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	For get and filter queries of NamedUserGroup, realm_for_sharding field is used instead of realm field, as directly using realm_for_sharding field on NamedUserGroup makes the query faster than using realm present on the base UserGroup table.
		
			
				
	
	
		
			216 lines
		
	
	
		
			8.9 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			216 lines
		
	
	
		
			8.9 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
import os
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import warnings
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from datetime import datetime, timezone
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from unittest import mock
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import orjson
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import time_machine
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from django.conf import settings
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from typing_extensions import override
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from analytics.models import UserCount
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from zerver.actions.realm_settings import do_change_realm_permission_group_setting
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from zerver.lib.test_classes import ZulipTestCase
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from zerver.models import NamedUserGroup
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from zerver.models.groups import SystemGroups
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from zerver.models.realms import get_realm
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warnings.filterwarnings("ignore", category=UserWarning, module="pydantic")
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warnings.filterwarnings("ignore", category=DeprecationWarning, module="pydantic")
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warnings.filterwarnings("ignore", category=DeprecationWarning, module="litellm")
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# Avoid network query to fetch the model cost map.
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os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
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import litellm
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# Fixture file to store recorded responses
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LLM_FIXTURES_FILE = "zerver/tests/fixtures/litellm/summary.json"
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class MessagesSummaryTestCase(ZulipTestCase):
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    @override
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    def setUp(self) -> None:
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        super().setUp()
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        self.user = self.example_user("iago")
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        self.topic_name = "New feature launch"
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        self.channel_name = "Zulip features"
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        self.login_user(self.user)
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        self.subscribe(self.user, self.channel_name)
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        content = "Zulip just launched a feature to generate summary of messages."
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        self.send_stream_message(
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            self.user, self.channel_name, content=content, topic_name=self.topic_name
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        )
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        content = "Sounds awesome! This will **greatly** help me when catching up."
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        self.send_stream_message(
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            self.user, self.channel_name, content=content, topic_name=self.topic_name
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        )
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        # Tests fail on the last day of the month due to us capturing the credit usage for that day
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        # on the first of the next month, so we need to set the date to a different day.
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        not_last_day_of_any_month = datetime(2025, 2, 18, 1, tzinfo=timezone.utc)
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        self.mocked_time_patcher = time_machine.travel(not_last_day_of_any_month, tick=False)
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        self.mocked_time_patcher.start()
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        if settings.GENERATE_LITELLM_FIXTURES:  # nocoverage
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            self.patcher = mock.patch("litellm.completion", wraps=litellm.completion)
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            self.mocked_completion = self.patcher.start()
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    @override
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    def tearDown(self) -> None:
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        self.mocked_time_patcher.stop()
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        if settings.GENERATE_LITELLM_FIXTURES:  # nocoverage
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            self.patcher.stop()
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        super().tearDown()
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    def test_summarize_messages_in_topic(self) -> None:
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        narrow = orjson.dumps([["channel", self.channel_name], ["topic", self.topic_name]]).decode()
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        if settings.GENERATE_LITELLM_FIXTURES:  # nocoverage
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            # NOTE: You need have proper credentials in zproject/dev-secrets.conf
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            # to generate the fixtures. (Tested using aws bedrock.)
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            # Trigger the API call to extract the arguments.
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            self.client_get("/json/messages/summary", dict(narrow=narrow))
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            call_args = self.mocked_completion.call_args
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            # Once we have the arguments, call the original method and save its response.
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            response = self.mocked_completion(**call_args.kwargs).json()
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            with open(LLM_FIXTURES_FILE, "wb") as f:
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                fixture_data = {
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                    # Only store model and messages.
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                    # We don't want to store any secrets.
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                    "model": call_args.kwargs["model"],
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                    "messages": call_args.kwargs["messages"],
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                    "response": response,
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                }
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                f.write(orjson.dumps(fixture_data, option=orjson.OPT_INDENT_2) + b"\n")
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            return
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        # In this code path, we test using the fixtures.
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        with open(LLM_FIXTURES_FILE, "rb") as f:
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            fixture_data = orjson.loads(f.read())
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        # Block summary requests if budget set to 0.
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        with self.settings(
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            TOPIC_SUMMARIZATION_MODEL="groq/llama-3.3-70b-versatile",
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            MAX_PER_USER_MONTHLY_AI_COST=0,
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        ):
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            response = self.client_get("/json/messages/summary")
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            self.assert_json_error_contains(response, "Reached monthly limit for AI credits.")
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        # Fake credentials to ensure we crash if actual network
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        # requests occur, which would reflect a problem with how the
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        # fixtures were set up.
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        with self.settings(
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            TOPIC_SUMMARIZATION_MODEL="groq/llama-3.3-70b-versatile",
