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245 lines
9.6 KiB
Python
245 lines
9.6 KiB
Python
"""Unit tests for feedback exports using SQLite-backed ORM rows.
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The export query joins five tables and applies its filters in SQL, so these tests
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use a real SQLite session instead of stubbing ``Session.execute`` results.
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"""
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import json
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from datetime import datetime
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from decimal import Decimal
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from typing import TypedDict
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import pytest
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from sqlalchemy.orm import Session
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from models.account import Account
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from models.enums import FeedbackFromSource, FeedbackRating
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from models.model import App, AppMode, Conversation, ConversationFromSource, IconType, Message, MessageFeedback
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from services.feedback_service import FeedbackService
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APP_ID = "11111111-1111-1111-1111-111111111111"
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TENANT_ID = "22222222-2222-2222-2222-222222222222"
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CONVERSATION_ID = "33333333-3333-3333-3333-333333333333"
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MESSAGE_ID = "44444444-4444-4444-4444-444444444444"
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ACCOUNT_ID = "55555555-5555-5555-5555-555555555555"
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END_USER_ID = "66666666-6666-6666-6666-666666666666"
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class FeedbackSample(TypedDict):
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app: App
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conversation: Conversation
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message: Message
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user_feedback: MessageFeedback
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admin_feedback: MessageFeedback
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@pytest.fixture
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def sample_data(sqlite_session: Session) -> FeedbackSample:
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"""Persist a complete user/admin feedback graph for export queries."""
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app = App(
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tenant_id=TENANT_ID,
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name="Test App",
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description="",
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mode=AppMode.CHAT,
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icon_type=IconType.EMOJI,
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icon="🤖",
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icon_background="#FFFFFF",
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enable_site=False,
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enable_api=False,
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max_active_requests=0,
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)
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app.id = APP_ID
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conversation = Conversation(
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app_id=APP_ID,
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mode=AppMode.CHAT,
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name="Test Conversation",
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from_source=ConversationFromSource.API,
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from_end_user_id=END_USER_ID,
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)
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conversation.id = CONVERSATION_ID
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conversation._inputs = {}
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message = Message(
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app_id=APP_ID,
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conversation_id=CONVERSATION_ID,
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query="What is AI?",
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message={"role": "user", "content": "What is AI?"},
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answer="AI is artificial intelligence.",
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message_unit_price=Decimal(0),
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answer_unit_price=Decimal(0),
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currency="USD",
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from_source=ConversationFromSource.API,
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from_end_user_id=END_USER_ID,
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created_at=datetime(2024, 1, 1, 10, 0, 0),
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)
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message.id = MESSAGE_ID
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message._inputs = {"query": "What is AI?"}
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account = Account(name="Admin User", email="admin@example.com")
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account.id = ACCOUNT_ID
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user_feedback = MessageFeedback(
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app_id=APP_ID,
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conversation_id=CONVERSATION_ID,
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message_id=MESSAGE_ID,
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rating=FeedbackRating.LIKE,
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from_source=FeedbackFromSource.USER,
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content="Great answer!",
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from_end_user_id=END_USER_ID,
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)
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user_feedback.created_at = datetime(2024, 1, 1, 10, 5, 0)
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admin_feedback = MessageFeedback(
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app_id=APP_ID,
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conversation_id=CONVERSATION_ID,
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message_id=MESSAGE_ID,
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rating=FeedbackRating.DISLIKE,
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from_source=FeedbackFromSource.ADMIN,
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content="Could be more detailed",
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from_account_id=ACCOUNT_ID,
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)
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admin_feedback.created_at = datetime(2024, 1, 1, 10, 10, 0)
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sqlite_session.add_all([app, conversation, message, account, user_feedback, admin_feedback])
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sqlite_session.commit()
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return {
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"app": app,
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"conversation": conversation,
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"message": message,
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"user_feedback": user_feedback,
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"admin_feedback": admin_feedback,
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}
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@pytest.mark.parametrize(
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"sqlite_session",
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[(App, Conversation, Message, MessageFeedback, Account)],
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indirect=True,
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)
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class TestFeedbackService:
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"""Exercise feedback export formatting and its database-side filters."""
