Initial mock interview concept

app.py

@@ -1,46 +1,99 @@
 import os
+import urllib
+from time import sleep
+import urllib.request
+
 import gradio as gr
 import openai
+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_json(uploaded_file, assistant_name,  assistant_message):
-    client = openai.OpenAI(api_key=os.environ["OPENAI_API_KEY"])
-    # Check if a file was uploaded
-    print(uploaded_file)
-    df = open(uploaded_file, "rb")
-    file = client.files.create(file=df,
-                               purpose='assistants')
+def create_assistant(job_role, company):
+    file_ids = create_files(company)
 
     assistant = client.beta.assistants.create(
-        name=assistant_name,
-        instructions=assistant_message,
-        model="gpt-4-0125-preview",
+        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
+                'type': 'retrieval'  # This adds the knowledge base as a tool
             }
         ],
-        file_ids=[file.id])
+        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    
+
 # Creating the Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("## To create an OpenAI Assistant please fill in the following sections. Upload a file to give the Assistant knowledge and a focus on something outside of it's normal training. Then add an assistant name and message. The Assistant message should guide the model into in a role. An example would be, You are a helpful Asssitant who is knowledgable in the field of...")
-    gr.Markdown("## After creating the ID head to [OpenAI_Assistant_Chat](https://huggingface.co/spaces/jadend/OpenAI_Assistant_Chat).")
-    with gr.Row():
-        file_input = gr.File(label="Upload your file", type="filepath")
-        assistant_name = gr.Textbox(label="The Assistant's Name")
-        assistant_message = gr.Textbox(label="Assistant Message")
-    generate_button = gr.Button("Generate Your Assistant ID") 
-    output_id = gr.Textbox(label="Your Asssistant ID", value="")
-    
-    generate_button.click(
-        fn=create_assistant_json,
-        inputs=[file_input, assistant_name, assistant_message],
-        outputs=output_id
-    )
+    chatbot = gr.ChatInterface(
+        chat,
+        additional_inputs=[
+            gr.Textbox(label='Job Role'),
+            gr.Textbox(label='Company')
+        ], 
+        title='I am your AI mock interviewer.', 
+        description='Make your selections above to configure me.',
+        theme='soft',
+        fill_height=True,
+        retry_btn=None,
+        undo_btn=None,
+        clear_btn='Clear').queue()
 
-if __name__ == "__main__":
+if __name__ == '__main__':
     demo.launch().queue()

requirements.txt

@@ -1,2 +1,3 @@
 openai==1.16.2
-gradio==4.25.0
+gradio==4.25.0
+python-dotenv==1.0.1