Promptise is an open-source Python framework for building Agentic Systems. Turn any LLM into a production-ready agent and skip months of glue code. Five composable modules: the Agent for production-ready agents with zero boilerplate, the Reasoning Engine to design how your agent thinks from the ground up, MCP for scalable, secure and production-ready APIs that agents understand, the Agent Runtime for autonomous agents that run forever and Prompt Engineering for prompts built like software.
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Most agent frameworks help you build an agent. Promptise helps you operate one.
There's a big gap between an agent that runs in a notebook and an agent that handles real users safely. Two to three months of infrastructure work, every time: authentication, rate limits, audit logs, memory isolation between users, approval flows for sensitive actions, restart after a crash, guardrails against prompt injection and leaked credentials.
Promptise ships that infrastructure as defaults. The production plumbing is the framework, not the tutorial you read afterwards.
Five pieces in one package:
The Agent comes with memory, security, caching, automated tool discovery, state-of-the-art token optimization unlike others and observability wired up the moment you call it.
The Reasoning Engine gives you the building blocks of how the agent thinks. Plan, think, critique, reflect, decide and many more. The agent itself chooses when to use them, so it stays a true agent instead of a scripted workflow. Start with the presets, or write your own nodes from scratch when a preset doesn't fit your use case.
MCP lets you build the tool APIs your agent calls, all the functionality of security and governance and true context request handling on the first line.
The Agent Runtime turns your agent into a long-running process that survives crashes, respects budgets, and can be monitored, paused, and updated while it runs.
Prompt Engineering treats prompts like typed, versioned code instead of string templates you debug at 2am.
All five share the same types and the same observability. You stop stitching libraries together.
And what I just described is maybe 10% of what Promptise actually does. Every piece goes several layers deeper. The whole framework is tuned around two things at once: the cleanest developer experience we could design and state-of-the-art security defaults you don't have to think about as much as usually.
Open source, Python, works with any LLM. One install. One function call and your agent is ready for real users.
What's the part of shipping an agent that costs you the most time you'd rather not spend?
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