1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
|
# coding=utf-8
# ------------------------------------
# Copyright (c) Microsoft.
# Licensed under the MIT License.
# ------------------------------------
"""
FILE: sample_import_project.py
DESCRIPTION:
This sample demonstrates how to import assets into a **Text Authoring** project.
USAGE:
python sample_import_project.py
REQUIRED ENV VARS (for AAD / DefaultAzureCredential):
AZURE_TEXT_ENDPOINT
AZURE_CLIENT_ID
AZURE_TENANT_ID
AZURE_CLIENT_SECRET
NOTE:
If you want to use AzureKeyCredential instead, set:
- AZURE_TEXT_ENDPOINT
- AZURE_TEXT_KEY
OPTIONAL ENV VARS:
PROJECT_NAME # defaults to "<project-name>"
LANGUAGE_TAG # defaults to "<language-tag>"
STORAGE_INPUT_CONTAINER_NAME # defaults to "<storage-container-name>"
DOC1_PATH # defaults to "<doc1-path>"
DOC2_PATH # defaults to "<doc2-path>"
"""
# [START text_authoring_import_project]
import os
from azure.identity import DefaultAzureCredential
from azure.core.exceptions import HttpResponseError
from azure.ai.textanalytics.authoring import TextAuthoringClient
from azure.ai.textanalytics.authoring.models import (
CreateProjectOptions,
ExportedProject,
ProjectSettings,
ExportedCustomSingleLabelClassificationProjectAsset,
ExportedCustomSingleLabelClassificationDocument,
ExportedDocumentClass,
ExportedClass,
ProjectKind,
StringIndexType,
)
def sample_import_project():
# settings
endpoint = os.environ["AZURE_TEXT_ENDPOINT"]
project_name = os.environ.get("PROJECT_NAME", "<project-name>")
language_tag = os.environ.get("LANGUAGE_TAG", "<language-tag>") # e.g., "en"
storage_container = os.environ.get("STORAGE_INPUT_CONTAINER_NAME", "<storage-container-name>")
doc1_path = os.environ.get("DOC1_PATH", "<doc1-path>") # e.g., "01.txt"
doc2_path = os.environ.get("DOC2_PATH", "<doc2-path>") # e.g., "02.txt"
# create a client with AAD
credential = DefaultAzureCredential()
client = TextAuthoringClient(endpoint, credential=credential)
# project-scoped client
project_client = client.get_project_client(project_name)
# ---------- Arrange metadata (project definition) ----------
project_metadata = CreateProjectOptions(
project_kind=ProjectKind.CUSTOM_SINGLE_LABEL_CLASSIFICATION,
storage_input_container_name=storage_container,
project_name=project_name,
language=language_tag,
description="Sample project imported via Python SDK.",
multilingual=False,
settings=ProjectSettings(),
)
# ---------- Arrange assets (classes + labeled documents) ----------
project_assets = ExportedCustomSingleLabelClassificationProjectAsset(
classes=[
ExportedClass(category="ClassA"),
ExportedClass(category="ClassB"),
ExportedClass(category="ClassC"),
],
documents=[
ExportedCustomSingleLabelClassificationDocument(
document_class=ExportedDocumentClass(category="ClassA"),
location=doc1_path,
language=language_tag,
),
ExportedCustomSingleLabelClassificationDocument(
document_class=ExportedDocumentClass(category="ClassB"),
location=doc2_path,
language=language_tag,
),
],
)
exported_project = ExportedProject(
project_file_version="2022-05-01",
string_index_type=StringIndexType.UTF16_CODE_UNIT,
metadata=project_metadata,
assets=project_assets,
)
# ---------- Import (LRO) with error handling ----------
poller = project_client.project.begin_import(body=exported_project)
try:
poller.result() # completes with None; raises on failure
print("Import completed.")
print(f"done: {poller.done()}")
print(f"status: {poller.status()}")
except HttpResponseError as e:
print(f"Operation failed: {e.message}")
print(e.error)
# [END text_authoring_import_project]
def main():
sample_import_project()
if __name__ == "__main__":
main()
|
