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hajimi
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import unittest
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import sys
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[1]
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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from ai_comment_dispatch import (
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AiCommentDispatcher,
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AiCommentSettings,
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CommentCandidate,
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DispatchTask,
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VirtualUser,
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extract_post_text,
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merge_candidates,
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select_balanced_candidates,
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)
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class FakeRepo:
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def __init__(self, article_candidates=None, post_candidates=None, daily_success=0, users=None):
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self.article_candidates = article_candidates or []
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self.post_candidates = post_candidates or []
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self.daily_success = daily_success
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self.users = users or []
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self.created_tasks = []
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self.saved_comments = []
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self.failed_tasks = []
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self.ensure_schema_called = False
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self.ensure_users_target = None
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def ensure_schema(self):
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self.ensure_schema_called = True
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def ensure_virtual_users(self, target_count):
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self.ensure_users_target = target_count
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return list(self.users)
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def count_daily_success(self, day_start, day_end):
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return self.daily_success
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def load_article_candidates(self, settings):
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return list(self.article_candidates)
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def load_post_candidates(self, settings):
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return list(self.post_candidates)
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def create_task(self, candidate, virtual_user, persona_key):
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task = DispatchTask(
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task_id=len(self.created_tasks) + 1,
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target_type=candidate.target_type,
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target_id=candidate.target_id,
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virtual_user_id=virtual_user.user_id,
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persona_key=persona_key,
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selection_sources=tuple(candidate.selection_sources),
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)
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self.created_tasks.append(task)
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return task
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def mark_task_success(self, task, comment_content):
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self.saved_comments.append((task, comment_content))
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def mark_task_failed(self, task, message):
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self.failed_tasks.append((task, message))
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class FakeClient:
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def __init__(self, outputs=None):
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self.outputs = outputs or {}
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self.calls = []
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def generate_comment(self, candidate, virtual_user, persona_key, settings):
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self.calls.append((candidate, virtual_user, persona_key))
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return self.outputs.get(
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(candidate.target_type, candidate.target_id),
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{"success": True, "content": f"{candidate.target_type}-{candidate.target_id}-comment"},
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)
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class AiCommentDispatchTest(unittest.TestCase):
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def test_merge_candidates_merges_selection_sources_by_target(self):
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merged = merge_candidates(
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[
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CommentCandidate("article", 10, "title-a", "body-a", ("cate:1",), created_at=100, rank_value=8),
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CommentCandidate("article", 10, "title-a", "body-a", ("top",), created_at=100, rank_value=8),
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CommentCandidate("article", 11, "title-b", "body-b", ("hot",), created_at=90, rank_value=5),
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]
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)
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self.assertEqual(len(merged), 2)
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self.assertEqual(merged[0].target_id, 10)
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self.assertEqual(set(merged[0].selection_sources), {"cate:1", "top"})
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def test_select_balanced_candidates_prefers_25_25_then_backfills(self):
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articles = [
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CommentCandidate("article", index, f"title-{index}", "body", (f"cate:{index}",), created_at=200 - index, rank_value=index)
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for index in range(1, 9)
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]
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posts = [
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CommentCandidate("post", index, "", f"post-{index}", (f"tag:{index}",), created_at=100 - index, rank_value=index)
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for index in range(1, 3)
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]
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selected = select_balanced_candidates(articles, posts, total_limit=6)
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self.assertEqual(len(selected), 6)
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self.assertEqual(sum(1 for item in selected if item.target_type == "post"), 2)
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self.assertEqual(sum(1 for item in selected if item.target_type == "article"), 4)
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self.assertEqual([item.target_id for item in selected[:3]], [1, 2, 3])
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def test_extract_post_text_prefers_image_only_analysis_content(self):
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content = extract_post_text(
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"",
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{
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"lottery_analysis_source": "image_only",
