Ollama

Ollama — run LLMs locally with a simple CLI and REST API.

AnalyticsSimple

Stack Components

RuntimeOllama

Backendllama.cpp

Why

One command to run any model, GGUF quantization, REST API, no GPU required. PostHog and Plausible offer privacy-first analytics without GDPR consent banners, growing 200% in 2024.

BigQuery and ClickHouse process petabyte-scale data at $5/TB scanned.

When

Use for local/private LLM inference. Avoid for high-throughput production.

How

1. Install ollama 2. ollama pull llama3.2 3. ollama run llama3.2 4. Use REST API at :11434 5. Add environment configuration — cp .env.example .env && edit values 6. Run tests — npm test or pnpm test to verify setup 7. Deploy — git push to trigger CI/CD or manual deploy

Example

curl http://localhost:11434/api/generate -d '{ "model": "llama3.2", "prompt": "Why is the sky blue?" }'

Common Problems

⚠Model not found — ollama pull first
⚠Slow on CPU — use smaller or quantized models
⚠Configuration drift between environments — use infrastructure-as-code (Terraform/Pulumi) to keep dev/staging/prod identical

Best Practices

✓Use Modelfile for custom configurations
✓Set num_ctx for longer context
✓Set up health checks and graceful shutdown — handle SIGTERM to drain in-flight requests before exit

FAQ

What is Ollama and what projects is it for?

Ollama — run LLMs locally with a simple CLI and REST API. It pairs layered technologies for end-to-end type safety and out-of-the-box deploys, fitting everything from MVPs to production SaaS.

How do I spin up a working demo with Ollama in 10 minutes?

Two steps: (1) Install ollama; (2) ollama pull llama3.2. Get the local dev server running, then wire one real data source to verify the end-to-end loop.

What is the most common pitfall with Ollama and how do I avoid it?

The most common pitfall is: Model not found — ollama pull first. Avoid it by adding the matching checklist to your PR template and running type-check + lint + unit tests in CI — three gates before merge.

What are the best practices for Ollama?

Best practices for Ollama include: Use Modelfile for custom configurations; Set num_ctx for longer context; Set up health checks and graceful shutdown — handle SIGTERM to drain in-flight requests before exit. The first one — "Use Modelfile for custom configurations" — should be set up at project init to avoid costly rework later.

When should I NOT choose Ollama?

Pick something else in three cases: (1) the team has zero experience with the core framework and the deadline is tight (learning-curve risk); (2) it's a pure content/marketing site (Astro is lighter); (3) you need very high throughput (>10k RPS) or strict-consistency microservices (Go/Rust). Ollama shines for mid-to-high complexity full-stack and API work — don't over-engineer simple static pages with it.