Update app.py

app.py

@@ -1,19 +1,28 @@
 import streamlit as st
-import cv2
-import numpy as np
-import tempfile
 import os
+import tempfile
+import numpy as np
 import easyocr
+
+# Only needed if you're doing any OCR or OpenCV processing
+# import cv2
+
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
 from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
 
+# Set page config
 st.set_page_config(page_title="Resume Validator", layout="centered", page_icon="📄")
 st.title("📄 AI Resume Validator")
 st.write("Upload your resume and get instant feedback on its quality and suggestions to improve.")
+
+# File uploader
 uploaded_file = st.file_uploader("Upload Resume (PDF or DOCX)", type=["pdf", "docx"])
+
+# Only run logic if a file is uploaded
 if uploaded_file:
-    if uploaded_file.name.endswith('.pdf'):
+    # Extract text based on file type
+    if uploaded_file.name.endswith(".pdf"):
         from pdfminer.high_level import extract_text
         resume_text = extract_text(uploaded_file)
     else:
@@ -22,32 +31,43 @@ if uploaded_file:
 
     st.markdown("### 📃 Extracted Resume Text")
     st.code(resume_text)
-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 = HuggingFaceEndpoint(repo_id="mistralai/Mistral-7B-Instruct-v0.3", temperature=0.5)
-model = ChatHuggingFace(llm=llm)
-chain = LLMChain(llm=model, prompt=prompt)
-
-if st.button("Validate Resume"):
-    with st.spinner("Analyzing..."):
-        result = chain.run(resume_text=resume_text)
-        st.success("✅ Resume Analysis Completed")
+
+    # Prompt template for evaluation
+    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)
+
+    # Initialize the model
+    llm = HuggingFaceEndpoint(
+        repo_id="mistralai/Mistral-7B-Instruct-v0.3",
+        temperature=0.5,
+        max_new_tokens=300,
+        task="conversational"
+    )
+    model = ChatHuggingFace(llm=llm)
+    chain = LLMChain(llm=model, prompt=prompt)
+
+    # Analyze resume on button click
+    if st.button("✅ Validate Resume"):
+        with st.spinner("Analyzing your resume..."):
+            result = chain.run(resume_text=resume_text)
         st.markdown("### 📊 Feedback")
-        st.write(result)
+        st.success(result)
+else:
+    st.info("Please upload a resume file (PDF or DOCX) to start the validation.")