diff --git a/config_examples/config_freqai.example.json b/config_examples/config_freqai.example.json
index 645c30227..65a93379e 100644
--- a/config_examples/config_freqai.example.json
+++ b/config_examples/config_freqai.example.json
@@ -48,7 +48,7 @@
],
"freqai": {
"enabled": true,
- "purge_old_models": true,
+ "purge_old_models": 2,
"train_period_days": 15,
"backtest_period_days": 7,
"live_retrain_hours": 0,
diff --git a/docs/freqai-configuration.md b/docs/freqai-configuration.md
index 88415bf59..886dc2338 100644
--- a/docs/freqai-configuration.md
+++ b/docs/freqai-configuration.md
@@ -9,7 +9,7 @@ FreqAI is configured through the typical [Freqtrade config file](configuration.m
```json
"freqai": {
"enabled": true,
- "purge_old_models": true,
+ "purge_old_models": 2,
"train_period_days": 30,
"backtest_period_days": 7,
"identifier" : "unique-id",
diff --git a/docs/freqai-parameter-table.md b/docs/freqai-parameter-table.md
index 23d2be8ef..7f0b0c213 100644
--- a/docs/freqai-parameter-table.md
+++ b/docs/freqai-parameter-table.md
@@ -15,7 +15,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
| `identifier` | **Required.**
A unique ID for the current model. If models are saved to disk, the `identifier` allows for reloading specific pre-trained models/data.
**Datatype:** String.
| `live_retrain_hours` | Frequency of retraining during dry/live runs.
**Datatype:** Float > 0.
Default: `0` (models retrain as often as possible).
| `expiration_hours` | Avoid making predictions if a model is more than `expiration_hours` old.
**Datatype:** Positive integer.
Default: `0` (models never expire).
-| `purge_old_models` | Delete all unused models during live runs (not relevant to backtesting). If set to false (not default), dry/live runs will accumulate all unused models to disk. If
**Datatype:** Boolean.
Default: `True`.
+| `purge_old_models` | Number of models to keep on disk (not relevant to backtesting). Default is 2, dry/live runs will keep 2 models on disk. Setting to 0 keeps all models. If
**Datatype:** Boolean.
Default: `2`.
| `save_backtest_models` | Save models to disk when running backtesting. Backtesting operates most efficiently by saving the prediction data and reusing them directly for subsequent runs (when you wish to tune entry/exit parameters). Saving backtesting models to disk also allows to use the same model files for starting a dry/live instance with the same model `identifier`.
**Datatype:** Boolean.
Default: `False` (no models are saved).
| `fit_live_predictions_candles` | Number of historical candles to use for computing target (label) statistics from prediction data, instead of from the training dataset (more information can be found [here](freqai-configuration.md#creating-a-dynamic-target-threshold)).
**Datatype:** Positive integer.
| `continual_learning` | Use the final state of the most recently trained model as starting point for the new model, allowing for incremental learning (more information can be found [here](freqai-running.md#continual-learning)).
**Datatype:** Boolean.
Default: `False`.
diff --git a/freqtrade/constants.py b/freqtrade/constants.py
index a724664a4..84c9b5cc9 100644
--- a/freqtrade/constants.py
+++ b/freqtrade/constants.py
@@ -546,7 +546,7 @@ CONF_SCHEMA = {
"enabled": {"type": "boolean", "default": False},
"keras": {"type": "boolean", "default": False},
"write_metrics_to_disk": {"type": "boolean", "default": False},
- "purge_old_models": {"type": "boolean", "default": True},
+ "purge_old_models": {"type": ["boolean", "number"], "default": 2},
"conv_width": {"type": "integer", "default": 1},
"train_period_days": {"type": "integer", "default": 0},
"backtest_period_days": {"type": "number", "default": 7},
diff --git a/freqtrade/freqai/data_drawer.py b/freqtrade/freqai/data_drawer.py
index fc4c9f7b6..c90bb23fc 100644
--- a/freqtrade/freqai/data_drawer.py
+++ b/freqtrade/freqai/data_drawer.py
@@ -366,6 +366,12 @@ class FreqaiDataDrawer:
def purge_old_models(self) -> None:
+ num_keep = self.freqai_info["purge_old_models"]
+ if not num_keep:
+ return
+ elif type(num_keep) == bool:
+ num_keep = 2
+
model_folders = [x for x in self.full_path.iterdir() if x.is_dir()]
pattern = re.compile(r"sub-train-(\w+)_(\d{10})")
@@ -388,11 +394,11 @@ class FreqaiDataDrawer:
delete_dict[coin]["timestamps"][int(timestamp)] = dir
for coin in delete_dict:
- if delete_dict[coin]["num_folders"] > 2:
+ if delete_dict[coin]["num_folders"] > num_keep:
sorted_dict = collections.OrderedDict(
sorted(delete_dict[coin]["timestamps"].items())
)
- num_delete = len(sorted_dict) - 2
+ num_delete = len(sorted_dict) - num_keep
deleted = 0
for k, v in sorted_dict.items():
if deleted >= num_delete:
diff --git a/freqtrade/freqai/freqai_interface.py b/freqtrade/freqai/freqai_interface.py
index fab5cbff8..0a4648c8a 100644
--- a/freqtrade/freqai/freqai_interface.py
+++ b/freqtrade/freqai/freqai_interface.py
@@ -629,8 +629,7 @@ class IFreqaiModel(ABC):
if self.plot_features:
plot_feature_importance(model, pair, dk, self.plot_features)
- if self.freqai_info.get("purge_old_models", False):
- self.dd.purge_old_models()
+ self.dd.purge_old_models()
def set_initial_historic_predictions(
self, pred_df: DataFrame, dk: FreqaiDataKitchen, pair: str, strat_df: DataFrame
diff --git a/freqtrade/templates/FreqaiExampleHybridStrategy.py b/freqtrade/templates/FreqaiExampleHybridStrategy.py
index 8a99dabc1..0e7113f8c 100644
--- a/freqtrade/templates/FreqaiExampleHybridStrategy.py
+++ b/freqtrade/templates/FreqaiExampleHybridStrategy.py
@@ -27,7 +27,7 @@ class FreqaiExampleHybridStrategy(IStrategy):
"freqai": {
"enabled": true,
- "purge_old_models": true,
+ "purge_old_models": 2,
"train_period_days": 15,
"identifier": "uniqe-id",
"feature_parameters": {
diff --git a/tests/freqai/conftest.py b/tests/freqai/conftest.py
index 5e8945239..97f2c2246 100644
--- a/tests/freqai/conftest.py
+++ b/tests/freqai/conftest.py
@@ -27,7 +27,7 @@ def freqai_conf(default_conf, tmpdir):
"timerange": "20180110-20180115",
"freqai": {
"enabled": True,
- "purge_old_models": True,
+ "purge_old_models": 2,
"train_period_days": 2,
"backtest_period_days": 10,
"live_retrain_hours": 0,