Update service.py

service.py

@@ -9,7 +9,7 @@ import json
 load_dotenv()
 
 # Access environment variables
-API_KEY = os.environ['CHAT_GPT_KEY']
+API_KEY = os.environ['openAI_key']
 
 class Stage(Enum):
     INITIAL_ASSESSMENT = "Initial Assessment"
@@ -29,12 +29,13 @@ class GPT_Service:
         self.base_url = 'https://api.openai.com/v1/chat/completions'
 
     def request_gpt_for_response(self, system_prompt, userPrompt):
+        print(f"System Prompt: {system_prompt}\n user Prompt: {userPrompt}\n")
         headers = {
             'Content-Type': 'application/json',
             'Authorization': f'Bearer {self.api_key}'
         }
         data = {
-            'model': 'gpt-3.5-turbo-1106',
+            'model': 'gpt-4-turbo',
             'temperature': 0.3,
             'messages': [
                 {
@@ -64,22 +65,75 @@ class GPT_Service:
         {f"Patient has the following medical history: {medicalHistory}" if medicalHistory is not None and medicalHistory != ""
         else ""}
         """
-        print(patientData)
         return patientData
     
-    def processOutputResults(self,jsonOutput):
+    def formulateUserPromptForDetailAssessment(self, rawPatientInformation, medicalHistory):
+        patientData= f"""
+        Sentences: {rawPatientInformation}.
+        {f"Patient has the following medical history: {medicalHistory}" if medicalHistory is not None and medicalHistory != ""
+        else ""}
+        """
+        return patientData
+    
+    def processOutputResults(self, jsonOutput):
         preprocessed_json_string = jsonOutput.replace('\n', '')
         data = json.loads(preprocessed_json_string)
-        variants = [value for value in data.values()]
-        # Fetch first three items from the array or pad with empty strings if not enough items are available
-        paddedVariants = variants[:3] + [''] * (3 - len(variants))
-        return paddedVariants
+        result_list = []
+        for key, value in data.items():
+            for variant, sentence in value.items():
+                result_list.append(sentence)
+
+        return result_list
 
     def getInitialAssessment(self, keywords,medicalHistory):
         userPrompt= self.formulateUserPrompt(Stage.INITIAL_ASSESSMENT.value,keywords,medicalHistory)
         response= self.request_gpt_for_response(Prompts.INITIAL_ASSESSMENT_PROMPT.value,userPrompt)
         return self.processOutputResults(response)
+    
+    def getShortTermGoals(self, keywords,medicalHistory):
+        userPrompt= self.formulateUserPrompt(Stage.SHORT_TERM_GOALS.value,keywords,medicalHistory)
+        response =  self.request_gpt_for_response(Prompts.SHORT_TERM_GOALS_PROMPT.value,userPrompt)
+        return self.processOutputResults(response)
+
+    def getLongTermGoals(self, keywords,medicalHistory):
+        userPrompt= self.formulateUserPrompt(Stage.LONG_TERM_GOALS.value,keywords,medicalHistory)
+        response = self.request_gpt_for_response(Prompts.LONG_TERM_GOALS_PROMPT.value,userPrompt)
+        return self.processOutputResults(response)
+    
+    def getRecommendation(self, keywords, medicalHistory):
+        userPrompt= self.formulateUserPrompt(Stage.RECOMMENDATION.value,keywords,medicalHistory)
+        response= self.request_gpt_for_response(Prompts.RECOMMENDATION_PROMPT.value,userPrompt)
+        return self.processOutputResults(response)
+    
+    # Detail Patient Evaluation Prompt
+
+    def getDetailInitialAssessment(self,medicalHistory,sentences):
+        rawPatientAssessment = " ".join(sentences)
+        userPrompt= self.formulateUserPromptForDetailAssessment(rawPatientAssessment,medicalHistory)
+        response= self.request_gpt_for_response(Prompts.DETAIL_PATIENT_ASSESSMENT_INITIAL_ASSESSMENT_GOALS.value,userPrompt)
+        return response
+    
+    def getDetailShortTermGoals(self,medicalHistory,sentences):
+        rawPatientAssessment = " ".join(sentences)
+        userPrompt= self.formulateUserPromptForDetailAssessment(rawPatientAssessment,medicalHistory)
+        response= self.request_gpt_for_response(Prompts.DETAIL_PATIENT_ASSESSMENT_SHORT_TERM_GOALS.value,userPrompt)
+        return response
+
+    def getDetailLongTermGoals(self,medicalHistory,sentences):
+        rawPatientAssessment = " ".join(sentences)
+        userPrompt= self.formulateUserPromptForDetailAssessment(rawPatientAssessment,medicalHistory)
+        response= self.request_gpt_for_response(Prompts.DETAIL_PATIENT_ASSESSMENT_LONG_TERM_GOALS.value,userPrompt)
+        return response
+    
+    def getDetailRecommendation(self, medicalHistory,sentences):
+        rawPatientAssessment = " ".join(sentences)
+        userPrompt= self.formulateUserPromptForDetailAssessment(rawPatientAssessment,medicalHistory)
+        response= self.request_gpt_for_response(Prompts.DETAIL_PATIENT_ASSESSMENT_RECOMMENDATION_GOALS.value,userPrompt)
+        return response
+    
 
+    # Extra helper functions
+    
     def getFollowUpAssessment(self, keywords, medicalHistory):
         userPrompt= self.formulateUserPrompt(Stage.FOLLOWUP_ASSESSMENT.value,keywords,medicalHistory)
         response= self.request_gpt_for_response(Prompts.FOLLOWUP_ASSESSMENT_PROMPT.value,userPrompt)
@@ -90,11 +144,6 @@ class GPT_Service:
         response= self.request_gpt_for_response(Prompts.EVALUATION_PROMPT.value,userPrompt)
         return self.processOutputResults(response)
     
-    def getRecommendation(self, keywords, medicalHistory):
-        userPrompt= self.formulateUserPrompt(Stage.RECOMMENDATION.value,keywords,medicalHistory)
-        response= self.request_gpt_for_response(Prompts.RECOMMENDATION_PROMPT.value,userPrompt)
-        return self.processOutputResults(response)
-
     def getDetailedEvaluation(self, keywords,medicalHistory):
         userPrompt= self.formulateUserPrompt(Stage.DETAILED_EVALUATION.value,keywords,medicalHistory)
         response= self.request_gpt_for_response(Prompts.DETAILED_EVALUATION_PROMPT.value,userPrompt)
@@ -108,14 +157,4 @@ class GPT_Service:
     def getDischargeSummary(self, keywords,medicalHistory):
         userPrompt= self.formulateUserPrompt(Stage.DISCHARGE_SUMMARY.value,keywords,medicalHistory)
         response = self.request_gpt_for_response(Prompts.DISCHARGE_SUMMARY_PROMPT.value,userPrompt)
-        return self.processOutputResults(response)
-    
-    def getShortTermGoals(self, keywords,medicalHistory):
-        userPrompt= self.formulateUserPrompt(Stage.SHORT_TERM_GOALS.value,keywords,medicalHistory)
-        response =  self.request_gpt_for_response(Prompts.SHORT_TERM_GOALS_PROMPT.value,userPrompt)
-        return self.processOutputResults(response)
-    
-    def getLongTermGoals(self, keywords,medicalHistory):
-        userPrompt= self.formulateUserPrompt(Stage.LONG_TERM_GOALS.value,keywords,medicalHistory)
-        response = self.request_gpt_for_response(Prompts.LONG_TERM_GOALS_PROMPT.value,userPrompt)
         return self.processOutputResults(response)