First model version

app.py

@@ -1,9 +1,83 @@
 import gradio as gr
+import pickle
+import os
+import numpy as np
+import pandas as pd
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import confusion_matrix
+import matplotlib.pyplot as plt
+import re
 
 
+def deEmojify(text):
+    regrex_pattern = re.compile(pattern = "["
+        u"\U0001F600-\U0001F64F"  # emoticons
+        u"\U0001F300-\U0001F5FF"  # symbols & pictographs
+        u"\U0001F680-\U0001F6FF"  # transport & map symbols
+        u"\U0001F1E0-\U0001F1FF"  # flags (iOS)
+        u"\U00002500-\U00002BEF"  # chinese char
+        u"\U00002702-\U000027B0"
+        u"\U00002702-\U000027B0"
+        u"\U000024C2-\U0001F251"
+        u"\U0001f926-\U0001f937"
+        u"\U00010000-\U0010ffff"
+        u"\u2640-\u2642"
+        u"\u2600-\u2B55"
+        u"\u200d"
+        u"\u23cf"
+        u"\u23e9"
+        u"\u231a"
+        u"\ufe0f"  # dingbats
+        u"\u3030"
+                           "]+", flags = re.UNICODE)
+    return regrex_pattern.sub(r'',text)
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def clean_me(data):
+  data['clean_text'] = data.str.replace(r'<[^<>]*>', '', regex=True)
+  data['clean2_text']= data['clean_text'].str.strip().str.lower().str.replace('\r+', ' ').str.replace('\n+',' ').str.replace('\t+',' ')
+  data['clean3_text'] = data.apply(lambda row: deEmojify(row['clean2_text']), axis=1)
+  return(data)
+
+def combine(a, b):
+    return a + " " + b
+
+
+def mirror(x):
+    return x
+
+
+with gr.Blocks() as demo:
+
+    txt = gr.Textbox(label="Input", lines=2)
+    txt_2 = gr.Textbox(label="Input 2")
+    txt_3 = gr.Textbox(value="", label="Output")
+    btn = gr.Button(value="Submit")
+    btn.click(combine, inputs=[txt, txt_2], outputs=[txt_3])
+
+    with gr.Row():
+        im = gr.Image()
+        im_2 = gr.Image()
+
+    btn = gr.Button(value="Mirror Image")
+    btn.click(mirror, inputs=[im], outputs=[im_2])
+
+    gr.Markdown("## Text Examples")
+    gr.Examples(
+        [["hi", "Adam"], ["hello", "Eve"]],
+        [txt, txt_2],
+        txt_3,
+        combine,
+        cache_examples=True,
+    )
+    gr.Markdown("## Image Examples")
+    gr.Examples(
+        examples=[os.path.join(os.path.dirname(__file__), "lion.jpg")],
+        inputs=im,
+        outputs=im_2,
+        fn=mirror,
+        cache_examples=True,
+    )
+
+if __name__ == "__main__":
+    demo.launch()