# Veri Documentation

## Docs

- [API Keys](https://docs.veri.studio/api-reference/api-keys.md): Create, list, and revoke API keys
- [Billing](https://docs.veri.studio/api-reference/billing.md): Check credit balance and transaction history
- [Cost](https://docs.veri.studio/api-reference/cost.md): Estimate and track training costs
- [Datasets](https://docs.veri.studio/api-reference/datasets.md): Upload and manage training datasets
- [Deployments](https://docs.veri.studio/api-reference/deployments.md): Deploy models as inference endpoints
- [API Reference](https://docs.veri.studio/api-reference/introduction.md): Complete reference for the Veri REST API
- [Reward Functions](https://docs.veri.studio/api-reference/reward-functions.md): Upload and manage Python reward functions
- [SSH Keys](https://docs.veri.studio/api-reference/ssh-keys.md): Manage SSH keys for VM-based compute providers
- [Training Jobs](https://docs.veri.studio/api-reference/training-jobs.md): Create, monitor, and manage training jobs
- [API / SDK](https://docs.veri.studio/api-sdk.md): Use Veri through the REST API, Python SDK, or CLI
- [Changelog](https://docs.veri.studio/changelog.md): Recent product and platform changes in Veri
- [CLI](https://docs.veri.studio/cli.md): Log in locally and manage Veri credentials from the command line
- [Datasets](https://docs.veri.studio/concepts/datasets.md): Preparing and uploading training datasets
- [GRPO Training](https://docs.veri.studio/concepts/grpo-training.md): How Group Relative Policy Optimization works in Veri
- [Reward Functions](https://docs.veri.studio/concepts/reward-functions.md): How to write reward functions for GRPO training
- [Cookbook](https://docs.veri.studio/cookbook.md): Practical starting points for common Veri workflows
- [Deployment](https://docs.veri.studio/deployment.md): Deploy fine-tuned models as inference endpoints
- [Evaluations](https://docs.veri.studio/evaluations.md): Run automated evaluations against trained checkpoints and deployments
- [Prepare a Custom Dataset](https://docs.veri.studio/examples/custom-dataset.md): Format JSONL examples and launch a Veri training job
- [Fine-tune for Function Calling](https://docs.veri.studio/examples/function-calling.md): Train a model to produce valid tool calls and structured JSON
- [Improve Domain Answers with GRPO](https://docs.veri.studio/examples/grpo-domain-qa.md): Use a reward function to optimize answers for a domain-specific rubric
- [Examples](https://docs.veri.studio/examples/index.md): Starting points for common Veri training workflows
- [Function Calling](https://docs.veri.studio/function-calling.md): Fine-tune models for structured outputs and tool-oriented behavior
- [Build with Veri](https://docs.veri.studio/index.md): Fine-tune open-source models to be the best for your use-case
- [Playground](https://docs.veri.studio/playground.md): Use the playground to explore the Veri product experience
- [Quickstart](https://docs.veri.studio/quickstart.md): Train your own reasoning model in minutes
- [Recommended Models](https://docs.veri.studio/recommended-models.md): How to choose the right model for your Veri workflow
- [Python SDK](https://docs.veri.studio/sdks/python.md): Official Python SDK for the Veri API
- [Security & Compliance](https://docs.veri.studio/security-compliance.md): Current status of security and compliance work at Veri
- [Supervised Fine-Tuning](https://docs.veri.studio/supervised-finetuning.md): Fine-tune video generation models with LoRA SFT

## OpenAPI Specs

- [openapi](https://docs.veri.studio/api-reference/openapi.json)