import os
os.environ["OPENAI_API_KEY"] = "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"

import openai
import os
import PyPDF2
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
from dotenv import load_dotenv, find_dotenv

_ = load_dotenv(find_dotenv())

openai.api_key = os.getenv('OPENAI_API_KEY')

def get_completion(prompt, model="gpt-3.5-turbo", temperature=0, max_tokens=500):
    messages = [{"role": "user", "content": prompt}]

    response = openai.ChatCompletion.create(
        model=model,
        temperature=temperature,
        max_tokens=max_tokens,
        messages=messages,
    )

    return response.choices[0].message["content"]

def generate_prompt(text, format="text"):
    prompt = f"""Play as an AI HR recruiter specialist and extract all the jobs as a list with :
                  1. Job Title
                  2. Location
                  3. Educations as list
                  4. Experiences as list
                  5. Skills and Competences as list
                  6. Functions and Tasks as list
                  7. Return the result in {format} format \
                  here the text \
                  ``` {text}```


                   """
    return prompt

import PyPDF2

def read_pdf(file_path):
    pdf_file = open(file_path, 'rb')
    pdf_reader = PyPDF2.PdfReader(pdf_file)
    text = ""
    for page in pdf_reader.pages:
        text += page.extract_text()
    pdf_file.close()
    return text

import PyPDF2
def summarize(input):
    text = read_pdf(input.name)
    prompt = generate_prompt(text)
    response = get_completion(prompt)
    return response

import gradio as gr
gr.close_all()
demo = gr.Interface(fn=summarize, inputs="file", outputs="text",title="Experiences And Skills Extraction From PDF file with gpt-3.5-turbo")
demo.launch()

#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
#++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

import gradio as gr

def colorize_text(text):
    return "<span style='color:red;background-color:orange'>" + text + "</span>" "<span style='color:white;background-color:red'>" + "Experiences" + "</span>"

iface = gr.Interface(fn=colorize_text, inputs="text", outputs="html")
iface.launch()