Update app.py

app.py

@@ -16,15 +16,9 @@ def extract_text_from_pdf(file):
         text += page.extract_text()
     return text
 
-def parse_score(score_text):
-    try:
-        return float(score_text.strip('%').strip()) / 100
-    except ValueError:
-        return None
-
 def ats_friendly_checker(file):
     resume_text = extract_text_from_pdf(file)
-    system_message = "Evaluate the following resume for ATS-friendliness and provide a score and feedback."
+    system_message = "Evaluate the following resume for ATS-friendliness and provide feedback."
     message = resume_text
     response = client.chat_completion(
         [{"role": "system", "content": system_message}, {"role": "user", "content": message}],
@@ -33,15 +27,8 @@ def ats_friendly_checker(file):
         top_p=0.95
     ).choices[0].message.content
     
-    score_text = response.split("\n")[0].split(":")[-1].strip()
-    feedback = "\n".join(response.split("\n")[1:])
-    score = parse_score(score_text)
-    if score is not None:
-        score *= 100  # Convert to percentage
-    else:
-        score = 0
-        feedback = "Error parsing score from the response."
-    return score, feedback
+    feedback = response
+    return feedback
 
 def scrape_job_description(url):
     response = requests.get(url)
@@ -52,7 +39,7 @@ def scrape_job_description(url):
 def resume_match_checker(file, job_url):
     resume_text = extract_text_from_pdf(file)
     job_description = scrape_job_description(job_url)
-    system_message = "Compare the following resume with the job description and provide a match score and feedback."
+    system_message = "Compare the following resume with the job description and provide feedback."
     message = f"Resume: {resume_text}\n\nJob Description: {job_description}"
     response = client.chat_completion(
         [{"role": "system", "content": system_message}, {"role": "user", "content": message}],
@@ -61,19 +48,12 @@ def resume_match_checker(file, job_url):
         top_p=0.95
     ).choices[0].message.content
 
-    match_score_text = response.split(":")[-1].strip()
-    feedback = "\n".join(response.split("\n")[1:])
-    match_score = parse_score(match_score_text)
-    if match_score is not None:
-        match_score *= 100  # Convert to percentage
-    else:
-        match_score = 0
-        feedback = "Error parsing match score from the response."
-    return match_score, feedback
+    feedback = response
+    return feedback
 
 def resume_quality_score(file):
     resume_text = extract_text_from_pdf(file)
-    system_message = "Evaluate the following resume for overall quality and provide a score and interpretation."
+    system_message = "Evaluate the following resume for overall quality and provide feedback."
     message = resume_text
     response = client.chat_completion(
         [{"role": "system", "content": system_message}, {"role": "user", "content": message}],
@@ -82,16 +62,8 @@ def resume_quality_score(file):
         top_p=0.95
     ).choices[0].message.content
 
-    score_lines = response.split("\n")
-    quality_score_text = score_lines[0].split(":")[-1].strip()
-    interpretation = "\n".join(score_lines[1:])
-    quality_score = parse_score(quality_score_text)
-    if quality_score is not None:
-        quality_score *= 100  # Convert to percentage
-    else:
-        quality_score = 0
-        interpretation = "Error parsing quality score from the response."
-    return quality_score, interpretation
+    interpretation = response
+    return interpretation
 
 def text_to_overleaf(resume_text):
     system_message = "Convert the following resume text to Overleaf code."
@@ -113,29 +85,26 @@ with gr.Blocks() as demo:
     with gr.Tab("ATS-Friendly Checker"):
         with gr.Row():
             resume = gr.File(label="Upload your Resume (PDF)")
-            score = gr.Number(label="ATS Score", interactive=False)
-            feedback = gr.Textbox(label="Feedback", interactive=False)
-        resume.upload(ats_friendly_checker, resume, [score, feedback])
+            feedback = gr.Textbox(label="Feedback", interactive=False, lines=15, max_lines=50)  # Increase lines to fill the page
+        resume.upload(ats_friendly_checker, resume, feedback)
     
     with gr.Tab("Resume Match Checker"):
         with gr.Row():
             resume = gr.File(label="Upload your Resume (PDF)")
             job_url = gr.Textbox(label="Job Description URL")
-            match_score = gr.Number(label="Match Score", interactive=False)
-            feedback = gr.Textbox(label="Feedback", interactive=False)
-        gr.Button("Check Match").click(resume_match_checker, [resume, job_url], [match_score, feedback])
+            feedback = gr.Textbox(label="Feedback", interactive=False, lines=15, max_lines=50)  # Increase lines to fill the page
+        gr.Button("Check Match").click(resume_match_checker, [resume, job_url], feedback)
     
     with gr.Tab("Resume Quality Score"):
         with gr.Row():
             resume = gr.File(label="Upload your Resume (PDF)")
-            quality_score = gr.Number(label="Quality Score", interactive=False)
-            interpretation = gr.Textbox(label="Interpretation", interactive=False)
-        resume.upload(resume_quality_score, resume, [quality_score, interpretation])
+            interpretation = gr.Textbox(label="Interpretation", interactive=False, lines=15, max_lines=50)  # Increase lines to fill the page
+        resume.upload(resume_quality_score, resume, interpretation)
     
     with gr.Tab("Text to Overleaf Code"):
         with gr.Row():
             resume_text = gr.Textbox(label="Resume Text")
-            overleaf_code = gr.Textbox(label="Overleaf Code", interactive=False)
+            overleaf_code = gr.Textbox(label="Overleaf Code", interactive=False, lines=15, max_lines=50)  # Increase lines to fill the page
         resume_text.submit(text_to_overleaf, resume_text, overleaf_code)
 
     gr.Markdown("---\nBuilt with love by [Bahae Eddine HALIM](https://www.linkedin.com/in/halimbahae/)")