update to FSRS-5 & support time unit

app.py

@@ -1,17 +1,34 @@
 from typing import List, Tuple
-import gradio as gr
+import gradio as gr  # type: ignore
 import os
 import sys
 
 if os.environ.get("DEV_MODE"):
     # for local development
     sys.path.insert(0, os.path.abspath("../fsrs-optimizer/src/fsrs_optimizer/"))
-from fsrs_optimizer import Optimizer, DEFAULT_WEIGHT, FSRS, lineToTensor
+from fsrs_optimizer import Optimizer, DEFAULT_PARAMETER, FSRS, lineToTensor  # type: ignore
+
+
+def convert_delta_ts(delta_ts: str) -> List[str]:
+    delta_ts_list = delta_ts.replace(" ", "").split(",")
+    converted_delta_ts = []
+    for dt in delta_ts_list:
+        if dt.endswith("d"):
+            converted_delta_ts.append(dt[:-1])
+        elif dt.endswith("m"):
+            value = float(dt[:-1]) * 30
+            converted_delta_ts.append(str(value))
+        elif dt.endswith("y"):
+            value = float(dt[:-1]) * 365
+            converted_delta_ts.append(str(value))
+        else:
+            converted_delta_ts.append(dt)
+    return converted_delta_ts
 
 
 def interface_func(
     weights: str, ratings: str, delta_ts: str, request_retention: float
-) -> str:
+) -> Tuple[str, str, str]:
     weights = weights.replace("[", "").replace("]", "")
     optimizer = Optimizer()
     optimizer.w = list(map(lambda x: float(x.strip()), weights.split(",")))
@@ -20,6 +37,12 @@ def interface_func(
     )
     default_preview = optimizer.preview(request_retention)
     if delta_ts != "":
+        ratings_list = ratings.replace(" ", "").split(",")
+        delta_ts_list = convert_delta_ts(delta_ts)
+        min_len = min(len(ratings_list), len(delta_ts_list))
+        ratings = ",".join(ratings_list[:min_len])
+        delta_ts = ",".join(delta_ts_list[:min_len])
+
         s_history, d_history = memory_state_sequence(ratings, delta_ts, optimizer.w)
         return (
             test_sequence,
@@ -31,13 +54,14 @@ def interface_func(
 
 def memory_state_sequence(
     r_history: str, t_history: str, weights: List[float]
-) -> Tuple[List[float], List[float]]:
+) -> Tuple[List[str], List[str]]:
     fsrs = FSRS(weights)
     line_tensor = lineToTensor(list(zip([t_history], [r_history]))[0]).unsqueeze(1)
     outputs, _ = fsrs(line_tensor)
     stabilities, difficulties = outputs.transpose(0, 1)[0].transpose(0, 1)
-    return map(lambda x: str(round(x, 2)), stabilities.tolist()), map(
-        lambda x: str(round(x, 2)), difficulties.tolist()
+    return (
+        list(map(lambda x: str(round(x, 2)), stabilities.tolist())),
+        list(map(lambda x: str(round(x, 2)), difficulties.tolist())),
     )
 
 
@@ -47,7 +71,7 @@ iface = gr.Interface(
         gr.Textbox(
             label="weights",
             lines=1,
-            value=str(DEFAULT_WEIGHT)[1:-1],
+            value=str(DEFAULT_PARAMETER)[1:-1],
         ),
         gr.Textbox(label="ratings", lines=1, value="3,3,3,3,1,3,3"),
         gr.Textbox(label="delta_ts (requried by state history)", lines=1, value=""),

requirements.txt

@@ -1 +1 @@
-FSRS-Optimizer==4.28.2
+FSRS-Optimizer==5.3.0