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import streamlit as st |
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from src.resume_parser import ResumeParser |
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from generate_questions.questions_generator import QuestionGenerator |
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import google.generativeai as genai |
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import os |
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from src.greetings import end_conversation,start_greeting |
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import json |
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from src.feedback import feed_back |
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genai.configure(api_key=os.getenv("GOOGLE_API_KEY")) |
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model = genai.GenerativeModel("gemini-pro") |
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chat = model.start_chat(history=[]) |
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resume_parser = ResumeParser() |
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questions_generator = QuestionGenerator() |
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class ResumeUploader: |
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def resume_upload(self): |
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st.title("TalentScout - Hiring Assistant Chatbot") |
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start_greeting() |
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st.sidebar.title("Candidate Details") |
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if "tech_stack" not in st.session_state: |
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st.session_state.tech_stack = [] |
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if "questions" not in st.session_state: |
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st.session_state.questions = {} |
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if "answers" not in st.session_state: |
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st.session_state.answers = {} |
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uploaded_file = st.sidebar.file_uploader("Upload Resume (PDF):", type=["pdf"]) |
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if uploaded_file: |
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candidate_details = resume_parser.parse(uploaded_file) |
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st.success("Resume uploaded and processed successfully!") |
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st.write("### Candidate Information") |
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st.write(f"**Name:** {candidate_details['name']}") |
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st.write(f"**Email:** {candidate_details['email']}") |
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st.write(f"**Phone:** {candidate_details['phone']}") |
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st.write(f"**Experience:** {candidate_details['experience']}") |
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st.write(f"**Position:** {candidate_details['position']}") |
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st.write(f"**Location:** {candidate_details['location']}") |
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st.write(f"**Tech Stack:** {', '.join(candidate_details['tech_stack'])}") |
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st.session_state.tech_stack = candidate_details["tech_stack"][:5] |
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if st.session_state.tech_stack: |
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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**") |
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if st.button("Generate Questions"): |
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for tech in st.session_state.tech_stack: |
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tech = tech.strip() |
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if tech not in st.session_state.questions: |
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questions = questions_generator.generate_questions(chat, tech) |
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st.session_state.questions[tech] = questions.split("\n") |
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st.session_state.answers[tech] = [""] * len(st.session_state.questions[tech]) |
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if st.session_state.questions: |
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for tech, questions in st.session_state.questions.items(): |
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st.write(f"### Technical Questions for {tech}") |
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for idx, question in enumerate(questions): |
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st.write(f"{idx + 1}. {question}") |
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st.session_state.answers[tech][idx] = st.text_area( |
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f"Answer for Q{idx + 1} ({tech})", |
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value=st.session_state.answers[tech][idx], |
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key=f"answer_{tech}_{idx}",) |
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if st.button("Submit Answers"): |
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greets = end_conversation() |
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st.write(greets) |
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output_data = [] |
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for tech, questions in st.session_state.questions.items(): |
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for idx, question in enumerate(questions): |
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output_data.append({ |
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"tech": tech, |
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"question": question, |
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"answer": st.session_state.answers[tech][idx] |
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}) |
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json_filename = "questions_answers.json" |
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with open(json_filename, "w") as json_file: |
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json.dump(output_data, json_file, indent=4) |
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feed_back() |
