refactor: reorganize project structure and enhance model verbosity

interface/dashboard.py

@@ -0,0 +1,76 @@
+import pandas as pd
+import streamlit as st
+
+from core.utils import get_data_file_path
+
+
+def load_dataset(file_path: str) -> pd.DataFrame:
+    try:
+        return pd.read_csv(file_path)
+    except Exception as e:
+        st.error(f"Error loading dataset: {e}")
+        return pd.DataFrame()
+
+
+class Dashboard:
+    def __init__(self, config, experiment_tracker, experiment_runner):
+        self.config = config
+        self.experiment_tracker = experiment_tracker
+        self.experiment_runner = experiment_runner
+
+    def index(self):
+        st.header("Dashboard")
+        col1, col2, col3, col4 = st.columns(4)
+
+        # Load basic statistics
+        try:
+            data_path = get_data_file_path(self.config.data.output_files["featured"], self.config)
+            if data_path.exists():
+                df = load_dataset(str(data_path))
+
+                with col1:
+                    st.metric("Total Names", f"{len(df):,}")
+
+                with col2:
+                    annotated = (df.get("annotated", 0) == 1).sum()
+                    st.metric("Annotated Names", f"{annotated:,}")
+
+                with col3:
+                    provinces = df["province"].nunique() if "province" in df.columns else 0
+                    st.metric("Provinces", provinces)
+
+                with col4:
+                    if "sex" in df.columns:
+                        gender_dist = df["sex"].value_counts()
+                        ratio = gender_dist.get("f", 0) / max(gender_dist.get("m", 1), 1)
+                        st.metric("F/M Ratio", f"{ratio:.2f}")
+            else:
+                st.warning("No processed data found. Please run data processing first.")
+
+        except Exception as e:
+            st.error(f"Error loading dashboard data: {e}")
+
+        # Recent experiments
+        st.subheader("Recent Experiments")
+        experiments = self.experiment_tracker.list_experiments()[:5]
+
+        if experiments:
+            exp_data = []
+            for exp in experiments:
+                exp_data.append(
+                    {
+                        "Name": exp.config.name,
+                        "Model": exp.config.model_type,
+                        "Status": exp.status.value,
+                        "Accuracy": (
+                            f"{exp.test_metrics.get('accuracy', 0):.3f}"
+                            if exp.test_metrics
+                            else "N/A"
+                        ),
+                        "Date": exp.start_time.strftime("%Y-%m-%d %H:%M"),
+                    }
+                )
+
+            st.dataframe(pd.DataFrame(exp_data), use_container_width=True)
+        else:
+            st.info("No experiments found. Create your first experiment in the Experiments tab!")