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* add tool usage statistics tracking - Add ToolUsageStats class with metrics for tool calls, turns, and statistical aggregates (mean/stddev per generation) - Extend ModelUsageStats to include tool_usage tracking - Update ModelFacade.generate() to track total tool calls and turns - Update tests with tool_call_count method and new assertions * silence noisy mcp logs * log message updates * add tools enabled info message * exclude empty tool_usage from usage stats output * add tool usage summary logging after column generation - Track tool usage snapshots before/after column processing - Log mean tool calls per generation for columns with tools enabled - Add get_tool_usage_snapshot/get_tool_usage_delta methods to ModelRegistry - Remove unused extra_info parameter from progress_tracker.log_start() - Add comprehensive tests for ToolUsageStats * pretty format model usage logs * reuse stubs and fixtures * add merge method to ToolUsageStats for accurate stats aggregation The previous implementation used extend() to combine tool usage stats, but extend() is designed for single generation data. This caused incorrect stddev calculations when merging stats from multiple sources. - Add ToolUsageStats.merge() that properly combines sum-of-squares - Update ModelUsageStats.extend() to use merge() for tool usage - Add tests verifying stddev accuracy after merging * fix tool usage stats missing generations_with_tools count When tracking tool usage after generation, the ToolUsageStats was created without setting generations_with_tools, causing the usage summary to report zeros for calls/gen and turns/gen metrics. * fix tool usage delta objects returning incorrect stddev values - Simplify facade API to use tool_usage.extend() directly - Return NaN for stddev when sum of squares wasn't tracked - Add docstring to get_tool_usage_delta explaining NaN behavior - Add comprehensive tests for stddev variance calculation * fix tool usage delta stddev by including sum of squares in deltas Convert sum_of_squares_turns and sum_of_squares_calls from private attributes to public fields, enabling them to be included in delta calculations. This allows get_tool_usage_delta to return objects that compute accurate stddev values instead of NaN. * fix test to use get_tool_usage_snapshot for accurate stddev tracking The test was manually constructing a ToolUsageStats snapshot without sum_of_squares fields, causing stddev to be NaN. Now uses the proper snapshot method that includes all fields needed for delta calculations. * use nvidia-reasoning by default * mean -> average in log message * refactor log indentation to use centralized LOG_INDENT constant - Add LOG_INDENT constant to logging.py for consistent indentation - Replace hardcoded " |-- " strings across all log statements - Add tool alias and MCP provider info to pre-generation logs - Improve model usage log format for better consistency - Update tests to match new log formats * simplify usage stats dict access in model registry Remove defensive .get() calls and unnecessary type casts since the usage statistics dictionary structure is now guaranteed. * walrus baby * simplify tool usage tracking and reduce log verbosity - Remove mean/stddev calculations from ToolUsageStats in favor of simple counts and generation ratios - Add total_generations field to track all tool-enabled generations - Simplify registry log output to show generations ratio (with_tools/total) - Remove per-column tool usage snapshot/delta logging from column builder - Track tool usage for all tool-enabled generations, not just those with calls * format inference parameters as multi-line log output - Add get_formatted_params() method to BaseInferenceParams - Add LOG_DOUBLE_INDENT constant for nested indentation - Update log_pre_generation() to display each parameter on its own line * update tests to use LOG_INDENT constants Align test assertions with the centralized log indentation constants introduced in the logging module refactor. * two-space consistency |
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