import json import numpy as np import httpx from constants import MUBERT_TAGS, MUBERT_LICENSE, MUBERT_MODE, MUBERT_TOKEN def get_mubert_tags_embeddings(w2v_model): return w2v_model.encode(MUBERT_TAGS) def get_pat(email: str): r = httpx.post('https://api-b2b.mubert.com/v2/GetServiceAccess', json={ "method": "GetServiceAccess", "params": { "email": email, "license": MUBERT_LICENSE, "token": MUBERT_TOKEN, "mode": MUBERT_MODE, } }) rdata = json.loads(r.text) assert rdata['status'] == 1, "probably incorrect e-mail" pat = rdata['data']['pat'] return pat def find_similar(em, embeddings, method='cosine'): scores = [] for ref in embeddings: if method == 'cosine': scores.append(1 - np.dot(ref, em) / (np.linalg.norm(ref) * np.linalg.norm(em))) if method == 'norm': scores.append(np.linalg.norm(ref - em)) return np.array(scores), np.argsort(scores) def get_tags_for_prompts(w2v_model, mubert_tags_embeddings, prompts, top_n=3, debug=False): prompts_embeddings = w2v_model.encode(prompts) ret = [] for i, pe in enumerate(prompts_embeddings): scores, idxs = find_similar(pe, mubert_tags_embeddings) top_tags = MUBERT_TAGS[idxs[:top_n]] top_prob = 1 - scores[idxs[:top_n]] if debug: print(f"Prompt: {prompts[i]}\nTags: {', '.join(top_tags)}\nScores: {top_prob}\n\n\n") ret.append((prompts[i], list(top_tags))) return ret