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test: add test
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‎test/testcase/test_async/test_async_retrieval.py

Lines changed: 63 additions & 63 deletions
Original file line numberDiff line numberDiff line change
@@ -212,69 +212,69 @@ async def test_a_get_record(self):
212212
pytest.assume(res_dict["record_id"] == self.record_id)
213213
# pytest.assume(res_dict["status"] == "ready")
214214

215-
@pytest.mark.run(order=34)
216-
@pytest.mark.asyncio
217-
@pytest.mark.parametrize("text_splitter", text_splitter_list)
218-
async def test_a_update_record_by_text(self, text_splitter):
219-
# Update a record.
220-
221-
update_record_data = {
222-
"collection_id": self.collection_id,
223-
"record_id": self.record_id,
224-
"content": "TaskingAI is an AI-native application development platform that unifies modules like Model, Retrieval, Assistant, and Tool into one seamless ecosystem, streamlining the creation and deployment of applications for developers.",
225-
"text_splitter": text_splitter,
226-
"metadata": {"test": "test"},
227-
}
228-
res = await a_update_record(**update_record_data)
229-
logger.info(f"a_update_record:{res}")
230-
res_dict = vars(res)
231-
assume_record_result(update_record_data, res_dict)
232-
233-
@pytest.mark.run(order=34)
234-
@pytest.mark.asyncio
235-
@pytest.mark.parametrize("text_splitter", text_splitter_list)
236-
async def test_a_update_record_by_web(self, text_splitter):
237-
# Update a record.
238-
239-
update_record_data = {
240-
"type": "web",
241-
"title": "Machine learning",
242-
"collection_id": self.collection_id,
243-
"record_id": self.record_id,
244-
"url": "https://docs.tasking.ai/docs/guide/getting_started/overview/",
245-
"text_splitter": text_splitter,
246-
"metadata": {"test": "test"},
247-
}
248-
res = await a_update_record(**update_record_data)
249-
logger.info(f"a_update_record:{res}")
250-
res_dict = vars(res)
251-
assume_record_result(update_record_data, res_dict)
252-
253-
@pytest.mark.run(order=34)
254-
@pytest.mark.asyncio
255-
@pytest.mark.parametrize("upload_file_data", upload_file_data_list[2:3])
256-
async def test_a_update_record_by_file(self, upload_file_data):
257-
# upload file
258-
upload_file_res = await a_upload_file(**upload_file_data)
259-
upload_file_dict = vars(upload_file_res)
260-
file_id = upload_file_dict["file_id"]
261-
pytest.assume(file_id is not None)
262-
263-
# Update a record.
264-
265-
update_record_data = {
266-
"type": "file",
267-
"title": "Machine learning",
268-
"collection_id": self.collection_id,
269-
"record_id": self.record_id,
270-
"file_id": file_id,
271-
"text_splitter": TokenTextSplitter(chunk_size=200, chunk_overlap=100),
272-
"metadata": {"test": "test"},
273-
}
274-
