# Case Study: App 03 — Prompt Forge
## 1. Overview
Prompt Forge is a structured content generation workbench. It allows marketing teams to craft tailored content variations across different personas (e.g. Friendly, Technical, CFO) and formats (LinkedIn, Email, Landing Page).
## 2. Learning & Technical Goals
- Implement pre-generation safety filtering with Azure Content Safety API.
- Support real-time Server-Sent Events (SSE) streaming with structured JSON parsing.
- Eliminate server-side prompt logging vulnerabilities by shifting history storage to client `localStorage`.
## 3. Architecture & Tech Stack
- **Frontend:** Next.js 16, Tailwind CSS, TypeScript.
- **Backend:** FastAPI, Python 3.12, Azure OpenAI, Azure Content Safety SDK.
## 4. Key Security & Cost Control Decisions
- **Content Safety:** Automated inspection for hate speech, self-harm, and violence before initiating LLM calls.
- **No Pseudo-Identity:** Removed `X-Client-ID` headers and server log endpoints (`/log`), preventing unauthorized log access.
- **Streaming Hardening:** SSE streams pass `Cache-Control: no-store` headers and do not log individual text deltas.
## 5. Outcome
Prompt Forge delivers fast, streaming content variations with strict safety bounds and zero prompt exposure on the backend.
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Project 03Prompt Engineering & Content Gen
Prompt Forge
Structured marketing variations with personas, SSE and safety checks.
Next.js 16FastAPIAzure OpenAIAzure Content Safety
Controls and retained data vary by application. See its README for the implemented behavior and limitations.