> For the complete documentation index, see [llms.txt](https://docs.graphite-note.com/graphite-note-documentation/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.graphite-note.com/graphite-note-documentation/rest-api/prediction-api/request-timeseries.md). # Request (Timeseries) ## Method API is using **POST** method Supports:\ ✅ **Time Series Forecasting** (predicting numeric values over a date range) ## Request URL ``` https://app.graphite-note.com/api/v1/prediction/model/[model-code] ``` Replace `[model-code]` with your model’s code.\ Find it in the model’s **Settings → ID** section. ## Headers * **Authorization:** `Bearer [token]`\ (Get your token in **Account Info** inside the app.) * **Content-Type:** `application/json` ## Body The v1 time-series API expects a structured object at `data.predict_values`: Required fields * `startDate` (string, `YYYY-MM-DD`) * `endDate` (string, `YYYY-MM-DD`) * `sequenceID` (string; use `"n/a"` if not applicable) Conditional field * `daysData` (array) — **only** when the model was trained **with regressors**.\ One object per date with: * `date` (string, `YYYY-MM-DD`) * All regressor columns used in training (e.g., `promotion`, `price`, `weather`, …) > If the model used regressors, you must supply **every regressor for every date** in the requested range via `daysData`. *** ### Example A — Without regressors ```bash curl -L -X POST 'https://app.graphite-note.com/api/v1/prediction/model/[model-code]' \ -H 'Authorization: Bearer [token]' \ -H 'Content-Type: application/json' \ -d '{ "data": { "predict_values": { "startDate": "2025-10-01", "endDate": "2025-12-01", "sequenceID": "Store001" } } }' ``` **Typical response** ```json { "data": [ { "date": "2025-10-01T00:00:00.000", "predicted": 1225707.2645253073, "predicted_lower": 1190271.3575973918, "predicted_upper": 1257483.2005986127 }, { "date": "2025-11-01T00:00:00.000", "predicted": 1354638.5614777768, "predicted_lower": 1322609.8547555234, "predicted_upper": 1388121.5808224094 }, { "date": "2025-12-01T00:00:00.000", "predicted": 1882129.6128404615, "predicted_lower": 1847289.9345675157, "predicted_upper": 1913548.0087476152 }, { "sequenceID": "Store001" } ] } ``` *** ### Example B — With regressors (`daysData` required) ```bash curl -L -X POST 'https://app.graphite-note.com/api/v1/prediction/model/[model-code]' \ -H 'Authorization: Bearer [token]' \ -H 'Content-Type: application/json' \ -d '{ "data": { "predict_values": { "startDate": "2025-09-22", "endDate": "2025-09-29", "sequenceID": "Alpha", "daysData": [ { "date": "2025-09-22", "promotion": "A" }, { "date": "2025-09-29", "promotion": "B" } ] } } }' ``` **Typical response** ```json { "data": [ { "date": "2025-09-22T00:00:00.000", "predicted": 2370.4695876452001, "predicted_lower": 2279.2000645561998, "predicted_upper": 2458.3810902849 }, { "date": "2025-09-29T00:00:00.000", "predicted": 2694.2617946204, "predicted_lower": 2604.5116258851999, "predicted_upper": 2788.9465525872001 }, { "sequenceID": "Alpha" } ] } ``` *** ## Parameter Reference | Field | Type | Required | Description | | ------------- | ------ | ----------- | ----------------------------------------------------------------------------------------- | | `startDate` | string | Yes | Start of prediction window (`YYYY-MM-DD`). Must align to model frequency. | | `endDate` | string | Yes | End of prediction window (`YYYY-MM-DD`). Inclusive for requested outputs. | | `sequenceID` | string | Yes | Sequence identifier. Use `"n/a"` if not used by your workflow. | | `daysData` | array | Conditional | Only for models trained **with regressors**. One row per date. | | `date` | string | Conditional | Inside `daysData`. Date the regressor values apply to (`YYYY-MM-DD`). | | `` | any | Conditional | Inside `daysData`. Every regressor column used in training must be present for each date. | **Response fields** * `date`: ISO datetime string (`YYYY-MM-DDT00:00:00.000`) aligned to the model frequency. * `predicted`: point forecast. * `predicted_lower`, `predicted_upper`: uncertainty bounds. * A trailing object with `{ "sequenceID": "…" }` echoes your request identifier. *** ## Validation Rules & Tips * **Dates:** Use `YYYY-MM-DD`. Ensure the range matches model frequency (daily, weekly, monthly). * **Regressors:** For regressor-trained models, provide **all regressors** for **every date** in `daysData`. Missing any will prevent forward predictions. * **Types:** Match training schema. Numeric vs categorical must align with what the model expects. * **Range size:** Extremely large ranges may be throttled. Test with a small window first. * **Echoed sequence:** The API echoes your `sequenceID` at the end of the response array to help correlate requests. *** --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. 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