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Update app.py
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app.py
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import streamlit as st
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from
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from
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import os
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hf_token = os.getenv("HUGGINGFACEHUB_API_KEY")
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model_kwargs={
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"temperature": 0.7,
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"max_new_tokens": 200
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)
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# repo_id="HuggingFaceH4/zephyr-7b-beta",
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# task="conversational",
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# temperature=0.7,
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# max_new_tokens=300,
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# model="huggingface",
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# provider="hf-inference"
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# Prompt template
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prompt = PromptTemplate.from_template("""
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You are an expert career advisor specializing in analyzing job descriptions and providing actionable insights to help job seekers tailor their resumes and skills for maximum impact.
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Given the Job Description below, extract and present the following sections **using markdown formatting**:
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**1. Key Technical Skills**
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List the main technical skills required using bullet points.
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**2. Important Soft Skills**
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List the soft skills emphasized by the employer using bullet points.
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**3. Suggested Mini Projects**
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Recommend mini projects or learning paths to strengthen the candidate’s profile, using bullet points.
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**4. Resume Improvement Tips**
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Provide practical and specific tips to improve the candidate's resume, using bullet points.
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Use **bold headings** for each section and markdown bullet points (`- `). Write in a professional yet friendly tone. Be concise, clear, and focused on actionable advice.
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Job Description:
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\"\"\"{job_description}\"\"\"
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""")
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# Chain
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chain = prompt | llm_model
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# Streamlit UI
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st.set_page_config(page_title="JD Analyzer AI")
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st.title("📄 JD Analyzer AI")
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st.markdown("Paste any job description below and get insights to improve your profile.")
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jd_input = st.text_area("Paste Job Description:", height=300)
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if st.button("Analyze"):
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import streamlit as st
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from langchain_core.prompts import PromptTemplate
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from langchain_community.chat_models import ChatHuggingFace
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import os
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hf_token = os.getenv("HUGGINGFACEHUB_API_KEY")
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if not hf_token:
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st.error("Hugging Face API token not found. Please set the environment variable 'HUGGINGFACE_API_TOKEN'.")
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st.stop()
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llm_model = ChatHuggingFace.from_model_id(
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model_id="HuggingFaceH4/zephyr-7b-beta",
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task="conversational",
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model_kwargs={
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"temperature": 0.7,
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"max_new_tokens": 200
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},
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huggingfacehub_api_token=hf_token
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)
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prompt = PromptTemplate.from_template("""
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You are an expert career advisor specializing in analyzing job descriptions and providing actionable insights to help job seekers tailor their resumes and skills for maximum impact.
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Given the Job Description below, extract and present the following sections **using markdown formatting**:
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**1. Key Technical Skills**
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List the main technical skills required using bullet points.
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**2. Important Soft Skills**
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List the soft skills emphasized by the employer using bullet points.
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**3. Suggested Mini Projects**
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Recommend mini projects or learning paths to strengthen the candidate’s profile, using bullet points.
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**4. Resume Improvement Tips**
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Provide practical and specific tips to improve the candidate's resume, using bullet points.
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Use **bold headings** for each section and markdown bullet points (`- `). Write in a professional yet friendly tone. Be concise, clear, and focused on actionable advice.
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Job Description:
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\"\"\"{job_description}\"\"\"
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""")
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chain = prompt | llm_model
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st.set_page_config(page_title="JD Analyzer AI")
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st.title("📄 JD Analyzer AI")
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st.markdown("Paste any job description below and get insights to improve your profile.")
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jd_input = st.text_area("Paste Job Description:", height=300)
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if st.button("Analyze"):
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if not jd_input.strip():
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st.warning("Please paste a job description to analyze.")
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else:
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try:
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with st.spinner("Analyzing..."):
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output = chain.invoke({"job_description": jd_input})
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st.markdown("### 🔍 Output")
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st.markdown(output)
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except Exception as e:
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st.error(f"Error: {e}")
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