set llm_model to "gpt-4-0125-preview"

app.py

@@ -7,28 +7,18 @@ from transformers import pipeline
 # from dotenv import load_dotenv, find_dotenv
 import huggingface_hub
 import json
-# from simcse import SimCSE # use for gpt
 from evaluate_data import store_sample_data, get_metrics_trf
 from sentence_transformers import SentenceTransformer
 from tqdm import tqdm
-# store_sample_data()
 
-
-
-# with open('./data/sample_data.json', 'r') as f:
-#     # sample_data = [
-#     #     {'id': "", 'text': "", 'orgs': ["", ""]}
-#     # ]
-#     sample_data = json.load(f)
-    
-# _ = load_dotenv(find_dotenv()) # read local .env file
 hf_token= os.environ['HF_TOKEN']
 huggingface_hub.login(hf_token)
 
 pipe = pipeline("token-classification", model="elshehawy/finer-ord-transformers", aggregation_strategy="first")
 
 
-llm_model = 'gpt-3.5-turbo-0125'
+# llm_model = 'gpt-3.5-turbo-0125'
+llm_model = 'gpt-4-0125-preview'
 # openai.api_key = os.environ['OPENAI_API_KEY']
 
 client = OpenAI(
@@ -63,31 +53,6 @@ def find_orgs_gpt(sentence):
     return sent_orgs
 
 
-    
-# def find_orgs_trf(sentence):
-#     org_list = []
-#     for ent in pipe(sentence):
-#         if ent['entity_group'] == 'ORG':
-#             # message += f'\n- {ent["word"]} \t- score: {ent["score"]}'
-#             # message += f'\n- {ent["word"]}'# \t- score: {ent["score"]}'
-#             org_list.append(ent['word'])
-#     return list(set(org_list))
-
-
-# true_orgs = [sent['orgs'] for sent in sample_data]
-
-# predicted_orgs_gpt = [find_orgs_gpt(sent['text']) for sent in sample_data]
-# predicted_orgs_trf = [find_orgs_trf(sent['text']) for sent in sample_data]
-
-# all_metrics = {}
-
-# sim_model = SimCSE('sentence-transformers/all-MiniLM-L6-v2')
-# all_metrics['gpt'] = calc_metrics(true_orgs, predicted_orgs_gpt, sim_model)
-# print('Finiding all metrics trf')
-# all_metrics['trf'] = get_metrics_trf()
-
-
-
 example = """
 My latest exclusive for The Hill : Conservative frustration over Republican efforts to force a House vote on reauthorizing the Export - Import Bank boiled over Wednesday during a contentious GOP meeting.
 
@@ -111,18 +76,11 @@ def find_orgs(uploaded_file):
     all_metrics['trf'] = get_metrics_trf(uploaded_data)
     
 
-    # with open('./data/sample_data.json', 'r') as f:
-    #     sample_data = json.load(f)
     
     
-        
-
-    # sim_model = SimCSE('sentence-transformers/all-MiniLM-L6-v2')
-    
     print(all_metrics)
     return all_metrics
-# radio_btn = gr.Radio(choices=['GPT', 'iSemantics'], value='iSemantics', label='Available models', show_label=True)
-# textbox = gr.Textbox(label="Enter your text", placeholder=str(all_metrics), lines=8)
+
 upload_btn = gr.UploadButton(label='Upload a json file.', type='binary')
 
 iface = gr.Interface(fn=find_orgs, inputs=upload_btn, outputs="text")