Merge pull request #737: normalize generated profile fields
Establish one canonical profile boundary before Twitter and Reddit serialization.
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commit
4064b68abf
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@ -27,6 +27,51 @@ from .zep_entity_reader import EntityNode, ZepEntityReader
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logger = get_logger('mirofish.oasis_profile')
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def _coerce_to_str(value: Any) -> str:
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"""Coerce a value to a plain string.
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Handles dict, list, and other non-string types that may be returned
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by LLM JSON parsing.
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"""
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if value is None:
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return ""
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if isinstance(value, str):
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return value
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if isinstance(value, dict):
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for key in ('text', 'value', 'description', 'content', 'summary', 'name'):
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if key in value:
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candidate = _coerce_to_str(value[key])
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if candidate:
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return candidate
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return json.dumps(value, ensure_ascii=False)
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if isinstance(value, (list, tuple)):
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str_items = [_coerce_to_str(item) for item in value]
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str_items = [item for item in str_items if item]
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return ', '.join(str_items)
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return str(value)
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def _coerce_to_str_list(value: Any) -> List[str]:
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"""Coerce a value to a list of strings.
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Handles nested structures that may be returned by LLM JSON parsing.
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"""
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if value is None:
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return []
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if isinstance(value, (list, tuple)):
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result: List[str] = []
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for item in value:
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if isinstance(item, (list, tuple)):
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result.extend(_coerce_to_str_list(item))
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else:
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text = _coerce_to_str(item)
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if text:
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result.append(text)
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return result
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text = _coerce_to_str(value)
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return [text] if text else []
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@dataclass
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class OasisAgentProfile:
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"""OASIS Agent Profile数据结构"""
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@ -36,7 +81,7 @@ class OasisAgentProfile:
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name: str
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bio: str
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persona: str
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# 可选字段 - Reddit风格
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karma: int = 1000
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@ -59,6 +104,18 @@ class OasisAgentProfile:
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created_at: str = field(default_factory=lambda: datetime.now().strftime("%Y-%m-%d"))
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def __post_init__(self):
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"""Normalize structured LLM fields once at the profile boundary."""
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self.bio = _coerce_to_str(self.bio) or self.name
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self.persona = _coerce_to_str(self.persona) or (
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f"{self.name} is a participant in social discussions."
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)
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self.country = _coerce_to_str(self.country) or None
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self.profession = _coerce_to_str(self.profession) or None
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self.gender = _coerce_to_str(self.gender) or None
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self.mbti = _coerce_to_str(self.mbti) or None
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self.interested_topics = _coerce_to_str_list(self.interested_topics)
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def to_reddit_format(self) -> Dict[str, Any]:
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"""转换为Reddit平台格式"""
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profile = {
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@ -1170,8 +1227,8 @@ class OasisProfileGenerator:
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"user_id": profile.user_id if profile.user_id is not None else idx, # 关键:必须包含 user_id
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"username": profile.user_name,
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"name": profile.name,
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"bio": profile.bio[:150] if profile.bio else f"{profile.name}",
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"persona": profile.persona or f"{profile.name} is a participant in social discussions.",
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"bio": profile.bio[:150],
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"persona": profile.persona,
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"karma": profile.karma if profile.karma else 1000,
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"created_at": profile.created_at,
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# OASIS必需字段 - 确保都有默认值
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@ -1204,4 +1261,3 @@ class OasisProfileGenerator:
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"""[已废弃] 请使用 save_profiles() 方法"""
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logger.warning("save_profiles_to_json已废弃,请使用save_profiles方法")
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self.save_profiles(profiles, file_path, platform)
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@ -0,0 +1,76 @@
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import csv
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import json
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from app.services.oasis_profile_generator import (
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OasisAgentProfile,
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OasisProfileGenerator,
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_coerce_to_str,
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_coerce_to_str_list,
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)
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def test_text_coercion_handles_none_nested_objects_and_lists():
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assert _coerce_to_str(None) == ""
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assert _coerce_to_str({"text": {"value": "中文"}}) == "中文"
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assert _coerce_to_str([None, {"description": "alpha"}, ["beta"]]) == "alpha, beta"
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assert _coerce_to_str({"unexpected": None}) == '{"unexpected": null}'
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def test_list_coercion_flattens_nested_values_and_drops_missing_items():
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assert _coerce_to_str_list(
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["AI", ["policy", None], {"name": "society"}, 4]
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) == ["AI", "policy", "society", "4"]
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assert _coerce_to_str_list(None) == []
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def test_profile_construction_is_the_single_normalization_boundary():
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profile = OasisAgentProfile(
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user_id=1,
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user_name="agent",
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name="Agent Name",
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bio=None,
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persona={"text": {"value": "详细人设"}},
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gender=["female"],
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mbti={"value": "INTJ"},
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country={"name": "中国"},
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profession={"description": "研究员"},
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interested_topics=["AI", ["政策", None], {"name": "社会"}],
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)
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assert profile.bio == "Agent Name"
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assert profile.persona == "详细人设"
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assert profile.gender == "female"
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assert profile.mbti == "INTJ"
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assert profile.country == "中国"
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assert profile.profession == "研究员"
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assert profile.interested_topics == ["AI", "政策", "社会"]
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assert "None" not in json.dumps(profile.to_dict(), ensure_ascii=False)
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def test_normalized_profile_serializes_to_twitter_and_reddit(tmp_path):
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profile = OasisAgentProfile(
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user_id=1,
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user_name="agent",
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name="Agent Name",
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bio={"summary": "公开简介"},
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persona=["详细", "人设"],
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mbti={"text": "ENFP"},
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interested_topics=["AI", ["政策"]],
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)
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generator = object.__new__(OasisProfileGenerator)
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twitter_path = tmp_path / "twitter_profiles.csv"
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reddit_path = tmp_path / "reddit_profiles.json"
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generator._save_twitter_csv([profile], str(twitter_path))
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generator._save_reddit_json([profile], str(reddit_path))
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with twitter_path.open(encoding="utf-8") as handle:
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twitter = next(csv.DictReader(handle))
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reddit = json.loads(reddit_path.read_text(encoding="utf-8"))[0]
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assert twitter["description"] == "公开简介"
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assert twitter["user_char"] == "公开简介 详细, 人设"
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assert reddit["bio"] == "公开简介"
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assert reddit["persona"] == "详细, 人设"
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assert reddit["mbti"] == "ENFP"
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assert reddit["interested_topics"] == ["AI", "政策"]
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