diff --git a/.gitignore b/.gitignore
index abc74c8..e589600 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,6 @@
+housekeeping/create_dataset/*.json
+tmdb_solr*.json
+solr_home/tmdb/conf/*
 venv
 *.pyc
 tmdb.json
@@ -7,3 +10,4 @@ bin/
 .idea/
 *.cfg
 .DS*
+__pycache__
diff --git a/.testing/README.md b/.testing/README.md
deleted file mode 100644
index 797e46a..0000000
--- a/.testing/README.md
+++ /dev/null
@@ -1,28 +0,0 @@
-## Testing TLRE examples
-
-TLRE examples are vunerable to changes in external tooling (Splainer) and Solr  itself. So to ensure things are ready to go for training we've scripted these "tests" to check all of the examples.
-
-#### Splainer
-
-These tests check that changes to Splainer don't damage TLRE examples.
-
-Splainer links from the slides are stored in `splainer_links_solr.csv`. The script `splainer_puppet_es.py` will visit each one of the links and report the HTTP status code back.
-
-```
-# pip install -r requirments.txt
-
-python splainer_puppet_solr.py
-```
-
-This will record the status code in the CSV file and print the number of failed queries to console.
-
-#### Newman
-
-These tests check that version changes in Solr don't damage TLRE examples.
-
-[Newman](https://github.com/postmanlabs/newman) is the command line tool for managing Postman collections. All examples from the class, beyond just the links to Splainer, are included in the collection `../es-postman-collection.json`
-
-```
-newman run --global-var "solr_host=localhost:8983" ../solr_postman_collection.json
-```
-
diff --git a/Pipfile b/Pipfile
deleted file mode 100644
index 5def1ca..0000000
--- a/Pipfile
+++ /dev/null
@@ -1,12 +0,0 @@
-[[source]]
-name = "pypi"
-url = "https://pypi.org/simple"
-verify_ssl = true
-
-[dev-packages]
-
-[packages]
-pysolr = "*"
-
-[requires]
-python_version = "3.6"
diff --git a/README.md b/README.md
index 38ae7c9..ee0cc65 100644
--- a/README.md
+++ b/README.md
@@ -2,25 +2,32 @@ Solr Index for the [The Movie Database](http://themoviedb.com).
 
 This repository is part of the _Think Like a Relevancy Engineer_ training provided by [OpenSource Connections](https://opensourceconnections.com/events/training/).
 
-The code in this repo requires [Python 3](https://www.python.org/downloads/). So if you have both Python 2 and Python 3 installed, you may need to append the version number to your `python` commands or set up an appropriate virtual environment.
+## Steps to get up and running:
+- Download this repo
+- Install the software (using either Docker or installing manually)
+- Index the TMDB movie data
+- Confirm Solr has the data
+- Install Postman (optional)
 
-```
- python3 indexTmdb.py
-```
+# Download this repo
 
-# Clone this repo
+Download the zip from https://github.com/o19s/solr-tmdb/archive/master.zip
+
+or clone it:
 
 ```
 git clone https://github.com/o19s/solr-tmdb.git
 ```
 
-After you clone this repo, change into the newly created directory.
+After you have this repo, change into the newly created directory.
 
-# Run Solr index
+# Install Solr
 
-Two options exist to run Solr.
+Two options exist to run Solr locally, however if neither of them will work for you, we do
+have a public version of this dataset deployed at http://quepid-solr.dev.o19s.com:8985/solr/ that
+you can use during the class as well.
 
-### Docker option (recomended)
+### Docker option (recommended)
 
 If you have [Docker](https://www.docker.com/products/docker-desktop) installed and running.
 
@@ -51,38 +58,25 @@ Regardless of the option you choose, navigate to [http://localhost:8983/solr/](h
 
 # Index TMDB movies
 
-1. Download [tmdb.json](https://o19s-public-datasets.s3.amazonaws.com/tmdb.json)
-
-```
-curl -o tmdb.json https://o19s-public-datasets.s3.amazonaws.com/tmdb.json
-```
-
-2. Install the [pysolr](https://github.com/django-haystack/pysolr) library
-
-Recomended: set up a virtual environment.
+Unzip the `tmdb_solr.json.zip` file first.
 
 ```
-python3 -m venv venv
+unzip tmdb_solr.json.zip
 ```
 
-then
+Then send the unzipped `tmdb_solr.json` into Solr.
 
 ```
-source venv/bin/activate
+./index.sh
 ```
 
-Required: install dependencies
+or
 
 ```
-pip3 install -r requirements.txt
+curl 'http://localhost:8983/solr/tmdb/update?commit=true' --data-binary @tmdb_solr.json -H 'Content-type:application/json'
 ```
 
-
-3. Index movies
-
-```
-python3 indexTmdb.py
-```
+You are indexing a *big 100 mb file*, so this will take up to five minutes!
 
 # Confirm Solr has TMDB movies
 
@@ -90,15 +84,15 @@ Navigate [here](http://localhost:8983/solr/tmdb/select?q=title:lego) and confirm
 
 If you don't see any results, trigger a [manual commit](http://localhost:8983/solr/tmdb/update?commit=true).
 
+
 # Postman
 
-[Postman](https://www.postman.com/) is an API development tool, that helps build, run and manage API requests. The examples from the TLRE slides exist here too as a Postman Collection (`solr-TLRE-postman_collection.json`). We like using Postman becasue it makes tinkering with query parameters nicer and we think it is a useful way to follow along as you learn about tuning search relevance.
+[Postman](https://www.postman.com/) is an API development tool, that helps build, run and manage API requests. The examples from the TLRE slides exist here too as a Postman Collection (`solr-postman_collection.json`). We like using Postman because it makes tinkering with query parameters nicer and we think it is a useful way to follow along as you learn about tuning search relevance.
 
 If you want to use Postman during the TLRE class:
 
 1. Download [Postman](https://www.postman.com/downloads/) for your OS
-2. Open Postman and Import (top-menu >> File) `solr-TLRE-postman_collection.json`
-3. Define a global variable (grey eye icon in the upper-right) `solr-host` to point to your running Elasticsearch instance (default is `localhost:8983`)
+2. Open Postman and Import (top-menu >> File) `solr-postman-collection.json`
+3. Define a global variable (grey eye icon in the upper-right) `solr_host` to point to your running Solr instance (default is `localhost:8983`)
 4. Tinker with the base URL, Params or JSON Body (optional)
 5. Press 'Send' (blue rectangle button right of URL bar)
-
diff --git a/cleanMovies.py b/cleanMovies.py
deleted file mode 100644
index 8241f5b..0000000
--- a/cleanMovies.py
+++ /dev/null
@@ -1,8 +0,0 @@
-
-from tmdbMovies import rawTmdbMovies, writeTmdbMovies
-
-def cleanTmdb():
-    # Some movies are innapropriatte for delivering training
-    # So we clean them up
-    moviesJson = rawTmdbMovies()
-
diff --git a/deleteTmdb.py b/deleteTmdb.py
deleted file mode 100644
index 4099d18..0000000
--- a/deleteTmdb.py
+++ /dev/null
@@ -1,6 +0,0 @@
-
-
-if __name__ == "__main__":
-    import pysolr
-    solr = pysolr.Solr('http://localhost:8983/solr/tmdb', timeout=100)
-    solr.delete(q='*:*', commit=True)
\ No newline at end of file
diff --git a/editMovies.py b/editMovies.py
deleted file mode 100644
index 8b13789..0000000
--- a/editMovies.py
+++ /dev/null
@@ -1 +0,0 @@
-
diff --git a/housekeeping/create_dataset/README.md b/housekeeping/create_dataset/README.md
new file mode 100644
index 0000000..4aa73d8
--- /dev/null
+++ b/housekeeping/create_dataset/README.md
@@ -0,0 +1,33 @@
+# Generating the TMDB dataset
+
+Periodically we update the TMDB dataset as new movies come out, or new data sources are added.
+
+1. Get the latest TMDB dump using the https://github.com/o19s/tmdb_dump project.
+
+2. Create the Solr schema formatted JSON file:
+
+Pass in the TMDB extract file and the name of the resulting Solr JSON file.
+
+```
+python3 createSolrTmdbDataset.py tmdb_2020-08-10.json tmdb_solr.json
+```
+
+3. Zip and store the file in the root directory
+
+```
+zip tmdb_solr.json.zip tmdb_solr.json
+cp ../../
+```
+
+
+https://raw.githubusercontent.com/o19s/tmdb_dump/master/tmdb_dataflows.png
+
+# Understanding Data Structure
+
+You can use `jq` to parse the JSON.   Just unzip a chunk and then do:
+
+> cat tmdb_solr_2020-08-11.json | jq .
+
+Or, to look at a specific movie dataset, look it up by id:
+
+> jq '.[] | select(.id=="87381")' tmdb_solr_2020-08-11.json
diff --git a/indexTmdb.py b/housekeeping/create_dataset/createSolrTmdbDataset.py
similarity index 59%
rename from indexTmdb.py
rename to housekeeping/create_dataset/createSolrTmdbDataset.py
index f1d754d..56f1187 100644
--- a/indexTmdb.py
+++ b/housekeeping/create_dataset/createSolrTmdbDataset.py
@@ -1,25 +1,23 @@
-import pysolr
+from tmdbMovies import tmdbMovies
+from tmdbMovies import writeTmdbMovies
 
-def indexableMovies():
-    """ Generates TMDB movies, similar to how ES Bulk indexing
-        uses a generator to generate bulk index/update actions """
-    from tmdbMovies import tmdbMovies
-    for movieId, tmdbMovie in tmdbMovies():
-        print("Indexing %s" % movieId)
+def indexableMovies(tmdb_source_file):
+    """ Generates TMDB movies in Solr JSON format """
+
+    for movieId, tmdbMovie in tmdbMovies(tmdb_source_file):
+        print("Formatting %s" % movieId)
         try:
-            releaseDate = None
-            if 'release_date' in tmdbMovie and len(tmdbMovie['release_date']) > 0:
-                releaseDate = tmdbMovie['release_date'] + 'T00:00:00Z'
 
             yield {'id': movieId,
                    'title': tmdbMovie['title'],
                    'overview': tmdbMovie['overview'],
                    'tagline': tmdbMovie['tagline'],
+                   'poster_path': 'https://image.tmdb.org/t/p/w185' + tmdbMovie['poster_path'],
                    'cast_nomv': " ".join([castMember['name'] for castMember in tmdbMovie['cast']]),
                    'directors': [director['name'] for director in tmdbMovie['directors']],
                    'cast': [castMember['name'] for castMember in tmdbMovie['cast']],
                    'genres': [genre['name'] for genre in tmdbMovie['genres']],
-                   'release_date': releaseDate,
+                   'release_date': tmdbMovie['release_date'] + 'T00:00:00Z',
                    'vote_average': tmdbMovie['vote_average'] if 'vote_average' in tmdbMovie else None,
                    'vote_count': int(tmdbMovie['vote_count']) if 'vote_count' in tmdbMovie else None,
                    }
@@ -29,5 +27,8 @@ def indexableMovies():
 
