from llama_index.llms.openai import OpenAI

response = OpenAI().complete("Paul Graham is ")
print(response)

# iterate through sub_question items captured in SUB_QUESTION event
from llama_index.core.callbacks import CBEventType, EventPayload

for i, (start_event, end_event) in enumerate(
    llama_debug.get_event_pairs(CBEventType.SUB_QUESTION)
):
    qa_pair = end_event.payload[EventPayload.SUB_QUESTION]
    print("Sub Question " + str(i) + ": " + qa_pair.sub_q.sub_question.strip())
    print("Answer: " + qa_pair.answer.strip())
    print("====================================")

token_counter = TokenCountingHandler(
        tokenizer=tiktoken.encoding_for_model("gpt-3.5-turbo").encode,
        verbose=True
    )
Settings.callback_manager = CallbackManager([token_counter])

custom_prompt = PromptTemplate(
    """\
Given a conversation (between Human and Assistant) and a follow up message from Human, \
rewrite the message to be a standalone question that captures all relevant context \
from the conversation.

<Chat History>
{chat_history}

<Follow Up Message>
{question}

<Standalone question>
"""
)

my_template = "Given a conversation (between Human and Assistant) and a follow up message from Human, rewrite the message to be a standalone question that captures all relevant context from the conversation.

<Chat History>
{chat_history}

<Follow Up Message>
{question}

<Standalone question>"

custom_prompt = PromptTemplate(my_template)