Update agents/reasoner.py

agents/reasoner.py

@@ -1,14 +1,26 @@
 import matplotlib.pyplot as plt
+import io
+from matplotlib.figure import Figure
 
 # -------------------------------------------------------------
-# SLOTING ANALYSIS
+# UTILITY: Convert Matplotlib Figure → PNG bytes (Gradio compatible)
 # -------------------------------------------------------------
+def fig_to_png_bytes(fig: Figure):
+    """Convert a matplotlib figure to PNG bytes for Gradio Image()."""
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png", dpi=120, bbox_inches="tight")
+    buf.seek(0)
+    return buf.getvalue()
+
 
+# -------------------------------------------------------------
+# SLOTING ANALYSIS
+# -------------------------------------------------------------
 def run_slotting_analysis(message, slotting_df):
     reasoning = []
     reasoning.append("Interpreting slotting optimization request.")
 
-    # Very simple example strategy:
+    # Example strategy:
     strategy = "Move slow movers outward to free prime space"
     reasoning.append(f"Selected strategy: {strategy}")
 
@@ -24,24 +36,25 @@ def run_slotting_analysis(message, slotting_df):
     return explanation, optimized
 
 
+
 # -------------------------------------------------------------
-# PICKING ROUTE OPTIMIZATION (WITH GRAPH OUTPUT)
+# PICKING ROUTE OPTIMIZATION (WITH PNG OUTPUT)
 # -------------------------------------------------------------
-
 def run_picking_optimization(message, picking_df):
     reasoning = []
     reasoning.append("Analyzing picking request…")
 
+    # Convert to integer pairs
     coords = list(zip(
         picking_df["Aisle"].astype(int).tolist(),
         picking_df["Rack"].astype(int).tolist()
     ))
 
-    # --- Nearest neighbour route ---
+    # --- Nearest neighbour route selection ---
     ordered = [coords.pop(0)]
     while coords:
         last = ordered[-1]
-        next_point = min(coords, key=lambda c: abs(c[0]-last[0]) + abs(c[1]-last[1]))
+        next_point = min(coords, key=lambda c: abs(c[0] - last[0]) + abs(c[1] - last[1]))
         ordered.append(next_point)
         coords.remove(next_point)
 
@@ -58,19 +71,22 @@ def run_picking_optimization(message, picking_df):
 
     explanation = " ".join(reasoning)
 
-    # return: explanation, plot, NO slotting table
-    return explanation, fig
+    # Convert FIG → PNG bytes
+    png_bytes = fig_to_png_bytes(fig)
+
+    # return explanation + PNG bytes (NO slotting table)
+    return explanation, png_bytes
+
 
 
 # -------------------------------------------------------------
-# FULL WAREHOUSE REPORT (COMBINED)
+# FULL WAREHOUSE REPORT (WITH GRAPH + TABLE)
 # -------------------------------------------------------------
-
 def run_full_report(message, slotting_df, picking_df):
     reasoning = []
     reasoning.append("Building unified warehouse operations report…")
 
-    # Simple combined logic
+    # Summary counts
     fast = (slotting_df["Velocity"] == "Fast").sum()
     med = (slotting_df["Velocity"] == "Medium").sum()
     slow = (slotting_df["Velocity"] == "Slow").sum()
@@ -84,8 +100,8 @@ def run_full_report(message, slotting_df, picking_df):
 
     explanation = " ".join(reasoning) + "\n" + summary
 
-    # We will include a picking graph in the full report
-    _, fig = run_picking_optimization(message, picking_df)
+    # Include picking graph in the full report
+    _, fig_bytes = run_picking_optimization(message, picking_df)
 
-    # Pass slotting table as part of full report
-    return explanation, fig, slotting_df.copy()
+    # Return: explanation, PNG route graph, AND slotting table
+    return explanation, fig_bytes, slotting_df.copy()