 
 if __name__ == "__main__":
-    solr = pysolr.Solr('http://localhost:8983/solr/tmdb', timeout=100)
-    solr.add(list(indexableMovies()), commit=True)
+    from sys import argv
+
+    tmdb_source_file = argv[1]
+    tmdb_solr_file = argv[2]
+    writeTmdbMovies(list(indexableMovies(tmdb_source_file=tmdb_source_file)),tmdb_solr_file)
diff --git a/housekeeping/create_dataset/tmdbMovies.py b/housekeeping/create_dataset/tmdbMovies.py
new file mode 100644
index 0000000..1dc9eb1
--- /dev/null
+++ b/housekeeping/create_dataset/tmdbMovies.py
@@ -0,0 +1,15 @@
+import json
+
+
+def rawTmdbMovies(tmdb_source_file):
+    return json.load(open(tmdb_source_file))
+
+
+def writeTmdbMovies(rawMoviesJson, path):
+    with open(path, 'w') as f:
+        json.dump(rawMoviesJson, f)
+
+def tmdbMovies(tmdb_source_file):
+    tmdbMovies = rawTmdbMovies(tmdb_source_file)
+    for movieId, tmdbMovie in tmdbMovies.items():
+        yield (movieId, tmdbMovie)
diff --git a/housekeeping/testing/README.md b/housekeeping/testing/README.md
new file mode 100644
index 0000000..d3d74f3
--- /dev/null
+++ b/housekeeping/testing/README.md
@@ -0,0 +1,35 @@
+# Testing TLRE examples
+
+TLRE examples are vunerable to changes in external tooling (Splainer, Quepid) and Solr itself. So to ensure things are ready to go for training we've scripted these "tests" to check all of the examples.
+
+## Splainer
+
+These tests check that changes to Splainer don't damage TLRE examples.
+
+Splainer links from the slides are stored in `splainer_links_solr.csv`. The script `splainer_puppet_solr.py` will visit each one of the links and report the HTTP status code back.
+
+These tests assume you are running the local Solr TMDB setup.
+
+Setup your virtual environment:
+```
+python3 -m venv venv
+source venv/bin/activate
+pip install -r requirements.txt
+```
+
+Run regression tests
+```
+python3 splainer_puppet_solr.py
+```
+
+This will record the status code in the CSV file and print the number of failed queries to console.
+
+## Newman
+
+These tests check that version changes in Solr don't damage TLRE examples.
+
+[Newman](https://github.com/postmanlabs/newman) is the command line tool for managing Postman collections. All examples from the class, beyond just the links to Splainer, are included in the collection `../solr-postman-collection.json`
+
+```
+newman run --global-var "solr_host=localhost:8983" ../../solr-postman-collection.json
+```
diff --git a/.testing/requirements.txt b/housekeeping/testing/requirements.txt
similarity index 100%
rename from .testing/requirements.txt
rename to housekeeping/testing/requirements.txt
diff --git a/.testing/splainer_links_solr.csv b/housekeeping/testing/splainer_links_solr.csv
similarity index 100%
rename from .testing/splainer_links_solr.csv
rename to housekeeping/testing/splainer_links_solr.csv
diff --git a/.testing/splainer_puppet_solr.py b/housekeeping/testing/splainer_puppet_solr.py
similarity index 100%
rename from .testing/splainer_puppet_solr.py
rename to housekeeping/testing/splainer_puppet_solr.py
diff --git a/index.sh b/index.sh
new file mode 100755
index 0000000..aebc0f3
--- /dev/null
+++ b/index.sh
@@ -0,0 +1,3 @@
+#!/bin/bash
+
+curl 'http://localhost:8983/solr/tmdb/update?commit=true' --data-binary @tmdb_solr.json -H 'Content-type:application/json'
diff --git a/indexEx1.py b/indexEx1.py
deleted file mode 100644
index 248926c..0000000
--- a/indexEx1.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import pysolr
-
-
-def nameDocs():
-    """ Generates TMDB movies, similar to how ES Bulk indexing
-        uses a generator to generate bulk index/update actions """
-    yield {
-        'id': 1,
-        'text': """What is the land speed of Luke sky walker dined with darth vader.
-                   Darth vader is his father. Darth and Anakin
-                   Skywalker. Luke's mom Padme Amidala was sad she couldn't make it. """
-    }
-
-    yield {
-        'id': 2,
-        'text': """Where is the land speed of  Bob's Big Boy is fantastic! I went there
-                     with my son, Luke. He got a Luke Skywalker action figure! """
-    }
-
-
-
-if __name__ == "__main__":
-    solr = pysolr.Solr('http://localhost:8983/solr/tmdb', timeout=100)
-    solr.delete(q="*:*")
-    solr.add(nameDocs())
diff --git a/ltr/README.md b/ltr/README.md
deleted file mode 100644
index 624cc9a..0000000
--- a/ltr/README.md
+++ /dev/null
@@ -1,51 +0,0 @@
-# Learning to Rank Demo
-
-This demo uses data from [TheMovieDB](http://themoviedb.org) (TMDB) to demonstrate using [Ranklib](https://sourceforge.net/p/lemur/wiki/RankLib/) learning to rank models with Solr.
-
-# Install Dependencies and prep data...
-
-This demo requires
-
-- Python 3+
-- Python `requests` libraries
-
-## Download the TMDB Data & Ranklib Jar
-
-The first time you run this demo, fetch RankyMcRankFace.jar (used to train model) and tmdb.json (the dataset used)
-
-```
-cd train
-python prepare.py
-```
-
-## Start Solr/install plugin
-
-Start a supported version of Solr and follow the [instructions to setup Solr LTR](https://lucene.apache.org/solr/guide/7_4/learning-to-rank.html), or use the config provided in this repo.
-
-## Index to Solr
-
-This script (in the parent directory) will index into the tmdb collection. 
-
-```
-cd ../..
-python indexTmdb.py
-```
-
-# Onto the machine learning...
-
-## TLDR
-
-If you're actually going to build a learning to rank system, read past this section. But to sum up, the full Movie demo can be run by
-
-```
-cd ltr/train/
-python train.py
-```
-
-Then you can search using
-
-```
-python search.py Rambo
-```
-
-and search results can be printed to the console.
diff --git a/ltr/base-search.html b/ltr/base-search.html
deleted file mode 100644
index 18293d9..0000000
--- a/ltr/base-search.html
+++ /dev/null
@@ -1,102 +0,0 @@
-<!doctype html>
-<html lang="en">
-<head>
-    <title>Elasticsearch Learning to Rank Demo</title>
-    <meta charset="utf8"/>
-</head>
-<body>
-<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/handlebars.js/4.0.10/handlebars.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/mustache.js/2.3.0/mustache.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/tether/1.4.0/js/tether.min.js" integrity="sha384-DztdAPBWPRXSA/3eYEEUWrWCy7G5KFbe8fFjk5JAIxUYHKkDx6Qin1DkWx51bBrb" crossorigin="anonymous"></script>
-<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-alpha.6/js/bootstrap.min.js" integrity="sha384-vBWWzlZJ8ea9aCX4pEW3rVHjgjt7zpkNpZk+02D9phzyeVkE+jo0ieGizqPLForn" crossorigin="anonymous"></script>
-
-<!-- Latest compiled and minified CSS -->
-<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-beta.2/css/bootstrap.min.css"
-      integrity="sha384-PsH8R72JQ3SOdhVi3uxftmaW6Vc51MKb0q5P2rRUpPvrszuE4W1povHYgTpBfshb" crossorigin="anonymous">
-<link rel="stylesheet" href="css/flatly.css">
-<a href="https://github.com/o19s/elasticsearch-ltr-demo"><img style="position: absolute; top: 0; right: 0; border: 0;" src="https://camo.githubusercontent.com/38ef81f8aca64bb9a64448d0d70f1308ef5341ab/68747470733a2f2f73332e616d617a6f6e6177732e636f6d2f6769746875622f726962626f6e732f666f726b6d655f72696768745f6461726b626c75655f3132313632312e706e67" alt="Fork me on GitHub" data-canonical-src="https://s3.amazonaws.com/github/ribbons/forkme_right_darkblue_121621.png"></a>
-
-<div class="container">
-  <ul class="nav nav-pills">
-    <li class="nav-item">
-      <a class="nav-link" href="index.html">Welcome!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link active" href="base-search.html">Lonely Search 😕</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="judgment-lists.html">Define Good/Bad Results</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="feature-selection.html">Select Features</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="training-process.html">Train!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="ltr-search.html">Happy LTR Search! 😀</a>
-    </li>
-  </ul>
-  
-	
-  <div class="jumbotron">
-  
-    <h3>😕 This Elasticsearch needs love...</h3>
-
-    <p class="lead">Search for "Star Wars", "Patrick Stewart", "Jabba The Hutt" or "Stuck on Mars"...</p>
-    
- 
-
-    <form onsubmit='resultsForBefore(); return false' class='form-inline' style="padding-bottom: 10px;">
-        <div class="form-row align-items-center">
-
-            <div  class="form-group row">
-                <div class="col-auto">
-                    <input type="search" name="search" class="form-control" style="width: 300px;"  id="inputSearch" value="stuck on mars">
-                </div>
-                <div class="col-auto">
-                  <button type="submit" name="search" class="btn btn-primary">Search</button>
-                </div>
-            </div>
-        </div>
-    </form>
-
-
-    <div class="row" style="border: 1px solid">
-        <div class="col-md-2"></div>
-        <div class="col-md-8">
-            <div id="before"></div>
-        </div>
-        <div class="col-md-2"></div>
-    </div>
-  </div>
-
-<script id="template" type="x-tmpl-mustache">
-    <h4 class="text-right">
-        <span class="badge badge-primary">
-        score {{doc._score}}
-        </span>
-    </h4>
-
-    <div class="row">
-        <div title="{{doc._source.overview}}" class="col-md-9">
-            <h2>{{ doc._source.title }}</h2>
-            <h4>popularity <span class="badge badge-primary">{{doc._source.popularity}}</span></h4>
-            <h4>release date <span class="badge badge-primary">{{doc._source.release_date}}</span></h4>
-            <p>{{doc.highlight.overview}}</p>
-        </div>
-        <div class="col-md-3 text-right">
-            <img src="http://image.tmdb.org/t/p/w130/{{doc._source.poster_path}}" />
-        </div>
-    </div>
-</script>
-<script src="search.js" crossorigin="anonymous"></script>
-<script> resultsForBefore(); </script>
-
-
-</div>
-
-</body>
-
-</html>
diff --git a/ltr/build-a-model.html b/ltr/build-a-model.html
deleted file mode 100644
index 7d57896..0000000
--- a/ltr/build-a-model.html
+++ /dev/null
@@ -1,82 +0,0 @@
-<!doctype html>
-<html lang="en">
-<head>
-    <title>Elasticsearch Learning to Rank Demo</title>
-</head>
-<body>
-<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/handlebars.js/4.0.10/handlebars.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/mustache.js/2.3.0/mustache.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/tether/1.4.0/js/tether.min.js" integrity="sha384-DztdAPBWPRXSA/3eYEEUWrWCy7G5KFbe8fFjk5JAIxUYHKkDx6Qin1DkWx51bBrb" crossorigin="anonymous"></script>
-<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-alpha.6/js/bootstrap.min.js" integrity="sha384-vBWWzlZJ8ea9aCX4pEW3rVHjgjt7zpkNpZk+02D9phzyeVkE+jo0ieGizqPLForn" crossorigin="anonymous"></script>
-
-<!-- Latest compiled and minified CSS -->
-<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-beta.2/css/bootstrap.min.css"
-      integrity="sha384-PsH8R72JQ3SOdhVi3uxftmaW6Vc51MKb0q5P2rRUpPvrszuE4W1povHYgTpBfshb" crossorigin="anonymous">
-<link rel="stylesheet" href="css/flatly.css">
-<a href="https://github.com/o19s/elasticsearch-ltr-demo"><img style="position: absolute; top: 0; right: 0; border: 0;" src="https://camo.githubusercontent.com/38ef81f8aca64bb9a64448d0d70f1308ef5341ab/68747470733a2f2f73332e616d617a6f6e6177732e636f6d2f6769746875622f726962626f6e732f666f726b6d655f72696768745f6461726b626c75655f3132313632312e706e67" alt="Fork me on GitHub" data-canonical-src="https://s3.amazonaws.com/github/ribbons/forkme_right_darkblue_121621.png"></a>
-
-<div class="container">
-
-
-<ul class="nav nav-pills">
-  <li class="nav-item">
-    <a class="nav-link" href="base-search.html">Basic Search</a>
-  </li>
-  <li class="nav-item">
-    <a class="nav-link" href="judgment-lists.html">Defining Good/Bad Results</a>
-  </li>
-  <li class="nav-item">
-    <a class="nav-link" href="feature-selection.html">Feature Selection</a>
-  </li>
-  <li class="nav-item">
-    <a class="nav-link" href="training-process.html">Training Process</a>
-  </li>
-  <li class="nav-item">
-    <a class="nav-link active" href="build-a-model.html">Build a Model</a>
-  </li>
-  <li class="nav-item">
-    <a class="nav-link" href="ltr-search.html">Try LTR!</a>
-  </li>
-</ul>
-
-<div class="row">
-  <div class="col-md-3"></div>
-  <div class="col-md-6">
-
-    <p>With a full training set, we now train a model offline. LTR models try to optimize the ordering of results. This demo uses Ranklib</p>
-
-
-    <p>Below is our judgment list from <a href="judgment-lists.html">earlier</a> annotated with the value of each feature at that document:</p>
-  </div>
-  <div class="col-md-3"></div>
-    
-</div>
-
-<div class="row">
-  <div class="col-md-1"></div>
-  <div class="col-md-10"><iframe style="overflow-x: scroll;" width="100%" src="train/movie_judgments_wfeatures_train.txt"></iframe></div>
-  <div class="col-md-1"></div>
-
-</div>
-
-<div class="row">
-  <div class="col-md-3"></div>
-  <div class="col-md-6">
-    <p>Each feature has a numerical identifier before the colon, followed by the value of that feature. For example, feature 3 is the number of users that rated a movie. You'll note in the first line, 777 people rated this movie.
-    </p>
-  
-  </div>
-  <div class="col-md-3"></div>
-
-</div>
-
-
-
-
-
-</div>
-
-</body>
-
-</html>
diff --git a/ltr/feature-selection.html b/ltr/feature-selection.html
deleted file mode 100644
index 431165c..0000000
--- a/ltr/feature-selection.html
+++ /dev/null
@@ -1,209 +0,0 @@
-<!doctype html>
-<html lang="en">
-<head>
-    <title>Elasticsearch Learning to Rank Demo</title>
-    <meta charset="utf8"/>
-</head>
-<body>
-<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/handlebars.js/4.0.10/handlebars.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/mustache.js/2.3.0/mustache.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/tether/1.4.0/js/tether.min.js" integrity="sha384-DztdAPBWPRXSA/3eYEEUWrWCy7G5KFbe8fFjk5JAIxUYHKkDx6Qin1DkWx51bBrb" crossorigin="anonymous"></script>
-<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-alpha.6/js/bootstrap.min.js" integrity="sha384-vBWWzlZJ8ea9aCX4pEW3rVHjgjt7zpkNpZk+02D9phzyeVkE+jo0ieGizqPLForn" crossorigin="anonymous"></script>
-
-<!-- Latest compiled and minified CSS -->
-<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-beta.2/css/bootstrap.min.css"
-      integrity="sha384-PsH8R72JQ3SOdhVi3uxftmaW6Vc51MKb0q5P2rRUpPvrszuE4W1povHYgTpBfshb" crossorigin="anonymous">
-<link rel="stylesheet" href="css/flatly.css">
-<a href="https://github.com/o19s/elasticsearch-ltr-demo"><img style="position: absolute; top: 0; right: 0; border: 0;" src="https://camo.githubusercontent.com/38ef81f8aca64bb9a64448d0d70f1308ef5341ab/68747470733a2f2f73332e616d617a6f6e6177732e636f6d2f6769746875622f726962626f6e732f666f726b6d655f72696768745f6461726b626c75655f3132313632312e706e67" alt="Fork me on GitHub" data-canonical-src="https://s3.amazonaws.com/github/ribbons/forkme_right_darkblue_121621.png"></a>
-
-<div class="container">
-  <ul class="nav nav-pills">
-    <li class="nav-item">
-      <a class="nav-link" href="index.html">Welcome!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="base-search.html">Lonely Search 😕</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="judgment-lists.html">Define Good/Bad Results</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link active" href="feature-selection.html">Select Features</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="training-process.html">Train!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="ltr-search.html">Happy LTR Search! 😀</a>
-    </li>
-  </ul>
-  
-
-<div class="jumbotron">
-  <div class="row">
-    <div class="col-md-2"></div>
-    <div class="col-md-8"><h3>Speaking the Same Language</h3></div>
-    <div class="col-md-2"></div>
-  </div>
-
-  <div class="row">
-    <div class="col-md-2"></div>
-    <div class="col-md-8">
-
-    <p class="lead">Next we hypothesize which <em>features</em> might predict the grades in the judgment list. Features here means the scores of Elasticsearch queries.</p>
-
-    <p class="lead">Check out a few of the features we'll use below:</p>
-
-
-  </div>
-    <div class="col-md-2"></div>
-
-  </div>
-
-  <div class="row">
-    <div class="col-md-3"></div>
-    <div class="col-md-6">
-      <div id="accordion" role="tablist" aria-multiselectable="true">
-        <div class="card">
-          <div class="card-header" role="tab" id="headingOne">
-            <h5 class="mb-0">
-              <a data-toggle="collapse" data-parent="#accordion" href="#collapseOne" aria-expanded="true" aria-controls="collapseOne">
-                Title Search
-              </a>
-            </h5>
-          </div>
-
-          <div id="collapseOne" class="collapse " role="tabpanel" aria-labelledby="headingOne">
-            <div class="card-block">
-              <iframe width="100%" src="train/10.json"></iframe>
-            </div>
-          </div>
-        </div>
-      </div>
-
-    </div>
-    <div class="col-md-3"></div>
-    
-  <div class="col-md-3"></div>
-    <div class="col-md-6">
-      <div id="accordion" role="tablist" aria-multiselectable="true">
-        <div class="card">
-          <div class="card-header" role="tab" id="headingOne">
-            <h5 class="mb-0">
-              <a data-toggle="collapse" data-parent="#accordion" href="#collapseTwo" aria-expanded="true" aria-controls="collapseTwo">
-                Text Search, English Stemmed
-              </a>
-            </h5>
-          </div>
-
-          <div id="collapseTwo" class="collapse " role="tabpanel" aria-labelledby="headingOne">
-            <div class="card-block">
-              <iframe width="100%" src="train/11.json"></iframe>
-            </div>
-          </div>
-        </div>
-      </div>
-
-    </div>
-    <div class="col-md-3"></div>
-
-
-  <div class="col-md-3"></div>
-    <div class="col-md-6">
-      <div id="accordion" role="tablist" aria-multiselectable="true">
-        <div class="card">
-          <div class="card-header" role="tab" id="headingOne">
-            <h5 class="mb-0">
-              <a data-toggle="collapse" data-parent="#accordion" href="#collapseThree" aria-expanded="true" aria-controls="collapseThree">
-                Number of Users That Rated Movie
-              </a>
-            </h5>
-          </div>
-
-          <div id="collapseThree" class="collapse " role="tabpanel" aria-labelledby="headingOne">
-            <div class="card-block">
-              <iframe width="100%" src="train/3.json"></iframe>
-            </div>
-          </div>
-        </div>
-      </div>
-
-    </div>
-    <div class="col-md-3"></div>
-
-
-    <div class="col-md-3"></div>
-    <div class="col-md-6">
-      <div id="accordion" role="tablist" aria-multiselectable="true">
-        <div class="card">
-          <div class="card-header" role="tab" id="headingOne">
-            <h5 class="mb-0">
-              <a data-toggle="collapse" data-parent="#accordion" href="#collapseFour" aria-expanded="true" aria-controls="collapseFour">
-                Length of Title
-              </a>
-            </h5>
-          </div>
-
-          <div id="collapseFour" class="collapse " role="tabpanel" aria-labelledby="headingOne">
-            <div class="card-block">
-              <iframe width="100%" src="train/4.json"></iframe>
-            </div>
-          </div>
-        </div>
-      </div>
-
-    </div>
-    <div class="col-md-3"></div>
-
-  </div>
-
-  <div class="row">
-    <div class="col-md-2"></div>
-    <div class="col-md-8">
-    
-
-      <p class="lead">We need to score feature values for each judgment. This means we:
-
-        <ol>
-          <li>Store our features in the LTR plugin</li>
-          <li>Ask Elasticsearch to log feature values for each judged document</li>
-          <li>Combine the judgments with features to create a full training set</li>
-        </ol>
-      
-      </p>
-
-      <p class="lead">Below is our full training set: the judgment list annotated with the value of each feature at that document:</p>
-    </div>
-    <div class="col-md-2"></div>
-      
-  </div>
-
-  <div class="row">
-    <div class="col-md-1"></div>
-    <div class="col-md-10"><iframe style="overflow-x: scroll;" width="100%" src="train/movie_judgments_wfeatures_train.txt"></iframe></div>
-    <div class="col-md-1"></div>
-
-  </div>
-
-
-  <div class="row">
-    <div class="col-md-2"></div>
-    <div class="col-md-8">
-
-    <p class="lead">Learn more about working with features <a href="http://elasticsearch-learning-to-rank.readthedocs.io/en/latest/building-features.html">the docs</a></p>
-
-
-</div>
-  <div class="col-md-2"></div>
-
-</div>
-
-</div>
-
-
-</div>
-
-</body>
-
-</html>
diff --git a/ltr/index.html b/ltr/index.html
deleted file mode 100644
index 162cf99..0000000
--- a/ltr/index.html
+++ /dev/null
@@ -1,72 +0,0 @@
-<!doctype html>
-<html lang="en">
-<head>
-    <title>Elasticsearch Learning to Rank Demo</title>
-    <meta charset="utf8"/>
-</head>
-<body>
-<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/handlebars.js/4.0.10/handlebars.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/mustache.js/2.3.0/mustache.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/tether/1.4.0/js/tether.min.js" integrity="sha384-DztdAPBWPRXSA/3eYEEUWrWCy7G5KFbe8fFjk5JAIxUYHKkDx6Qin1DkWx51bBrb" crossorigin="anonymous"></script>
-<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-alpha.6/js/bootstrap.min.js" integrity="sha384-vBWWzlZJ8ea9aCX4pEW3rVHjgjt7zpkNpZk+02D9phzyeVkE+jo0ieGizqPLForn" crossorigin="anonymous"></script>
-
-<!-- Latest compiled and minified CSS -->
-<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-beta.2/css/bootstrap.min.css"
-      integrity="sha384-PsH8R72JQ3SOdhVi3uxftmaW6Vc51MKb0q5P2rRUpPvrszuE4W1povHYgTpBfshb" crossorigin="anonymous">
-<link rel="stylesheet" href="css/flatly.css">
-<a href="https://github.com/o19s/elasticsearch-ltr-demo"><img style="position: absolute; top: 0; right: 0; border: 0;" src="https://camo.githubusercontent.com/38ef81f8aca64bb9a64448d0d70f1308ef5341ab/68747470733a2f2f73332e616d617a6f6e6177732e636f6d2f6769746875622f726962626f6e732f666f726b6d655f72696768745f6461726b626c75655f3132313632312e706e67" alt="Fork me on GitHub" data-canonical-src="https://s3.amazonaws.com/github/ribbons/forkme_right_darkblue_121621.png"></a>
-
-<div class="container">
-  
-  <ul class="nav nav-pills">
-    <li class="nav-item">
-      <a class="nav-link active" href="index.html">Welcome!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="base-search.html">Lonely Search 😕</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="judgment-lists.html">Define Good/Bad Results</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="feature-selection.html">Select Features</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="training-process.html">Train!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="ltr-search.html">Happy LTR Search! 😀</a>
-    </li>
-  </ul>
-
-  <div class="jumbotron">
-
-    <h1>Machine Learning ❤️ &nbsp;Search</h1>
-
-
-    <p class="lead text-muted">All alone, search struggles to address <em>contradictory and nuanced ranking requirements.</em> </p>
-    
-    <p class="lead">Follow along this movie search demo-torial of <a href="http://github.com/o19s/elasticsearch-learning-to-rank">Elasticsearch Learning to Rank Plugin</a> to learn where the magic comes from.</p>
-
-    <ul>
-      <li>Elasticsearch <a href="base-search.html">all alone.</a> Notice the problems!</li>
-      <li><a href="judgment-lists.html">Define good/bad results</a> to train a machine learning model</a></li>
-      <li><a href="">Hypothesize features</a> that can help build a model</li>
-      <li>Learn about <a href="">training a model</a></li>
-      <li>Try the <a href="ltr-search.html">Learning to Rank Search</a>. Let us know what you think!</li>
-
-    </ul>
-
-
-    <a href="/base-search.html" class="btn btn-large">Try the Stock Elasticsearch</button>
-  </div>
-</div>
-
-
-
-</div>
-
-</body>
-
-</html>
diff --git a/ltr/judgment-lists.html b/ltr/judgment-lists.html
deleted file mode 100644
index 193f233..0000000
--- a/ltr/judgment-lists.html
+++ /dev/null
@@ -1,177 +0,0 @@
-<!doctype html>
-<html lang="en">
-<head>
-    <title>Elasticsearch Learning to Rank Demo</title>
-    <meta charset="utf8"/>
-</head>
-<body>
-<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/handlebars.js/4.0.10/handlebars.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/mustache.js/2.3.0/mustache.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/tether/1.4.0/js/tether.min.js" integrity="sha384-DztdAPBWPRXSA/3eYEEUWrWCy7G5KFbe8fFjk5JAIxUYHKkDx6Qin1DkWx51bBrb" crossorigin="anonymous"></script>
-<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-alpha.6/js/bootstrap.min.js" integrity="sha384-vBWWzlZJ8ea9aCX4pEW3rVHjgjt7zpkNpZk+02D9phzyeVkE+jo0ieGizqPLForn" crossorigin="anonymous"></script>
-
-<!-- Latest compiled and minified CSS -->
-<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-beta.2/css/bootstrap.min.css"
-      integrity="sha384-PsH8R72JQ3SOdhVi3uxftmaW6Vc51MKb0q5P2rRUpPvrszuE4W1povHYgTpBfshb" crossorigin="anonymous">
-<link rel="stylesheet" href="css/flatly.css">
-<a href="https://github.com/o19s/elasticsearch-ltr-demo"><img style="position: absolute; top: 0; right: 0; border: 0;" src="https://camo.githubusercontent.com/38ef81f8aca64bb9a64448d0d70f1308ef5341ab/68747470733a2f2f73332e616d617a6f6e6177732e636f6d2f6769746875622f726962626f6e732f666f726b6d655f72696768745f6461726b626c75655f3132313632312e706e67" alt="Fork me on GitHub" data-canonical-src="https://s3.amazonaws.com/github/ribbons/forkme_right_darkblue_121621.png"></a>
-
-<div class="container">
-  <ul class="nav nav-pills">
-    <li class="nav-item">
-      <a class="nav-link" href="index.html">Welcome!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="base-search.html">Lonely Search 😕</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link active" href="judgment-lists.html">Define Good/Bad Results</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="feature-selection.html">Select Features</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="training-process.html">Train!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="ltr-search.html">Happy LTR Search! 😀</a>
-    </li>
-  </ul>
-
-
-<div class="jumbotron">
-
-  <div class="row">
-    <div class="col-md-2"></div>
-    <div class="col-md-8"><h3>Communicating what we need</h3></div>
-    <div class="col-md-2"></div>
-  </div>
