feat: initialize resume agent with OfferPai sync

backend/app/profile_summary.py

@@ -0,0 +1,122 @@
+from __future__ import annotations
+
+from copy import deepcopy
+from datetime import UTC, datetime
+from typing import Any, Protocol
+
+from pydantic import BaseModel, ConfigDict, Field
+
+from .llm_services import OpenAICompatibleStructuredClient
+from .settings import Settings
+
+
+class ProfileSummaryOutput(BaseModel):
+    model_config = ConfigDict(extra="forbid")
+
+    content: str = Field(min_length=20, max_length=600)
+
+
+class ProfileSummaryGenerator(Protocol):
+    def generate(self, content: dict[str, Any]) -> str: ...
+
+
+class RuleBasedProfileSummaryGenerator:
+    """Deterministic Chinese summary for tests and configured rule fallback."""
+
+    def generate(self, content: dict[str, Any]) -> str:
+        basics = content.get("basics") if isinstance(content.get("basics"), dict) else {}
+        target = content.get("target") if isinstance(content.get("target"), dict) else {}
+        position = str(target.get("position") or target.get("target_position") or "目标岗位").strip()
+        groups = content.get("skill_groups") if isinstance(content.get("skill_groups"), list) else []
+        skills = [
+            str(skill).strip()
+            for group in groups
+            if isinstance(group, dict)
+            for skill in group.get("skills") or []
+            if str(skill).strip()
+        ][:5]
+        first_entry: dict[str, Any] = {}
+        for section in content.get("sections") or []:
+            if isinstance(section, dict) and section.get("items"):
+                candidate = section["items"][0]
+                if isinstance(candidate, dict):
+                    first_entry = candidate
+                    break
+        major = str(first_entry.get("major") or basics.get("major") or "").strip()
+        focus = str(
+            first_entry.get("company")
+            or first_entry.get("project_name")
+            or first_entry.get("school")
+            or "相关实践"
+        ).strip()
+        skill_text = "、".join(dict.fromkeys(skills)) or "相关技术与实践能力"
+        major_text = f"，具备{major}相关学习背景" if major else ""
+        return f"面向{position}{major_text}，具备{skill_text}等能力，拥有{focus}相关经历，能够结合已完成的项目与实践持续提升岗位匹配度。"
+
+
+class OpenAIProfileSummaryGenerator:
+    def __init__(self, completion: OpenAICompatibleStructuredClient) -> None:
+        self.completion = completion
+
+    def generate(self, content: dict[str, Any]) -> str:
+        output: ProfileSummaryOutput = self.completion.complete(
+            schema=ProfileSummaryOutput,
+            schema_name="profile_summary",
+            system_prompt=(
+                "你是中文简历个人总结撰写助手。仅返回 JSON。根据用户已确认的简历内容，"
+                "写一段 80 到 180 字、适合置于中文简历开头的个人总结。"
+                "只概括目标岗位、教育/经历、项目和技能中的已有事实；不得包含手机、邮箱等隐私信息，"
+                "不得编造公司、学校、项目、学历、奖项、证书或量化数字。"
+                "内容应自然连贯，不使用标题、列表、Markdown 或解释。"
+            ),
+            payload={"resume": _summary_source(content)},
+        )
+        return _validate_summary(output.content)
+
+
+class FallbackProfileSummaryGenerator:
+    def __init__(self, primary: ProfileSummaryGenerator, fallback: ProfileSummaryGenerator) -> None:
+        self.primary = primary
+        self.fallback = fallback
+
+    def generate(self, content: dict[str, Any]) -> str:
+        try:
+            return self.primary.generate(content)
+        except Exception:
+            return self.fallback.generate(content)
+
+
+def build_profile_summary_generator(
+    settings: Settings, client: Any | None = None
+) -> ProfileSummaryGenerator:
+    rules = RuleBasedProfileSummaryGenerator()
+    if not settings.use_openai:
+        return rules
+    primary = OpenAIProfileSummaryGenerator(OpenAICompatibleStructuredClient(settings, client))
+    return FallbackProfileSummaryGenerator(primary, rules) if settings.fallback_to_rules else primary
+
+
+def generated_summary(content: str) -> dict[str, Any]:
+    return {
+        "content": _validate_summary(content),
+        "source": "ai_generated",
+        "generated_at": datetime.now(UTC).isoformat(),
+        "stale": False,
+    }
+
+
+def _validate_summary(value: str) -> str:
+    clean = " ".join(str(value or "").split())
+    if not 20 <= len(clean) <= 600:
+        raise ValueError("profile_summary_invalid")
+    return clean
+
+
+def _summary_source(content: dict[str, Any]) -> dict[str, Any]:
+    result = deepcopy(content)
+    basics = result.get("basics")
+    if isinstance(basics, dict):
+        for field in ("phone", "email", "masked_phone"):
+            basics.pop(field, None)
+    result.pop("profile_summary", None)
+    return result