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What self-hosting LibreTranslate means
LibreTranslate is an open-source translation API powered by Argos Translate. Self-hosting puts the API process, translation models, logs, credentials and network policy on infrastructure you administer instead of sending requests to a third-party endpoint. That can help when an application needs a private network path, predictable control over data handling, or a custom operational policy.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsA VPS is simply one place to run it. The service can be installed directly with Python, packaged in Docker, launched with Gunicorn, or installed in Kubernetes through the project’s Helm chart. The project’s installation documentation recommends Gunicorn or Docker for production because the development-style process can suffer memory leaks over long runs.
There is no authoritative VPS CPU, RAM, throughput, latency, supported-language count or operating-cost figure in the available documentation. Choose a VPS size from your workload, then observe memory, CPU, request duration and model-loading behavior rather than relying on an invented minimum.
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Plan the deployment before installing
Decide who can reach the API
LibreTranslate listens on 127.0.0.1 and port 5000 by default. That loopback binding accepts requests from the VPS itself but not directly from the public internet. It is a good starting point when a reverse proxy will provide the public hostname, TLS and access controls.
If you deliberately bind the process to an externally reachable interface, you become responsible for the firewall, TLS, authentication and abuse controls at that exposed boundary. Do not treat a changed bind address as a security feature; it only changes reachability.
Choose a process model
| Method | Best fit | Operational characteristics |
|---|---|---|
| Python package | Evaluation, development, or a tightly managed small service | Install with Python 3.8 or newer and run the libretranslate command. You manage the virtual environment, process lifetime and restarts. |
| Docker | Repeatable deployments and isolated dependencies | Use the project image and its repository-provided run scripts. Container configuration must include persistent model storage and a restart policy appropriate to your VPS. |
| Gunicorn | Production process management outside a container | The documented command binds Gunicorn to port 5000 and calls the WSGI application, keeping the service under a production WSGI server. |
| Helm on Kubernetes | Clusters that already provide scheduling, secrets and observability | The project documents a Helm chart. You must supply cluster networking, persistent storage and ingress policy separately. |
For one VPS, Docker or Gunicorn is the documented production direction. Python is useful for proving that the service and models work before you add a proxy or service manager.
Install with Python and test locally
1. Install a supported Python version
The pip route requires Python 3.8 or newer. Check the interpreter that your service account will use, then create an isolated environment so LibreTranslate’s dependencies do not conflict with other applications.
python3 --version
python3 -m venv .venv
. .venv/bin/activate
python -m pip install --upgrade pip
pip install libretranslateThe final command installs the package. Start the server with the libretranslate command and any flags required by your design:
libretranslateWith no host or port override, the process uses 127.0.0.1:5000. Keep that default for a reverse-proxy architecture. If you need a different interface or port, set the documented --host and --port options explicitly and update the proxy and firewall configuration to match.
2. Confirm that the process is listening
From the VPS, check the service before exposing a hostname. A local HTTP request should reach port 5000. If it does not, inspect the process output first: model downloads, an invalid option, a missing dependency or a port already in use will usually be reported there.
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Run the service with Docker
Docker gives you a repeatable image and keeps application dependencies separate from the VPS operating system. The project documents Docker through its repository run scripts, run.sh and run.bat, and publishes the image as libretranslate/libretranslate.
1. Obtain the image
docker pull libretranslate/libretranslateUse the repository’s current run script or container instructions to supply the host, port and LibreTranslate arguments. Do not assume that a host bind, model directory or API-key setting from an old example still matches the image version you pulled.
2. Persist model files
Translation models are downloaded data, not disposable application logs. Mount a persistent volume or host directory at the model location specified by the current Docker configuration. Without persistent storage, recreating a container can trigger model downloads again, increasing startup time and consuming bandwidth.
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3. Map exposure deliberately
For a reverse-proxy setup, map the container’s port to a VPS loopback address rather than all interfaces, then let the proxy publish HTTPS. If the container is intentionally public, map it to the required interface only after the firewall, TLS and authentication policy are ready.
