The framework also provides a quick start guide for setting up a simple starter application with an OpenAI Chatbot. It includes components for building, experimenting, analyzing, deploying, client SDK, tracing, and a control panel called Palico Studio. Palico also provides a FAQ section addressing comparisons with libraries like LangChain and evaluation libraries, emphasizing its integrated framework for rapid experimentation and deployment.
Key takeaways:
- Palico is an LLM Development Framework that streamlines the process of running experiments to improve the accuracy of your LLM application.
- It provides tools to build your LLM application, run experiments for accuracy improvement, deploy with Docker Containers, and integrate your LLM application to other systems via REST API or SDK.
- Palico Studio is a control panel for your Palico App that allows you to chat with your LLM Agents or Workflows, manage experiments, and review runtime traces.
- Unlike libraries like LangChain or LlamaIndex, Palico is a framework that provides a standard process and an integrated set of tools for LLM application development, focusing on maximizing experiment-ability to reach accuracy goals faster.