detect response

Author: devvratbhardwaj

aimon/extensions/react.py

@@ -60,35 +60,37 @@ def react(self, user_query, user_instructions,):
 
         detect_response = self.client.inference.detect(body=[aimon_payload])
 
-        for _ in range(self.react_configuration.max_attempts):
+        return detect_response
 
-            failed_instructions = []
-            ## Loop to check for failed instructions
-            for x in detect_response.instruction_adherence['results']:
-                if x['adherence'] == False:
-                    failed_instructions.append(x['instruction'])
+        # for _ in range(self.react_configuration.max_attempts):
 
-            hallucination_score = detect_response.hallucination['score'] 
+        #     failed_instructions = []
+        #     ## Loop to check for failed instructions
+        #     for x in detect_response.instruction_adherence['results']:
+        #         if x['adherence'] == False:
+        #             failed_instructions.append(x['instruction'])
 
-            ## Check whether the hallucination score is greater than the required threshold OR if any of the supplied instructions are not complied with
-            if  self.react_configuration.hallucination_threshold > 0 and \
-                (hallucination_score > self.react_configuration.hallucination_threshold or len(failed_instructions)>0): 
+        #     hallucination_score = detect_response.hallucination['score'] 
+
+        #     ## Check whether the hallucination score is greater than the required threshold OR if any of the supplied instructions are not complied with
+        #     if  self.react_configuration.hallucination_threshold > 0 and \
+        #         (hallucination_score > self.react_configuration.hallucination_threshold or len(failed_instructions)>0): 
 
-                llm_response = self.llm_app(user_query, user_instructions, reprompted_flag=True, hallucination_score=hallucination_score)
+        #         llm_response = self.llm_app(user_query, user_instructions, reprompted_flag=True, hallucination_score=hallucination_score)
 
-                context = self.context_extractor(user_query, user_instructions, llm_response)
+        #         context = self.context_extractor(user_query, user_instructions, llm_response)
 
-                ## Generated text for LLM Response, if the user employs the LlamaIndex framework
-                if llm_response.response or self.react_configuration.framework=="llamaindex":
-                    generated_text = llm_response.response
-                else:
-                    generated_text = llm_response
+        #         ## Generated text for LLM Response, if the user employs the LlamaIndex framework
+        #         if llm_response.response or self.react_configuration.framework=="llamaindex":
+        #             generated_text = llm_response.response
+        #         else:
+        #             generated_text = llm_response
 
-                new_aimon_payload = self.create_payload(context, user_query, user_instructions, generated_text)
+        #         new_aimon_payload = self.create_payload(context, user_query, user_instructions, generated_text)
 
-                detect_response = self.client.inference.detect(body=[new_aimon_payload])
+        #         detect_response = self.client.inference.detect(body=[new_aimon_payload])
 
-        if hallucination_score > self.react_configuration.hallucination_threshold:
-            return f"The generated LLM response, even after {self.react_configuration.max_attempts} attempts of ReAct is still hallucinated. The response: {generated_text}"
+        # if hallucination_score > self.react_configuration.hallucination_threshold:
+        #     return f"The generated LLM response, even after {self.react_configuration.max_attempts} attempts of ReAct is still hallucinated. The response: {generated_text}"
 
-        return generated_text
+        # return generated_text