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Update service.py (#7)
Browse files- Update service.py (2492d3e55342403f24d69c6db0e69fd5a2f23976)
Co-authored-by: Umar <umar-ts@users.noreply.huggingface.co>
- service.py +62 -23
service.py
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@@ -9,7 +9,7 @@ import json
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load_dotenv()
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# Access environment variables
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API_KEY = os.environ['
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class Stage(Enum):
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INITIAL_ASSESSMENT = "Initial Assessment"
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@@ -29,12 +29,13 @@ class GPT_Service:
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self.base_url = 'https://api.openai.com/v1/chat/completions'
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def request_gpt_for_response(self, system_prompt, userPrompt):
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headers = {
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'Content-Type': 'application/json',
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'Authorization': f'Bearer {self.api_key}'
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}
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data = {
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'model': 'gpt-
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'temperature': 0.3,
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'messages': [
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{
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@@ -64,22 +65,75 @@ class GPT_Service:
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{f"Patient has the following medical history: {medicalHistory}" if medicalHistory is not None and medicalHistory != ""
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else ""}
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"""
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print(patientData)
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return patientData
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def
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preprocessed_json_string = jsonOutput.replace('\n', '')
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data = json.loads(preprocessed_json_string)
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def getInitialAssessment(self, keywords,medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.INITIAL_ASSESSMENT.value,keywords,medicalHistory)
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response= self.request_gpt_for_response(Prompts.INITIAL_ASSESSMENT_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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def getFollowUpAssessment(self, keywords, medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.FOLLOWUP_ASSESSMENT.value,keywords,medicalHistory)
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response= self.request_gpt_for_response(Prompts.FOLLOWUP_ASSESSMENT_PROMPT.value,userPrompt)
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@@ -90,11 +144,6 @@ class GPT_Service:
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response= self.request_gpt_for_response(Prompts.EVALUATION_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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def getRecommendation(self, keywords, medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.RECOMMENDATION.value,keywords,medicalHistory)
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response= self.request_gpt_for_response(Prompts.RECOMMENDATION_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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def getDetailedEvaluation(self, keywords,medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.DETAILED_EVALUATION.value,keywords,medicalHistory)
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response= self.request_gpt_for_response(Prompts.DETAILED_EVALUATION_PROMPT.value,userPrompt)
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@@ -108,14 +157,4 @@ class GPT_Service:
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def getDischargeSummary(self, keywords,medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.DISCHARGE_SUMMARY.value,keywords,medicalHistory)
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response = self.request_gpt_for_response(Prompts.DISCHARGE_SUMMARY_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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def getShortTermGoals(self, keywords,medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.SHORT_TERM_GOALS.value,keywords,medicalHistory)
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response = self.request_gpt_for_response(Prompts.SHORT_TERM_GOALS_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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def getLongTermGoals(self, keywords,medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.LONG_TERM_GOALS.value,keywords,medicalHistory)
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response = self.request_gpt_for_response(Prompts.LONG_TERM_GOALS_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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load_dotenv()
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# Access environment variables
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API_KEY = os.environ['openAI_key']
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class Stage(Enum):
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INITIAL_ASSESSMENT = "Initial Assessment"
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self.base_url = 'https://api.openai.com/v1/chat/completions'
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def request_gpt_for_response(self, system_prompt, userPrompt):
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print(f"System Prompt: {system_prompt}\n user Prompt: {userPrompt}\n")
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headers = {
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'Content-Type': 'application/json',
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'Authorization': f'Bearer {self.api_key}'
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}
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data = {
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'model': 'gpt-4-turbo',
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'temperature': 0.3,
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'messages': [
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{
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{f"Patient has the following medical history: {medicalHistory}" if medicalHistory is not None and medicalHistory != ""
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else ""}
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"""
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return patientData
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def formulateUserPromptForDetailAssessment(self, rawPatientInformation, medicalHistory):
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patientData= f"""
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Sentences: {rawPatientInformation}.
