Update interface.py

interface.py

@@ -1,25 +1,22 @@
-# interface.py
-# (Gradio UI definition and sample data generator)
-
 import gradio as gr
 import spaces
 import json
+import os
+import pandas as pd
 from datetime import datetime, timedelta
 import numpy as np
 from analyzer import TetherProAnalyzer
 
+
 def create_sample_data():
     """Generate sample conversation data for testing"""
     sample_data = []
     base_date = datetime.now() - timedelta(days=30)
-    
     for i in range(15):
         base_score = 25 + (i * 3.5)
         if i % 5 == 0:
             base_score += 20
-        
         abuse_score = min(95, max(5, base_score + np.random.normal(0, 8)))
-        
         sample_data.append({
             'timestamp': (base_date + timedelta(days=i*2)).isoformat(),
             'abuse_score': round(abuse_score, 1),
@@ -29,32 +26,63 @@ def create_sample_data():
             'emotional_tone': 'menacing_calm' if abuse_score > 70 else 'neutral',
             'risk_level': 'high' if abuse_score > 70 else 'moderate' if abuse_score > 40 else 'low'
         })
-    
     return json.dumps(sample_data, indent=2)
 
+
+def load_messages_from_file(file_obj):
+    """
+    Read uploaded CSV or Excel file and convert to JSON string of message dicts.
+    """
+    ext = os.path.splitext(file_obj.name)[1].lower()
+    try:
+        if ext == '.csv':
+            df = pd.read_csv(file_obj.name)
+        elif ext in ['.xls', '.xlsx']:
+            df = pd.read_excel(file_obj.name)
+        else:
+            return {'error': 'Unsupported file type. Please upload a .csv or .xlsx file.'}
+    except Exception as e:
+        return {'error': f'Failed to read file: {e}'}
+
+    messages_data = df.to_dict(orient='records')
+    return json.dumps(messages_data)
+
+
+def analyze_uploaded_file(file_obj):
+    """
+    Wrapper to load messages from file and analyze via TetherProAnalyzer.
+    """
+    messages_json = load_messages_from_file(file_obj)
+    if isinstance(messages_json, dict):
+        return messages_json
+    return TetherProAnalyzer().analyze_conversation_history(messages_json)
+
+
 def create_tether_pro_interface():
     css = """
     .gradio-container { max-width: 1200px !important; margin: 0 auto !important; }
-    /* …your other CSS… */
     """
     with gr.Blocks(css=css) as demo:
         gr.Markdown("# Tether Pro Conversation Analyzer")
         with gr.Row():
-            input_box = gr.Textbox(label="Paste conversation JSON here", lines=10)
+            file_input = gr.File(
+                label="Upload conversation file (.csv or .xlsx)",
+                file_types=[".csv", ".xlsx"]
+            )
             run_button = gr.Button("Analyze")
         output = gr.JSON(label="Analysis Results")
         run_button.click(
-            fn=TetherProAnalyzer().analyze_conversation_history,
-            inputs=input_box,
+            fn=analyze_uploaded_file,
+            inputs=file_input,
             outputs=output
         )
-        
+
         gr.Markdown("## Sample Data")
         sample_button = gr.Button("Load Sample")
         sample_output = gr.Code(label="Sample JSON")
         sample_button.click(fn=create_sample_data, inputs=None, outputs=sample_output)
-        
+
     return demo
 
-# instantiate but do not launch
+
 demo = create_tether_pro_interface()