ci: tests for macOS on Gitlab CI

[nit.git] / lib / nlp / stanford.nit

diff --git a/lib/nlp/stanford.nit b/lib/nlp/stanford.nit
index 29058b3..a637d53 100644 (file)
--- a/lib/nlp/stanford.nit
+++ b/lib/nlp/stanford.nit
@@ -19,6 +19,8 @@ module stanford
 
 import opts
 import dom
+import curl
+import pthreads
 
 # Natural Language Processor
 #
@@ -277,11 +279,99 @@ class NLPToken
        # ~~~
        init from_xml(xml: XMLStartTag) do
                var index = xml.attributes.first.as(XMLStringAttr).value.to_i
-               var word = xml["word"].first.as(XMLStartTag).data
-               var lemma = xml["lemma"].first.as(XMLStartTag).data
-               var begin_offset = xml["CharacterOffsetBegin"].first.as(XMLStartTag).data.to_i
-               var end_offset = xml["CharacterOffsetEnd"].first.as(XMLStartTag).data.to_i
-               var pos = xml["POS"].first.as(XMLStartTag).data
+               var word = read_data(xml, "word")
+               var lemma = read_data(xml, "lemma")
+               var begin_offset = read_data(xml, "CharacterOffsetBegin").to_i
+               var end_offset = read_data(xml, "CharacterOffsetEnd").to_i
+               var pos = read_data(xml, "POS")
                init(index, word, lemma, begin_offset, end_offset, pos)
        end
+
+       private fun read_data(xml: XMLStartTag, tag_name: String): String do
+               var res = ""
+               if xml[tag_name].is_empty then return res
+               var first = xml[tag_name].first
+               if not first isa XMLStartTag then return res
+               var data = first.data
+               if data == null then return res
+               return data
+       end
+end
+
+# Stanford web server
+#
+# Runs the server on `port`.
+#
+# For more details about the stanford NLP server see
+# https://stanfordnlp.github.io/CoreNLP/corenlp-server.html
+class NLPServer
+       super Thread
+
+       # Stanford jar classpath
+       #
+       # Classpath to give to Java when loading the StanfordNLP jars.
+       var java_cp: String
+
+       # Port the Java server will listen on
+       var port: Int
+
+       redef fun main do
+               sys.system "java -mx4g -cp \"{java_cp}\" edu.stanford.nlp.pipeline.StanfordCoreNLPServer -port {port.to_s} -timeout 15000"
+               return null
+       end
+end
+
+# A NLPProcessor using a NLPServer as backend
+class NLPClient
+       super NLPProcessor
+
+       # Base uri of the NLP server API
+       #
+       # For examples "http://localhost:9000" or "https://myserver.com"
+       var api_uri: String
+
+       # Annotators to use
+       #
+       # The specified annotators must exist on the server.
+       #
+       # Defaults are: `tokenize`, `ssplit`, `pos` and `lemma`.
+       var annotators: Array[String] = ["tokenize", "ssplit", "pos", "lemma"] is writable
+
+       # Language to process
+       #
+       # The language must be available on the server.
+       #
+       # Default is `en`.
+       var language = "en" is writable
+
+       # Output format to ask.
+       #
+       # Only `xml` is implemented at the moment.
+       private var format = "xml"
+
+       # API uri used to build curl POST requests
+       fun post_uri: String do
+               return "{api_uri}/?properties=%7B%22annotators%22%3A%20%22tokenize%2Cssplit%2Cpos%2clemma%22%2C%22outputFormat%22%3A%22{format}%22%7D&pipelineLanguage={language}"
+       end
+
+       redef fun process(string) do
+               var request = new CurlHTTPRequest(post_uri)
+               request.body = string
+               var response = request.execute
+               if response isa CurlResponseSuccess then
+                       if response.status_code != 200 then
+                               print "Error: {response.body_str}"
+                               return new NLPDocument
+                       end
+                       var xml = response.body_str.to_xml
+                       if xml isa XMLError then
+                               print xml
+                       end
+                       return new NLPDocument.from_xml(response.body_str.to_xml.as(XMLDocument))
+               else if response isa CurlResponseFailed then
+                       print "Error: {response.error_msg}"
+                       return new NLPDocument
+               end
+               return new NLPDocument
+       end
 end