Update app.py

app.py

@@ -1,26 +1,26 @@
-import gradio as gr
+from fastapi import FastAPI
+from pydantic import BaseModel
 from transformers import pipeline
 
-# Load your model from the Hub
+# Load model
 generator = pipeline(
-    "summarization",  # officially supported tag
+    "summarization",  # use summarization since text2text-generation is deprecated in HF metadata
     model="andersondequan5/checkin-bart-model",
     tokenizer="andersondequan5/checkin-bart-model"
 )
 
-# Function to expand check-in
-def expand_checkin(task: str):
-    result = generator(task, max_length=200, num_beams=4, do_sample=False)
-    return result[0]["summary_text"]
+# FastAPI app
+app = FastAPI(title="Check-In Expansion API")
 
-# Gradio Interface
-demo = gr.Interface(
-    fn=expand_checkin,
-    inputs=gr.Textbox(lines=3, placeholder="Enter a short task like: 'fix API routes and write docs'"),
-    outputs="text",
-    title="Check-In Expansion API",
-    description="Submit a short input task and get a polished daily check-in expansion."
-)
+# Request/Response schema
+class CheckInRequest(BaseModel):
+    task: str
+
+class CheckInResponse(BaseModel):
+    checkin: str
 
-if __name__ == "__main__":
-    demo.launch()
+@app.post("/predict", response_model=CheckInResponse)
+def predict(request: CheckInRequest):
+    """Expand a short input into a detailed check-in."""
+    result = generator(request.task, max_length=200, num_beams=4, do_sample=False)
+    return {"checkin": result[0]["summary_text"]}