-
-
-  <div class="row">
-    <div class="col-md-2"></div>
-    <div class="col-md-8">
-      <p class="lead">Collect good/bad search examples called <em>judgments</em>. These grade which documents are relevant for each query:</p>
-    </div>
-    <div class="col-md-2"></div>
-  </div>
-
-  <div class="row">
-    <div class="col-md-2"></div>
-    <div class="col-md-8" style="height: 20em; overflow-y: scroll; border: 1px solid">
-      <pre>
-
-# Mapping of Queries -> Keywords
-# qid:1: rambo*1
-# qid:2: rocky*1
-# qid:3: second world war*1
-# qid:4: sharon stone sylvester stallone*1
-
-# Grade, query id, # docId
-4	qid:1	 # 7555	rambo
-3	qid:1	 # 1370	rambo
-3	qid:1	 # 1369	rambo
-3	qid:1	 # 13258	rambo
-4	qid:1	 # 1368	rambo
-0	qid:1	 # 319074	rambo
-0	qid:1	 # 10296	rambo
-0	qid:1	 # 35868	rambo
-4	qid:2	 # 1366	rocky
-3	qid:2	 # 1374	rocky
-3	qid:2	 # 1371	rocky
-3	qid:2	 # 1246	rocky
-3	qid:2	 # 1375	rocky
-3	qid:2	 # 1367	rocky
-3	qid:2	 # 60375	rocky
-1	qid:2	 # 110123	rocky
-1	qid:2	 # 36685	rocky
-1	qid:2	 # 17711	rocky
-0	qid:2	 # 2153	rocky
-0	qid:2	 # 339403	rocky
-0	qid:2	 # 21501	rocky
-0	qid:2	 # 81182	rocky
-0	qid:2	 # 62414	rocky
-0	qid:2	 # 21989	rocky
-0	qid:2	 # 11	rocky
-0	qid:2	 # 12180	rocky
-0	qid:2	 # 140607	rocky
-0	qid:2	 # 1893	rocky
-1	qid:3	 # 60976	world war 2
-3	qid:3	 # 75015	world war 2
-3	qid:3	 # 129405	world war 2
-2	qid:3	 # 288109	world war 2
-0	qid:3	 # 38828	world war 2
-4	qid:3	 # 1654	world war 2
-3	qid:3	 # 36571	world war 2
-3	qid:3	 # 36572	world war 2
-3	qid:3	 # 36573	world war 2
-0	qid:3	 # 26652	world war 2
-4	qid:3	 # 1251	world war 2
-3	qid:3	 # 18712	world war 2
-4	qid:3	 # 3683	world war 2
-0	qid:3	 # 211672	world war 2
-0	qid:3	 # 54551	world war 2
-0	qid:3	 # 229407	world war 2
-1	qid:4	 # 23916	sharon stone sylvester stallone
-1	qid:4	 # 81830	sharon stone sylvester stallone
-1	qid:4	 # 38925	sharon stone sylvester stallone
-4	qid:4	 # 2636	sharon stone sylvester stallone
-1	qid:4	 # 1825	sharon stone sylvester stallone
-0	qid:4	 # 19575	sharon stone sylvester stallone
-0	qid:4	 # 10608	sharon stone sylvester stallone
-0	qid:4	 # 10276	sharon stone sylvester stallone
-0	qid:4	 # 26030	sharon stone sylvester stallone
-0	qid:4	 # 26520	sharon stone sylvester stallone
-0	qid:4	 # 44874	sharon stone sylvester stallone
-0	qid:4	 # 15016	sharon stone sylvester stallone
-0	qid:4	 # 15167	sharon stone sylvester stallone
-0	qid:4	 # 77499	sharon stone sylvester stallone
-0	qid:4	 # 34564	sharon stone sylvester stallone
-1	qid:4	 # 45712	sharon stone sylvester stallone
-1	qid:4	 # 31922	sharon stone sylvester stallone
-1	qid:4	 # 32067	sharon stone sylvester stallone
-1	qid:4	 # 31700	sharon stone sylvester stallone
-1	qid:4	 # 61265	sharon stone sylvester stallone
-0	qid:4	 # 18722	sharon stone sylvester stallone
-0	qid:4	 # 1792	sharon stone sylvester stallone
-0	qid:4	 # 18885	sharon stone sylvester stallone
-      </pre>
-    </div>
-    <div class="col-md-2"></div>
-
-  </div>
-
-  <div class="row">
-    <div class="col-md-2"></div>
-    <div class="col-md-8">
-        <p class="lead">Each search is given an id (qid). Then each qid is given a grade for each document, in the form:</p>
-  
-        <pre>(grade 0-4) qid:(qid) # (document identifier)</pre>
-    </div>
-    <div class="col-md-2"></div>
-
-  </div>
-
-  <div class="row">
-    <div class="col-md-2"></div>
-    <div class="col-md-8">
-      <h2>How do you get this data?</h2>
-
-      <p class="lead">You can build judgments from user clicks, purchases, and other events after a search. Domain experts (ie doctors) might manually grade results. Still others crowdsource judgments. You can inspect our full judgment list <a href="https://github.com/o19s/elasticsearch-ltr-demo/blob/master/train/movie_judgments.txt">here.</a></p>
-
-      <p class="lead">Read more in the <a href="">documentation</a> for tips on good judgment lists.</p>
-    </div>
-    <div class="col-md-2"></div>
-  </div>
-
-
-
-</div> <!-- end jumbotron-->
-
-
-</div>
-
-</body>
-
-</html>
diff --git a/ltr/ltr-search.html b/ltr/ltr-search.html
deleted file mode 100644
index 7d709c9..0000000
--- a/ltr/ltr-search.html
+++ /dev/null
@@ -1,115 +0,0 @@
-<!doctype html>
-<html lang="en">
-<head>
-    <title>Elasticsearch Learning to Rank Demo</title>
-    <meta charset="utf8"/>
-</head>
-<body>
-<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/handlebars.js/4.0.10/handlebars.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/mustache.js/2.3.0/mustache.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/tether/1.4.0/js/tether.min.js" integrity="sha384-DztdAPBWPRXSA/3eYEEUWrWCy7G5KFbe8fFjk5JAIxUYHKkDx6Qin1DkWx51bBrb" crossorigin="anonymous"></script>
-<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-alpha.6/js/bootstrap.min.js" integrity="sha384-vBWWzlZJ8ea9aCX4pEW3rVHjgjt7zpkNpZk+02D9phzyeVkE+jo0ieGizqPLForn" crossorigin="anonymous"></script>
-
-<!-- Latest compiled and minified CSS -->
-<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-beta.2/css/bootstrap.min.css"
-      integrity="sha384-PsH8R72JQ3SOdhVi3uxftmaW6Vc51MKb0q5P2rRUpPvrszuE4W1povHYgTpBfshb" crossorigin="anonymous">
-<link rel="stylesheet" href="css/flatly.css">
-<a href="https://github.com/o19s/elasticsearch-ltr-demo"><img style="position: absolute; top: 0; right: 0; border: 0;" src="https://camo.githubusercontent.com/38ef81f8aca64bb9a64448d0d70f1308ef5341ab/68747470733a2f2f73332e616d617a6f6e6177732e636f6d2f6769746875622f726962626f6e732f666f726b6d655f72696768745f6461726b626c75655f3132313632312e706e67" alt="Fork me on GitHub" data-canonical-src="https://s3.amazonaws.com/github/ribbons/forkme_right_darkblue_121621.png"></a>
-
-<div class="container">
-  <ul class="nav nav-pills">
-    <li class="nav-item">
-      <a class="nav-link" href="index.html">Welcome!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="base-search.html">Lonely Search 😕</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="judgment-lists.html">Define Good/Bad Results</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="feature-selection.html">Select Features</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="training-process.html">Train!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link active " href="ltr-search.html">Happy LTR Search! 😀</a>
-    </li>
-  </ul>
-  <div class="jumbotron">
-    <p class="lead text-muted">Using machine learning to optimize search relevance. Built by <a href="http://o19s.com/">OpenSource Connections</a>. </p>
-    <p class="lead">Try searches like 'basketball with cartoon aliens' or 'jabba the hutt'</p>
- 
-
-    <form onsubmit='resultsForAfter(); return false' class='form-inline' style="padding-bottom: 10px;">
-        <div class="form-row align-items-center">
-
-            <div  class="form-group row">
-                <div class="col-auto">
-                    <input type="search" name="search" class="form-control" style="width: 300px;"  id="inputSearch" value="stuck on mars">
-                </div>
-                <div class="col-auto">
-                  <button type="submit" name="search" class="btn btn-primary">Search</button>
-                </div>
-            </div>
-        </div>
-
-  								  <label style="padding-left: 40px;" class="custom-control custom-radio">
-                        <input id="test_9" name="radio" type="radio" class="custom-control-input"
-                               onclick='resultsForAfter(document.getElementById("inputSearch").value);'>
-                        <span class="custom-control-indicator"></span>
-                        <span class="custom-control-description">Optimal Boosts</span>
-                    </label>
-                    <label class="custom-control custom-radio">
-                        <input id="test_6" name="radio" type="radio" class="custom-control-input"
-                               onclick='resultsForAfter(document.getElementById("inputSearch").value);'
-                               checked="true">
-                        <span class="custom-control-indicator"></span>
-                        <span class="custom-control-description">LambdaMART</span>
-                    </label>
-                    <label class="custom-control custom-radio">
-                        <input id="test_8" name="radio" type="radio" class="custom-control-input"
-                               onclick='resultsForAfter(document.getElementById("inputSearch").value);'>
-                        <span class="custom-control-indicator"></span>
-                        <span class="custom-control-description">Random Forests</span>
-                    </label>
-    </form>
-
-
-    <div class="row" style="border: 1px solid">
-        <div class="col-md-2"></div>
-        <div class="col-md-8">
-            <div id="after"></div>
-        </div>
-        <div class="col-md-2"></div>
-    </div>
-  </div>
-    
-
-</div>
-<script id="template" type="x-tmpl-mustache">
-    <h4 class="text-right">
-        <span class="badge badge-primary">
-        score {{doc._score}}
-        </span>
-    </h4>
-
-    <div class="row">
-        <div title="{{doc._source.overview}}" class="col-md-9">
-            <h2>{{ doc._source.title }}</h2>
-            <h4>popularity <span class="badge badge-primary">{{doc._source.popularity}}</span></h4>
-            <h4>release date <span class="badge badge-primary">{{doc._source.release_date}}</span></h4>
-            <p>{{doc.highlight.overview}}</p>
-        </div>
-        <div class="col-md-3 text-right">
-            <img src="http://image.tmdb.org/t/p/w130/{{doc._source.poster_path}}" />
-        </div>
-    </div>
-</script>
-<script src="search.js" crossorigin="anonymous"></script>
-<script> resultsForAfter(); </script>
-</body>
-
-</html>
diff --git a/ltr/search.js b/ltr/search.js
deleted file mode 100644
index c3e3001..0000000
--- a/ltr/search.js
+++ /dev/null
@@ -1,173 +0,0 @@
-  function renderResults(data, search, modelName, beforeOrAfter) {
-    // handle requested data from server
-    var template = document.getElementById('template').innerHTML;
-    Mustache.parse(template);   // optional, speeds up future uses
-    var rendered = ""; //"<h5>" + search + "</h5>";
-    if (beforeOrAfter === 'after') {
-      // rendered += "<h3>Learning to Rank Results <small class='text-muted'></br>" + modelName + " model trained with <a href=\"https://github.com/o19s/elasticsearch-ltr-demo/blob/master/train/movie_judgments.txt#L57\">this training data</a></small></h3>"
-    } else {
-      // rendered += "<h4><small class='text-muted'>Untuned Elasticsearch</small></h4>"
-    }
-    data.hits.hits.forEach(function (document) {
-      rendered = rendered + Mustache.render(template, {doc: document, search: search});
-    });
-    document.getElementById(beforeOrAfter).innerHTML = rendered;
-  };
-
-  //var esUrl = 'http://localhost:9200/tmdb/_search'
-  var esUrl = "http://es-for-ltr.labs.o19s.com:7271/tmdb/_search";
-
-  function getExpansions(search, searchField, expandField, shardSize, minDocCount, onDone) {
-      body = {
-          "size": 0,
-          "query": {
-              "match": {
-              }
-          },
-          "aggs": {
-               "over_top_n" : {
-                  "sampler" : {
-                      "shard_size" : shardSize
-                  },
-                  "aggs": {
-                      "expansions": {
-                          "significant_terms": {
-                              "field": expandField,
-                              "min_doc_count": minDocCount
-                          }
-                      }
-                  }
-               }
-          }
-      }
-      body.query.match[searchField] = search;
-      $.ajax({
-        method: "GET",
-        url: esUrl,
-        crossDomain: true,
-        async: false,
-        data: "source=" + JSON.stringify(body),
-        dataType: 'json',
-        contentType: 'application/json',
-      })
-        .done(function (data) {
-          // for sigTerm in results['aggregations']['over_top_n']['expansions']['buckets']:
-          var rVal = "";
-          data.aggregations.over_top_n.expansions.buckets.forEach(function (sigTerm) {
-
-            var term = sigTerm.key;
-            var weight = sigTerm.score;
-
-            var multiTerm = term.split(/s+/);
-            if (multiTerm.length > 0) {
-              var i = 0;
-              term = "\"";
-              for (i = 0; i < multiTerm.length; i++) {
-                term += multiTerm[i] + " ";
-              }
-              term += "\"";
-            }
-            rVal += " " + term + "^" + weight;
-
-          });
-
-          onDone(rVal);
-        })
-  }
-
-  function resultsForAfter() {
-    var search = document.getElementById("inputSearch").value;
-    getResults(search, 'after');
-  }
-
-  function resultsForBefore() {
-    var search = document.getElementById("inputSearch").value;
-    getResults(search, 'before');
-  }
-
-  function resultsForBoth() {
-    var search = document.getElementById("inputSearch").value;
-    getResults(search, 'after');
-    getResults(search, 'before');
-  }
-
-  function getResults(search, beforeOrAfter) {
-    getExpansions(search, 'text_all', 'text_all.trigramed', 100, 1, (expansionsTextAllTrigrams) => {
-          getExpansions(search, 'text_all', 'genre.name', 100, 1, (expansionsGenre) => {
-
-            var data = {
-              "query": {
-                "multi_match": {
-                  "query": search,
-                  "fields": ["text_all.en"],
-                  "type": "cross_fields"
-                }
-              },
-              "highlight" : {
-                  "fields" : {
-                      "overview.en" : {}
-                  }
-              },
-              "rescore": {
-                "window_size": 500,
-                "query": {
-                  "query_weight": 1.0,
-                  "rescore_query_weight": 100.0,
-                  "rescore_query": {
-                    "sltr": {
-                      "params": {
-                        "keywords": search,
-                        "expansions_text_all_trigrams": expansionsTextAllTrigrams,
-                        "expansions_genre": expansionsGenre,
-                      },
-                      "model": "test_1"
-                    }
-                  }
-                }
-              }
-            };
-            var model = null;
-            if (beforeOrAfter == 'after') {
-              switch (true) {
-                case document.getElementById('test_6').checked:
-                  data.rescore.query.rescore_query.sltr.model = 'test_6';
-                  model = "LambdaMART";
-                  break;
-                case document.getElementById('test_8').checked:
-                  data.rescore.query.rescore_query.sltr.model = 'test_8';
-                  model = "Random Forest";
-                  break;
-                case document.getElementById('test_9').checked:
-                  data.rescore.query.rescore_query.sltr.model = 'test_9';
-                  model = "Linear";
-                  break;
-                default:
-                  delete data.rescore;
-              }
-            } else {
-              delete data.rescore;
-            }
-
-            $.ajax({
-              method: "GET",
-              url: esUrl,
-              crossDomain: true,
-              async: false,
-              data: "source=" + JSON.stringify(data),
-              dataType: 'json',
-              contentType: 'application/json',
-            })
-              .done(function (data) {
-                renderResults(data, search, model, beforeOrAfter);
-              })
-              .fail(function (data) {
-                console.log(data);
-              });
-
-
-          })
-
-    })
-
-  }
-
diff --git a/ltr/train/1.json b/ltr/train/1.json
deleted file mode 100644
index 0c10ac2..0000000
--- a/ltr/train/1.json
+++ /dev/null
@@ -1,7 +0,0 @@
-{
-  "name": "titleSearch",
-  "class": "org.apache.solr.ltr.feature.SolrFeature",
-  "params": {
-    "q": "{!edismax qf='title'}${keywords}"
-  }
-}
\ No newline at end of file
diff --git a/ltr/train/2.json b/ltr/train/2.json
deleted file mode 100644
index 68e6ede..0000000
--- a/ltr/train/2.json
+++ /dev/null
@@ -1,7 +0,0 @@
-{
-  "name": "overviewSearch",
-  "class": "org.apache.solr.ltr.feature.SolrFeature",
-  "params": {
-    "q": "{!edismax qf='overview'}${keywords}"
-  }
-}
\ No newline at end of file
diff --git a/ltr/train/collectFeatures.py b/ltr/train/collectFeatures.py
deleted file mode 100644
index 7aaf520..0000000
--- a/ltr/train/collectFeatures.py
+++ /dev/null
@@ -1,70 +0,0 @@
-import json
-from solr import SolrColl
-import atexit
-from loadFeatures import featureOrdToName
-
-def featureCsvToList(features, ftrMapping):
-
-    ftrNameToOrd = {name: _ord for (_ord, name) in ftrMapping}
-    ftrDict = dict(feature.split("=") for feature in features.split(","))
-
-    rVal = [0.0] * len(ftrMapping)
-
-    for ftrName, value in ftrDict.items():
-        _ord = ftrNameToOrd[ftrName]
-        rVal[_ord - 1] = value
-
-    return rVal
-
-
-def logFeatures(solrColl, judgmentsByQid):
-    idx = 0
-
-    ftrMapping = featureOrdToName()
-
-    featuresPerDoc = {}
-
-    for qid, judgments in judgmentsByQid.items():
-        keywords = judgments[0].keywords
-        docIds = [judgment.docId for judgment in judgments]
-        idsQuery = 'id:(' + ' '.join(docIds) + ')'
-
-        resp = solrColl.query(handler='select', params={'q': idsQuery,
-                                                        'rows': '100',
-                                                        'fl': "id,title,[features efi.keywords='%s']" % keywords} )
-
-
-
-        for doc in resp['response']['docs']:
-            docId = doc['id']
-            features = doc['[features]']
-            featuresPerDoc[docId] = featureCsvToList(features, ftrMapping)
-
-        print("REBUILDING TRAINING DATA for %s (%s/%s)" % (judgments[0].keywords, idx, len(judgmentsByQid)))
-        # Append features from ES back to ranklib judgment list
-        for judgment in judgments:
-            try:
-                features = featuresPerDoc[judgment.docId] # If KeyError, then we have a judgment but no movie in index
-                judgment.features = features
-            except KeyError:
-                print("Missing movie %s" % judgment.docId)
-        idx += 1
-
-
-
-
-def buildFeaturesJudgmentsFile(judgmentsWithFeatures, filename):
-    with open(filename, 'w') as judgmentFile:
-        for qid, judgmentList in judgmentsWithFeatures.items():
-            for judgment in judgmentList:
-                judgmentFile.write(judgment.toRanklibFormat() + "\n")
-
-
-if __name__ == "__main__":
-    from judgments import judgmentsFromFile, judgmentsByQid
-
-    solrColl = SolrColl('http://localhost:8983/solr/tmdb/')
-    judgmentsByQid = judgmentsByQid(judgmentsFromFile('movie_judgments.txt'))
-    logFeatures(solrColl, judgmentsByQid)
-    buildFeaturesJudgmentsFile(judgmentsByQid, "sample_judgments_wfeatures.txt")
-
diff --git a/ltr/train/esUrlParse.py b/ltr/train/esUrlParse.py
deleted file mode 100644
index 8335d94..0000000
--- a/ltr/train/esUrlParse.py
+++ /dev/null
@@ -1,15 +0,0 @@
-def parseUrl(fullEsUrl):
-    from urllib.parse import urlsplit, urlunsplit
-    import os.path
-    o = urlsplit(fullEsUrl)
-
-    esUrl = urlunsplit([o.scheme, o.netloc, '','',''])
-
-    indexAndSearchType = os.path.split(o.path)
-
-    return (esUrl, indexAndSearchType[0][1:], indexAndSearchType[1])
-
-
-if __name__ == "__main__":
-    from sys import argv
-    print(parseUrl(argv[1]))
diff --git a/ltr/train/features.txt b/ltr/train/features.txt
deleted file mode 100644
index 1191247..0000000
--- a/ltr/train/features.txt
+++ /dev/null
@@ -1,2 +0,0 @@
-1
-2
diff --git a/ltr/train/judgments.py b/ltr/train/judgments.py
deleted file mode 100644
index 958c6ed..0000000
--- a/ltr/train/judgments.py
+++ /dev/null
@@ -1,144 +0,0 @@
-import re
-
-class Judgment:
-    def __init__(self, grade, qid, keywords, docId, weight=1):
-        self.grade = grade
-        self.qid = qid
-        self.keywords = keywords
-        self.docId = docId
-        self.features = [] # 0th feature is ranklib feature 1
-        self.weight = weight
-
-    def sameQueryAndDoc(self, other):
-        return self.qid == other.qid and self.docId == other.docId
-
-    def __str__(self):
-        return "grade:%s qid:%s (%s) docid:%s" % (self.grade, self.qid, self.keywords, self.docId)
-
-    def toRanklibFormat(self):
-        featuresAsStrs = ["%s:%s" % (idx+1, feature) for idx, feature in enumerate(self.features)]
-        comment = "# %s\t%s" % (self.docId, self.keywords)
-        return "%s\tqid:%s\t%s %s" % (self.grade, self.qid, "\t".join(featuresAsStrs), comment)
-
-
-def _queriesToHeader(qidToKwDict):
-    rVal = ""
-    for qid, kws in qidToKwDict.items():
-        rVal += "# qid:%s: %s" % (qid, kws[0])
-        rVal += "*%s\n" % kws[1]
-    rVal += "\n"
-    return rVal
-
-
-def _queriesFromHeader(lines):
-    """ Parses out mapping between, query id and user keywords
-        from header comments, ie:
-        # qid:523: First Blood
-        returns dict mapping all query ids to search keywords"""
-    # Regex can be debugged here:
-    # http://www.regexpal.com/?fam=96564
-    regex = re.compile('#\sqid:(\d+?):\s+?(.*)')
-    rVal = {}
-    for line in lines:
-        if line[0] != '#':
-            break
-        m = re.match(regex, line)
-        try:
-            if m:
-                keywordAndWeight = m.group(2).split('*')
-                keyword = keywordAndWeight[0]
-                weight = 1
-                if len(keywordAndWeight) > 1:
-                    weight = int(keywordAndWeight[-1])
-                rVal[int(m.group(1))] = (keyword, weight)
-        except ValueError as e:
-            import pdb; pdb.set_trace()
-            print(e)
-
-    return rVal
-
-def _judgmentsFromBody(lines):
-    """ Parses out judgment/grade, query id, and docId in line such as:
-         4  qid:523   # a01  Grade for Rambo for query Foo
-        <judgment> qid:<queryid> # docId <rest of comment ignored...)"""
-    # Regex can be debugged here:
-    # http://www.regexpal.com/?fam=96565
-    regex = re.compile('^(\d+)\s+qid:(\d+)\s+#\s+(\w+).*')
-    for line in lines:
-        m = re.match(regex, line)
-        if m:
-            yield int(m.group(1)), int(m.group(2)), m.group(3)
-        else:
-            print("Not Recognized as Judgment %s" % line)
-
-
-def judgmentsFromFile(filename):
-    with open(filename) as f:
-        qidToKeywords = _queriesFromHeader(f)
-    with open(filename) as f:
-        lastQid = -1
-        for grade, qid, docId in _judgmentsFromBody(f):
-            if lastQid != qid and qid % 100 == 0:
-                print("Parsing %s" % qid)
-            yield Judgment(grade=grade, qid=qid, keywords=qidToKeywords[qid][0], weight=qidToKeywords[qid][1], docId=docId)
-            lastQid = qid
-
-
-def judgmentsToFile(filename, judgmentsList):
-    judgToQid = judgmentsByQid(judgmentsList) #Pretty hideosly slow stuff
-    fileHeader = _queriesToHeader({qid: (judgs[0].keywords, judgs[0].weight) for qid, judgs in judgToQid.items()})
-    judgByQid = sorted(judgmentsList, key=lambda j: j.qid)
-    with open(filename, 'w+') as f:
-        f.write(fileHeader)
-        for judg in judgByQid:
-            f.write(judg.toRanklibFormat() + '\n')
-
-
-
-
-def judgmentsByQid(judgments):
-    rVal = {}
-    for judgment in judgments:
-        try:
-            rVal[judgment.qid].append(judgment)
-        except KeyError:
-            rVal[judgment.qid] = [judgment]
-    return rVal
-
-
-def duplicateJudgmentsByWeight(judgmentsByQid):
-
-    def copyJudgments(srcJudgments):
-        destJudgments = []
-        for judg in srcJudgments:
-            destJudgments.append(Judgment(grade=judg.grade,
-                                          qid=judg.qid,
-                                          keywords=judg.keywords,
-                                          weight=judg.weight,
-                                          docId=judg.docId))
-        return destJudgments
-
-    rVal = {}
-    maxQid = 0
-    for qid, judgments in judgmentsByQid.items():
-        maxQid = qid
-    for qid, judgments in judgmentsByQid.items():
-        rVal[qid] = judgments
-        if (qid % 100 == 0):
-            print("Duping %s" % qid)
-        if (judgments[0].weight > 1):
-            for i in range(judgments[0].weight - 1):
-                rVal[maxQid] = copyJudgments(judgments)
-                for judg in judgments:
-                    judg.qid = maxQid
-                maxQid += 1
-
-
-    return rVal
-
-if __name__ == "__main__":
-    from sys import argv
-    for judgment in judgmentsFromFile(argv[1]):
-        print(judgment)
-
-
diff --git a/ltr/train/loadFeatures.py b/ltr/train/loadFeatures.py
deleted file mode 100644
index b2f14a5..0000000
--- a/ltr/train/loadFeatures.py
+++ /dev/null
@@ -1,30 +0,0 @@
-import json
-
-def getFeature(ftrId):
-    return json.loads(open('%s.json' % ftrId).read())
-
-
-def featureOrdToName():
-    features = []
-    for ftrId, feature in eachFeature():
-        features.append((ftrId, feature['name']))
-    return features
-
-def eachFeature():
-    try:
-        ftrId = 1
-        while True:
-            parsedJson = getFeature(ftrId)
-            yield ftrId, parsedJson
-            ftrId += 1
-    except IOError:
-        pass
-
-
-
-if __name__ == "__main__":
-    from solr import SolrColl
-    solrHost='http://localhost:8983'
-    solrColl = SolrColl('http://localhost:8983/solr/tmdb/')
-    solrColl.reloadFeatures(features=eachFeature())
-    print(featureOrdToName())
diff --git a/ltr/train/movie_judgments.txt b/ltr/train/movie_judgments.txt
deleted file mode 100644
index 40e97e4..0000000
--- a/ltr/train/movie_judgments.txt
+++ /dev/null
@@ -1,2090 +0,0 @@
-# qid:1: rambo*1
-# qid:2: rocky*1
-# qid:3: war games*1
-# qid:4: crocodile dundee*1
-# qid:5: matrix*1
-# qid:6: contact*1
-# qid:7: space jam*1
-# qid:8: battlestar galactica*1
-# qid:9: her*1
-# qid:10: jobs*1
-# qid:11: social network*1
-# qid:12: rocky horror*1
-# qid:13: shawshank redemption*1
-# qid:14: french connection*1
-# qid:15: star wars new hope*1
-# qid:16: lego batman*1
-# qid:17: crouching tiger hidden dragon*1
-# qid:18: fight club*1
-# qid:19: die hard*1
-# qid:20: last temptation of christ*1
-# qid:21: tree of life*1
