Model tester

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Use the API

Read endpoints are open. Write endpoints require an API key in X-API-Key. Time series models can expose /forecast and /evaluate through a per-model adapter.

# List models
                        curl -s ${API_BASE}models

                        # Predict (generic)
                        curl -s -X POST ${API_BASE}predict/<model_name> \
                        -H "Content-Type: application/json" \
                        -d '{"input": [[0,0,0,0]]}'

                        # Upload (protected)
                        curl -s -X POST ${API_BASE}models/upload \
                        -H "X-API-Key: YOUR_KEY" \
                        -F "model_name=my_model" \
                        -F "model=@/path/to/model.pkl" \
                        -F "overwrite=true"

import requests
                API_BASE = "https://your-api-host/"
                r = requests.post(API_BASE + "predict/rf_demo",
                            json={"input": [[0,0,0,0]]})
                print(r.status_code, r.json())

Upload a model

Accepts .pkl, .joblib, or a .zip that may include metadata.json, metrics.json, and inference.py.

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