Update application

app.py

@@ -5,10 +5,6 @@ import requests
 from mtranslate import translate
 import streamlit as st
 
-from prompts import PROMPT_LIST
-
-
-headers = {}
 
 LOGO = "https://raw.githubusercontent.com/nlp-en-es/assets/main/logo.png"
 
@@ -21,12 +17,18 @@ MODELS = {
     },
 }
 
+PROMPT_LIST = {
+    "Érase una vez...": ["Érase una vez "],
+    "¡Hola!": ["¡Hola! Me llamo "],
+    "¿Ser o no ser?": ["En mi opinión, 'ser' es "],
+}
+
 
 def query(payload, model_name):
     data = json.dumps(payload)
     print("model url:", MODELS[model_name]["url"])
     response = requests.request(
-        "POST", MODELS[model_name]["url"], headers=headers, data=data
+        "POST", MODELS[model_name]["url"], headers={}, data=data
     )
     return json.loads(response.content.decode("utf-8"))
 
@@ -50,9 +52,11 @@ def process(
     return query(payload, model_name)
 
 
+# Page
 st.set_page_config(page_title="Spanish GPT-2 Demo", page_icon=LOGO)
 st.title("Spanish GPT-2")
 
+
 # Sidebar
 st.sidebar.image(LOGO)
 st.sidebar.subheader("Configurable parameters")
@@ -89,6 +93,8 @@ do_sample = st.sidebar.selectbox(
     help="Whether or not to use sampling; use greedy decoding otherwise.",
 )
 
+
+# Body
 st.markdown(
     """
     Spanish GPT-2 models trained from scratch on two different datasets. One
@@ -104,10 +110,7 @@ st.markdown(
     """
 )
 
-model_name = st.selectbox(
-    "Model",
-    (["Model trained on OSCAR", "Model trained on the Large Spanish Corpus"]),
-)
+model_name = st.selectbox("Model", (list(MODELS.keys())))
 
 ALL_PROMPTS = list(PROMPT_LIST.keys()) + ["Custom"]
 prompt = st.selectbox("Prompt", ALL_PROMPTS, index=len(ALL_PROMPTS) - 1)

prompts.py

@@ -1,5 +0,0 @@
-PROMPT_LIST = {
-    "Érase una vez...": ["Érase una vez "],
-    "¡Hola!": ["¡Hola! Me llamo "],
-    "¿Ser o no ser?": ["En mi opinión, 'ser' es "],
-}