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Download synthetic_data.py from manayporwal07/Agentic-Evaluation-Framework: direct link, hf CLI and curl.
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https://huggingface.co/spaces/manayporwal07/Agentic-Evaluation-Framework/resolve/37e95fb2b3c3d612dc8d486fd1ceacd72fd54841/synthetic_data.py
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hf download hf://spaces/manayporwal07/Agentic-Evaluation-Framework@37e95fb2b3c3d612dc8d486fd1ceacd72fd54841/synthetic_data.py
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curl -L -o synthetic_data.py https://huggingface.co/spaces/manayporwal07/Agentic-Evaluation-Framework/resolve/37e95fb2b3c3d612dc8d486fd1ceacd72fd54841/synthetic_data.py
475 Bytes
| import pandas as pd | |
| import random | |
| def generate_synthetic_dataset(num_agents=5, num_samples=20): | |
| data = [] | |
| for agent in range(num_agents): | |
| for i in range(num_samples): | |
| instr = f"Task {i}: Summarize topic {random.randint(1,10)}" | |
| resp = f"This is a response to {instr}. Agent {agent} provides details." | |
| data.append({"agent": f"Agent_{agent}", "instruction": instr, "response": resp}) | |
| return pd.DataFrame(data) | |