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from sentence_transformers import SentenceTransformer |
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from fastapi import FastAPI |
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from pydantic import BaseModel |
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import torch |
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app = FastAPI() |
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model_name = "meedan/paraphrase-filipino-mpnet-base-v2" |
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model = SentenceTransformer(model_name) |
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class TextInput(BaseModel): |
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text: str |
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@app.post("/embed") |
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def embed_text(input: TextInput): |
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with torch.no_grad(): |
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embedding = model.encode([input.text])[0].tolist() |
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return {"embedding": embedding} |
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@app.get("/") |
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def read_root(): |
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return f"Encode text to numerical vectors using sentence transformer: {model_name}" |
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