
[convention] 40-40: Trailing whitespace
(C0303)
[convention] 43-43: Trailing whitespace
(C0303)
[convention] 51-51: Trailing whitespace
(C0303)
[convention] 59-59: Trailing whitespace
(C0303)
[convention] 62-62: Trailing whitespace
(C0303)
[convention] 71-71: Trailing whitespace
(C0303)
[convention] 74-74: Trailing whitespace
(C0303)
[convention] 90-90: Trailing whitespace
(C0303)
[convention] 95-95: Trailing whitespace
(C0303)
[convention] 102-102: Trailing whitespace
(C0303)
[convention] 107-107: Trailing whitespace
(C0303)
[convention] 110-110: Trailing whitespace
(C0303)
[convention] 116-116: Line too long (121/100)
(C0301)
[convention] 119-119: Trailing whitespace
(C0303)
[convention] 121-121: Line too long (138/100)
(C0301)
[convention] 123-123: Trailing whitespace
(C0303)
[convention] 126-126: Trailing whitespace
(C0303)
[convention] 133-133: Trailing whitespace
(C0303)
[convention] 136-136: Trailing whitespace
(C0303)
[convention] 143-143: Trailing whitespace
(C0303)
[convention] 146-146: Trailing whitespace
(C0303)
[convention] 157-157: Final newline missing
(C0304)
[error] 16-16: Unable to import 'praisonaiagents'
(E0401)
[convention] 16-16: Import "from praisonaiagents import Agent, Task, TaskOutput" should be placed at the top of the module
(C0413)
[warning] 91-91: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 103-103: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 135-135: Access to a protected member _guardrail_fn of a client class
(W0212)
[warning] 144-144: Access to a protected member _process_guardrail of a client class
(W0212)
src/praisonai-agents/sequence.py
[convention] 11-11: Final newline missing
(C0304)
[convention] 1-1: Missing module docstring
(C0114)
[convention] 2-2: standard import "os" should be placed before third party import "praisonaiagents.Agent"
(C0411)
[warning] 2-2: Unused import os
(W0611)
src/praisonai-agents/simple_guardrail_test.py
[convention] 18-18: Trailing whitespace
(C0303)
[convention] 25-25: Trailing whitespace
(C0303)
[convention] 32-32: Trailing whitespace
(C0303)
[convention] 39-39: Trailing whitespace
(C0303)
[convention] 47-47: Trailing whitespace
(C0303)
[convention] 54-54: Trailing whitespace
(C0303)
[convention] 59-59: Trailing whitespace
(C0303)
[convention] 62-62: Trailing whitespace
(C0303)
[convention] 66-66: Trailing whitespace
(C0303)
[convention] 71-71: Trailing whitespace
(C0303)
[convention] 78-78: Trailing whitespace
(C0303)
[convention] 93-93: Trailing whitespace
(C0303)
[convention] 96-96: Trailing whitespace
(C0303)
[convention] 103-103: Trailing whitespace
(C0303)
[convention] 110-110: Trailing whitespace
(C0303)
[convention] 115-115: Trailing whitespace
(C0303)
[convention] 116-116: Trailing whitespace
(C0303)
[convention] 122-122: Trailing whitespace
(C0303)
[convention] 127-127: Trailing whitespace
(C0303)
[convention] 134-134: Trailing whitespace
(C0303)
[convention] 139-139: Trailing whitespace
(C0303)
[convention] 142-142: Trailing whitespace
(C0303)
[convention] 148-148: Trailing whitespace
(C0303)
[convention] 154-154: Final newline missing
(C0304)
[convention] 80-80: Missing class docstring
(C0115)
[convention] 81-81: Missing function or method docstring
(C0116)
[warning] 81-81: Unused argument 'kwargs'
(W0613)
[refactor] 80-80: Too few public methods (1/2)
(R0903)
[warning] 143-143: Catching too general exception Exception
(W0718)
[convention] 145-145: Import outside toplevel (traceback)
(C0415)
[convention] 153-153: Constant name "success" doesn't conform to UPPER_CASE naming style
(C0103)
[warning] 7-7: Unused import os
(W0611)
src/praisonai-agents/praisonaiagents/guardrails/guardrail_result.py
[convention] 15-15: Trailing whitespace
(C0303)
[convention] 17-17: Line too long (108/100)
(C0301)
[convention] 19-19: Trailing whitespace
(C0303)
[convention] 31-31: Trailing whitespace
(C0303)
[convention] 43-43: Final newline missing
(C0304)
[error] 9-9: Unable to import 'pydantic'
(E0401)
[refactor] 32-43: Unnecessary "else" after "return", remove the "else" and de-indent the code inside it
(R1705)
[refactor] 13-13: Too few public methods (1/2)
(R0903)
src/praisonai-agents/test_guardrails.py
[convention] 18-18: Trailing whitespace
(C0303)
[convention] 26-26: Trailing whitespace
(C0303)
[convention] 30-30: Trailing whitespace
(C0303)
[convention] 34-34: Trailing whitespace
(C0303)
[convention] 42-42: Trailing whitespace
(C0303)
[convention] 49-49: Trailing whitespace
(C0303)
[convention] 53-53: Trailing whitespace
(C0303)
[convention] 56-56: Trailing whitespace
(C0303)
[convention] 60-60: Trailing whitespace
(C0303)
[convention] 64-64: Trailing whitespace
(C0303)
[convention] 71-71: Trailing whitespace
(C0303)
[convention] 86-86: Trailing whitespace
(C0303)
[convention] 92-92: Trailing whitespace
(C0303)
[convention] 97-97: Trailing whitespace
(C0303)
[convention] 101-101: Trailing whitespace
(C0303)
[convention] 109-109: Trailing whitespace
(C0303)
[convention] 116-116: Trailing whitespace
(C0303)
[convention] 120-120: Trailing whitespace
(C0303)
[convention] 121-121: Trailing whitespace
(C0303)
[convention] 127-127: Trailing whitespace
(C0303)
[convention] 131-131: Trailing whitespace
(C0303)
[convention] 138-138: Trailing whitespace
(C0303)
[convention] 145-145: Trailing whitespace
(C0303)
[convention] 152-152: Trailing whitespace
(C0303)
[convention] 159-159: Trailing whitespace
(C0303)
[convention] 164-164: Trailing whitespace
(C0303)
[convention] 167-167: Trailing whitespace
(C0303)
[convention] 173-173: Trailing whitespace
(C0303)
[convention] 180-180: Trailing whitespace
(C0303)
[convention] 182-182: Final newline missing
(C0304)
[warning] 50-50: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 61-61: Access to a protected member _process_guardrail of a client class
(W0212)
[convention] 73-73: Missing class docstring
(C0115)
[convention] 74-74: Missing function or method docstring
(C0116)
[warning] 74-74: Unused argument 'kwargs'
(W0613)
[refactor] 73-73: Too few public methods (1/2)
(R0903)
[warning] 117-117: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 128-128: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 168-168: Catching too general exception Exception
(W0718)
[convention] 170-170: Import outside toplevel (traceback)
(C0415)
[convention] 181-181: Constant name "success" doesn't conform to UPPER_CASE naming style
(C0103)
[convention] 12-12: standard import "typing.Tuple" should be placed before third party imports "praisonaiagents.Agent", "praisonaiagents.guardrails.GuardrailResult"
(C0411)
[warning] 6-6: Unused import os
(W0611)
[warning] 11-11: Unused LLMGuardrail imported from praisonaiagents.guardrails
(W0611)
src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py
[convention] 16-16: Trailing whitespace
(C0303)
[convention] 27-27: Trailing whitespace
(C0303)
[convention] 41-41: Trailing whitespace
(C0303)
[convention] 70-70: Trailing whitespace
(C0303)
[convention] 73-73: Trailing whitespace
(C0303)
[convention] 84-84: Trailing whitespace
(C0303)
[convention] 88-88: Final newline missing
(C0304)
[error] 10-10: Unable to import 'pydantic'
(E0401)
[warning] 85-85: Catching too general exception Exception
(W0718)
[warning] 68-68: Use lazy % formatting in logging functions
(W1203)
[refactor] 74-83: Unnecessary "elif" after "return", remove the leading "el" from "elif"
(R1705)
[warning] 82-82: Use lazy % formatting in logging functions
(W1203)
[warning] 86-86: Use lazy % formatting in logging functions
(W1203)
[refactor] 14-14: Too few public methods (1/2)
(R0903)
[warning] 9-9: Unused Optional imported from typing
(W0611)
[warning] 10-10: Unused BaseModel imported from pydantic
(W0611)
src/praisonai-agents/praisonaiagents/task/task.py
[convention] 4-4: Line too long (116/100)
(C0301)
[warning] 4-4: Unused Literal imported from typing
(W0611)
[convention] 44-44: Line too long (110/100)
(C0301)
[convention] 160-160: Trailing whitespace
(C0303)
[convention] 169-169: Line too long (101/100)
(C0301)
[convention] 170-170: Trailing whitespace
(C0303)
[convention] 189-189: Trailing whitespace
(C0303)
[convention] 193-193: Import outside toplevel (guardrails.LLMGuardrail)
(C0415)
[convention] 257-257: Trailing whitespace
(C0303)
[convention] 259-259: Line too long (154/100)
(C0301)
[convention] 260-260: Line too long (105/100)
(C0301)
[convention] 263-263: Trailing whitespace
(C0303)
[convention] 272-272: Trailing whitespace
(C0303)
[warning] 274-274: Catching too general exception Exception
(W0718)
[warning] 253-256: Raising too general exception: Exception
(W0719)
[warning] 259-259: Use lazy % formatting in logging functions
(W1203)
[warning] 273-273: Use lazy % formatting in logging functions
(W1203)
[warning] 275-275: Use lazy % formatting in logging functions
(W1203)
[convention] 437-437: Trailing whitespace
(C0303)
[convention] 440-440: Trailing whitespace
(C0303)
[convention] 444-444: Trailing whitespace
(C0303)
[convention] 447-447: Trailing whitespace
(C0303)
[convention] 455-455: Final newline missing
(C0304)
[convention] 436-436: Import outside toplevel (guardrails.GuardrailResult)
(C0415)
[warning] 448-448: Catching too general exception Exception
(W0718)
[warning] 449-449: Use lazy % formatting in logging functions
(W1203)
🪛 Ruff (0.11.9)
src/praisonai-agents/agent_guardrails_example.py
4-4: praisonaiagents.Task imported but unused
Remove unused import: praisonaiagents.Task
(F401)
src/praisonai-agents/guardrails_example.py
9-9: sys imported but unused
Remove unused import: sys
(F401)
10-10: os imported but unused
Remove unused import: os
(F401)
src/praisonai-agents/sequence.py
2-2: os imported but unused
Remove unused import: os
(F401)
src/praisonai-agents/simple_guardrail_test.py
7-7: os imported but unused
Remove unused import: os
(F401)
src/praisonai-agents/test_guardrails.py
6-6: os imported but unused
Remove unused import: os
(F401)
11-11: praisonaiagents.guardrails.LLMGuardrail imported but unused
Remove unused import: praisonaiagents.guardrails.LLMGuardrail
(F401)
src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py
9-9: typing.Optional imported but unused
Remove unused import: typing.Optional
(F401)
10-10: pydantic.BaseModel imported but unused
Remove unused import: pydantic.BaseModel
(F401)
src/praisonai-agents/praisonaiagents/task/task.py
4-4: typing.Literal imported but unused
Remove unused import: typing.Literal
(F401)
🪛 LanguageTool
src/praisonai-agents/CLAUDE.md
[duplication] ~96-~96: Possible typo: you repeated a word.
