First commit

app.py

@@ -0,0 +1,149 @@
+from annotated_text import annotated_text
+from bs4 import BeautifulSoup
+from gramformer import Gramformer
+import streamlit as st
+import pandas as pd
+import torch
+import math
+import re
+
+def set_seed(seed):
+    torch.manual_seed(seed)
+    if torch.cuda.is_available():
+        torch.cuda.manual_seed_all(seed)
+set_seed(1212)
+
+class GramformerDemo:
+
+    def __init__(self):
+        st.set_page_config(
+            page_title="Gramformer Demo",
+            initial_sidebar_state="expanded",
+            layout="wide"
+            )
+        self.model_map = {
+            'Corrector': 1,
+            'Detector - coming soon': 2
+            }
+        self.examples = [
+            "what be the reason for everyone leave the comapny",
+            "He are moving here.",
+            "I am doing fine. How is you?",
+            "How is they?",
+            "Matt like fish",
+            "the collection of letters was original used by the ancient Romans",
+            "We enjoys horror movies",
+            "Anna and Mike is going skiing",
+            "I walk to the store and I bought milk",
+            " We all eat the fish and then made dessert",
+            "I will eat fish for dinner and drink milk",
+            ]
+
+    @st.cache(show_spinner=False, suppress_st_warning=True, allow_output_mutation=True)
+    def load_gf(self, model: int):
+        """
+            Load Gramformer model
+        """
+        gf = Gramformer(models=model, use_gpu=False)
+        return gf
+    
+    def show_highlights(self, gf: object, input_text: str, corrected_sentence: str):
+        """
+            To show highlights
+        """
+        try:
+            strikeout = lambda x: '\u0336'.join(x) + '\u0336'
+            highlight_text = gf.highlight(input_text, corrected_sentence)
+            color_map = {'d':'#faa', 'a':'#afa', 'c':'#fea'}
+            tokens = re.split(r'(<[dac]\s.*?<\/[dac]>)', highlight_text)
+            annotations = []
+            for token in tokens:
+                soup = BeautifulSoup(token, 'html.parser')
+                tags = soup.findAll()
+                if tags:
+                    _tag = tags[0].name
+                    _type = tags[0]['type']
+                    _text = tags[0]['edit']
+                    _color = color_map[_tag]
+
+                    if _tag == 'd':
+                        _text = strikeout(tags[0].text)
+
+                    annotations.append((_text, _type, _color))
+                else:
+                    annotations.append(token)
+            args = {
+                'height': 45*(math.ceil(len(highlight_text)/100)),
+                'scrolling': True
+            }
+            annotated_text(*annotations, **args)
+        except Exception as e:
+            st.error('Some error occured!')
+            st.stop()
+    
+    def show_edits(self, gf: object, input_text: str, corrected_sentence: str):
+        """
+            To show edits
+        """
+        try:
+            edits = gf.get_edits(input_text, corrected_sentence)
+            df = pd.DataFrame(edits, columns=['type','original word', 'original start', 'original end', 'correct word', 'correct start', 'correct end'])
+            df = df.set_index('type')
+            st.table(df)
+        except Exception as e:
+            st.error('Some error occured!')
+            st.stop()
+    
+    def main(self):
+        github_repo = 'https://github.com/PrithivirajDamodaran/Gramformer'
+        st.title("Gramformer")
+        st.write(f'GitHub Link - [{github_repo}]({github_repo})')
+        st.markdown('A framework for detecting, highlighting and correcting grammatical errors on natural language text')
+
+        model_type = st.sidebar.selectbox(
+            label='Choose Model',
+            options=list(self.model_map.keys())
+            )
+        if model_type == 'Corrector':
+            max_candidates = st.sidebar.number_input(
+                label='Max candidates',
+                min_value=1,
+                max_value=10,
+                value=1
+                )
+        else:
+            # NOTE: 
+            st.warning('TO BE IMPLEMENTED !!')
+            st.stop()
+
+        with st.spinner('Loading model..'):
+            gf = self.load_gf(self.model_map[model_type])
+    
+        input_text = st.selectbox(
+            label="Choose an example",
+            options=self.examples
+            )
+        input_text = st.text_input(
+            label="Input text",
+            value=input_text
+        )
+
+        if input_text.strip():
+            results = gf.correct(input_text, max_candidates=max_candidates)
+            corrected_sentence, score = results[0]
+            st.markdown(f'#### Output:')
+            st.write('')
+            st.success(corrected_sentence)
+            exp1 = st.beta_expander(label='Show highlights', expanded=True)
+            with exp1:
+                self.show_highlights(gf, input_text, corrected_sentence)
+            exp2 = st.beta_expander(label='Show edits')
+            with exp2:
+                self.show_edits(gf, input_text, corrected_sentence)
+
+        else:
+            st.warning("Please select/enter text to proceed")
+        
+if __name__ == "__main__":
+    obj = GramformerDemo()
+    obj.main()

requirements.txt

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+st-annotated-text
+beautifulsoup4
+git+https://github.com/PrithivirajDamodaran/Gramformer.git