From b21f402e1e869eb837393a70af10db42b9ffbaae Mon Sep 17 00:00:00 2001
From: Luigi Maiorano <luigi.maiorano@qumo.io>
Date: Mon, 1 Dec 2025 17:19:46 +0100
Subject: [PATCH] multi theme handling

---
 Architecture_Overview.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/Architecture_Overview.py b/Architecture_Overview.py
index 9309606..19922bc 100644
--- a/Architecture_Overview.py
+++ b/Architecture_Overview.py
@@ -82,6 +82,7 @@ def _(mo):
     2.  **Process:**
         *   The LLM analyzes each transcript segment-by-segment.
         *   It extracts specific quotes that match a Theme Definition.
+        *   **Multi-Theme Handling:** If a quote applies to multiple themes, it is tagged with *all* relevant themes. In the dataset, this creates multiple entries (one per theme) so the quote informs the synthesis of each relevant topic.
         *   **Granular Sentiment Analysis:** For each quote, the model identifies:
             *   **Subject:** The specific topic/object being discussed (e.g., "Login Flow", "Brand Tone").
             *   **Sentiment:** Positive / Neutral / Negative.