Most **LLM **apps start with a few hardcoded prompts. Then the project grows, the logic spreads across files, and prompt handling becomes a mix of strings, environment checks, and scattered config. That is exactly the problem DynaPrompt is trying to solve: a dynamic prompt management and configuration library for LLM applications, with lazy loading, Jinja2 templates, and Pydantic schema support. GitHub : mohamed-em2m/dynaprompt Why prompt management gets messy When prompts live directly inside application code, they become harder to test, harder to version, and harder to reuse. DynaPrompt takes the opposite approach: keep templates separate from business logic, and treat prompts like configuration instead of inline strings. Here is the kind of code that gets ugly fast: import os import json user_name = os . getenv ( " USER_NAME " , " Guest " ) SYSTEM_PROMPT = f """ You are a helpful assistant. Current User: { user_name } Format your output according to this schema: { json . dumps ( MySchema .…