ConfigGenerator

Ollama Docker Generator

Generate Ollama Docker Compose configs with models, volumes, ports, GPU support, environment variables, health checks, and deployment notes.

Output:A ready-to-use configuration file for Ollama Docker with best practices applied.

The primary model to pull on startup (e.g., llama3.1, mistral, qwen2.5).

Default is 11434.

- Pass GPU devices into the Docker container.
- Save downloaded models to a volume so they aren't lost on restart.

Where to map the volume on the host.

- Add an OpenAI-compatible web interface to the compose stack.

Comma-separated domains or '*' to allow web apps to hit the API.

How long to keep models in VRAM (e.g., 5m, 1h, -1 for forever).

e.g., '4.0' to restrict to 4 CPU cores.

e.g., '16g' to restrict to 16GB RAM.

What is this tool?

Short answer: Use an Ollama Docker Generator when you want to run local LLM models with Docker Compose, persistent volumes, GPU support, and model setup notes.

The Ollama Docker Generator creates optimized docker-compose.yml files for running large language models locally. It handles complex Docker GPU passthrough settings, port bindings, and persistent volumes automatically.

Note: Docker-based Ollama deployment is mainly for desktop, server, or containerized cloud environments. It is not intended for native Android or iOS application deployments.

How to Use This Tool

  1. Select Hardware: Choose whether to enable NVIDIA, AMD, or Apple Silicon GPU acceleration.
  2. Configure Networking: Bind to 127.0.0.1 for local-only access or 0.0.0.0 for LAN access.
  3. Add UI: Toggle the inclusion of Open WebUI for a ChatGPT-like interface alongside the API.
  4. Generate: Get the docker-compose file, a `.env.example`, and a setup script to pull models automatically.

Best Practices

  • Always use persistent volumes (`/root/.ollama`) so you don't have to re-download multi-gigabyte models on container restart.
  • Bind to `127.0.0.1` (localhost) unless you specifically need other devices on your network to access the API.
  • Use Docker resource limits (CPU/Mem) if you are running other critical services on the same host.
  • Combine Ollama with Open WebUI in a single compose file for a fully featured local AI workspace.

Common Mistakes

  • Forgetting to install the NVIDIA Container Toolkit on Linux before attempting GPU passthrough.
  • Binding to `0.0.0.0` on a public cloud server without a reverse proxy (this exposes your compute to attackers).
  • Not setting `OLLAMA_KEEP_ALIVE`, causing models to unload from VRAM too quickly during active chat sessions.

Security Notes

  • Ollama does NOT have built-in authentication. If you bind to `0.0.0.0`, you MUST put it behind Nginx or Traefik with Basic Auth or OAuth.
  • Do not run the container as `--privileged` unless strictly necessary.
  • Regularly pull the latest Ollama image to patch vulnerabilities in its internal dependencies.

How We Keep Your Configs Safe & Valid

Built-in Error Checking

Every file is checked against official rules. We catch missing fields and bad syntax. YAML indentation errors are flagged right away. Kubernetes, Terraform, and Docker specs are all covered. API versions and labels are verified too. You get valid output every time you generate.

100% Private & Local

All tools run in your browser only. Your API keys never leave your machine. We do not use any tracking scripts. No data is sent to any server. Passwords and secrets stay on your device. Crypto operations use the Web Crypto API. Your privacy is fully protected at all times.

Secure Settings by Default

Configs use safe defaults out of the box. Containers run as non-root users. Root filesystems are set to read-only. Dangerous Linux capabilities are dropped. Network policies limit pod-to-pod traffic. TLS 1.3 is enabled for web servers. Security headers are added where needed.

Ready for CI/CD & Git

Output files are ready for your Git repo. Use them with ArgoCD, Flux, or GitHub Actions. Files use clear formatting and comments. Code review is easy for your team. Indentation and key order are consistent. Test in staging before going to production. Every file is clean and well-structured.

Infrastructure as Code

Store configs in Git alongside your code. Terraform modules include typed variables. Backend configs support remote state locking. Outputs work across multiple modules. Ansible playbooks use clear task steps. Chef and Puppet configs are also supported. Every file works with version control tools.

Monitoring & Tracing

Set up Prometheus with auto-discovery rules. Create Grafana dashboards with template variables. Add alerting rules with severity labels. Use OpenTelemetry for trace collection. Forward logs to Loki or Elasticsearch. Connect to Jaeger or Tempo for tracing. Monitor metrics, logs, and traces together.

Container & Docker Safety

Dockerfiles use multi-stage builds for small images. Base images are pinned to exact versions. Dev files are excluded from final images. Health checks are added for orchestrator use. Containers switch to non-root users. Docker Compose uses named volumes and networks. Resource limits are set in deploy configs.

Multiple Output Formats

Export as YAML, JSON, HCL, or TOML. Kubernetes uses YAML with proper separators. Terraform uses HCL with correct escaping. JSON output has consistent indentation. Copy to clipboard with one click. Preview output with syntax highlighting. Line numbers help you review quickly.

Related Tools

Docker Compose GeneratorLangChain Config GeneratorVector Database Config GeneratorKubernetes YAML Generators

Frequently Asked Questions

What is an Ollama Docker Generator?

An Ollama Docker Generator creates optimized `docker-compose.yml` and Dockerfile configurations tailored for running local LLMs securely, automatically handling GPU passthrough, volume persistence, and networking settings.

How do I run Ollama with Docker Compose?

Simply use this tool to generate a `docker-compose.yml` file, place it in an empty directory, and run `docker-compose up -d`. This will pull the official Ollama Docker image and start the service.

Can I use GPU with Ollama Docker?

Yes, you can enable GPU acceleration. For NVIDIA GPUs on Linux, you must also install the NVIDIA Container Toolkit and ensure the generated compose file includes the `deploy.resources.reservations.devices` block.

How do I set Ollama Docker environment variables?

You can pass variables directly in the `environment:` section of the compose file or through an `.env` file. Common variables include `OLLAMA_KEEP_ALIVE` and `OLLAMA_HOST`.

How do I preload a model in Ollama Docker?

You can run an execution script after startup (`docker exec -it ollama ollama run llama3`), or you can create a custom `Dockerfile` that `FROM ollama/ollama` and runs the pull command during the build phase.

Can I deploy Ollama on Kubernetes?

Yes, Ollama can be deployed on Kubernetes. You will need to convert the generated Docker compose logic into Kubernetes Deployments and Services, and use a NodeSelector for GPU nodes.

Does Ollama Docker work with LangChain?

Absolutely. Once the Ollama Docker container is running locally (usually on port 11434), you can point any LangChain application to it by setting the `base_url` to `http://localhost:11434`.

Is this an official Ollama Docker image generator?

No, this is a community tool. It generates valid configurations that utilize the official Ollama Docker image provided by the Ollama team on Docker Hub.