Locally? It's not really possible to run the model locally, but finetuning on directories is possible. Here's the code: It's runs on three different directory

Locally? It's not really possible to run the model locally, but finetuning on directories is possible. Here's the code: It's runs on three different directorys to give me three different 'answers' using an excel sheet to pull the q's from. def excelGPT(self, dir, excel_file, sheet): #my GPT Key os.environ['OPENAI_API_KEY'] = 'sk- #Working Directory for training # root = root_folder1 = documents1 = SimpleDirectoryReader(root_folder1).load_data() index1 = GPTSimpleVectorIndex(documents1) root_folder2 = documents2 = SimpleDirectoryReader(root_folder2).load_data() index2 = GPTSimpleVectorIndex(documents2) root_folder3 = documents3 = SimpleDirectoryReader(root_folder3).load_data() index3 = GPTSimpleVectorIndex(documents3) file_name = dir + excel_file df = pd.read_excel(file_name, sheet_name=sheet) GSA_answer_array = [] basic_answer_array = [] QA_answer_array = [] df_series = df.iloc[:,0] for i,x in enumerate(df_series): print("This is the index ", i) print(x) GSA_response = index1.query(x) basic_response = index2.query(x) QA_response = index3.query(x) GSA_answer_array.append(str(GSA_response)) basic_answer_array.append(str(basic_response)) QA_answer_array.append(str(QA_response)) self.zip_to_docv2(dir, "Gippie_Response.docx", df_series, GSA_answer_array, basic_answer_array, QA_answer_array)