-# qid:22: murray saves christmas*1
-# qid:23: black swan*1
-# qid:24: emma*1
-# qid:25: mad max fury road*1
-# qid:26: kung fury*1
-# qid:27: mr smith goes to washington*1
-# qid:28: kill bill*1
-# qid:29: the godfather*1
-# qid:30: pulp fiction*1
-# qid:31: christmas vacation*1
-# qid:32: psycho*1
-# qid:33: life is beautiful*1
-# qid:34: dark knight*1
-# qid:35: the green mile*1
-# qid:36: forrest gump*1
-# qid:37: spaceship movie*1
-# qid:38: basketball cartoon aliens*10
-# qid:39: christmas movie*1
-# qid:40: reindeer movie*1
-# qid:41: alien invasion*1
-# qid:42: video game movie*1
-# qid:43: football sunday*1
-# qid:44: football titans*1
-# qid:45: stuck on mars*10
-# qid:46: world war 2*1
-# qid:47: world war 1*1
-# qid:48: science fiction*1
-# qid:49: world war i*1
-# qid:50: world war ii*1
-# qid:51: korean war*1
-# qid:52: music industry*1
-# qid:53: historical comedy*1
-# qid:54: second world war*1
-# qid:55: first world war*1
-# qid:56: coco*1
-# qid:57: harts war*1
-# qid:58: football movie*1
-# qid:59: football*1
-# qid:60: stallone sharon stone*1
-# qid:61: patrick stewart*1
-# qid:62: william shatner*1
-# qid:63: stallone*1
-# qid:64: sharon stone sylvester stallone*1
-
-4	qid:1	 # 7555	rambo
-3	qid:1	 # 1370	rambo
-3	qid:1	 # 1369	rambo
-3	qid:1	 # 13258	rambo
-4	qid:1	 # 1368	rambo
-1	qid:1	 # 31362	rambo
-1	qid:1	 # 61410	rambo
-0	qid:1	 # 319074	rambo
-0	qid:1	 # 10296	rambo
-0	qid:1	 # 35868	rambo
-0	qid:1	 # 131457	rambo
-0	qid:1	 # 94794	rambo
-0	qid:1	 # 169869	rambo
-0	qid:1	 # 34561	rambo
-0	qid:1	 # 13763	rambo
-0	qid:1	 # 62414	rambo
-0	qid:1	 # 21989	rambo
-0	qid:1	 # 210577	rambo
-0	qid:1	 # 56949	rambo
-0	qid:1	 # 79401	rambo
-0	qid:1	 # 117942	rambo
-0	qid:1	 # 223195	rambo
-0	qid:1	 # 70	rambo
-0	qid:1	 # 22777	rambo
-0	qid:1	 # 43189	rambo
-0	qid:1	 # 318	rambo
-0	qid:1	 # 39829	rambo
-1	qid:1	 # 208982	rambo
-1	qid:1	 # 250761	rambo
-1	qid:1	 # 801	rambo
-1	qid:1	 # 78999	rambo
-1	qid:1	 # 600	rambo
-0	qid:1	 # 26397	rambo
-0	qid:1	 # 45046	rambo
-0	qid:1	 # 271110	rambo
-0	qid:1	 # 59401	rambo
-0	qid:1	 # 79773	rambo
-4	qid:2	 # 1366	rocky
-3	qid:2	 # 1374	rocky
-3	qid:2	 # 1371	rocky
-3	qid:2	 # 1246	rocky
-3	qid:2	 # 1375	rocky
-3	qid:2	 # 1367	rocky
-3	qid:2	 # 60375	rocky
-1	qid:2	 # 110123	rocky
-1	qid:2	 # 36685	rocky
-1	qid:2	 # 17711	rocky
-0	qid:2	 # 2153	rocky
-0	qid:2	 # 339403	rocky
-0	qid:2	 # 21501	rocky
-0	qid:2	 # 81182	rocky
-0	qid:2	 # 62414	rocky
-0	qid:2	 # 21989	rocky
-0	qid:2	 # 11	rocky
-0	qid:2	 # 12180	rocky
-0	qid:2	 # 140607	rocky
-0	qid:2	 # 1893	rocky
-0	qid:2	 # 330459	rocky
-0	qid:2	 # 152601	rocky
-0	qid:2	 # 17819	rocky
-0	qid:2	 # 198001	rocky
-0	qid:2	 # 170430	rocky
-0	qid:2	 # 18206	rocky
-1	qid:2	 # 47059	rocky
-0	qid:2	 # 18215	rocky
-1	qid:2	 # 70808	rocky
-1	qid:2	 # 351862	rocky
-1	qid:2	 # 154019	rocky
-1	qid:2	 # 70	rocky
-0	qid:2	 # 22777	rocky
-0	qid:2	 # 43189	rocky
-0	qid:2	 # 318	rocky
-0	qid:2	 # 39829	rocky
-1	qid:2	 # 1578	rocky
-0	qid:2	 # 25855	rocky
-1	qid:2	 # 42012	rocky
-0	qid:2	 # 32276	rocky
-0	qid:2	 # 105536	rocky
-3	qid:3	 # 14154	war games
-0	qid:3	 # 365371	war games
-0	qid:3	 # 116059	war games
-0	qid:3	 # 335988	war games
-0	qid:3	 # 354287	war games
-0	qid:3	 # 390054	war games
-0	qid:3	 # 346672	war games
-0	qid:3	 # 369885	war games
-0	qid:3	 # 293767	war games
-0	qid:3	 # 381288	war games
-4	qid:3	 # 860	war games
-0	qid:3	 # 9614	war games
-0	qid:3	 # 125842	war games
-0	qid:3	 # 427760	war games
-0	qid:3	 # 4247	war games
-0	qid:3	 # 30335	war games
-0	qid:3	 # 10207	war games
-0	qid:3	 # 24964	war games
-0	qid:3	 # 91893	war games
-0	qid:3	 # 10951	war games
-0	qid:3	 # 126148	war games
-1	qid:3	 # 10428	war games
-1	qid:3	 # 12699	war games
-0	qid:3	 # 136698	war games
-1	qid:3	 # 1557	war games
-1	qid:3	 # 19433	war games
-4	qid:4	 # 9671	crocodile dundee
-4	qid:4	 # 9396	crocodile dundee
-3	qid:4	 # 9290	crocodile dundee
-1	qid:4	 # 248390	crocodile dundee
-1	qid:4	 # 221737	crocodile dundee
-0	qid:4	 # 13022	crocodile dundee
-0	qid:4	 # 10539	crocodile dundee
-1	qid:4	 # 17043	crocodile dundee
-1	qid:4	 # 78402	crocodile dundee
-1	qid:4	 # 25652	crocodile dundee
-0	qid:4	 # 36068	crocodile dundee
-0	qid:4	 # 77680	crocodile dundee
-1	qid:4	 # 6972	crocodile dundee
-1	qid:4	 # 182848	crocodile dundee
-1	qid:4	 # 259311	crocodile dundee
-0	qid:4	 # 293028	crocodile dundee
-0	qid:4	 # 64586	crocodile dundee
-1	qid:4	 # 40466	crocodile dundee
-0	qid:4	 # 104221	crocodile dundee
-0	qid:4	 # 183894	crocodile dundee
-0	qid:4	 # 3573	crocodile dundee
-0	qid:4	 # 12254	crocodile dundee
-0	qid:4	 # 17813	crocodile dundee
-0	qid:4	 # 9835	crocodile dundee
-0	qid:4	 # 70490	crocodile dundee
-0	qid:4	 # 239877	crocodile dundee
-0	qid:4	 # 8995	crocodile dundee
-0	qid:4	 # 47964	crocodile dundee
-4	qid:5	 # 603	matrix
-3	qid:5	 # 604	matrix
-3	qid:5	 # 605	matrix
-2	qid:5	 # 55931	matrix
-0	qid:5	 # 1857	matrix
-0	qid:5	 # 10999	matrix
-0	qid:5	 # 4247	matrix
-0	qid:5	 # 21874	matrix
-0	qid:5	 # 181886	matrix
-0	qid:5	 # 21208	matrix
-0	qid:5	 # 125607	matrix
-0	qid:5	 # 56441	matrix
-0	qid:5	 # 124080	matrix
-0	qid:5	 # 1487	matrix
-0	qid:5	 # 72867	matrix
-0	qid:5	 # 11253	matrix
-0	qid:5	 # 213110	matrix
-0	qid:5	 # 13805	matrix
-0	qid:5	 # 104221	matrix
-0	qid:5	 # 183894	matrix
-0	qid:5	 # 3573	matrix
-0	qid:5	 # 12254	matrix
-0	qid:5	 # 17813	matrix
-1	qid:5	 # 73262	matrix
-0	qid:5	 # 17960	matrix
-0	qid:5	 # 33068	matrix
-0	qid:5	 # 28377	matrix
-0	qid:5	 # 13300	matrix
-0	qid:5	 # 680	matrix
-0	qid:5	 # 28131	matrix
-0	qid:5	 # 37988	matrix
-0	qid:5	 # 18451	matrix
-0	qid:5	 # 75404	matrix
-4	qid:6	 # 686	contact
-1	qid:6	 # 7011	contact
-1	qid:6	 # 20236	contact
-1	qid:6	 # 31337	contact
-1	qid:6	 # 199	contact
-1	qid:6	 # 21136	contact
-1	qid:6	 # 109572	contact
-1	qid:6	 # 68730	contact
-1	qid:6	 # 340676	contact
-1	qid:6	 # 364433	contact
-1	qid:6	 # 289318	contact
-1	qid:6	 # 15990	contact
-1	qid:6	 # 775	contact
-1	qid:6	 # 22379	contact
-0	qid:6	 # 101609	contact
-0	qid:6	 # 2153	contact
-0	qid:6	 # 339403	contact
-0	qid:6	 # 103	contact
-0	qid:6	 # 9677	contact
-0	qid:6	 # 38187	contact
-1	qid:6	 # 157336	contact
-0	qid:6	 # 11504	contact
-0	qid:6	 # 37910	contact
-1	qid:6	 # 2164	contact
-1	qid:6	 # 26978	contact
-1	qid:6	 # 61591	contact
-0	qid:6	 # 20305	contact
-1	qid:6	 # 98355	contact
-1	qid:6	 # 16203	contact
-0	qid:6	 # 8652	contact
-0	qid:6	 # 15142	contact
-0	qid:6	 # 120271	contact
-0	qid:6	 # 13926	contact
-0	qid:6	 # 47500	contact
-0	qid:6	 # 97397	contact
-0	qid:6	 # 696	contact
-0	qid:6	 # 16988	contact
-0	qid:6	 # 24810	contact
-0	qid:6	 # 61415	contact
-4	qid:7	 # 2300	space jam
-0	qid:7	 # 395992	space jam
-0	qid:7	 # 365942	space jam
-0	qid:7	 # 188927	space jam
-0	qid:7	 # 279096	space jam
-0	qid:7	 # 332502	space jam
-0	qid:7	 # 158852	space jam
-0	qid:7	 # 301728	space jam
-0	qid:7	 # 243938	space jam
-0	qid:7	 # 157336	space jam
-0	qid:7	 # 36373	space jam
-0	qid:7	 # 7555	space jam
-0	qid:7	 # 1370	space jam
-0	qid:7	 # 1369	space jam
-0	qid:7	 # 1368	space jam
-0	qid:7	 # 288183	space jam
-1	qid:7	 # 10474	space jam
-0	qid:7	 # 105583	space jam
-0	qid:7	 # 267345	space jam
-0	qid:7	 # 93856	space jam
-0	qid:7	 # 12435	space jam
-1	qid:7	 # 14736	space jam
-1	qid:7	 # 20737	space jam
-0	qid:7	 # 267	space jam
-1	qid:7	 # 46094	space jam
-0	qid:7	 # 10575	space jam
-0	qid:7	 # 213985	space jam
-0	qid:7	 # 162442	space jam
-0	qid:7	 # 76155	space jam
-0	qid:7	 # 49001	space jam
-0	qid:7	 # 245950	space jam
-0	qid:7	 # 272165	space jam
-0	qid:7	 # 66118	space jam
-0	qid:7	 # 73351	space jam
-0	qid:7	 # 136741	space jam
-0	qid:8	 # 51999	battlestar galactica
-0	qid:8	 # 24128	battlestar galactica
-0	qid:8	 # 61120	battlestar galactica
-0	qid:8	 # 4584	battlestar galactica
-0	qid:8	 # 315010	battlestar galactica
-4	qid:8	 # 325553	battlestar galactica
-3	qid:8	 # 69315	battlestar galactica
-3	qid:8	 # 105077	battlestar galactica
-1	qid:8	 # 11	battlestar galactica
-1	qid:8	 # 12180	battlestar galactica
-1	qid:8	 # 140607	battlestar galactica
-1	qid:8	 # 1893	battlestar galactica
-1	qid:8	 # 330459	battlestar galactica
-0	qid:8	 # 9876	battlestar galactica
-0	qid:8	 # 34614	battlestar galactica
-0	qid:8	 # 74208	battlestar galactica
-0	qid:8	 # 16384	battlestar galactica
-0	qid:8	 # 1918	battlestar galactica
-0	qid:8	 # 34582	battlestar galactica
-0	qid:8	 # 31546	battlestar galactica
-0	qid:8	 # 99258	battlestar galactica
-0	qid:8	 # 44375	battlestar galactica
-0	qid:8	 # 195617	battlestar galactica
-0	qid:8	 # 143841	battlestar galactica
-0	qid:8	 # 247112	battlestar galactica
-0	qid:8	 # 13371	battlestar galactica
-0	qid:8	 # 77887	battlestar galactica
-0	qid:8	 # 82424	battlestar galactica
-0	qid:8	 # 18238	battlestar galactica
-0	qid:8	 # 105538	battlestar galactica
-0	qid:8	 # 99648	battlestar galactica
-0	qid:8	 # 44479	battlestar galactica
-0	qid:8	 # 138535	battlestar galactica
-0	qid:8	 # 8068	battlestar galactica
-0	qid:8	 # 7085	battlestar galactica
-0	qid:8	 # 43212	battlestar galactica
-0	qid:8	 # 54186	battlestar galactica
-0	qid:8	 # 50479	battlestar galactica
-4	qid:9	 # 152601	her
-0	qid:9	 # 17819	her
-0	qid:9	 # 198001	her
-0	qid:9	 # 170430	her
-0	qid:9	 # 18206	her
-0	qid:9	 # 96769	her
-0	qid:9	 # 86457	her
-0	qid:9	 # 130750	her
-0	qid:9	 # 59527	her
-0	qid:9	 # 5143	her
-0	qid:9	 # 1919	her
-0	qid:9	 # 23967	her
-0	qid:9	 # 53156	her
-0	qid:9	 # 79887	her
-0	qid:9	 # 11931	her
-0	qid:9	 # 45241	her
-0	qid:9	 # 14556	her
-0	qid:9	 # 9374	her
-0	qid:9	 # 66113	her
-0	qid:9	 # 265966	her
-1	qid:9	 # 4032	her
-1	qid:9	 # 11317	her
-0	qid:9	 # 73969	her
-0	qid:9	 # 14279	her
-0	qid:9	 # 54198	her
-0	qid:9	 # 47607	her
-0	qid:9	 # 28687	her
-0	qid:9	 # 42757	her
-1	qid:9	 # 11446	her
-0	qid:9	 # 2026	her
-2	qid:9	 # 12223	her
-2	qid:9	 # 9890	her
-0	qid:9	 # 288772	her
-1	qid:9	 # 200236	her
-1	qid:9	 # 60140	her
-4	qid:10	 # 115782	jobs
-4	qid:10	 # 321697	jobs
-3	qid:10	 # 89638	jobs
-0	qid:10	 # 127929	jobs
-0	qid:10	 # 47099	jobs
-0	qid:10	 # 16406	jobs
-0	qid:10	 # 15302	jobs
-0	qid:10	 # 41588	jobs
-0	qid:10	 # 281289	jobs
-0	qid:10	 # 14773	jobs
-0	qid:10	 # 55069	jobs
-0	qid:10	 # 21629	jobs
-0	qid:10	 # 3293	jobs
-3	qid:10	 # 186606	jobs
-0	qid:10	 # 213938	jobs
-0	qid:10	 # 54559	jobs
-0	qid:10	 # 13119	jobs
-0	qid:10	 # 27223	jobs
-0	qid:10	 # 133469	jobs
-0	qid:10	 # 1774	jobs
-4	qid:11	 # 37799	social network
-0	qid:11	 # 267752	social network
-0	qid:11	 # 18467	social network
-0	qid:11	 # 78294	social network
-0	qid:11	 # 10774	social network
-0	qid:11	 # 49980	social network
-0	qid:11	 # 38408	social network
-0	qid:11	 # 39002	social network
-0	qid:11	 # 59387	social network
-0	qid:11	 # 28303	social network
-0	qid:11	 # 32547	social network
-0	qid:11	 # 268735	social network
-0	qid:11	 # 328069	social network
-0	qid:11	 # 16988	social network
-0	qid:11	 # 24664	social network
-0	qid:11	 # 25218	social network
-0	qid:11	 # 23451	social network
-0	qid:11	 # 39750	social network
-0	qid:11	 # 11779	social network
-0	qid:11	 # 33358	social network
-4	qid:12	 # 36685	rocky horror
-0	qid:12	 # 1374	rocky horror
-0	qid:12	 # 1246	rocky horror
-0	qid:12	 # 1371	rocky horror
-0	qid:12	 # 1375	rocky horror
-0	qid:12	 # 1367	rocky horror
-0	qid:12	 # 81830	rocky horror
-0	qid:12	 # 60375	rocky horror
-0	qid:12	 # 110123	rocky horror
-0	qid:12	 # 33475	rocky horror
-0	qid:12	 # 1366	rocky horror
-0	qid:12	 # 13696	rocky horror
-0	qid:12	 # 17711	rocky horror
-0	qid:12	 # 7443	rocky horror
-0	qid:12	 # 300669	rocky horror
-0	qid:12	 # 14228	rocky horror
-0	qid:12	 # 791	rocky horror
-0	qid:12	 # 27997	rocky horror
-0	qid:12	 # 16139	rocky horror
-0	qid:12	 # 49445	rocky horror
-4	qid:13	 # 278	shawshank redemption
-0	qid:13	 # 214857	shawshank redemption
-0	qid:13	 # 31781	shawshank redemption
-0	qid:13	 # 295958	shawshank redemption
-0	qid:13	 # 81657	shawshank redemption
-0	qid:13	 # 198130	shawshank redemption
-0	qid:13	 # 46016	shawshank redemption
-0	qid:13	 # 241287	shawshank redemption
-0	qid:13	 # 126056	shawshank redemption
-0	qid:13	 # 78049	shawshank redemption
-0	qid:13	 # 13989	shawshank redemption
-0	qid:13	 # 136418	shawshank redemption
-0	qid:13	 # 38124	shawshank redemption
-0	qid:13	 # 38234	shawshank redemption
-0	qid:13	 # 135714	shawshank redemption
-0	qid:13	 # 220820	shawshank redemption
-0	qid:13	 # 75576	shawshank redemption
-0	qid:13	 # 288162	shawshank redemption
-0	qid:13	 # 166901	shawshank redemption
-0	qid:13	 # 48199	shawshank redemption
-4	qid:14	 # 1051	french connection
-3	qid:14	 # 10711	french connection
-1	qid:14	 # 197950	french connection
-0	qid:14	 # 288953	french connection
-0	qid:14	 # 44379	french connection
-0	qid:14	 # 59558	french connection
-0	qid:14	 # 27067	french connection
-0	qid:14	 # 24166	french connection
-0	qid:14	 # 19086	french connection
-0	qid:14	 # 288290	french connection
-0	qid:14	 # 2011	french connection
-0	qid:14	 # 266040	french connection
-0	qid:14	 # 33996	french connection
-0	qid:14	 # 223519	french connection
-0	qid:14	 # 236661	french connection
-0	qid:14	 # 30238	french connection
-0	qid:14	 # 36095	french connection
-0	qid:14	 # 61462	french connection
-0	qid:14	 # 15053	french connection
-0	qid:14	 # 37845	french connection
-2	qid:15	 # 278604	star wars new hope
-2	qid:15	 # 278468	star wars new hope
-3	qid:15	 # 12180	star wars new hope
-2	qid:15	 # 20787	star wars new hope
-2	qid:15	 # 76180	star wars new hope
-3	qid:15	 # 1895	star wars new hope
-3	qid:15	 # 1894	star wars new hope
-4	qid:15	 # 11	star wars new hope
-3	qid:15	 # 330459	star wars new hope
-1	qid:15	 # 101609	star wars new hope
-1	qid:15	 # 81899	star wars new hope
-0	qid:15	 # 29587	star wars new hope
-0	qid:15	 # 11008	star wars new hope
-3	qid:15	 # 140607	star wars new hope
-3	qid:15	 # 1893	star wars new hope
-0	qid:15	 # 25872	star wars new hope
-0	qid:15	 # 19837	star wars new hope
-0	qid:15	 # 18046	star wars new hope
-0	qid:15	 # 10521	star wars new hope
-0	qid:15	 # 5717	star wars new hope
-4	qid:16	 # 324849	lego batman
-3	qid:16	 # 177271	lego batman
-3	qid:16	 # 322456	lego batman
-3	qid:16	 # 137106	lego batman
-2	qid:16	 # 33427	lego batman
-1	qid:16	 # 45162	lego batman
-1	qid:16	 # 364	lego batman
-1	qid:16	 # 251519	lego batman
-1	qid:16	 # 382322	lego batman
-1	qid:16	 # 321528	lego batman
-1	qid:16	 # 415	lego batman
-1	qid:16	 # 29751	lego batman
-1	qid:16	 # 15805	lego batman
-1	qid:16	 # 17074	lego batman
-1	qid:16	 # 125249	lego batman
-1	qid:16	 # 40662	lego batman
-1	qid:16	 # 366924	lego batman
-1	qid:16	 # 21683	lego batman
-1	qid:16	 # 20077	lego batman
-1	qid:16	 # 93560	lego batman
-4	qid:17	 # 146	crouching tiger hidden dragon
-3	qid:17	 # 263341	crouching tiger hidden dragon
-1	qid:17	 # 15860	crouching tiger hidden dragon
-0	qid:17	 # 214857	crouching tiger hidden dragon
-0	qid:17	 # 16407	crouching tiger hidden dragon
-0	qid:17	 # 103173	crouching tiger hidden dragon
-0	qid:17	 # 81870	crouching tiger hidden dragon
-0	qid:17	 # 10473	crouching tiger hidden dragon
-0	qid:17	 # 21521	crouching tiger hidden dragon
-0	qid:17	 # 75465	crouching tiger hidden dragon
-0	qid:17	 # 287233	crouching tiger hidden dragon
-0	qid:17	 # 22752	crouching tiger hidden dragon
-0	qid:17	 # 220504	crouching tiger hidden dragon
-0	qid:17	 # 39144	crouching tiger hidden dragon
-0	qid:17	 # 47626	crouching tiger hidden dragon
-0	qid:17	 # 2805	crouching tiger hidden dragon
-0	qid:17	 # 75507	crouching tiger hidden dragon
-0	qid:17	 # 35868	crouching tiger hidden dragon
-0	qid:17	 # 27245	crouching tiger hidden dragon
-0	qid:17	 # 39148	crouching tiger hidden dragon
-4	qid:18	 # 550	fight club
-1	qid:18	 # 1366	fight club
-0	qid:18	 # 26555	fight club
-0	qid:18	 # 51976	fight club
-0	qid:18	 # 248774	fight club
-0	qid:18	 # 43522	fight club
-0	qid:18	 # 277622	fight club
-0	qid:18	 # 293660	fight club
-0	qid:18	 # 17136	fight club
-0	qid:18	 # 276120	fight club
-0	qid:18	 # 110491	fight club
-0	qid:18	 # 13973	fight club
-0	qid:18	 # 137145	fight club
-0	qid:18	 # 5951	fight club
-0	qid:18	 # 39578	fight club
-0	qid:18	 # 23683	fight club
-0	qid:18	 # 213983	fight club
-0	qid:18	 # 55831	fight club
-0	qid:18	 # 39254	fight club
-0	qid:18	 # 197033	fight club
-4	qid:19	 # 562	die hard
-3	qid:19	 # 1573	die hard
-3	qid:19	 # 1572	die hard
-3	qid:19	 # 1571	die hard
-3	qid:19	 # 47964	die hard
-0	qid:19	 # 26244	die hard
-0	qid:19	 # 7517	die hard
-0	qid:19	 # 269494	die hard
-0	qid:19	 # 201414	die hard
-0	qid:19	 # 90374	die hard
-0	qid:19	 # 20160	die hard
-0	qid:19	 # 44103	die hard
-0	qid:19	 # 4836	die hard
-0	qid:19	 # 73335	die hard
-0	qid:19	 # 233487	die hard
-0	qid:19	 # 23449	die hard
-0	qid:19	 # 13063	die hard
-0	qid:19	 # 31046	die hard
-0	qid:19	 # 289010	die hard
-0	qid:19	 # 259616	die hard
-0	qid:19	 # 10258	die hard
-0	qid:19	 # 51311	die hard
-0	qid:19	 # 13250	die hard
-0	qid:19	 # 34599	die hard
-0	qid:19	 # 37270	die hard
-0	qid:19	 # 83125	die hard
-4	qid:20	 # 11051	last temptation of christ
-1	qid:20	 # 28169	last temptation of christ
-0	qid:20	 # 23830	last temptation of christ
-2	qid:20	 # 615	last temptation of christ
-2	qid:20	 # 19401	last temptation of christ
-0	qid:20	 # 20268	last temptation of christ
-2	qid:20	 # 47980	last temptation of christ
-0	qid:20	 # 97006	last temptation of christ
-1	qid:20	 # 262904	last temptation of christ
-1	qid:20	 # 96973	last temptation of christ
-2	qid:20	 # 24192	last temptation of christ
-1	qid:20	 # 36226	last temptation of christ
-2	qid:20	 # 12545	last temptation of christ
-0	qid:20	 # 23522	last temptation of christ
-2	qid:20	 # 31510	last temptation of christ
-2	qid:20	 # 199512	last temptation of christ
-0	qid:20	 # 68981	last temptation of christ
-0	qid:20	 # 46756	last temptation of christ
-2	qid:20	 # 213386	last temptation of christ
-0	qid:20	 # 149145	last temptation of christ
-4	qid:21	 # 8967	tree of life
-0	qid:21	 # 62394	tree of life
-0	qid:21	 # 51409	tree of life
-0	qid:21	 # 45974	tree of life
-0	qid:21	 # 165911	tree of life
-0	qid:21	 # 30177	tree of life
-0	qid:21	 # 91737	tree of life
-0	qid:21	 # 43008	tree of life
-0	qid:21	 # 37284	tree of life
-0	qid:21	 # 43767	tree of life
-0	qid:21	 # 94706	tree of life
-0	qid:21	 # 117730	tree of life
-0	qid:21	 # 36540	tree of life
-0	qid:21	 # 61080	tree of life
-0	qid:21	 # 72358	tree of life
-0	qid:21	 # 25435	tree of life
-0	qid:21	 # 79042	tree of life
-0	qid:21	 # 36072	tree of life
-0	qid:21	 # 159138	tree of life
-0	qid:21	 # 158711	tree of life
-0	qid:21	 # 7555	tree of life
-0	qid:21	 # 1370	tree of life
-0	qid:21	 # 1369	tree of life
-0	qid:21	 # 1368	tree of life
-0	qid:21	 # 288183	tree of life
-2	qid:22	 # 26386	murray saves christmas
-3	qid:22	 # 364067	murray saves christmas
-2	qid:22	 # 9647	murray saves christmas
-0	qid:22	 # 175555	murray saves christmas
-0	qid:22	 # 5825	murray saves christmas
-0	qid:22	 # 10433	murray saves christmas
-0	qid:22	 # 28033	murray saves christmas
-1	qid:22	 # 81393	murray saves christmas
-1	qid:22	 # 21501	murray saves christmas
-1	qid:22	 # 172413	murray saves christmas
-1	qid:22	 # 20785	murray saves christmas
-1	qid:22	 # 46240	murray saves christmas
-1	qid:22	 # 86778	murray saves christmas
-1	qid:22	 # 45697	murray saves christmas
-1	qid:22	 # 13187	murray saves christmas
-1	qid:22	 # 14813	murray saves christmas
-1	qid:22	 # 49742	murray saves christmas
-1	qid:22	 # 850	murray saves christmas
-1	qid:22	 # 13189	murray saves christmas
-1	qid:22	 # 13358	murray saves christmas
-0	qid:22	 # 1366	murray saves christmas
-0	qid:22	 # 1374	murray saves christmas
-0	qid:22	 # 1246	murray saves christmas
-0	qid:22	 # 1367	murray saves christmas
-0	qid:22	 # 1371	murray saves christmas
-0	qid:22	 # 44718	murray saves christmas
-0	qid:22	 # 127451	murray saves christmas
-0	qid:22	 # 87169	murray saves christmas
-0	qid:22	 # 153141	murray saves christmas
-0	qid:22	 # 12493	murray saves christmas
-1	qid:22	 # 81182	murray saves christmas
-1	qid:22	 # 9656	murray saves christmas
-1	qid:22	 # 340402	murray saves christmas
-1	qid:22	 # 16412	murray saves christmas
-0	qid:22	 # 52105	murray saves christmas
-0	qid:22	 # 9871	murray saves christmas
-0	qid:22	 # 27429	murray saves christmas
-0	qid:22	 # 73065	murray saves christmas
-0	qid:22	 # 20077	murray saves christmas
-0	qid:22	 # 192393	murray saves christmas
-0	qid:22	 # 15906	murray saves christmas
-0	qid:22	 # 43532	murray saves christmas
-0	qid:22	 # 36670	murray saves christmas
-0	qid:22	 # 13343	murray saves christmas
-4	qid:23	 # 44214	black swan
-4	qid:23	 # 29882	black swan
-1	qid:23	 # 8966	black swan
-0	qid:23	 # 124461	black swan
-0	qid:23	 # 27327	black swan
-0	qid:23	 # 39424	black swan
-0	qid:23	 # 18239	black swan
-0	qid:23	 # 95242	black swan
-2	qid:23	 # 22586	black swan
-2	qid:23	 # 15016	black swan
-1	qid:23	 # 28302	black swan
-1	qid:23	 # 54113	black swan
-0	qid:23	 # 50619	black swan
-0	qid:23	 # 54491	black swan
-1	qid:23	 # 61048	black swan
-0	qid:23	 # 40440	black swan
-0	qid:23	 # 24021	black swan
-0	qid:23	 # 199818	black swan
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-0	qid:23	 # 39914	black swan
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-0	qid:23	 # 15167	black swan
-1	qid:23	 # 13759	black swan
-0	qid:23	 # 49852	black swan
-0	qid:23	 # 24696	black swan
-0	qid:23	 # 22582	black swan
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-0	qid:23	 # 76891	black swan
-0	qid:23	 # 39853	black swan
-0	qid:23	 # 30669	black swan
-0	qid:23	 # 91292	black swan
-0	qid:23	 # 11816	black swan
-0	qid:23	 # 116983	black swan
-0	qid:23	 # 76346	black swan
-4	qid:24	 # 104221	emma
-4	qid:24	 # 183894	emma
-4	qid:24	 # 3573	emma
-4	qid:24	 # 12254	emma
-3	qid:24	 # 17813	emma
-0	qid:24	 # 78646	emma
-0	qid:24	 # 12432	emma
-0	qid:24	 # 63727	emma
-0	qid:24	 # 152584	emma
-0	qid:24	 # 77468	emma
-0	qid:24	 # 26985	emma
-0	qid:24	 # 2528	emma
-0	qid:24	 # 23512	emma
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-0	qid:24	 # 24869	emma
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-0	qid:24	 # 11050	emma
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-0	qid:24	 # 80215	emma
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-0	qid:24	 # 20873	emma
-0	qid:24	 # 541	emma
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-4	qid:25	 # 76341	mad max fury road
-3	qid:25	 # 8810	mad max fury road
-3	qid:25	 # 9659	mad max fury road
-3	qid:25	 # 9355	mad max fury road
-1	qid:25	 # 290999	mad max fury road
-0	qid:25	 # 37776	mad max fury road
-0	qid:25	 # 9770	mad max fury road
-0	qid:25	 # 149172	mad max fury road
-0	qid:25	 # 27460	mad max fury road
-0	qid:25	 # 62529	mad max fury road
-0	qid:25	 # 92667	mad max fury road
-0	qid:25	 # 27543	mad max fury road
-0	qid:25	 # 24351	mad max fury road
-0	qid:25	 # 159615	mad max fury road
-0	qid:25	 # 26258	mad max fury road
-0	qid:25	 # 251516	mad max fury road
-0	qid:25	 # 4148	mad max fury road
-0	qid:25	 # 228150	mad max fury road
-0	qid:25	 # 47608	mad max fury road
-0	qid:25	 # 201086	mad max fury road
-0	qid:25	 # 239573	mad max fury road
-0	qid:25	 # 13911	mad max fury road
-0	qid:25	 # 28036	mad max fury road
-0	qid:25	 # 9346	mad max fury road
-0	qid:25	 # 32074	mad max fury road
-4	qid:26	 # 251516	kung fury
-1	qid:26	 # 18666	kung fury
-0	qid:26	 # 37776	kung fury
-0	qid:26	 # 149172	kung fury
-0	qid:26	 # 27460	kung fury
-0	qid:26	 # 62529	kung fury
-0	qid:26	 # 11891	kung fury
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-0	qid:26	 # 24351	kung fury
-0	qid:26	 # 159615	kung fury
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-0	qid:26	 # 86577	kung fury
-0	qid:26	 # 41870	kung fury
-0	qid:26	 # 339428	kung fury
-0	qid:26	 # 9614	kung fury
-4	qid:27	 # 3083	mr smith goes to washington
-2	qid:27	 # 25058	mr smith goes to washington
-1	qid:27	 # 266814	mr smith goes to washington
-0	qid:27	 # 15670	mr smith goes to washington
-0	qid:27	 # 78140	mr smith goes to washington
-0	qid:27	 # 787	mr smith goes to washington
-0	qid:27	 # 45019	mr smith goes to washington
-0	qid:27	 # 35262	mr smith goes to washington
-0	qid:27	 # 31309	mr smith goes to washington
-0	qid:27	 # 162284	mr smith goes to washington
-0	qid:27	 # 260	mr smith goes to washington
-0	qid:27	 # 303742	mr smith goes to washington
-0	qid:27	 # 44383	mr smith goes to washington
-0	qid:27	 # 77012	mr smith goes to washington
-0	qid:27	 # 33831	mr smith goes to washington
-0	qid:27	 # 24197	mr smith goes to washington
-0	qid:27	 # 101449	mr smith goes to washington
-0	qid:27	 # 55863	mr smith goes to washington
-0	qid:27	 # 909	mr smith goes to washington
-0	qid:27	 # 14434	mr smith goes to washington
-0	qid:27	 # 9928	mr smith goes to washington
-0	qid:27	 # 10681	mr smith goes to washington
-0	qid:27	 # 283995	mr smith goes to washington
-0	qid:27	 # 62994	mr smith goes to washington
-0	qid:27	 # 212849	mr smith goes to washington
-0	qid:27	 # 83735	mr smith goes to washington
-0	qid:27	 # 10107	mr smith goes to washington
-0	qid:27	 # 287991	mr smith goes to washington
-0	qid:27	 # 59744	mr smith goes to washington
-0	qid:27	 # 27297	mr smith goes to washington
-0	qid:27	 # 67750	mr smith goes to washington
-0	qid:27	 # 288153	mr smith goes to washington
-0	qid:27	 # 5424	mr smith goes to washington
-0	qid:27	 # 20980	mr smith goes to washington
-0	qid:27	 # 15292	mr smith goes to washington
-0	qid:27	 # 9067	mr smith goes to washington
-0	qid:27	 # 12629	mr smith goes to washington
-0	qid:27	 # 9804	mr smith goes to washington
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-0	qid:28	 # 330711	kill bill
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-0	qid:28	 # 13589	kill bill
-0	qid:28	 # 53063	kill bill
-0	qid:28	 # 128276	kill bill
-0	qid:28	 # 167305	kill bill
-0	qid:28	 # 54102	kill bill
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-0	qid:28	 # 3080	kill bill
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-0	qid:29	 # 220933	the godfather
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-0	qid:29	 # 39514	the godfather
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-0	qid:36	 # 73952	forrest gump
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-0	qid:60	 # 8984	stallone sharon stone
-0	qid:60	 # 9395	stallone sharon stone
-0	qid:60	 # 32726	stallone sharon stone
-2	qid:60	 # 45712	stallone sharon stone
-2	qid:60	 # 31922	stallone sharon stone
-2	qid:60	 # 8916	stallone sharon stone
-2	qid:60	 # 23916	stallone sharon stone
-0	qid:60	 # 9614	stallone sharon stone
-0	qid:60	 # 125842	stallone sharon stone
-0	qid:60	 # 427760	stallone sharon stone
-0	qid:60	 # 30335	stallone sharon stone
