constantes.py

import os


GPT_4_0_MINI_MODEL="openai:gpt-4o-mini"
GPT_4_1_MINI_MODEL="openai:gpt-4.1-mini"
GPT_4o_MODEL="openai:gpt-4o"


OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
TAVILY_API_KEY = os.getenv("TAVILY_API_KEY")
GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
LANGCHAIN_API_KEY = os.getenv("LANGCHAIN_API_KEY")
os.environ["LANGCHAIN_TRACING_V2"] = "true"
os.environ["LANGCHAIN_PROJECT"] = "hf-final-assessment"

OUTPUT_AUDIO_PATH   ="./tmp/audio_analysis_output"
AUDIO_FILENAME = "downloaded_audio"
TRANSCRIPT_FILENAME = "transcript.txt"

OUTPUT_IMAGE_PATH = "./tmp/image_analysis_output"
IMAGE_FILE_NAME = "downloaded_image"

OUTPUT_VIDEO_PATH = "./tmp/video_analysis_output"
VIDEO_FILE_NAME = "downloaded_video"
FRAME_INTERVAL_SECONDS = 0.5 # Intervalo entre frames a serem extraídos
INICIO_FRAME_IMPORTANTE  = 191 # inicio intervalo relevante, para não ficar caro a inferencia ao gpt
FIM_FRAME_IMPORTANTE = 193# fim intervalo relevante, para não ficar caro a inferencia ao gpt
YOUTUBE_COOKIE_PATH = "./support/cookie-youtube.txt"

GPT_IMAGE_MODEL = "gpt-4o"
GEMINI_MODEL = "gemini-2.0-flash"
CHESSVISION_TO_FEN_URL = "http://app.chessvision.ai/predict"
CHESS_MOVE_API = "https://chess-api.com/v1"

AGENTS_FILES_PATH = "./tmp"
HUGGINGFACE_DATASET_URL_TEMPLATE = (
    "https://huggingface.co/datasets/gdms/gaia/resolve/main/{filename}"
)

MEASURE_WORDS = {
        "dash", "pinch", "cup", "cups", "tablespoon", "tablespoons",
        "teaspoon", "teaspoons", "pound", "pounds", "oz", "ounce", "ounces",
        "grams", "gram", "ml", "liter", "liters", "slice", "slices", "of", "a", "an"
    }

LISTA_TASKS_PROCESSAR = [
    "8e867cd7-cff9-4e6c-867a-ff5ddc2550be",
    "a1e91b78-d3d8-4675-bb8d-62741b4b68a6",
    "2d83110e-a098-4ebb-9987-066c06fa42d0",
    "cca530fc-4052-43b2-b130-b30968d8aa44",
    "6f37996b-2ac7-44b0-8e68-6d28256631b4",   
    "9d191bce-651d-4746-be2d-7ef8ecadb9c2",
    "99c9cc74-fdc8-46c6-8f8d-3ce2d3bfeea3",
    "f918266a-b3e0-4914-865d-4faa564f1aef",
    "1f975693-876d-457b-a649-393859e79bf3",
    "7bd855d8-463d-4ed5-93ca-5fe35145f733",
    "3cef3a44-215e-4aed-8e3b-b1e3f08063b7",
    "cf106601-ab4f-4af9-b045-5295fe67b37d",
    "5a0c1adf-205e-4841-a666-7c3ef95def9d",   
    "3f57289b-8c60-48be-bd80-01f8099ca449",   
# Pendentes
#    "4fc2f1ae-8625-45b5-ab34-ad4433bc21f8",        
#    "cabe07ed-9eca-40ea-8ead-410ef5e83f91",
#    "305ac316-eef6-4446-960a-92d80d542f82",  
#    "840bfca7-4f7b-481a-8794-c560c340185d",
#    "bda648d7-d618-4883-88f4-3466eabd860e",
#    "a0c07678-e491-4bbc-8f0b-07405144218f",
      
]