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Sleeping
import time | |
import streamlit as st | |
COST_PER_1000_TOKENS_USD = 0.139 / 80 | |
def stream_handler(session_state, chat_stream, prompt, placeholder): | |
# 1. Uses the chat_stream and streams message on placeholder | |
# 2. returns full_response for token calculation | |
start_time = time.time() | |
full_response = "" | |
for chunk in chat_stream: | |
if chunk.token.text in ["</s>", "<|im_end|>"]: | |
break; | |
full_response += chunk.token.text | |
placeholder.markdown(full_response + "β") | |
placeholder.markdown(full_response) | |
end_time = time.time() | |
elapsed_time = end_time - start_time | |
total_tokens_processed = len(full_response.split()) | |
tokens_per_second = total_tokens_processed // elapsed_time | |
len_response = (len(prompt.split()) + len(full_response.split())) * 1.25 | |
col1, col2, col3 = st.columns(3) | |
with col1: | |
st.write(f"**{tokens_per_second} tokens/second**") | |
with col2: | |
st.write(f"**{int(len_response)} tokens generated**") | |
with col3: | |
st.write( | |
f"**$ {round(len_response * COST_PER_1000_TOKENS_USD / 1000, 5)} cost incurred**" | |
) | |
session_state["tps"] = tokens_per_second | |
session_state["tokens_used"] = len_response + session_state["tokens_used"] | |
return full_response | |