-0	qid:60	 # 20178	stallone sharon stone
-0	qid:60	 # 24655	stallone sharon stone
-0	qid:60	 # 310133	stallone sharon stone
-0	qid:60	 # 46989	stallone sharon stone
-0	qid:60	 # 15462	stallone sharon stone
-0	qid:60	 # 13931	stallone sharon stone
-0	qid:60	 # 786	stallone sharon stone
-0	qid:60	 # 8886	stallone sharon stone
-0	qid:60	 # 105586	stallone sharon stone
-0	qid:60	 # 125034	stallone sharon stone
-0	qid:60	 # 257442	stallone sharon stone
-0	qid:60	 # 3179	stallone sharon stone
-0	qid:60	 # 16290	stallone sharon stone
-0	qid:60	 # 102431	stallone sharon stone
-0	qid:60	 # 1574	stallone sharon stone
-0	qid:60	 # 128298	stallone sharon stone
-0	qid:60	 # 43213	stallone sharon stone
-0	qid:60	 # 28816	stallone sharon stone
-0	qid:60	 # 116008	stallone sharon stone
-0	qid:61	 # 13894	patrick stewart
-3	qid:61	 # 25950	patrick stewart
-0	qid:61	 # 19664	patrick stewart
-3	qid:61	 # 47913	patrick stewart
-0	qid:61	 # 133119	patrick stewart
-1	qid:61	 # 13475	patrick stewart
-4	qid:61	 # 193	patrick stewart
-4	qid:61	 # 200	patrick stewart
-4	qid:61	 # 199	patrick stewart
-4	qid:61	 # 201	patrick stewart
-0	qid:61	 # 44233	patrick stewart
-0	qid:61	 # 241554	patrick stewart
-0	qid:61	 # 18702	patrick stewart
-0	qid:61	 # 48864	patrick stewart
-0	qid:61	 # 222649	patrick stewart
-0	qid:61	 # 37292	patrick stewart
-0	qid:61	 # 18264	patrick stewart
-0	qid:61	 # 43882	patrick stewart
-0	qid:61	 # 4934	patrick stewart
-0	qid:61	 # 91419	patrick stewart
-1	qid:61	 # 154	patrick stewart
-0	qid:61	 # 67109	patrick stewart
-0	qid:61	 # 68247	patrick stewart
-0	qid:61	 # 180954	patrick stewart
-0	qid:61	 # 332411	patrick stewart
-4	qid:61	 # 36657	patrick stewart
-1	qid:61	 # 49538	patrick stewart
-3	qid:61	 # 2080	patrick stewart
-1	qid:61	 # 246655	patrick stewart
-3	qid:61	 # 36668	patrick stewart
-0	qid:61	 # 3080	patrick stewart
-0	qid:61	 # 99875	patrick stewart
-0	qid:61	 # 43580	patrick stewart
-0	qid:61	 # 10588	patrick stewart
-0	qid:61	 # 20239	patrick stewart
-0	qid:61	 # 9651	patrick stewart
-0	qid:61	 # 54182	patrick stewart
-0	qid:61	 # 104329	patrick stewart
-0	qid:61	 # 8840	patrick stewart
-0	qid:61	 # 38866	patrick stewart
-0	qid:61	 # 4518	patrick stewart
-0	qid:61	 # 11788	patrick stewart
-0	qid:61	 # 4517	patrick stewart
-0	qid:61	 # 65035	patrick stewart
-0	qid:61	 # 16902	patrick stewart
-0	qid:61	 # 14043	patrick stewart
-0	qid:61	 # 47883	patrick stewart
-0	qid:61	 # 25975	patrick stewart
-0	qid:61	 # 213831	patrick stewart
-0	qid:61	 # 47882	patrick stewart
-0	qid:61	 # 8208	patrick stewart
-0	qid:61	 # 574	patrick stewart
-0	qid:61	 # 9414	patrick stewart
-0	qid:61	 # 2762	patrick stewart
-0	qid:61	 # 86261	patrick stewart
-0	qid:61	 # 11857	patrick stewart
-0	qid:61	 # 84857	patrick stewart
-0	qid:61	 # 185	patrick stewart
-0	qid:61	 # 633	patrick stewart
-0	qid:61	 # 277686	patrick stewart
-0	qid:61	 # 27573	patrick stewart
-0	qid:61	 # 54054	patrick stewart
-0	qid:61	 # 5922	patrick stewart
-0	qid:61	 # 51859	patrick stewart
-0	qid:61	 # 429	patrick stewart
-0	qid:61	 # 20442	patrick stewart
-0	qid:61	 # 38804	patrick stewart
-0	qid:61	 # 19063	patrick stewart
-0	qid:61	 # 81657	patrick stewart
-0	qid:61	 # 635	patrick stewart
-0	qid:61	 # 11697	patrick stewart
-0	qid:61	 # 2165	patrick stewart
-0	qid:61	 # 28638	patrick stewart
-0	qid:61	 # 51594	patrick stewart
-0	qid:61	 # 66600	patrick stewart
-0	qid:61	 # 11836	patrick stewart
-0	qid:61	 # 228165	patrick stewart
-0	qid:61	 # 510	patrick stewart
-0	qid:61	 # 57211	patrick stewart
-0	qid:61	 # 82866	patrick stewart
-0	qid:61	 # 293310	patrick stewart
-0	qid:61	 # 10338	patrick stewart
-3	qid:62	 # 70703	william shatner
-3	qid:62	 # 13533	william shatner
-2	qid:62	 # 21846	william shatner
-3	qid:62	 # 5851	william shatner
-2	qid:62	 # 20305	william shatner
-2	qid:62	 # 13475	william shatner
-4	qid:62	 # 193	william shatner
-1	qid:62	 # 200	william shatner
-1	qid:62	 # 199	william shatner
-1	qid:62	 # 201	william shatner
-4	qid:62	 # 168	william shatner
-1	qid:62	 # 81899	william shatner
-4	qid:62	 # 157	william shatner
-0	qid:62	 # 1075	william shatner
-0	qid:62	 # 25508	william shatner
-0	qid:62	 # 6217	william shatner
-0	qid:62	 # 11694	william shatner
-0	qid:62	 # 25078	william shatner
-0	qid:62	 # 99875	william shatner
-0	qid:62	 # 43580	william shatner
-0	qid:62	 # 10588	william shatner
-0	qid:62	 # 13675	william shatner
-0	qid:62	 # 3080	william shatner
-0	qid:62	 # 513	william shatner
-0	qid:62	 # 139567	william shatner
-0	qid:62	 # 334521	william shatner
-0	qid:62	 # 12503	william shatner
-0	qid:62	 # 13153	william shatner
-0	qid:62	 # 92381	william shatner
-0	qid:62	 # 276518	william shatner
-0	qid:62	 # 39113	william shatner
-0	qid:62	 # 83732	william shatner
-0	qid:62	 # 37843	william shatner
-3	qid:63	 # 23916	stallone
-3	qid:63	 # 38925	stallone
-3	qid:63	 # 81830	stallone
-3	qid:63	 # 1825	stallone
-3	qid:63	 # 9876	stallone
-4	qid:63	 # 1366	stallone
-4	qid:63	 # 1246	stallone
-4	qid:63	 # 1374	stallone
-4	qid:63	 # 1367	stallone
-4	qid:63	 # 1371	stallone
-4	qid:63	 # 7555	stallone
-3	qid:63	 # 1370	stallone
-3	qid:63	 # 1369	stallone
-4	qid:63	 # 1368	stallone
-0	qid:63	 # 31362	stallone
-0	qid:63	 # 22048	stallone
-0	qid:63	 # 52270	stallone
-0	qid:63	 # 17589	stallone
-0	qid:63	 # 25941	stallone
-0	qid:63	 # 84197	stallone
-0	qid:63	 # 10009	stallone
-0	qid:63	 # 81675	stallone
-0	qid:63	 # 2383	stallone
-0	qid:63	 # 125948	stallone
-0	qid:63	 # 41515	stallone
-0	qid:63	 # 74055	stallone
-0	qid:63	 # 36764	stallone
-0	qid:63	 # 171372	stallone
-0	qid:63	 # 4365	stallone
-0	qid:63	 # 71933	stallone
-0	qid:63	 # 57521	stallone
-0	qid:63	 # 118761	stallone
-0	qid:63	 # 128442	stallone
-0	qid:63	 # 126136	stallone
-0	qid:63	 # 91	stallone
-1	qid:64	 # 23916	sharon stone sylvester stallone
-1	qid:64	 # 81830	sharon stone sylvester stallone
-1	qid:64	 # 38925	sharon stone sylvester stallone
-4	qid:64	 # 2636	sharon stone sylvester stallone
-1	qid:64	 # 1825	sharon stone sylvester stallone
-0	qid:64	 # 19575	sharon stone sylvester stallone
-0	qid:64	 # 10608	sharon stone sylvester stallone
-0	qid:64	 # 10276	sharon stone sylvester stallone
-0	qid:64	 # 26030	sharon stone sylvester stallone
-0	qid:64	 # 26520	sharon stone sylvester stallone
-0	qid:64	 # 44874	sharon stone sylvester stallone
-0	qid:64	 # 15016	sharon stone sylvester stallone
-0	qid:64	 # 15167	sharon stone sylvester stallone
-0	qid:64	 # 77499	sharon stone sylvester stallone
-0	qid:64	 # 34564	sharon stone sylvester stallone
-1	qid:64	 # 45712	sharon stone sylvester stallone
-1	qid:64	 # 31922	sharon stone sylvester stallone
-1	qid:64	 # 32067	sharon stone sylvester stallone
-1	qid:64	 # 31700	sharon stone sylvester stallone
-1	qid:64	 # 61265	sharon stone sylvester stallone
-0	qid:64	 # 18722	sharon stone sylvester stallone
-0	qid:64	 # 1792	sharon stone sylvester stallone
-0	qid:64	 # 18885	sharon stone sylvester stallone
-0	qid:64	 # 13341	sharon stone sylvester stallone
-0	qid:64	 # 15104	sharon stone sylvester stallone
-4	qid:64	 # 8916	sharon stone sylvester stallone
diff --git a/ltr/train/prepare.py b/ltr/train/prepare.py
deleted file mode 100644
index d6434ff..0000000
--- a/ltr/train/prepare.py
+++ /dev/null
@@ -1,17 +0,0 @@
-from urllib.parse import urljoin
-import requests
-
-def downloadLtrResource(resource):
-    ltrDomain = 'http://es-learn-to-rank.labs.o19s.com/'
-    resourceUrl = urljoin(ltrDomain, resource)
-    with open(resource, 'wb') as dest:
-        print("GET %s" % resourceUrl)
-        resp = requests.get(resourceUrl, stream=True)
-        for chunk in resp.iter_content(chunk_size=1024):
-            if chunk:
-                dest.write(chunk)
-
-
-if __name__ == "__main__":
-    downloadLtrResource('tmdb.json')
-    downloadLtrResource('RankyMcRankFace.jar')
diff --git a/ltr/train/ranklibToSolr.py b/ltr/train/ranklibToSolr.py
deleted file mode 100644
index 9bd0ac4..0000000
--- a/ltr/train/ranklibToSolr.py
+++ /dev/null
@@ -1,138 +0,0 @@
-from loadFeatures import featureOrdToName
-import json
-from xml.etree import ElementTree
-
-#
-# Thanks Christine Poerschke
-# taken from LTR w/ bees
-# https://github.com/cpoerschke/ltr-with-bees/blob/master/py-wrappers/trees.py
-#
-def rankLibMartToSolr(ensemble_xml_string, modelName, featureIndex2featureName):
-
-  def transform_branches(root, featureIndex2featureName):
-
-    # turn feature index into feature name
-    for feature in root.findall("feature"):
-      feature.text = featureIndex2featureName[int(feature.text)]
-
-    for threshold in root.findall("threshold"):
-        threshold.text = str(float(threshold.text))
-
-    for branch in root.findall("split"):
-      # turn <split> element with pos='???' attribute into <???> element
-      branch.tag = branch.get("pos")
-
-      # turn <output> element into <value> element
-      for output in branch.findall("output"):
-        output.tag = "value"
-        output.text = str(float(output.text))
-
-      # recurse
-      transform_branches(branch, featureIndex2featureName)
-
-
-  def parse_and_adjust_xml(xml_string):
-
-    ensemble = ElementTree.fromstring(xml_string)
-
-    for tree in ensemble.findall("tree"):
-
-      # turn 'weight' attribute into 'weight' sub-element
-      weight = ElementTree.SubElement(tree, 'weight')
-      weight.text = str(tree.get("weight"))
-
-      # rename tree root from <split> to <root>
-      for root in tree.findall("split"):
-        root.tag = "root"
-
-        transform_branches(root, featureIndex2featureName)
-
-    return ensemble
-
-
-  def json_from_xml(input):
-
-    if input.text != None and input.text.replace("\n","").replace("\t","") != "":
-
-      return input.text
-
-    else:
-
-      return { elem.tag : json_from_xml(input.find(elem.tag)) for elem in list(input) }
-
-
-  def trees_from_ensemble(xml_string):
-
-    ensemble_xml = parse_and_adjust_xml(xml_string)
-
-    return [ json_from_xml(tree) for tree in ensemble_xml.findall("tree") ]
-
-
-  def features_set_from_trees(trees):
-
-    features_set = set()
-
-    def collect_features_from_tree(sub_tree):
-
-      if 'feature' in sub_tree:
-        features_set.add(sub_tree.get("feature"))
-
-      if 'left' in sub_tree:
-        collect_features_from_tree(sub_tree.get("left"))
-
-      if 'right' in sub_tree:
-        collect_features_from_tree(sub_tree.get("right"))
-
-    for tree in trees:
-      collect_features_from_tree(tree.get("root"))
-
-    return [ { "name" : name } for name in features_set ]
-
-  ensemble_xml_string = '\n'.join(ensemble_xml_string.split('\n')[7:])
-
-  trees = trees_from_ensemble(ensemble_xml_string)
-  features = list(features_set_from_trees(trees))
-
-  treesModel = {
-    "class" : "org.apache.solr.ltr.model.MultipleAdditiveTreesModel",
-    "name" : modelName,
-    "features" : features,
-    "params" : { "trees" : trees }
-  }
-  return treesModel
-
-def getModelType(modelTxt):
-    # 0, MART
-    # 1, RankNet
-    # 2, RankBoost
-    # 3, AdaRank
-    # 4, coord Ascent
-    # 6, LambdaMART
-    # 7, ListNET
-    # 8, Random Forests
-    # 9, Linear Regression
-    modelHeader = modelTxt.split('\n')[0]
-    modelName = modelHeader[2:].strip()
-    if modelName == "MART":
-        return 0
-    elif modelName == "RankNet":
-        return 1
-    elif modelName == "RankBoost":
-        return 2
-    elif modelName == "AdaRank":
-        return 3
-    if modelName == "LambdaMART":
-        return 6
-    print(modelName)
-
-if __name__ == "__main__":
-    with open('model.txt') as f:
-        modelTxt = f.read()
-        getModelType(modelTxt)
-        nameToOrd = {_ord: name for (_ord, name) in  featureOrdToName()}
-        treesModel = rankLibMartToSolr(modelTxt, modelName='doug', featureIndex2featureName=nameToOrd)
-    outFile = 'model_solr.json'
-    print("Saved %s " % outFile)
-    with open(outFile, 'w') as f:
-        json.dump(treesModel, f, indent=2, separators=(',', ' : '))
-
diff --git a/ltr/train/search.py b/ltr/train/search.py
deleted file mode 100644
index 01fa678..0000000
--- a/ltr/train/search.py
+++ /dev/null
@@ -1,26 +0,0 @@
-from solr import SolrColl
-
-def search(solrConn, model, keywords, rerankWeight):
-    resp = solrConn.query(handler="select",
-                            params={"q": keywords,
-                                    "defType": "edismax",
-                                    "qf": "text_all",
-                                    "rq": "{!ltr model='%s' efi.keywords='%s' rerankDocs=100, rerankWeight=%s}" % (model, keywords, rerankWeight)})
-    return resp
-
-
-
-
-if __name__ == "__main__":
-    import configparser
-    from sys import argv
-
-    config = configparser.ConfigParser()
-    config.read('settings.cfg')
-    solrColl=config['DEFAULT']['SolrColl']
-
-    solrColl = SolrColl(solrColl=solrColl)
-    model = "doug_6"
-    resp = search(solrColl, model=model, keywords=argv[1], rerankWeight=1)
-    for doc in resp['response']['docs']:
-        print(doc['title'])
diff --git a/ltr/train/settings.cfg b/ltr/train/settings.cfg
deleted file mode 100644
index c69697e..0000000
--- a/ltr/train/settings.cfg
+++ /dev/null
@@ -1,2 +0,0 @@
-[DEFAULT]
-SolrColl = http://localhost:8983/solr/tmdb/
\ No newline at end of file
diff --git a/ltr/train/solr.py b/ltr/train/solr.py
deleted file mode 100644
index 2c5cc30..0000000
--- a/ltr/train/solr.py
+++ /dev/null
@@ -1,55 +0,0 @@
-import requests
-import json
-from ranklibToSolr import rankLibMartToSolr
-
-class SolrColl:
-    """ Solr helpers around a collection... """
-    def __init__(self, solrColl='http://localhost:8983/solr/tmdb/', verbose=True):
-        self.solrColl = solrColl
-        if self.solrColl[-1] != '/':
-            self.solrColl += '/'
-        self.verbose = verbose
-
-    def ifVerbosePrint(self, aStr):
-        if self.verbose:
-            print(aStr)
-
-
-    def handleResp(self, resp):
-        self.ifVerbosePrint(resp.status_code)
-        if resp.status_code < 200 or resp.status_code >= 300:
-            print(resp.text)
-            raise IOError("Solr Error %s" % resp.text)
-
-
-    def query(self, handler, params):
-        queryUrl = self.solrColl + handler
-        self.ifVerbosePrint("GET %s" % queryUrl)
-        self.ifVerbosePrint(json.dumps(params, indent=2))
-        resp = requests.get(queryUrl, params=params)
-        self.handleResp(resp)
-        return json.loads(resp.text)
-
-
-    def reloadFeatures(self, features):
-        url = self.solrColl + "schema/feature-store"
-        deletePath = url + '/_DEFAULT_'
-
-        self.ifVerbosePrint("DELETE %s" % url)
-        resp = requests.delete(deletePath)
-        self.ifVerbosePrint(resp.status_code)
-
-        featureSet = [feature for _, feature in features]
-        self.ifVerbosePrint("POST %s" % url)
-        self.ifVerbosePrint(json.dumps(featureSet, indent=2))
-        resp = requests.post(url, json.dumps(featureSet))
-        self.handleResp(resp)
-
-    def saveRankLibModel(self, modelName, modelTxt, ftrOrdToName):
-        solrModel = rankLibMartToSolr(modelTxt, modelName, ftrOrdToName)
-        url = self.solrColl + "schema/model-store"
-        self.ifVerbosePrint("PUT %s" % url)
-        resp = requests.put(url, json.dumps(solrModel))
-        self.handleResp(resp)
-
-
diff --git a/ltr/train/train.py b/ltr/train/train.py
deleted file mode 100644
index fa9d1f1..0000000
--- a/ltr/train/train.py
+++ /dev/null
@@ -1,91 +0,0 @@
-import os
-from collectFeatures import logFeatures, buildFeaturesJudgmentsFile, featureOrdToName
-from loadFeatures import eachFeature
-
-
-def trainModel(trainingData, testData, modelOutput, whichModel=8):
-    # java -jar RankLib-2.6.jar -metric2t NDCG@4 -ranker 6 -kcv -train osc_judgments_wfeatures_train.txt -test osc_judgments_wfeatures_test.txt -save model.txt
-
-    # For random forest
-    # - bags of LambdaMART models
-    #  - each is trained against a proportion of the training data (-srate)
-    #  - each is trained using a subset of the features (-frate)
-    #  - each can be either a MART or LambdaMART model (-rtype 6 lambda mart)
-    cmd = "java -jar RankyMcRankFace.jar -gmax 20 -metric2t DCG@5 -bag 4 -srate 0.6 -frate 0.6 -rtype 6 -shrinkage 0.1 -tree 10 -ranker %s -train %s -test %s -save %s -feature features.txt" % (whichModel, trainingData, testData, modelOutput)
-    print("*********************************************************************")
-    print("*********************************************************************")
-    print("Running %s" % cmd)
-    os.system(cmd)
-    pass
-
-
-def partitionJudgments(judgments, testProportion=0.1):
-    testJudgments = {}
-    trainJudgments = {}
-    from random import random
-    for qid, judgment in judgments.items():
-        draw = random()
-        if draw <= testProportion:
-            testJudgments[qid] = judgment
-        else:
-            trainJudgments[qid] = judgment
-
-    return (trainJudgments, testJudgments)
-
-if __name__ == "__main__":
-
-    HUMAN_JUDGMENTS = 'movie_judgments.txt'
-    TRAIN_JUDGMENTS = 'movie_judgments_wfeatures_train.txt'
-    TEST_JUDGMENTS = 'movie_judgments_wfeatures_test.txt'
-
-    #HUMAN_JUDGMENTS = 'synth_judg.txt'
-    #TRAIN_JUDGMENTS = 'synth_judg_wfeatures_train.txt'
-    #TEST_JUDGMENTS = 'synth_judg_wfeatures_test.txt'
-
-    import configparser
-    from solr import SolrColl
-    from judgments import judgmentsFromFile, judgmentsByQid, duplicateJudgmentsByWeight
-
-    config = configparser.ConfigParser()
-    config.read('settings.cfg')
-    solrUrl = config['DEFAULT']['SolrColl']
-
-    solrColl = SolrColl(solrUrl)
-
-    # Load features into Solr
-    solrColl.reloadFeatures(features=eachFeature())
-    # Parse a judgments
-    print("-Parse judgments...")
-    movieJudgments = judgmentsByQid(judgmentsFromFile(filename=HUMAN_JUDGMENTS))
-    print("-Dup judgments by weight...")
-    movieJudgments = duplicateJudgmentsByWeight(movieJudgments)
-    print("-Train test split")
-    trainJudgments, testJudgments = partitionJudgments(movieJudgments, testProportion=0.1)
-
-    # Use proposed Solr queries (1.json... N.json) to generate a training set
-    # output as "sample_judgments_wfeatures.txt"
-    print("-Log Features")
-    logFeatures(solrColl, judgmentsByQid=movieJudgments)
-
-    print("-Build training")
-    buildFeaturesJudgmentsFile(trainJudgments, filename=TRAIN_JUDGMENTS)
-    buildFeaturesJudgmentsFile(testJudgments, filename=TEST_JUDGMENTS)
-
-    ftrOrdToName = {_ord: name for (_ord, name) in  featureOrdToName()}
-
-    # Train each ranklib model type
-    for modelType in [6]:
-        # 0, MART
-        # 1, RankNet
-        # 2, RankBoost
-        # 3, AdaRank
-        # 4, coord Ascent
-        # 6, LambdaMART
-        # 7, ListNET
-        # 8, Random Forests
-        # 9, Linear Regression
-        print("*** Training %s " % modelType)
-        trainModel(trainingData=TRAIN_JUDGMENTS, testData=TEST_JUDGMENTS, modelOutput='model.txt', whichModel=modelType)
-        with open('model.txt') as f:
-            rankLibModel = f.read()
-            solrColl.saveRankLibModel(modelName="doug_%s" % modelType, modelTxt=rankLibModel, ftrOrdToName=ftrOrdToName)
diff --git a/ltr/training-process.html b/ltr/training-process.html
deleted file mode 100644
index eccb5ce..0000000
--- a/ltr/training-process.html
+++ /dev/null
@@ -1,105 +0,0 @@
-<!doctype html>
-<html lang="en">
-<head>
-    <title>Elasticsearch Learning to Rank Demo</title>
-    <meta charset="utf8"/>
-</head>
-<body>
-<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.1/jquery.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/handlebars.js/4.0.10/handlebars.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/mustache.js/2.3.0/mustache.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/tether/1.4.0/js/tether.min.js" integrity="sha384-DztdAPBWPRXSA/3eYEEUWrWCy7G5KFbe8fFjk5JAIxUYHKkDx6Qin1DkWx51bBrb" crossorigin="anonymous"></script>
-<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-alpha.6/js/bootstrap.min.js" integrity="sha384-vBWWzlZJ8ea9aCX4pEW3rVHjgjt7zpkNpZk+02D9phzyeVkE+jo0ieGizqPLForn" crossorigin="anonymous"></script>
-
-<!-- Latest compiled and minified CSS -->
-<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-beta.2/css/bootstrap.min.css"
-      integrity="sha384-PsH8R72JQ3SOdhVi3uxftmaW6Vc51MKb0q5P2rRUpPvrszuE4W1povHYgTpBfshb" crossorigin="anonymous">
-<link rel="stylesheet" href="css/flatly.css">
-<a href="https://github.com/o19s/elasticsearch-ltr-demo"><img style="position: absolute; top: 0; right: 0; border: 0;" src="https://camo.githubusercontent.com/38ef81f8aca64bb9a64448d0d70f1308ef5341ab/68747470733a2f2f73332e616d617a6f6e6177732e636f6d2f6769746875622f726962626f6e732f666f726b6d655f72696768745f6461726b626c75655f3132313632312e706e67" alt="Fork me on GitHub" data-canonical-src="https://s3.amazonaws.com/github/ribbons/forkme_right_darkblue_121621.png"></a>
-
-<div class="container">
-<ul class="nav nav-pills">
-    <li class="nav-item">
-      <a class="nav-link" href="index.html">Welcome!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="base-search.html">Lonely Search 😕</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="judgment-lists.html">Define Good/Bad Results</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link" href="feature-selection.html">Select Features</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link active" href="training-process.html">Train!</a>
-    </li>
-    <li class="nav-item">
-      <a class="nav-link " href="ltr-search.html">Happy LTR Search! 😀</a>
-    </li>
-  </ul>
-
-
-<div class="jumbotron">
- <div class="row">
-    <div class="col-md-2"></div>
-    <div class="col-md-8"><h3>Dance!</h3></div>
-    <div class="col-md-2"></div>
-  </div> 
-
-
-<div class="row">
-  <div class="col-md-2"></div>
-  <div class="col-md-8">
-	
-
-    <p class="lead">Tools like <a href="https://sourceforge.net/p/lemur/wiki/RankLib/">Ranklib</a> use training data to generate a ranking model. Ranklib is run as below: 
-    </p>
-    
-    <pre>
-      java -jar RankLib.jar -ranker 6 \ 
-                -train training_set.txt \ 
-                -save model.txt 
-    </pre>
-
-    <p class="lead">This command takes as input our training set <code>training_set.txt</code>, to create a model of type "6" (aka LamdbaMART), output to <code>model.txt</code>.</p>
-
-    <p class="lead">In this demo, we've trained three types of models:
-    <ol>
-      <li><span style="text-decoration: underline">Linear Model</span> -- A naive way of predicting the appropriatte weight or "boost" to apply to each feature.</li>
-      <li><span style="text-decoration: underline">LambdaMART</span> -- Relevance is rarely linear! More often each use case has it's own ranking requirements. LambdaMART is an ensemble of decision trees. Each level acts as an "if" statement, able to capture nuance specific to each use case. ie If a strong title match THEN rank the most popular movies with strongest title match first. </li>
-      <li><span style="text-decoration: underline">Random Forest</span> -- a collection of LambdaMART models trained on random subset of features and training data. This can prevent overfitting, creating a more generalizable model to use cases outside the training set. </li>
-
-
-    </ol>
-    
-    
-    </p>
-
-  </div>
-  <div class="col-md-2"></div>
-    
-</div>
-
-<div class="row">
-  <div class="col-md-3"></div>
-  <div class="col-md-6">
-	
-
-  </div>
-  <div class="col-md-3"></div>
-    
-</div>
-
-
-
-
-</div>
-
-
-</div>
-</div>
-
-</body>
-
-</html>
diff --git a/print_solr_explain.py b/print_solr_explain.py
deleted file mode 100644
index 81097e2..0000000
--- a/print_solr_explain.py
+++ /dev/null
@@ -1,11 +0,0 @@
-def main():
-    """
-    Just a simple print to format a Solr explain plan.
-    :return: None.
-    """
-    print(
-        '"7555": "\n24.63695 = sum of:\n  12.318475 = max of:\n    10.573916 = weight(overview:rambo in 3199) [SchemaSimilarity], result of:\n      10.573916 = score(doc=3199,freq=2.0 = termFreq=2.0\n), product of:\n        8.204964 = idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:\n          7.0 = docFreq\n          27442.0 = docCount\n        1.2887219 = tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:\n          2.0 = termFreq=2.0\n          1.2 = parameter k1\n          0.75 = parameter b\n          54.925552 = avgFieldLength\n          68.0 = fieldLength\n    12.318475 = weight(title:rambo in 3199) [SchemaSimilarity], result of:\n      12.318475 = score(doc=3199,freq=1.0 = termFreq=1.0\n), product of:\n        8.978624 = idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:\n          3.0 = docFreq\n          27760.0 = docCount\n        1.3719779 = tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:\n          1.0 = termFreq=1.0\n          1.2 = parameter k1\n          0.75 = parameter b\n          2.9651656 = avgFieldLength\n          1.0 = fieldLength\n  12.318475 = weight(title:rambo in 3199) [SchemaSimilarity], result of:\n    12.318475 = score(doc=3199,freq=1.0 = termFreq=1.0\n), product of:\n      8.978624 = idf, computed as log(1 + (docCount - docFreq + 0.5) / (docFreq + 0.5)) from:\n        3.0 = docFreq\n        27760.0 = docCount\n      1.3719779 = tfNorm, computed as (freq * (k1 + 1)) / (freq + k1 * (1 - b + b * fieldLength / avgFieldLength)) from:\n        1.0 = termFreq=1.0\n        1.2 = parameter k1\n        0.75 = parameter b\n        2.9651656 = avgFieldLength\n        1.0 = fieldLength\n"'
-    )
-
-if __name__ == "__main__":
-    main()
diff --git a/requirements.txt b/requirements.txt
deleted file mode 100644
index 83e62f5..0000000
--- a/requirements.txt
+++ /dev/null
@@ -1,6 +0,0 @@
-certifi==2020.4.5.1
-chardet==3.0.4
-idna==2.9
-pysolr==3.9.0
-requests==2.23.0
-urllib3==1.25.9
diff --git a/solr_postman_collection.json b/solr-postman-collection.json
similarity index 100%
rename from solr_postman_collection.json
rename to solr-postman-collection.json
diff --git a/solr_home/tmdb/conf/_schema_analysis_stopwords_english.json b/solr_home/tmdb/conf/_schema_analysis_stopwords_english.json
new file mode 100644
index 0000000..ab37f40
--- /dev/null
+++ b/solr_home/tmdb/conf/_schema_analysis_stopwords_english.json
@@ -0,0 +1,3 @@
+{
+  "initArgs":{"ignoreCase":false},
+  "managedList":[]}
\ No newline at end of file
diff --git a/solr_home/tmdb/conf/schema.xml b/solr_home/tmdb/conf/schema.xml
index 0708a7a..a94d983 100644
--- a/solr_home/tmdb/conf/schema.xml
+++ b/solr_home/tmdb/conf/schema.xml
@@ -16,10 +16,10 @@
  limitations under the License.
 -->
 
