Update app.py

app.py

@@ -1,5 +1,4 @@
 # app.py
-
 import os
 import gradio as gr
 from PyPDF2 import PdfReader
@@ -13,7 +12,7 @@ from google.genai.types import GenerateContentConfig, ThinkingConfig
 from datetime import datetime
 
 # Initialize components
-kw_extractor = yake.KeywordExtractor(n=1, top=10)
+kw_extractor = yake.KeywordExtractor(n=2, top=20)
 embedder = SentenceTransformer("all-MiniLM-L6-v2")
 genai_client = genai.Client(api_key=os.getenv("GEMINI_API_KEY"))
 
@@ -32,8 +31,18 @@ def extract_text(file):
     return ""
 
 # 2️⃣ Extract keywords using YAKE
-def get_keywords(text):
-    return [k for k, _ in kw_extractor.extract_keywords(text)][:5]
+def extract_keywords(text):
+    """
+    Returns the top 20 1–2‑gram keywords from the text.
+    """
+    kws = kw_extractor.extract_keywords(text)
+    # kws is list of (keyword, score). We only want the keyword string.
+    return [kw for kw,score in kws]
+
+def on_resume_upload(file):
+    text = extract_text(file)
+    kws = extract_keywords(text)
+    return ", ".join(kws)
 
 # 3️⃣ Fetch jobs from free public APIs
 def fetch_arbeitnow(keywords):
@@ -89,9 +98,9 @@ def format_posted(job):
 def find_jobs(file, added_kw, use_ai):
     resume = extract_text(file) or ""
     print("Resume", resume)
-    extracted = get_keywords(resume)
-    print("Extracted", extracted)
-    keywords = [kw.strip() for kw in added_kw.split(",") if kw.strip()] or extracted
+    base_kws = added_kw.split(",") if added_kw.strip() else extract_keywords(resume)[:5]
+    print("Base_kws", base_kws)
+    keywords = [kw.strip() for kw in base_kws if kw.strip()]
     print("Keywords", keywords)
     jobs = fetch_arbeitnow(keywords) + fetch_remotive(keywords) + fetch_remoteok(keywords)
     print("Jobs", jobs)
@@ -120,25 +129,29 @@ def find_jobs(file, added_kw, use_ai):
     return table, explanation
 
 # 7️⃣ Jobs in Markdown
-def jobs_to_markdown(table):
+def jobs_to_markdown(table, explanation):
+    # Build the markdown table
     md  = "| Role | Company | Location | Posted | Score | Apply |\n"
     md += "| ---  | ------- | -------- | ------ | ----- | ----- |\n"
     for row in table:
         link = f"[Apply]({row['Apply']})" if row['Apply'] else ""
         md += (
-            f"| {row['Role']} | {row['Company']} "
-            f"| {row['Location']} | {row['Posted']} "
-            f"| {row['Score']} | {link} |\n"
+            f"| {row['Role']} | {row['Company']} | {row['Location']} "
+            f"| {row['Posted']} | {row['Score']} | {link} |\n"
         )
+    # Append the AI explanation, if any
+    if explanation:
+        md += "\n---\n**AI Explanation:**\n\n" + explanation
     return md
 
-
 # 7️⃣ Gradio UI
-with gr.Blocks() as demo:
+with gr.Blocks(theme=gr.themes.Base()) as demo:
     gr.Markdown("## 🌍 Global Job Finder (Arbeitnow · Remotive · RemoteOK)")
     with gr.Row():
         resume = gr.File(label="Upload Resume (PDF/DOCX)")
         added = gr.Textbox(label="Add keywords (comma-separated)", placeholder="e.g. Python, ML")
+
+    resume.upload(on_resume_upload, inputs=[resume], outputs=[added])
     use_ai = gr.Checkbox(label="Use AI to refine explanation", value=False)
     btn = gr.Button("Find Jobs")
     jobs_md = gr.Markdown()