Model Pipeline - Test cases for tool-using agents
This pipeline tests how an AI agent uses external tools to complete tasks. It checks if the agent correctly selects, uses, and integrates tool outputs to improve task performance.
Jump into concepts and practice - no test required
This pipeline tests how an AI agent uses external tools to complete tasks. It checks if the agent correctly selects, uses, and integrates tool outputs to improve task performance.
Loss
0.5 |****
0.4 |***
0.3 |**
0.2 |*
0.1 |
1 2 3 4 5 Epochs| Epoch | Loss ↓ | Accuracy ↑ | Observation |
|---|---|---|---|
| 1 | 0.45 | 0.60 | Agent starts learning to select correct tools. |
| 2 | 0.32 | 0.75 | Better tool selection and output integration. |
| 3 | 0.20 | 0.85 | Agent improves in using tools effectively. |
| 4 | 0.15 | 0.90 | High accuracy in task completion with tools. |
| 5 | 0.12 | 0.93 | Training converges with stable performance. |
def test_agent_tool():
result = agent.use_tool('calculator', '2+2')
assert result == 4
print('Test passed')def test_agent_tool():
result = agent.use_tool('search', 'weather today')
assert result = 'sunny'
print('Test passed')