-<!--  
+<!--
  This is the Solr schema file. This file should be named "schema.xml" and
  should be in the conf directory under the solr home
- (i.e. ./solr/conf/schema.xml by default) 
+ (i.e. ./solr/conf/schema.xml by default)
  or located where the classloader for the Solr webapp can find it.
 
  This example schema is the recommended starting point for users.
@@ -47,19 +47,19 @@
 
 <schema name="example-basic" version="1.6">
     <!-- attribute "name" is the name of this schema and is only used for display purposes.
-       version="x.y" is Solr's version number for the schema syntax and 
+       version="x.y" is Solr's version number for the schema syntax and
        semantics.  It should not normally be changed by applications.
 
-       1.0: multiValued attribute did not exist, all fields are multiValued 
+       1.0: multiValued attribute did not exist, all fields are multiValued
             by nature
-       1.1: multiValued attribute introduced, false by default 
-       1.2: omitTermFreqAndPositions attribute introduced, true by default 
+       1.1: multiValued attribute introduced, false by default
+       1.2: omitTermFreqAndPositions attribute introduced, true by default
             except for text fields.
        1.3: removed optional field compress feature
        1.4: autoGeneratePhraseQueries attribute introduced to drive QueryParser
-            behavior when a single string produces multiple tokens.  Defaults 
+            behavior when a single string produces multiple tokens.  Defaults
             to off for version >= 1.4
-       1.5: omitNorms defaults to true for primitive field types 
+       1.5: omitNorms defaults to true for primitive field types
             (int, float, boolean, string...)
        1.6: useDocValuesAsStored defaults to true.
     -->
@@ -106,14 +106,14 @@
       trailing underscores (e.g. _version_) are reserved.
     -->
 
