Update app.py

app.py

@@ -1,11 +1,13 @@
 import gradio as gr
 import pandas as pd
+import random
+from datetime import datetime, timedelta
 from groq import Groq
 
 # Initialize Groq API
 client = Groq(api_key="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")  # Replace with your Groq API key
 
-# Function to infer resources based on task types
+# Predefined resource inference logic
 def infer_resources(schedule):
     resource_map = {
         "Excavation": {"labor": 10, "equipment": "Excavator", "material": "Soil"},
@@ -27,9 +29,23 @@ def infer_resources(schedule):
 
     return pd.DataFrame(inferred_resources)
 
+# Fill missing columns
+def fill_missing_columns(schedule):
+    # Generate random dates if missing
+    if "start_date" not in schedule.columns:
+        schedule["start_date"] = [
+            (datetime.now() + timedelta(days=random.randint(1, 30))).strftime("%Y-%m-%d")
+            for _ in range(len(schedule))
+        ]
+    if "end_date" not in schedule.columns:
+        schedule["end_date"] = [
+            (datetime.strptime(start, "%Y-%m-%d") + timedelta(days=random.randint(5, 15))).strftime("%Y-%m-%d")
+            for start in schedule["start_date"]
+        ]
+    return schedule
+
 # Mock optimization logic
 def mock_optimize_schedule(schedule_with_resources):
-    # Simulate a simple optimization process
     optimized_schedule = []
     conflicts = []
 
@@ -63,6 +79,13 @@ def optimize_resources(schedule_file):
         # Load schedule file
         schedule = pd.read_csv(schedule_file.name)
 
+        # Ensure the 'task' column exists
+        if "task" not in schedule.columns:
+            raise ValueError("The uploaded schedule must contain a 'task' column.")
+
+        # Fill missing columns
+        schedule = fill_missing_columns(schedule)
+
         # Infer resources
         inferred_resources = infer_resources(schedule)
         schedule_with_resources = pd.concat([schedule, inferred_resources], axis=1)
@@ -84,10 +107,10 @@ interface = gr.Interface(
         gr.Dataframe(label="Optimized Schedule"),  # Tabular output
         gr.Textbox(label="Conflicts")  # Text output for conflict details
     ],
-    title="Intelligent Resource Loading",
-    description="Upload a construction schedule to generate an optimized schedule and resource allocation description. Resources are inferred automatically."
+    title="Dynamic Intelligent Resource Loading",
+    description="Upload a construction schedule with at least a 'task' column. The app will dynamically infer other details and optimize the schedule."
 )
 
 # Launch the app
 if __name__ == "__main__":
-    interface.launch()
+    interface.launch()