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DO NOT MERGE : feat: implement secure API key handling #164
DO NOT MERGE : feat: implement secure API key handling #164
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🤖 Devin AI EngineerI'll be helping with this pull request! Here's what you should know: ✅ I will automatically:
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Disclaimer: This review was made by a crew of AI Agents. Code Review Comment for PR #164OverviewThis pull request proposes modifications to enhance the functionality and robustness of the Findings and Recommendations1. Parameter ValidationThe constructor currently lacks validation for the Current Code Example: def __init__(self, model: str = "openhermes"): Suggested Improvement: def __init__(self, model: str = "openhermes"):
supported_models = ["openhermes", "llama2", "mistral"]
if model not in supported_models:
raise ValueError(f"Model {model} not supported. Choose from: {supported_models}")
self.model = model 2. Error Handling in API CallsThe error handling in the Current Code: async def execute(self, prompt: str) -> str:
response = await Ollama().generate(model=self.model, prompt=prompt)
return response['response'] Recommended Code: async def execute(self, prompt: str) -> str:
try:
response = await Ollama().generate(model=self.model, prompt=prompt)
if not response or 'response' not in response:
raise ValueError("Invalid response from Ollama API")
return response['response']
except Exception as e:
raise Exception(f"Error generating response with Ollama: {str(e)}") 3. Type Hints and DocumentationAdding return type hints can enhance code readability and maintainability. Furthermore, proper class docstrings will clarify the purpose and usage of the class. Current Code: def get_name(self):
return "Ollama Tool" Recommended Changes: def get_name(self) -> str:
return "Ollama Tool"
def get_description(self) -> str:
return f"A tool that allows you to interact with Ollama using the {self.model} model" Suggested Docstring: class OllamaTool(BaseTool):
"""
A tool for interacting with Ollama language models.
Attributes:
model (str): The name of the Ollama model to use.
Methods:
execute(prompt: str) -> str: Generates a response using the specified model.
get_name() -> str: Returns the tool's name.
get_description() -> str: Returns the tool's description.
""" General Recommendations
Example test structure: import pytest
from crewai_tools.tools.ollama_tool import OllamaTool
@pytest.mark.asyncio
async def test_ollama_tool_execution():
tool = OllamaTool(model="openhermes")
response = await tool.execute("Test prompt")
assert isinstance(response, str)
assert len(response) > 0 ConclusionThis pull request presents valuable improvements to the By following these recommendations, the contributions made in this PR can significantly enhance the overall project quality and functionality. Thank you for your efforts in improving the Ollama tool, and I look forward to seeing the implemented recommendations! |
feat: integration of scrapegraph APIs Co-Authored-By: Joe Moura <[email protected]>
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- Add type validation for environment variables - Implement secure error message masking - Create central environment variable documentation - Update API tool to use generic error messages This change improves security by: 1. Preventing exposure of sensitive data in error messages 2. Adding type validation for environment variables 3. Centralizing environment variable documentation 4. Standardizing error handling across tools Co-Authored-By: Joe Moura <[email protected]>
Closing due to inactivity. |
Changes
Security Improvements
Testing
Link to Devin run: https://app.devin.ai/sessions/3e0f445722ea461792285ad84b0fd53c