Refactor

.env.example

@@ -0,0 +1 @@
+OPENAI_API_KEY=PASTE-KEY-HERE

app.py

@@ -9,91 +9,102 @@ from dotenv import load_dotenv
 
 load_dotenv()
 
-client = openai.OpenAI(api_key=os.environ['OPENAI_API_KEY'])
-
-def create_files(company):
-    if company.lower() == 'amazon':
-        url = 'https://www.aboutamazon.com/about-us/leadership-principles'
-        filename = 'leadership_principles.html'
-    else:
-        return []
-    
-    filename, headers = urllib.request.urlretrieve(url, filename)
-    with open(filename, 'rb') as file:
-        assistant_file = client.files.create(file=file, purpose='assistants')
-        file_ids = [assistant_file.id]
-    os.remove(filename)
-    return file_ids
-
-# Assistant Creation function
-def create_assistant(job_role, company):
-    file_ids = create_files(company)
-
-    assistant = client.beta.assistants.create(
-        name='Mock Interviewer',
-        instructions=f'You are an AI mock interviewer for {job_role} roles at {company}. If you have been provided a file, use it as an interview guide.',
-        model='gpt-4-0125-preview',
-        tools=[
-            {
-                'type': 'retrieval'  # This adds the knowledge base as a tool
-            }
-        ],
-        file_ids=file_ids)
-    
-    return assistant.id
-
-def chat(usr_message, history, job_role, company):
-    print('Started function')
-    thread = client.beta.threads.create()
-    user_input = usr_message
-
-    # TODO: this creates the assistant every single chat interaction, need to 
-    # cache this if role/company haven't changed
-    assistant_id = create_assistant(job_role, company)
-
-    # Add the user's message to the thread
-    client.beta.threads.messages.create(thread_id=thread.id,
-                                        role="user",
-                                        content=user_input)
-    print('Client made')
-    # Run the Assistant
-    run = client.beta.threads.runs.create(thread_id=thread.id,
-                                            assistant_id=assistant_id)
-    print('Run created')
-
-    # Check if the Run requires action (function call)
-    while True:
-        run_status = client.beta.threads.runs.retrieve(thread_id=thread.id,
-                                                    run_id=run.id)
-        print(f"Run status: {run_status.status}")
-        if run_status.status == 'completed':
-            break
-
-        sleep(1)  # Wait for a second before checking again
-
-    # Retrieve and return the latest message from the assistant
-    messages = client.beta.threads.messages.list(thread_id=thread.id)
-    response = messages.data[0].content[0].text.value
-
-    print(f"Assistant response: {response}")  # Debugging line
-    #return json.dumps({"response": response})
-    yield response    
+class MockInterviewer:
+
+    def __init__(self):
+        self.client = openai.OpenAI(api_key=os.environ['OPENAI_API_KEY'])
+        self.job_role = ''
+        self.company = ''
+        self.assistant_id = ''
+
+    def create_files(self, company):
+        if company.lower() == 'amazon':
+            url = 'https://www.aboutamazon.com/about-us/leadership-principles'
+            filename = 'leadership_principles.html'
+        else:
+            return []
+        
+        filename, headers = urllib.request.urlretrieve(url, filename)
+        with open(filename, 'rb') as file:
+            assistant_file = self.client.files.create(file=file, purpose='assistants')
+            file_ids = [assistant_file.id]
+        os.remove(filename)
+        return file_ids
+
+    def init_assistant(self, job_role, company):
+        if not job_role and not company:
+            raise gr.Error('Job Role and Company are requried fields.')
+        if not job_role:
+            raise gr.Error('Job Role is a required field.')
+        if not company:
+            raise gr.Error('Company is a required field.')
+
+        if job_role != self.job_role or company != self.company:
+            file_ids = self.create_files(company)
+
+            assistant = self.client.beta.assistants.create(
+                name='Mock Interviewer',
+                instructions=f'You are an AI mock interviewer for {job_role} roles at {company}. If you have been provided a file, use it as an interview guide.',
+                model='gpt-4-0125-preview',
+                tools=[
+                    {
+                        'type': 'retrieval'  # This adds the knowledge base as a tool
+                    }
+                ],
+                file_ids=file_ids)
+            
+            self.assistant_id = assistant.id
+
+    def chat(self, usr_message, history, job_role, company):
+        print('Started function')
+        thread = self.client.beta.threads.create()
+        user_input = usr_message['text']
+
+        self.init_assistant(job_role, company)
+
+        # Add the user's message to the thread
+        self.client.beta.threads.messages.create(thread_id=thread.id,
+                                                 role="user",
+                                                 content=user_input)
+        print('Client made')
+        # Run the Assistant
+        run = self.client.beta.threads.runs.create(thread_id=thread.id,
+                                                   assistant_id=self.assistant_id)
+        print('Run created')
+
+        # Check if the Run requires action (function call)
+        while True:
+            run_status = self.client.beta.threads.runs.retrieve(thread_id=thread.id,
+                                                                run_id=run.id)
+            print(f"Run status: {run_status.status}")
+            if run_status.status == 'completed':
+                break
+
+            sleep(1)  # Wait for a second before checking again
+
+        # Retrieve and return the latest message from the assistant
+        messages = self.client.beta.threads.messages.list(thread_id=thread.id)
+        response = messages.data[0].content[0].text.value
+
+        print(f"Assistant response: {response}")  # Debugging line
+        #return json.dumps({"response": response})
+        yield response    
 
 # Creating the Gradio interface
 with gr.Blocks() as demo:
+    mock_interviewer = MockInterviewer()
+
     chatbot = gr.ChatInterface(
-        chat,
+        mock_interviewer.chat,
         additional_inputs=[
             gr.Textbox(label='Job Role'),
             gr.Textbox(label='Company')
         ], 
-        title='I am your AI mock interviewer.', 
+        title='I am your AI mock interviewer', 
         description='Make your selections above to configure me.',
-        theme='soft',
-        fill_height=True,
+        multimodal=True,
         retry_btn=None,
-        undo_btn=None,
-        clear_btn='Clear').queue()
+        undo_btn=None).queue()
 
 if __name__ == '__main__':
     demo.launch().queue()