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Update app.py
Browse files
app.py
CHANGED
@@ -11,25 +11,40 @@ class TwitterCloneApp:
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self.processor = None
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def process_upload(self, file):
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"""Process uploaded PDF file and analyze personality"""
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try:
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self.processor = TweetDatasetProcessor()
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text = self.processor.extract_text_from_pdf(file.name)
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df = self.processor.process_pdf_content(text)
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mentions = df['mentions'].explode().dropna().unique().tolist()
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hashtags = df['hashtags'].explode().dropna().unique().tolist()
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personality_analysis = self.processor.analyze_personality()
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except Exception as e:
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return f"Error processing file: {str(e)}"
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def generate_tweet(self, context):
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"""Generate a new tweet based on the analyzed personality"""
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if not self.processor:
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return "Please upload and analyze a dataset first."
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try:
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# Predefined contexts
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@@ -48,18 +63,18 @@ class TwitterCloneApp:
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combined_contexts = additional_contexts + historical_topics
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selected_contexts = random.sample(combined_contexts, min(3, len(combined_contexts)))
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#
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if context:
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selected_contexts.
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# Generate the tweet
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tweet = self.processor.generate_tweet(context=" | ".join(selected_contexts))
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return tweet
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except Exception as e:
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return f"Error generating tweet: {str(e)}"
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def create_interface(self):
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"""Create the Gradio interface"""
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with gr.Blocks(title="Twitter Personality Cloner") as interface:
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gr.Markdown("# Twitter Personality Cloner")
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gr.Markdown("Upload a PDF file containing tweets to analyze the author's personality and generate new tweets in their style.")
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@@ -67,7 +82,7 @@ class TwitterCloneApp:
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with gr.Tab("Analyze Personality"):
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file_input = gr.File(label="Upload PDF Dataset", file_types=[".pdf"])
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analyze_button = gr.Button("Analyze Dataset")
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analysis_output = gr.Textbox(label="Analysis Results", lines=10)
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analyze_button.click(
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fn=self.process_upload,
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@@ -78,7 +93,7 @@ class TwitterCloneApp:
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with gr.Tab("Generate Tweets"):
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context_input = gr.Textbox(label="Context (optional)", placeholder="Enter topic or context for the tweet")
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generate_button = gr.Button("Generate Tweet")
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tweet_output = gr.Textbox(label="Generated Tweet")
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generate_button.click(
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fn=self.generate_tweet,
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@@ -97,3 +112,4 @@ if __name__ == "__main__":
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main()
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self.processor = None
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def process_upload(self, file):
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"""Process uploaded PDF file and analyze personality."""
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if not file:
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return "Error: No file uploaded. Please upload a PDF dataset."
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self.processor = TweetDatasetProcessor()
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text = self.processor.extract_text_from_pdf(file.name)
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df = self.processor.process_pdf_content(text)
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# Extract mentions and hashtags
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mentions = df['mentions'].explode().dropna().unique().tolist()
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hashtags = df['hashtags'].explode().dropna().unique().tolist()
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# Perform personality analysis
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personality_analysis = self.processor.analyze_personality()
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# Format output
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result = f"""
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### Analysis Complete
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- **Processed Tweets**: {len(df)}
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- **Mentions**: {", ".join(mentions) if mentions else "None"}
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- **Hashtags**: {", ".join(hashtags) if hashtags else "None"}
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### Personality Analysis
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{personality_analysis}
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"""
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return result
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except Exception as e:
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return f"Error processing file: {str(e)}"
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def generate_tweet(self, context):
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"""Generate a new tweet based on the analyzed personality."""
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if not self.processor:
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return "Error: Please upload and analyze a dataset first."
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try:
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# Predefined contexts
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combined_contexts = additional_contexts + historical_topics
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selected_contexts = random.sample(combined_contexts, min(3, len(combined_contexts)))
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# Prioritize user context if provided
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if context:
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selected_contexts.insert(0, context)
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# Generate the tweet
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tweet = self.processor.generate_tweet(context=" | ".join(selected_contexts))
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return f"### Generated Tweet\n{tweet}"
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except Exception as e:
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return f"Error generating tweet: {str(e)}"
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def create_interface(self):
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"""Create the Gradio interface."""
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with gr.Blocks(title="Twitter Personality Cloner") as interface:
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gr.Markdown("# Twitter Personality Cloner")
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gr.Markdown("Upload a PDF file containing tweets to analyze the author's personality and generate new tweets in their style.")
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with gr.Tab("Analyze Personality"):
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file_input = gr.File(label="Upload PDF Dataset", file_types=[".pdf"])
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analyze_button = gr.Button("Analyze Dataset")
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analysis_output = gr.Textbox(label="Analysis Results", lines=10, interactive=False)
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analyze_button.click(
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fn=self.process_upload,
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with gr.Tab("Generate Tweets"):
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context_input = gr.Textbox(label="Context (optional)", placeholder="Enter topic or context for the tweet")
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generate_button = gr.Button("Generate Tweet")
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tweet_output = gr.Textbox(label="Generated Tweet", lines=3, interactive=False)
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generate_button.click(
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fn=self.generate_tweet,
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main()
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