{
  "$schema": "https://mintlify.com/docs.json",
  "banner": {
    "content": "🚀  **TimeGPT-2** is here, the next generation of foundation models for time series forecasting! [Read the full announcement](https://www.nixtla.io/blog/timegpt-2-announcement)",
    "dismissible": true
  },
  "theme": "mint",
  "name": "TimeGPT Foundational model for time series forecasting and anomaly detection",
  "colors": {
    "primary": "#161616",
    "light": "#FFF",
    "dark": "#161616"
  },
  "favicon": "/favicon.ico",
  "ignore": [
    "utils/**",
    "depracted-docs/**",
    "pending_content/**"
  ],
  "navigation": {
    "groups": [
      {
        "group": "INTRODUCTION",
        "pages": [
          "/introduction/introduction",
          "/introduction/why_timegpt",
          "/introduction/about_timegpt",
          "/introduction/timegpt_subscription_plans",
          "/introduction/faq"
        ]
      },
      {
        "group": "SETUP",
        "pages": [
          "/setup/setting_up_your_api_key",
          "/setup/python_wheel",
          "/setup/docker",
          "/setup/azureai"
        ]
      },
      {
        "group": "DATA REQUIREMENTS",
        "pages": [
          "/data_requirements/data_requirements",
          "/data_requirements/multiple_series",
          "/data_requirements/missing_values",
          "/data_requirements/audit_clean"
        ]
      },
      {
        "group": "FORECASTING",
        "pages": [
          "/forecasting/timegpt_quickstart",
          {
            "group": "Exogenous variables",
            "pages": [
              "/forecasting/exogenous-variables/numeric_features",
              "/forecasting/exogenous-variables/categorical_features",
              "/forecasting/exogenous-variables/holiday_and_special_dates",
              "/forecasting/exogenous-variables/date_features",
              "/forecasting/exogenous-variables/interpretability_with_shap"
            ]
          },
          {
            "group": "Fine-tuning",
            "pages": [
              "/forecasting/fine-tuning/steps",
              "/forecasting/fine-tuning/depth",
              "/forecasting/fine-tuning/custom_loss",
              "/forecasting/fine-tuning/save_reuse_delete_finetuned_models"
            ]
          },
          {
            "group": "Probabilistic forecasting",
            "pages": [
              "/forecasting/probabilistic/introduction",
              "/forecasting/probabilistic/prediction_intervals",
              "/forecasting/probabilistic/quantiles"
            ]
          },
          {
            "group": "Model versions",
            "pages": [
              "/forecasting/model-version/longhorizon_model"
            ]
          },
          {
            "group": "Evaluation",
            "pages": [
              "/forecasting/evaluation/cross_validation",
              "/forecasting/evaluation/evaluation_metrics",
              "/forecasting/evaluation/evaluation_utilsforecast"
            ]
          },
          {
            "group": "Special topics",
            "pages": [
              "/forecasting/special-topics/irregular_timestamps",
              "/forecasting/special-topics/bounded_forecasts",
              "/forecasting/special-topics/hierarchical_forecasting",
              "/forecasting/special-topics/temporal_hierarchical"
            ]
          },
          "/forecasting/improve_accuracy",
          {
            "group": "Forecasting at scale",
            "pages": [
              "/forecasting/forecasting-at-scale/computing_at_scale",
              "/forecasting/forecasting-at-scale/spark",
              "/forecasting/forecasting-at-scale/dask",
              "/forecasting/forecasting-at-scale/ray"
            ]
          }
        ]
      },
      {
        "group": "ANOMALY DETECTION",
        "pages": [
          "/anomaly_detection/historical_anomaly_detection",
          "/anomaly_detection/exogenous_variables",
          {
            "group": "Real-time anomaly detection",
            "pages": [
              "/anomaly_detection/real-time/introduction",
              "/anomaly_detection/real-time/adjusting_detection",
              "/anomaly_detection/real-time/univariate_multivariate"
            ]
          }
        ]
      },
      {
        "group": "USE CASES",
        "pages": [
          "/use_cases/forecasting_web_traffic",
          "/use_cases/bitcoin_price_prediction",
          "/use_cases/forecasting_energy_demand",
