done

.gitignore

@@ -159,3 +159,5 @@ cython_debug/
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
 .vercel
+
+cache/

app.py

@@ -0,0 +1,51 @@
+import streamlit as st
+from transformers import MT5ForConditionalGeneration, T5Tokenizer
+import time
+
+@st.cache_resource
+def load_model():
+    model = MT5ForConditionalGeneration.from_pretrained('iliemihai/mt5-base-romanian-diacritics', cache_dir='cache/')
+    return model
+
+@st.cache_resource
+def load_tokenizer():
+    tokenizer = T5Tokenizer.from_pretrained('iliemihai/mt5-base-romanian-diacritics', legacy=False, cache_dir='cache/')
+    return tokenizer
+
+def initialize_app():
+    st.set_page_config(
+        page_title="Dia-critic",
+        page_icon="public/favicon.ico",
+        menu_items={
+            "About": "### Contact\n ✉️[email protected]",
+        },
+    )
+    st.title("🖋️Dia-critic")
+    st.caption("Made with :heart: by NEBO Technologies")
+
+def generate_text(text):
+    model = load_model()
+    tokenizer = load_tokenizer()
+    inputs = tokenizer(text, max_length=256, truncation=True, return_tensors="pt")
+    outputs = model.generate(input_ids=inputs["input_ids"], attention_mask=inputs["attention_mask"])
+    output = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return output
+
+def main():
+    initialize_app()
+
+    input_text = st.text_area("Introduceți textul mai jos")
+    st.write(f'{len(input_text)} caractere.')
+    if st.button("Corectează"):
+        if input_text != "":
+            res = ''
+            with st.spinner('Sarcină în desfășurare...'):
+                # start task
+                res = generate_text(input_text)
+                with st.container(border=True):
+                    st.markdown(res)
+        else:
+            st.warning("Câmpul este gol!")
+
+if __name__ == "__main__":
+    main()

index.py

@@ -1,17 +0,0 @@
-from flask import Flask, request, jsonify
-from transformers import MT5ForConditionalGeneration, T5Tokenizer
-
-app = Flask(__name__)
-
-model = MT5ForConditionalGeneration.from_pretrained('iliemihai/mt5-base-romanian-diacritics', cache_dir='cache/')
-tokenizer = T5Tokenizer.from_pretrained('iliemihai/mt5-base-romanian-diacritics', legacy=False, cache_dir='cache/')
-
-@app.route('/generate', methods=['POST'])
-def generate_text():
-    input_text = request.get_json()['input_text']
-    if input_text is None:
-        return jsonify({'error': 'No input text provided'})
-    inputs = tokenizer(input_text, max_length=256, truncation=True, return_tensors="pt")
-    outputs = model.generate(input_ids=inputs["input_ids"], attention_mask=inputs["attention_mask"])
-    output = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return jsonify({'output': output})

package.json

@@ -1,5 +0,0 @@
-{
-  "engines": {
-    "node": "18.x"
-  }
-}

requirements.txt

@@ -1,4 +1,4 @@
-Flask==3.0.0
-torch
+streamlit
+transformers==4.27.4
 torchvision
-transformers
+sentencepiece

test.http

@@ -1,5 +0,0 @@
-POST http://94.101.98.71:5000/generate
-
-{
-    "input_text": "cat de multe as vrea sa-ti spun tie"
-}