promptulate

Undertone0809/promptulate is ranked 18,061 among these 8 peers; Accenture/mcp-bench is ranked 18,055.

The core philosophy of Promptulate is to borrow and integrate the wisdom of the open-source community, incorporating the highlights of various development frameworks to lower the barrier to entry and unify the consensus among developers. With Promptulate, you can manipulate components like LLM, Agent, Tool, RAG, etc. , with the most succinct code, as most tasks can be easily completed with just a few lines of code. 🚀 💡 Features 🐍 Pythonic Code Style: Embraces the habits of Python developers, providing a Pythonic

SDK calling approach, putting everything within your grasp with just one function to encapsulate all essential functionalities. 🧠 Model Compatibility: Supports nearly all types of large models on the market and allows for easy customization to meet specific needs. 🕵️‍♂️ Diverse Agents: Offers various types of Agents, such as WebAgent, ToolAgent, CodeAgent, etc. , capable of planning, reasoning, and acting to handle complex problems. Atomize the Planner and other components to simplify the development process. 🔗 Low-Cost Integration: Effortlessly integrates tools from different

frameworks like LangChain, significantly reducing integration costs. 🔨 Functions as Tools: Converts any Python function directly into a tool usable by Agents, simplifying the tool creation and usage process. 🪝 Lifecycle and Hooks: Provides a wealth of Hooks and comprehensive lifecycle management, allowing the insertion of custom code at various stages of Agents, Tools, and LLMs. 💻 Terminal Integration: Easily integrates application terminals, with built-in client support, offering rapid debugging capabilities for prompts. ⏱️ Prompt Caching: Offers a caching mechanism for LLM Prompts

to reduce repetitive work and enhance development efficiency. 🤖 Powerful OpenAI Wrapper: With pne, you no longer need to use the openai sdk, the core functions can be replaced with pne. chat, and provides enhanced features to simplify development difficulty. 🧰 Streamlit Component Integration: Quickly prototype and provide many out-of-the-box examples and reusable streamlit components. The following diagram shows the core architecture of : The core concept of Promptulate is we hope to provide a simple, pythonic and efficient way

to build AI applications, which means you don't need to spend a lot of time learning the framework. We hope to use to do most of the works, and you can easily build any AI application with just a few lines of code. Below, stands for Promptulate, which is the nickname for Promptulate. The and represent the beginning and end of Promptulate, respectively, and stands for 9, which is a shorthand for the nine letters between and . Now let's see

how to run local llama3 models of ollama with pne. 14 OpenAI launched their newest "omni" model, offering improved speed and pricing compared to turbo. You can use the available multimodal capabilities of it in any of your promptulate applications! Use to call the model, and you can easily build any third-party model calls. For more models, please visit the litellm documentation. You can also see how to use in the Getting Started/Official Documentation. 📗 Related Documentation Getting Started

/Official Documentation Current Development Plan Contributing/Developer's Manual Frequently Asked Questions PyPI Repository 📝 Examples Build streamlit chatbot by pne Build