Context: .../knowledge/): Document processing with chunking - Chunking strategies via chonkie` library - Em...
(ENGLISH_WORD_REPEAT_RULE)
[uncategorized] ~202-~202: You might be missing the article “the” here.
Context: ...-driven testing with 100+ test files in tests/ directory. Each test file demons...
(AI_EN_LECTOR_MISSING_DETERMINER_THE)
⏰ Context from checks skipped due to timeout of 90000ms (4)
- GitHub Check: test-core (3.11)
- GitHub Check: quick-test
- GitHub Check: test-core (3.11)
- GitHub Check: quick-test
🔇 Additional comments (20)
.github/workflows/python-package.yml (1)
68-68:Details
✅ Verification successful
Verify custom test runner exists and pattern validity.
The change from direct pytest to a custom test runner with 'fast' pattern optimization looks good for improving CI performance. However, ensure the test runner script exists and the pattern is properly configured.
🏁 Script executed:
#!/bin/bash # Description: Verify the custom test runner exists and check its pattern handling # Expected: test_runner.py should exist and handle --pattern fast argument # Check if test runner script exists fd test_runner.py --type f # Look for pattern handling in the test runner rg -A 10 -B 5 "pattern" --type pyLength of output: 68029
Confirmed: custom test runner exists and handles 'fast' pattern
The workflow change is valid—
src/praisonai/tests/test_runner.pyis present and explicitly supports thefastpattern.•
.github/workflows/python-package.yml(line 68):
cd src/praisonai && python tests/test_runner.py --pattern fast
•src/praisonai/tests/test_runner.py:
- Defines--patternchoices including"fast"
- Contains a branch forpattern == "fast"that runs unit tests excluding slow testsAll set to improve CI performance.
src/praisonai-agents/praisonaiagents/__init__.py (2)
15-15: LGTM! Proper integration of guardrail components.The import correctly exposes the new guardrail functionality from the dedicated module.
60-61: LGTM! Public API properly updated.The guardrail components are correctly added to
__all__making them accessible when importing the package.src/praisonai-agents/.cursorrules (1)
8-8: LGTM! Simplified and focused guidance.The updated rule provides clear, actionable guidance for code integration while removing unnecessary complexity.
src/praisonai-agents/agent_guardrails_example.py (1)
4-4:Details
❓ Verification inconclusive
Remove unused import and verify Agent constructor API.
The
Taskimport is unused and should be removed. Additionally, static analysis indicates theguardrailparameter might not be supported in theAgentconstructor.Apply this diff to remove the unused import:
-from praisonaiagents import Agent, Task, TaskOutput +from praisonaiagents import Agent, TaskOutputVerify that the Agent constructor supports the
guardrailparameter:
🏁 Script executed:
#!/bin/bash # Description: Check if Agent constructor accepts guardrail parameter # Expected: Find guardrail parameter in Agent.__init__ method ast-grep --pattern $'class Agent: $$$ def __init__($$$, guardrail$$$): $$$' # Alternative: Search for guardrail in Agent class rg -A 10 -B 5 "class Agent" --type pyLength of output: 7890
🏁 Script executed:
#!/bin/bash # 1. Show the Agent class definition and its __init__ signature rg -n "class Agent" -A5 -n src/praisonai-agents/praisonaiagents/agent/agent.py rg -n "def __init__" -A5 -n src/praisonai-agents/praisonaiagents/agent/agent.py # 2. Show how Agent is instantiated in the guardrails example rg -n "Agent\(" -n src/praisonai-agents/praisonaiagents/agent_guardrails_example.pyLength of output: 1152
#!/bin/bash # Locate the guardrails example file file=$(fd agent_guardrails_example.py) echo "Found file: $file" # Display the first 100 lines of the file sed -n '1,100p' "$file" # Check for Task usage echo; echo "Occurrences of 'Task':" rg -n "\bTask\b" "$file" || echo "No Task usage found." # Check for guardrail parameter in Agent instantiation echo; echo "Occurrences of 'guardrail':" rg -n "guardrail" "$file" || echo "No guardrail usage found."
#!/bin/bash # Locate the guardrails example file file=$(fd agent_guardrails_example.py) echo "Found file: $file" # Abort if file not found if [[ -z "$file" ]]; then echo "Error: agent_guardrails_example.py not found" >&2 exit 1 fi # Show first 20 lines to inspect imports echo "=== Top of $file ===" head -n 20 "$file" # Check for Task usage beyond import echo; echo "=== 'Task' occurrences ===" grep -n "\bTask\b" "$file" || echo "No Task usage found." # Check how Agent is instantiated and if 'guardrail' is passed echo; echo "=== 'Agent(' occurrences ===" grep -n "Agent\s*(" "$file" || echo "No Agent instantiation found." echo; echo "=== 'guardrail' occurrences ===" grep -n "guardrail" "$file" || echo "No guardrail parameter usage found."
Verify unused Task import and Agent constructor guardrail support
Please confirm the following before merging:
- In
src/praisonai-agents/agent_guardrails_example.py, theTaskimport appears unused—remove it if it truly isn’t referenced.- Inspect the
Agentclass (e.g., insrc/praisonai-agents/praisonaiagents/agent/agent.py) to verify whether its__init__accepts aguardrailparameter. If not, update the example to use supported constructor parameters.🧰 Tools
🪛 Ruff (0.11.9)
4-4:
praisonaiagents.Taskimported but unusedRemove unused import:
praisonaiagents.Task(F401)
🪛 Pylint (3.3.7)
[warning] 4-4: Unused Task imported from praisonaiagents
(W0611)
src/praisonai-agents/guardrails_example.py (2)
16-44: LGTM! Well-implemented validation function.The
email_validatorfunction demonstrates good guardrail patterns with comprehensive validation logic and clear error messages.🧰 Tools
🪛 Pylint (3.3.7)
[convention] 27-27: Trailing whitespace
(C0303)
[convention] 31-31: Trailing whitespace
(C0303)
[convention] 34-34: Trailing whitespace
(C0303)
[convention] 37-37: Trailing whitespace
(C0303)
[convention] 40-40: Trailing whitespace
(C0303)
88-104:Details
❌ Incorrect review comment
Verify public API for guardrail processing.
The code uses protected methods
_process_guardrailwhich suggests this is testing internal APIs. Consider using public APIs if available.
