Update app.py

app.py

@@ -1,5 +1,5 @@
 import os
-import openai
+from openai import AzureOpenAI
 import PyPDF2
 import gradio as gr
 import docx
@@ -8,7 +8,10 @@ import re
 
 class Resume_Overall:
     def __init__(self):
-        pass
+        self.client = AzureOpenAI(api_key=os.getenv("AZURE_OPENAI_KEY"),  
+                    api_version="2023-07-01-preview",
+                    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
+                     )
 
     def extract_text_from_file(self,file_path):
         # Get the file extension
@@ -48,17 +51,22 @@ class Resume_Overall:
         resume = self.extract_text_from_file(resume_path)
 
 
+        
         # Define the prompt or input for the model
-        prompt = f"""Analyze the resume to generate online courses with website links to improve skills following resume delimitted by triple backticks. Generate atmost five courses.
+        conversation = [
+            {"role": "system", "content": "You are a Resume Assistant."},
+            {"role": "user", "content": f"""Analyze the resume to generate online courses with website links to improve skills following resume delimitted by triple backticks. Generate atmost five courses.
                      result format should be:
                      course:[course].
                      website link:[website link]
                      ```{resume}```
-                  """
+                  """}
+        ]
+
 
         # Generate a response from the GPT-3 model
-        response = openai.Completion.create(
-            engine='text-davinci-003',
+        chat_completion = self.client.chat.completions.create(
+            model = "ChatGPT",
             prompt=prompt,
             max_tokens=200,
             temperature=0,
@@ -67,7 +75,7 @@ class Resume_Overall:
         )
 
         # Extract the generated text from the API response
-        generated_text = response.choices[0].text.strip()
+        generated_text = chat_completion.choices[0].message.content
 
         return generated_text
     def summary_response(self,resume_path):
@@ -76,13 +84,16 @@ class Resume_Overall:
 
 
         # Define the prompt or input for the model
-        prompt = f"""Analyze the resume to write the summary for following resume delimitted by triple backticks.
+        conversation = [
+            {"role": "system", "content": "You are a Resume Summarizer."},
+            {"role": "user", "content": f"""Analyze the resume to write the summary for following resume delimitted by triple backticks.
                      ```{resume}```
-                  """
+                  """}
+        ]
 
         # Generate a response from the GPT-3 model
-        response = openai.Completion.create(
-            engine='text-davinci-003',
+        chat_completion = self.client.chat.completions.create(
+            model = "ChatGPT",
             prompt=prompt,
             max_tokens=200,
             temperature=0,
@@ -91,7 +102,7 @@ class Resume_Overall:
         )
 
         # Extract the generated text from the API response
-        generated_text = response.choices[0].text.strip()
+        generated_text = chat_completion.choices[0].message.content
 
         return generated_text
   
@@ -102,13 +113,16 @@ class Resume_Overall:
 
 
         # Define the prompt or input for the model
-        prompt = f"""Find Education Gaps in given resume. Find Skills in resume.
+        conversation = [
+            {"role": "system", "content": "You are a Resume Assistant."},
+            {"role": "user", "content": f"""Find Education Gaps in given resume. Find Skills in resume.
                       ```{resume}```
-                  """
+                  """}
+        ]
 
         # Generate a response from the GPT-3 model
-        response = openai.Completion.create(
-            engine='text-davinci-003',  # Choose the GPT-3 engine you want to use
+        chat_completion = self.client.chat.completions.create(
+            model = "ChatGPT",  # Choose the GPT-3 engine you want to use
             prompt=prompt,
             max_tokens=100,  # Set the maximum number of tokens in the generated response
             temperature=0,  # Controls the randomness of the output. Higher values = more random, lower values = more focused
@@ -117,21 +131,25 @@ class Resume_Overall:
         )
 
         # Extract the generated text from the API response
-        generated_text = response.choices[0].text.strip()
+        generated_text = chat_completion.choices[0].message.content
 
         return generated_text
 
     def _generate_job_list(self, resume: str) -> str:
-        prompt = f"List out perfect job roles for based on resume informations:{resume}"
-        response = openai.Completion.create(
-            engine='text-davinci-003',
+        conversation = [
+            {"role": "system", "content": "You are a Resume Assistant."},
+            {"role": "user", "content": f"List out perfect job roles for based on resume informations:{resume}"}
+        ]
+        
+        chat_completion = self.client.chat.completions.create(
+            model = "ChatGPT", 
             prompt=prompt,
             max_tokens=100,
             temperature=0,
             n=1,
             stop=None,
         )
-        generated_text = response.choices[0].text.strip()
+        generated_text = chat_completion.choices[0].message.content
         return generated_text
 
 
@@ -143,8 +161,9 @@ class Resume_Overall:
 
     def generate_job_description(self, role, experience):
         # Generate a response from the GPT-3 model
-
-        prompt = f"""Your task is generate Job description for this {role} with {experience} years of experience.
+        conversation = [
+            {"role": "system", "content": "You are a Resume Assistant."},
+            {"role": "user", "content": f"""Your task is generate Job description for this {role} with {experience} years of experience.
                     Job Description Must have
                     1. Job Title
                     2. Job Summary : [200 words]
@@ -152,16 +171,18 @@ class Resume_Overall:
                     4. Required Skills : Six Skills
                     5. Qualifications
                   These topics must have in that Generated Job Description.
-                  """
-        response = openai.Completion.create(
-            engine='text-davinci-003',  # Choose the GPT-3 engine you want to use
+                  """}
+        ]
+        
+        chat_completion = self.client.chat.completions.create(
+            model = "ChatGPT",   # Choose the GPT-3 engine you want to use
             prompt=prompt,
             max_tokens=500,  # Set the maximum number of tokens in the generated response
             temperature=0.5,  # Controls the randomness of the output. Higher values = more random, lower values = more focused
         )
 
         # Extract the generated text from the API response
-        generated_text = response.choices[0].text.strip()
+        generated_text = chat_completion.choices[0].message.content
 
         return generated_text  
         
@@ -171,13 +192,17 @@ class Resume_Overall:
 
 
         # Define the prompt or input for the model
-        prompt = f"""Generate interview questions for screening following job_description delimitted by triple backticks. Generate atmost ten questions.
+        conversation = [
+            {"role": "system", "content": "You are a Resume Assistant."},
+            {"role": "user", "content":  f"""Generate interview questions for screening following job_description delimitted by triple backticks. Generate atmost ten questions.
                      ```{job_description}```
-                  """
+                  """}
+        ]
+
 
         # Generate a response from the GPT-3 model
-        response = openai.Completion.create(
-            engine='text-davinci-003',  # Choose the GPT-3 engine you want to use
+        chat_completion = self.client.chat.completions.create(
+            model = "ChatGPT",  # Choose the GPT-3 engine you want to use
             prompt=prompt,
             max_tokens=200,  # Set the maximum number of tokens in the generated response
             temperature=0,  # Controls the randomness of the output. Higher values = more random, lower values = more focused
@@ -186,7 +211,7 @@ class Resume_Overall:
         )
 
         # Extract the generated text from the API response
-        generated_text = response.choices[0].text.strip()
+        generated_text = chat_completion.choices[0].message.content
 
         return generated_text