| import requests |
| import spacy |
| from spacy import displacy |
| from dotenv import load_dotenv |
| import os |
| from stm import ShortTermMemory |
|
|
| load_dotenv() |
| api_key = os.getenv("API_KEY") |
|
|
| API_URL = "https://api-inference.huggingface.co/models/cleopatro/Entity_Rec" |
| headers = {"Authorization": f"Bearer {api_key}"} |
| NER = spacy.load("en_core_web_sm") |
|
|
| def extract_word_and_entity_group(dict): |
| words = [] |
| result = [] |
| |
| for item in dict: |
| word = item['word'] |
| words.append(word) |
| |
| return words |
|
|
|
|
| def get_abs(payload): |
| response = requests.post(API_URL, headers=headers, json=payload) |
| return response.json() |
| |
|
|
| def get_loc_time(sentence): |
| text1 = NER(sentence) |
| locations = [] |
| times = [] |
| for ent in text1.ents: |
| if ent.label_ == "GPE" or ent.label_ == "LOC": |
| locations.append(ent.text) |
| elif ent.label_ == "TIME" or ent.label_ == "DATE": |
| times.append(ent.text) |
| return locations, times |
|
|
|
|
| def get_ent(sentence): |
| abs_dict = get_abs(sentence) |
| abs_tags = extract_word_and_entity_group(abs_dict) |
| loc_tags, time_tags = get_loc_time(sentence["inputs"]) |
| return abs_tags, loc_tags, time_tags |
|
|
|
|
|
|
| |
| |
| |
|
|
| |
|
|
| |
|
|
| |
| |
|
|