-    <!-- In this data_driven_schema_configs configset, only three fields are pre-declared: 
+    <!-- In this data_driven_schema_configs configset, only three fields are pre-declared:
          id, _version_, and _text_.  All other fields will be type guessed and added via the
-         "add-unknown-fields-to-the-schema" update request processor chain declared 
+         "add-unknown-fields-to-the-schema" update request processor chain declared
          in solrconfig.xml.
-         
-         Note that many dynamic fields are also defined - you can use them to specify a 
+
+         Note that many dynamic fields are also defined - you can use them to specify a
          field's type via field naming conventions - see below.
-  
+
          WARNING: The _text_ catch-all field will significantly increase your index size.
          If you don't need it, consider removing it and the corresponding copyField directive.
     -->
@@ -122,6 +122,7 @@
     <field name="title" type="text_general" indexed="true" stored="true" termVectors="true" termPositions="true"
            termOffsets="true"/>
     <field name="tagline" type="text_general" indexed="true" stored="true"/>
+    <field name="poster_path" type="string" indexed="true" stored="true"/>
     <field name="cast" type="text_general" indexed="true" stored="true" multiValued="true"/>
     <field name="directors" type="text_general" indexed="true" stored="true" multiValued="true"/>
     <field name="genres" type="text_general" indexed="true" stored="true" multiValued="true"/>
@@ -224,11 +225,11 @@
     <field name="text_all" type="text_general" indexed="true" stored="true" multiValued="true"/>
 
