Update app.py

app.py

@@ -3,10 +3,8 @@ from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
 import random
 from datetime import datetime
 
-# Initialize sentiment analysis pipeline
+# Initialize models (same as before)
 sentiment_analyzer = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
-
-# Initialize text generation model
 model_name = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name)
@@ -20,129 +18,159 @@ text_generator = pipeline(
     pad_token_id=tokenizer.eos_token_id
 )
 
-class JournalCompanion:
-    def __init__(self):
-        self.entries = []
+# JournalCompanion class remains the same as in previous example
+# ... (insert the entire JournalCompanion class here)
+
+def create_journal_interface():
+    journal = JournalCompanion()
     
-    def generate_prompts(self, sentiment):
-        prompt_template = f"""Generate three reflective journal prompts for someone feeling {sentiment.lower()}. 
-        Make them thoughtful and encouraging. Format them as a bullet point list."""
+    # Custom CSS for better styling
+    custom_css = """
+        /* Global styles */
+        .container {
+            max-width: 1200px;
+            margin: 0 auto;
+            padding: 20px;
+        }
         
-        try:
-            response = text_generator(prompt_template)[0]['generated_text']
-            # Extract the generated prompts after the input prompt
-            prompts = response[len(prompt_template):]
-            return "\n\nReflective Prompts:" + prompts
-        except Exception as e:
-            print("Error generating prompts:", e)
-            return "\n\nReflective Prompts:\n- What thoughts and feelings are you experiencing right now?\n- How has this experience affected you?\n- What would be helpful for you at this moment?"
-
-    def generate_affirmation(self, sentiment):
-        affirmation_template = f"Generate a short, encouraging affirmation for someone feeling {sentiment.lower()}."
+        /* Header styles */
+        .header {
+            text-align: center;
+            margin-bottom: 2rem;
+            background: linear-gradient(135deg, #6B73FF 0%, #000DFF 100%);
+            padding: 2rem;
+            border-radius: 15px;
+            color: white;
+        }
         
-        try:
-            response = text_generator(affirmation_template)[0]['generated_text']
-            # Extract the generated affirmation after the input prompt
-            affirmation = response[len(affirmation_template):].strip()
-            return affirmation
-        except Exception as e:
-            print("Error generating affirmation:", e)
-            return "I acknowledge my feelings and trust in my ability to handle this moment."
-
-    def analyze_entry(self, entry_text):
-        if not entry_text.strip():
-            return ("Please write something in your journal entry.", "", "", "")
-
-        try:
-            # Perform sentiment analysis
-            sentiment_result = sentiment_analyzer(entry_text)[0]
-            sentiment = sentiment_result["label"].upper()
-            sentiment_score = sentiment_result["score"]
-        except Exception as e:
-            print("Error during sentiment analysis:", e)
-            return (
-                "An error occurred during analysis. Please try again.",
-                "Error",
-                "Could not analyze sentiment due to an error.",
-                "Could not generate affirmation due to an error."
-            )
-
-        entry_data = {
-            "text": entry_text,
-            "timestamp": datetime.now().isoformat(),
-            "sentiment": sentiment,
-            "sentiment_score": sentiment_score
+        /* Input area styles */
+        .input-container {
+            background: white;
+            border-radius: 15px;
+            padding: 20px;
+            box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
+            margin-bottom: 20px;
         }
-        self.entries.append(entry_data)
-
-        # Generate responses using TinyLlama
-        prompts = self.generate_prompts(sentiment)
-        affirmation = self.generate_affirmation(sentiment)
-        sentiment_percentage = f"{sentiment_score * 100:.1f}%"
-        message = f"Entry analyzed! Sentiment: {sentiment} ({sentiment_percentage} confidence)"
         
-        return message, sentiment, prompts, affirmation
-
-    def get_monthly_insights(self):
-        if not self.entries:
-            return "No entries yet to analyze."
-            
-        total_entries = len(self.entries)
-        positive_entries = sum(1 for entry in self.entries if entry["sentiment"] == "POSITIVE")
+        /* Output area styles */
+        .output-container {
+            background: #f8f9fa;
+            border-radius: 15px;
+            padding: 20px;
+            margin-top: 20px;
+        }
+        
+        /* Button styles */
+        .custom-button {
+            background: linear-gradient(135deg, #6B73FF 0%, #000DFF 100%);
+            border: none;
+            padding: 10px 20px;
+            border-radius: 8px;
+            color: white;
+            font-weight: bold;
+            cursor: pointer;
+            transition: transform 0.2s;
+        }
         