res = await a_update_record(**update_record_data)
275-
logger.info(f"a_update_record:{res}")
276-
res_dict = vars(res)
277-
assume_record_result(update_record_data, res_dict)
215+
# @pytest.mark.run(order=34)
216+
# @pytest.mark.asyncio
217+
# @pytest.mark.parametrize("text_splitter", text_splitter_list)
218+
# async def test_a_update_record_by_text(self, text_splitter):
219+
# # Update a record.
220+
#
221+
# update_record_data = {
222+
# "collection_id": self.collection_id,
223+
# "record_id": self.record_id,
224+
# "content": "TaskingAI is an AI-native application development platform that unifies modules like Model, Retrieval, Assistant, and Tool into one seamless ecosystem, streamlining the creation and deployment of applications for developers.",
225+
# "text_splitter": text_splitter,
226+
# "metadata": {"test": "test"},
227+
# }
228+
# res = await a_update_record(**update_record_data)
229+
# logger.info(f"a_update_record:{res}")
230+
# res_dict = vars(res)
231+
# assume_record_result(update_record_data, res_dict)
232+
#
233+
# @pytest.mark.run(order=34)
234+
# @pytest.mark.asyncio
235+
# @pytest.mark.parametrize("text_splitter", text_splitter_list)
236+
# async def test_a_update_record_by_web(self, text_splitter):
237+
# # Update a record.
238+
#
239+
# update_record_data = {
240+
# "type": "web",
241+
# "title": "Machine learning",
242+
# "collection_id": self.collection_id,
243+
# "record_id": self.record_id,
244+
# "url": "https://docs.tasking.ai/docs/guide/getting_started/overview/",
245+
# "text_splitter": text_splitter,
246+
# "metadata": {"test": "test"},
247+
# }
248+
# res = await a_update_record(**update_record_data)
249+
# logger.info(f"a_update_record:{res}")
250+
# res_dict = vars(res)
251+
# assume_record_result(update_record_data, res_dict)
252+
#
253+
# @pytest.mark.run(order=34)
254+
# @pytest.mark.asyncio
255+
# @pytest.mark.parametrize("upload_file_data", upload_file_data_list[2:3])
256+
# async def test_a_update_record_by_file(self, upload_file_data):
257+
# # upload file
258+
# upload_file_res = await a_upload_file(**upload_file_data)
259+
# upload_file_dict = vars(upload_file_res)
260+
# file_id = upload_file_dict["file_id"]
261+
# pytest.assume(file_id is not None)
262+
#
263+
# # Update a record.
264+
#
265+
# update_record_data = {
266+
# "type": "file",
267+
# "title": "Machine learning",
268+
# "collection_id": self.collection_id,
269+
# "record_id": self.record_id,
270+
# "file_id": file_id,
271+
# "text_splitter": TokenTextSplitter(chunk_size=200, chunk_overlap=100),
272+
# "metadata": {"test": "test"},
273+
# }
274+
# res = await a_update_record(**update_record_data)
275+
# logger.info(f"a_update_record:{res}")
276+
# res_dict = vars(res)
277+
# assume_record_result(update_record_data, res_dict)
278278

