2024-09-12 00:01:03 +00:00
|
|
|
# Example usage
|
2024-09-12 21:36:02 +00:00
|
|
|
'''from scripts.run_assessment_prediction_trainer import CompanyModelPipeline
|
|
|
|
|
company_ids = ['testid']
|
|
|
|
|
input_base_path = '/root/ds_erp_ai/data/raw/erp_assessment_prediction' # The base path where the raw data for each company is stored
|
2024-09-05 02:59:01 +00:00
|
|
|
|
2024-09-12 00:01:03 +00:00
|
|
|
pipeline = CompanyModelPipeline(company_ids=company_ids, input_base_path=input_base_path)
|
2024-09-12 21:36:02 +00:00
|
|
|
pipeline.run_pipeline()'''
|
|
|
|
|
|
2024-09-14 01:50:41 +00:00
|
|
|
'''from src.pipeline.inference import AssessmentInference
|
2024-09-12 21:36:02 +00:00
|
|
|
|
|
|
|
|
inference = AssessmentInference(
|
|
|
|
|
company_id="testid",num_assessments=2
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
result = inference.run()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
print(result)
|
2024-09-14 01:50:41 +00:00
|
|
|
'''
|
|
|
|
|
'''
|
|
|
|
|
response2 = bot.predict_next_n_assessment(
|
|
|
|
|
company_info=company_info,
|
|
|
|
|
companyid="testid",
|
|
|
|
|
N=3
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
print(f"Predictions {response2}")
|
|
|
|
|
'''
|
|
|
|
|
|
|
|
|
|
from src.services.chatbot import Chatbot
|
|
|
|
|
company_info = {
|
|
|
|
|
'company_name': "ABC Corp",
|
|
|
|
|
'company_size': "Medium", # Can be "Small", "Medium", or "Large"
|
|
|
|
|
'departments': ["Sales", "Marketing", "IT", "Finance", "HR", "Logistics"]
|
|
|
|
|
}
|
|
|
|
|
bot = Chatbot()
|
|
|
|
|
response = bot.predict_based_on_past_assessment(
|
|
|
|
|
query="Should i make my next assessment weekly or biweekly to meet up to deadline?",
|
|
|
|
|
company_info=company_info,
|
|
|
|
|
companyid="testid"
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
print(f"Result: {response}")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|