feat: protocol generation — LLM integration, prompt templates, Celery task

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

backend/app/schemas/prompt_template.py

@@ -0,0 +1,40 @@
+import uuid
+from datetime import datetime
+from typing import Any
+
+from pydantic import BaseModel
+
+from app.models.prompt_template import TemplateType
+
+
+class TemplateCreate(BaseModel):
+    name: str
+    description: str = ""
+    type: TemplateType = TemplateType.custom
+    system_prompt: str
+    user_prompt: str
+    output_schema: dict[str, Any] = {}
+    is_default: bool = False
+
+
+class TemplateUpdate(BaseModel):
+    name: str | None = None
+    description: str | None = None
+    system_prompt: str | None = None
+    user_prompt: str | None = None
+    output_schema: dict[str, Any] | None = None
+    is_default: bool | None = None
+
+
+class TemplateResponse(BaseModel):
+    id: uuid.UUID
+    name: str
+    description: str
+    type: TemplateType
+    system_prompt: str
+    user_prompt: str
+    output_schema: dict[str, Any]
+    is_default: bool
+    created_at: datetime
+
+    model_config = {"from_attributes": True}