wehub-resource-sync
e768098d0e
tools_continuous_delivery / Private PyPI non-main branch release (push) Has been skipped
tools_continuous_delivery / Private PyPI main branch release (push) Failing after 2m42s
Publish Promptflow Doc / Build (push) Has been cancelled
Publish Promptflow Doc / Deploy (push) Has been cancelled
Flake8 Lint / flake8 (push) Has been cancelled
Spell check CI / Spell_Check (push) Has been cancelled
68 lines
2.4 KiB
Python
68 lines
2.4 KiB
Python
import asyncio
|
|
import json
|
|
from pathlib import Path
|
|
from workflow import EvalInput, create_workflow
|
|
|
|
|
|
async def test_single_row():
|
|
"""Smoke test - requires Azure OpenAI credentials in .env"""
|
|
chat_history = [
|
|
{
|
|
"inputs": {"question": "What is prompt flow?", "ground_truth": "A tool for LLM apps."},
|
|
"outputs": {
|
|
"answer": "Prompt flow is a tool to build LLM applications.",
|
|
"context": "Prompt flow is an open-source tool for building LLM applications.",
|
|
},
|
|
},
|
|
]
|
|
wf = create_workflow()
|
|
result = await wf.run(EvalInput(chat_history=chat_history))
|
|
scores = result.get_outputs()[0]
|
|
assert isinstance(scores, dict)
|
|
assert "answer_relevance" in scores
|
|
assert "grounding" in scores
|
|
print(f"PASS: test_single_row (scores={scores})")
|
|
|
|
|
|
async def test_selective_metrics():
|
|
"""Test with only some metrics enabled"""
|
|
chat_history = [
|
|
{
|
|
"inputs": {"question": "Hello", "ground_truth": "Hi"},
|
|
"outputs": {"answer": "Hi there!", "context": "Greeting context."},
|
|
},
|
|
]
|
|
wf = create_workflow()
|
|
result = await wf.run(EvalInput(chat_history=chat_history, metrics="creativity,answer_relevance"))
|
|
scores = result.get_outputs()[0]
|
|
assert scores["grounding"] is None
|
|
assert scores["conversation_quality"] is None
|
|
print(f"PASS: test_selective_metrics (scores={scores})")
|
|
|
|
|
|
async def test_data_jsonl():
|
|
"""Run eval on every row in data.jsonl"""
|
|
data_path = Path(__file__).parent / "data.jsonl"
|
|
rows = [json.loads(line) for line in data_path.read_text(encoding="utf-8").splitlines() if line.strip()]
|
|
wf = create_workflow()
|
|
for i, row in enumerate(rows):
|
|
result = await wf.run(EvalInput(
|
|
chat_history=row["chat_history"],
|
|
metrics=row.get("metrics", "creativity,conversation_quality,answer_relevance,grounding"),
|
|
))
|
|
scores = result.get_outputs()[0]
|
|
assert isinstance(scores, dict), f"Row {i}: expected dict, got {type(scores)}"
|
|
print(f" Row {i}: scores={scores}")
|
|
print(f"PASS: test_data_jsonl ({len(rows)} rows)")
|
|
|
|
|
|
async def main():
|
|
await test_single_row()
|
|
await test_selective_metrics()
|
|
await test_data_jsonl()
|
|
print("\nAll tests passed!")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
asyncio.run(main())
|