Multiple models.
A workspace you manage.

One chat interface.
Different AI models.

LibreChat is an open-source chat application that you can host yourself. It provides a browser-based interface for talking to AI models; it is not an AI model of its own. Think of it as a workspace that brings supported models and your conversations into one place. About LibreChat ↗

The project identifies Danny Avila as its founder and maintainer and publishes its software under the MIT licence. “MIT” is the name of the software licence, not evidence of an institutional affiliation with the Massachusetts Institute of Technology. Project founder ↗ · Software licence ↗

LibreChat connects to multiple providers, including Anthropic and OpenAI, through their APIs. The aim is to select among configured models without moving between separate chat applications. Available models and features depend on each provider and the deployment’s configuration. LibreChat provider documentation ↗

This is a project in deploying and operating LibreChat—not a claim to have created the underlying application or models. My intended use is a consistent personal workspace on desktop and mobile, with optional access for other people through their own accounts.

A cloud home
for the workspace.

DigitalOcean is a cloud infrastructure provider, in the same broad category as Amazon Web Services (AWS). It rents computing, storage and networking resources so applications can run online without relying on your own computer. Its virtual servers are called Droplets.

Its offering emphasises straightforward server management and predictable pricing. Droplets also include monitoring and cloud firewalls. Those are useful considerations for a small hosted application; the right provider still depends on requirements, total costs and the ability to operate it. DigitalOcean Droplets ↗

In this deployment, DigitalOcean hosts the LibreChat application and supporting services, including its database and uploaded-file storage. The chat subdomain gives the workspace a browser-accessible address independent of my laptop.

For API-based models, generation happens at the model provider. Server resources support the application’s workload; they do not move Claude onto the server. No performance improvement or concurrency capacity has been established by benchmarks for this project.

OpenAI and Anthropic API credentials are configured. Successful requests and accounting for each exposed model still need end-to-end verification.

More control.
A responsibility to protect it.

Self-hosting LibreChat can support confidentiality by giving the operator control over workspace access, stored conversations and integrations. Those benefits depend on the actual configuration and operation. Installing the application alone does not establish a confidential environment.

• On the workspace server: conversations and uploaded files require access controls, secure backups, retention rules and timely security updates. Administrators with sufficient access may be able to read stored content.
• At the selected model provider: prompts and included conversation or file context leave the workspace when an external API is used. Hosting the app in one country does not establish where every provider processes the request.
• Across integrations: search, tools, document processing and other connected services may introduce additional recipients. Local inference can keep model processing on your computer, but only a review of the complete data path establishes what stays local.

Separate accounts are intended to separate users’ histories. This is different from making conversations inaccessible to the operator or model provider. This experimental workspace has not been validated for confidential material.

The terms matter
as much as the interface.

ChatGPT and Claude’s consumer applications have their own privacy settings and terms. OpenAI may use consumer content for model improvement depending on settings. Claude’s consumer policy describes choices to allow model improvement, along with feedback and safety-related exceptions. A paid personal subscription should not be treated as an enterprise confidentiality arrangement. OpenAI consumer data policy ↗ · Claude consumer data policy ↗

OpenAI’s API and Anthropic’s commercial services do not use inputs and outputs for model training by default; voluntary data sharing or feedback can change that. This protection comes from the applicable service terms, rather than from LibreChat itself. Business offerings from the providers also have different protections from consumer accounts. OpenAI API data controls ↗ · Anthropic commercial data policy ↗

No training does not mean no retention or no access. OpenAI documents abuse-monitoring retention and endpoint-specific storage; special retention controls have eligibility requirements. Review the exact provider, account, features and agreement before handling sensitive information.

BYOK means “bring your own key”. It identifies how model access is authorised. It does not, by itself, establish where prompts travel, who stores them or who can access them. For any hosted BYOK product, check whether requests pass through its servers, how it protects keys, and its own retention and access policies.

A workspace connected
to my own platform.

The purpose here is to combine multiple model providers in a workspace accessible from my website, desktop and phone, while choosing how the application is hosted and configured. It is also a practical project in understanding the responsibilities that come with operating an AI service.

LibreChat can be hosted under a domain you control and linked from your website. An embedded window can also be an integration option, subject to compatible browser, sign-in and security settings. Embedding changes how the workspace appears; it does not change which services process its data.

What about LibreChat’s public platform? The official service at chat.librechat.ai is a public demo. Its terms limit its purpose to evaluation, testing and education, exclude sensitive or confidential data, and give no continuity guarantee. It is useful for exploring the software, rather than establishing a dependable personal workspace. LibreChat demo terms ↗

A separately managed hosting service is a different proposition and should be assessed on its own terms. If it meets the same requirements with less operational effort, it may be the better choice.

Convenience is the start.
Operation is the test.

Can one interface make it easier to choose a model for a task? What is the trade-off between an accessible hosted service and a local setup? How do access controls, model costs and reliability affect everyday use?

The next demonstrations should show a repeatable task, the models and settings used, the output, human review and measured cost or latency. No comparative performance results are claimed yet.

Provider API access is configured separately from the providers’ consumer chat interfaces. This project does not promise every feature available in those interfaces.

A working experiment.
Learning in practice.

The workspace is deployed, with account access still under review. Findings will be added as the experience is tested. Use non-sensitive material when exploring.

Provider policies reviewed on 4 October 2026. The linked sources describe their own services; they do not certify this deployment. Recheck the applicable terms when selecting a service.