import time import openai import os import pandas as pd import numpy as np import gradio as gr from llama_index import GPTSimpleVectorIndex from openai.embeddings_utils import get_embedding, cosine_similarity openai.api_key = os.getenv("OPENAI_API_KEY") passwd = os.getenv("PASSWD_SECRET") title = "Confidential forensics tool with ChatGPT" examples = ["Who is Phillip Allen?", "What the project in Austin is about?", "Give me more details about the real estate project"] index = GPTSimpleVectorIndex.load_from_disk('email.json') df = pd.read_feather("emails.feather") df2 = df["subject"].replace([None], "").head(10).to_frame() def search_emails(opt, message, n=3): "Outputs the top n emails that match the most the pattern" if len(message.strip()) < 1: message = "Oops, it looks like your query was not valid. Please make sure you typed something in your text box and then try again." else: try: embedding = get_embedding(message) message = "" df['similarities'] = df.embedding.apply(func=(lambda x: cosine_similarity(x, embedding))) message_tmp = df.sort_values('similarities', ascending=False).head(n) message_tmp = [(row.file, row.body, row.similarities) for index, row in message_tmp.iterrows()] for msg in message_tmp: message += f"Mail ID: {msg[0]}\nContent: {msg[1].strip()}\nSimilarity score: {msg[2]}\n\n" except Exception as e: message = "An error occured when handling your query, please try again." print(e) return message, "" def respond_upload(btn_upload, message, chat_history): time.sleep(2) message = "***File uploaded***" bot_message = "Your document has been uploaded and will be accounted for your queries." chat_history.append((message, bot_message)) return btn_upload, "", chat_history def respond2(message, chat_history, box, btn): if len(message.strip()) < 1: message = "***Empty***" bot_message = "Oops, it looks like your query was not valid. Please make sure you typed something in your text box and then try again." else: try: bot_message = str(index.query(message)).strip() except: bot_message = "An error occured when handling your query, please try again." chat_history.append((message, bot_message)) return message, chat_history, box def respond(message, chat_history): if len(message.strip()) < 1: message = "***Empty***" bot_message = "Oops, it looks like your query was not valid. Please make sure you typed something in your text box and then try again." else: try: bot_message = str(index.query(message)).strip() except: bot_message = "An error occured when handling your query, please try again." chat_history.append((message, bot_message)) return "", chat_history with gr.Blocks(title=title) as demo: gr.Markdown( """ # """ + title + """ """) dat = gr.Dataframe( value=df2, max_cols=1, max_rows=4, title="Documents loaded", overflow_row_behaviour="paginate", ) btn_upload = gr.UploadButton("Upload a new document...", file_types=["text"]) gr.Markdown( """ ## Chatbot """) chatbot = gr.Chatbot().style(height=400) with gr.Row(): with gr.Column(scale=0.85): msg = gr.Textbox( show_label=False, placeholder="Enter text and press enter, or click on Send.", ).style(container=False) with gr.Column(scale=0.15, min_width=0): btn_send = gr.Button("Send your query") with gr.Row(): gr.Markdown( """ Example of queries """) for ex in examples: btn = gr.Button(ex) btn.click(respond2, [btn, chatbot, msg], [btn, chatbot, msg]) msg.submit(respond, [msg, chatbot], [msg, chatbot]) btn_send.click(respond, [msg, chatbot], [msg, chatbot]) btn_upload.upload(respond_upload, [btn_upload, msg, chatbot], [btn_upload, msg, chatbot]) gr.Markdown( """ ## Search the matching document """) opt = gr.Textbox( show_label=False, placeholder="The document matching with your query will be shown here.", interactive=False, lines=8 ) with gr.Row(): with gr.Column(scale=0.85): msg2 = gr.Textbox( show_label=False, placeholder="Enter text and press enter, or click on Send.", ).style(container=False) with gr.Column(scale=0.15, min_width=0): btn_send2 = gr.Button("Send your query") btn_send2.click(search_emails, [opt, msg2], [opt, msg2]) if __name__ == "__main__": # demo.launch(auth=("mithril", passwd)) demo.launch()