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Oil-Flow-Barrels-Per-Day-Predictor

Runtime error

naughtondale commited on Jun 27, 2023

Commit

8892f9a

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1 Parent(s): 7a147e7

Update app.py

Files changed (1) hide show

app.py CHANGED Viewed

@@ -38,7 +38,7 @@ iface = gr.Interface(
     fn=train_and_predict,
     inputs=[gr.inputs.File(type="bytes"), "number", "number", "number", "number", "number", "number", "number", "number"],
     outputs="text",
-    title="Oil Flow Production & Optimization Predictor App",
     description="""This application is the interface of a machine learning model that allows Oil and Gas executives with no coding knowledge or experience to enter inputs related to oil production and predict the number of barrels that will be produced per day given those inputs. The executive engage in scenario planning to optimize oil flow by tweaking/changing various input values to see what would result in greater oil flow. STEPS: Upload the oil production dataset. Enter the input values (Qwater, Qgas, BHP, WHP, WHT, Tsep, Psep, Choke_in) and then click Submit. The model will initiate and complete its training in the background using the dataset provided and then return the output value (Qoil) to you.
     Input Features:

     fn=train_and_predict,
     inputs=[gr.inputs.File(type="bytes"), "number", "number", "number", "number", "number", "number", "number", "number"],
     outputs="text",
+    title="Oil Flow Production & Optimization Application",
     description="""This application is the interface of a machine learning model that allows Oil and Gas executives with no coding knowledge or experience to enter inputs related to oil production and predict the number of barrels that will be produced per day given those inputs. The executive engage in scenario planning to optimize oil flow by tweaking/changing various input values to see what would result in greater oil flow. STEPS: Upload the oil production dataset. Enter the input values (Qwater, Qgas, BHP, WHP, WHT, Tsep, Psep, Choke_in) and then click Submit. The model will initiate and complete its training in the background using the dataset provided and then return the output value (Qoil) to you.
     Input Features: