Improve docs for inference job creation

Author: nginyc

docs/src/user/client-create-inference-job.include.rst

@@ -1,5 +1,6 @@
-To create an model deployment job, you need to submit the app name associated with a *stopped* train job.
-The inference job would be created from the best trials from the train job.
+To create an model serving job, you'll have to wait for your train job to stop. 
+Then, you'll submit the app name associated with the train job (with a status of ``STOPPED``).
+The inference job would be created from the best trials from that train job.
 
 Example:
 

docs/src/user/making-predictions.include.rst

@@ -25,8 +25,9 @@ Example:
 
         .. code-block:: shell
 
+            predictor_host='127.0.0.1:30000'
             body='{"query": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 1, 0, 0, 7, 0, 37, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 27, 84, 11, 0, 0, 0, 0, 0, 0, 119, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 88, 143, 110, 0, 0, 0, 0, 22, 93, 106, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 53, 129, 120, 147, 175, 157, 166, 135, 154, 168, 140, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 11, 137, 130, 128, 160, 176, 159, 167, 178, 149, 151, 144, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 2, 1, 0, 3, 0, 0, 115, 114, 106, 137, 168, 153, 156, 165, 167, 143, 157, 158, 11, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 3, 0, 0, 89, 139, 90, 94, 153, 149, 131, 151, 169, 172, 143, 159, 169, 48, 0], [0, 0, 0, 0, 0, 0, 2, 4, 1, 0, 0, 0, 98, 136, 110, 109, 110, 162, 135, 144, 149, 159, 167, 144, 158, 169, 119, 0], [0, 0, 2, 2, 1, 2, 0, 0, 0, 0, 26, 108, 117, 99, 111, 117, 136, 156, 134, 154, 154, 156, 160, 141, 147, 156, 178, 0], [3, 0, 0, 0, 0, 0, 0, 21, 53, 92, 117, 111, 103, 115, 129, 134, 143, 154, 165, 170, 154, 151, 154, 143, 138, 150, 165, 43], [0, 0, 23, 54, 65, 76, 85, 118, 128, 123, 111, 113, 118, 127, 125, 139, 133, 136, 160, 140, 155, 161, 144, 155, 172, 161, 189, 62], [0, 68, 94, 90, 111, 114, 111, 114, 115, 127, 135, 136, 143, 126, 127, 151, 154, 143, 148, 125, 162, 162, 144, 138, 153, 162, 196, 58], [70, 169, 129, 104, 98, 100, 94, 97, 98, 102, 108, 106, 119, 120, 129, 149, 156, 167, 190, 190, 196, 198, 198, 187, 197, 189, 184, 36], [16, 126, 171, 188, 188, 184, 171, 153, 135, 120, 126, 127, 146, 185, 195, 209, 208, 255, 209, 177, 245, 252, 251, 251, 247, 220, 206, 49], [0, 0, 0, 12, 67, 106, 164, 185, 199, 210, 211, 210, 208, 190, 150, 82, 8, 0, 0, 0, 178, 208, 188, 175, 162, 158, 151, 11], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}'
-            curl -H "Content-Type: application/json" -X POST -d "$body" 127.0.0.1:30000/predict
+            curl -H "Content-Type: application/json" -X POST -d "$body" $predictor_host/predict
 
     Output: