added overall fit

static/instructions.html

@@ -35,6 +35,17 @@
         <li><b>Aligned</b> - The user is very likely to ask this query. </li>
         <li><b>Unclear</b> - It is unclear whether the user will ask this query.</li> </ol>
 </p>
+<p><strong><mark>Overall Fit</mark>:</strong></p>
+<p>Evaluate how well the query aligns with the given filters and persona.
+    Consider all factors, including relevance, clarity, and persona alignment, to give an overall rating.
+<br>Your options are:
+<ol style="padding-left:2rem;">
+    <li><b>Persona-Only Match</b> - The query aligns well with the persona but does not clearly match the filters.</li>
+    <li><b>Filters-Only Match</b> - The query aligns well with the filters but does not clearly match the persona.</li>
+    <li><b>Partial Fit: Incomplete Match</b> - The query aligns with some filters but not all, or it matches the persona but has issues with clarity or alignment.</li>
+    <li><b>Strong Fit</b> - The query is mostly relevant, clear, and well-aligned with the persona and filters.</li>
+<!--    <li><b>Excellent</b> - The query is highly relevant, clear, and perfectly aligned with the persona and filters.</li>-->
+</ol></p>
 <p><strong><mark>Additional Comments (Optional)</mark>:</strong>
     If you have any feedback, remarks, or interesting observations about the data, you can leave them here.
     This is completely optional.

views/questions_screen.py

@@ -166,9 +166,9 @@ def render_query_ratings(
             cols[2] if has_persona_alignment else cols[1],
         )
         overall_rating = render_single_rating(
-            "Overall rating:",
-            [0, 1, 2, 3],
-            lambda x: ["N/A", "Not Clear", "Somewhat Clear", "Very Clear"][x],
+            "Overall Fit:",
+            [0, 1, 2, 3, 4],
+            lambda x: ["N/A", "Persona-Only Match", "Filters-Only Match", "Partial Fit", "Strong Fit"][x],
             f"rating_{model_name}{query_key}_overall_",
             stored_overall_rating,
             cols[3] if has_persona_alignment else cols[2],