133 lines
5.1 KiB
Python
133 lines
5.1 KiB
Python
import unittest
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import json
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from pathlib import Path
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from tempfile import TemporaryDirectory
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from ai_daily_report.runner import run_daily_report
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class RunnerTests(unittest.TestCase):
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def test_run_daily_report_mock_mode_writes_markdown_and_reports(self):
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with TemporaryDirectory() as temp_dir:
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result = run_daily_report(
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run_date="2026-06-04",
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mode="dry-run",
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source_mode="mock",
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llm_mode="mock",
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out_dir=Path(temp_dir),
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base_url="https://blog.example",
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)
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run_dir = Path(result["run_dir"])
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self.assertTrue((run_dir / "blog_markdown.md").exists())
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self.assertTrue((run_dir / "run_report.json").exists())
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self.assertEqual(result["reports"]["stage8"]["status"], "ok")
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def test_run_daily_report_live_sources_can_use_config_and_fetch_text(self):
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with TemporaryDirectory() as temp_dir:
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out_dir = Path(temp_dir) / "out"
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source_config = Path(temp_dir) / "sources.json"
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source_config.write_text(
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json.dumps(
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[
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{
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"name": "InfoQ AI",
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"type": "rss",
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"url": "https://feed.example/rss",
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"role": "supplement",
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"priority": 40,
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"enabled": True,
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}
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]
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),
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encoding="utf-8",
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)
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def fetch_text(url, timeout):
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return """<?xml version="1.0"?><rss><channel><item><title>GPT-5 API 发布</title><link>https://example.com/gpt5</link><description>OpenAI 发布 GPT-5 API。</description></item></channel></rss>"""
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result = run_daily_report(
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run_date="2026-06-04",
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mode="dry-run",
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source_mode="live",
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llm_mode="mock",
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out_dir=out_dir,
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base_url="https://blog.example",
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sources_path=source_config,
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fetch_text=fetch_text,
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)
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self.assertEqual(result["reports"]["stage0"]["raw_item_count"], 1)
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self.assertTrue((out_dir / "2026-06-04" / "blog_markdown.md").exists())
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def test_run_daily_report_live_llm_uses_env_config_in_dry_run(self):
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class FakeLlmClient:
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def __init__(self):
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self.prompts = []
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def chat(self, prompt):
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self.prompts.append(prompt)
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if "duplicate_groups" in prompt:
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return json.dumps({"duplicate_groups": [], "not_duplicates": [], "uncertain": []})
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if "rewrites" in prompt:
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payload = json.loads(prompt)
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return json.dumps(
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{
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"rewrites": [
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{
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"id": item["id"],
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"title": item["title_raw"],
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"summary": item["summary_raw"],
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"flags": [],
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}
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for item in payload["items"]
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]
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}
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)
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return json.dumps(
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{
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"theme": "模型能力继续进入产品入口。",
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"threads": [
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{
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"title": "模型 API 更新",
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"text": "GPT-5 API 发布，说明模型能力继续进入产品入口。",
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"item_ids": [json.loads(prompt)["items"][0]["id"]],
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"kind": "thread",
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}
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],
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}
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)
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fake_client = FakeLlmClient()
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captured_config = {}
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def llm_client_factory(**config):
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captured_config.update(config)
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return fake_client
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with TemporaryDirectory() as temp_dir:
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result = run_daily_report(
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run_date="2026-06-04",
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mode="dry-run",
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source_mode="mock",
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llm_mode="live",
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out_dir=Path(temp_dir),
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base_url="https://blog.example",
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env={
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"LLM_API_KEY": "test-key",
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"LLM_BASE_URL": "https://llm.example/v1",
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"LLM_MODEL": "test-model",
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},
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llm_client_factory=llm_client_factory,
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)
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self.assertEqual(captured_config["api_key"], "test-key")
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self.assertEqual(captured_config["base_url"], "https://llm.example/v1")
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self.assertEqual(captured_config["model"], "test-model")
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self.assertGreaterEqual(len(fake_client.prompts), 2)
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self.assertEqual(result["reports"]["stage8"]["status"], "ok")
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if __name__ == "__main__":
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unittest.main()
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