Made it look better :)

app.py

@@ -1,58 +1,49 @@
-import gradio as gr
-import io
-from PyPDF2 import PdfReader
-from app import create_agent
+import yaml
+from smolagents import CodeAgent, HfApiModel
+from smolagents.tools import Tool
+from tools.resumescraper import ResumeScraperTool
+from huggingface_hub import InferenceClient
 
-def extract_text_from_pdf(file_obj) -> str:
-    reader = PdfReader(file_obj)
-    text = ""
-    for page in reader.pages:
-        page_text = page.extract_text()
-        if page_text:
-            text += page_text + "\n"
-    return text
-
-def process_resume(input_method, resume_text, pdf_file):
-    if input_method == "Text":
-        text = resume_text
-    else:
-        if pdf_file is None:
-            return "No PDF uploaded."
-        # Check if pdf_file is a string (i.e. a file path) or a file-like object
-        if isinstance(pdf_file, str):
-            with open(pdf_file, "rb") as f:
-                file_bytes = f.read()
-        else:
-            file_bytes = pdf_file.read()
-        file_obj = io.BytesIO(file_bytes)
-        text = extract_text_from_pdf(file_obj)
-    
-    if not text.strip():
-        return "No resume text found."
-    
-    agent = create_agent()
-    # Instruct the agent to roast the resume using the resume text.
-    response = agent.run(f"Roast this resume: {text}")
-    return response
+class FinalAnswerTool(Tool):
+    name = "final_answer"
+    description = "Use this tool to provide your final roast"
+    inputs = {
+        "answer": {
+            "type": "string",
+            "description": "The final roast for the resume"
+        }
+    }
+    output_type = "string"
 
+    def forward(self, answer: str) -> str:
+        return answer
 
-def toggle_inputs(method):
-    if method == "Text":
-        return gr.update(visible=True), gr.update(visible=False)
-    else:
-        return gr.update(visible=False), gr.update(visible=True)
-
-with gr.Blocks() as demo:
-    gr.Markdown("# Resume Roaster")
-    gr.Markdown("Enter your resume as text or upload a PDF to receive a humorous, professional roast!")
+def create_agent():
+    final_answer = FinalAnswerTool()
+    resume_scraper = ResumeScraperTool()
     
-    input_method = gr.Radio(choices=["Text", "PDF"], label="Input Method", value="Text")
-    resume_text = gr.Textbox(label="Resume Text", lines=10, visible=True)
-    pdf_file = gr.File(label="Upload Resume PDF", file_types=[".pdf"], visible=False)
-    output = gr.Textbox(label="Roast Result", lines=10)
-    submit_btn = gr.Button("Roast It!")
+    # Instantiate HfApiModel using Qwen/Qwen2.5-Coder-32B-Instruct for roasting.
+    model = HfApiModel(
+        max_tokens=2096,
+        temperature=0.5,
+        model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
+        custom_role_conversions=None,
+    )
     
-    input_method.change(fn=toggle_inputs, inputs=input_method, outputs=[resume_text, pdf_file])
-    submit_btn.click(fn=process_resume, inputs=[input_method, resume_text, pdf_file], outputs=output)
+    # Create a dedicated InferenceClient using your public endpoint
+    client = InferenceClient("https://jc26mwg228mkj8dw.us-east-1.aws.endpoints.huggingface.cloud")
+    # Override the model's client with our dedicated client
+    model.client = client
+
+    with open("prompts.yaml", 'r') as stream:
+        prompt_templates = yaml.safe_load(stream)
+        
+    agent = CodeAgent(
+        model=model,
+        tools=[resume_scraper, final_answer],
+        max_steps=6,
+        verbosity_level=1,
+        prompt_templates=prompt_templates
+    )
     
-demo.launch(share=True)
+    return agent

main.py

@@ -24,7 +24,6 @@ def process_resume(input_method, resume_text, pdf_file):
                 file_bytes = f.read()
         else:
             file_bytes = pdf_file.read()
-        import io
         file_obj = io.BytesIO(file_bytes)
         text = extract_text_from_pdf(file_obj)
     
@@ -32,28 +31,76 @@ def process_resume(input_method, resume_text, pdf_file):
         return "No resume text found."
     
