Add spacy

app.py

@@ -1,4 +1,3 @@
-# Sami Alghamdi 21 May 2023
 import pandas as pd
 import spacy
 import gradio as gr
@@ -6,6 +5,10 @@ from nrclex import NRCLex
 from transformers import pipeline
 from rake_nltk import Rake
 import io
+import spacy.cli
+
+# Download the spaCy model
+spacy.cli.download("en_core_web_sm")
 
 # Initialize objects
 emotion_pipeline = pipeline('sentiment-analysis', model='nlptown/bert-base-multilingual-uncased-sentiment')
@@ -19,14 +22,14 @@ def process_csv(file):
     entities = []
     keywords = []
     for _, row in df.iterrows():
-        text = row['Content']  # Replace 'Content' with the correct column name
+        text = row['Content']
         nrc_obj = NRCLex(text)
         emotion_scores = nrc_obj.affect_frequencies
         emotions.append(emotion_scores)
         sentiment = analyze_emotion(text)
         sentiments.append(sentiment)
         entities.append(analyze_entities(text))
-        keywords.append(extract_keywords(text))  # Extract keywords for each text
+        keywords.append(extract_keywords(text))
 
     df['emotions'] = emotions
     df['sentiment'] = sentiments
@@ -47,7 +50,7 @@ def analyze_entities(text):
 
 def extract_keywords(text):
     rake.extract_keywords_from_text(text)
-    return rake.get_ranked_phrases()  # Extract keywords from text
+    return rake.get_ranked_phrases()
 
 iface = gr.Interface(fn=process_csv, inputs=gr.inputs.Textbox(lines=13, label="Paste CSV Here"), outputs="text")
 iface.launch()