I've been working on a project / playing with IBM Watson to try
and understand a little more about the services on offer with Watson.
I have been utilising the IBM Watson Conversation service and at
times I would like to output as a Watson response a document, or the title of a
document that is within retrieve and rank collections.
Background: A Node JS runtime on IBM Bluemix has a web
front end and application server. We get input from a user which we parse
into the conversation service. The output goes to the backend server where we
do some processing and output the response from the conversation as
"Watson Response".
So what will it do next?
Next: Whilst processing the conversation response, we want to
search a string i.e. "rarCollectionName". When we see that
string in the response we want to begin a process where we invoke the retrieve
and rank service and get records back.
But, this was easier said then done. At first I looked for the
documentation that would provide node JS instructions: https://www.ibm.com/watson/developercloud/retrieve-and-rank/api/v1/?node#
This gave pretty clear instructions on how to implement the node
side of the service:
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However, "Line 3" will cause a failure as the
watson-developer-cloud does not have a retrieve_and_rank service but
instead has a retrieve-and-rank service.
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If we look at the node module documentation here,
we see this:
which means we no longer need to declare "v1" when
creating a new retrieve and rank instance:
What confused me in the instructions was the part where it said
-
// Get a Solr client for indexing and searching documents.
// See https://github.com/watson-developer-cloud/node-sdk/blob/master/services/retrieve_and_rank/v1.js
which implied (to my inexperienced eyes) that we had to install
the solr-client npm and create a solr client in this way. In reality, this
functionality is already in retrieve and rank which comes with the
solr-client npm.
There are two ways to create your Solr Client using the retrieve
and rank service:
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I put all this together and my end result of code was
something like this:
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I haven't posted the full project, but the key differences to
the standard example are:
- Depending on the response from the conversation service,
I populate the solrClient parameters to the different collections I would need
to search i.e. recipes / journals
- I take the first document we get from retrieve and rank
"searchResponse.response.docs[0]" and put it on a variable so I can
replace the conversation tool output with the body of the returned retrieve and
rank result. (Lines 43, 44 and 45)
I
hope this helps. As ever feel free to leave a comment below if this becomes out
of date or you have a question.
