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import gradio as gr | |
import os | |
from functools import partial | |
import gdown | |
import pandas as pd | |
from logs import save_logs | |
import gdown | |
import time | |
import pandas as pd | |
from config import logs_folder_id, json_url_id | |
from ice_cold import get_refresher | |
from web_scrapping_engine import get_linkedin_profile | |
choices = ["sofwareAG"] | |
title = """""" | |
def stream(company): | |
linkedin_extracted_info = get_linkedin_profile(company) | |
linkedin_extracted_info["profile"]["similar_companies"] = "" | |
resp = get_refresher(linkedin_extracted_info) | |
answer = "*(Latest update as per Linkedin)*\n" | |
for chunk in resp: | |
if chunk.choices[0].delta.content is not None: | |
answer = answer + chunk.choices[0].delta.content | |
yield answer | |
answer_to_save = answer + "\n============\n" + str(linkedin_extracted_info) | |
save_logs(company, answer_to_save, folder_id=logs_folder_id) | |
download_url = f'https://drive.google.com/uc?id={json_url_id}' | |
output = 'secret_google_service_account.json' | |
gdown.download(download_url, output, quiet=False) | |
with gr.Blocks(title=title,theme='nota-ai/theme',css="footer {visibility: hidden}") as demo: | |
gr.Markdown(f"## {title}") | |
with gr.Row(): | |
with gr.Column(scale=6): | |
with gr.Row(): | |
with gr.Column(scale=3): | |
chat_input = gr.Textbox(placeholder="Company Name", lines=1, label="Get instant refresher on any company") | |
chat_submit_button = gr.Button(value="Submit ▶") | |
with gr.Column(scale=6): | |
chat_output = gr.Markdown("Waiting for company...") | |
fn_chat = stream | |
chat_submit_button.click(fn=fn_chat, inputs=[chat_input], outputs=[chat_output]) | |
demo.launch(max_threads=40) |