Update app.py

app.py

@@ -8,6 +8,8 @@ from bs4 import BeautifulSoup
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
 def extract_text_from_pdf(file):
+    if file is None:
+        return ""
     reader = PdfReader(file)
     text = ""
     for page in reader.pages:
@@ -24,7 +26,7 @@ def ats_friendly_checker(file):
         max_tokens=512,
         temperature=0.7,
         top_p=0.95
-    ).choices[0].message["content"]
+    ).choices[0].message.content
     
     score = response.split("\n")[0].split(":")[-1].strip()
     feedback = "\n".join(response.split("\n")[1:])
@@ -47,7 +49,7 @@ def resume_match_checker(file, job_url):
         max_tokens=512,
         temperature=0.7,
         top_p=0.95
-    ).choices[0].message["content"]
+    ).choices[0].message.content
 
     match_score = response.split(":")[-1].strip()
     return match_score
@@ -55,17 +57,19 @@ def resume_match_checker(file, job_url):
 def resume_quality_score(file):
     resume_text = extract_text_from_pdf(file)
     # Implement resume quality scoring logic using LLM
-    system_message = "Evaluate the following resume for overall quality and provide a score."
+    system_message = "Evaluate the following resume for overall quality and provide a score and interpretation."
     message = resume_text
     response = client.chat_completion(
         [{"role": "system", "content": system_message}, {"role": "user", "content": message}],
         max_tokens=512,
         temperature=0.7,
         top_p=0.95
-    ).choices[0].message["content"]
+    ).choices[0].message.content
 
-    quality_score = response.split(":")[-1].strip()
-    return quality_score
+    score_lines = response.split("\n")
+    quality_score = score_lines[0].split(":")[-1].strip()
+    interpretation = "\n".join(score_lines[1:])
+    return quality_score, interpretation
 
 def text_to_overleaf(resume_text):
     # Implement the conversion to Overleaf code using LLM
@@ -76,7 +80,7 @@ def text_to_overleaf(resume_text):
         max_tokens=512,
         temperature=0.7,
         top_p=0.95
-    ).choices[0].message["content"]
+    ).choices[0].message.content
     
     overleaf_code = response
     return overleaf_code
@@ -103,7 +107,8 @@ with gr.Blocks() as demo:
         with gr.Row():
             resume = gr.File(label="Upload your Resume (PDF)")
             quality_score = gr.Number(label="Quality Score", interactive=False)
-        resume.upload(resume_quality_score, resume, quality_score)
+            interpretation = gr.Textbox(label="Interpretation", interactive=False)
+        resume.upload(resume_quality_score, resume, [quality_score, interpretation])
     
     with gr.Tab("Text to Overleaf Code"):
         with gr.Row():
@@ -114,4 +119,4 @@ with gr.Blocks() as demo:
     gr.Markdown("---\nBuilt with love by [Bahae Eddine HALIM](https://www.linkedin.com/in/halimbahae/)")
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(share=True)