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from pathlib import Path |
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import os |
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import sys |
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BASE_DIR = Path(__file__).resolve().parents[2] |
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if str(BASE_DIR) not in sys.path: |
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sys.path.insert(0, str(BASE_DIR)) |
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EMBEDDING_MODEL = "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2" |
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STATIC_VS_PATH = BASE_DIR / "app" / "vectorstore" / "faiss_index" |
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LIVE_VS_PATH = BASE_DIR / "app" / "vectorstore" / "live_rag_index" |
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VECTORSTORE_PATH = LIVE_VS_PATH |
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WEATHER_API_KEY = os.getenv("WEATHER_API_KEY", "1eefcad138134d62a1e220003252608") |
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CLASSIFIER_PATH = BASE_DIR / "app" / "models" / "intent_classifier_v2.joblib" |
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CLASSIFIER_CONFIDENCE_THRESHOLD = float(os.getenv("CLASSIFIER_CONFIDENCE_THRESHOLD", "0.6")) |
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EXPERT_MODEL_NAME = os.getenv("EXPERT_MODEL_NAME", "Qwen/Qwen3-4B-Instruct-2507") |
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LANG_ID_MODEL_REPO = os.getenv("LANG_ID_MODEL_REPO", "facebook/fasttext-language-identification") |
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LANG_ID_MODEL_FILE = os.getenv("LANG_ID_MODEL_FILE", "model.bin") |
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TRANSLATION_MODEL_NAME = os.getenv("TRANSLATION_MODEL_NAME", "drrobot9/nllb-ig-yo-ha-finetuned") |
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DATA_SOURCES = { |
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"harvestplus": "https://agronigeria.ng/category/news/", |
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} |
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STATES = [ |
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"Abuja", "Lagos", "Kano", "Kaduna", "Rivers", "Enugu", "Anambra", "Ogun", |
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"Oyo", "Delta", "Edo", "Katsina", "Borno", "Benue", "Niger", "Plateau", |
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"Bauchi", "Adamawa", "Cross River", "Akwa Ibom", "Ekiti", "Osun", "Ondo", |
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"Imo", "Abia", "Ebonyi", "Taraba", "Kebbi", "Zamfara", "Yobe", "Gombe", |
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"Sokoto", "Kogi", "Bayelsa", "Nasarawa", "Jigawa" |
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] |
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hf_cache = "/models/huggingface" |
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os.environ["HF_HOME"] = hf_cache |
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os.environ["TRANSFORMERS_CACHE"] = hf_cache |
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os.environ["HUGGINGFACE_HUB_CACHE"] = hf_cache |
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os.makedirs(hf_cache, exist_ok=True) |
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