Update app.py

app.py

@@ -127,31 +127,49 @@ def process_input():
 
 
 def get_case_summary(conv_detail):
-    chatresponse_desc = openai.ChatCompletion.create(
-    model="gpt-3.5-turbo",
-    temperature=0,
-    max_tokens=128,
-    messages=[
-        {"role": "system", "content": "You are an Text Summarizer."},
-        {"role": "user", "content": "You need to summarise the conversation between an agent and customer mentioned below. Remember to keep the Product Name, Customer Tone and other key elements from the convsersation"},
-        {"role": "user", "content": conv_detail}
-    ]
+    #chatresponse_desc = openai.ChatCompletion.create(
+    #model="gpt-3.5-turbo",
+    #temperature=0,
+    #max_tokens=128,
+    #messages=[
+    #    {"role": "system", "content": "You are an Text Summarizer."},
+    #    {"role": "user", "content": "You need to summarise the conversation between an agent and customer mentioned below. Remember to keep the Product Name, Customer Tone and other key elements from the convsersation"},
+    #    {"role": "user", "content": conv_detail}
+    #]
+    #)
+    #case_desc = chatresponse_desc.choices[0].message.content
+    chatresponse_desc = completion.create( 
+    model = 'text-davinci-003',
+    prompt = 'Summarise the conversation between an agent and customer.Remember to keep the Product Name, Customer Tone and other key elements from the convsersation.Here is the conversation: ' + conv_detail,
+    temperature = 0,
+    top_p =1,
+    best_of=1,
+    max_tokens=256
     )
-    case_desc = chatresponse_desc.choices[0].message.content
+    case_desc = chatresponse_desc.choices[0].text.strip()
     return case_desc
 
 def get_case_subject(conv_detail):     
-    chatresponse_subj = openai.ChatCompletion.create(
-    model="gpt-3.5-turbo",
-    temperature=0,
-    max_tokens=32,
-    messages=[
-        {"role": "system", "content": "You are an Text Summarizer."},
-        {"role": "user", "content": "You need to summarise the conversation between an agent and customer in 15 words mentioned below for case subject."},
-        {"role": "user", "content": conv_detail}
-    ]
+    #chatresponse_subj = openai.ChatCompletion.create(
+    #model="gpt-3.5-turbo",
+    #temperature=0,
+    #max_tokens=32,
+    #messages=[
+    #    {"role": "system", "content": "You are an Text Summarizer."},
+    #    {"role": "user", "content": "You need to summarise the conversation between an agent and customer in 15 words mentioned below for case subject."},
+    #    {"role": "user", "content": conv_detail}
+    #]
+    #)
+    #case_subj = chatresponse_subj.choices[0].message.content
+    chatresponse_subj = completion.create( 
+    model = 'text-davinci-003',
+    prompt = 'Summarise the conversation between an agent and customer in 15 words mentioned below for Case Subject. Here is the conversation: ' + conv_detail,
+    temperature = 0,
+    top_p =1,
+    best_of=1,
+    max_tokens=256
     )
-    case_subj = chatresponse_subj.choices[0].message.content
+    case_subj = chatresponse_subj.choices[0].text.strip()
     return case_subj
 
 # Define a function to create a case record in Salesforce