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import json |
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import random |
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import torch |
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from model import NeuralNet |
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from nltk_utils import bag_of_words, tokenize |
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from spell_check import correct_typos |
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu") |
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with open("intents.json") as json_data: |
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intents = json.load(json_data) |
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FILE = "data.pth" |
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data = torch.load(FILE) |
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input_size = data["input_size"] |
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hidden_size = data["hidden_size"] |
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output_size = data["output_size"] |
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all_words = data["all_words"] |
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tags = data["tags"] |
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model_state = data["model_state"] |
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model = NeuralNet(input_size, hidden_size, output_size).to(device) |
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model.load_state_dict(model_state) |
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model.eval() |
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bot_name = "BGPT" |
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def generate_tag(sentence): |
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sentence = correct_typos(sentence) |
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if sentence.lower() == "quit" or sentence.lower() == "q": |
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pass |
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sentence = tokenize(sentence) |
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X = bag_of_words(sentence, all_words) |
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X = X.reshape(1, X.shape[0]) |
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X = torch.from_numpy(X).to(device) |
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output = model(X) |
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_, predicted = torch.max(output, dim=1) |
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tag = tags[predicted.item()] |
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return tag |
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def generate_response(sentence): |
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sentence = correct_typos(sentence) |
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if sentence.lower() == "quit" or sentence.lower() == "q": |
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pass |
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sentence = tokenize(sentence) |
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X = bag_of_words(sentence, all_words) |
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X = X.reshape(1, X.shape[0]) |
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X = torch.from_numpy(X).to(device) |
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output = model(X) |
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_, predicted = torch.max(output, dim=1) |
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tag = tags[predicted.item()] |
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probs = torch.softmax(output, dim=1) |
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prob = probs[0][predicted.item()] |
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if prob.item() > 0.8: |
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for intent in intents["intents"]: |
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if tag == intent["tag"]: |
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return f"{bot_name}: {random.choice(intent['responses'])}" |
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else: |
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return ( |
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f"{bot_name}: Sorry, I didn't understand... Can you be more " |
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"specific on your question? You can ask about Bibek's skillset, " |
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"experiences, portfolio, education, achievements " |
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"and KAIST activities." |
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"These are some sample questions: " |
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"(I) Tell me about Bibek,\n" |
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"(II) What skills does he have?,\n" |
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"(III) What work experience does Bibek have?,\n" |
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"(IV) What is Bibek's educational background?,\n" |
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"(V) What awards has he won?,\n" |
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"(VI) What projects has he completed? &\n" |
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"(VII) How can I contact Bibek?" |
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) |
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