Update app.py

app.py

@@ -6,7 +6,8 @@ from transformers import pipeline
 import PyPDF2
 import gradio as gr
 
-# Initialize required tools
+# Download and initialize required tools
+spacy.cli.download("en_core_web_sm")
 nlp = spacy.load("en_core_web_sm")
 nltk.download('punkt')
 
@@ -14,7 +15,6 @@ nltk.download('punkt')
 device = 0 if torch.cuda.is_available() else -1
 analyzer = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english", device=device)
 
-# Define functions for text analysis
 def spacy_ner_analysis(text):
     doc = nlp(text)
     entities = [(ent.text, ent.label_) for ent in doc.ents]
@@ -45,33 +45,6 @@ def extract_pdf_text(file_path):
             text += page.extract_text()
     return text
 
-def analyze_text(text):
-    try:
-        result = analyzer(text)
-        return result
-    except Exception as e:
-        print(f"Error analyzing text: {str(e)}")
-        return ""
-
-def process_text(text, output_directory, filename_prefix):
-    spacy_entities = spacy_ner_analysis(text)
-    sentences = nltk_extract_sentences(text)
-    quotes = nltk_extract_quotes(text)
-    token_count = count_tokens(text)
-    
-    # Save results to files
-    with open(os.path.join(output_directory, f"{filename_prefix}_spacy_entities.txt"), "w", encoding="utf-8") as file:
-        file.write(str(spacy_entities))
-
-    with open(os.path.join(output_directory, f"{filename_prefix}_sentences.txt"), "w", encoding="utf-8") as file:
-        file.write("\n".join(sentences))
-
-    with open(os.path.join(output_directory, f"{filename_prefix}_quotes.txt"), "w", encoding="utf-8") as file:
-        file.write("\n".join(quotes))
-
-    with open(os.path.join(output_directory, f"{filename_prefix}_token_count.txt"), "w", encoding="utf-8") as file:
-        file.write(str(token_count))
-
 def analyze_and_complete(file_path):
     if file_path.endswith(".pdf"):
         text = extract_pdf_text(file_path)
@@ -81,7 +54,6 @@ def analyze_and_complete(file_path):
     
     output_directory = "/Users/Home/Library/Mobile Documents/com~apple~CloudDocs/osa/سيناريوهات/ليالي ألف ليلة"
     filename_prefix = os.path.splitext(os.path.basename(file_path))[0]
-    process_text(text, output_directory, filename_prefix)
     
     spacy_entities = spacy_ner_analysis(text)
     sentences = nltk_extract_sentences(text)
@@ -100,4 +72,4 @@ interface = gr.Interface(
 )
 
 if __name__ == "__main__":
-    interface.launch(share=True)
+    interface.launch()