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chore: import upstream snapshot with attribution
2026-07-13 13:39:52 +08:00

99 lines
3.1 KiB
Python

import os
import unittest
import promptflow
from base_test import BaseTest
from promptflow._sdk._errors import InvalidRunStatusError
class TestChatWithPDF(BaseTest):
def setUp(self):
super().setUp()
self.pf = promptflow.PFClient()
def tearDown(self) -> None:
return super().tearDown()
def test_run_chat_with_pdf(self):
result = self.pf.test(
flow=self.flow_path,
inputs={
"chat_history": [],
"pdf_url": "https://arxiv.org/pdf/1810.04805.pdf",
"question": "BERT stands for?",
"config": self.config_2k_context,
},
)
print(result)
self.assertTrue(
result["answer"].find(
"Bidirectional Encoder Representations from Transformers"
)
!= -1
)
def test_bulk_run_chat_with_pdf(self):
run = self.create_chat_run()
self.pf.stream(run) # wait for completion
self.assertEqual(run.status, "Completed")
details = self.pf.get_details(run)
self.assertEqual(details.shape[0], 3)
def test_eval(self):
run_2k, eval_groundedness_2k, eval_pi_2k = self.run_eval_with_config(
self.config_2k_context,
display_name="chat_with_pdf_2k_context",
)
run_3k, eval_groundedness_3k, eval_pi_3k = self.run_eval_with_config(
self.config_3k_context,
display_name="chat_with_pdf_3k_context",
)
self.check_run_basics(run_2k)
self.check_run_basics(run_3k)
self.check_run_basics(eval_groundedness_2k)
self.check_run_basics(eval_pi_2k)
self.check_run_basics(eval_groundedness_3k)
self.check_run_basics(eval_pi_3k)
def test_bulk_run_valid_mapping(self):
run = self.create_chat_run(
column_mapping={
"question": "${data.question}",
"pdf_url": "${data.pdf_url}",
"chat_history": "${data.chat_history}",
"config": self.config_2k_context,
}
)
self.pf.stream(run) # wait for completion
self.assertEqual(run.status, "Completed")
details = self.pf.get_details(run)
self.assertEqual(details.shape[0], 3)
def test_bulk_run_mapping_missing_one_column(self):
data_path = os.path.join(
self.flow_path, "data/invalid-data-missing-column.jsonl"
)
with self.assertRaises(InvalidRunStatusError):
self.create_chat_run(
column_mapping={
"question": "${data.question}",
},
data=data_path
)
def test_bulk_run_invalid_mapping(self):
with self.assertRaises(InvalidRunStatusError):
self.create_chat_run(
column_mapping={
"question": "${data.question_not_exist}",
"pdf_url": "${data.pdf_url}",
"chat_history": "${data.chat_history}",
}
)
if __name__ == "__main__":
unittest.main()