 
-    <!-- uncomment the following to ignore any fields that don't already match an existing 
-        field name or dynamic field, rather than reporting them as an error. 
-        alternately, change the type="ignored" to some other type e.g. "text" if you want 
-        unknown fields indexed and/or stored by default 
-        
+    <!-- uncomment the following to ignore any fields that don't already match an existing
+        field name or dynamic field, rather than reporting them as an error.
+        alternately, change the type="ignored" to some other type e.g. "text" if you want
+        unknown fields indexed and/or stored by default
+
         NB: use of "*" dynamic fields will disable field type guessing and adding
         unknown fields to the schema. -->
     <!--dynamicField name="*" type="ignored" multiValued="true" /-->
@@ -324,11 +325,11 @@
 
     <!-- The "RandomSortField" is not used to store or search any
          data.  You can declare fields of this type it in your schema
-         to generate pseudo-random orderings of your docs for sorting 
+         to generate pseudo-random orderings of your docs for sorting
          or function purposes.  The ordering is generated based on the field
          name and the version of the index. As long as the index version
          remains unchanged, and the same field name is reused,
-         the ordering of the docs will be consistent.  
+         the ordering of the docs will be consistent.
          If you want different psuedo-random orderings of documents,
          for the same version of the index, use a dynamicField and
          change the field name in the request.
@@ -403,7 +404,7 @@
          posn
          1      2            3         4         5
          the    science(2)   fi (2)    fiction   movie
-                sci(1)    
+                sci(1)
                 sci-fi(3)
 
 
@@ -785,8 +786,8 @@
 
 
     <!-- Similarity is the scoring routine for each document vs. a query.
-       A custom Similarity or SimilarityFactory may be specified here, but 
-       the default is fine for most applications.  
+       A custom Similarity or SimilarityFactory may be specified here, but
+       the default is fine for most applications.
        For more info: http://wiki.apache.org/solr/SchemaXml#Similarity
     -->
     <!--
diff --git a/tmdb.py b/tmdb.py
deleted file mode 100644
index dd75aab..0000000
--- a/tmdb.py
+++ /dev/null
@@ -1,73 +0,0 @@
-import requests
-import json
-import os
-import time
-from requests.exceptions import ConnectionError
-
-# you'll need to have an API key for TMDB
-# to run these examples,
-# run export TMDB_API_KEY=<YourAPIKey>
-tmdb_api_key = os.environ["TMDB_API_KEY"]
-# Setup tmdb as its own session, caching requests
-# (we only want to cache tmdb, not elasticsearch)
-# Get your TMDB API key from
-#  https://www.themoviedb.org/documentation/api
-# then in shell do export TMDB_API_KEY=<Your Key>
-tmdb_api = requests.Session()
-tmdb_api.params={'api_key': tmdb_api_key}
-
-def movieList(linksFile='ml-20m/links.csv'):
-    import csv
-    rdr = csv.reader(open(linksFile))
-    tmdbIds = {}
-    numMissing = 0
-    for rowNo, row in enumerate(rdr):
-        if rowNo == 0:
-            continue
-        try:
-            tmdbIds[row[0]] = int(row[2])
-        except ValueError:
-            numMissing += 1
-            print("No TMDB ID at %s, imdb is: %s, missing %s/%s" % (row[0], row[1], numMissing, rowNo))
-    return tmdbIds
-
-def getCastAndCrew(movieId, movie):
-    httpResp = tmdb_api.get("https://api.themoviedb.org/3/movie/%s/credits" % movieId, verify=False)
-    credits = json.loads(httpResp.text) #C
-    try:
-        crew = credits['crew']
-        directors = []
-        for crewMember in crew: #D
-            if crewMember['job'] == 'Director':
-                directors.append(crewMember)
-        movie['cast'] = credits['cast'] #E
-        movie['directors'] = directors
-    except KeyError as e:
-        print e
-        print credits
-
-def extract(movieIds=[]):
-    movieDict = {}
-    for idx, (mlensId, tmdbId) in enumerate(movieIds.iteritems()):
-        try:
-            print("On %s / %s movies" % (idx, len(movieIds)))
-            httpResp = tmdb_api.get("https://api.themoviedb.org/3/movie/%s"
-                                    % tmdbId, verify=False)
-            if int(httpResp.headers['x-ratelimit-remaining']) < 10:
-                print("Rate limited, sleeping")
-                time.sleep(6)
-            movie = json.loads(httpResp.text)
-            movie['mlensId'] = mlensId
-            getCastAndCrew(tmdbId, movie)
-            movieDict[tmdbId] = movie
-        except ConnectionError as e:
-            print e
-    return movieDict
-
-
-
-if __name__ == "__main__":
-    movieIds = movieList()
-    movieDict = extract(movieIds)
-    f = open('tmdb.json', 'w')
-    f.write(json.dumps(movieDict))
diff --git a/tmdbMovies.py b/tmdbMovies.py
deleted file mode 100644
index a9d7cd1..0000000
--- a/tmdbMovies.py
+++ /dev/null
@@ -1,15 +0,0 @@
-import json
-
-
-def rawTmdbMovies():
-    return json.load(open('tmdb.json'))
-
-
-def writeTmdmMovies(rawMoviesJson, path):
-    with open(path, 'w') as f:
-        json.dump(rawMoviesJson, f)
-
-def tmdbMovies():
-    tmdbMovies = rawTmdbMovies()
-    for movieId, tmdbMovie in tmdbMovies.items():
-        yield (movieId, tmdbMovie)
diff --git a/tmdb_solr.json.zip b/tmdb_solr.json.zip
new file mode 100644
index 0000000..2038adf
Binary files /dev/null and b/tmdb_solr.json.zip differ