LLMStack
LLMStack Overview
LLMStack is a user-friendly platform that supports all major model providers like OpenAI, Cohere, Stability AI, Hugging Face, and more. It allows users to import their own data and connect it to LLM models to enhance their generative AI applications and chatbots. The tool is powered by React and offers a collaborative environment for building apps, with options to share publicly or restrict access using a granular permission model.
LLMStack Highlights
- Supports all major model providers, enabling users to build powerful apps.
- Allows users to import their own data and connect it to LLM models, supercharging generative AI applications and chatbots.
- Provides a collaborative environment for building apps, with options to share publicly or restrict access.
Use Cases
A business wants to create a chatbot for their website to handle customer inquiries. They have a unique dataset of previous customer interactions that they want to use to train the chatbot.
The business uses LLMStack to import their own data and connect it to a model from Hugging Face. They are able to build a powerful, customized chatbot that can handle customer inquiries effectively, improving customer service and reducing the workload on their human staff.
A team of developers is working on a new app that uses generative AI. They need a platform where they can collaborate on the project and easily share their progress with stakeholders.
The team uses LLMStack for their project. The platform's collaborative environment allows them to work together efficiently, and the granular permission model lets them control who has access to their work. They can easily share their progress with stakeholders, speeding up the development process.
A company has an existing AI application that they want to enhance with more powerful models. They want to experiment with models from different providers to see which one works best.
The company uses LLMStack to test models from various providers, including OpenAI, Cohere, and Stability AI. They are able to quickly and easily compare the performance of the different models and choose the one that best enhances their application.