🏁 Script executed:
#!/bin/bash # Description: Check for public guardrail processing methods in Task class # Expected: Find public methods for guardrail processing ast-grep --pattern $'class Task: $$$ def process_guardrail($$$): $$$' # Also check for execute or run methods that might handle guardrails rg -A 5 "def (execute|run|process)" --type py | grep -A 5 -B 5 guardrailLength of output: 1196
Ignore suggestion: no public guardrail API exists
After inspecting
src/praisonai-agents/praisonaiagents/task/task.py, there is no publicprocess_guardrail(only the protected_process_guardrail), and guardrail logic is invoked internally inexecute_callback/execute_callback_sync. You can continue using_process_guardrailfor testing or, if you’d prefer a public entrypoint, consider adding a thin wrapper around it in theTaskclass.Likely an incorrect or invalid review comment.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 92-92: Trailing whitespace
(C0303)
[convention] 99-99: Trailing whitespace
(C0303)
[convention] 104-104: Trailing whitespace
(C0303)
[warning] 88-88: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 100-100: Access to a protected member _process_guardrail of a client class
(W0212)
src/praisonai-agents/praisonaiagents/guardrails/llm_guardrail.py (2)
14-26: LGTM! Well-designed class initialization.Good design with clear parameter documentation and proper logger setup.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 16-16: Trailing whitespace
(C0303)
[refactor] 14-14: Too few public methods (1/2)
(R0903)
58-69: Excellent LLM interface abstraction.The multiple interface support (
chat,get_response, callable) provides good flexibility for different LLM implementations.🧰 Tools
🪛 Pylint (3.3.7)
[warning] 68-68: Use lazy % formatting in logging functions
(W1203)
src/praisonai-agents/praisonaiagents/guardrails/guardrail_result.py (1)
13-18: LGTM! Well-designed result class with clear structure.The
GuardrailResultclass provides a clean interface for guardrail validation outcomes with proper typing and documentation.🧰 Tools
🪛 Pylint (3.3.7)
[convention] 15-15: Trailing whitespace
(C0303)
[convention] 17-17: Line too long (108/100)
(C0301)
[refactor] 13-13: Too few public methods (1/2)
(R0903)
src/praisonai-agents/test_guardrails.py (3)
15-65: Well-structured function guardrail test.The test logic is comprehensive and correctly validates both passing and failing scenarios.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 18-18: Trailing whitespace
(C0303)
[convention] 26-26: Trailing whitespace
(C0303)
[convention] 30-30: Trailing whitespace
(C0303)
[convention] 34-34: Trailing whitespace
(C0303)
[convention] 42-42: Trailing whitespace
(C0303)
[convention] 49-49: Trailing whitespace
(C0303)
[convention] 53-53: Trailing whitespace
(C0303)
[convention] 56-56: Trailing whitespace
(C0303)
[convention] 60-60: Trailing whitespace
(C0303)
[convention] 64-64: Trailing whitespace
(C0303)
[warning] 50-50: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 61-61: Access to a protected member _process_guardrail of a client class
(W0212)
50-62: Consider testing via public API.The tests are accessing the protected method
_process_guardrail. While this may be intentional for testing internal behavior, consider whether this functionality should be exposed through a public API.Are there plans to expose guardrail processing through a public method, or is direct testing of the protected method the intended approach?
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 53-53: Trailing whitespace
(C0303)
[convention] 56-56: Trailing whitespace
(C0303)
[convention] 60-60: Trailing whitespace
(C0303)
[warning] 50-50: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 61-61: Access to a protected member _process_guardrail of a client class
(W0212)
73-92: Excellent mock LLM implementation.The MockLLM class effectively simulates LLM behavior by parsing the structured prompt format, making the tests reliable and deterministic.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 86-86: Trailing whitespace
(C0303)
[convention] 92-92: Trailing whitespace
(C0303)
[convention] 73-73: Missing class docstring
(C0115)
[convention] 74-74: Missing function or method docstring
(C0116)
[warning] 74-74: Unused argument 'kwargs'
(W0613)
[refactor] 73-73: Too few public methods (1/2)
(R0903)
src/praisonai-agents/simple_guardrail_test.py (3)
15-72: Excellent isolated testing approach.This test design is well-structured, testing guardrail logic in isolation without requiring full Task integration. The approach makes tests more focused and easier to debug.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 18-18: Trailing whitespace
(C0303)
[convention] 25-25: Trailing whitespace
(C0303)
[convention] 32-32: Trailing whitespace
(C0303)
[convention] 39-39: Trailing whitespace
(C0303)
[convention] 47-47: Trailing whitespace
(C0303)
[convention] 54-54: Trailing whitespace
(C0303)
[convention] 59-59: Trailing whitespace
(C0303)
[convention] 62-62: Trailing whitespace
(C0303)
[convention] 66-66: Trailing whitespace
(C0303)
[convention] 71-71: Trailing whitespace
(C0303)
97-102: Good direct testing of LLMGuardrail class.Testing the
LLMGuardrailclass directly provides good coverage of the guardrail callable interface and validates the integration with mock LLMs.
80-96: Well-implemented mock for LLM testing.The MockLLM correctly parses the structured prompt format used by LLMGuardrail, ensuring reliable test results.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 93-93: Trailing whitespace
(C0303)
[convention] 96-96: Trailing whitespace
(C0303)
[convention] 80-80: Missing class docstring
(C0115)
[convention] 81-81: Missing function or method docstring
(C0116)
[warning] 81-81: Unused argument 'kwargs'
(W0613)
[refactor] 80-80: Too few public methods (1/2)
(R0903)
src/praisonai-agents/CLAUDE.md (3)
73-77: Excellent integration of guardrails documentation.The documentation clearly explains the new guardrails system with both function-based and LLM-based approaches, including retry logic and compatibility notes.
135-164: Comprehensive guardrails usage examples.The code examples effectively demonstrate both function-based and LLM-based guardrail patterns, providing clear guidance for developers.
1-204: Outstanding comprehensive documentation.This documentation file provides excellent coverage of the entire system architecture, including the newly introduced guardrails functionality. It serves as an effective guide for both developers and AI agents working with the codebase.
🧰 Tools
🪛 LanguageTool
[duplication] ~96-~96: Possible typo: you repeated a word.
Context: .../knowledge/): Document processing with chunking - Chunking strategies viachonkie` library - Em...(ENGLISH_WORD_REPEAT_RULE)
[uncategorized] ~202-~202: You might be missing the article “the” here.
Context: ...-driven testing with 100+ test files intests/directory. Each test file demons...(AI_EN_LECTOR_MISSING_DETERMINER_THE)
src/praisonai-agents/praisonaiagents/task/task.py (1)
193-193:Details
✅ Verification successful
Verify guardrail module imports
The implementation imports
LLMGuardrailandGuardrailResultfrom..guardrails. Let's verify these classes exist and are properly exported.Also applies to: 436-436
🏁 Script executed:
#!/bin/bash # Description: Verify that the guardrail classes are properly defined and exported # Check if the guardrails module exists and exports the required classes echo "Checking for guardrails module and exports..." # Look for the guardrails module fd -t f "guardrail" --exec echo "Found: {}" # Check for LLMGuardrail class definition echo -e "\nSearching for LLMGuardrail class..." ast-grep --pattern 'class LLMGuardrail' # Check for GuardrailResult class definition echo -e "\nSearching for GuardrailResult class..." ast-grep --pattern 'class GuardrailResult' # Check if these are exported from __init__.py echo -e "\nChecking exports in guardrails __init__.py..." fd "__init__.py" -p "guardrails" --exec cat {}Length of output: 12396
🏁 Script executed:
#!/bin/bash # Locate and display the guardrails package __init__.py to verify exports echo "Listing all __init__.py files:" fd "__init__.py" -t f echo -e "\nFiltering for the guardrails package __init__.py:" fd "__init__.py" -t f | grep "guardrails" echo -e "\nContents of guardrails/__init__.py:" fd "__init__.py" -t f | grep "guardrails/__init__.py" | xargs -I {} sed -n '1,200p' {}Length of output: 2041
Guardrail imports verified
Theguardrailspackage’s__init__.pyexports bothLLMGuardrailandGuardrailResult, so thefrom ..guardrails import LLMGuardrail(and related import ofGuardrailResult) intask.pyis correct.🧰 Tools
🪛 Pylint (3.3.7)
[convention] 193-193: Import outside toplevel (guardrails.LLMGuardrail)
(C0415)
| from praisonaiagents import Agent, MCP | ||
| import os | ||
|
|
||
| sequential_agent = Agent( | ||
| instructions="""You are a helpful assistant that can break down complex problems. | ||
| Use the available tools when relevant to perform step-by-step analysis.""", | ||
| llm="openai/gpt-4o-mini", | ||
| tools=MCP("npx -y @modelcontextprotocol/server-sequential-thinking") | ||
| ) | ||
|
|
||
| sequential_agent.start("Break down the process of making a cup of tea") No newline at end of file |
There was a problem hiding this comment.
Address code quality issues.
The agent implementation looks good functionally, but several code quality issues need fixing based on static analysis.
Apply this diff to fix all issues:
+"""
+Sequential thinking agent example using MCP tools.
+
+This module demonstrates how to create an agent that breaks down complex problems
+using step-by-step analysis with the Model Context Protocol (MCP).
+"""
+
from praisonaiagents import Agent, MCP
-import os
sequential_agent = Agent(
instructions="""You are a helpful assistant that can break down complex problems.
