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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()) | |