Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -1,23 +1,16 @@
|
|
1 |
import pandas as pd
|
2 |
import gradio as gr
|
3 |
-
from fastapi import FastAPI, Request
|
4 |
-
from fastapi.responses import JSONResponse
|
5 |
from retriever import get_relevant_passages
|
6 |
from reranker import rerank
|
7 |
|
8 |
-
# === FastAPI App ===
|
9 |
-
app = FastAPI()
|
10 |
-
|
11 |
# === Load and Clean CSV ===
|
12 |
def clean_df(df):
|
13 |
df = df.copy()
|
14 |
second_col = df.iloc[:, 2].astype(str)
|
15 |
-
|
16 |
if second_col.str.contains('http').any() or second_col.str.contains('www').any():
|
17 |
df["url"] = second_col
|
18 |
else:
|
19 |
df["url"] = "https://www.shl.com" + second_col.str.replace(r'^(?!/)', '/', regex=True)
|
20 |
-
|
21 |
df["remote_support"] = df.iloc[:, 3].map(lambda x: "Yes" if x == "T" else "No")
|
22 |
df["adaptive_support"] = df.iloc[:, 4].map(lambda x: "Yes" if x == "T" else "No")
|
23 |
df["test_type"] = df.iloc[:, 5].apply(lambda x: eval(x) if isinstance(x, str) else x)
|
@@ -32,7 +25,6 @@ except Exception as e:
|
|
32 |
print(f"Error loading data: {e}")
|
33 |
df_clean = pd.DataFrame(columns=["url", "adaptive_support", "remote_support", "description", "duration", "test_type"])
|
34 |
|
35 |
-
# === Utility ===
|
36 |
def validate_and_fix_urls(candidates):
|
37 |
for candidate in candidates:
|
38 |
if not isinstance(candidate, dict):
|
@@ -48,7 +40,6 @@ def validate_and_fix_urls(candidates):
|
|
48 |
candidate['url'] = f"https://www.shl.com{url}" if url.startswith('/') else f"https://www.shl.com/{url}"
|
49 |
return candidates
|
50 |
|
51 |
-
# === Recommendation Logic ===
|
52 |
def recommend(query):
|
53 |
if not query.strip():
|
54 |
return {"error": "Please enter a job description"}
|
@@ -74,31 +65,10 @@ def recommend(query):
|
|
74 |
return {"error": f"Error processing request: {str(e)}"}
|
75 |
|
76 |
# === Gradio UI ===
|
77 |
-
|
78 |
fn=recommend,
|
79 |
inputs=gr.Textbox(label="Enter Job Description", lines=4),
|
80 |
outputs="json",
|
81 |
title="SHL Assessment Recommender",
|
82 |
description="Paste a job description to get the most relevant SHL assessments."
|
83 |
-
)
|
84 |
-
|
85 |
-
# === FastAPI Endpoints ===
|
86 |
-
@app.get("/health")
|
87 |
-
async def health():
|
88 |
-
return JSONResponse(content={"status": "healthy"}, status_code=200)
|
89 |
-
|
90 |
-
@app.post("/recommend")
|
91 |
-
async def recommend_api(request: Request):
|
92 |
-
try:
|
93 |
-
data = await request.json()
|
94 |
-
query = data.get("query", "").strip()
|
95 |
-
if not query:
|
96 |
-
return JSONResponse(content={"error": "Missing query"}, status_code=400)
|
97 |
-
result = recommend(query)
|
98 |
-
return JSONResponse(content=result, status_code=200)
|
99 |
-
except Exception as e:
|
100 |
-
return JSONResponse(content={"error": str(e)}, status_code=500)
|
101 |
-
|
102 |
-
# === Mount Gradio to FastAPI ===
|
103 |
-
from gradio.routes import mount_gradio_app
|
104 |
-
app = mount_gradio_app(app, gr_interface, path="/")
|
|
|
1 |
import pandas as pd
|
2 |
import gradio as gr
|
|
|
|
|
3 |
from retriever import get_relevant_passages
|
4 |
from reranker import rerank
|
5 |
|
|
|
|
|
|
|
6 |
# === Load and Clean CSV ===
|
7 |
def clean_df(df):
|
8 |
df = df.copy()
|
9 |
second_col = df.iloc[:, 2].astype(str)
|
|
|
10 |
if second_col.str.contains('http').any() or second_col.str.contains('www').any():
|
11 |
df["url"] = second_col
|
12 |
else:
|
13 |
df["url"] = "https://www.shl.com" + second_col.str.replace(r'^(?!/)', '/', regex=True)
|
|
|
14 |
df["remote_support"] = df.iloc[:, 3].map(lambda x: "Yes" if x == "T" else "No")
|
15 |
df["adaptive_support"] = df.iloc[:, 4].map(lambda x: "Yes" if x == "T" else "No")
|
16 |
df["test_type"] = df.iloc[:, 5].apply(lambda x: eval(x) if isinstance(x, str) else x)
|
|
|
25 |
print(f"Error loading data: {e}")
|
26 |
df_clean = pd.DataFrame(columns=["url", "adaptive_support", "remote_support", "description", "duration", "test_type"])
|
27 |
|
|
|
28 |
def validate_and_fix_urls(candidates):
|
29 |
for candidate in candidates:
|
30 |
if not isinstance(candidate, dict):
|
|
|
40 |
candidate['url'] = f"https://www.shl.com{url}" if url.startswith('/') else f"https://www.shl.com/{url}"
|
41 |
return candidates
|
42 |
|
|
|
43 |
def recommend(query):
|
44 |
if not query.strip():
|
45 |
return {"error": "Please enter a job description"}
|
|
|
65 |
return {"error": f"Error processing request: {str(e)}"}
|
66 |
|
67 |
# === Gradio UI ===
|
68 |
+
gr.Interface(
|
69 |
fn=recommend,
|
70 |
inputs=gr.Textbox(label="Enter Job Description", lines=4),
|
71 |
outputs="json",
|
72 |
title="SHL Assessment Recommender",
|
73 |
description="Paste a job description to get the most relevant SHL assessments."
|
74 |
+
).launch()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|