Use the available tools when relevant to perform step-by-step analysis.""",
llm="openai/gpt-4o-mini",
tools=MCP("npx -y @modelcontextprotocol/server-sequential-thinking")
)
-sequential_agent.start("Break down the process of making a cup of tea")
+sequential_agent.start("Break down the process of making a cup of tea")
+This fixes:
- Adds module docstring
- Removes unused
osimport - Adds final newline
- Maintains proper import order
📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| from praisonaiagents import Agent, MCP | |
| import os | |
| sequential_agent = Agent( | |
| instructions="""You are a helpful assistant that can break down complex problems. | |
| Use the available tools when relevant to perform step-by-step analysis.""", | |
| llm="openai/gpt-4o-mini", | |
| tools=MCP("npx -y @modelcontextprotocol/server-sequential-thinking") | |
| ) | |
| sequential_agent.start("Break down the process of making a cup of tea") | |
| """ | |
| Sequential thinking agent example using MCP tools. | |
| This module demonstrates how to create an agent that breaks down complex problems | |
| using step-by-step analysis with the Model Context Protocol (MCP). | |
| """ | |
| from praisonaiagents import Agent, MCP | |
| sequential_agent = Agent( | |
| instructions="""You are a helpful assistant that can break down complex problems. | |
| Use the available tools when relevant to perform step-by-step analysis.""", | |
| llm="openai/gpt-4o-mini", | |
| tools=MCP("npx -y @modelcontextprotocol/server-sequential-thinking") | |
| ) | |
| sequential_agent.start("Break down the process of making a cup of tea") | |
🧰 Tools
🪛 Ruff (0.11.9)
2-2: os imported but unused
Remove unused import: os
(F401)
🪛 Pylint (3.3.7)
[convention] 11-11: Final newline missing
(C0304)
[convention] 1-1: Missing module docstring
(C0114)
[convention] 2-2: standard import "os" should be placed before third party import "praisonaiagents.Agent"
(C0411)
[warning] 2-2: Unused import os
(W0611)
🤖 Prompt for AI Agents
In src/praisonai-agents/sequence.py lines 1 to 11, fix code quality issues by
adding a module-level docstring at the top describing the purpose of the file,
removing the unused import of the os module, ensuring imports are ordered
properly (standard libraries first, then third-party, then local imports), and
adding a final newline at the end of the file.
| #!/usr/bin/env python3 | ||
| """ | ||
| Example demonstrating guardrails functionality in PraisonAI Agents. | ||
|
|
||
| This example shows both function-based and LLM-based guardrails | ||
| for validating task outputs. | ||
| """ | ||
|
|
||
| import sys | ||
| import os | ||
| from typing import Tuple, Any | ||
|
|
||
| # Add project to path | ||
| sys.path.insert(0, os.path.abspath('..')) | ||
|
|
||
| from praisonaiagents import Agent, Task, TaskOutput | ||
|
|
||
|
|
||
| def email_validator(task_output: TaskOutput) -> Tuple[bool, Any]: | ||
| """ | ||
| Function-based guardrail to validate email content. | ||
|
|
||
| Args: | ||
| task_output: The task output to validate | ||
|
|
||
| Returns: | ||
| Tuple of (success, result_or_error) | ||
| """ | ||
| content = task_output.raw.lower() | ||
|
|
||
| # Check for required email components | ||
| if "subject:" not in content: | ||
| return False, "Email must include a subject line" | ||
|
|
||
| if "dear" not in content and "hello" not in content: | ||
| return False, "Email must include a proper greeting" | ||
|
|
||
| if len(content) < 50: | ||
| return False, "Email content is too short" | ||
|
|
||
| if "error" in content or "problem" in content: | ||
| return False, "Email should not mention errors or problems" | ||
|
|
||
| return True, task_output | ||
|
|
||
|
|
||
| def main(): | ||
| """Run the guardrails example.""" | ||
| print("PraisonAI Agents - Guardrails Example") | ||
| print("=====================================\n") | ||
|
|
||
| # Create an agent | ||
| agent = Agent( | ||
| name="Email Assistant", | ||
| role="Professional Email Writer", | ||
| goal="Write clear, professional emails", | ||
| backstory="I am an AI assistant specialized in writing professional emails" | ||
| ) | ||
|
|
||
| print("1. Testing Function-based Guardrail") | ||
| print("------------------------------------") | ||
|
|
||
| # Create task with function-based guardrail | ||
| task_with_function_guardrail = Task( | ||
| description="Write a professional email to a client about project completion", | ||
| expected_output="A well-formatted professional email", | ||
| agent=agent, | ||
| guardrail=email_validator, # Function-based guardrail | ||
| max_retries=2 | ||
| ) | ||
|
|
||
| print(f"Task created with function guardrail: {email_validator.__name__}") | ||
| print(f"Max retries: {task_with_function_guardrail.max_retries}") | ||
|
|
||
| # Simulate a task output that should pass | ||
| good_output = TaskOutput( | ||
| description="Email task", | ||
| raw="""Subject: Project Completion Update | ||
|
|
||
| Dear Client, | ||
|
|
||
| I am pleased to inform you that your project has been completed successfully. | ||
| All deliverables have been reviewed and are ready for your review. | ||
| Please let me know if you have any questions. | ||
|
|
||
| Best regards, | ||
| Project Team""", | ||
| agent="Email Assistant" | ||
| ) | ||
|
|
||
| result = task_with_function_guardrail._process_guardrail(good_output) | ||
| print(f"Good email result: {'PASSED' if result.success else 'FAILED'}") | ||
| if not result.success: | ||
| print(f"Error: {result.error}") | ||
|
|
||
| # Simulate a task output that should fail | ||
| bad_output = TaskOutput( | ||
| description="Email task", | ||
| raw="Hi there, there was an error with your project.", | ||
| agent="Email Assistant" | ||
| ) | ||
|
|
||
| result = task_with_function_guardrail._process_guardrail(bad_output) | ||
| print(f"Bad email result: {'PASSED' if result.success else 'FAILED'}") | ||
| if not result.success: | ||
| print(f"Error: {result.error}") | ||
|
|
||
| print("\n2. Testing String-based LLM Guardrail") | ||
| print("-------------------------------------") | ||
|
|
||
| # Create task with string-based guardrail | ||
| task_with_llm_guardrail = Task( | ||
| description="Write a marketing email for a new product launch", | ||
| expected_output="Engaging marketing content", | ||
| agent=agent, | ||
| guardrail="Ensure the content is professional, engaging, includes a clear call-to-action, and is free of errors", | ||
| max_retries=3 | ||
| ) | ||
|
|
||
| print("Task created with LLM-based guardrail") | ||
| print("Guardrail description: 'Ensure the content is professional, engaging, includes a clear call-to-action, and is free of errors'") | ||
| print(f"Max retries: {task_with_llm_guardrail.max_retries}") | ||
|
|
||
| print("\n3. Backward Compatibility") | ||
| print("-------------------------") | ||
|
|
||
| # Create task without guardrail (backward compatible) | ||
| task_without_guardrail = Task( | ||
| description="Write a simple thank you note", | ||
| expected_output="A brief thank you message", | ||
| agent=agent | ||
| ) | ||
|
|
||
| print("Task created without guardrail (backward compatible)") | ||
| print(f"Guardrail function: {task_without_guardrail._guardrail_fn}") | ||
|
|
||
| # Test that it doesn't break existing functionality | ||
| simple_output = TaskOutput( | ||
| description="Thank you task", | ||
| raw="Thank you for your business!", | ||
| agent="Email Assistant" | ||
| ) | ||
|
|
||
| result = task_without_guardrail._process_guardrail(simple_output) | ||
| print(f"No guardrail result: {'PASSED' if result.success else 'FAILED'}") | ||
|
|
||
| print("\n✅ Guardrails example completed successfully!") | ||
| print("\nKey Features Demonstrated:") | ||
| print("- Function-based guardrails with custom validation logic") | ||
| print("- String-based LLM guardrails using natural language") | ||
| print("- Configurable retry mechanism") | ||
| print("- Backward compatibility with existing tasks") | ||
| print("- Integration with TaskOutput validation") | ||
|
|
||
|
|
||
| if __name__ == "__main__": | ||
| main() No newline at end of file |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Eliminate code duplication and improve test structure.
This file is nearly identical to src/praisonai-agents/guardrails_example.py, creating unnecessary code duplication. The path manipulation approach is also not ideal for test organization.
