This repo contains the code used in the DevNet Expert in-lab documentation search engine. The primary code pieces are taken from the Lucene search example code with a few tweaks for running it out of a Flask service.
Combined the backend, the frontend Java code will scan the index for matching hits.
To build the frontend search code, run the scripts/compile-classes.sh script.
First create a python/search-conf.yaml file. Typically you can just copy the example. You
won't have access to the actual docs, so the docroot doesn't matter.
However, if you're building a custom index, you must adjust the last element in the docroot path as well
as customize the path_token so that they are the same. For example, if you're indexing a directory,
~/src/git/DocTree, make the docroot "https://lds-stg.ccie.cisco.com/static/docs/DocTree" and the
path_token DocTree.
Copy the directory that holds the generated index from the backend to this directory. Best to call the
directory docs-index so no other config change is required.
The frontend runs as a Flask/WSGI service. Create a Python virtual environment, pip install -r requirements,
and then you can run cd python && ./search_web.py and then
connect to https://127.0.0.1:8080. Note: for the search to work, you must first
have the index from the backend repo.