YAML Generator
Commercial use OK
380+ models
No watermark
No sign-up needed
Model:
+ GPT-5, Claude, Gemini
Write, validate, or generate YAML — Kubernetes manifests, GitHub Actions workflows, Docker Compose, CircleCI, Ansible, Helm values. Pick a flavor preset and describe what you want, or paste existing YAML to lint, explain, or convert to JSON/TOML.
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Generate YAML configs with free AI. Kubernetes, Docker, CI/CD, and more.
How to Use YAML Generator
1
Enter your input
Type text, upload a file, or describe what you want. No account needed.
2
Click generate
Our AI processes your request in seconds using the best open-source models.
3
Download & share
Download, copy, or share your result. Free for personal and commercial use.
Use this tool via API
Automate this tool from your own code. OpenAI-compatible REST endpoint, Bearer-token auth, no extra SDK required. Token costs match the web interface.
curl -X POST https://api.free.ai/v1/chat/ \
-H "Authorization: Bearer sk-free-..." \
-H "Content-Type: application/json" \
-d '{"model": "qwen-coder", "messages": [{"role": "user", "content": "Write a Python function that reverses a string."}]}'YAML Generator — FAQ
Generate, validate, explain, or convert YAML. 11 flavor presets — plain YAML 1.2, Kubernetes manifest, Helm values, GitHub Actions workflow, GitLab CI, CircleCI, Docker Compose, Ansible playbook, OpenAPI 3.1 spec, AWS CloudFormation, dbt project. Each preset loads a flavor-specific system prompt so the output passes the real validator on first try.
yamllint is a style / syntax linter only — it catches tabs, indent, trailing whitespace but has no idea whether your Kubernetes Deployment is valid against the k8s schema. Copilot ($10/mo) writes YAML inline as you type but knows the general YAML grammar, not flavor-specific rules. Free.ai combines both: syntactic validation + schema-aware generation with flavor-specific prompts (latest apiVersion for k8s 1.28+, actions/setup-* @v5+, Docker Compose v3 healthchecks).
Yes — the system prompt pins to current stable versions: Kubernetes 1.28+ apiVersions, actions/checkout@v4+ and actions/setup-*@v5+ for GitHub Actions, Ansible fully-qualified collection names (ansible.builtin.apt, not apt), OpenAPI 3.1 (with JSON Schema 2020-12). Models drift over time — always double-check deprecation timing against the upstream changelog.
Usually yes for standard resources (Deployment, Service, ConfigMap, Secret, Ingress). The prompt forces sensible defaults — resources.limits + requests set, readiness/liveness probes included, labels with app.kubernetes.io/name. Always run kubectl apply --dry-run=client before actually applying. For Ingress / StorageClass / admission-webhook style resources, the model may need hand-tuning.
In validate mode, yes — flags :latest image tags, privileged:true, hostNetwork:true, missing readOnlyRootFilesystem, missing resource limits (DoS risk), unrestricted RBAC verbs, secrets checked into manifests. Dedicated security scanners (kube-bench, kube-score, polaris) go deeper; use them in CI after the initial generation.
Yes — JSON-to-YAML and YAML-to-JSON actions. The shape is preserved exactly. Anchors / aliases in YAML are inlined (JSON has no equivalent). Multi-document YAML (separated by three dashes) becomes a JSON array of documents.
Uses YAML 1.2 semantics: "no" and "on" are strings, not booleans (1.1 autoconverted these — called the Norway problem). Quotes non-obvious strings to prevent ambiguity. Uses pipe for preserved-newlines strings and > for folded strings where appropriate. If the input uses 1.1 conventions, the validator flags the ambiguities.
Yes — pick "Explain each section". The model walks through every top-level key, states the effective behavior when the file is applied / run, and flags common pitfalls. Great for onboarding onto an existing project k8s manifests or CI configs.
OpenAPI preset generates valid OpenAPI 3.1 (not 3.0 — 3.1 aligns with JSON Schema 2020-12). Every operation gets summary, description, responses (at least 200 + 4xx), proper components/schemas with $ref. Validate with swagger-cli or Redocly before shipping.
Qwen 3 Coder (default, free) is very strong on YAML — it is in the training set heavily. Qwen 3 30B for general-purpose. Premium Claude Sonnet 4 / GPT-5 when generating a full Helm chart or multi-document Kubernetes bundle that needs cross-file consistency.
Input is sent to the model, processed, discarded. Not stored, not used for training. For maximum privacy pick Qwen 3 Coder — self-hosted on Free.ai's GPUs.
Yes — POST to /v1/chat/ with the YAML system prompt (flavor + action) and the input as the user message. Useful for CI steps that auto-generate manifests. See /api/.
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