Use Gunicorn for a production Python process
The installation guide gives this Gunicorn form:
gunicorn --bind 0.0.0.0:5000 'wsgi:app()'The example binds Gunicorn to all interfaces, which is appropriate only when your network policy intentionally allows that exposure or when another layer constrains it. If your proxy and Gunicorn share the VPS, bind the application to a private or loopback address instead and configure the proxy to use that address. Keep the command in a service manager so it starts after reboot, restarts after failure and writes logs to a location you monitor.
Gunicorn is a process server, not a complete public-edge security policy. It does not replace TLS termination, firewall rules, request limits or API-key enforcement.
Deploy with the Helm chart when you already run Kubernetes
The project documents a Helm chart for Kubernetes. This route makes sense when your cluster already handles scheduling, ingress, secrets, persistent volumes and monitoring. Define those resources as part of the deployment rather than assuming the chart supplies a public TLS policy or durable model storage.
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- Use a persistent volume for model files if pods should not redownload them after replacement.
- Keep API credentials in Kubernetes secrets, not in a committed values file.
- Expose the service through an ingress or internal service according to the clients that need it.
- Set resource requests and limits from observed usage; the project does not publish a universal VPS or pod minimum.
Choose and load language models
Install only what the application needs
LibreTranslate installs support for all available languages by default. That broad installation increases the amount of model data and can lengthen startup. If your application only translates between a few languages, pass the --load-only option with a comma-separated list, such as:
libretranslate --load-only en,es,frReplace the example codes with the language codes your clients actually use. A request for a language model that was not loaded cannot succeed, so map your product’s supported pairs before narrowing the list.
Update models deliberately
Model updates can be requested with the --update-models option or by running the project’s scripts/install_models.py script. Schedule updates when you can observe startup and translation behavior, and keep enough persistent disk space for the existing and newly downloaded files during a replacement.
Do not combine an automatic model update with an unobserved production restart. First run the update in a maintenance window or staging instance, verify the language pairs your application uses, then roll it into the service instance.
Put a public API behind a controlled network boundary
Recommended VPS layout
- Run LibreTranslate or Gunicorn on a private or loopback address.
- Terminate HTTPS at your reverse proxy or ingress.
- Forward only the required path to the internal service.
- Allow the proxy-to-application port through the local firewall, while keeping the application port closed to the wider internet.
- Apply request-size, timeout and access policies at the edge as well as LibreTranslate’s own limits.
The documentation lists TLS-related and operational flags, but it does not prescribe a particular reverse-proxy product, firewall, certificate authority or VPS provider. Select those components according to your operating system and existing security standards.
Direct exposure is a deliberate trade-off
Binding LibreTranslate to an external interface can remove a proxy hop, but it also places TLS and more abuse handling directly on the application boundary. Use it only when you have explicitly configured certificates, firewall rules, monitoring and authentication for that design. A public IP and an open port are not substitutes for those controls.
Require API keys and limit abuse
The documented request-limit default is “No limit,” and API-key storage is disabled by default. Those defaults may be convenient for a local test but are not a production access policy.
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Require a key for every request
The hardening combination documented by LibreTranslate is:
libretranslate --req-limit 0 --api-keysSetting --req-limit to 0 together with --api-keys makes API-key use mandatory according to the installation guide. Configure and distribute keys using the mechanism supported by the version you installed; keep them out of source control, browser code and public logs.
Set limits that match your clients
LibreTranslate exposes controls including --char-limit, --req-limit and --batch-limit. Choose values from the largest legitimate translation your application sends, its expected burst pattern and the CPU and memory you observe. A limit that is too low creates avoidable failures; one that is too high lets a single client consume the whole VPS.
- Character limit: caps the amount of text accepted in a request.
- Request limit: controls request frequency; API keys enable per-client rate limits when a request limit is configured.
- Batch limit: constrains the number of items handled in a batch request.
- Origin and edge policy: restrict browser origins and proxy access to the applications that should call the API.
Use separate keys or client identities where you need independent quotas and revocation. Rotate credentials when an application changes ownership or a secret may have been exposed, and review logs for repeated rejected or unusually large requests.
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Verify the translation endpoint
Run the documented quick test
The quickstart checks a local service with a POST request:
curl -X POST http://localhost:5000/translate -d q="Hello" -d source=en -d target=esA successful example response is:
{"translatedText":"Hola"}On a VPS, run this test from the server first. After the local path works, repeat it through the protected hostname or private address that your application will use. Test one request without credentials to confirm that your chosen authentication policy rejects it, then test with a valid client credential through the same proxy path.
