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Backend development agent for Resume Matcher. Handles FastAPI endpoints, Pydantic schemas, TinyDB operations, LiteLLM integration, and Python service logic. Use when creating or modifying backend code.
npx skill4agent add srbhr/resume-matcher backend-devUse when creating or modifying FastAPI endpoints, Pydantic schemas, database operations, LLM integrations, or Python service logic.
docs/agent/architecture/backend-guide.mddocs/agent/apis/front-end-apis.mddocs/agent/llm-integration.mdcopy.deepcopy()asyncio.Lock()api_key=os.environapps/backend/app/
├── main.py # FastAPI app, CORS, lifespan, routers
├── config.py # Pydantic BaseSettings from env
├── database.py # TinyDB wrapper (JSON file storage)
├── llm.py # LiteLLM wrapper (multi-provider)
├── routers/ # API endpoint handlers
├── services/ # Business logic layer
├── schemas/ # Pydantic request/response models
└── prompts/ # LLM prompt templates (Jinja2)from fastapi import APIRouter, HTTPException
from app.schemas.my_schema import MyRequest, MyResponse
from app.services.my_service import process_data
import logging
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/v1", tags=["my-feature"])
@router.post("/my-endpoint", response_model=MyResponse)
async def create_thing(request: MyRequest) -> MyResponse:
try:
result = await process_data(request)
return result
except Exception as e:
logger.error(f"Failed to create thing: {e}")
raise HTTPException(status_code=500, detail="Operation failed. Please try again.")from pydantic import BaseModel, Field
class MyRequest(BaseModel):
name: str = Field(..., min_length=1, max_length=200)
description: str | None = None
class MyResponse(BaseModel):
id: str
name: str
status: str = "created"import copy
from app.database import get_db
DEFAULT_DATA = {"sections": [], "metadata": {}}
async def get_or_create(doc_id: str) -> dict:
db = get_db()
existing = db.get(doc_id)
if existing:
return existing
data = copy.deepcopy(DEFAULT_DATA) # ALWAYS deepcopy mutable defaults
db.insert(data)
return datafrom app.llm import get_completion
from app.config import settings
async def improve_text(text: str) -> str:
prompt = f"Improve this resume text:\n\n{text}"
result = await get_completion(
prompt=prompt,
model=settings.LLM_MODEL,
api_key=settings.LLM_API_KEY, # Pass directly, not via env
json_mode=True,
)
return resultexcept Exception as e:
logger.error(f"Operation failed: {e}") # Detailed for server logs
raise HTTPException(
status_code=500,
detail="Operation failed. Please try again." # Generic for client
)copy.deepcopy()main.pyapi_key=