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reverted agg and topk examples and replaced with two new files for te…
…sting multithreading
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,254 +1,21 @@ | ||
| import time | ||
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| import pandas as pd | ||
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| import lotus | ||
| from lotus.models import LM | ||
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| def main(): | ||
| lm = LM(model="gpt-4o-mini") | ||
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| lotus.settings.configure(lm=lm) | ||
| lotus.settings.configure(enable_multithreading=True) | ||
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| # turn on lotus debug logging | ||
| lotus.logger.setLevel("DEBUG") | ||
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| data = { | ||
| "Course Name": [ | ||
| "Probability and Random Processes", | ||
| "Optimization Methods in Engineering", | ||
| "Digital Design and Integrated Circuits", | ||
| "Computer Security", | ||
| "Cooking", | ||
| "Food Sciences", | ||
| "Machine Learning", | ||
| "Data Structures and Algorithms", | ||
| "Quantum Mechanics", | ||
| "Organic Chemistry", | ||
| "Artificial Intelligence", | ||
| "Robotics", | ||
| "Thermodynamics", | ||
| "Fluid Mechanics", | ||
| "Molecular Biology", | ||
| "Genetics", | ||
| "Astrophysics", | ||
| "Neuroscience", | ||
| "Microeconomics", | ||
| "Macroeconomics", | ||
| "Linear Algebra", | ||
| "Calculus", | ||
| "Statistics", | ||
| "Differential Equations", | ||
| "Discrete Mathematics", | ||
| "Number Theory", | ||
| "Graph Theory", | ||
| "Topology", | ||
| "Complex Analysis", | ||
| "Real Analysis", | ||
| "Abstract Algebra", | ||
| "Numerical Methods", | ||
| "Cryptography", | ||
| "Network Security", | ||
| "Operating Systems", | ||
| "Databases", | ||
| "Computer Networks", | ||
| "Software Engineering", | ||
| "Compilers", | ||
| "Computer Architecture", | ||
| "Parallel Computing", | ||
| "Distributed Systems", | ||
| "Cloud Computing", | ||
| "Big Data Analytics", | ||
| "Natural Language Processing", | ||
| "Computer Vision", | ||
| "Reinforcement Learning", | ||
| "Deep Learning", | ||
| "Bioinformatics", | ||
| "Computational Biology", | ||
| "Systems Biology", | ||
| "Biochemistry", | ||
| "Physical Chemistry", | ||
| "Inorganic Chemistry", | ||
| "Analytical Chemistry", | ||
| "Environmental Chemistry", | ||
| "Materials Science", | ||
| "Nanotechnology", | ||
| "Optics", | ||
| "Electromagnetism", | ||
| "Nuclear Physics", | ||
| "Particle Physics", | ||
| "Cosmology", | ||
| "Planetary Science", | ||
| "Geophysics", | ||
| "Atmospheric Science", | ||
| "Oceanography", | ||
| "Ecology", | ||
| "Evolutionary Biology", | ||
| "Botany", | ||
| "Zoology", | ||
| "Microbiology", | ||
| "Immunology", | ||
| "Virology", | ||
| "Pharmacology", | ||
| "Physiology", | ||
| "Anatomy", | ||
| "Neurobiology", | ||
| "Cognitive Science", | ||
| "Psychology", | ||
| "Sociology", | ||
| "Anthropology", | ||
| "Archaeology", | ||
| "Linguistics", | ||
| "Philosophy", | ||
| "Ethics", | ||
| "Logic", | ||
| "Political Science", | ||
| "International Relations", | ||
| "Public Policy", | ||
| "Economics", | ||
| "Finance", | ||
| "Accounting", | ||
| "Marketing", | ||
| "Management", | ||
| "Entrepreneurship", | ||
| "Law", | ||
| "Criminal Justice", | ||
| "Human Rights", | ||
| "Environmental Studies", | ||
| "Sustainability", | ||
| "Urban Planning", | ||
| "Architecture", | ||
| "Civil Engineering", | ||
| "Mechanical Engineering", | ||
| "Electrical Engineering", | ||
| "Chemical Engineering", | ||
| "Aerospace Engineering", | ||
| "Biomedical Engineering", | ||
| "Environmental Engineering", | ||
| ], | ||
| "Grade Level": [ | ||
| "High School", | ||
| "Graduate", | ||
| "Graduate", | ||
| "High School", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "High School", | ||
| "Undergraduate", | ||
| "High School", | ||
| "Undergraduate", | ||
| "High School", | ||
| "Graduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Graduate", | ||
| "Undergraduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "High School", | ||
| "High School", | ||
| "Undergraduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "High School", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "High School", | ||
| "Undergraduate", | ||
| "High School", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Graduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Undergraduate", | ||
| "Graduate", | ||
| "Undergraduate", | ||
| "High School", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "High School", | ||
| "Graduate", | ||
| "High School", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "High School", | ||
| "High School", | ||
| "High School", | ||
| "Undergraduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "High School", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "High School", | ||
| "High School", | ||
| "Graduate", | ||
| "Graduate", | ||
| "High School", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "High School", | ||
| "High School", | ||
| "Graduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Undergraduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| "Graduate", | ||
| ], | ||
| } | ||
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| df = pd.DataFrame(data) | ||
| start_time = time.time() | ||
| df = df.sem_agg("Summarize all {Course Name}", group_by=["Grade Level"]) | ||
| end_time = time.time() | ||
| print(df._output[0]) | ||
| print(f"Total execution time: {end_time - start_time:.2f} seconds") | ||
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| if __name__ == "__main__": | ||
| main() | ||
| lm = LM(model="gpt-4o-mini") | ||
|
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| lotus.settings.configure(lm=lm) | ||
| data = { | ||
| "Course Name": [ | ||
| "Probability and Random Processes", | ||
| "Optimization Methods in Engineering", | ||
| "Digital Design and Integrated Circuits", | ||
| "Computer Security", | ||
| "Cooking", | ||
| "Food Sciences", | ||
| ] | ||
| } | ||
| df = pd.DataFrame(data) | ||
| df = df.sem_agg("Summarize all {Course Name}") | ||
| print(df._output[0]) |
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