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import streamlit as st
import os
import tempfile
import docx2txt
from pdfminer.high_level import extract_text
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
# Handle Hugging Face token
hf_token = os.getenv("HF_TOKEN") # For local dev
if hf_token:
os.environ["HUGGINGFACEHUB_API_KEY"] = hf_token
# UI Configuration
st.set_page_config(page_title="Resume Validator", layout="centered", page_icon="📄")
st.markdown("""
<h1 style='text-align: center;'>📄 AI Resume Validator</h1>
<p style='text-align: center;'>Upload your resume and receive instant feedback with suggestions for improvement</p>
<br>
""", unsafe_allow_html=True)
# File upload
uploaded_file = st.file_uploader("📤 Upload Resume (PDF or DOCX)", type=["pdf", "docx"])
resume_text = ""
if uploaded_file:
with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(uploaded_file.name)[-1]) as tmp_file:
tmp_file.write(uploaded_file.read())
temp_path = tmp_file.name
# Extract text
if uploaded_file.name.endswith(".pdf"):
resume_text = extract_text(temp_path)
else:
resume_text = docx2txt.process(temp_path)
# Remove temp file
os.remove(temp_path)
st.markdown("### 📃 Extracted Resume Text")
st.text_area("Resume Text", resume_text, height=300)
# Prompt template
template = """
You are an expert HR recruiter.
Here is the content of a resume:
{resume_text}
Evaluate the resume on the following criteria:
1. Clarity and grammar
2. Relevance of skills and keywords
3. Structure (sections like Education, Experience, Projects, etc.)
4. Overall impact
Provide:
- A rating out of 10
- Key strengths
- Weaknesses
- Actionable suggestions to improve
"""
prompt = PromptTemplate(input_variables=["resume_text"], template=template)
# LLM Configuration
# llm = HuggingFaceEndpoint(
# repo_id="mistralai/Mistral-7B-Instruct-v0.3",
# temperature=0.5,
# max_new_tokens=10,
# task="text-generation"
# )
# from langchain_huggingface import HuggingFaceEndpoint
llm = HuggingFaceEndpoint(
repo_id="mistralai/Mistral-7B-Instruct-v0.3",
temperature=0.5,
max_new_tokens=10,
task="text-generation",
huggingfacehub_api_token=os.getenv("HF"))
model = ChatHuggingFace(llm=llm)
chain = LLMChain(llm=model, prompt=prompt)
if st.button("✅ Validate Resume"):
with st.spinner("Analyzing your resume..."):
try:
result = chain.run(resume_text=resume_text)
st.success("✅ Resume Analysis Completed")
st.markdown("### 📊 Feedback")
st.markdown(result)
except Exception as e:
st.error(f"⚠️ An error occurred: {e}")
else:
st.markdown("<center><i>Please upload your resume to start validation.</i></center>", unsafe_allow_html=True)
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