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import numpy as np | |
from shortGPT.database.content_database import ContentDatabase | |
db = ContentDatabase() | |
all = [] | |
# Calculate average and price of the average for OpenAI | |
openai_array = [short.get('api_openai') for short in all] | |
avr_openai = np.mean(openai_array) | |
OPENAI_CONST = 0.002 / 1000 | |
price_openai = avr_openai * OPENAI_CONST | |
max_openai = max(openai_array) | |
price_max_openai = max_openai * OPENAI_CONST | |
# Calculate average and price of the average for Eleven | |
eleven_array = [short.get('api_openai') for short in all] | |
avr_eleven = np.mean(eleven_array) | |
ELEVEN_CONST = 0.3 / 1000 | |
price_eleven = avr_eleven * ELEVEN_CONST | |
max_eleven = max(eleven_array) | |
price_max_eleven = max_eleven * ELEVEN_CONST | |
# Print results | |
print("OpenAI:") | |
print("- Average:", avr_openai) | |
print("- Price of the average:", price_openai) | |
print("- Max:", max_openai) | |
print("- Price of the max:", price_max_openai) | |
print("Eleven:") | |
print("- Average:", avr_eleven) | |
print("- Price of the average:", price_eleven) | |
print("- Max:", max_eleven) | |
print("- Price of the max:", price_max_eleven) | |
# for id in ids: | |
# builder = AskingRedditorShortBuilder(AR, id) | |
# print(id, builder.dataManager.getVideoPath()) | |
#createShorts(30, 'AskingRedditors') | |
# AR = ChannelManager("AskingRedditors") | |
# newShort = AskingRedditorShortBuilder(channelDB= AR, short_id="FyhKkqx9xDxTEtRpanSD") | |
# print(newShort.channelDB.getStaticEditingAsset('background_onepiece')) | |
# print(newShort.channelDB.getStaticEditingAsset('reddit_template_dark')) | |
# print(newShort.channelDB.getStaticEditingAsset('subscribe_animation')) | |
#print("Scraping requests remaining: ",image_api.getScrapingCredits()) | |