Update tools/visuals.py

tools/visuals.py

@@ -1,25 +1,132 @@
+import os
+import tempfile
 import pandas as pd
 import plotly.express as px
+from typing import Union, Tuple
 
-def histogram_tool(file_path: str, column: str):
-    df = pd.read_csv(file_path)
-    fig = px.histogram(df, x=column, nbins=30, title=f"Histogram – {column}", template="plotly_dark")
-    return fig
+def _save_fig(fig, prefix: str, output_dir: str) -> str:
+    """
+    Save a Plotly figure as a PNG to a temp file and return its path.
+    """
+    os.makedirs(output_dir, exist_ok=True)
+    tmp = tempfile.NamedTemporaryFile(suffix='.png', prefix=prefix, dir=output_dir, delete=False)
+    path = tmp.name
+    tmp.close()
+    try:
+        fig.write_image(path, scale=2)
+    except Exception as e:
+        raise
+    return path
 
-def scatter_matrix_tool(file_path: str, cols: list[str]):
-    df = pd.read_csv(file_path)
-    fig = px.scatter_matrix(df[cols], title="Scatter‑Matrix", template="plotly_dark")
-    return fig
 
-def corr_heatmap_tool(file_path: str):
-    df = pd.read_csv(file_path).select_dtypes("number")
-    corr = df.corr(numeric_only=True)
+def histogram_tool(
+    file_path: str,
+    column: str,
+    output_dir: str = '/tmp',
+    bins: int = 30
+) -> Union[Tuple[px.Figure, str], str]:
+    """
+    Build a histogram for a numeric column, return a Plotly Figure and PNG path,
+    or an error string starting with '❌'.
+    """
+    # Load data
+    ext = os.path.splitext(file_path)[1].lower()
+    try:
+        df = pd.read_excel(file_path) if ext in ('.xls', '.xlsx') else pd.read_csv(file_path)
+    except Exception as exc:
+        return f"❌ Failed to load file: {exc}"
+
+    # Validate column
+    if column not in df.columns:
+        return f"❌ Column '{column}' not found."
+
+    # Coerce to numeric
+    df[column] = pd.to_numeric(df[column], errors='coerce')
+    series = df[column].dropna()
+    if series.empty:
+        return f"❌ No valid numeric data in '{column}'."
+
+    # Create figure
+    fig = px.histogram(
+        df,
+        x=column,
+        nbins=bins,
+        title=f"Histogram – {column}",
+        template='plotly_dark'
+    )
+    # Save PNG
+    img_path = _save_fig(fig, f"hist_{column}_", output_dir)
+    return fig, img_path
+
+
+def scatter_matrix_tool(
+    file_path: str,
+    cols: list[str],
+    output_dir: str = '/tmp'
+) -> Union[Tuple[px.Figure, str], str]:
+    """
+    Build a scatter-matrix for selected numeric columns, return figure and PNG path,
+    or an error string starting with '❌'.
+    """
+    # Load data
+    ext = os.path.splitext(file_path)[1].lower()
+    try:
+        df = pd.read_excel(file_path) if ext in ('.xls', '.xlsx') else pd.read_csv(file_path)
+    except Exception as exc:
+        return f"❌ Failed to load file: {exc}"
+
+    # Validate columns
+    missing = [c for c in cols if c not in df.columns]
+    if missing:
+        return f"❌ Missing columns: {', '.join(missing)}"
+
+    # Filter numeric
+    df_num = df[cols].apply(pd.to_numeric, errors='coerce').dropna()
+    if df_num.empty:
+        return f"❌ No valid numeric data in selected columns."
+
+    # Create figure
+    fig = px.scatter_matrix(
+        df_num,
+        dimensions=cols,
+        title="Scatter-Matrix",
+        template='plotly_dark'
+    )
+    # Save PNG
+    img_path = _save_fig(fig, "scatter_matrix_", output_dir)
+    return fig, img_path
+
+
+def corr_heatmap_tool(
+    file_path: str,
+    output_dir: str = '/tmp',
+    color_continuous_scale: str = 'RdBu'
+) -> Union[Tuple[px.Figure, str], str]:
+    """
+    Build a correlation heatmap for numeric columns, return figure and PNG path,
+    or an error string starting with '❌'.
+    """
+    # Load data
+    ext = os.path.splitext(file_path)[1].lower()
+    try:
+        df = pd.read_excel(file_path) if ext in ('.xls', '.xlsx') else pd.read_csv(file_path)
+    except Exception as exc:
+        return f"❌ Failed to load file: {exc}"
+
+    # Compute correlation
+    df_num = df.select_dtypes(include='number').apply(pd.to_numeric, errors='coerce')
+    if df_num.empty:
+        return "❌ No numeric columns available for correlation."
+    corr = df_num.corr()
+
+    # Create figure
     fig = px.imshow(
         corr,
-        color_continuous_scale="RdBu",
-        title="Correlation Heat‑map",
-        aspect="auto",
-        labels=dict(color="ρ"),
-        template="plotly_dark",
+        color_continuous_scale=color_continuous_scale,
+        title="Correlation Heatmap",
+        labels=dict(color="Correlation"),
+        template='plotly_dark'
     )
-    return fig
+    # Save PNG
+    img_path = _save_fig(fig, "corr_heatmap_", output_dir)
+    return fig, img_path