Create app.py

app.py

@@ -0,0 +1,62 @@
+import gradio as gr
+import pandas as pd
+from agents.brain import AutoWarehouseAgent
+
+agent = AutoWarehouseAgent()
+
+
+def df_from_input(df):
+    return pd.DataFrame(df) if df else pd.DataFrame()
+
+
+def run_agent(query, slot_df, pick_df):
+    slotting = df_from_input(slot_df)
+    picking = df_from_input(pick_df)
+
+    return agent.run(query, slotting, picking)
+
+
+def build_ui():
+
+    with gr.Blocks() as demo:
+
+        gr.Markdown(
+            "<h1 style='color:#FF6A00;'>Procelevate Autonomous Warehouse Operator</h1>"
+        )
+
+        query = gr.Textbox(label="Enter your request")
+
+        gr.Markdown("### Slotting Data")
+        slot_df = gr.Dataframe(
+            headers=["SKU", "Velocity", "Frequency"],
+            value=[
+                ["A123", "Fast", 120],
+                ["B555", "Medium", 60],
+                ["C888", "Slow", 8],
+            ],
+        )
+
+        gr.Markdown("### Picking Data")
+        pick_df = gr.Dataframe(
+            headers=["Aisle", "Rack"],
+            value=[[5, 14], [3, 10], [12, 7]],
+        )
+
+        btn = gr.Button("Run Agent", variant="primary")
+
+        out_report = gr.Markdown()
+        out_route = gr.Image()
+        out_heat = gr.Image()
+        out_slot = gr.Dataframe()
+
+        btn.click(
+            run_agent,
+            inputs=[query, slot_df, pick_df],
+            outputs=[out_report, out_route, out_heat, out_slot],
+        )
+
+    return demo
+
+
+demo = build_ui()
+demo.launch()