Update app.py

app.py

@@ -1,7 +1,31 @@
 import gradio as gr
+from transformers import pipeline
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Load your text-generation model from HF
+# (change "YourUsername/YourModel" to whichever model you want to use)
+generator = pipeline("text-generation", model="YourUsername/DeepSeek-R1")
+
+def generate_cv(name, education, experience):
+    # Build a "prompt" for your model
+    prompt = (
+        f"Generate a CV based on these details:\n"
+        f"Name: {name}\n"
+        f"Education: {education}\n"
+        f"Experience: {experience}\n"
+        "CV:\n"
+    )
+
+    # Call the pipeline to generate text (you can tweak max_length, etc.)
+    outputs = generator(prompt, max_length=300)
+    cv_text = outputs[0]["generated_text"]
+    return cv_text
+
+# Create a Gradio interface with 3 textboxes as input
+demo = gr.Interface(
+    fn=generate_cv, 
+    inputs=["text", "text", "text"],  # or gr.Textbox(…), etc.
+    outputs="text",
+    title="Automated CV Generator"
+)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
 demo.launch()