added more explanation for multi-assignment design
@@ -82,7 +82,8 @@ ParlAI provides a generic MTurk dialog interface that one can use to implement a
A few things to keep in mind:
1. To end a conversation, you should send a message with ``episode_done = True`` from the first non-MTurk agent, and the conversation is ended after all MTurk agents respond.
-2. Make sure to test your dialog task using MTurk's sandbox mode before pushing it live, by using the ``--sandbox`` flag (enabled by default) when running ``run.py``.
+2. In ``run.py``, You can use ``hit_index`` and ``assignment_index`` to differentiate between different HITs and assignments, and change the content of the task accordingly.
+3. Make sure to test your dialog task using MTurk's sandbox mode before pushing it live, by using the ``--sandbox`` flag (enabled by default) when running ``run.py``.
Running a Task
