test

app.py

@@ -7,10 +7,7 @@ from langdetect import detect
 # Load a summarization model
 summarizer = pipeline("summarization")
 
-# Load a text generation model from Hugging Face
-text_generator = pipeline("text-generation", model="gpt2")
-
-def text_analysis(text):
+def text_analysis_and_summarization(text):
     # Analyze text: word count, character count, language detection, and readability
     words = re.findall(r'\w+', text.lower())
     sentences = re.split(r'[.!?]+', text)
@@ -20,40 +17,24 @@ def text_analysis(text):
     reading_ease = textstat.flesch_reading_ease(text)
     language = detect(text)
 
+    # Summarize text using the transformer model
+    summary = summarizer(text, max_length=130, min_length=30, do_sample=False)[0]['summary_text']
+
     # Format the results
     return {
         "Language": language,
         "Sentences": num_sentences,
         "Words": num_words,
         "Characters": num_chars,
-        "Readability (Flesch Reading Ease)": reading_ease
+        "Readability (Flesch Reading Ease)": reading_ease,
+        "Summary": summary
     }
 
-def text_summarization(text):
-    # Summarize text using the transformer model
-    summary = summarizer(text, max_length=130, min_length=30, do_sample=False)[0]['summary_text']
-    return summary
-
-def generate_text(prompt):
-    # Generate text using the loaded Hugging Face model
-    generated_text = text_generator(prompt, max_length=50, num_return_sequences=1)[0]['generated_text']
-    return generated_text
-
-# Define interfaces for text analysis, text summarization, and text generation
-text_analysis_interface = gr.Interface(fn=text_analysis, 
-                                       inputs=gr.Textbox(lines=4, placeholder="Type something here..."), 
-                                       outputs=gr.JSON(label="Text Analysis"))
-
-text_summarization_interface = gr.Interface(fn=text_summarization, 
-                                            inputs=gr.Textbox(lines=4, placeholder="Type something here..."), 
-                                            outputs="text")
-
-text_generation_interface = gr.Interface(fn=generate_text, 
-                                         inputs=gr.Textbox(lines=4, placeholder="Type a prompt..."), 
-                                         outputs="text")
+# Define an interface for text analysis and summarization
+text_analysis_and_summarization_interface = gr.Interface(fn=text_analysis_and_summarization, 
+                                                        inputs=gr.Textbox(lines=4, placeholder="Type something here..."), 
+                                                        outputs=gr.JSON(label="Text Analysis and Summarization"))
 
-# Launch the interfaces
+# Launch the interface
 if __name__ == "__main__":
-    text_analysis_interface.launch()
-    text_summarization_interface.launch()
-    text_generation_interface.launch()
+    text_analysis_and_summarization_interface.launch()