I have this code that runs perfectly with API assistant v.1 I have created a new assistant in v.2 but I don’t know why this code doesn’t run and I get the error that:
"BadRequestError: Error code: 400 - {‘error’: {‘message’: “The requested model ‘gpt-4o’ cannot be used with the Assistants API in v1. Follow the migration guide to upgrade to v2: https://platform.openai.com/docs/assistants/migration.”, ‘type’: ‘invalid_request_error’, ‘param’: ‘model’, ‘code’: ‘unsupported_model’}}
"
I didn’t select any tool here because already when I was creating the assistant on the platform I have activated all the tools and uploaded the required files for file search.
import os
import pandas as pd
from openai import OpenAI
from dotenv import load_dotenv
# Load environment variables from api.env
load_dotenv('api.env')
# Retrieve the API key from environment variables
api_key = os.getenv('api_key')
# Initialize the OpenAI client with the API key
client = OpenAI(api_key=api_key)
# Load the Questions and Treatments data from Excel files
questions_df = pd.read_excel('....xlsx')
treatments_df = pd.read_excel('....xlsx')
# Extract the questions and treatments into dictionaries
questions = dict(zip(questions_df['Q_id'], questions_df['Question']))
treatments = dict(zip(treatments_df['Group'], zip(treatments_df['Title'], treatments_df['Information'])))
# Load the Persona data from the Excel file
persona_df = pd.read_excel('....xlsx')
# Specify the number of personas to select
num_personas = 6
# Randomly select the specified number of personas
selected_personas = persona_df.sample(n=num_personas, random_state=42)
# Define the run number
Run = 1
# Assistant IDs
assistants = {
f"Assistant_N_Run{Run}": "...."
}
# Define the number of runs for each treatment group
group_runs = {
'T_1': 5,
'T_2': 5,
'T_3': 5,
'T_4': 5,
'T_5': 5,
'T_6': 5
}
# Assign the selected personas to treatment groups
selected_personas['Group'] = pd.qcut(selected_personas.index, q=len(group_runs), labels=list(group_runs.keys()))
# Iterate over each assistant
for assistant_name, assistant_id in assistants.items():
# Store results for the current assistant
results = []
# Iterate over each treatment group
for treatment_group, num_runs in group_runs.items():
# Filter the selected personas for the current treatment group
group_personas = selected_personas[selected_personas['Group'] == treatment_group]
# Iterate over the runs for the current treatment group
for run, (_, persona) in enumerate(group_personas.iterrows()):
# Get the treatment information
treatment_title, treatment_info = treatments[treatment_group]
# Initialize the result row
result_row = [run, treatment_group, persona['Age'], persona['Gender'], persona['Education'], persona['Marital'], persona['Income']]
# Iterate over the initial questions (Q1_I to Q5_I)
for question_id in [q for q in questions.keys() if q.endswith('_I')]:
# Get the question
question = questions[question_id]
# Create a Thread
my_thread = client.beta.threads.create()
# Add a Message to a Thread with the question
my_thread_message = client.beta.threads.messages.create(
thread_id=my_thread.id,
role="user",
content=question
)
# Run the Assistant
my_run = client.beta.threads.runs.create(
thread_id=my_thread.id,
assistant_id=assistant_id,
instructions=f"You are a {persona['Age']} year old {persona['Gender']} .....ets."
)
# Wait for the Run to complete and retrieve the result
while True:
keep_retrieving_run = client.beta.threads.runs.retrieve(
thread_id=my_thread.id,
run_id=my_run.id
)
if keep_retrieving_run.status == "completed":
all_messages = client.beta.threads.messages.list(
thread_id=my_thread.id
)
response = all_messages.data[0].content[0].text.value
result_row.append(response)
break
# Iterate over the follow-up questions (Q1_F to Q2_F)
for question_id in [q for q in questions.keys() if q.endswith('_F')]:
# If not in the control group (T_1), provide additional context and ask the follow-up question
if treatment_group != 'T_1111':
# Get the question
question = questions[question_id]
# Add a Message to the Thread with the additional context and follow-up question
my_thread_message = client.beta.threads.messages.create(
thread_id=my_thread.id,
role="user",
content=f"{treatment_info}\n\n{question}"
)
# Run the Assistant for the follow-up question
my_run = client.beta.threads.runs.create(
thread_id=my_thread.id,
assistant_id=assistant_id,
instructions=f"You are a {persona['Age']} year old {persona['Gender']} .....ets."
)
# Wait for the Run to complete and retrieve the result for the follow-up question
while True:
keep_retrieving_run = client.beta.threads.runs.retrieve(
thread_id=my_thread.id,
run_id=my_run.id
)
if keep_retrieving_run.status == "completed":
all_messages = client.beta.threads.messages.list(
thread_id=my_thread.id
)
follow_up_response = all_messages.data[0].content[0].text.value
result_row.append(follow_up_response)
break
else:
# If in the control group (T_1), append empty responses for the follow-up questions
result_row.append('')
# Append the result row to the results list
results.append(result_row)
# Print the result row for the current run
print(f"Assistant: {assistant_name}, Group: {treatment_group}, Run {run + 1}: {result_row}")
# Define the column names for the DataFrame
columns = ['Run', 'Group', 'Age', 'Gender', 'Education', 'Marital', 'Income'] + [f"{q}" for q in questions.keys() if q.endswith('_I')] + [f"{q}" for q in questions.keys() if q.endswith('_F')]
# Convert results to DataFrame
df = pd.DataFrame(results, columns=columns)
# Print the results for the current assistant
print(f"\nFinal Results for {assistant_name}:")
print(df)
# Save to Excel
df.to_excel(f'results_{assistant_name}.xlsx', index=False)
print(f"Results for {assistant_name} saved to results_{assistant_name}.xlsx")
Many thanks for any help.