Validate more than HTTP 200
- Confirm the response contains the expected translated text field.
- Use a language pair that you explicitly loaded when
--load-onlyis enabled. - Send a request near, but not beyond, your configured character and batch limits.
- Check that the proxy preserves the
/translatepath and permits POST bodies. - Verify that TLS certificate validation and hostname routing work from the client network, not only from the VPS.
Operate, monitor and update the service
Enable metrics when you have a collector
Metrics are disabled by default. Add --metrics to mount a /metrics endpoint for Prometheus-compatible collection. Keep that endpoint on an internal monitoring path or protect it at the proxy; it should not become an unauthenticated public information leak.
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Track process restarts, model-load failures, memory growth, request counts, rejected requests and translation errors. Correlate spikes with model updates, traffic changes and VPS resource pressure.
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Update the package or image
For a pip installation, the documented update command is:
pip install -U libretranslateFor Docker, update the image with:
docker pull libretranslate/libretranslateRestart the service after updating, then repeat the local and proxied /translate checks. Keep the previous package environment or image available until the new instance has passed those checks, so rollback remains practical.
Keep configuration reproducible
Record the exact command-line flags, loaded language list, model-update procedure, volume paths and proxy route in your deployment documentation. Store secrets separately. A restart should reproduce the same language coverage and security policy without relying on an operator’s shell history.
Common failures and fixes
The service works locally but not from another machine
Check the bind address first. A process on 127.0.0.1 is intentionally reachable only from the VPS. If a proxy is in use, verify that it can reach the internal port, that the firewall permits that hop, and that DNS and TLS route to the proxy rather than directly to port 5000.
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Confirm that LibreTranslate is running, listening on the address and port configured upstream, and not still downloading models. Test the upstream URL from the proxy host. A mismatch between container port mapping, Gunicorn bind address and proxy target is a common cause.
A language pair fails after using --load-only
Inspect the language codes in the request and compare them with the list passed to --load-only. Add the required code, restart so the model loads, and retest. Narrow loading saves startup and storage only when the resulting coverage matches the application.
Requests are rejected unexpectedly
Compare the request with every configured limit: API-key requirement, request rate, character count, batch size and any edge-origin rule. Test with a small known-good request, then increase one dimension at a time. This distinguishes an authentication failure from a payload or rate-limit failure.
Restarts take too long
Check whether a container recreation discarded the model volume or whether an update is downloading models at startup. Persist the model directory and load only the languages you need. Run model updates deliberately instead of coupling them to every deployment.
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Practical deployment decision table
| Decision | Option A | Option B | What changes |
|---|---|---|---|
| Application packaging | pip and a virtual environment | Docker image | pip is simple to inspect; Docker improves dependency isolation and repeatability but requires image and volume lifecycle management. |
| Process serving | Direct libretranslate process |
Gunicorn | The direct process is useful for testing; Gunicorn is the documented production direction for long-running service operation. |
| Public networking | Loopback plus reverse proxy | Direct external bind | Loopback limits exposure and centralizes TLS at the proxy; direct binding requires you to implement TLS, firewall and access policy at that boundary. |
| Language coverage | All available languages | --load-only list |
All languages maximize immediate coverage; a narrowed list reduces model loading and startup work but excludes unlisted pairs. |
| Access control | Default unlimited, keyless mode | API keys with limits | The default is convenient for local testing; keys and calibrated limits provide accountability and better abuse resistance for public traffic. |
A safe first production rollout
- Create the VPS user, firewall policy and persistent storage you will use for the service.
- Install with pip, Docker or Gunicorn and confirm the default local endpoint.
- Choose the language list and update models before opening client access.
- Set character, request and batch limits based on the application’s real payloads.
- Enable API-key enforcement with
--req-limit 0 --api-keyswhen every request must be authenticated. - Place the service behind a TLS-terminating reverse proxy, or document and secure every component of a direct exposure design.
- Run the
/translatePOST test locally, through the proxy, with an invalid credential and with a valid credential. - Enable
--metricsonly when the endpoint is protected and a collector is ready. - Document update and rollback steps, then monitor memory, restarts, model loading and rejected traffic.
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