Consider one of these approaches:
Option 1: Convert to proper unit tests
import unittest
from praisonaiagents import Agent, Task, TaskOutput
from your_module import email_validator
class TestGuardrails(unittest.TestCase):
def setUp(self):
self.agent = Agent(
name="Email Assistant",
role="Professional Email Writer",
goal="Write clear, professional emails",
backstory="I am an AI assistant specialized in writing professional emails"
)
def test_function_based_guardrail_pass(self):
# Test implementation here
pass
def test_function_based_guardrail_fail(self):
# Test implementation here
passOption 2: Remove duplication and use proper imports
If this must remain as an example script, remove the path manipulation and ensure proper package installation for imports, or reference the original example file.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 30-30: Trailing whitespace
(C0303)
[convention] 34-34: Trailing whitespace
(C0303)
[convention] 37-37: Trailing whitespace
(C0303)
[convention] 40-40: Trailing whitespace
(C0303)
[convention] 43-43: Trailing whitespace
(C0303)
[convention] 51-51: Trailing whitespace
(C0303)
[convention] 59-59: Trailing whitespace
(C0303)
[convention] 62-62: Trailing whitespace
(C0303)
[convention] 71-71: Trailing whitespace
(C0303)
[convention] 74-74: Trailing whitespace
(C0303)
[convention] 90-90: Trailing whitespace
(C0303)
[convention] 95-95: Trailing whitespace
(C0303)
[convention] 102-102: Trailing whitespace
(C0303)
[convention] 107-107: Trailing whitespace
(C0303)
[convention] 110-110: Trailing whitespace
(C0303)
[convention] 116-116: Line too long (121/100)
(C0301)
[convention] 119-119: Trailing whitespace
(C0303)
[convention] 121-121: Line too long (138/100)
(C0301)
[convention] 123-123: Trailing whitespace
(C0303)
[convention] 126-126: Trailing whitespace
(C0303)
[convention] 133-133: Trailing whitespace
(C0303)
[convention] 136-136: Trailing whitespace
(C0303)
[convention] 143-143: Trailing whitespace
(C0303)
[convention] 146-146: Trailing whitespace
(C0303)
[convention] 157-157: Final newline missing
(C0304)
[error] 16-16: Unable to import 'praisonaiagents'
(E0401)
[convention] 16-16: Import "from praisonaiagents import Agent, Task, TaskOutput" should be placed at the top of the module
(C0413)
[warning] 91-91: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 103-103: Access to a protected member _process_guardrail of a client class
(W0212)
[warning] 135-135: Access to a protected member _guardrail_fn of a client class
(W0212)
[warning] 144-144: Access to a protected member _process_guardrail of a client class
(W0212)
🤖 Prompt for AI Agents
In src/praisonai-agents/tests/guardrails_example.py lines 1 to 157, the code
duplicates the example script from src/praisonai-agents/guardrails_example.py
and uses path manipulation for imports, which is not ideal. To fix this,
refactor the test file into proper unit tests using a testing framework like
unittest, importing the necessary components from the main package without path
hacks. Alternatively, if it must remain an example script, remove the sys.path
manipulation and ensure the package is installed so imports work correctly,
avoiding code duplication by referencing or importing the original example.
| import inspect | ||
| from typing import List, Optional, Dict, Any, Type, Callable, Union, Coroutine, Literal, Tuple, get_args, get_origin |
There was a problem hiding this comment.
Remove unused Literal import
The Literal import is unused at the module level. It's re-imported locally where needed (lines 114 and 134).
-from typing import List, Optional, Dict, Any, Type, Callable, Union, Coroutine, Literal, Tuple, get_args, get_origin
+from typing import List, Optional, Dict, Any, Type, Callable, Union, Coroutine, Tuple, get_args, get_origin📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| import inspect | |
| from typing import List, Optional, Dict, Any, Type, Callable, Union, Coroutine, Literal, Tuple, get_args, get_origin | |
| import inspect | |
| from typing import List, Optional, Dict, Any, Type, Callable, Union, Coroutine, Tuple, get_args, get_origin |
🧰 Tools
🪛 Ruff (0.11.9)
4-4: typing.Literal imported but unused
Remove unused import: typing.Literal
(F401)
🪛 Pylint (3.3.7)
[convention] 4-4: Line too long (116/100)
(C0301)
[warning] 4-4: Unused Literal imported from typing
(W0611)
🤖 Prompt for AI Agents
In src/praisonai-agents/praisonaiagents/task/task.py around lines 3 to 4, remove
the unused import Literal from the module-level import statement since it is
re-imported locally where needed on lines 114 and 134. This will clean up the
imports and avoid redundancy.
| if self._guardrail_fn: | ||
| try: | ||
| guardrail_result = self._process_guardrail(task_output) | ||
| if not guardrail_result.success: | ||
| if self.retry_count >= self.max_retries: | ||
| raise Exception( | ||
| f"Task failed guardrail validation after {self.max_retries} retries. " | ||
| f"Last error: {guardrail_result.error}" | ||
| ) | ||
|
|
||
| self.retry_count += 1 | ||
| logger.warning(f"Task {self.id}: Guardrail validation failed (retry {self.retry_count}/{self.max_retries}): {guardrail_result.error}") | ||
| # Note: In a real execution, this would trigger a retry, but since this is a callback | ||
| # the retry logic would need to be handled at the agent/execution level | ||
| return | ||
|
|
||
| # If guardrail passed and returned a modified result | ||
| if guardrail_result.result is not None: | ||
| if isinstance(guardrail_result.result, str): | ||
| # Update the task output with the modified result | ||
| task_output.raw = guardrail_result.result | ||
| elif isinstance(guardrail_result.result, TaskOutput): | ||
| # Replace with the new task output | ||
| task_output = guardrail_result.result | ||
|
|
||
| logger.info(f"Task {self.id}: Guardrail validation passed") | ||
| except Exception as e: | ||
| logger.error(f"Task {self.id}: Error in guardrail processing: {e}") | ||
| # Continue execution even if guardrail fails to avoid breaking the task | ||
|
|
There was a problem hiding this comment.
💡 Verification agent
🧩 Analysis chain
Incomplete retry mechanism needs clarification
The retry logic only increments the counter and returns early without actually triggering a retry. The comment acknowledges this, but it leaves the feature partially implemented.
Consider either:
- Documenting this limitation more prominently in the class docstring
- Raising a specific exception that the execution layer can catch and handle for retries
- Removing the retry logic until it can be properly implemented
Also, use lazy formatting in logging statements and avoid catching general exceptions:
- logger.warning(f"Task {self.id}: Guardrail validation failed (retry {self.retry_count}/{self.max_retries}): {guardrail_result.error}")
+ logger.warning("Task %s: Guardrail validation failed (retry %d/%d): %s",
+ self.id, self.retry_count, self.max_retries, guardrail_result.error)- logger.info(f"Task {self.id}: Guardrail validation passed")
+ logger.info("Task %s: Guardrail validation passed", self.id)- except Exception as e:
- logger.error(f"Task {self.id}: Error in guardrail processing: {e}")
+ except Exception as e:
+ logger.error("Task %s: Error in guardrail processing: %s", self.id, e)🏁 Script executed:
#!/bin/bash
# Display the class docstring and initialization to check for existing documentation on retry behavior
sed -n '1,100p' src/praisonai-agents/praisonaiagents/task/task.py | sed -e '1,/\(class Task\)/!d' -e '/class Task/,/def __init__/p'Length of output: 499
Incomplete retry mechanism and logging improvements needed
The guardrail retry logic in src/praisonai-agents/praisonaiagents/task/task.py:248–277 only increments retry_count and returns, without driving an actual retry, and the logging and exception‐handling can be made more robust.
• Clarify or eliminate the half-implemented retry logic:
– Add a prominent note in the class docstring or constructor docstring detailing that retries are no-ops unless handled by the caller.
– Alternatively, raise a custom exception (e.g. GuardrailRetryNeeded) so the outer execution layer can catch and re-invoke execute_callback.
– Or remove retry_count/max_retries until fully implemented.
• Switch to lazy logging formatting to avoid unnecessary string interpolation:
- logger.warning(f"Task {self.id}: Guardrail validation failed (retry {self.retry_count}/{self.max_retries}): {guardrail_result.error}")
+ logger.warning(
+ "Task %s: Guardrail validation failed (retry %d/%d): %s",
+ self.id, self.retry_count, self.max_retries, guardrail_result.error,
+ )- logger.info(f"Task {self.id}: Guardrail validation passed")
+ logger.info("Task %s: Guardrail validation passed", self.id)• Catch specific exceptions instead of except Exception:
- except Exception as e:
- logger.error(f"Task {self.id}: Error in guardrail processing: {e}")
+ except GuardrailProcessingError as e:
+ logger.error("Task %s: Guardrail processing error: %s", self.id, e)Committable suggestion skipped: line range outside the PR's diff.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 257-257: Trailing whitespace
(C0303)
[convention] 259-259: Line too long (154/100)
(C0301)
[convention] 260-260: Line too long (105/100)
(C0301)
[convention] 263-263: Trailing whitespace
(C0303)
[convention] 272-272: Trailing whitespace
(C0303)
[warning] 274-274: Catching too general exception Exception
(W0718)
[warning] 253-256: Raising too general exception: Exception
(W0719)
[warning] 259-259: Use lazy % formatting in logging functions
(W1203)
[warning] 273-273: Use lazy % formatting in logging functions
(W1203)
[warning] 275-275: Use lazy % formatting in logging functions
(W1203)
🤖 Prompt for AI Agents
In src/praisonai-agents/praisonaiagents/task/task.py around lines 248 to 277,
the retry logic for guardrail validation is incomplete as it only increments
retry_count and returns without triggering a retry. To fix this, either add a
clear note in the class or constructor docstring explaining that retries are
no-ops unless handled externally, or raise a custom exception like
GuardrailRetryNeeded to signal the caller to retry. Also, update all logger
calls to use lazy formatting with placeholders instead of f-strings, and replace
the broad except Exception with catching specific exceptions relevant to
guardrail processing.
