Update app.py

app.py

@@ -158,14 +158,15 @@ class LangChain_Document_QA:
         except:
           pass
 
-        prompt = f"""Analyse the patient json If asked for information take it from {patient_details}\
-            you first get patient details : <get name,age,gender,contact,address from patient> if not match patient json information start new chat else match patient json information ask previous: <description,symptoms,diagnosis,treatment talk about patient>As an empathic AI Mental Healthcare Doctor Chatbot, provide effective solutions to patients' mental health concerns. \
-            first start the conversation ask existing patient or new patient. if new patient get name,age,gender,contact,address from the patient and start. 
-            if existing customer get name,age,gender,contact,address details and start the chat about existing issues and current issues.
-            if patient say thanking tone message to end the conversation with a thanking greeting when the patient expresses gratitude.  
-              Chat History:['''{history}''']
-              Patient: ['''{text}''']
-              Perform as Mental Healthcare Doctor Chatbot
+        prompt = f"""Analyse the patient json If asked for information take it from {patient_details} \
+            you first get patient details : <get name,age,gender,contact,address from patient> if not match patient json information start new chat else match patient \
+            json information ask previous: <description,symptoms,diagnosis,treatment talk about patient> As an empathic AI Mental Healthcare Doctor Chatbot, provide effective solutions to patients' mental health concerns. \
+            first start the conversation ask existing patient or new patient. if new patient get name,age,gender,contact,address from the patient and start. \
+            if existing customer get name,age,gender,contact,address details and start the chat about existing issues and current issues. \
+            if patient say thanking tone message to end the conversation with a thanking greeting when the patient expresses gratitude. \
+            Chat History:['''{history}'''] 
+            Patient: ['''{text}''']
+            Perform as Mental Healthcare Doctor Chatbot
                  """
         response = openai.Completion.create(
             model="text-davinci-003",