Entdecke die besten multimodalen Prompt-Bibliotheken für KI-Modelle. Vergleiche die Top-Repositories nach Aktivität und Features, um die beste Lösung für dein Projekt zu finden.
Ell is a Python library that treats prompts as callable functions, transforming a Python function into a language model program where the docstring defines the system message and the return value defines the user message. It provides a framework for writing language model programs that can accept and return images, audio, and text natively within message objects, and supports chaining multiple model calls into a single function for multi-step reasoning or test-time compute. The library decouples model selection from client instantiation through a registry that supports multiple provider backe
Ell is a Python library that turns functions into language model programs, natively handling text, image, and audio in messages while supporting multiple model providers, making it a fit for multimodal prompt engineering, though it lacks an explicit template system or interactive UI.
This project is a LangChain-based framework for building retrieval-augmented generation systems, autonomous agents, and multimodal chatbots. It functions as an open-source orchestrator that connects local inference engines and online APIs to manage various large language model deployments. The system distinguishes itself by providing specialized interfaces for local knowledge bases, allowing the loading and vectorization of private documents to create context-aware assistants. It also supports multimodal capabilities, enabling the processing of both text and image inputs through vision-capabl
This LangChain-based framework constructs prompts for text and image modalities to power chatbots and agents, matching the core capability of a multimodal prompt engineering library, though it does not highlight audio support or a dedicated template system.