xxx

src/moldinsight/services/llm_service.py

@@ -179,6 +179,33 @@ _PARTING_USER = """请评估以下候选分模方向并推荐最优方案：
 请综合评估制造可行性、成本和风险，给出推荐。"""
 
 
+_COST_ESTIMATE_SYSTEM = """你是一位资深模具报价工程师，擅长根据产品几何与模具设计方案估算模具造价与单件成本。
+
+要求：
+1. 使用中文，金额用人民币（¥）
+2. 基于给定数据合理估算，数据不足时给出区间并标注假设
+3. 综合考虑：模具材料、加工复杂度（滑块/斜顶/镶件）、型腔数、产品材料用量、成型周期
+
+严格输出 JSON，不要输出其他内容。JSON 格式：
+{
+  "mold_cost": {
+    "material": "¥XX（P20 钢，约 XX kg）",
+    "machining": "¥XX（含 CNC/EDM/线切割）",
+    "complexity_factor": "1.2（含 X 个滑块/斜顶）",
+    "subtotal": "¥XX"
+  },
+  "part_cost": {
+    "material": "¥XX（ABS，约 XX g）",
+    "cycle_time": "30 s",
+    "cost_per_part": "¥XX"
+  },
+  "total_mold_cost": "¥XX",
+  "cost_per_part": "¥XX",
+  "confidence": 0.7,
+  "assumptions": ["假设模具寿命 50 万模次", "假设..."]
+}"""
+
+
 class LLMService:
     """LLM 增强分析服务（单例）"""
 
@@ -308,6 +335,61 @@ class LLMService:
             logger.warning("LLM 分型推荐失败（不影响主流程）: %s", e)
             return None
 
+    async def estimate_cost(
+        self,
+        analysis_result: Dict[str, Any],
+        detailed_cavity_json: Optional[Dict[str, Any]] = None,
+    ) -> Optional[Dict[str, Any]]:
+        """估算模具造价与单件成本 (结构化 JSON)"""
+        if not self._enabled:
+            return None
+        try:
+            prompt = self._build_cost_estimate_prompt(analysis_result, detailed_cavity_json)
+            response = await self._chat(
+                _COST_ESTIMATE_SYSTEM,
+                prompt,
+                min(self._max_tokens, 1200),
+                expect_json=True,
+            )
+            if not response:
+                return None
+            result = self._parse_json_response(response)
+            if result:
+                logger.info("LLM 成本估算生成成功: total=%s", result.get("total_mold_cost"))
+            return result
+        except Exception as e:
+            logger.warning("LLM 成本估算失败（不影响主流程）: %s", e)
+            return None
+
+    def _build_cost_estimate_prompt(self, analysis_result: Dict[str, Any], detailed_cavity_json: Optional[Dict[str, Any]]) -> str:
+        geometry_data = analysis_result.get("geometry_data", {}) or (detailed_cavity_json or {}).get("geometry_data", {})
+        volume = geometry_data.get("volume", 0) or 0
+        bbox = geometry_data.get("bounding_box", {}) or {}
+        dims = bbox.get("dimensions", [0, 0, 0])
+        meta = (detailed_cavity_json or {}).get("metadata", {}) or {}
+        material = meta.get("selected_material") or analysis_result.get("material") or "ABS"
+        schemes = (detailed_cavity_json or {}).get("candidate_schemes", []) or []
+        best = schemes[0] if schemes else {}
+        cd = best.get("cavity_data", {}) if isinstance(best, dict) else {}
+        mfg = cd.get("manufacturing_info", {}) if isinstance(cd, dict) else {}
+        features = analysis_result.get("detected_features", []) or []
+        complexity_hints = [
+            f.get("description", f.get("feature_type", ""))
+            for f in features
+            if f.get("feature_type") in ("undercut", "side_action", "insert")
+        ]
+        return (
+            f"产品材料：{material}\n"
+            f"体积：{float(volume):.1f} mm³\n"
+            f"边界框尺寸（长×宽×高）：{float(dims[0]):.1f} × {float(dims[1]):.1f} × {float(dims[2]):.1f} mm\n"
+            f"预估锁模力：{mfg.get('estimated_clamping_force', '未知')}\n"
+            f"预估模具尺寸：{json.dumps(mfg.get('estimated_mold_size', {}), ensure_ascii=False)}\n"
+            f"预估成型周期：{mfg.get('estimated_cycle_time', '未知')}\n"
+            f"型腔数：{best.get('cavity_count', 1) if isinstance(best, dict) else 1}\n"
+            f"模具结构：{best.get('mold_structure_type', '未知') if isinstance(best, dict) else '未知'}\n"
+            f"复杂度线索：{', '.join(complexity_hints) if complexity_hints else '无明显倒扣/滑块'}\n"
+        )
+
     def _build_design_report_prompt(self, analysis_result, detailed_cavity_json) -> str:
         features = json.dumps(analysis_result.get("detected_features", []), ensure_ascii=False, indent=2)
         if len(features) > 4000: