Spaces:
Sleeping
Sleeping
File size: 4,052 Bytes
9fec341 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 |
import streamlit as st
from src.resume_parser import ResumeParser
from generate_questions.questions_generator import QuestionGenerator
import google.generativeai as genai
import os
from src.greetings import end_conversation,start_greeting
import json
from src.feedback import feed_back
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
model = genai.GenerativeModel("gemini-pro")
chat = model.start_chat(history=[])
resume_parser = ResumeParser()
questions_generator = QuestionGenerator()
class ResumeUploader:
def resume_upload(self):
st.title("TalentScout - Hiring Assistant Chatbot")
start_greeting()
st.sidebar.title("Candidate Details")
if "tech_stack" not in st.session_state:
st.session_state.tech_stack = []
if "questions" not in st.session_state:
st.session_state.questions = {}
if "answers" not in st.session_state:
st.session_state.answers = {}
uploaded_file = st.sidebar.file_uploader("Upload Resume (PDF):", type=["pdf"])
if uploaded_file:
candidate_details = resume_parser.parse(uploaded_file)
st.success("Resume uploaded and processed successfully!")
st.write("### Candidate Information")
st.write(f"**Name:** {candidate_details['name']}")
st.write(f"**Email:** {candidate_details['email']}")
st.write(f"**Phone:** {candidate_details['phone']}")
st.write(f"**Experience:** {candidate_details['experience']}")
st.write(f"**Position:** {candidate_details['position']}")
st.write(f"**Location:** {candidate_details['location']}")
st.write(f"**Tech Stack:** {', '.join(candidate_details['tech_stack'])}")
st.session_state.tech_stack = candidate_details["tech_stack"][:5]
if st.session_state.tech_stack:
st.write("**Based on your Top 5 skills ,we generate Technical Question , you need to answer the question .If you are ready please click Generate Questions button**")
if st.button("Generate Questions"):
for tech in st.session_state.tech_stack:
tech = tech.strip()
if tech not in st.session_state.questions:
questions = questions_generator.generate_questions(chat, tech)
st.session_state.questions[tech] = questions.split("\n")
st.session_state.answers[tech] = [""] * len(st.session_state.questions[tech])
# Display questions and answers
if st.session_state.questions:
for tech, questions in st.session_state.questions.items():
st.write(f"### Technical Questions for {tech}")
for idx, question in enumerate(questions):
st.write(f"{idx + 1}. {question}")
st.session_state.answers[tech][idx] = st.text_area(
f"Answer for Q{idx + 1} ({tech})",
value=st.session_state.answers[tech][idx],
key=f"answer_{tech}_{idx}",)
if st.button("Submit Answers"):
# Combine questions and answers into a JSON format
greets = end_conversation()
st.write(greets)
output_data = []
for tech, questions in st.session_state.questions.items():
for idx, question in enumerate(questions):
output_data.append({
"tech": tech,
"question": question,
"answer": st.session_state.answers[tech][idx]
})
# Save as JSON file
json_filename = "questions_answers.json"
with open(json_filename, "w") as json_file:
json.dump(output_data, json_file, indent=4)
feed_back() |