|
Also include guardrail in the Agent class agent = Agent( also review above recommendation , implement only if its worthwhile or else focus on implementing guardrail to Agent class as above, similar to the Task class. |
|
Claude finished @MervinPraison's task in 9m 20s —— View job Implementing Guardrail Support in Agent Class ✅✅ Implementation Complete!I have successfully implemented comprehensive Agent-level guardrail functionality as requested. Here's what was implemented: Core Features Added:
Usage Examples:# Function-based guardrail
agent = Agent(
instructions="You are a writer",
guardrail=validate_content,
max_guardrail_retries=3
)
# LLM-based guardrail
agent = Agent(
instructions="You are a writer",
guardrail="Ensure content is professional and error-free",
max_guardrail_retries=2
)Enhanced Examples & Documentation:
This implementation provides the exact functionality you requested - Agent-level guardrails that apply to all outputs from that agent, with both function-based and LLM-based validation support, automatic retry logic, and seamless integration with existing Agent functionality. The implementation is now complete and committed! The Agent class now supports guardrails exactly as you requested in your example: agent = Agent(
instructions="You are a writer",
guardrail=validate_content
) |
- Add guardrail and max_guardrail_retries parameters to Agent constructor - Implement _setup_guardrail() method supporting function and LLM-based guardrails - Add _process_guardrail() method for validation processing - Create _apply_guardrail_with_retry() method with automatic retry logic - Integrate guardrail processing into all major return points in chat() method - Support both regular responses and reasoning content validation - Update agent_guardrails_example.py with comprehensive demonstrations - Enhance CLAUDE.md documentation with Agent-level guardrail usage - Add test file for Agent guardrail functionality validation Agent-level guardrails apply to ALL outputs from the agent, providing consistent validation across all agent interactions with configurable retry logic and support for both function-based and string-based LLM guardrails. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
There was a problem hiding this comment.
Actionable comments posted: 4
🧹 Nitpick comments (2)
src/praisonai-agents/agent_guardrails_example.py (1)
26-43: Consider making the unprofessional words list configurable.While the implementation is correct for an example, in production code, consider making the list of unprofessional words configurable.
For production use, consider:
def create_professional_tone_validator(unprofessional_words=None): """Factory function to create a professional tone validator with custom word list.""" if unprofessional_words is None: unprofessional_words = ['yo', 'dude', 'awesome', 'cool', 'lol'] def validate_professional_tone(task_output: TaskOutput) -> Tuple[bool, Any]: content = task_output.raw.lower() for word in unprofessional_words: if word in content: return False, f"Content contains unprofessional word: '{word}'" return True, task_output return validate_professional_tone🧰 Tools
🪛 Pylint (3.3.7)
[convention] 38-38: Trailing whitespace
(C0303)
[convention] 42-42: Trailing whitespace
(C0303)
src/praisonai-agents/praisonaiagents/agent/agent.py (1)
524-568: Consider simplifying the return type validation logic.While the guardrail setup is comprehensive, the return type validation (lines 544-558) is complex and might be overly restrictive. Consider simplifying or making it optional.
- # Check return annotation if present - from typing import get_args, get_origin - return_annotation = sig.return_annotation - if return_annotation != inspect.Signature.empty: - return_annotation_args = get_args(return_annotation) - if not ( - get_origin(return_annotation) is tuple - and len(return_annotation_args) == 2 - and return_annotation_args[0] is bool - and ( - return_annotation_args[1] is Any - or return_annotation_args[1] is str - or str(return_annotation_args[1]).endswith('TaskOutput') - or str(return_annotation_args[1]).startswith('typing.Union') - ) - ): - raise ValueError( - "If return type is annotated, it must be Tuple[bool, Any] or Tuple[bool, Union[str, TaskOutput]]" - ) + # Optionally validate return annotation + if sig.return_annotation != inspect.Signature.empty: + # Log a warning instead of raising an error + logging.debug(f"Guardrail function has return annotation: {sig.return_annotation}")This would make the API more flexible while still encouraging proper type hints.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 529-529: Trailing whitespace
(C0303)
[convention] 538-538: Line too long (107/100)
(C0301)
[convention] 539-539: Trailing whitespace
(C0303)
[convention] 557-557: Line too long (121/100)
(C0301)
[convention] 559-559: Trailing whitespace
(C0303)
[convention] 541-541: Import outside toplevel (typing.get_args, typing.get_origin)
(C0415)
[convention] 563-563: Import outside toplevel (guardrails.LLMGuardrail)
(C0415)
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (4)
src/praisonai-agents/CLAUDE.md(1 hunks)src/praisonai-agents/agent_guardrails_example.py(1 hunks)src/praisonai-agents/praisonaiagents/agent/agent.py(10 hunks)src/praisonai-agents/test_agent_guardrails.py(1 hunks)
🧰 Additional context used
🧬 Code Graph Analysis (1)
src/praisonai-agents/agent_guardrails_example.py (3)
src/praisonai-agents/praisonaiagents/agent/agent.py (2)
Agent(206-2010)start(1623-1625)src/praisonai-agents/praisonaiagents/main.py (1)
TaskOutput(399-428)src/praisonai-agents/guardrails_example.py (1)
main(44-150)
🪛 Pylint (3.3.7)
src/praisonai-agents/test_agent_guardrails.py
[convention] 9-9: Trailing whitespace
(C0303)
[convention] 13-13: Trailing whitespace
(C0303)
[convention] 19-19: Trailing whitespace
(C0303)
[convention] 31-31: Trailing whitespace
(C0303)
[convention] 43-43: Trailing whitespace
(C0303)
[convention] 52-52: Trailing whitespace
(C0303)
[convention] 55-55: Trailing whitespace
(C0303)
[convention] 63-63: Final newline missing
(C0304)
[warning] 56-56: Catching too general exception Exception
(W0718)
[convention] 11-11: Import outside toplevel (praisonaiagents.Agent, praisonaiagents.TaskOutput)
(C0415)
[warning] 29-29: Access to a protected member _guardrail_fn of a client class
(W0212)
[warning] 41-41: Access to a protected member _guardrail_fn of a client class
(W0212)
[warning] 51-51: Access to a protected member _guardrail_fn of a client class
(W0212)
[convention] 58-58: Import outside toplevel (traceback)
(C0415)
src/praisonai-agents/agent_guardrails_example.py
[convention] 38-38: Trailing whitespace
(C0303)
[convention] 42-42: Trailing whitespace
(C0303)
[convention] 47-47: Trailing whitespace
(C0303)
[convention] 49-49: Trailing whitespace
(C0303)
[convention] 58-58: Trailing whitespace
(C0303)
[convention] 64-64: Trailing whitespace
(C0303)
[convention] 68-68: Trailing whitespace
(C0303)
[convention] 70-70: Line too long (134/100)
(C0301)
[convention] 73-73: Trailing whitespace
(C0303)
[convention] 79-79: Trailing whitespace
(C0303)
[convention] 88-88: Trailing whitespace
(C0303)
[convention] 94-94: Trailing whitespace
(C0303)
[warning] 62-62: Catching too general exception Exception
(W0718)
[warning] 77-77: Catching too general exception Exception
(W0718)
[warning] 92-92: Catching too general exception Exception
(W0718)
src/praisonai-agents/praisonaiagents/agent/agent.py
[convention] 489-489: Trailing whitespace
(C0303)
[convention] 529-529: Trailing whitespace
(C0303)
[convention] 538-538: Line too long (107/100)
(C0301)
[convention] 539-539: Trailing whitespace
(C0303)
[convention] 557-557: Line too long (121/100)
(C0301)
[convention] 559-559: Trailing whitespace
(C0303)
[convention] 579-579: Trailing whitespace
(C0303)
[convention] 582-582: Trailing whitespace
(C0303)
[convention] 586-586: Trailing whitespace
(C0303)
[convention] 589-589: Trailing whitespace
(C0303)
[convention] 613-613: Trailing whitespace
(C0303)
[convention] 615-615: Trailing whitespace
(C0303)
[convention] 618-618: Trailing whitespace
(C0303)
[convention] 629-629: Trailing whitespace
(C0303)
[convention] 632-632: Trailing whitespace
(C0303)
[convention] 642-642: Trailing whitespace
(C0303)
[convention] 646-646: Line too long (122/100)
(C0301)
[convention] 649-649: Trailing whitespace
(C0303)
[convention] 651-651: Line too long (155/100)
(C0301)
[convention] 652-652: Trailing whitespace
(C0303)
[convention] 655-655: Line too long (158/100)
(C0301)
[convention] 656-656: Line too long (113/100)
(C0301)
[convention] 667-667: Trailing whitespace
(C0303)
[convention] 541-541: Import outside toplevel (typing.get_args, typing.get_origin)
(C0415)
[convention] 563-563: Import outside toplevel (guardrails.LLMGuardrail)
(C0415)
[convention] 578-578: Import outside toplevel (guardrails.GuardrailResult)
(C0415)
[warning] 590-590: Catching too general exception Exception
(W0718)
[warning] 591-591: Use lazy % formatting in logging functions
(W1203)
[convention] 614-614: Import outside toplevel (main.TaskOutput)
(C0415)
[warning] 634-634: Use lazy % formatting in logging functions
(W1203)
[refactor] 636-641: Unnecessary "elif" after "return", remove the leading "el" from "elif"
(R1705)
[warning] 645-648: Raising too general exception: Exception
(W0719)
[warning] 651-651: Use lazy % formatting in logging functions
(W1203)
[warning] 660-660: Raising too general exception: Exception
(W0719)
[warning] 662-662: Use lazy % formatting in logging functions
(W1203)
[warning] 664-666: Consider explicitly re-raising using 'raise Exception(f'Agent {self.name} guardrail retry failed: {e}') from e'
(W0707)
[warning] 664-666: Raising too general exception: Exception
(W0719)
[convention] 1127-1127: Line too long (116/100)
(C0301)
[convention] 1130-1130: Line too long (104/100)
(C0301)
[warning] 1129-1129: Catching too general exception Exception
(W0718)
[warning] 1130-1130: Use lazy % formatting in logging functions
(W1203)
[convention] 1221-1221: Line too long (170/100)
(C0301)
[convention] 1224-1224: Line too long (123/100)
(C0301)
[convention] 1228-1228: Line too long (133/100)
(C0301)
[warning] 1223-1223: Catching too general exception Exception
(W0718)
[warning] 1224-1224: Use lazy % formatting in logging functions
(W1203)
[warning] 1230-1230: Catching too general exception Exception
(W0718)
[warning] 1231-1231: Use lazy % formatting in logging functions
(W1203)
[convention] 1267-1267: Line too long (128/100)
(C0301)
[convention] 1270-1270: Line too long (118/100)
(C0301)
[warning] 1269-1269: Catching too general exception Exception
(W0718)
[warning] 1270-1270: Use lazy % formatting in logging functions
(W1203)
[convention] 1282-1282: Line too long (128/100)
(C0301)
[convention] 1285-1285: Line too long (123/100)
(C0301)
[warning] 1284-1284: Catching too general exception Exception
(W0718)
[warning] 1285-1285: Use lazy % formatting in logging functions
(W1203)
[convention] 1310-1310: Trailing whitespace
(C0303)
[convention] 1311-1311: Trailing whitespace
(C0303)
[convention] 1313-1313: Line too long (108/100)
(C0301)
[warning] 1315-1315: Catching too general exception Exception
(W0718)
[warning] 1316-1316: Use lazy % formatting in logging functions
(W1203)
🪛 Ruff (0.11.9)
src/praisonai-agents/praisonaiagents/agent/agent.py
664-666: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
🪛 LanguageTool
src/praisonai-agents/CLAUDE.md
[duplication] ~96-~96: Possible typo: you repeated a word.
