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import os
os.system('pip install duckduckgo-search -U')
os.system('pip install huggingface_hub -U')
os.system('pip install requests -U')
os.system('pip install autotrain -U')
import requests
import json
from huggingface_hub import HfFolder
from autotrain import AutoTrain
def get_answers_from_duckduckgo(query):
url = f"https://api.duckduckgo.com/?q={query}&format=json"
response = requests.get(url)
data = response.json()
if 'RelatedTopics' in data:
answers = [topic['Text'] for topic in data['RelatedTopics'] if 'Text' in topic]
return answers
return []
def prepare_training_data(answers, query):
training_data = []
for answer in answers:
training_data.append({"text": query, "label": answer})
return training_data
def main():
user_query = input("Type your question: ")
answers = get_answers_from_duckduckgo(user_query)
if not answers:
print("No answers found.")
return
training_data = prepare_training_data(answers, user_query)
training_file = 'training_data.json'
with open(training_file, 'w') as f:
json.dump(training_data, f)
print("Training data prepared and saved!")
auto_train = AutoTrain(dataset_path=training_file)
auto_train.train(model_name="distilbert-base-uncased", num_train_epochs=3)
print("Training completed!")
if __name__ == "__main__":
main() |