| from sentence_transformers import SentenceTransformer | |
| import gradio as gr | |
| model = SentenceTransformer('sentence-transformers/multi-qa-mpnet-base-cos-v1') | |
| def generate_embedding(query): | |
| # return "Connected" | |
| embeddings = model.encode(query) | |
| resposne = "" | |
| for char in embeddings.tolist(): | |
| resposne += str(char) + " " | |
| # mySeparator = " " | |
| # resposne = mySeparator.join(embeddings.tolist()) | |
| return resposne | |
| demo = gr.Interface(fn=generate_embedding, inputs="text", outputs="text") | |
| demo.launch( show_api=True) |