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| import gspread | |
| import os,random | |
| from Candidate import JobCandidate | |
| from dotenv import load_dotenv | |
| from compator import bubble_sort | |
| from results import writeToSheets | |
| from resume_conversation import chat_with_candidate | |
| sa = gspread.service_account(filename='service_creds.json') | |
| sh = sa.open("Figma_swe") | |
| load_dotenv() | |
| wks = sh.worksheet("Sheet1") | |
| data = wks.get_all_values() | |
| # Load environment variables from the .env file | |
| load_dotenv() | |
| # destination_path = os.path.join(os.getcwd(), id) | |
| candidates=[] | |
| # os.environ['COMPARATOR_LLM']="chat-bison" | |
| os.environ['COMPARATOR_LLM']="gpt-3.5-turbo-1106" | |
| for i in range(1, 7): | |
| candid =JobCandidate(data[i]) | |
| candidates.append(candid) | |
| # random.shuffle(candidates) | |
| sort_cand = bubble_sort(candidates) | |
| writeToSheets(candidates) | |
| for idx, candidate in enumerate(sort_cand): | |
| print(str(idx) + '. ' + candidate.email) | |
| print('Select a candidate to chat with. Type in their index number. Type -1 if you dont want to chat.') | |
| idx = int(input()) | |
| if idx != -1: | |
| selected_candidate = candidates[idx] | |
| chat_with_candidate(selected_candidate) | |
| # for candidate in candidates: | |
| # print(candidate) | |
| # print() # Print a blank line between candidates for better readability | |