Upload app_fixed.py

app_fixed.py

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+
+import gradio as gr
+import os
+from tweet_analyzer import TweetDatasetProcessor
+from dotenv import load_dotenv
+
+load_dotenv()
+
+class TwitterCloneApp:
+    def __init__(self):
+        self.processor = None
+        
+    def process_upload(self, file):
+        """Process uploaded PDF file and analyze personality"""
+        try:
+            self.processor = TweetDatasetProcessor()
+            text = self.processor.extract_text_from_pdf(file.name)
+            df = self.processor.process_pdf_content(text)
+            
+            mentions = df['mentions'].explode().dropna().unique().tolist()
+            hashtags = df['hashtags'].explode().dropna().unique().tolist()
+
+            personality_analysis = self.processor.analyze_personality()
+            
+            return f"Processed {len(df)} tweets\n\nMentions: {mentions}\n\nHashtags: {hashtags}\n\nPersonality Analysis:\n{personality_analysis}"
+        except Exception as e:
+            return f"Error processing file: {str(e)}"
+    
+    def analyze_topics(self, n_topics=5):
+        """Analyze topics in the dataset"""
+        if not self.processor:
+            return "Please upload and analyze a dataset first."
+        
+        # Check if the analyze_topics method exists
+        if hasattr(self.processor, 'analyze_topics'):
+            try:
+                topics = self.processor.analyze_topics(n_topics=n_topics)
+                return f"Identified Topics:\n{topics}"
+            except Exception as e:
+                return f"Error analyzing topics: {str(e)}"
+        else:
+            return "Topic analysis is not available in this version of TweetDatasetProcessor."
+    
+    def generate_tweet(self, context):
+        """Generate a new tweet based on the analyzed personality"""
+        if not self.processor:
+            return "Please upload and analyze a dataset first."
+        
+        try:
+            tweet = self.processor.generate_tweet(context)
+            return tweet
+        except Exception as e:
+            return f"Error generating tweet: {str(e)}"
+    
+    def create_interface(self):
+        """Create the Gradio interface"""
+        with gr.Blocks(title="Twitter Personality Cloner") as interface:
+            gr.Markdown("# Twitter Personality Cloner")
+            gr.Markdown("Upload a PDF file containing tweets to analyze the author's personality and generate new tweets in their style.")
+            
+            with gr.Tab("Analyze Personality"):
+                file_input = gr.File(label="Upload PDF Dataset", file_types=[".pdf"])
+                analyze_button = gr.Button("Analyze Dataset")
+                analysis_output = gr.Textbox(label="Analysis Results", lines=10)
+                
+                analyze_button.click(
+                    fn=self.process_upload,
+                    inputs=file_input,
+                    outputs=analysis_output
+                )
+            
+            with gr.Tab("Analyze Topics"):
+                topic_button = gr.Button("Analyze Topics")
+                topic_output = gr.Textbox(label="Identified Topics")
+                
+                topic_button.click(
+                    fn=self.analyze_topics,
+                    inputs=[],
+                    outputs=topic_output
+                )
+
+            with gr.Tab("Generate Tweets"):
+                context_input = gr.Textbox(label="Context (optional)", placeholder="Enter topic or context for the tweet")
+                generate_button = gr.Button("Generate Tweet")
+                tweet_output = gr.Textbox(label="Generated Tweet")
+                
+                generate_button.click(
+                    fn=self.generate_tweet,
+                    inputs=context_input,
+                    outputs=tweet_output
+                )
+        
+        return interface
+
+def main():
+    app = TwitterCloneApp()
+    interface = app.create_interface()
+    interface.launch(share=True)
+
+if __name__ == "__main__":
+    main()