Update app.py

app.py

@@ -1,15 +1,16 @@
 import pandas as pd
 import gradio as gr
 from fastapi import FastAPI, Request
-from fastapi.responses import JSONResponse, RedirectResponse
+from fastapi.responses import JSONResponse
 from fastapi.middleware.cors import CORSMiddleware
+import traceback
 from retriever import get_relevant_passages
 from reranker import rerank
 
-# === Create FastAPI App ===
-app = FastAPI(title="SHL Assessment Recommender API")
+# Create FastAPI app
+app = FastAPI()
 
-# Add CORS middleware to allow cross-origin requests
+# Add CORS middleware
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"],
@@ -80,7 +81,6 @@ def recommend(query):
             result['recommended_assessments'] = validate_and_fix_urls(result['recommended_assessments'])
         return result
     except Exception as e:
-        import traceback
         print(traceback.format_exc())
         return {"error": f"Error processing request: {str(e)}"}
 
@@ -101,40 +101,23 @@ async def recommend_api(request: Request):
     except Exception as e:
         return JSONResponse(content={"error": str(e)}, status_code=500)
 
+# Create a Gradio interface
+demo = gr.Interface(
+    fn=recommend,
+    inputs=gr.Textbox(
+        label="Enter Job Description",
+        lines=4,
+        placeholder="Paste a job description here..."
+    ),
+    outputs=gr.JSON(label="Recommended Assessments"),
+    title="SHL Assessment Recommender",
+    description="Paste a job description to get the most relevant SHL assessments.",
+)
 
-# === Create Gradio Interface as a Separate App ===
-# For newer Gradio versions (5.x), create a standalone Gradio app
-with gr.Blocks(title="SHL Assessment Recommender") as demo:
-    gr.Markdown("# SHL Assessment Recommender")
-    gr.Markdown("Paste a job description to get the most relevant SHL assessments.")
-    
-    with gr.Row():
-        job_description = gr.Textbox(
-            label="Enter Job Description", 
-            lines=4, 
-            placeholder="Paste a job description here..."
-        )
-    
-    with gr.Row():
-        submit_btn = gr.Button("Get Recommendations", variant="primary")
-    
-    with gr.Row():
-        output = gr.JSON(label="Recommended Assessments")
-    
-    submit_btn.click(fn=recommend, inputs=job_description, outputs=output)
-
-# Add path to access Gradio directly at root
-@app.get("/")
-async def root():
-    return RedirectResponse(url="/")
-
-# For Hugging Face Spaces deployment with Gradio SDK
-app = gr.mount_gradio_app(app, demo)
+# This is the pattern for Gradio 5.x
+app = gr.mount_gradio_app(app, demo, path="/")
 
-# If running standalone (not through Hugging Face), use this instead
+# Entry point
 if __name__ == "__main__":
     import uvicorn
-    # Uncomment the line below if running locally not on HF
-    # uvicorn.run(app, host="0.0.0.0", port=7860)
-    # Use this for Hugging Face deployment
-    demo.launch()
+    uvicorn.run(app, host="0.0.0.0", port=7860)