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import time
import os
import gradio as gr
from openai import OpenAI
client = OpenAI(api_key=os.environ['OPENAI_API_KEY'])
# Initialize the client
# Set your OpenAI API key
'''file = client.files.create(
file=open("file.extension", "rb"),
purpose='assistants'
)'''
# Step 1: Create an Assistant
assistant = client.beta.assistants.create(
name="SAFe Specialist",
instructions="As a Scaled Agile Framework (SAFe) Specialist, you guide organizations from a siloed project model \
to an integrated product mode, focusing on humanitarian organizations offering digital solutions. You understand \
their unique context by asking about current practices and challenges, using direct questions and multiple-choice \
options. You tailor responses for a smooth transition, emphasizing core SAFe principles and addressing challenges \
like cultural resistance and highlighting best practices. You communicate with a balance of honesty and \
encouragement, providing realistic yet optimistic guidance. You avoid giving advice on areas outside \
the scope of SAFe, like financial management or legal compliance. Additionally, you recognize that \
SAFe may not suit all organizations, especially those with rigid structures or those not ready for\
significant cultural changes. In such cases, you guide users towards understanding the \
limitations of SAFe in their specific context. Walk the user through the step by step process \
and ask clarifying questions one at a time and wait for an answer before responding. Then \
formulate your response.",
model="gpt-4-1106-preview",
# file_ids=[file.id],
tools=[{"type": "retrieval"}]
)
# Step 2: Create a Thread
thread = client.beta.threads.create()
def main(query, history):
# Step 3: Add a Message to a Thread
history=history,
message = client.beta.threads.messages.create(
thread_id=thread.id,
role="user",
content=query
)
# Step 4: Run the Assistant
run = client.beta.threads.runs.create(
thread_id=thread.id,
assistant_id=assistant.id,
instructions="The user is a humanitarian worker who is going through digital transformation"
)
while True:
# Wait for 5 seconds
time.sleep(0.5)
# Retrieve the run status
run_status = client.beta.threads.runs.retrieve(
thread_id=thread.id,
run_id=run.id
)
# If run is completed, get messages
if run_status.status == 'completed':
messages = client.beta.threads.messages.list(
thread_id=thread.id
)
response = ""
data = messages.data
first_thread_message = data[0]
content = first_thread_message.content
response = content[0].text.value
return response
else:
continue
# Create a Gradio Interface
iface = gr.ChatInterface(main, title="SAFe Specialist: Your Guide to Scaled Agile Framework",\
description="SAFe Specialist guiding transitions with realistic and \
optimistic advice towards a product centric approach. For more info, check out this medium post: https://medium.com/p/bcc1b8ebf2b2 or github: https://github.com/jmesplana/openai_assistant",\
examples=["How can I shift from project to product mode?",\
"What are the key SAFe principles for my organization?",\
"Can you provide options for agile practices in my setting?",\
"How do I deal with cultural resistance in SAFe adoption?", \
"What's your advice for an org with many different digital solutions?",\
"Could you walk me through the step-by-step process of moving into SAFe?"]).queue()
if __name__ == "__main__":
iface.launch() |