Update app.py

app.py

@@ -1,28 +1,40 @@
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
+from transformers import AutoModel, AutoTokenizer
+from peft import PeftModel
 import torch
+import torch.nn.functional as F
 
-# Load model
-model_name = "shashu2325/resume-job-matcher-lora"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSequenceClassification.from_pretrained(model_name)
+# Load models
+base_model = AutoModel.from_pretrained("BAAI/bge-large-en-v1.5")
+model = PeftModel.from_pretrained(base_model, "shashu2325/resume-job-matcher-lora")
+tokenizer = AutoTokenizer.from_pretrained("BAAI/bge-large-en-v1.5")
+
+def get_match_score(resume_text, job_text):
+    resume_inputs = tokenizer(resume_text, return_tensors="pt", max_length=512, padding="max_length", truncation=True)
+    job_inputs = tokenizer(job_text, return_tensors="pt", max_length=512, padding="max_length", truncation=True)
 
-def match_resume(resume_text, job_text):
-    inputs = tokenizer(resume_text, job_text, return_tensors="pt", truncation=True)
     with torch.no_grad():
-        outputs = model(**inputs)
-        score = torch.nn.functional.softmax(outputs.logits, dim=1)[0][1].item()
+        resume_outputs = model(**resume_inputs)
+        job_outputs = model(**job_inputs)
+
+        resume_emb = resume_outputs.last_hidden_state.mean(dim=1)
+        job_emb = job_outputs.last_hidden_state.mean(dim=1)
+
+        resume_emb = F.normalize(resume_emb, p=2, dim=1)
+        job_emb = F.normalize(job_emb, p=2, dim=1)
+
+        similarity = torch.sum(resume_emb * job_emb, dim=1)
+        score = torch.sigmoid(similarity).item()
+
     return f"Match Score: {score*100:.2f}%"
 
-demo = gr.Interface(
-    fn=match_resume,
+gr.Interface(
+    fn=get_match_score,
     inputs=[
-        gr.Textbox(label="Resume Text", lines=15),
-        gr.Textbox(label="Job Description", lines=15),
+        gr.Textbox(label="Resume Text", lines=12, placeholder="Paste resume here..."),
+        gr.Textbox(label="Job Description", lines=12, placeholder="Paste job description here...")
     ],
     outputs="text",
     title="Resume-Job Matcher",
-    description="Paste a resume and a job description to get a match score."
-)
-
-demo.launch()
+    description="Upload resume and job description to get a match score using LoRA fine-tuned BGE model."
+).launch()