zhanghongyu_0626
bcd6175d4e
- Introduced `analyst_auth_adapter.py` for managing authentication context and access control for the data analysis agent. - Added new API endpoints in `analyst.py` for chat, dashboard, asset management, and metrics, utilizing the new authentication context. - Created Pydantic models in `analyst_schemas.py` for request and response structures, ensuring consistent data handling. - Updated SQL guard logic in `sql_guard.py` to enforce access restrictions based on user roles and contexts. - Implemented migration scripts for new database tables related to the data analysis agent, enhancing data management capabilities. - Removed legacy authentication code from `auth.py`, streamlining the authentication process. This update significantly enhances the data analysis capabilities, providing a robust framework for querying and managing data securely.
23 lines
580 B
Python
23 lines
580 B
Python
"""llm 客户端测试（extract_sql 纯逻辑 + DeepSeek 真实冒烟）。"""
|
|
import unittest
|
|
|
|
from app.service.llm import extract_sql
|
|
|
|
|
|
class TestExtractSql(unittest.TestCase):
|
|
def test_plain(self):
|
|
self.assertEqual(extract_sql("SELECT 1"), "SELECT 1")
|
|
|
|
def test_fenced(self):
|
|
self.assertEqual(
|
|
extract_sql("结果如下：\n```sql\nSELECT 1\n```"),
|
|
"SELECT 1",
|
|
)
|
|
|
|
def test_fenced_no_lang(self):
|
|
self.assertEqual(extract_sql("```\nSELECT 2\n```"), "SELECT 2")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|