Update app.py

app.py

@@ -1,29 +1,19 @@
-import os
-import openai
 import gradio as gr
-from keybert.llm import OpenAI as KeyBERTOpenAI
-from keybert import KeyLLM
+from keybert import KeyBERT
+from sentence_transformers import SentenceTransformer
 
-# 🔐 Load API key from Hugging Face Secrets
-api_key = os.environ.get("OPENAI_API_KEY")
-openai.api_key = api_key
-client = openai
-
-# 🔧 Initialize KeyLLM
-llm = KeyBERTOpenAI(client)
-kw_model = KeyLLM(llm)
+# ✅ Load Hugging Face model (no API key needed)
+model = SentenceTransformer('all-MiniLM-L6-v2')
+kw_model = KeyBERT(model)
 
+# 🔍 Keyword extraction function
 def extract_keywords(job_desc, resume_text, analyze_with_jd):
-    try:
-        if not resume_text.strip():
-            return "Please paste your resume text."
-
-        text = job_desc + "\n\n" + resume_text if analyze_with_jd and job_desc else resume_text
-        keywords = kw_model.extract_keywords([text], check_vocab=True)
-        return ", ".join(keywords[0]) if keywords else "No keywords found."
-    except Exception as e:
-        return f"❌ Error: {str(e)}"
+    if not resume_text.strip():
+        return "Please paste your resume."
 
+    text = job_desc + "\n\n" + resume_text if analyze_with_jd and job_desc else resume_text
+    keywords = kw_model.extract_keywords(text, top_n=10, stop_words='english')
+    return ", ".join([kw for kw, _ in keywords]) if keywords else "No keywords found."
 
 # 🎛️ Gradio UI
 with gr.Blocks() as demo:
@@ -35,8 +25,7 @@ with gr.Blocks() as demo:
         with gr.Column():
             output_keywords = gr.Textbox(label="Extracted Keywords", lines=12)
 
-    # Trigger keyword extraction when any input changes
-    job_desc.change(fn=extract_keywords, inputs=[job_desc, resume_text, analyze_checkbox], outputs=output_keywords)
     resume_text.change(fn=extract_keywords, inputs=[job_desc, resume_text, analyze_checkbox], outputs=output_keywords)
+    job_desc.change(fn=extract_keywords, inputs=[job_desc, resume_text, analyze_checkbox], outputs=output_keywords)
 
 demo.launch()