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| # import requests | |
| # import time | |
| # import streamlit as st | |
| # import os | |
| # # SECRET_TOKEN | |
| # SECRET_TOKEN = os.getenv("HF_IBOA") | |
| # DISTILIBERT = "https://api-inference.huggingface.co/models/MENG21/stud-fac-eval-distilbert-base-uncased" | |
| # BERTLARGE = "https://api-inference.huggingface.co/models/MENG21/stud-fac-eval-bert-large-uncased" | |
| # BERTBASE = "https://api-inference.huggingface.co/models/MENG21/stud-fac-eval-bert-base-uncased" | |
| # headers = {"Authorization": SECRET_TOKEN} | |
| # # @st.cache_resource | |
| # @st.cache_resource(experimental_allow_widgets=True, show_spinner=False) | |
| # def query(payload, selected_model): | |
| # if selected_model == "DISTILIBERT MODEL": | |
| # API_URL = DISTILIBERT | |
| # elif selected_model == "BERT-LARGE MODEL": | |
| # API_URL = BERTLARGE | |
| # elif selected_model == "BERT-BASE MODEL": | |
| # API_URL = BERTBASE | |
| # else: | |
| # API_URL = DISTILIBERT | |
| # start_time = time.time() | |
| # counter = 0 | |
| # with st.spinner("Processing..."): | |
| # while True: | |
| # response = requests.post(API_URL, headers=headers, json=payload) | |
| # # st.write(response) | |
| # if response.status_code == 200: | |
| # return response.json() | |
| # else: | |
| # time.sleep(1) # Wait for 1 second before retrying | |
| # def analyze_sintement(text, selected_model): | |
| # output = query({"inputs": text}, selected_model) | |
| # if output: | |
| # # st.success(f"Translation complete!") | |
| # return output[0][0]['label'], output[0][0]['score'] | |
| # else: | |
| # st.warning("Error! Please try again.") | |
| import requests | |
| import time | |
| import streamlit as st | |
| import os | |
| # Define constants for API URLs | |
| MODEL_URLS = { | |
| "DISTILIBERT MODEL": "https://api-inference.huggingface.co/models/MENG21/stud-fac-eval-distilbert-base-uncased", | |
| "BERT-LARGE MODEL": "https://api-inference.huggingface.co/models/MENG21/stud-fac-eval-bert-large-uncased", | |
| "BERT-BASE MODEL": "https://api-inference.huggingface.co/models/MENG21/stud-fac-eval-bert-base-uncased" | |
| } | |
| # SECRET_TOKEN | |
| SECRET_TOKEN = os.getenv("HF_IBOA") | |
| # Set headers | |
| headers = {"Authorization": SECRET_TOKEN} | |
| # Define retry parameters | |
| MAX_RETRIES = 3 | |
| RETRY_INTERVAL = 1 # in seconds | |
| # @st.cache_resource(experimental_allow_widgets=True, show_spinner=False) | |
| def query(payload, selected_model): | |
| # st.write(selected_model) | |
| API_URL = MODEL_URLS.get(selected_model, MODEL_URLS[selected_model]) # Get API URL based on selected model | |
| for retry in range(MAX_RETRIES): | |
| response = requests.post(API_URL, headers=headers, json=payload) | |
| if response.status_code == 200: | |
| return response.json() | |
| else: | |
| st.info("loading..") | |
| time.sleep(RETRY_INTERVAL) | |
| return None | |
| def analyze_sintement(text, selected_model): | |
| # print(headers) | |
| output = query({"inputs": text}, selected_model) | |
| if output: | |
| return output[0][0]['label'], output[0][0]['score'] | |
| else: | |
| st.warning("Error! Please try again.") | |
| pass |