# Wood Wide AI SDK Documentation

## Docs

- [Introduction](https://docs.woodwide.ai/Intro.md): Wood Wide AI provides a numeric reasoning API for AI applications and agents.
- [Datasets](https://docs.woodwide.ai/api-reference/datasets.md): Upload, manage, and version your tabular datasets.
- [Complete Signed-URL Upload](https://docs.woodwide.ai/api-reference/datasets/complete-signed-url-upload.md): Signal that the signed-URL upload is complete and trigger ingestion.
- [Create Dataset](https://docs.woodwide.ai/api-reference/datasets/create-dataset.md): Upload a CSV or Parquet file to create a new dataset or add a new version.
- [Delete Dataset](https://docs.woodwide.ai/api-reference/datasets/delete-dataset.md): Soft delete a dataset.
- [Get Dataset](https://docs.woodwide.ai/api-reference/datasets/get-dataset.md): Retrieves details for a specific dataset.
- [Get Dataset Version](https://docs.woodwide.ai/api-reference/datasets/get-dataset-version.md): Get details of a specific dataset version, including schema, stats, and ingestion status.
- [List Dataset Versions](https://docs.woodwide.ai/api-reference/datasets/list-dataset-versions.md): List all versions of a dataset in reverse chronological order.
- [List Datasets](https://docs.woodwide.ai/api-reference/datasets/list-datasets.md): List all datasets in the current organization.
- [List Models Trained on Dataset](https://docs.woodwide.ai/api-reference/datasets/list-models-trained-on-dataset.md): List all models with at least one version trained on any version of this dataset.
- [Look Up Dataset Rows](https://docs.woodwide.ai/api-reference/datasets/look-up-dataset-rows.md): Return full row data for one or more row IDs from the dataset's latest ready version.
- [Prepare Signed-URL Upload](https://docs.woodwide.ai/api-reference/datasets/prepare-signed-url-upload.md): Get a signed URL for uploading a large dataset file.
- [Preview Dataset Rows](https://docs.woodwide.ai/api-reference/datasets/preview-dataset-rows.md): Return a sample of rows from the dataset's latest ready version.
- [Update Dataset Metadata](https://docs.woodwide.ai/api-reference/datasets/update-dataset-metadata.md): Update dataset name and/or description.
- [Quickstart](https://docs.woodwide.ai/api-reference/getting-started.md): Authenticate, upload your first dataset, train a model, and run inference using the Wood Wide AI API.
- [Inference](https://docs.woodwide.ai/api-reference/inference.md): Run predictions on new data using a trained model.
- [Async Infer (Dataset)](https://docs.woodwide.ai/api-reference/inference/async-infer-dataset.md): Run inference asynchronously using a dataset reference instead of a file upload.
- [Async Infer (File Upload)](https://docs.woodwide.ai/api-reference/inference/async-infer-file-upload.md): Upload a CSV file and start inference asynchronously.
- [Infer (File Upload)](https://docs.woodwide.ai/api-reference/inference/infer-file-upload.md): Upload a CSV file and get results back immediately.
- [Jobs](https://docs.woodwide.ai/api-reference/jobs.md): Track and manage long-running training and inference jobs.
- [Cancel Job](https://docs.woodwide.ai/api-reference/jobs/cancel-job.md): Cancel a running or queued job. Best-effort — the job may have already completed by the time cancellation is processed.
- [Get Job Detail](https://docs.woodwide.ai/api-reference/jobs/get-job-detail.md): Get detailed job information including input, output, error, ML runtime info, and billing details.
- [Get Job Results](https://docs.woodwide.ai/api-reference/jobs/get-job-results.md): Get the typed results of a completed job.
- [List Jobs](https://docs.woodwide.ai/api-reference/jobs/list-jobs.md): List jobs for the current organization.
- [Retry Job](https://docs.woodwide.ai/api-reference/jobs/retry-job.md): Retry a failed job by creating a new job with the same parameters. Only failed jobs can be retried.
- [Models](https://docs.woodwide.ai/api-reference/models.md): Train, retrain, and manage your models.
- [Delete Model](https://docs.woodwide.ai/api-reference/models/delete-model.md): Soft delete a model.
- [Get Model](https://docs.woodwide.ai/api-reference/models/get-model.md): Get model details.
- [Get Model Version](https://docs.woodwide.ai/api-reference/models/get-model-version.md): Get details of a specific model version.
- [List Model Versions](https://docs.woodwide.ai/api-reference/models/list-model-versions.md): List all versions of a model.
- [List Models](https://docs.woodwide.ai/api-reference/models/list-models.md): List all models in the current organization.
- [Retrain Model](https://docs.woodwide.ai/api-reference/models/retrain-model.md): Retrain an existing model with new data, creating a new version.
- [Train Model](https://docs.woodwide.ai/api-reference/models/train-model.md): Create and train a new model.
- [Update Model Metadata](https://docs.woodwide.ai/api-reference/models/update-model-metadata.md): Update model metadata (name, description).
- [Pagination](https://docs.woodwide.ai/api-reference/pagination.md): Cursor-based pagination for list endpoints.
- [Rate Limits](https://docs.woodwide.ai/api-reference/rate-limits.md): Per-key rate limits enforced by the API.
- [Schema Inference and Coercion](https://docs.woodwide.ai/api-reference/schema-inference.md): Your inference data doesn't need to match your training data exactly -- Wood Wide AI handles the differences automatically.
- [Anomaly Detection](https://docs.woodwide.ai/capabilities/anomaly.md): Identify unusual rows in your data.
- [Clustering](https://docs.woodwide.ai/capabilities/clustering.md): Unsupervised grouping with human-readable cluster descriptions.
- [Embeddings](https://docs.woodwide.ai/capabilities/embeddings.md): Generate dense vector representations of each row.
- [Factor Analysis](https://docs.woodwide.ai/capabilities/factors.md): Discover the latent factors that explain variance in your data.
- [Overview](https://docs.woodwide.ai/capabilities/overview.md): Wood Wide AI supports six model types for tabular data: prediction, clustering, anomaly detection, embeddings, search, and factor analysis.
- [Prediction](https://docs.woodwide.ai/capabilities/prediction.md): Supervised classification and regression on a target column.
- [Search](https://docs.woodwide.ai/capabilities/search.md): Find the most similar training-set row for each query row.
- [Changelog](https://docs.woodwide.ai/changelog.md): Documentation updates and API changes.
- [Compound Insights](https://docs.woodwide.ai/compound-insight-recipes.md)
- [Data Preparation](https://docs.woodwide.ai/data-preparation-guide.md)
- [Improving Performance](https://docs.woodwide.ai/improving-performance.md): Practical strategies to improve Wood Wide AI model quality beyond the default configuration.

## OpenAPI Specs

- [openapi](https://docs.woodwide.ai/openapi.json)