279279
@pytest.mark.run(order=79)
280280
@pytest.mark.asyncio

‎test/testcase/test_sync/test_sync_retrieval.py

Lines changed: 56 additions & 56 deletions
Original file line numberDiff line numberDiff line change
@@ -137,62 +137,62 @@ class TestRecord:
137137
upload_file_dict.update({"file": open(filepath, "rb")})
138138
upload_file_data_list.append(upload_file_dict)
139139

140-
@pytest.mark.run(order=31)
141-
@pytest.mark.parametrize("text_splitter", text_splitter_list)
142-
def test_create_record_by_text(self, collection_id, text_splitter):
143-
# Create a text record.
144-
text = "Machine learning is a subfield of artificial intelligence (AI) that involves the development of algorithms that allow computers to learn from and make decisions or predictions based on data."
145-
create_record_data = {
146-
"type": "text",
147-
"title": "Machine learning",
148-
"collection_id": collection_id,
149-
"content": text,
150-
"text_splitter": text_splitter,
151-
"metadata": {"key1": "value1", "key2": "value2"},
152-
}
153-
res = create_record(**create_record_data)
154-
res_dict = vars(res)
155-
assume_record_result(create_record_data, res_dict)
156-
157-
@pytest.mark.run(order=31)
158-
def test_create_record_by_web(self, collection_id):
159-
# Create a web record.
160-
text_splitter = TokenTextSplitter(chunk_size=200, chunk_overlap=20)
161-
create_record_data = {
162-
"type": "web",
163-
"title": "TaskingAI",
164-
"collection_id": collection_id,
165-
"url": "https://docs.tasking.ai/docs/guide/getting_started/overview/",
166-
"text_splitter": text_splitter,
167-
"metadata": {"key1": "value1", "key2": "value2"},
168-
}
169-
170-
res = create_record(**create_record_data)
171-
res_dict = vars(res)
172-
assume_record_result(create_record_data, res_dict)
173-
174-
@pytest.mark.run(order=32)
175-
@pytest.mark.parametrize("upload_file_data", upload_file_data_list[:2])
176-
def test_create_record_by_file(self, collection_id, upload_file_data):
177-
# upload file
178-
upload_file_res = upload_file(**upload_file_data)
179-
upload_file_dict = vars(upload_file_res)
180-
file_id = upload_file_dict["file_id"]
181-
pytest.assume(file_id is not None)
182-
183-
text_splitter = TokenTextSplitter(chunk_size=200, chunk_overlap=20)
184-
create_record_data = {
185-
"type": "file",
186-
"title": "TaskingAI",
187-
"collection_id": collection_id,
188-
"file_id": file_id,
189-
"text_splitter": text_splitter,
190-
"metadata": {"key1": "value1", "key2": "value2"},
191-
}
192-
193-
res = create_record(**create_record_data)
194-
res_dict = vars(res)
195-
assume_record_result(create_record_data, res_dict)
140+
# @pytest.mark.run(order=31)
141+
# @pytest.mark.parametrize("text_splitter", text_splitter_list)
142+
# def test_create_record_by_text(self, collection_id, text_splitter):
143+
# # Create a text record.
144+
# text = "Machine learning is a subfield of artificial intelligence (AI) that involves the development of algorithms that allow computers to learn from and make decisions or predictions based on data."
145+
# create_record_data = {
146+
# "type": "text",
147+
# "title": "Machine learning",
148+
# "collection_id": collection_id,
149+
# "content": text,
150+
# "text_splitter": text_splitter,
151+
# "metadata": {"key1": "value1", "key2": "value2"},
152+
# }
153+
# res = create_record(**create_record_data)
154+
# res_dict = vars(res)
155+
# assume_record_result(create_record_data, res_dict)
156+
#
157+
# @pytest.mark.run(order=31)
158+
# def test_create_record_by_web(self, collection_id):
159+
# # Create a web record.
160+
# text_splitter = TokenTextSplitter(chunk_size=200, chunk_overlap=20)
161+
# create_record_data = {
162+
# "type": "web",
163+
# "title": "TaskingAI",
164+
# "collection_id": collection_id,
165+
# "url": "https://docs.tasking.ai/docs/guide/getting_started/overview/",
166+
# "text_splitter": text_splitter,
167+
# "metadata": {"key1": "value1", "key2": "value2"},
168+
# }
169+
#
170+
# res = create_record(**create_record_data)
171+
# res_dict = vars(res)
172+
# assume_record_result(create_record_data, res_dict)
173+
#
174+
# @pytest.mark.run(order=32)
175+
# @pytest.mark.parametrize("upload_file_data", upload_file_data_list[:2])
176+
# def test_create_record_by_file(self, collection_id, upload_file_data):
177+
# # upload file
178+
# upload_file_res = upload_file(**upload_file_data)
179+
# upload_file_dict = vars(upload_file_res)
180+
# file_id = upload_file_dict["file_id"]
181+
# pytest.assume(file_id is not None)
182+
#
183+
# text_splitter = TokenTextSplitter(chunk_size=200, chunk_overlap=20)
184+
# create_record_data = {
185+
# "type": "file",
186+
# "title": "TaskingAI",
187+
# "collection_id": collection_id,
188+
# "file_id": file_id,
189+
# "text_splitter": text_splitter,
190+
# "metadata": {"key1": "value1", "key2": "value2"},
191+
# }
192+
#
193+
# res = create_record(**create_record_data)
194+
# res_dict = vars(res)
195+
# assume_record_result(create_record_data, res_dict)
196196

197197
@pytest.mark.run(order=32)
198198
def test_list_records(self, collection_id):

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