          "/use_cases/forecasting_intermittent_demand",
          "/use_cases/what_if_forecasting_price_effects_in_retail"
        ]
      },
      {
        "group": "REFERENCE",
        "pages": [
          "/reference/sdk_reference",
          "/reference/date_features",
          "/reference/timegpt_excel_add_in_beta_",
          "/reference/timegpt_in_r"
        ],
        "openapi": "./openapi.json"
      },
      {
        "group": "About",
        "pages": [
          "/about/key-concepts",
          "/about/sub-categoria",
          "/about/terms-and-conditions",
          "/about/privacy-notice"
        ]
      }
    ],
    "global": {
      "anchors": [
        {
          "anchor": "Home",
          "href": "https://www.nixtla.io",
          "icon": "book-open-cover"
        },
        {
          "anchor": "Get in touch",
          "href": "https://share.hsforms.com/2kPRkvHcfRHO5m4Qqc9wKqArbxr6",
          "icon": "envelope"
        },
        {
          "anchor": "Meet with us",
          "href": "https://meetings.hubspot.com/cristian-challu/enterprise-contact-us?uuid=dc037f5a-d93b-4%5B…%5D90b-a611dd9460af&utm_source=docs&utm_medium=docs",
          "icon": "calendar"
        }
      ]
    }
  },
  "logo": {
    "light": "/logo/light.svg",
    "dark": "/logo/dark.svg"
  },
  "navbar": {
    "links": [
      {
        "label": "Book a meeting",
        "href": "https://meetings.hubspot.com/cristian-challu/enterprise-contact-us?uuid=dc037f5a-d93b-4%5B…%5D90b-a611dd9460af&utm_source=docs&utm_medium=docs"
      }
    ],
    "primary": {
      "type": "button",
      "label": "Get Started",
      "href": "https://dashboard.nixtla.io"
    }
  },
  "footer": {
    "socials": {
      "x": "https://x.com/nixtlainc",
      "github": "https://github.com/nixtla",
      "linkedin": "https://linkedin.com/company/nixtlainc"
    }
  },
  "integrations": {
    "amplitude": {
      "apiKey": "799ca210229ab5f1a23493c6302eaae1"
    },
    "gtm": {
      "tagId": "GTM-TBJ64S3X"
    },
    "posthog": {
      "apiKey": "phc_hblNl72piphlbRCYfGM8QkgazW9NNrDrP6dMbGzMp82"
    },
    "intercom": {
      "appId": "j7y9c2ep"
    }
  },
  "redirects": [
    {
      "source": "/use-cases-forecasting_web_traffic",
      "destination": "/use_cases/forecasting_web_traffic"
    },
    {
      "source": "/use-cases-bitcoin_price_prediction",
      "destination": "/use_cases/bitcoin_price_prediction"
    },
    {
      "source": "/use-cases-forecasting_energy_demand",
      "destination": "/use_cases/forecasting_energy_demand"
    },
    {
      "source": "/use-cases-forecasting_intermittent_demand",
      "destination": "/use_cases/forecasting_intermittent_demand"
    },
    {
      "source": "/use-cases-what_if_forecasting_price_effects_in_retail",
      "destination": "/use_cases/what_if_forecasting_price_effects_in_retail"
    },
    {
      "source": "/getting-started-timegpt_quickstart",
      "destination": "/forecasting/timegpt_quickstart"
    },
    {
      "source": "/tutorials-special_topics-tutorials-improve_forecast_accuracy_with_timegpt",
      "destination": "/forecasting/improve_accuracy"
    },
    {
      "source": "/capabilities-anomaly-detection-anomaly_detection",
      "destination": "/anomaly_detection/historical_anomaly_detection"
    },
    {
      "source": "/getting-started-timegen_1_quickstart_azure_",
      "destination": "/setup/azureai"
    },
    {
      "source": "/capabilities-forecast-cross_validation",
      "destination": "/forecasting/evaluation/cross_validation"
    },
    {
      "source": "/capabilities-forecast-multiple_series_forecasting",
      "destination": "/data_requirements/multiple_series"
    },
    {
      "source": "/tutorials-computing_at_scale",
      "destination": "/forecasting/forecasting-at-scale/computing_at_scale"
    },
    {
      "source": "/tutorials-special_topics-tutorials-hierarchical_forecasting",
      "destination": "/forecasting/special-topics/temporal_hierarchical"
    },
    {
      "source": "/tutorials-exogenous_variables-tutorials-shap_values_for_timegpt_and_timegen",
      "destination": "/forecasting/exogenous-variables/interpretability_with_shap"
    },
    {
      "source": "/tutorials-uncertainty_quantification-tutorials-prediction_intervals",
      "destination": "/forecasting/probabilistic/introduction#uncertainty-quantification-with-timegpt"
    }
  ],
  "contextual": {
    "options": [
      "copy",
      "view",
      "chatgpt",
      "claude"
    ]
  }
}