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from fastapi import FastAPI |
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from pydantic import BaseModel |
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from typing import List |
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from sentence_transformers import SentenceTransformer |
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from sklearn.metrics.pairwise import cosine_similarity |
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app = FastAPI() |
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model = SentenceTransformer("paraphrase-MiniLM-L3-v2") |
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class SimilarityRequest(BaseModel): |
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ideal_profile: str |
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text_blocks: List[str] |
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@app.post("/similarity") |
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def compute_similarity(req: SimilarityRequest): |
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profile_vec = model.encode(req.ideal_profile) |
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text_vecs = model.encode(req.text_blocks) |
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similarities = cosine_similarity([profile_vec], text_vecs)[0].tolist() |
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return similarities |
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