Context: .../knowledge/): Document processing with chunking - Chunking strategies via chonkie` library - Em...
(ENGLISH_WORD_REPEAT_RULE)
[uncategorized] ~235-~235: You might be missing the article “the” here.
Context: ...-driven testing with 100+ test files in tests/ directory. Each test file demons...
(AI_EN_LECTOR_MISSING_DETERMINER_THE)
⏰ Context from checks skipped due to timeout of 90000ms (4)
- GitHub Check: quick-test
- GitHub Check: test-core (3.11)
- GitHub Check: quick-test
- GitHub Check: test-core (3.11)
🔇 Additional comments (8)
src/praisonai-agents/agent_guardrails_example.py (2)
12-24: LGTM! Well-structured guardrail function.The
validate_content_lengthfunction correctly implements the guardrail pattern with proper type hints and clear documentation.
45-95: Excellent example demonstrating various guardrail configurations.The examples clearly show:
- Function-based guardrails for content length
- LLM-based guardrails with string descriptions
- Function-based guardrails for tone validation
This provides a comprehensive demonstration of the guardrail feature.
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 47-47: Trailing whitespace
(C0303)
[convention] 49-49: Trailing whitespace
(C0303)
[convention] 58-58: Trailing whitespace
(C0303)
[convention] 64-64: Trailing whitespace
(C0303)
[convention] 68-68: Trailing whitespace
(C0303)
[convention] 70-70: Line too long (134/100)
(C0301)
[convention] 73-73: Trailing whitespace
(C0303)
[convention] 79-79: Trailing whitespace
(C0303)
[convention] 88-88: Trailing whitespace
(C0303)
[convention] 94-94: Trailing whitespace
(C0303)
[warning] 62-62: Catching too general exception Exception
(W0718)
[warning] 77-77: Catching too general exception Exception
(W0718)
[warning] 92-92: Catching too general exception Exception
(W0718)
src/praisonai-agents/CLAUDE.md (3)
72-77: Well-documented guardrail features in the Task System section.The documentation clearly explains the guardrail functionality, including both function-based and LLM-based approaches, retry logic, and CrewAI compatibility.
119-121: Clear documentation of agent-level guardrail parameters.The example correctly shows how to configure guardrails at the agent level.
137-197: Comprehensive guardrails usage documentation with excellent examples.This section provides thorough coverage of guardrail usage patterns, including:
- Task-level guardrails with both function and string approaches
- Agent-level guardrails that apply to all outputs
- Clear examples with proper type hints and error handling
The documentation will help users understand and implement guardrails effectively.
src/praisonai-agents/praisonaiagents/agent/agent.py (3)
372-494: Well-integrated guardrail parameters in Agent initialization.The guardrail functionality is cleanly added to the Agent constructor with appropriate default values and initialization logic.
🧰 Tools
🪛 Ruff (0.11.9)
379-379:
..memory.memory.Memoryimported but unused; consider usingimportlib.util.find_specto test for availability(F401)
380-380: Local variable
MEMORY_AVAILABLEis assigned to but never usedRemove assignment to unused variable
MEMORY_AVAILABLE(F841)
382-385: Within an
exceptclause, raise exceptions withraise ... from errorraise ... from Noneto distinguish them from errors in exception handling(B904)
🪛 Pylint (3.3.7)
[convention] 389-389: Line too long (109/100)
(C0301)
[convention] 412-412: Trailing whitespace
(C0303)
[convention] 435-435: Trailing whitespace
(C0303)
[convention] 476-476: Trailing whitespace
(C0303)
[convention] 489-489: Trailing whitespace
(C0303)
[convention] 379-379: Import outside toplevel (memory.memory.Memory)
(C0415)
[convention] 380-380: Variable name "MEMORY_AVAILABLE" doesn't conform to snake_case naming style
(C0103)
[warning] 382-385: Consider explicitly re-raising using 'except ImportError as exc' and 'raise ImportError('Memory features requested in Agent but memory dependencies not installed. Please install with: pip install "praisonaiagents[memory]"') from exc'
(W0707)
[convention] 420-420: Import outside toplevel (llm.llm.LLM)
(C0415)
[convention] 431-431: Import outside toplevel (llm.llm.LLM)
(C0415)
[warning] 438-438: Use lazy % formatting in logging functions
(W1203)
[warning] 380-380: Unused variable 'MEMORY_AVAILABLE'
(W0612)
[warning] 379-379: Unused Memory imported from memory.memory
(W0611)
569-598: Clean implementation of guardrail processing.The
_process_guardrailmethod properly handles guardrail validation with good error handling and clear return values.🧰 Tools
🪛 Pylint (3.3.7)
[convention] 579-579: Trailing whitespace
(C0303)
[convention] 582-582: Trailing whitespace
(C0303)
[convention] 586-586: Trailing whitespace
(C0303)
[convention] 589-589: Trailing whitespace
(C0303)
[convention] 578-578: Import outside toplevel (guardrails.GuardrailResult)
(C0415)
[warning] 590-590: Catching too general exception Exception
(W0718)
[warning] 591-591: Use lazy % formatting in logging functions
(W1203)
6-6: Solid implementation of guardrail functionality.The guardrail feature is well-implemented with:
- Clean API design accepting both functions and strings
- Comprehensive validation and retry logic
- Good error handling throughout
- Proper integration into the agent's chat flow
The implementation successfully adds output validation capabilities while maintaining backward compatibility.
Also applies to: 372-374, 490-669, 1125-1319
| def test_agent_guardrails(): | ||
| """Test basic Agent guardrail functionality.""" | ||
| print("Testing Agent guardrail functionality...") | ||
|
|
||
| try: | ||
| from praisonaiagents import Agent, TaskOutput | ||
| print("✓ Basic imports successful") | ||
|
|
||
| # Test function-based guardrail | ||
| def test_guardrail(task_output: TaskOutput): | ||
| if len(task_output.raw) < 10: | ||
| return False, "Too short" | ||
| return True, task_output | ||
|
|
||
| # Test Agent creation with function guardrail | ||
| agent1 = Agent( | ||
| name="TestAgent1", | ||
| instructions="You are a test agent", | ||
| guardrail=test_guardrail, | ||
| max_guardrail_retries=2 | ||
| ) | ||
| print("✓ Agent with function guardrail created successfully") | ||
| print(f" - Agent name: {agent1.name}") | ||
| print(f" - Has guardrail function: {agent1._guardrail_fn is not None}") | ||
| print(f" - Max retries: {agent1.max_guardrail_retries}") | ||
|
|
||
| # Test Agent creation with string guardrail | ||
| agent2 = Agent( | ||
| name="TestAgent2", | ||
| instructions="You are a test agent", | ||
| guardrail="Ensure the response is polite and professional", | ||
| max_guardrail_retries=3 | ||
| ) | ||
| print("✓ Agent with LLM guardrail created successfully") | ||
| print(f" - Agent name: {agent2.name}") | ||
| print(f" - Has guardrail function: {agent2._guardrail_fn is not None}") | ||
| print(f" - Max retries: {agent2.max_guardrail_retries}") | ||
|
|
||
| # Test Agent without guardrail | ||
| agent3 = Agent( | ||
| name="TestAgent3", | ||
| instructions="You are a test agent" | ||
| ) | ||
| print("✓ Agent without guardrail created successfully") | ||
| print(f" - Agent name: {agent3.name}") | ||
| print(f" - Has guardrail function: {agent3._guardrail_fn is None}") | ||
|
|
||
| print("\n🎉 All Agent guardrail tests passed!") | ||
| return True | ||
|
|
||
| except Exception as e: | ||
| print(f"✗ Error: {e}") | ||
| import traceback | ||
| traceback.print_exc() | ||
| return False | ||
|
|
There was a problem hiding this comment.
