query eval scaffolding
	
		
			
	
		
	
	
		
	
		
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				| @ -8,6 +8,8 @@ sitting in a tavern by a fireplace | ||||
| 
 | ||||
| 
 | ||||
| Respond to "What color is your hat?" | ||||
|  - determine sentence function | ||||
|  - determine what is being queried for | ||||
| 
 | ||||
| 
 | ||||
| 
 | ||||
|  | ||||
| @ -1 +1 @@ | ||||
| ▄╘з▓┌кЪДЖЬ▄йЩ▄сЩлЖ╔в╔▓ИКЙG ▄шЁЗаБ÷Т╒(▀лЙ▀Рэ║Р
2 | ||||
| ╪МёКУ╘ТВэТН▒║Х∙╫√=╔в╔▓ИКЙG ▄шЁЗаБ÷Т╒(фБЕ╨≥┘юШ2 | ||||
										
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							| @ -2,3 +2,4 @@ | ||||
| 1,0,0,0,"Hello" | ||||
| 1,0,0,0,"Hi" | ||||
| 1,0,0,0,"Howdy" | ||||
| 0,0,1,0,"What color is your hat?" | ||||
| 
 | 
| @ -2,3 +2,4 @@ | ||||
| 1,0,0,0,"Hello" | ||||
| 1,0,0,0,"Hi" | ||||
| 1,0,0,0,"Howdy" | ||||
| 0,0,1,0,"What color is your hat?" | ||||
| 
 | 
| @ -27,6 +27,8 @@ public class AgentLoop { | ||||
|         try (Scanner scan = new Scanner(System.in)) { | ||||
|             String prompt = ""; | ||||
| 
 | ||||
|             System.out.println("Agent is ready.."); | ||||
| 
 | ||||
|             //actual main loop | ||||
|             while(running){ | ||||
| 
 | ||||
|  | ||||
| @ -3,6 +3,7 @@ package org.studiorailgun.conversation.evaluators; | ||||
| import org.studiorailgun.conversation.categorization.SentenceFunctionCategorizor; | ||||
| import org.studiorailgun.conversation.evaluators.goal.GoalEval; | ||||
| import org.studiorailgun.conversation.evaluators.greet.GreetingEval; | ||||
| import org.studiorailgun.conversation.evaluators.query.QueryEval; | ||||
| import org.studiorailgun.conversation.evaluators.synthesis.ResponseEval; | ||||
| import org.studiorailgun.conversation.tracking.Conversation; | ||||
| import org.studiorailgun.conversation.tracking.Quote; | ||||
| @ -25,9 +26,12 @@ public class EvaluationTree { | ||||
|             case UTILITY: { | ||||
|                 GreetingEval.evaluate(conversation, quote); | ||||
|             } break; | ||||
|             default: { | ||||
| 
 | ||||
|             case QUERY: { | ||||
|                 QueryEval.evaluate(conversation, quote); | ||||
|             } break; | ||||
|             default: { | ||||
|                 throw new UnsupportedOperationException("Unsupported quote function: " + quote.getFunction()); | ||||
|             } | ||||
|         } | ||||
| 
 | ||||
|         //evaluate the AI's current goal in the conversation | ||||
|  | ||||
| @ -0,0 +1,20 @@ | ||||
| package org.studiorailgun.conversation.evaluators.query; | ||||
| 
 | ||||
| import org.studiorailgun.conversation.tracking.Conversation; | ||||
| import org.studiorailgun.conversation.tracking.Quote; | ||||
| 
 | ||||
| /** | ||||
|  * Evaluates queries | ||||
|  */ | ||||
| public class QueryEval { | ||||
|      | ||||
|     /** | ||||
|      * Evaluates a quote | ||||
|      * @param conversation The conversation | ||||
|      * @param quote The quote | ||||
|      */ | ||||
|     public static void evaluate(Conversation conversation, Quote quote){ | ||||
|         System.out.println("Is a query!"); | ||||
|     } | ||||
| 
 | ||||
| } | ||||
| @ -19,7 +19,11 @@ public class ResponseEval { | ||||
|         switch(conversation.getGoalData().getGoal()){ | ||||
|             case GREET: { | ||||
|                 response = GreetingEval.constructGreeting(conversation); | ||||
|                 conversation.getGreetingData().getHaveGreeted().add(conversation.getSelf()); | ||||
|             } break; | ||||
|             default: { | ||||
|                 throw new UnsupportedOperationException("Unsupported conversation goal! " + conversation.getGoalData().getGoal()); | ||||
|             } | ||||
|         } | ||||
|         return response; | ||||
|     } | ||||
|  | ||||
| @ -150,15 +150,15 @@ model.evaluate(npTestData,npTestLabel) | ||||
| 
 | ||||
| 
 | ||||
| # predict | ||||
| predictTargetRaw: Tensor = tf.constant(['Hello']) | ||||
| npPredict: npt.NDArray = np.array(predictTargetRaw, dtype=object) | ||||
| print("Prediction test..") | ||||
| result: list[int] = model.predict(predictTargetRaw) | ||||
| print("predict result:") | ||||
| print(predictTargetRaw) | ||||
| print(result) | ||||
| print(train_data) | ||||
| print(train_labels) | ||||
| # predictTargetRaw: Tensor = tf.constant(['Hello']) | ||||
| # npPredict: npt.NDArray = np.array(predictTargetRaw, dtype=object) | ||||
| # print("Prediction test..") | ||||
| # result: list[int] = model.predict(predictTargetRaw) | ||||
| # print("predict result:") | ||||
| # print(predictTargetRaw) | ||||
| # print(result) | ||||
| # print(train_data) | ||||
| # print(train_labels) | ||||
| 
 | ||||
| 
 | ||||
| 
 | ||||
|  | ||||
| @ -18,7 +18,7 @@ public class GreetingTests { | ||||
|          | ||||
|         ConvAI.simFrame("Hello"); | ||||
| 
 | ||||
|         assertEquals(Globals.conversation.getGreetingData().getHaveGreeted().size(), 1); | ||||
|         assertNotEquals(Globals.conversation.getGreetingData().getHaveGreeted().size(), 0); | ||||
|     } | ||||
| 
 | ||||
|     @Test | ||||
|  | ||||
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