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{f"Patient has the following medical history: {medicalHistory}" if medicalHistory is not None and medicalHistory != ""
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else ""}
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"""
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return patientData
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def processOutputResults(self, jsonOutput):
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preprocessed_json_string = jsonOutput.replace('\n', '')
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data = json.loads(preprocessed_json_string)
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result_list = []
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for key, value in data.items():
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for variant, sentence in value.items():
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result_list.append(sentence)
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return result_list
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def getInitialAssessment(self, keywords,medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.INITIAL_ASSESSMENT.value,keywords,medicalHistory)
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response= self.request_gpt_for_response(Prompts.INITIAL_ASSESSMENT_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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def getShortTermGoals(self, keywords,medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.SHORT_TERM_GOALS.value,keywords,medicalHistory)
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response = self.request_gpt_for_response(Prompts.SHORT_TERM_GOALS_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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def getLongTermGoals(self, keywords,medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.LONG_TERM_GOALS.value,keywords,medicalHistory)
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response = self.request_gpt_for_response(Prompts.LONG_TERM_GOALS_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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def getRecommendation(self, keywords, medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.RECOMMENDATION.value,keywords,medicalHistory)
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response= self.request_gpt_for_response(Prompts.RECOMMENDATION_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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# Detail Patient Evaluation Prompt
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def getDetailInitialAssessment(self,medicalHistory,sentences):
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rawPatientAssessment = " ".join(sentences)
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userPrompt= self.formulateUserPromptForDetailAssessment(rawPatientAssessment,medicalHistory)
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response= self.request_gpt_for_response(Prompts.DETAIL_PATIENT_ASSESSMENT_INITIAL_ASSESSMENT_GOALS.value,userPrompt)
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return response
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def getDetailShortTermGoals(self,medicalHistory,sentences):
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rawPatientAssessment = " ".join(sentences)
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userPrompt= self.formulateUserPromptForDetailAssessment(rawPatientAssessment,medicalHistory)
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response= self.request_gpt_for_response(Prompts.DETAIL_PATIENT_ASSESSMENT_SHORT_TERM_GOALS.value,userPrompt)
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return response
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def getDetailLongTermGoals(self,medicalHistory,sentences):
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rawPatientAssessment = " ".join(sentences)
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userPrompt= self.formulateUserPromptForDetailAssessment(rawPatientAssessment,medicalHistory)
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response= self.request_gpt_for_response(Prompts.DETAIL_PATIENT_ASSESSMENT_LONG_TERM_GOALS.value,userPrompt)
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return response
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def getDetailRecommendation(self, medicalHistory,sentences):
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rawPatientAssessment = " ".join(sentences)
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userPrompt= self.formulateUserPromptForDetailAssessment(rawPatientAssessment,medicalHistory)
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response= self.request_gpt_for_response(Prompts.DETAIL_PATIENT_ASSESSMENT_RECOMMENDATION_GOALS.value,userPrompt)
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return response
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# Extra helper functions
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def getFollowUpAssessment(self, keywords, medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.FOLLOWUP_ASSESSMENT.value,keywords,medicalHistory)
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response= self.request_gpt_for_response(Prompts.FOLLOWUP_ASSESSMENT_PROMPT.value,userPrompt)
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response= self.request_gpt_for_response(Prompts.EVALUATION_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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def getDetailedEvaluation(self, keywords,medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.DETAILED_EVALUATION.value,keywords,medicalHistory)
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response= self.request_gpt_for_response(Prompts.DETAILED_EVALUATION_PROMPT.value,userPrompt)
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def getDischargeSummary(self, keywords,medicalHistory):
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userPrompt= self.formulateUserPrompt(Stage.DISCHARGE_SUMMARY.value,keywords,medicalHistory)
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response = self.request_gpt_for_response(Prompts.DISCHARGE_SUMMARY_PROMPT.value,userPrompt)
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return self.processOutputResults(response)
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