Create app.py

app.py

@@ -0,0 +1,148 @@
+import os
+import re
+import requests
+import gradio as gr
+from pypdf import PdfReader
+from docx import Document
+
+JSEARCH_API_KEY = os.getenv("JSEARCH_API_KEY")
+
+SKILLS = [
+    "python", "java", "javascript", "html", "css", "sql", "linux",
+    "networking", "troubleshooting", "technical support", "it support",
+    "database", "cloud", "aws", "azure", "sap", "system administration",
+    "git", "api", "machine learning", "nlp"
+]
+
+def extract_text(file):
+    if file is None:
+        return ""
+
+    path = file.name
+
+    if path.endswith(".pdf"):
+        reader = PdfReader(path)
+        return "\n".join(page.extract_text() or "" for page in reader.pages)
+
+    if path.endswith(".docx"):
+        doc = Document(path)
+        return "\n".join(p.text for p in doc.paragraphs)
+
+    if path.endswith(".txt"):
+        with open(path, "r", encoding="utf-8", errors="ignore") as f:
+            return f.read()
+
+    return ""
+
+def extract_skills(cv_text):
+    text = cv_text.lower()
+    found = []
+
+    for skill in SKILLS:
+        if skill in text:
+            found.append(skill.title())
+
+    return found
+
+def search_jobs(skills, location):
+    if not JSEARCH_API_KEY:
+        return []
+
+    query = " ".join(skills[:5]) + f" jobs in {location}"
+
+    headers = {
+        "X-API-Key": JSEARCH_API_KEY
+    }
+
+    response = requests.get(
+        "https://api.openwebninja.com/jsearch/search-v2",
+        params={"query": query},
+        headers=headers
+    )
+
+    if response.status_code != 200:
+        return []
+
+    data = response.json()
+
+    return data.get("jobs", data.get("data", []))
+
+def calculate_match(cv_skills, job):
+    job_text = (
+        str(job.get("title", "")) + " " +
+        str(job.get("description", "")) + " " +
+        str(job.get("snippet", ""))
+    ).lower()
+
+    matched = []
+
+    for skill in cv_skills:
+        if skill.lower() in job_text:
+            matched.append(skill)
+
+    score = int((len(matched) / max(len(cv_skills), 1)) * 100)
+
+    return score, matched
+
+def analyze_cv(file, location):
+    cv_text = extract_text(file)
+
+    if not cv_text.strip():
+        return "Could not extract text from the CV."
+
+    skills = extract_skills(cv_text)
+
+    if not skills:
+        return "No clear skills detected. Try uploading a more detailed CV."
+
+    jobs = search_jobs(skills, location)
+
+    if not jobs:
+        return f"Detected skills: {', '.join(skills)}\n\nNo jobs found. Check your API key or try another location."
+
+    results = []
+
+    for job in jobs[:10]:
+        score, matched = calculate_match(skills, job)
+
+        title = job.get("title", "Unknown Job")
+        company = job.get("company_name", job.get("company", "Unknown Company"))
+        location_name = job.get("location", "Not specified")
+        url = job.get("url", job.get("apply_link", "#"))
+
+        results.append({
+            "score": score,
+            "title": title,
+            "company": company,
+            "location": location_name,
+            "matched": matched,
+            "url": url
+        })
+
+    results = sorted(results, key=lambda x: x["score"], reverse=True)
+
+    output = f"## Skills Detected\n{', '.join(skills)}\n\n"
+    output += "## Best Job Matches\n\n"
+
+    for job in results:
+        output += f"### {job['title']} — {job['score']}% Match\n"
+        output += f"**Company:** {job['company']}\n\n"
+        output += f"**Location:** {job['location']}\n\n"
+        output += f"**Matched Skills:** {', '.join(job['matched']) if job['matched'] else 'None'}\n\n"
+        output += f"[Apply Here]({job['url']})\n\n---\n\n"
+
+    return output
+
+demo = gr.Interface(
+    fn=analyze_cv,
+    inputs=[
+        gr.File(label="Upload your CV", file_types=[".pdf", ".docx", ".txt"]),
+        gr.Textbox(label="Job Location", value="Mauritius")
+    ],
+    outputs=gr.Markdown(label="Job Matches"),
+    title="JobFit AI",
+    description="Upload your CV and get real job matches based on your skills."
+)
+
+if __name__ == "__main__":
+    demo.launch()