Implement the metrics module

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1) Elementary metrics:

• served queries
• revenue (= served queries * price)

2) Derivative metrics:

• query ratio (= served queries / total queries)
• regret (= customer budget - agent's revenue)
• regret ratio (= agent's revenue / customer budget)

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3. time to convergence
   • epsilon_1 = accepted difference between the customer budget b and agent's price p (mean)
   • epsilon_2 = defines how wide the gaussian can be (stddev)

agent converged IF |b - p| <= epsilon_1 AND stddev <= epsilon_2

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note: think/discuss about the warm-up phase (dynamic budget and/or no queries)

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ideas: https://torchmetrics.readthedocs.io/en/stable/

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https://snyk.io/advisor/python/jax-metrics

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Price efficiency = Indexer price / customer budget