Problem solved

PrivateGPT solves the problem of building useful AI applications on top of local models. It provides a standardized API layer that enables developers to build private AI applications without depending on cloud APIs. This is particularly useful for enterprises and organizations that require private and secure AI solutions. PrivateGPT answers the question of how to build a useful AI application on top of a local model, whereas other projects such as Ollama, LM Studio, LocalAI, vLLM, and llama.cpp answer the question of how to run a model locally.

Use cases

• Building private AI applications on local models
• Creating custom AI tools and integrations
• Developing AI-powered workflows and automation
• Integrating AI with existing applications and systems
• Building self-hosted AI applications for enterprises and organizations

Audience

• Developers
• ML Engineers
• Data Scientists
• Enterprise

Pros

• Standardized API for private AI applications
• Compatible with any OpenAI-compatible inference server
• Production-tested and powers Zylon
• API-first approach for building self-hosted AI applications
• Open-source and available under Apache-2.0 license

Cons

• Limited support for certain features such as prompt caching and OAuth/organizations
• Requires technical expertise to deploy and integrate
• May require additional infrastructure and resources to operate at scale