ContextForge AI
Data Sources
Decomposed prompt into 5 Clean Architecture modules.
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy.orm import Session
from typing import List, Optional
from pydantic import BaseModel, Field
from app.services.patients_service import PatientService

router = APIRouter(prefix="/patients", tags=["Patients"])

class PatientCreate(BaseModel):
    name: str = Field(..., example="John Doe")
    age: int = Field(..., example=35)
    medical_history: Optional[str] = Field("None")

class PatientResponse(BaseModel):
    id: int
    name: str
    age: int
    status: str

@router.post("/", response_model=PatientResponse, status_code=status.HTTP_201_CREATED)
def create_patient(item_in: PatientCreate):
    return PatientService.create(item_in)

@router.get("/", response_model=List[PatientResponse])
def list_patients():
    return PatientService.list_all()
Multi-Agent Pipeline (Phase 1)
Presets:
Planner Agent

Decomposed prompt into 5 modules: Auth, Patients, Doctors, Billing, Reports.

Context Agent (Mocked)

Loaded static JSON metadata: 4 tables, 2 PII fields.

Impact Analysis Agent

Risk Score: MEDIUM. 2 APIs & 1 Dashboard affected.

Backend Generator Agent

Wrote FastAPI models, routers, alembic & Dockerfile to disk.

Frontend Generator Agent

Wrote Next.js TSX list & form page stubs to disk.