Delete main.py

main.py

@@ -1,45 +0,0 @@
-from createVectorDB import createVectorDB
-from splitBioModels import splitBioModels
-from createDocuments import createDocuments
-from generateResponse import generateResponse
-from selectBioModels import search_biomodels
-from selectBioModels import copy_matching_files
-
-DATA_PATH = r"C:\Users\navan\Downloads\BioModelsRAG\BioModelsRAG\2data"
-CHROMA_DATA_PATH = r"C:\Users\navan\Downloads\BioModelsRAG\CHROMA_EMBEDDINGS_PATH"
-directory = r'C:\Users\navan\Downloads\BioModelsRAG\BioModelsRAG\data'
-output_file = r'C:\Users\navan\Downloads\BioModelsRAG\biomodels_output.csv'
-final_models_folder = r'C:\Users\navan\Downloads\BioModelsRAG\final_models'
-user_keywords = input("Keyword you would like to search for: ").split()
-
-
-def main(report:bool = True, directory = DATA_PATH, chroma_data_path = CHROMA_DATA_PATH):
-    data = []
-    search_biomodels(directory, user_keywords, output_file)
-    copy_matching_files(output_file, directory, final_models_folder)
-    
-    splitBioModels(directory=DATA_PATH, final_items=data)
-
-    collection = createVectorDB(
-        collection_name="123456789101112131415",
-        chroma_data_path=chroma_data_path,
-        embed_model="all-MiniLM-L6-v2",
-        metadata={"hnsw:space": "cosine"}
-    )
-
-    if report:
-        print("Collection created:", collection)
-
-    createDocuments(final_items=data, collection=collection)
-
-    if report:
-        print("Documents added to collection.")
-
-    query = "What protein interacts with DesensitizedAch2?"
-    result = generateResponse(query_text=query, collection=collection)
-    return result
-#name of the program running v
-if __name__ == "__main__":
-    result = main()
-    print(result)
-