     agent = create_agent()
-    # Directly run the agent to roast the resume. With our updated prompts,
-    # the agent should output plain text that we can simply print.
+    # Use the agent to roast the resume.
     response = agent.run(f"Roast this resume: {text}")
     return response
 
 def toggle_inputs(method):
+    # Updated order: pdf_file first, then resume_text.
     if method == "Text":
-        return gr.update(visible=True), gr.update(visible=False)
-    else:
         return gr.update(visible=False), gr.update(visible=True)
+    else:
+        return gr.update(visible=True), gr.update(visible=False)
+
+css_custom = """
+footer {visibility: hidden;}
+.center { 
+  margin: 0 auto; 
+  text-align: center; 
+}
+@keyframes beat {
+  0%, 20%, 40%, 60%, 80%, 100% { transform: scale(1); }
+  10%, 30%, 50%, 70%, 90% { transform: scale(1.2); }
+}
+.beating-heart {
+  display: inline-block;
+  animation: beat 2s infinite;
+}
+.fire-effect {
+  font-size: 2.5em;
+  font-weight: bold;
+  background: linear-gradient(45deg, red, orange, yellow);
+  background-size: 200%;
+  -webkit-background-clip: text;
+  -webkit-text-fill-color: transparent;
+  animation: fireAnimation 3s linear infinite;
+}
+@keyframes fireAnimation {
+  0% { background-position: 0%; }
+  50% { background-position: 100%; }
+  100% { background-position: 0%; }
+}
+/* Center the radio button options */
+div[role="radiogroup"] {
+  display: flex;
+  justify-content: center;
+}
+"""
 
-with gr.Blocks() as demo:
-    gr.Markdown("# Resume Roaster")
-    gr.Markdown("Enter your resume as text or upload a PDF to receive a humorous, professional roast!")
+with gr.Blocks(css=css_custom) as demo:
+    with gr.Column(elem_classes="center"):
+        gr.Markdown('<div class="fire-effect">Resume Roaster</div>')
+        gr.Markdown("Upload your resume as a PDF (default) or paste the text to receive a humorous, professional roast!")
     
-    input_method = gr.Radio(choices=["Text", "PDF"], label="Input Method", value="Text")
-    resume_text = gr.Textbox(label="Resume Text", lines=10, visible=True)
-    pdf_file = gr.File(label="Upload Resume PDF", file_types=[".pdf"], visible=False)
-    output = gr.Textbox(label="Roast Result", lines=10)
-    submit_btn = gr.Button("Roast It!")
+        # Reordered radio choices so that PDF is first.
+        input_method = gr.Radio(choices=["PDF", "Text"], label="Input Method", value="PDF")
+        # PDF upload comes first
+        pdf_file = gr.File(label="Upload Resume PDF", file_types=[".pdf"], visible=True)
+        resume_text = gr.Textbox(label="Resume Text", lines=10, visible=False)
+        output = gr.Textbox(label="Roast Result", lines=10)
+        submit_btn = gr.Button("Roast It!")
     
-    input_method.change(fn=toggle_inputs, inputs=input_method, outputs=[resume_text, pdf_file])
+    # Adjusted toggle outputs to match new order.
+    input_method.change(fn=toggle_inputs, inputs=input_method, outputs=[pdf_file, resume_text])
     submit_btn.click(fn=process_resume, inputs=[input_method, resume_text, pdf_file], outputs=output)
     
-demo.launch(share=True)
+    gr.Markdown(
+        """
+        <div id="custom_footer" style="text-align: center; margin-top: 20px; font-size: 14px;">
+          Made with <span class="beating-heart">💓</span> by Kuber Mehta<br>
+          All jokes are crafted in good humor to provide professional levity.
+        </div>
+        """
+    )
+
+demo.launch(share=False)

prompts.yaml

@@ -3,12 +3,14 @@ system_prompt: |
   Your job is to create a humorous, professional roast of a resume.
   Focus on teasing overly verbose descriptions, excessive buzzwords, and generic statements,
   while keeping the tone light and appropriate for a professional setting.
+  
 task_prompt: |
   Using the provided resume details, craft a roast that:
   1. References key sections such as Summary, Experience, Education, and Skills.
   2. Is humorous but not mean-spirited.
   3. Maintains a professional tone.
   4. Adds creative flair that makes the roast both entertaining and insightful.
+
 final_answer:
   pre_messages: "Final Roast:"
   post_messages: ""

tools/resumescraper.py

@@ -46,4 +46,4 @@ class ResumeScraperTool(Tool):
             end = lower_text.find("\n\n", start)
             sections["skills"] = resume_text[start + len("skills:"): end].strip() if end != -1 else resume_text[start + len("skills:"):].strip()
 
-        return sections
+        return sections