chore: import upstream snapshot with attribution

sdk/python/test/test_frontend_api/test_chunk.py

@@ -0,0 +1,74 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+
+from common import create_dataset, list_dataset, rm_dataset, upload_file
+from common import list_document, get_docs_info, parse_docs
+from time import sleep
+from timeit import default_timer as timer
+
+
+def test_parse_txt_document(get_auth):
+    # create dataset
+    res = create_dataset(get_auth, {"name": "test_parse_txt_document"})
+    assert res.get("code") == 0, f"{res.get('message')}"
+
+    # list dataset
+    page_number = 1
+    dataset_list = []
+    dataset_id = None
+    while True:
+        res = list_dataset(get_auth, {"page": page_number, "page_size": 150})
+        data = res.get("data")
+        if isinstance(data, dict):
+            data = data.get("kbs", [])
+        for item in data:
+            dataset_id = item.get("id")
+            dataset_list.append(dataset_id)
+        if len(dataset_list) < page_number * 150:
+            break
+        page_number += 1
+
+    filename = "ragflow_test.txt"
+    res = upload_file(get_auth, dataset_id, f"../test_sdk_api/test_data/{filename}")
+    assert res.get("code") == 0, f"{res.get('message')}"
+
+    res = list_document(get_auth, dataset_id)
+
+    doc_id_list = []
+    for doc in res["data"]["docs"]:
+        doc_id_list.append(doc["id"])
+
+    res = get_docs_info(get_auth, dataset_id, doc_ids=doc_id_list)
+    print(doc_id_list)
+    doc_count = len(doc_id_list)
+    res = parse_docs(get_auth, doc_id_list)
+
+    start_ts = timer()
+    while True:
+        res = get_docs_info(get_auth, dataset_id, doc_ids=doc_id_list)
+        finished_count = 0
+        for doc_info in res["data"]:
+            if doc_info["progress"] == 1:
+                finished_count += 1
+        if finished_count == doc_count:
+            break
+        sleep(1)
+    print("time cost {:.1f}s".format(timer() - start_ts))
+
+    # delete dataset
+    if dataset_list:
+        res = rm_dataset(get_auth, dataset_list)
+        assert res.get("code") == 0, f"{res.get('message')}"
+    print(f"{len(dataset_list)} datasets are deleted")