| # ================================================================================= | |
| # config.py: Project configuration settings | |
| # ================================================================================= | |
| # This file contains constant parameters like model names, file paths, etc. | |
| # Sensitive information like API keys will be read from the .env file. | |
| # --- Model Settings --- | |
| # The main language model to be used in the RAG chain | |
| LLM_MODEL_ID = "gemini-2.0-flash-001" | |
| # The embedding model for converting text to vectors | |
| EMBEDDING_MODEL_NAME = "pritamdeka/S-BioBert-snli-multinli-stsb" | |
| # --- File Paths --- | |
| # Path to the raw data downloaded from the openFDA API | |
| RAW_DATA_PATH = "./fda_data/drug_labels_all.json" | |
| # Path to the cleaned/processed data | |
| CLEANED_DATA_PATH = "./fda_data/fda_data_processed.jsonl" | |
| # The name of the folder where the vector database will be saved | |
| VECTOR_STORE_PATH = "llamaIndexVectorBase_fda" | |
| # ================================================================================= | |
| # LlamaIndex Settings | |
| # ================================================================================= | |
| LLAMA_INDEX_STORE_PATH = "./llamaIndexVectorBase_fda" | |
| # ================================================================================= | |
| # Data Source Paths | |
| # ================================================================================= | |
| ##HEALTHCARE_MAGIC_PATH = "../healthCareMagic/HealthCareMagic-100k.json" | |
| ##MEDQUAD_PATH = "../medQuad/medDataset.json" | |