Update app.py

app.py

@@ -311,9 +311,9 @@ def inference(input_batch,isurl,use_archive,limit_companies=10):
 title = "ESG API Demo"
 description = """This is a demonstration of the full ESG pipeline backend where given a list of URL (english, news) the news contents are extracted, using extractnet, and fed to three models:
 
+- A custom scheme for company extraction
+- A custom ESG classifier for the ESG labeling of the news
 - An off-the-shelf sentiment classification model (ProsusAI/finbert)
-- A custom NER for the company extraction
-- A custom ESG classifier for the ESG labeling of the news (the extracted text is also lemmatised prior to be fed to this classifier) 
 
 API input parameters:
 - List: list of text. Either list of Url of the news (english) or list of extracted news contents