init

app.py

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+import gradio as gr
+from gradio.mix import Parallel
+from transformers import pipeline
+from sentence_transformers import SentenceTransformer, util
+from rembg import remove
+
+
+generator = pipeline('text-generation', model='gpt2')
+model_txt_embedding = SentenceTransformer("sentence-transformers/all-mpnet-base-v2")
+
+
+# 文本向量
+def embedding(txt):
+    return str(model_txt_embedding.encode(txt, convert_to_tensor=True, convert_to_numpy=True).tolist())
+
+# 文本相似度
+def embedding_sim(text1, text2):
+    embeddings1 = model_txt_embedding.encode(text1, convert_to_tensor=True)
+    embeddings2 = model_txt_embedding.encode(text2, convert_to_tensor=True)
+    return str(util.cos_sim(embeddings1, embeddings2).item())
+
+def remove_bg(image):
+    # return image
+    return remove(image)
+
+tab1 = gr.Interface(fn=embedding, inputs="text", outputs="text")
+tab2 = gr.Interface(fn=embedding_sim, inputs=["text", "text"], outputs="text")
+tab3 = gr.Interface(fn=remove_bg, inputs="image", outputs="image")
+
+app = gr.TabbedInterface([tab1, tab2, tab3], ["文本向量", "文本相似度", "抠图"])
+app.queue()
+app.launch()

requirements.txt

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+rembg==2.0.30
+gradio==3.22.1
+transformers==4.24.0
+sentence-transformers==2.2.2