Duplicate from DeepLearning101/Customer-Service-Call_PaddleNLP-UIE

Co-authored-by: Deep Learning 101 <[email protected]>

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README.md

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+---
+title: Customer-Service-Call PaddleNLP-UIE
+emoji: 📊
+colorFrom: green
+colorTo: blue
+sdk: gradio
+sdk_version: 3.23.0
+app_file: app.py
+pinned: false
+license: mit
+duplicated_from: DeepLearning101/Customer-Service-Call_PaddleNLP-UIE
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+# -*- coding:utf-8 -*-
+from paddlenlp import Taskflow
+from hanziconv import HanziConv
+import json
+import gradio as gr
+
+def custompaddle(text): 
+
+    schema = ["观点词", "情感倾向[正向,负向,未提及]"]
+    aspects = ["服务", "价格"]
+    ie = Taskflow("sentiment_analysis", model="uie-senta-base", schema=schema, aspects=aspects)
+    output = ie(HanziConv.toSimplified(text))
+    return HanziConv.toTraditional(json.dumps(output, indent = 4, ensure_ascii = False))
+
+examples = [
+    ["請問劉小姐在嗎？謝謝您，沒關係喔；那還是說我晚一點再撥過來，謝謝您，再見沒關係。"],
+    ["謝謝您透過人員投保防癌定期健康保險保單，法令規定為了維護您的權益，希望可以用電話跟您說明保單重點，請問目前方便打擾您大概3分鐘嗎？"],
+    ["這個方案的時限很長，客戶服務很熱情，就是價格有點貴。"],    
+    ["客戶服務品質不錯，服務人員也很熱情，價格也說明得非常清楚。"],
+]
+    
+demo = gr.Interface(
+    fn=custompaddle,
+    inputs=gr.inputs.Textbox(label="客服電訪質檢原始語音文本內容"),
+    outputs=gr.outputs.Textbox(label="客服電訪質檢之情感信息擷取結果"),
+    examples=examples,
+    title="<p style='text-align: center'><a href='https://www.twman.org/AI' target='_blank'>客服電訪質檢：PaddleNLP 的 Senta-UIE</a>",
+    description=(
+        "這是將情感信息分析擷取應用在客服電訪質檢，使用的是 PaddleNLP 的 Senta-UIE，並搭配 doccano 另外自行標註了數據，fine-tuning 前的結果；但只用CPU，所以不快"
+    ),    
+)
+
+demo.launch(debug=True)

requirements.txt

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+paddlepaddle == 2.3.2
+paddlenlp == 2.5.2
+wordcloud == 1.8.2.2
+hanziconv