new gradio app
Browse files- app.py +20 -0
- requirements.txt +3 -0
app.py
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import gradio as gr
|
2 |
+
from sentence_transformers.cross_encoder import CrossEncoder
|
3 |
+
|
4 |
+
ce = CrossEncoder("cross-encoder/ms-marco-MiniLM-L6-v2")
|
5 |
+
|
6 |
+
def rerank(query, docs_list):
|
7 |
+
pairs = [[query, doc] for doc in docs_list]
|
8 |
+
scores = ce.predict(pairs)
|
9 |
+
sorted_docs = [doc for _, doc in sorted(zip(scores, docs_list), reverse=True)]
|
10 |
+
return sorted_docs, scores.tolist()
|
11 |
+
|
12 |
+
app = gr.Interface(
|
13 |
+
fn=rerank,
|
14 |
+
inputs=[gr.Textbox(label="Query"), gr.Textbox(label="Docs (JSON‑list)")],
|
15 |
+
outputs=[gr.Dataframe(type="array", headers=["doc","score"])],
|
16 |
+
api_name="rerank"
|
17 |
+
)
|
18 |
+
|
19 |
+
if __name__ == "__main__":
|
20 |
+
app.launch()
|
requirements.txt
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
gradio
|
2 |
+
sentence-transformers
|
3 |
+
torch
|