| 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 | |