Make generation parameters configurable

app.py

@@ -17,26 +17,6 @@ Met een snelheid van 319 Tb/s zouden 57.000 films per seconde kunnen worden gedo
 Voorlopig lijkt de techniek overigens niet meer te zijn dan een experiment, vanwege de hoge kosten die ermee zijn gemoeid. In Nederland zijn providers bezig met het aanleggen van internet met een hoge downloadsnelheid. Deze glasvezelnetwerken bereiken snelheden tot 1 gigabit per seconde.
 """
 
-generator_kwargs_beam = {
-    "max_length": 142,
-    "min_length": 75,
-    "no_repeat_ngram_size": 2,
-    "early_stopping": True,
-    "num_beams": 5,
-    "length_penalty": 1.5,
-    "num_return_sequences": 1,
-}
-
-generator_kwargs_top_k = {
-    "max_length": 142,
-    "min_length": 75,
-    "no_repeat_ngram_size": 2,
-    "do_sample": True,
-    "top_k": 60,
-    "top_p": 0.95,
-    "num_return_sequences": 1,
-}
-
 
 class TextSummarizer:
     def __init__(self):
@@ -103,16 +83,63 @@ def main():
 transformer model. Please refer to the [model page](https://huggingface.co/flax-community/t5-base-dutch-demo) for more information.
 """
     )
-    st.sidebar.title("Mode:")
+    st.sidebar.title("Parameters:")
+
+    min_length = st.sidebar.number_input(
+        "Min length", min_value=10, max_value=150, value=30
+    )
+    max_length = st.sidebar.number_input(
+        "Max length", min_value=50, max_value=250, value=142
+    )
+    no_repeat_ngram_size = st.sidebar.number_input(
+        "No repeat NGram size", min_value=1, max_value=5, value=3
+    )
 
     if sampling_mode := st.sidebar.selectbox(
         "select a Mode", index=0, options=["Beam Search", "Top-k Sampling"]
     ):
         if sampling_mode == "Beam Search":
-            params = generator_kwargs_beam
+            num_beams = st.sidebar.number_input(
+                "Num beams", min_value=1, max_value=10, value=4
+            )
+            length_penalty = st.sidebar.number_input(
+                "Length penalty", min_value=0.0, max_value=5.0, value=1.5, step=0.1
+            )
+            params = {
+                "min_length": min_length,
+                "max_length": max_length,
+                "no_repeat_ngram_size": no_repeat_ngram_size,
+                "num_beams": num_beams,
+                "early_stopping": True,
+                "length_penalty": length_penalty,
+                "num_return_sequences": 1,
+            }
         else:
-            params = generator_kwargs_top_k
-        st.sidebar.json(params)
+            top_k = st.sidebar.number_input(
+                "Top K", min_value=0, max_value=100, value=50
+            )
+            top_p = st.sidebar.number_input(
+                "Top P", min_value=0.0, max_value=1.0, value=0.9, step=0.05
+            )
+            temperature = st.sidebar.number_input(
+                "Temperature", min_value=0.0, max_value=1.0, value=1.0, step=0.05
+            )
+            params = {
+                "min_length": min_length,
+                "max_length": max_length,
+                "no_repeat_ngram_size": no_repeat_ngram_size,
+                "do_sample": True,
+                "top_k": top_k,
+                "top_p": top_p,
+                "temperature": temperature,
+                "num_return_sequences": 1,
+            }
+
+    st.sidebar.markdown(
+        """For an explanation of the parameters, please to the [Huggingface blog post about text generation](https://huggingface.co/blog/how-to-generate)
+        and the [Huggingface text generation interface doc](https://huggingface.co/transformers/main_classes/model.html?highlight=generate#transformers.generation_utils.GenerationMixin.generate).
+        """
+    )
 
     input_text = st.text_area("Enter a Dutch news text", DEFAULT_TEXT, height=500)