app.py

import openai
import os
from paperqa import Docs
import gradio as gr
from langchain.document_loaders import PyPDFLoader
from langchain.vectorstores import Chroma
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.document_loaders import UnstructuredPDFLoader
from langchain.llms import OpenAI
from langchain.chains.question_answering import load_qa_chain
from langchain.chat_models import ChatOpenAI

# Set your OpenAI API key here
OPENAI_API_KEY = 'sk-proj-'
os.environ['OPENAI_API_KEY'] = OPENAI_API_KEY

css_style = """
.gradio-container {
    font-family: "IBM Plex Mono";
}
.answerText p {
    font-size: 24px !important;
    color: #8dbcfe !important;
}
"""

def run(uploaded_files):
    all_files = []
    if uploaded_files is None:
        return all_files
    for file in uploaded_files:
        if file.name.endswith('.pdf'):
            all_files.append(file.name)
            print(f"File uploaded: {file.name}, Size: {file.size} bytes")
    return all_files

def createAnswer(files, designation):
    # Initialize the Docs object with the OpenAI API key
    docs = Docs(llm='gpt-3.5-turbo')

    # Add the uploaded files to the Docs object
    for d in files:
        try:
            docs.add(d.name)
            print(f"Successfully added file: {d.name}")
        except Exception as e:
            print(f"Error adding file {d.name}: {e}")
            return f"Error reading file {d.name}. Please ensure the file is not empty or corrupted."

    # Query the documents to find the best candidate for the given designation
    answer = docs.query(
        f"Who is the best candidate to hire for {designation}. Provide a list with the candidate name. If you don't know, simply say None of the candidates are suited for the Job role."
    )

    print(answer.formatted_answer)
    print(type(answer))
    return answer.answer

with gr.Blocks(css=css_style) as demo:
    gr.Markdown(f"""
    # HR-GPT - Filter & Find The Best Candidate for the Job using AI
    *By Amin Memon ([@AminMemon](https://twitter.com/AminMemon))*
    This tool will enable asking questions of your uploaded text, PDF documents,.
    It uses OpenAI's ChatGPT model & OpenAI Embeddings and thus you must enter your API key below.
    This tool is under active development and currently uses many tokens - up to 10,000
    for a single query. That is $0.10-0.20 per query, so please be careful!
    Porting it to Llama.cpp soon for saved cost.
    1. Upload your Resumes (Try a few resumes/cv to try < 5)
    2. Provide Designation for which you are hiring
    """)

    position = gr.Text(
        label='Position/Designation for which you are hiring for', value="")

    with gr.Tab('File Upload'):
        uploaded_files = gr.File(
            label="Resume Upload - ONLY PDF. (Doc File Support Coming Soon)", file_count="multiple", show_progress=True)

    uploaded_files.change(
        fn=run, inputs=[uploaded_files], outputs=[uploaded_files])
    ask = gr.Button("Find Top Candidate")
    answer = gr.Markdown(label="Result",  elem_classes='answerText')
    ask.click(fn=createAnswer, inputs=[
              uploaded_files, position], outputs=[answer])

demo.queue(concurrency_count=20)
demo.launch(show_error=True)