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pragnakalp
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•
c6a2c72
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Parent(s):
3b60e31
Update app.py
Browse files
app.py
CHANGED
@@ -4,10 +4,19 @@ import gc
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import os
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import pandas as pd
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tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-emotion")
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model_base = AutoModelWithLMHead.from_pretrained(model_path)
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def get_emotion(text):
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# input_ids = tokenizer.encode(text + '</s>', return_tensors='pt')
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@@ -45,13 +54,50 @@ def generate_emotion(article):
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# }
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result = {'Input':sen_list_temp, 'Detected Emotion':results}
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gc.collect()
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demo = gr.Interface(
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generate_emotion,
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import os
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import pandas as pd
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HF_TOKEN = os.environ.get("HF_TOKEN")
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DATASET_NAME = "emotion_detection"
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DATASET_REPO_URL = f"https://huggingface.co/datasets/pragnakalp/{DATASET_NAME}"
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DATA_FILENAME = "emotion_detection_logs.csv"
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DATA_FILE = os.path.join("emotion_detection_logs", DATA_FILENAME)
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DATASET_REPO_ID = "pragnakalp/emotion_detection"
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print("is none?", HF_TOKEN is None)
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sentences_value = """Raj loves Simran.\nLast year I lost my Dog.\nI bought a new phone!\nShe is scared of cockroaches.\nWow! I was not expecting that.\nShe got mad at him."""
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tokenizer = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-emotion")
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model_base = AutoModelWithLMHead.from_pretrained(model_path)
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def get_emotion(text):
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# input_ids = tokenizer.encode(text + '</s>', return_tensors='pt')
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# }
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result = {'Input':sen_list_temp, 'Detected Emotion':results}
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gc.collect()
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add_csv = [results_dict]
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with open(DATA_FILE, "a") as f:
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writer = csv.writer(f)
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# write the data
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writer.writerow(add_csv)
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commit_url = repo.push_to_hub()
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print("commit data :",commit_url)
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return pd.DataFrame(result)
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"""
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Save generated details
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"""
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# def save_data_and_sendmail(article,generated_questions,num_que,result):
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# try:
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# hostname = {}
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# hostname = get_device_ip_address()
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# url = 'https://pragnakalpdev35.pythonanywhere.com/HF_space_que_gen'
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# # url = 'http://pragnakalpdev33.pythonanywhere.com/HF_space_question_generator'
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# myobj = {'article': article,'total_que': num_que,'gen_que':result,'ip_addr':hostname.get("ip_addr",""),'host':hostname.get("host","")}
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# x = requests.post(url, json = myobj)
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# add_csv = [article, generated_questions, num_que]
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# with open(DATA_FILE, "a") as f:
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# writer = csv.writer(f)
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# # write the data
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# writer.writerow(add_csv)
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# commit_url = repo.push_to_hub()
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# print("commit data :",commit_url)
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# # except Exception as e:
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# # return "Error while storing data -->" + e
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# # try:
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# # with open(DATA_FILE, "r") as file:
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# # data = json.load(file)
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# # data.append(entry)
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# # with open(DATA_FILE, "w") as file:
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# # json.dump(data, file)
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# # commit_url = repo.push_to_hub()
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# except Exception as e:
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# return "Error while sending mail" + e
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# return "Successfully save data"
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inputs = gr.Textbox(value=sentences_value,lines=10, label="Sentences",elem_id="inp_div")
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outputs = [gr.Dataframe(row_count = (2, "dynamic"), col_count=(2, "fixed"), label="Here is the Result", headers=["Input","Detected Emotion"])]
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demo = gr.Interface(
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generate_emotion,
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