Create app.py

app.py

@@ -0,0 +1,97 @@
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+# Initialize the Inference Client
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+
+def ats_friendly_checker(resume):
+    # Implement the ATS-friendly checker logic here
+    # For demonstration, we'll return a mock score and feedback
+    score = 75  # Mock score
+    feedback = "Your resume needs more keywords related to the job."
+    return score, feedback
+
+def resume_match_checker(resume, job_description):
+    # Implement the resume match logic here
+    # For demonstration, we'll return a mock match score
+    match_score = 80  # Mock match score
+    return match_score
+
+def resume_quality_score(resume):
+    # Implement the resume quality scoring logic here
+    # For demonstration, we'll return a mock quality score
+    quality_score = 85  # Mock quality score
+    return quality_score
+
+def text_to_overleaf(resume_text):
+    # Implement the conversion to Overleaf code here
+    # For demonstration, we'll return a mock Overleaf code
+    overleaf_code = "Mock Overleaf Code"
+    return overleaf_code
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
+
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    messages.append({"role": "user", "content": message})
+
+    response = ""
+
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+    ):
+        token = message.choices[0].delta.content
+
+        response += token
+        yield response
+
+# Define the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Resume Enhancement Tool\nEnhance your resume with the following features.")
+    
+    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])
+    
+    with gr.Tab("Resume Match Checker"):
+        with gr.Row():
+            resume = gr.File(label="Upload your Resume (PDF)")
+            job_description = gr.Textbox(label="Job Description")
+            match_score = gr.Number(label="Match Score", interactive=False)
+        resume.upload(resume_match_checker, [resume, job_description], match_score)
+    
+    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)
+        resume.upload(resume_quality_score, resume, quality_score)
+    
+    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)
+        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/)")
+
+if __name__ == "__main__":
+    demo.launch()