add makespan

app.py

@@ -149,7 +149,7 @@ def solve(file):
             fig.update_yaxes(
                 autorange=True
             )
-        return pretty_output, fig, str(total_time) + " seconds"
+        return current_solution_cost,  str(total_time) + " seconds", pretty_output, fig
 
 ray.init(log_to_driver=False,
         ignore_reinit_error=True,
@@ -160,12 +160,11 @@ description = "A Job-Shop Scheduling Reinforcement Learning based solver, using
               "However, due to resource limitations on the HuggingFace platform (a single vCPU available, no GPU), " \
               "the results you obtain here don't represent the full potential of the approach. <br>" \
               "For large instance, we recommend to run this locally outside the interface as it causes a lot of " \
-              "For large instance, we recommend to run this locally outside the interface as it causes a lot of " \
               "overhead. <br>" \
               "For fast inference, check out the cached examples below."
 
 article = "<p style='text-align: center'>Article Under Review</p>"
 # list all non-hidden files in the 'instances' directory
 examples = ['instances/' + f for f in os.listdir('instances') if not f.startswith('.')]
-iface = gr.Interface(fn=solve, inputs=gr.File(label="Instance File"), outputs=[gr.Text(label="Solution"), gr.Plot(label="Solution's Gantt Chart"), gr.Text(label="Elapsed Time")], title=title, description=description, article=article, examples=examples)
+iface = gr.Interface(fn=solve, inputs=gr.File(label="Instance File"), outputs=[gr.Text(label="Makespan"), gr.Text(label="Elapsed Time"), gr.Text(label="Solution"), gr.Plot(label="Solution's Gantt Chart")], title=title, description=description, article=article, examples=examples)
 iface.launch(enable_queue=True)