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            TOPIC_SUMMARIZATION_API_KEY="test",
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        ):
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            input_tokens = fixture_data["response"]["usage"]["prompt_tokens"]
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            output_tokens = fixture_data["response"]["usage"]["completion_tokens"]
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            credits_used = (output_tokens * settings.OUTPUT_COST_PER_GIGATOKEN) + (
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                input_tokens * settings.INPUT_COST_PER_GIGATOKEN
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            )
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            self.assertFalse(
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                UserCount.objects.filter(
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                    property="ai_credit_usage::day", value=credits_used, user_id=self.user.id
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                ).exists()
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            )
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            with mock.patch("litellm.completion", return_value=fixture_data["response"]):
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                payload = self.client_get("/json/messages/summary", dict(narrow=narrow))
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                self.assertEqual(payload.status_code, 200)
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            # Check that we recorded this usage.
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            self.assertTrue(
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                UserCount.objects.filter(
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                    property="ai_credit_usage::day", value=credits_used, user_id=self.user.id
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                ).exists()
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            )
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        # If we reached the credit usage limit, block summary requests.
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        with self.settings(
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            TOPIC_SUMMARIZATION_MODEL="groq/llama-3.3-70b-versatile",
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            MAX_PER_USER_MONTHLY_AI_COST=credits_used / 1000000000,
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        ):
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            response = self.client_get("/json/messages/summary")
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            self.assert_json_error_contains(response, "Reached monthly limit for AI credits.")
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    def test_permission_to_summarize_message_in_topics(self) -> None:
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        narrow = orjson.dumps([["channel", self.channel_name], ["topic", self.topic_name]]).decode()
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        realm = get_realm("zulip")
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        moderators_group = NamedUserGroup.objects.get(
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            name=SystemGroups.MODERATORS, realm_for_sharding=realm, is_system_group=True
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        )
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        do_change_realm_permission_group_setting(
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            realm,
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            "can_summarize_topics_group",
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            moderators_group,
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            acting_user=None,
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        )
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        # In this code path, we test using the fixtures.
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        with open(LLM_FIXTURES_FILE, "rb") as f:
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            fixture_data = orjson.loads(f.read())
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        def check_message_summary_permission(user: str, expect_fail: bool = False) -> None:
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            self.login(user)
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            with (
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                self.settings(
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                    TOPIC_SUMMARIZATION_MODEL="groq/llama-3.3-70b-versatile",
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                    TOPIC_SUMMARIZATION_API_KEY="test",
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                ),
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                mock.patch("litellm.completion", return_value=fixture_data["response"]),
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            ):
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                result = self.client_get("/json/messages/summary", dict(narrow=narrow))
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            if expect_fail:
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                self.assert_json_error(result, "Insufficient permission")
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            else:
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                self.assert_json_success(result)
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        check_message_summary_permission("hamlet", expect_fail=True)
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        check_message_summary_permission("shiva")
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        nobody_group = NamedUserGroup.objects.get(
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            name=SystemGroups.NOBODY, realm_for_sharding=realm, is_system_group=True
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        )
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        do_change_realm_permission_group_setting(
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            realm,
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            "can_summarize_topics_group",
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            nobody_group,
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            acting_user=None,
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        )
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        check_message_summary_permission("desdemona", expect_fail=True)
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        hamletcharacters_group = NamedUserGroup.objects.get(
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            name="hamletcharacters", realm_for_sharding=realm
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        )
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        do_change_realm_permission_group_setting(
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            realm,
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            "can_summarize_topics_group",
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            hamletcharacters_group,
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            acting_user=None,
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        )
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        check_message_summary_permission("desdemona", expect_fail=True)
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        check_message_summary_permission("othello", expect_fail=True)
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        check_message_summary_permission("hamlet")
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        check_message_summary_permission("cordelia")
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        setting_group = self.create_or_update_anonymous_group_for_setting(
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            [self.example_user("othello")], [moderators_group]
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        )
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        do_change_realm_permission_group_setting(
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            realm,
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            "can_summarize_topics_group",
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            setting_group,
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            acting_user=None,
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        )
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        check_message_summary_permission("cordelia", expect_fail=True)
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        check_message_summary_permission("hamlet", expect_fail=True)
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        check_message_summary_permission("othello")
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        check_message_summary_permission("shiva")
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        check_message_summary_permission("desdemona")
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