Update app.py

app.py

@@ -6,10 +6,10 @@ from sklearn.decomposition import PCA
 import plotly.graph_objects as go
 import re
 
-# مدل زبانی
+# Load model
 model = SentenceTransformer('paraphrase-multilingual-MiniLM-L12-v2')
 
-# داده‌ها
+# Reference philosophical data
 school_data = {
     "Stoicism": [
         "The key to happiness is accepting things we cannot control.",
@@ -43,42 +43,32 @@ school_profiles = {
 psychological_categories = [
     {
         "name": "Moral guilt",
-        "keywords": [
-            "guilt", "remorse", "regret", "پشیمانی", "عذاب وجدان", "ندامت"
-        ],
+        "keywords": ["guilt", "remorse", "regret", "پشیمانی", "عذاب وجدان", "ندامت"],
         "followed": "Helps in personal growth, emotional release, and reconciliation.",
         "ignored": "Can lead to chronic anxiety, regret, or depression."
     },
     {
         "name": "Freedom & Will",
-        "keywords": [
-            "freedom", "free will", "liberty", "independence", "آزادی", "اراده", "خودمختاری"
-        ],
+        "keywords": ["freedom", "free will", "liberty", "independence", "آزادی", "اراده", "خودمختاری"],
         "followed": "Encourages autonomy and a sense of responsibility.",
         "ignored": "May result in feelings of helplessness or existential crisis."
     },
     {
         "name": "Altruism",
-        "keywords": [
-            "altruism", "help", "helping", "helped", "assist", "support", "others",
-            "نوع‌دوستی", "کمک", "یاری", "حمایت"
-        ],
+        "keywords": ["altruism", "help", "helping", "helped", "assist", "support", "others",
+                     "نوع‌دوستی", "کمک", "یاری", "حمایت"],
         "followed": "Improves social bonding and personal satisfaction.",
         "ignored": "May cause loneliness or self-centered thinking."
     },
     {
         "name": "Anxiety & Fear",
-        "keywords": [
-            "anxiety", "fear", "worry", "stress", "ترس", "اضطراب", "استرس", "نگرانی"
-        ],
+        "keywords": ["anxiety", "fear", "worry", "stress", "ترس", "اضطراب", "استرس", "نگرانی"],
         "followed": "Leads to caution and preparedness.",
         "ignored": "Might cause mental blocks, phobia, or stress disorders."
     },
     {
         "name": "Rationality",
-        "keywords": [
-            "reason", "logic", "rational", "عقل", "منطق", "استدلال", "عقلانی"
-        ],
+        "keywords": ["reason", "logic", "rational", "عقل", "منطق", "استدلال", "عقلانی"],
         "followed": "Supports wise decision-making and clarity.",
         "ignored": "Can result in poor judgments and emotional impulses."
     }
@@ -139,70 +129,47 @@ def analyze_text(text):
         return "Please enter a philosophical text.", "", "", "", "", None, ""
 
     user_vec = model.encode([text])[0]
-
-    best_school = None
-    best_score = -1
-    best_match = ""
+    best_school, best_score, best_match = None, -1, ""
 
     for school, quotes in school_data.items():
         for quote in quotes:
             quote_vec = model.encode([quote])[0]
             score = cosine_similarity([user_vec], [quote_vec])[0][0]
             if score > best_score:
-                best_score = score
-                best_school = school
-                best_match = quote
+                best_score, best_school, best_match = score, school, quote
 
     semantic_plot = create_semantic_plot(user_vec, best_school)
     school_profile = school_profiles[best_school]["profile"]
     timeline = school_profiles[best_school]["timeline"]
-
     psych_output = psychological_analysis(text)
 
     return best_school, f"{best_score:.2f}", school_profile, timeline, best_match, semantic_plot, psych_output
 
+def clear_fields():
+    return "", "", "", "", "", None, ""
 
 with gr.Blocks(title="Philosophical Analyzer") as demo:
     gr.Markdown("## 📝 Enter Philosophical Text")
     input_text = gr.Textbox(lines=4, placeholder="Type or paste a philosophical text...")
 
-    submit_btn = gr.Button("Analyze")
+    with gr.Row():
+        submit_btn = gr.Button("Analyze")
+        clear_btn = gr.Button("Clear")
 
     with gr.Row():
         with gr.Column():
-            gr.Markdown("### 🧠 Philosophical School Detected:")
-            school = gr.Textbox()
-
-            gr.Markdown("### 📈 Similarity Score:")
-            score = gr.Textbox()
-
-            gr.Markdown("### 🧬 School Profile:")
-            profile_box = gr.Textbox()
-
-            gr.Markdown("### 🧠 Psychological Profile:")
-            psych_box = gr.Textbox()
-
-            gr.Markdown("### 🕰️ Philosophy Timeline")
-            timeline = gr.Textbox()
-
-            with gr.Accordion("🧾 Most Similar Reference Quote", open=False):
+            school = gr.Textbox(label="Philosophical School Detected")
+            score = gr.Textbox(label="Similarity Score")
+            profile_box = gr.Textbox(label="School Profile")
+            psych_box = gr.Textbox(label="Psychological Profile")
+            timeline = gr.Textbox(label="Philosophy Timeline")
+            with gr.Accordion("Most Similar Reference Quote", open=False):
                 best_quote = gr.Textbox()
-
         with gr.Column():
             conceptual_map = gr.Plot(label="🧭 Conceptual Map")
 
-    submit_btn.click(
-        fn=analyze_text,
-        inputs=input_text,
-        outputs=[
-            school,
-            score,
-            profile_box,
-            timeline,
-            best_quote,
-            conceptual_map,
-            psych_box
-        ]
-    )
+    submit_btn.click(analyze_text, inputs=input_text,
+                     outputs=[school, score, profile_box, timeline, best_quote, conceptual_map, psych_box])
+    clear_btn.click(clear_fields, outputs=[school, score, profile_box, timeline, best_quote, conceptual_map, psych_box])
 
 demo.launch()