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def test_export_feedbacks_csv_format(self, sqlite_session: Session, sample_data: FeedbackSample) -> None:
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result = FeedbackService.export_feedbacks(
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app_id=APP_ID,
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session=sqlite_session,
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from_source=FeedbackFromSource.USER,
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format_type="csv",
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)
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assert "text/csv" in result.headers["Content-Type"]
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assert "attachment" in result.headers["Content-Disposition"]
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csv_content = result.get_data(as_text=True)
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assert "feedback_id" in csv_content
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assert "app_name" in csv_content
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assert "conversation_id" in csv_content
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assert sample_data["app"].name in csv_content
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assert sample_data["message"].query in csv_content
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assert sample_data["user_feedback"].content in csv_content
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assert sample_data["admin_feedback"].content not in csv_content
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def test_export_feedbacks_json_format(self, sqlite_session: Session, sample_data: FeedbackSample) -> None:
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result = FeedbackService.export_feedbacks(
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app_id=APP_ID,
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session=sqlite_session,
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from_source=FeedbackFromSource.ADMIN,
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format_type="json",
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)
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assert "application/json" in result.headers["Content-Type"]
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assert "attachment" in result.headers["Content-Disposition"]
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json_content = json.loads(result.get_data(as_text=True))
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assert json_content["export_info"]["app_id"] == APP_ID
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assert json_content["export_info"]["total_records"] == 1
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assert json_content["feedback_data"][0]["from_account_name"] == "Admin User"
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def test_export_feedbacks_with_filters(self, sqlite_session: Session, sample_data: FeedbackSample) -> None:
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result = FeedbackService.export_feedbacks(
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app_id=APP_ID,
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session=sqlite_session,
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from_source=FeedbackFromSource.ADMIN,
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rating=FeedbackRating.DISLIKE,
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has_comment=True,
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start_date="2024-01-01",
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end_date="2024-12-31",
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format_type="csv",
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)
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csv_content = result.get_data(as_text=True)
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assert sample_data["admin_feedback"].content in csv_content
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assert sample_data["user_feedback"].content not in csv_content
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assert len([line for line in csv_content.strip().splitlines() if line.strip()]) == 2
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def test_export_feedbacks_no_data(self, sqlite_session: Session, sample_data: FeedbackSample) -> None:
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result = FeedbackService.export_feedbacks(
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app_id="77777777-7777-7777-7777-777777777777",
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session=sqlite_session,
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format_type="csv",
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)
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csv_content = result.get_data(as_text=True)
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assert "text/csv" in result.headers["Content-Type"]
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assert "feedback_id" in csv_content
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assert "app_name" in csv_content
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assert "conversation_id" in csv_content
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assert len([line for line in csv_content.strip().splitlines() if line.strip()]) == 1
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def test_export_feedbacks_invalid_date_format(self, sqlite_session: Session, sample_data: FeedbackSample) -> None:
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with pytest.raises(ValueError, match="Invalid start_date format"):
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FeedbackService.export_feedbacks(
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app_id=APP_ID,
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session=sqlite_session,
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start_date="invalid-date-format",
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)
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with pytest.raises(ValueError, match="Invalid end_date format"):
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FeedbackService.export_feedbacks(
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app_id=APP_ID,
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session=sqlite_session,
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end_date="invalid-date-format",
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)
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def test_export_feedbacks_invalid_format(self, sqlite_session: Session, sample_data: FeedbackSample) -> None:
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with pytest.raises(ValueError, match="Unsupported format"):
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FeedbackService.export_feedbacks(app_id=APP_ID, session=sqlite_session, format_type="xml")
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def test_export_feedbacks_long_response_truncation(
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self, sqlite_session: Session, sample_data: FeedbackSample
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) -> None:
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sample_data["message"].answer = "A" * 600
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sqlite_session.commit()
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result = FeedbackService.export_feedbacks(
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app_id=APP_ID,
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session=sqlite_session,
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from_source=FeedbackFromSource.USER,
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format_type="json",
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)
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exported_answer = json.loads(result.get_data(as_text=True))["feedback_data"][0]["ai_response"]
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assert exported_answer == "A" * 500 + "..."
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def test_export_feedbacks_unicode_content(self, sqlite_session: Session, sample_data: FeedbackSample) -> None:
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sample_data["message"].query = "什么是人工智能？"
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sample_data["message"].answer = "人工智能是模拟人类智能的技术。"
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sample_data["user_feedback"].content = "回答不够详细，需要更多信息"
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sqlite_session.commit()
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result = FeedbackService.export_feedbacks(
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app_id=APP_ID,
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session=sqlite_session,
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from_source=FeedbackFromSource.USER,
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format_type="csv",
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)
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csv_content = result.get_data(as_text=True)
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assert "什么是人工智能？" in csv_content
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assert "回答不够详细，需要更多信息" in csv_content
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assert "人工智能是模拟人类智能的技术" in csv_content
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def test_export_feedbacks_emoji_ratings(self, sqlite_session: Session, sample_data: FeedbackSample) -> None:
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result = FeedbackService.export_feedbacks(app_id=APP_ID, session=sqlite_session, format_type="json")
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feedback_data = json.loads(result.get_data(as_text=True))["feedback_data"]
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assert len(feedback_data) == 2
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like_feedback = next(item for item in feedback_data if item["feedback_rating_raw"] == "like")
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dislike_feedback = next(item for item in feedback_data if item["feedback_rating_raw"] == "dislike")
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assert like_feedback["feedback_rating"] == "👍"
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assert dislike_feedback["feedback_rating"] == "👎"
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