Update app.py

app.py

@@ -1,5 +1,3 @@
-# app.py
-
 import streamlit as st
 from streamlit_option_menu import option_menu
 from langchain_groq import ChatGroq
@@ -16,7 +14,7 @@ import json
 # Initialize the LLM with your Groq API key from Streamlit secrets
 llm = ChatGroq(
     temperature=0,
-    groq_api_key="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",
+    groq_api_key="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",  # Securely accessing the Groq API key
     model_name="llama-3.1-70b-versatile"
 )
 
@@ -46,7 +44,7 @@ def extract_job_description(job_link):
         response = requests.get(job_link, headers=headers)
         response.raise_for_status()
         soup = BeautifulSoup(response.text, 'html.parser')
-        # Adjust selectors based on the website's structure for better extraction
+        # You might need to adjust the selectors based on the website's structure
         job_description = soup.get_text(separator='\n')
         return job_description.strip()
     except Exception as e:
@@ -190,47 +188,30 @@ def suggest_keywords(resume_text, job_description=None):
 
 def get_job_recommendations(resume_text, location="India"):
     """
-    Fetches job recommendations using the JSearch API based on the user's skills.
+    Fetches job recommendations using the Remotive.io API based on the user's skills.
     """
     # Extract skills from resume
     skills = extract_skills(resume_text)
     query = " ".join(skills) if skills else "Software Engineer"
 
-    url = "https://jsearch.p.rapidapi.com/search"
-    headers = {
-        "X-RapidAPI-Key": "2a4a8a38a9msh97ce530a89589a6p1d0106jsn1acc0a5ea6bc",
-        "X-RapidAPI-Host": "jsearch.p.rapidapi.com"
-    }
+    url = "https://remotive.io/api/remote-jobs"
     params = {
-        "query": query,
-        "page": "1",
-        "num_pages": "1",
-        "size": "20",
-        "remote_filter": "false",
-        "location": location,
-        "sort": "relevance",
-        "salary_min": "0",
-        "salary_max": "0",
-        "salary_currency": "INR",
-        "radius": "0",
-        "company_type": "",
-        "job_type": "",
-        "degree_level": "",
-        "career_level": "",
-        "include_remote": "false"
+        "search": query,
+        "limit": 20
     }
 
     try:
-        response = requests.get(url, headers=headers, params=params)
+        response = requests.get(url, params=params)
         response.raise_for_status()
         data = response.json()
-        jobs = data.get("data", [])
+        jobs = data.get("jobs", [])
         job_list = []
         for job in jobs:
             job_info = {
-                "title": job.get("job_title"),
-                "company": job.get("employer", {}).get("name"),
-                "link": job.get("job_apply_link") or job.get("job_listing_url")
+                "title": job.get("title"),
+                "company": job.get("company_name"),
+                "link": job.get("url"),
+                "job_description": job.get("description") 
             }
             job_list.append(job_info)
         return job_list
@@ -473,9 +454,11 @@ def job_recommendations_page():
             st.subheader("Recommended Jobs")
             jobs = get_job_recommendations(resume_text)
             if jobs:
-                for job in jobs:
-                    st.write(f"**{job['title']}** at {job['company']}")
+                for idx, job in enumerate(jobs, 1):
+                    st.markdown(f"### Job {idx}")
+                    st.write(f"**{job['title']}** at **{job['company']}**")
                     st.markdown(f"[Apply Here]({job['link']})")
+                    st.write("---")
             else:
                 st.write("No job recommendations found based on your skills.")
         else:
@@ -484,42 +467,63 @@ def job_recommendations_page():
 def skill_matching_page():
     st.header("Skill Matching and Gap Analysis")
 
-    job_description_input = st.text_area("Paste the job description here:")
     uploaded_file = st.file_uploader("Upload your resume (PDF format):", type="pdf")
 
-    if st.button("Analyze Skills"):
-        if not job_description_input:
-            st.error("Please paste the job description.")
-            return
-        if not uploaded_file:
-            st.error("Please upload your resume.")
-            return
-
-        with st.spinner("Analyzing..."):
-            # Extract resume text
-            resume_text = extract_text_from_pdf(uploaded_file)
-            if not resume_text:
-                st.error("Failed to extract text from resume.")
-                return
-
-            # Extract skills
-            resume_skills = extract_skills(resume_text)
-            job_skills = extract_skills(job_description_input)
-
-            # Find matches and gaps
-            matching_skills = set(resume_skills).intersection(set(job_skills))
-            missing_skills = set(job_skills) - set(resume_skills)
+    # Fetch job recommendations once resume is uploaded
+    if uploaded_file:
+        resume_text = extract_text_from_pdf(uploaded_file)
+        if resume_text:
+            st.success("Resume uploaded successfully!")
+            # Fetch job recommendations
+            jobs = get_job_recommendations(resume_text)
+            if jobs:
+                # Display job recommendations with selection
+                job_titles = [f"{job['title']} at {job['company']}" for job in jobs]
+                selected_job = st.selectbox("Select a job for Skill Matching:", job_titles)
+                if selected_job:
+                    # Find the selected job's details
+                    selected_index = job_titles.index(selected_job)
+                    selected_job_info = jobs[selected_index]
+                    job_description = selected_job_info['job_description']
+                    
+                    # Extract requirements
+                    requirements = extract_requirements(job_description)
+                    if not requirements:
+                        st.error("Failed to extract requirements.")
+                        return
+
+                    # Extract skills from resume
+                    resume_skills = extract_skills(resume_text)
+                    job_skills = extract_skills(job_description)
+
+                    # Find matches and gaps
+                    matching_skills = set(resume_skills).intersection(set(job_skills))
+                    missing_skills = set(job_skills) - set(resume_skills)
+
+                    # Display results
+                    st.subheader("Matching Skills")
+                    st.write(', '.join(matching_skills) if matching_skills else "No matching skills found.")
+
+                    st.subheader("Missing Skills")
+                    st.write(', '.join(missing_skills) if missing_skills else "No missing skills.")
+
+                    # Provide suggestions
+                    st.subheader("Suggestions for Improvement")
+                    if missing_skills:
+                        st.write("- **Acquire Missing Skills:** Consider pursuing courses or certifications in the following areas:")
+                        for skill in missing_skills:
+                            st.write(f"  - {skill}")
+                    else:
+                        st.write("You have all the required skills for this job!")
 
-            # Display results
-            st.subheader("Matching Skills")
-            st.write(', '.join(matching_skills) if matching_skills else "No matching skills found.")
+            else:
+                st.write("No job recommendations found based on your skills.")
+        else:
+            st.error("Failed to extract text from resume.")
+    else:
+        st.write("Please upload your resume to perform Skill Matching.")
 
-            st.subheader("Missing Skills")
-            st.write(', '.join(missing_skills) if missing_skills else "No missing skills.")
 
-# -------------------------------
-# Main App with Sidebar Navigation
-# -------------------------------
 
 def main():
     st.set_page_config(page_title="Job Application Assistant", layout="wide")