Integrate elements.

* Move interface to KnowledgeBase object.
 * Connect process and evaluate calls.

naive-nlu/parsing.py

@@ -2,31 +2,29 @@
 
 from functools import reduce
 
-from knowledge_base import KnowledgeBase
 
-
-def make_template(knowledge_base: KnowledgeBase, text, parsed):
+def make_template(knowledge_base, text, parsed):
     tokens = text.split()
+    matcher = list(tokens)
     template = list(parsed)
-    for i in range(len(tokens)):
-        word = tokens[i]
+    for i in range(len(matcher)):
+        word = matcher[i]
         if word in template:
-            print(word, i, template)
             template[template.index(word)] = i
-            print(knowledge_base)
-            tokens[i] = {'groups': set(knowledge_base.knowledge[word]['groups'])}
-    return tokens, template
+            matcher[i] = {
+                'groups': set(knowledge_base.knowledge[word]['groups'])
+            }
+    return tokens, matcher, template
 
 
-def integrate_language(knowledge_base: KnowledgeBase, example):
+def integrate_language(knowledge_base, example):
     text = example["text"].lower()
     parsed = example["parsed"]
-    matcher, result = make_template(knowledge_base, text, parsed)
+    tokens, matcher, result = make_template(knowledge_base, text, parsed)
     print(text)
     print(parsed)
     print()
-    return matcher, result
-
+    return tokens, matcher, result
 
 
 def get_matching(sample, other):
@@ -67,3 +65,15 @@ def reprocess_language_knowledge(knowledge_base, examples):
         print()
     return pattern_examples
 
+
+def get_fit(knowledge, row):
+    for sample, ast in knowledge.trained:
+        if len(sample) != len(row):
+            continue
+
+        if all(map(lambda x: (not isinstance(sample[x], str)
+                              or sample[x] == row[x]),
+                   range(len(sample)))):
+            return sample, ast
+    else:
+        return None