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This scenario implements a modified version of the HumanEval benchmark.
Compared to the original benchmark, there are two key differences here:
Navigate to HumanEval
cd benchmarks/HumanEval
Update config.yaml to point to your model host, as appropriate. The default configuration points to 'gpt-4o'.
Now initialize the tasks.
python Scripts/init_tasks.py
Note: This will attempt to download HumanEval
Then run Scripts/init_tasks.py again.
Once the script completes, you should now see a folder in your current directory called Tasks that contains one JSONL file per template in Templates.
Now to run a specific subset of HumanEval use:
agbench run Tasks/human_eval_AgentChat.jsonl
You should see the command line print the raw logs that shows the agents in action To see a summary of the results (e.g., task completion rates), in a new terminal run the following:
agbench tabulate Results/human_eval_AgentChat
Evaluating Large Language Models Trained on Code<br/>
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, Wojciech Zaremba<br/>
https://arxiv.org/abs/2107.03374
This is a mirror of AutoGen from GitHub. AutoGen is a framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks.
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