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import logging
import httpx
import os
from dotenv import load_dotenv
# Load environment variables from .env file
load_dotenv()
# Get the API key and endpoint from environment variables
api_key = os.getenv('AZURE_OPENAI_API_KEY')
endpoint = os.getenv('AZURE_OPENAI_ENDPOINT')
def list_fine_tuning_jobs() -> dict:
"""List fine-tuning jobs.
Returns:
dict: The response from the API containing the list of fine-tuning jobs.
"""
try:
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {api_key}"
}
response = httpx.get(f"{endpoint}/openai/fine-tunes", headers=headers)
response.raise_for_status()
return response.json()
except httpx.HTTPStatusError as e:
logging.error(f"Error listing fine-tuning jobs: {e.response.text}")
return None
except Exception as e:
logging.error(f"Unexpected error: {e}")
return None
def upload_file_for_fine_tuning(file_path: str) -> dict:
"""Upload a file for fine-tuning.
Args:
file_path (str): The path to the file to be uploaded.
Returns:
dict: The response from the API after uploading the file.
"""
try:
headers = {
"Authorization": f"Bearer {api_key}"
}
with open(file_path, 'rb') as file:
files = {'file': file}
response = httpx.post(f"{endpoint}/openai/files", headers=headers, files=files)
response.raise_for_status()
return response.json()
except httpx.HTTPStatusError as e:
logging.error(f"Error uploading file for fine-tuning: {e.response.text}")
return None
except Exception as e:
logging.error(f"Unexpected error: {e}")
return None
def create_fine_tuning_job(training_file_id: str, model: str = "davinci") -> dict:
"""Create a fine-tuning job.
Args:
training_file_id (str): The ID of the training file.
model (str): The model to be fine-tuned. Default is "davinci".
Returns:
dict: The response from the API after creating the fine-tuning job.
"""
try:
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {api_key}"
}
payload = {
"training_file": training_file_id,
"model": model
}
response = httpx.post(f"{endpoint}/openai/fine-tunes", headers=headers, json=payload)
response.raise_for_status()
return response.json()
except httpx.HTTPStatusError as e:
logging.error(f"Error creating fine-tuning job: {e.response.text}")
return None
except Exception as e:
logging.error(f"Unexpected error: {e}")
return None
def make_post_request(url: str, data: dict, headers: dict) -> dict:
"""Make a POST request.
Args:
url (str): The URL to make the POST request to.
data (dict): The data to be sent in the POST request.
headers (dict): The headers to be sent in the POST request.
Returns:
dict: The response from the API after making the POST request.
"""
try:
response = httpx.post(url, json=data, headers=headers)
response.raise_for_status()
return response.json()
except httpx.HTTPStatusError as e:
logging.error(f"Error making POST request: {e.response.text}")
return None
except Exception as e:
logging.error(f"Unexpected error: {e}")
return None
def azure_chat_completion_request(messages: list, deployment_id: str) -> str:
"""Make a chat completion request to Azure OpenAI.
Args:
messages (list): The list of messages to be sent in the chat completion request.
deployment_id (str): The deployment ID for the chat completion request.
Returns:
str: The response content from the chat completion request.
"""
try:
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {api_key}"
}
payload = {
"deployment_id": deployment_id,
"messages": messages
}
response = httpx.post(f"{endpoint}/openai/deployments/{deployment_id}/chat/completions", headers=headers, json=payload)
response.raise_for_status()
return response.json()["choices"][0]["message"]["content"].strip()
except httpx.HTTPStatusError as e:
logging.error(f"Error making chat completion request: {e.response.text}")
return None
except Exception as e:
logging.error(f"Unexpected error: {e}")
return None
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