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import openai | |
import time | |
import logging | |
import streamlit as st | |
openai_api_key = st.secrets["openai_api_key"] | |
client = openai.OpenAI(api_key = openai_api_key) | |
model = "gpt-3.5-turbo-16k" | |
# === Thread an empty thread | |
thread = client.beta.threads.create() | |
thread_id = thread.id | |
def wait_for_run_completion(client, thread_id, run_id, sleep_interval=5): | |
""" | |
Waits for a run to complete and prints the elapsed time.:param client: The OpenAI client object. | |
:param thread_id: The ID of the thread. | |
:param run_id: The ID of the run. | |
:param sleep_interval: Time in seconds to wait between checks. | |
""" | |
while True: | |
try: | |
run = client.beta.threads.runs.retrieve(thread_id = thread_id, run_id = run_id) | |
if run.completed_at: | |
elapsed_time = run.completed_at - run.created_at | |
formatted_elapsed_time = time.strftime( | |
"%H:%M:%S", time.gmtime(elapsed_time) | |
) | |
print(f"Run completed in {formatted_elapsed_time}") | |
logging.info(f"Run completed in {formatted_elapsed_time}") | |
# Get messages here once Run is completed! | |
messages = client.beta.threads.messages.list(thread_id=thread_id) | |
last_message = messages.data[0] | |
response = last_message.content[0].text.value | |
st.write(response) | |
break | |
except Exception as e: | |
logging.error(f"An error occurred while retrieving the run: {e}") | |
break | |
logging.info("Waiting for run to complete...") | |
time.sleep(sleep_interval) | |
def create_new_assistant(): | |
personal_trainer_assis = client.beta.assistants.create( | |
name="Data Analyst", | |
instructions="""You are great at creating beautiful data visualizations. You analyze data present in .csv files, understand trends, and come up with data visualizations relevant to those trends. You also share a brief text summary of the trends observed.""", | |
model=model | |
) | |
print(f"Created new assistant with ID: {personal_trainer_assis.id}") | |
return personal_trainer_assis.id | |
def main(): | |
# Streamlit interface | |
st.title("Data Analyst") | |
# Note that API key's running out of budget | |
contact_url = "https://www.linkedin.com/in/linhvuu" | |
st.write("If no result returns, it means I am running out of energy. Please contact [Linh Vuu](%s) to wake me up." % contact_url) | |
uploaded_file = st.file_uploader("Upload a CSV file for analysis", type=['csv']) | |
if uploaded_file is not None: | |
file_content = uploaded_file.read() | |
# Upload a file with an "assistants" purpose | |
file_array = [file_content] | |
file_id_array = [] | |
for file in file_array: | |
file = client.files.create( | |
file = file_content, | |
purpose="assistants" | |
) | |
file_id_array.append(file.id) | |
print(file_id_array) | |
with st.form(key="user_input_form"): | |
question = st.text_input("Enter question:") | |
submit_button = st.form_submit_button(label="Response to my question above") | |
if submit_button: | |
# ==== Create a Message ==== | |
message = question | |
message = client.beta.threads.messages.create( | |
thread_id = thread_id, role = "user", content = message, file_ids = file_id_array | |
) | |
# Define assistant_id before the try-except block | |
assistant_id = "asst_IY1VCWqTnQ2Uvj9zWHLXmblg" | |
run = None | |
# === Run our Assistant === | |
try: | |
if assistant_id is None: | |
# If assistant_id is None, create a new assistant | |
assistant_id = create_new_assistant() | |
run = client.beta.threads.runs.create( | |
thread_id = thread_id, | |
assistant_id = assistant_id | |
) | |
except openai.NotFoundError: | |
# If assistant_id does not exist, create a new assistant and retry | |
assistant_id = create_new_assistant() | |
run = client.beta.threads.runs.create( | |
thread_id = thread_id, | |
assistant_id = assistant_id | |
) | |
# === Run === | |
wait_for_run_completion(client=client, thread_id=thread_id, run_id=run.id) | |
if __name__ == "__main__": | |
main() |