add twitter feature

app.py

@@ -36,6 +36,9 @@ def ner(text):
     output = ner_pipeline(text)
     return {"text": text, "entities": output}
 
+def sentiment_ner(text):
+    return(sentiment_analysis(text), ner(text))
+
 def sentiment_df(df):
     text_list = list(df["Text"].astype(str).values)
     result = [sentiment_analysis(text) for text in text_list]
@@ -64,19 +67,29 @@ if __name__ == "__main__":
             )
 
         with gr.Tab("Single Input"):
-            sentiment_demo = gr.Interface(
-                fn=sentiment_analysis,
-                inputs="text",
-                outputs="label"
-                )
-
-            ner_demo = gr.Interface(
-                ner,
-                "text",
-                gr.HighlightedText(),
-                examples=examples,
-                allow_flagging='never'
-                )
+            with gr.Row():
+                with gr.Column():
+                    input_text = gr.TextBox(label="Input Text")
+                    analyze_button = gr.Button(label="Analyze")
+                with gr.Column():
+                    sent_output = gr.TextBox(label="Sentiment Analysis")
+                    ner_output = gr.TextBox(label="Named Entity Recognition")
+
+            analyze_button.click(sentiment_analysis, input_text, [sent_output, ner_output])
+
+            # sentiment_demo = gr.Interface(
+            #     fn=sentiment_analysis,
+            #     inputs="text",
+            #     outputs="label"
+            #     )
+
+            # ner_demo = gr.Interface(
+            #     ner,
+            #     "text",
+            #     gr.HighlightedText(),
+            #     examples=examples,
+            #     allow_flagging='never'
+            #     )
 
             # Parallel(
             #         sentiment_demo, ner_demo,
@@ -84,7 +97,7 @@ if __name__ == "__main__":
             #         examples=examples
             #         )
 
-            gr.InterfaceList([sentiment_demo, ner_demo])
+            # gr.InterfaceList([sentiment_demo, ner_demo])
 
         with gr.Tab("Twitter"):
             with gr.Blocks():
@@ -92,7 +105,7 @@ if __name__ == "__main__":
                     with gr.Column():
                         keyword_textbox = gr.Textbox(lines=1, label="Keyword")
                         max_tweets_component = gr.Number(value=10, label="Total of Tweets to Scrape", precision=0)
-                        button = gr.Button("Submit")
+                        submit_button = gr.Button("Submit")
 
                     plot_component = gr.Plot(label="Pie Chart of Sentiments")
                 dataframe_component = gr.DataFrame(type="pandas",
@@ -100,7 +113,7 @@ if __name__ == "__main__":
                                                 max_rows=(20,'fixed'),
                                                 overflow_row_behaviour='paginate',
                                                 wrap=True)
-                button.click(twitter_analyzer,
+                submit_button.click(twitter_analyzer,
                     inputs=[keyword_textbox, max_tweets_component],
                     outputs=[plot_component, dataframe_component])