OpenAI Chat Completion

  from athina_logger.api_key import AthinaApiKey
  from athina_logger.openai_wrapper import openai

  AthinaApiKey.set_api_key(os.getenv('ATHINA_API_KEY'))
  openai.api_key = os.getenv('OPENAI_API_KEY')

  from athina_logger.openai_wrapper import openai

from athina_logger.athina_meta import AthinaMeta
messages = [ { "role": "user", "content": "How much funding does Y Combinator provide?" } ]

# Use openai.ChatCompletion just as you would normally
# Add fields to AthinaMeta for better segmentation of your data
openai.ChatCompletion.create(
  model="gpt-4",
  messages=messages,
  stream=False,
  athina_meta=AthinaMeta(
    prompt_slug="yc_rag_v1",
    user_query="How much funding does Y Combinator provide?", # For RAG Q&A systems, log the user's query
    context={"information": retrieved_documents} # Your retrieved documents
    session_id=session_id, # Conversation ID
    customer_id=customer_id, # Your Customer's ID
    customer_user_id=customer_id, # Your End User's ID
    environment=environment, # Environment (production, staging, dev, etc)
    external_reference_id="ext_ref_123456",
    custom_attributes={
      "name": "John",
      "age": 30,
      "city": "New York"
    } # Your custom-attributes
  ),
)