fix(app): resolve ImportError by using LLMService class directly

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 from pathlib import Path
 from pipeline.process import process_texts
 from pipeline.visualize import generate_visualizations, generate_word_count_chart
-from pipeline.llm_service import get_interpretation
+from pipeline.llm_service import LLMService
 import logging
 import pandas as pd
 from datetime import datetime
@@ -485,7 +485,8 @@ Each segment is represented as a vector of these TF-IDF scores, and the cosine s
                 
                 # Get interpretation from LLM (using OpenRouter API)
                 progress(0.3, desc="Generating scholarly interpretation (this may take 20-40 seconds)...")
-                interpretation = get_interpretation(df_results)
+                llm_service = LLMService()
+                interpretation = llm_service.analyze_similarity(df_results)
                 
                 # Simulate completion steps
                 progress(0.9, desc="Formatting results...")