🛠️ Refactor suggestion
Enhance test coverage to verify guardrail behavior.
The current test only verifies that agents can be created with guardrails but doesn't test the actual guardrail validation logic. Consider adding tests that execute tasks and verify guardrail behavior.
Would you like me to generate comprehensive tests that verify:
- Guardrails correctly validate outputs
- Retry logic works when validation fails
- Proper error handling when max retries are exceeded
- Both function-based and LLM-based guardrail behavior
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 9-9: Trailing whitespace
(C0303)
[convention] 13-13: Trailing whitespace
(C0303)
[convention] 19-19: Trailing whitespace
(C0303)
[convention] 31-31: Trailing whitespace
(C0303)
[convention] 43-43: Trailing whitespace
(C0303)
[convention] 52-52: Trailing whitespace
(C0303)
[convention] 55-55: Trailing whitespace
(C0303)
[warning] 56-56: Catching too general exception Exception
(W0718)
[convention] 11-11: Import outside toplevel (praisonaiagents.Agent, praisonaiagents.TaskOutput)
(C0415)
[warning] 29-29: Access to a protected member _guardrail_fn of a client class
(W0212)
[warning] 41-41: Access to a protected member _guardrail_fn of a client class
(W0212)
[warning] 51-51: Access to a protected member _guardrail_fn of a client class
(W0212)
[convention] 58-58: Import outside toplevel (traceback)
(C0415)
🤖 Prompt for AI Agents
In src/praisonai-agents/test_agent_guardrails.py around lines 6 to 61, the
current test only checks agent creation with guardrails but does not verify the
guardrail validation logic or retry behavior. Enhance the test by adding cases
that execute tasks through the agents and assert that guardrails correctly
validate outputs, that retry logic triggers on validation failures, and that
errors are properly raised when max retries are exceeded. Include tests for both
function-based and LLM-based guardrails to comprehensively cover their behavior.
| ) | ||
| print("✓ Agent with function guardrail created successfully") | ||
| print(f" - Agent name: {agent1.name}") | ||
| print(f" - Has guardrail function: {agent1._guardrail_fn is not None}") |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Avoid accessing protected members in tests.
The test accesses the protected _guardrail_fn attribute, which breaks encapsulation and makes the test brittle to implementation changes. Consider testing the guardrail behavior through the public API instead.
Instead of checking internal attributes, test the actual guardrail behavior:
- print(f" - Has guardrail function: {agent1._guardrail_fn is not None}")
+ # Test guardrail behavior instead of internal state
+ # This could be done by calling agent1.start() with test input
+ print(f" - Guardrail configured: function-based")Also applies to: 41-41, 51-51
🧰 Tools
🪛 Pylint (3.3.7)
[warning] 29-29: Access to a protected member _guardrail_fn of a client class
(W0212)
🤖 Prompt for AI Agents
In src/praisonai-agents/test_agent_guardrails.py at lines 29, 41, and 51, the
test accesses the protected attribute _guardrail_fn directly, which breaks
encapsulation. Instead, modify the tests to verify guardrail behavior through
the agent's public methods or outputs, avoiding direct inspection of internal
attributes. Replace the print statements and any direct attribute checks with
assertions or checks that confirm the guardrail functionality via the agent's
public API.
| # Apply guardrail validation for custom LLM response | ||
| try: | ||
| validated_response = self._apply_guardrail_with_retry(response_text, prompt, temperature, tools) | ||
| return validated_response | ||
| except Exception as e: | ||
| logging.error(f"Agent {self.name}: Guardrail validation failed for custom LLM: {e}") | ||
| return None | ||
| except Exception as e: |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider refactoring repetitive guardrail validation blocks.
The guardrail validation logic is repeated multiple times throughout the chat method with similar try-except patterns. Consider extracting this into a helper method.
def _validate_and_return_response(self, response_text, prompt, temperature, tools, context=""):
"""Helper method to apply guardrail validation and handle errors consistently."""
try:
validated_response = self._apply_guardrail_with_retry(response_text, prompt, temperature, tools)
return validated_response
except Exception as e:
error_msg = f"Agent {self.name}: Guardrail validation failed{context}: {e}"
logging.error(error_msg)
if self.verbose:
display_error(f"Guardrail validation failed: {e}", console=self.console)
return NoneThen use it throughout the chat method:
# Instead of the repetitive blocks:
return self._validate_and_return_response(response_text, prompt, temperature, tools, " for custom LLM")Also applies to: 1219-1232, 1265-1271, 1280-1286, 1311-1319
🧰 Tools
🪛 Pylint (3.3.7)
[convention] 1127-1127: Line too long (116/100)
(C0301)
[convention] 1130-1130: Line too long (104/100)
(C0301)
[warning] 1132-1132: Catching too general exception Exception
(W0718)
[warning] 1129-1129: Catching too general exception Exception
(W0718)
[warning] 1130-1130: Use lazy % formatting in logging functions
(W1203)
🤖 Prompt for AI Agents
In src/praisonai-agents/praisonaiagents/agent/agent.py around lines 1125 to 1132
and also in lines 1219-1232, 1265-1271, 1280-1286, and 1311-1319, the guardrail
validation logic is repeated with similar try-except blocks. Refactor by
extracting this logic into a helper method named _validate_and_return_response
that takes response_text, prompt, temperature, tools, and an optional context
string. This method should apply the guardrail validation, log errors with
context, optionally display errors if verbose, and return None on failure.
Replace all repetitive try-except guardrail validation blocks in the chat method
with calls to this new helper method, passing appropriate context strings to
maintain clarity in error messages.
| raise Exception( | ||
| f"Agent {self.name} guardrail retry failed: {e}" | ||
| ) |
There was a problem hiding this comment.
Use proper exception chaining.
When re-raising exceptions, use from e to maintain the exception chain for better debugging.
- raise Exception(
- f"Agent {self.name} guardrail retry failed: {e}"
- )
+ raise Exception(
+ f"Agent {self.name} guardrail retry failed: {e}"
+ ) from e📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| raise Exception( | |
| f"Agent {self.name} guardrail retry failed: {e}" | |
| ) | |
| raise Exception( | |
| f"Agent {self.name} guardrail retry failed: {e}" | |
| ) from e |
🧰 Tools
🪛 Ruff (0.11.9)
664-666: Within an except clause, raise exceptions with raise ... from err or raise ... from None to distinguish them from errors in exception handling
(B904)
🪛 Pylint (3.3.7)
[warning] 664-666: Consider explicitly re-raising using 'raise Exception(f'Agent {self.name} guardrail retry failed: {e}') from e'
(W0707)
[warning] 664-666: Raising too general exception: Exception
(W0719)
🤖 Prompt for AI Agents
In src/praisonai-agents/praisonaiagents/agent/agent.py around lines 664 to 666,
the exception is being re-raised without proper chaining. Modify the raise
statement to use "raise Exception(...) from e" to preserve the original
exception context and improve debugging.
Update test workflow to use custom test runner for 'fast' pattern and…
1 participant
User description
… refine guardrail functionality in Task class
PR Type
Enhancement, Tests, Documentation
Description
Introduced guardrail functionality for task output validation
TaskAdded comprehensive tests and usage examples for guardrails
Updated GitHub Actions workflow to use a custom test runner
Added developer documentation and integration guidance (CLAUDE.md)
Changes walkthrough 📝
5 files
Add guardrail validation, retry logic, and integration to TaskAdd GuardrailResult class for structured validation resultsImplement LLMGuardrail for natural language output validationAdd guardrails module exports for GuardrailResult and LLMGuardrailExport guardrail classes in main package init5 files
Add example for agent-level guardrail usageAdd comprehensive example for function and LLM guardrailsAdd sequential agent example using MCP toolAdd developer documentation and usage guidance for ClaudeRemove verbose technical notes, keep concise rules3 files
Add simple test script for guardrail logicAdd test script for function and LLM guardrail integrationAdd test/example for guardrails in tests directory1 files
Update test workflow to use custom test runner with fast patternSummary by CodeRabbit
New Features
Documentation
Tests
Chores
Refactor