Welcome to the TFC API. If you have any issues or feedback please get in touch with us at support@theforecastingcompany.com.
https://api.retrocast.comPerform inference with foundation models.
Authorization
The Authorization header is used to authenticate with the API using your API key. Value is of the format Bearer YOUR_KEY_HERE.
model
The forecasting model to use for inference. Note that only tabpfn-ts, moirai and moirai-moe support exogenous variables.
moirai
chronos
chronos-bolt
timesfm
timesfm-2
moirai-moe
tabpfn-ts
series
horizon
Number of steps to forecast given the frequency.
freq
Frequency of the time series.
H
D
W
M
Q
Y
15min
contextThe amount of history to use when forecasting. This is the number of steps to look back in the target series. More history can improve the forecast accuracy, but can also increase the computation time. By default this is set to the max of model capability or the length of the provided target series, whichever is shorter.
quantiles
covariatesApply additional co-variates provided by TFC. Only supported by the following models: Navi, Moirai, Moriai-MoE and TabPFN-TS.
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{
"series": [
{
"future_variables": {
"local_attendance_forecast": [
125,
75,
200,
122,
123,
150,
100,
120,
121,
119
]
},
"future_variables_index": [
"2001-01-06",
"2001-01-07",
"2001-01-08",
"2001-01-09",
"2001-01-10",
"2001-01-11",
"2001-01-12",
"2001-01-13",
"2001-01-14",
"2001-01-15"
],
"hist_variables": {
"temperature": [
74,
72,
79,
77,
75
]
},
"index": [
"2001-01-06",
"2001-01-07",
"2001-01-08",
"2001-01-09",
"2001-01-10"
],
"static_variables": {
"Population": 100000
},
"target": [
125,
120,
140,
135,
133
]
}
],
"horizon": 5,
"freq": "D",
"context": 20,
"quantiles": [
0.1,
0.9,
0.4,
0.5
],
"covariates": [
{
"config": {
"country": "US"
},
"type": "holidays'"
}
]
}Perform historic inference for a range of forecast creation dates (fcds). These jobs can run longer and need to be retrieved with a separate endpoint and the returned job ID.
Authorization
The Authorization header is used to authenticate with the API using your API key. Value is of the format Bearer YOUR_KEY_HERE.
model
The forecasting model to use for inference. Note that only tabpfn-ts, moirai, and moirai-moe support exogenous variables.
tabpfn-ts
moirai
chronos
chronos-bolt
timesfm
timesfm-2
time-moe
series
horizon
Number of steps to forecast given the frequency.
freq
Frequency of the time series.
H
D
W
M
Q
Y
15min
contextThe amount of history to use when forecasting. This is the number of steps to look back in the target series. More history can improve the forecast accuracy, but can also increase the computation time. By default this is set to the max of model capability or the length of the provided target series, whichever is shorter.
quantiles
covariatesApply additional co-variates provided by TFC. Only supported by the following models: Navi, Moirai, Moriai-MoE and TabPFN-TS.
1
{
"series": [
{
"future_variables": {
"local_attendance_forecast": [
125,
75,
200,
122,
123,
150,
100,
120,
121,
119
]
},
"future_variables_index": [
"2001-01-06",
"2001-01-07",
"2001-01-08",
"2001-01-09",
"2001-01-10",
"2001-01-11",
"2001-01-12",
"2001-01-13",
"2001-01-14",
"2001-01-15"
],
"hist_variables": {
"temperature": [
74,
72,
79,
77,
75
]
},
"index": [
"2001-01-06",
"2001-01-07",
"2001-01-08",
"2001-01-09",
"2001-01-10"
],
"static_variables": {
"Population": 100000
},
"target": [
125,
120,
140,
135,
133
]
}
],
"horizon": 5,
"freq": "D",
"context": null,
"quantiles": [
0.1,
0.9,
0.4,
0.5
],
"covariates": [
{
"config": {
"country": "US"
},
"type": "holidays'"
}
]
}Retrieve the forecast result from a retrocast job.
Authorization
The Authorization header is used to authenticate with the API using your API key. Value is of the format Bearer YOUR_KEY_HERE.
job_id
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Return the OpenAPI spec for the TFC API.
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