emem Jepa Predict V2 API

openapi: 3.2.0
info:
  description: emem is shared memory for AI agents working together in the real world.
  license:
    name: Apache-2.0
  title: emem Jepa Predict V2 API
  version: 2.4.0
  x-emem-surface-asymmetry:
    memory_notes: MCP only
    reach_them_at: POST /mcp, method tools/call
    read_side_is_here:
    - /v1/memory/search
    - /v1/memory/sse
    - /memories/{path}
    tools:
    - emem_memory_create
    - emem_memory_view
    - emem_memory_delete
    - emem_memory_rename
    - emem_memory_str_replace
    - emem_memory_supersede
    why_not_here: These write the agent correspondence plane, which is prose and untrusted-by-declaration. It is deliberately not part of the REST fact surface, and the two planes are kept apart rather than merged for convenience.
servers:
- description: Hosted instance (HTTPS-only)
  url: https://emem.dev
tags:
- name: Jepa Predict V2
paths:
  /v1/jepa_predict_v2:
    post:
      description: 'Predict the next-step value of 4 environmental scalars at a cell (`indices.ndvi`, `modis.lst_day_8day`, `modis.lst_night_8day`, `cams.pm25`) using a small learned dynamics MLP. Reads up to K=6 most-recent attested lags per band, runs them through an ONNX dynamics head (~200k params, CPU-fast), and returns a per-band {value, confidence, n_real_lags, via}. The receipt''s `model` block carries `model_id`, `version`, `blake2b_hex` (model_cid), training/validation provenance, a top-level `skill_vs_persistence` block, and `honesty_warnings`, flagging `untrained_baseline` when the artifact is the zero-init sentinel and `NEGATIVE_SKILL` when the learned model is worse than persistence on real held-out NDVI. When the model does not beat persistence, bands with a real lag are returned from that lag tagged `via:persistence_fallback_negative_skill` (bands with no real lag fall back to labelled climatology). Distinct from v1 (`emem_jepa_predict`) which returns a single NDVI scalar via closed-form coefficients.


        When to use: Use when you want a short-horizon forecast of NDVI / land-surface temperature / PM2.5 at a cell grounded in its attested history. Returns 422 with a `/v1/backfill` hint when the cell lacks enough cached lags. Always read the receipt''s `model.honesty_warnings`, `untrained_baseline` means the trivial ''predict last vintage'' baseline (treat as no-op), and `NEGATIVE_SKILL` means the served values are the persistence fallback, not a learned improvement. Check each band''s `via` field to see whether its value came from the learned model, persistence, or climatology.'
      operationId: emem_jepa_predict_v2
      requestBody:
        content:
          application/json:
            schema:
              properties:
                cell:
                  description: cell64 or place name
                  type: string
                target_month:
                  description: Month-of-year to forecast (1-12); defaults to the month after now.
                  maximum: 12
                  minimum: 1
                  type: integer
              required:
              - cell
              type: object
        required: true
      responses:
        '200':
          content:
            application/json:
              schema:
                type: object
          description: ok
        default:
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ErrorEnvelope'
          description: 'error, the emem.error.v1 envelope. Branch on the stable `code` (see GET /v1/errors), not the message. A malformed or missing-field request body returns `code: invalid_argument` with the offending field named in `message`.'
      summary: 'learned multi-band-scalar dynamics head: predicts the next-step value of 4…'
      tags:
      - Jepa Predict V2
components:
  schemas:
    ErrorEnvelope:
      description: The `emem.error.v1` failure envelope returned by every endpoint on a 4xx/5xx. Branch on the stable `code` (not the human `message`). See GET /v1/errors for the full code catalog.
      properties:
        code:
          description: Stable machine-readable error code. One of the codes in GET /v1/errors.
          example: invalid_argument
          type: string
        details:
          description: Optional structured recovery hints; present on errors that ship machine-readable next-steps.
          type: object
        message:
          description: Human-readable detail. For invalid_argument this names the offending field (e.g. "missing field `q`").
          type: string
        path:
          description: Request path that produced the error.
          example: /v1/ask
          type: string
        schema:
          const: emem.error.v1
          type: string
      required:
      - code
      - message
      - schema
      type: object