first pipes

app.py

@@ -1,10 +1,32 @@
 import gradio as gr
+from transformers import pipeline
+from pydantic import BaseModel
 
-def greet(name):
-    return "Hello " + name + "!"
+# RU_SUMMARY_MODEL = "IlyaGusev/rubart-large-sum"
+RU_SUMMARY_MODEL = "IlyaGusev/mbart_ru_sum_gazeta"
+# RU_SENTIMENT_MODEL = "IlyaGusev/rubart-large-sentiment"
+RU_SENTIMENT_MODEL = "seara/rubert-tiny2-russian-sentiment"
+EN_SUMMARY_MODEL = "sshleifer/distilbart-cnn-12-6"
+EN_SENTIMENT_MODEL = "ProsusAI/finbert"
 
+class Summarizer(BaseModel):
+    ru_summary_pipe: pipeline
+    ru_sentiment_pipe: pipeline
+    
+    def __init__(self) -> None:
+        self.ru_summary_pipe = pipeline("summarization", model=RU_SUMMARY_MODEL)
+        self.ru_summary_pipe = pipeline("sentiment-analysis", model=RU_SENTIMENT_MODEL)
+        
+    def summarize(self, text: str) -> str:
+        result = {}
+        result["summary"] = self.ru_summary_pipe(text)[0]["label"]
+        result["sentiment"] = self.ru_sentiment_pipe(text)[0]["label"]
+        return f"Summary: {result['summary']}\n Sentiment:{result['sentiment']}"
+
+pipe = Summarizer()
+    
 demo = gr.Interface(
-    fn=greet, 
+    fn=pipe.summarize, 
     inputs=gr.Textbox(lines=5, placeholder="Write your text here..."), 
     outputs=gr.Textbox(lines=5, placeholder="Summary and Sentiment would be here..."), 
 )