refactor(ui): enhance Dataframe and Log components in detection model evaluation

app.py

@@ -439,7 +439,10 @@ with gr.Blocks() as detection_model_eval_playground:
             predictions_df = gr.Dataframe(
                 label="Model Predictions",
                 headers=["Arch / Dataset", "By", "AI", "Real", "Label"],
-                datatype=["str", "str", "number", "number", "str"]
+                datatype=["str", "str", "number", "number", "str"],
+                show_label=False,
+                row_count=(8, "dynamic")
+
             )
             gallery = gr.Gallery(label="Post Processed Images", visible=True, columns=[4], rows=[2], container=False, height="auto", object_fit="contain", elem_id="post-gallery")
             raw_json = gr.JSON(label="Raw Model Results", visible=False)
@@ -447,7 +450,7 @@ with gr.Blocks() as detection_model_eval_playground:
     with gr.Accordion("Agent Logs", open=False, elem_id="agent-logs-accordion"):
         with gr.Row():
             with gr.Column():
-                context_intelligence_log = Log(label="Context Log", dark=True, xterm_font_size=12, log_file=AGENT_LOG_FILES["context_intelligence"], container=False, tail=40)
+                context_intelligence_log = Log(label="Context Log", dark=True, xterm_font_size=12, log_file=AGENT_LOG_FILES["context_intelligence"], tail=40)
                 ensemble_monitor_log = Log(label="Ensemble Monitor Log", dark=True, xterm_font_size=12, log_file=AGENT_LOG_FILES["ensemble_monitor"], tail=40)
             with gr.Column():
                 weight_optimization_log = Log(label="Weight Optimization Log", dark=True, xterm_font_size=12, log_file=AGENT_LOG_FILES["weight_optimization"], tail=40)