-        # Generate insights using TinyLlama
-        insight_template = f"""Based on journal entries:
-        Total Entries: {total_entries}
-        Positive Entries: {positive_entries} ({(positive_entries / total_entries * 100):.1f}%)
-        Negative Entries: {total_entries - positive_entries} ({((total_entries - positive_entries) / total_entries * 100):.1f}%)
+        .custom-button:hover {
+            transform: translateY(-2px);
+        }
+        
+        /* Card styles */
+        .card {
+            background: white;
+            border-radius: 10px;
+            padding: 15px;
+            margin: 10px 0;
+            box-shadow: 0 2px 4px rgba(0, 0, 0, 0.05);
+            transition: transform 0.2s;
+        }
+        
+        .card:hover {
+            transform: translateY(-2px);
+        }
+        
+        /* Animation for results */
+        @keyframes fadeIn {
+            from { opacity: 0; transform: translateY(10px); }
+            to { opacity: 1; transform: translateY(0); }
+        }
         
-        Generate a brief insight about this pattern."""
+        .result-animation {
+            animation: fadeIn 0.5s ease-out;
+        }
         
-        try:
-            response = text_generator(insight_template)[0]['generated_text']
-            insights = response[len(insight_template):].strip()
-            return f"""Monthly Insights:
-            {insights}
+        /* Responsive design */
+        @media (max-width: 768px) {
+            .container {
+                padding: 10px;
+            }
             
-            Statistics:
-            Total Entries: {total_entries}
-            Positive Entries: {positive_entries} ({(positive_entries / total_entries * 100):.1f}%)
-            Negative Entries: {total_entries - positive_entries} ({((total_entries - positive_entries) / total_entries * 100):.1f}%)
-            """
-        except Exception as e:
-            print("Error generating insights:", e)
-            return f"""Monthly Insights:
-            Total Entries: {total_entries}
-            Positive Entries: {positive_entries} ({(positive_entries / total_entries * 100):.1f}%)
-            Negative Entries: {total_entries - positive_entries} ({((total_entries - positive_entries) / total_entries * 100):.1f}%)
-            """
-
-def create_journal_interface():
-    journal = JournalCompanion()
+            .header {
+                padding: 1rem;
+            }
+        }
+    """
     
-    with gr.Blocks(title="AI Journal Companion") as interface:
-        gr.Markdown("# 📔 AI Journal Companion")
-        gr.Markdown("Write your thoughts and receive AI-powered insights, prompts, and affirmations.")
-        
-        with gr.Row():
-            with gr.Column():
-                entry_input = gr.Textbox(
-                    label="Journal Entry",
-                    placeholder="Write your journal entry here...",
-                    lines=5
+    with gr.Blocks(css=custom_css, title="AI Journal Companion") as interface:
+        with gr.Column(elem_classes="container"):
+            # Header
+            with gr.Column(elem_classes="header"):
+                gr.Markdown("# 📔 AI Journal Companion")
+                gr.Markdown(
+                    "Transform your thoughts into insights with AI-powered journaling",
+                    elem_classes="subtitle"
                 )
-                submit_btn = gr.Button("Submit Entry", variant="primary")
-
-            with gr.Column():
-                result_message = gr.Markdown(label="Analysis Result")
-                sentiment_output = gr.Textbox(label="Detected Sentiment")
-                prompt_output = gr.Markdown(label="Reflective Prompts")
-                affirmation_output = gr.Textbox(label="Daily Affirmation")
+            
+            # Main content
+            with gr.Row():
+                # Input Column
+                with gr.Column(scale=1, elem_classes="input-container"):
+                    entry_input = gr.Textbox(
+                        label="Write Your Thoughts",
+                        placeholder="Share what's on your mind...",
+                        lines=8,
+                        elem_classes="journal-input"
+                    )
+                    submit_btn = gr.Button(
+                        "✨ Analyze Entry",
+                        variant="primary",
+                        elem_classes="custom-button"
+                    )
                 
-        with gr.Row():
-            insights_btn = gr.Button("Show Monthly Insights")
-            insights_output = gr.Markdown(label="Monthly Insights")
+                # Output Column
+                with gr.Column(scale=1, elem_classes="output-container"):
+                    with gr.Column(elem_classes="card result-animation"):
+                        result_message = gr.Markdown(label="Analysis")
+                        sentiment_output = gr.Textbox(
+                            label="Emotional Tone",
+                            elem_classes="sentiment-output"
+                        )
+                    
+                    with gr.Column(elem_classes="card result-animation"):
+                        prompt_output = gr.Markdown(
+                            label="Reflection Prompts",
+                            elem_classes="prompts-output"
+                        )
+                    
+                    with gr.Column(elem_classes="card result-animation"):
+                        affirmation_output = gr.Textbox(
+                            label="Your Daily Affirmation",
+                            elem_classes="affirmation-output"
+                        )
+            
+            # Insights Section
+            with gr.Row(elem_classes="insights-section"):
+                with gr.Column(scale=1):
+                    insights_btn = gr.Button(
+                        "📊 View Monthly Insights",
+                        elem_classes="custom-button"
+                    )
+                    insights_output = gr.Markdown(
+                        elem_classes="card insights-card"
+                    )
 
+        # Event handlers
         submit_btn.click(
             fn=journal.analyze_entry,
             inputs=[entry_input],