[EXPORT AOP] [BUG][#1108]
Kye Gomez
1 week ago
parent
3de4c78bfe
commit
ea30c40d74
@ -0,0 +1,150 @@
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from pydantic import BaseModel
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from swarms.tools.pydantic_to_json import (
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base_model_to_openai_function,
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multi_base_model_to_openai_function,
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)
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from swarms.tools.base_tool import BaseTool
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# Test Pydantic model
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class TestModel(BaseModel):
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"""A test model for validation."""
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name: str
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age: int
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email: str = "test@example.com"
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def test_base_model_to_openai_function():
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"""Test that base_model_to_openai_function accepts output_str parameter."""
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print(
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"Testing base_model_to_openai_function with output_str=False..."
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)
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result_dict = base_model_to_openai_function(
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TestModel, output_str=False
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)
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print(f"✓ Dict result type: {type(result_dict)}")
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print(f"✓ Dict result keys: {list(result_dict.keys())}")
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print(
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"\nTesting base_model_to_openai_function with output_str=True..."
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)
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result_str = base_model_to_openai_function(
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TestModel, output_str=True
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)
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print(f"✓ String result type: {type(result_str)}")
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print(f"✓ String result preview: {result_str[:100]}...")
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def test_multi_base_model_to_openai_function():
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"""Test that multi_base_model_to_openai_function handles output_str correctly."""
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print(
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"\nTesting multi_base_model_to_openai_function with output_str=False..."
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)
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result_dict = multi_base_model_to_openai_function(
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[TestModel], output_str=False
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)
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print(f"✓ Dict result type: {type(result_dict)}")
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print(f"✓ Dict result keys: {list(result_dict.keys())}")
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print(
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"\nTesting multi_base_model_to_openai_function with output_str=True..."
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)
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result_str = multi_base_model_to_openai_function(
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[TestModel], output_str=True
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)
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print(f"✓ String result type: {type(result_str)}")
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print(f"✓ String result preview: {result_str[:100]}...")
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def test_base_tool_methods():
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"""Test that BaseTool methods handle output_str parameter correctly."""
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print(
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"\nTesting BaseTool.base_model_to_dict with output_str=False..."
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)
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tool = BaseTool()
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result_dict = tool.base_model_to_dict(TestModel, output_str=False)
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print(f"✓ Dict result type: {type(result_dict)}")
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print(f"✓ Dict result keys: {list(result_dict.keys())}")
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print(
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"\nTesting BaseTool.base_model_to_dict with output_str=True..."
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)
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result_str = tool.base_model_to_dict(TestModel, output_str=True)
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print(f"✓ String result type: {type(result_str)}")
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print(f"✓ String result preview: {result_str[:100]}...")
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print(
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"\nTesting BaseTool.multi_base_models_to_dict with output_str=False..."
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)
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result_dict = tool.multi_base_models_to_dict(
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[TestModel], output_str=False
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)
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print(f"✓ Dict result type: {type(result_dict)}")
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print(f"✓ Dict result length: {len(result_dict)}")
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print(
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"\nTesting BaseTool.multi_base_models_to_dict with output_str=True..."
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)
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result_str = tool.multi_base_models_to_dict(
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[TestModel], output_str=True
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)
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print(f"✓ String result type: {type(result_str)}")
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print(f"✓ String result preview: {result_str[:100]}...")
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def test_agent_integration():
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"""Test that the Agent class can use the fixed methods without errors."""
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print("\nTesting Agent integration...")
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try:
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from swarms import Agent
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# Create a simple agent with a tool schema
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agent = Agent(
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model_name="gpt-4o-mini",
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tool_schema=TestModel,
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max_loops=1,
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verbose=True,
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)
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# This should not raise an error anymore
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agent.handle_tool_schema_ops()
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print(
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"✓ Agent.handle_tool_schema_ops() completed successfully"
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)
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except Exception as e:
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print(f"✗ Agent integration failed: {e}")
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return False
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return True
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if __name__ == "__main__":
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print("=" * 60)
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print("Testing output_str parameter fix")
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print("=" * 60)
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try:
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test_base_model_to_openai_function()
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test_multi_base_model_to_openai_function()
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test_base_tool_methods()
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if test_agent_integration():
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print("\n" + "=" * 60)
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print(
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"✅ All tests passed! The output_str parameter fix is working correctly."
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)
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print("=" * 60)
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else:
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print("\n" + "=" * 60)
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print(
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"❌ Some tests failed. Please check the implementation."
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)
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print("=" * 60)
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except Exception as e:
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print(f"\n❌ Test failed with error: {e}")
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import traceback
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traceback.print_exc()
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