Update app.py

app.py

@@ -1,12 +1,15 @@
 import pandas as pd
 import gradio as gr
-import json
-from fastapi import FastAPI
+from fastapi import FastAPI, Request
 from fastapi.responses import JSONResponse
 from retriever import get_relevant_passages
 from reranker import rerank
+import uvicorn
 
-# Load and clean CSV
+# === FastAPI App ===
+app = FastAPI()
+
+# === Load and Clean CSV ===
 def clean_df(df):
     df = df.copy()
     second_col = df.iloc[:, 2].astype(str)
@@ -21,10 +24,8 @@ def clean_df(df):
     df["test_type"] = df.iloc[:, 5].apply(lambda x: eval(x) if isinstance(x, str) else x)
     df["description"] = df.iloc[:, 6]
     df["duration"] = pd.to_numeric(df.iloc[:, 9].astype(str).str.extract(r'(\d+)')[0], errors='coerce')
-
     return df[["url", "adaptive_support", "remote_support", "description", "duration", "test_type"]]
 
-# Load data and clean
 try:
     df = pd.read_csv("assesments.csv", encoding='utf-8')
     df_clean = clean_df(df)
@@ -32,7 +33,7 @@ except Exception as e:
     print(f"Error loading data: {e}")
     df_clean = pd.DataFrame(columns=["url", "adaptive_support", "remote_support", "description", "duration", "test_type"])
 
-# Fix URLs
+# === Utility ===
 def validate_and_fix_urls(candidates):
     for candidate in candidates:
         if not isinstance(candidate, dict):
@@ -48,7 +49,7 @@ def validate_and_fix_urls(candidates):
             candidate['url'] = f"https://www.shl.com{url}" if url.startswith('/') else f"https://www.shl.com/{url}"
     return candidates
 
-# Recommendation Logic
+# === Recommendation Logic ===
 def recommend(query):
     if not query.strip():
         return {"error": "Please enter a job description"}
@@ -73,24 +74,20 @@ def recommend(query):
         print(traceback.format_exc())
         return {"error": f"Error processing request: {str(e)}"}
 
-# Initialize Gradio App
-def gradio_interface(query):
-    return recommend(query)
-
-iface = gr.Interface(
-    fn=gradio_interface,
+# === Gradio UI ===
+gr_interface = gr.Interface(
+    fn=recommend,
     inputs=gr.Textbox(label="Enter Job Description", lines=4),
     outputs="json",
     title="SHL Assessment Recommender",
     description="Paste a job description to get the most relevant SHL assessments."
 )
 
-# FastAPI-like Health Endpoint in Gradio
+# === FastAPI Endpoints ===
 @app.get("/health")
 async def health():
     return JSONResponse(content={"status": "healthy"}, status_code=200)
 
-# FastAPI-like Recommendation Endpoint in Gradio
 @app.post("/recommend")
 async def recommend_api(request: Request):
     try:
@@ -103,11 +100,10 @@ async def recommend_api(request: Request):
     except Exception as e:
         return JSONResponse(content={"error": str(e)}, status_code=500)
 
-# Use Gradio app with the FastAPI app
-app = FastAPI()
-
-@app.on_event("startup")
-async def startup():
-    # Launch Gradio app when FastAPI app starts
-    iface.launch(inline=True, server_name="0.0.0.0", server_port=7860)
+# === Mount Gradio to FastAPI ===
+from gradio.routes import mount_gradio_app
+app = mount_gradio_app(app, gr_interface, path="/")
 
+# === Run App ===
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)