Add analysis feature

backend/schemas.py

@@ -90,6 +90,45 @@ class KnowledgeRetrievalConfig(CamelModel):
         return value
 
 
+class AnalysisField(CamelModel):
+    id: str = Field(min_length=1, max_length=64)
+    name: str = Field(pattern=r"^[A-Za-z][A-Za-z0-9_]{0,63}$")
+    type: Literal["string", "boolean", "integer", "number", "enum"] = "string"
+    description: str = Field(default="", max_length=500)
+    enum_values: list[str] = Field(default_factory=list, max_length=30)
+
+    @model_validator(mode="after")
+    def validate_enum_values(self):
+        normalized = list(
+            dict.fromkeys(
+                value.strip() for value in self.enum_values if value.strip()
+            )
+        )
+        if self.type == "enum" and not normalized:
+            raise ValueError("enum 字段必须至少配置一个枚举值")
+        self.enum_values = normalized if self.type == "enum" else []
+        return self
+
+
+class AnalysisConfig(CamelModel):
+    enabled: bool = False
+    model_resource_id: str = ""
+    fields: list[AnalysisField] = Field(default_factory=list, max_length=20)
+
+    @model_validator(mode="after")
+    def validate_enabled_config(self):
+        if not self.enabled:
+            return self
+        if not self.model_resource_id:
+            raise ValueError("开启通话后分析时必须选择分析模型")
+        if not self.fields:
+            raise ValueError("开启通话后分析时必须配置至少一个关键信息字段")
+        names = [field.name for field in self.fields]
+        if len(names) != len(set(names)):
+            raise ValueError("关键信息字段名不能重复")
+        return self
+
+
 # 各 type 允许的瘦字段(其余字段写入时清零,防止跨类型脏数据)
 ALLOWED_FIELDS: dict[str, set[str]] = {
     "prompt": {"prompt"},
@@ -171,6 +210,7 @@ class AssistantUpsert(CamelModel):
     dynamic_variable_definitions: dict[str, "DynamicVariableDefinition"] = Field(
         default_factory=dict
     )
+    analysis_config: AnalysisConfig = Field(default_factory=AnalysisConfig)
     api_url: str = ""
     api_key: str = ""  # 写时:占位符/空 → 保留旧(哨兵)
     app_id: str = ""
@@ -500,9 +540,25 @@ class ConversationOut(CamelModel):
     ended_at: datetime | None
 
 
+class ConversationAnalysisFieldOut(CamelModel):
+    name: str
+    type: str
+    value: Any = None
+
+
+class ConversationAnalysisOut(CamelModel):
+    status: Literal[
+        "none", "pending", "processing", "completed", "failed"
+    ] = "none"
+    fields: list[ConversationAnalysisFieldOut] = Field(default_factory=list)
+    error: str = ""
+    completed_at: datetime | None = None
+
+
 class ConversationDetailOut(ConversationOut):
     extra: dict[str, Any] = Field(default_factory=dict)
     messages: list[ConversationMessageOut] = Field(default_factory=list)
+    analysis: ConversationAnalysisOut = Field(default_factory=ConversationAnalysisOut)
 
 
 class ConversationListOut(CamelModel):