anchor.diff:  
   // query
   JsonObject response = engineClient.sendQuery(ImmutableMap.<String, Object>of(
  -        "user", 1,
  +        "user", "1",
           "num",  4
       ));
   ```
     </div>
     <div data-tab="REST API" data-lang="json">
   ```
  -$ curl -H "Content-Type: application/json" -d '{ "user": 1, "num": 4 }' http://localhost:8000/queries.json
  +$ curl -H "Content-Type: application/json" -d '{ "user": "1", "num": 4 }' http://localhost:8000/queries.json
   
   {"productScores":[{"product":22,"score":4.072304374729956},{"product":62,"score":4.058482414005789},{"product":75,"score":4.046063009943821},{"product":68,"score":3.8153661512945325}]}
   ```
  
positive.code: ```python
  import predictionio
  engine_client = predictionio.EngineClient(url="http://localhost:8000")
  print engine_client.send_query({"user": 1, "num": 4})
  ```
    </div>
    <div data-tab="PHP SDK" data-lang="php">
  
negative.code: 
  
  Now, You can try to retrieve predicted results. To recommend 4 movies to user
  whose id is 1, you send this JSON `{ "user": "1", "num": 4 }` to the deployed
  engine and it will return a JSON of the recommended movies. Simply send a query
  by making a HTTP request or through the `EngineClient` of an SDK:
  
  