Undertone0809/promptulate
🚀Lightweight Large language model automation and Autonomous Language Agents development framework. Build your LLM Agent Application in a pythonic way!
What it solves
Promptulate is a framework designed to simplify the development of AI Agent applications. It aims to lower the barrier to entry for developers by providing a concise, Pythonic way to build agents, reducing the amount of boilerplate code and learning time required to integrate LLMs, tools, and RAG components.
How it works
At its core, the framework centers around the pne.chat() function, which encapsulates most essential functionalities. It integrates litellm to provide broad compatibility with nearly all major LLM providers. The framework allows developers to convert Python functions directly into tools and supports a "Plan-and-Solve" approach where agents can plan, reason, and act to solve complex problems. It also includes a caching mechanism for prompts and a comprehensive lifecycle management system with hooks for custom code insertion.
Who it’s for
It is built for Python developers who want to build AI agents and LLM applications quickly and efficiently without spending excessive time learning complex framework-specific paradigms.
Highlights
- Pythonic SDK: Uses a streamlined approach where
pne.chat()handles the majority of application logic. - Broad Model Support: Compatible with a wide range of providers including OpenAI, Azure, AWS, Google, Anthropic, and local models via Ollama.
- Agentic Capabilities: Supports specialized agents (WebAgent, ToolAgent, CodeAgent) with built-in planning and reflection.
- Structured Output: Easy integration with Pydantic's
BaseModelto ensure LLMs return stable, formatted data. - Low-Cost Integration: Effortlessly incorporates tools from other frameworks like LangChain.
- Prototyping Tools: Includes built-in client support for terminal debugging and Streamlit component integration for rapid prototyping.