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| import config | |
| import openai | |
| import sys, getopt | |
| from datetime import datetime | |
| import streamlit as st | |
| import boto3 | |
| def get_chatgpt_resp(question): | |
| openai.api_key = st.secrets['OPENAI_API_KEY'] | |
| response = openai.ChatCompletion.create( | |
| model='gpt-3.5-turbo', | |
| messages=[ | |
| {"role":"system","content":"You are a chatbot"}, | |
| {"role":"system","content":question}] | |
| ) | |
| result = '' | |
| for choice in response.choices: | |
| result+=choice.message.content | |
| return (result) | |
| def gsearch(query, num_results): | |
| try: | |
| from googlesearch import search | |
| except ImportError: | |
| print("No module named 'google' found") | |
| # Google Search and return 10 links | |
| search_links = [] | |
| for j in search(query, tld="com", num=num_results, stop=num_results, pause=2): | |
| search_links.append(j) | |
| return(search_links) | |
| def chatgpt_prompt(pname, search_links): | |
| all_links = '\n'.join(map(str,search_links)) | |
| prompt_text = "You are a expert KYC analyst. I need help to identify if there is any adverse news about {}\ | |
| in the following links. \n {}. \n. In the reply include a 20 word summary of the text in each link and if you find any adverse\ | |
| news (Yes or No)".format(pname, all_links) | |
| return(prompt_text) | |
| def generate_kyc_output(query, search_links, chat_response, start_time): | |
| rep_txt = '' | |
| rep_txt += 'Summary of Google Search for {} \n'.format(query) | |
| rep_txt += '\n' | |
| rep_txt += "Report generated on {} \n".format(datetime.now()) | |
| #rep_txt += "----------------------------------------------------- \n" | |
| rep_txt += '\n' | |
| rep_txt += "Top Google Search Links " | |
| rep_txt += '\n' | |
| rep_txt += '\n'.join(map(str,search_links)) | |
| #rep_txt += "\n----------------------------------------------------- \n" | |
| rep_txt += '\n' | |
| rep_txt+= "\n Summary of searches and adverse news findings \n" | |
| #rep_txt += "----------------------------------------------------- \n" | |
| rep_txt += chat_response | |
| rep_txt += '\n' | |
| end_time = datetime.now() | |
| exec_time = (end_time - start_time).total_seconds() | |
| rep_txt += "Execution runtime {} seconds \n".format(exec_time) | |
| rep_txt += '\n' | |
| return(rep_txt) | |
| def save_to_s3(search_text,date_time): | |
| s3 = boto3.resource( | |
| 's3', | |
| region_name='us-east-1', | |
| aws_access_key_id=st.secrets['AWS_ACCESS_KEY_ID'], | |
| aws_secret_access_key=st.secrets['AWS_ACCESS_KEY'] | |
| ) | |
| fname = ("{}.txt").format(date_time) | |
| object = s3.Object('adverse-news-search', fname) | |
| object.put(Body=search_text) | |
| def main(argv): | |
| try: | |
| opts, args = getopt.getopt(argv,"i:", ["person="]) | |
| except getopt.GetoptError: | |
| print ('Usage: python app.py --person=<person name>') | |
| sys.exit(2) | |
| for opt, arg in opts: | |
| if opt == '--person': | |
| pname = arg | |
| # Google search for the person name and get the first 20 query links | |
| search_links = gsearch(pname) | |
| # Construct the prompt | |
| prompt_text = chatgpt_prompt(pname, search_links) | |
| #get ChatGPT response | |
| resp = get_chatgpt_resp(prompt_text) | |
| # Create PDF with links and summary | |
| #rep_txt= generate_kyc_output(pname, search_links, resp) | |
| #print(rep_txt) | |
| if __name__ == "__main__": | |
| main(sys.argv[1:]) |