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app.py

@@ -1,37 +1,37 @@
-# app.py
-import gradio as gr
-from pyabsa import ATEPCCheckpointManager
-
-# 모델 로딩 (최초 실행 시 약간 시간 소요)
-aspect_extractor = ATEPCCheckpointManager.get_aspect_sentiment_extractor(
-    checkpoint='yangheng/deberta-v3-base-absa-v1.1'
-)
-
-def analyze_aspects(text, aspect_input):
-    aspects = [a.strip() for a in aspect_input.split(",") if a.strip()]
-    pair_list = [[text, aspect] for aspect in aspects]
-
-    result = aspect_extractor.extract_aspect_sentiment_inference(
-        inference_source=[text],
-        aspect_sentiment_pair_list=pair_list
-    )
-
-    output = ""
-    for res in result:
-        for aspect, sentiment in res["aspect_sentiment_pair"]:
-            output += f"- **{aspect}** → **{sentiment}**\n"
-    return output
-
-# Gradio 인터페이스 설정
-iface = gr.Interface(
-    fn=analyze_aspects,
-    inputs=[
-        gr.Textbox(label="입력 문장", placeholder="예: The food was great but the service was slow."),
-        gr.Textbox(label="속성 목록 (쉼표로 구분)", placeholder="예: food, service")
-    ],
-    outputs=gr.Markdown(label="감정 분석 결과"),
-    title="ABSA 감정 분석기 (DeBERTa v3)",
-    description="문장과 속성(aspect)를 입력하면 속성별 감정을 추출합니다. 모델: yangheng/deberta-v3-base-absa-v1.1"
-)
-
-iface.launch()
+import gradio as gr
+from pyabsa import AspectSentimentClassification as ASC
+
+# 모델 로드
+aspect_extractor = ASC.SentimentClassifier(
+    checkpoint='yangheng/deberta-v3-base-absa-v1.1'
+)
+
+# 분석 함수
+def absa(text, aspect_input):
+    aspects = [a.strip() for a in aspect_input.split(",") if a.strip()]
+    pairs = [[text, aspect] for aspect in aspects]
+
+    results = aspect_extractor.infer(
+        inference_source=[text],
+        aspect_sentiment_pair_list=pairs
+    )
+
+    output = ""
+    for res in results:
+        for aspect, sentiment in res["aspect_sentiment_pair"]:
+            output += f"- **{aspect}** → **{sentiment}**\n"
+    return output
+
+# Gradio 인터페이스 생성
+iface = gr.Interface(
+    fn=absa,
+    inputs=[
+        gr.Textbox(label="문장 입력", placeholder="예: The battery is good, but the screen is dim."),
+        gr.Textbox(label="속성 입력 (쉼표로 구분)", placeholder="예: battery, screen")
+    ],
+    outputs=gr.Markdown(label="속성별 감정 분석 결과"),
+    title="ABSA 감정 분석기 (DeBERTa v3)",
+    description="문장과 속성을 입력하면 속성별 감정을 추출합니다. 모델: yangheng/deberta-v3-base-absa-v1.1"
+)
+
+iface.launch()

requirements.txt

@@ -1,4 +1,6 @@
-gradio
-pyabsa
-findfile
-pytorch_lightning
+gradio
+git+https://github.com/yangheng95/ABSAgym
+transformers==4.28.1
+protobuf==4.25.2
+findfile
+pytorch_lightning==1.9.5