Update app.py

app.py

@@ -1,65 +1,39 @@
-import openai  # ✅ Correct: lowercase 'openai' module from PyPI
-from keybert.llm import OpenAI as KeyBERTOpenAI
 import os
+import openai
 import gradio as gr
-import docx2txt
-import PyPDF2
-from keybert.llm import OpenAI
+from keybert.llm import OpenAI as KeyBERTOpenAI
 from keybert import KeyLLM
 
-# ✅ Get OpenAI token
+# 🔐 Load API key from Hugging Face Secrets
 api_key = os.environ.get("OPENAI_API_KEY")
-
-# ✅ Set up OpenAI client
 openai.api_key = api_key
 client = openai
 
-# ✅ Plug it into KeyLLM
+# 🔧 Initialize KeyLLM
 llm = KeyBERTOpenAI(client)
 kw_model = KeyLLM(llm)
 
-# Function to extract text from uploaded resume
-def extract_text(file):
-    if file is None:
-        return ""
-    ext = file.name.split('.')[-1].lower()
-    if ext == 'pdf':
-        reader = PyPDF2.PdfReader(file)
-        return "\n".join([page.extract_text() for page in reader.pages if page.extract_text()])
-    elif ext == 'docx':
-        return docx2txt.process(file.name)
-    else:
-        return "Unsupported file format."
-
-# Function to extract keywords using KeyLLM
-def extract_keywords_from_resume(job_desc, resume_file, analyze_with_jd):
-    resume_text = extract_text(resume_file)
+# 🧠 Extract keywords from pasted text
+def extract_keywords(job_desc, resume_text, analyze_with_jd):
     if not resume_text.strip():
-        return "Could not extract text from resume."
-
-    # Create combined document if analysis is requested
-    document = job_desc + "\n\n" + resume_text if analyze_with_jd and job_desc else resume_text
+        return "Please paste your resume text."
 
-    # Use KeyLLM to extract keywords
-    keywords = kw_model.extract_keywords([document], check_vocab=True)
+    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."
 
-# Gradio UI
+# 🎛️ Gradio UI
 with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
             analyze_checkbox = gr.Checkbox(label="Analyze with Job Description", value=True)
-            job_desc = gr.Textbox(label="Job Description", lines=6)
-            resume_file = gr.File(label="Upload Resume (PDF or DOCX)", file_types=[".pdf", ".docx"])
+            job_desc = gr.Textbox(label="Job Description", lines=6, placeholder="Paste job description here...")
+            resume_text = gr.Textbox(label="Resume Text", lines=12, placeholder="Paste resume content here...")
         with gr.Column():
-            output_keywords = gr.Textbox(label="Extracted Keywords", lines=10)
-
-    resume_file.change(fn=extract_keywords_from_resume,
-                       inputs=[job_desc, resume_file, analyze_checkbox],
-                       outputs=output_keywords)
+            output_keywords = gr.Textbox(label="Extracted Keywords", lines=12)
 
-    job_desc.change(fn=extract_keywords_from_resume,
-                    inputs=[job_desc, resume_file, analyze_checkbox],
-                    outputs=output_keywords)
+    # 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)
 
 demo.launch()