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"lottery_analysis_content": "杀码思路和冷热分析",
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},
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)
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self.assertEqual(content, "杀码思路和冷热分析")
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def test_dispatcher_stops_when_daily_cap_reached(self):
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repo = FakeRepo(daily_success=500, users=[VirtualUser(1, "ai_comment_0001", "AI评论员01", "data_analyst")])
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client = FakeClient()
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dispatcher = AiCommentDispatcher(repo, client)
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settings = AiCommentSettings(per_run=10, daily_cap=500, user_pool_size=100)
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summary = dispatcher.run(settings)
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self.assertTrue(repo.ensure_schema_called)
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self.assertEqual(repo.ensure_users_target, 100)
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self.assertEqual(summary["status"], "skipped")
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self.assertEqual(summary["reason"], "daily_cap_reached")
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self.assertEqual(len(repo.created_tasks), 0)
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self.assertEqual(len(client.calls), 0)
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def test_dispatcher_creates_tasks_and_marks_success_or_failure(self):
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article_candidates = [
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CommentCandidate("article", 101, "article-101", "body", ("cate:10",), created_at=10, rank_value=3),
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CommentCandidate("article", 102, "article-102", "body", ("hot",), created_at=9, rank_value=2),
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]
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post_candidates = [
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CommentCandidate("post", 201, "", "post-201", ("tag:14",), created_at=8, rank_value=5),
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CommentCandidate("post", 202, "", "post-202", ("tag:15",), created_at=7, rank_value=4),
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]
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users = [
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VirtualUser(1, "ai_comment_0001", "AI评论员01", "data_analyst"),
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VirtualUser(2, "ai_comment_0002", "AI评论员02", "old_fan"),
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VirtualUser(3, "ai_comment_0003", "AI评论员03", "coach_view"),
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VirtualUser(4, "ai_comment_0004", "AI评论员04", "night_shift_editor"),
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]
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repo = FakeRepo(article_candidates=article_candidates, post_candidates=post_candidates, users=users)
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client = FakeClient(
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outputs={
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("article", 101): {"success": True, "content": "文章评论A"},
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("article", 102): {"success": False, "error": "上游超时"},
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("post", 201): {"success": True, "content": "帖子评论B"},
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("post", 202): {"success": True, "content": "帖子评论C"},
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}
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)
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dispatcher = AiCommentDispatcher(repo, client)
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settings = AiCommentSettings(per_run=4, daily_cap=500, user_pool_size=4, concurrency=2)
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summary = dispatcher.run(settings)
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self.assertEqual(summary["status"], "success")
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self.assertEqual(summary["selected_count"], 4)
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self.assertEqual(summary["success_count"], 4)
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self.assertEqual(summary["failed_count"], 0)
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self.assertEqual(len(repo.created_tasks), 4)
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self.assertEqual(len(repo.saved_comments), 4)
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self.assertEqual(len(repo.failed_tasks), 0)
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self.assertIn("后续", repo.saved_comments[1][1])
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self.assertEqual(len({task.virtual_user_id for task in repo.created_tasks}), 4)
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def test_settings_reads_new_config_values(self):
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settings = AiCommentSettings.from_config_map(
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{
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"auto_comment_enabled": "1",
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"auto_comment_user_pool_size": "100",
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"auto_comment_per_run": "50",
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"auto_comment_daily_cap": "500",
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"auto_comment_concurrency": "4",
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"auto_comment_request_timeout": "180",
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"auto_comment_article_prompt": "article prompt",
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"auto_comment_post_prompt": "post prompt",
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"openai_api_key": "sk-demo",
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"openai_base_url": "https://example.com",
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"openai_model": "gpt-5.5",
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"openai_wire_api": "responses",
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"openai_provider_label": "OpenAI",
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"openai_reasoning_effort": "high",
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"openai_disable_response_storage": "1",
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"max_tokens": "300",
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"temperature": "0.65",
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}
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)
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self.assertTrue(settings.enabled)
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self.assertEqual(settings.user_pool_size, 100)
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self.assertEqual(settings.per_run, 50)
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self.assertEqual(settings.daily_cap, 500)
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self.assertEqual(settings.concurrency, 4)
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self.assertEqual(settings.request_timeout, 180)
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self.assertEqual(settings.article_prompt, "article prompt")
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self.assertEqual(settings.post_prompt, "post prompt")
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self.assertEqual(settings.openai_api_key, "sk-demo")
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self.assertEqual(settings.max_tokens, 300)
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self.assertAlmostEqual(settings.temperature, 0.65)
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if __name__ == "__main__":
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unittest.main()
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