Design typed model struct with registry and config#326
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svilupp
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Dec 25, 2025
svilupp
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- Add TokenUsage struct for standardized token tracking across providers with fields for input/output, cache (read/write), reasoning, audio tokens
- Add usage field to AIMessage, DataMessage, AIToolRequest for unified tracking
- Add extract_usage(schema, resp) dispatched by provider schema
- Add call_cost_with_cache with provider-specific cache discounts:
- OpenAI GPT-4: 50% read discount
- Anthropic: 90% read discount, 25% write premium
- Gemini/GPT-5: 90% read discount
- Add build_message utility for unified message construction
- Add extract_log_prob utility for OpenAI-style responses
- Refactor response_to_message in llm_openai_chat.jl to use new utilities
- Refactor message construction in llm_anthropic.jl and llm_ollama.jl
- Add comprehensive tests in test/usage.jl
- Add TokenUsage struct for standardized token tracking across providers with fields for input/output, cache (read/write), reasoning, audio tokens - Add usage field to AIMessage, DataMessage, AIToolRequest for unified tracking - Add extract_usage(schema, resp) dispatched by provider schema - Add call_cost_with_cache with provider-specific cache discounts: - OpenAI GPT-4: 50% read discount - Anthropic: 90% read discount, 25% write premium - Gemini/GPT-5: 90% read discount - Add build_message utility for unified message construction - Add extract_log_prob utility for OpenAI-style responses - Refactor response_to_message in llm_openai_chat.jl to use new utilities - Refactor message construction in llm_anthropic.jl and llm_ollama.jl - Add comprehensive tests in test/usage.jl
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