* feat: add zai-glm-4.6 model and update gpt-oss-120b for Cerebras
- Add zai-glm-4.6 with 128K context window and 40K max tokens
- Set zai-glm-4.6 as default Cerebras model
- Update gpt-oss-120b to 128K context and 40K max tokens
* feat: add zai-glm-4.6 model to Cerebras provider
- Add zai-glm-4.6 with 128K context window and 40K max tokens
- Set zai-glm-4.6 as default Cerebras model
- Model provides ~2000 tokens/s for general-purpose tasks
* add [SOON TO BE DEPRECATED] warning for Q3C
* chore: set gpt-oss-120b as default Cerebras model
* Fix cerebras test: update expected default model to gpt-oss-120b
* Apply suggestion from @mrubens
Co-authored-by: Matt Rubens <mrubens@users.noreply.github.com>
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Co-authored-by: kevint-cerebras <kevin.taylor@cerebras.net>
Co-authored-by: Matt Rubens <mrubens@users.noreply.github.com>
* feat: Add supportsReasoning property for Z.ai GLM binary thinking mode
- Add supportsReasoning to ModelInfo schema for binary reasoning models
- Update GLM-4.5 and GLM-4.6 models to use supportsReasoning: true
- Implement thinking parameter support in ZAiHandler for Deep Thinking API
- Update ThinkingBudget component to show simple toggle for supportsReasoning models
- Add comprehensive tests for binary reasoning functionality
Closes#8465
* refactor: rename supportsReasoning to supportsReasoningBinary for clarity
- Rename supportsReasoning -> supportsReasoningBinary in model schema
- Update Z.AI GLM model configurations to use supportsReasoningBinary
- Update Z.AI provider logic in createStream and completePrompt methods
- Update ThinkingBudget UI component and tests
- Update all test comments and expectations
This change improves naming clarity by distinguishing between:
- supportsReasoningBinary: Simple on/off reasoning toggle
- supportsReasoningBudget: Advanced reasoning with token budget controls
- supportsReasoningEffort: Advanced reasoning with effort levels
* Use monotonic clock for rate limiting
* Fix LiteLLM test failures after merge
- Remove supportsComputerUse from LiteLLM implementation as it's no longer part of ModelInfo interface
- Update test expectations to include cacheWritesPrice and cacheReadsPrice fields
- Fix test for max_output_tokens preference functionality
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Co-authored-by: Christiaan Arnoldus <christiaan.arnoldus@outlook.com>
* feat(zai): add GLM-4.5-X, AirX, Flash; sync with Z.ai docs; keep canonical api line keys
* feat(zai): add GLM-4.5V vision model (supportsImages, pricing, 16K max output); add tests
* feat(types,zai): sync Z.AI international model map and tests
- Update pricing, context window, and capabilities for:
glm-4.5-x, glm-4.5-airx, glm-4.5-flash, glm-4.5v, glm-4.6
- Add glm-4-32b-0414-128k
- Align tests with new model specs
* fix(zai): align handler generics with expanded model ids to satisfy CI compile step
* chore(zai): remove tier pricing blocks for Z.ai models
* fix(zai): simplify names in zaiApiLineConfigs for clarity
* chore(zai): set default temperature to 0.6
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Co-authored-by: Roo Code <roomote@roocode.com>
* fix: apply tiered pricing for Gemini models via Vertex AI
- Modified calculateCost method to handle models where cacheReadsPrice is only defined in tiers
- Added comprehensive tests for Vertex AI tiered pricing calculation
- Fixes issue where local cost calculation always showed highest tier rates
Fixes#8017
* Delete src/api/providers/__tests__/vertex-tiered-pricing.spec.ts
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Co-authored-by: Roo Code <roomote@roocode.com>
Co-authored-by: Daniel <57051444+daniel-lxs@users.noreply.github.com>
* fix: add cache reporting support for OpenAI-Native provider
- Add normalizeUsage method to properly extract cache tokens from Responses API
- Support both detailed token shapes (input_tokens_details) and legacy fields
- Calculate cache read/write tokens with proper fallbacks
- Include reasoning tokens when available in output_tokens_details
- Ensure accurate cost calculation using uncached input tokens
This fixes the issue where caching information was not being reported
when using the OpenAI-Native provider with the Responses API.
* fix: improve cache token normalization and add comprehensive tests
- Add fallback to derive total input tokens from details when totals are missing
- Remove unused convertToOpenAiMessages import
- Add comment explaining cost calculation alignment with Gemini provider
- Add comprehensive test coverage for normalizeUsage method covering:
- Detailed token shapes with cached/miss tokens
- Legacy field names and SSE-only events
- Edge cases including missing totals with details-only
- Cost calculation with uncached input tokens
* fix: address PR review comments
- Remove incorrect fallback to missFromDetails for cache write tokens
- Fix cost calculation to pass total input tokens (calculateApiCostOpenAI handles subtraction)
- Improve readability by extracting cache detail checks to intermediate variables
- Remove redundant ?? undefined
- Update tests to reflect correct behavior (miss tokens are not cache writes)
- Add clarifying comments about cache miss vs cache write tokens
* feat: add Ollama API key support for Turbo mode
- Add ollamaApiKey field to ProviderSettings schema
- Add ollamaApiKey to SECRET_STATE_KEYS for secure storage
- Update Ollama and NativeOllama providers to use API key for authentication
- Add UI field for Ollama API key (shown when custom base URL is provided)
- Add test coverage for API key functionality
This enables users to use Ollama Turbo with datacenter-grade hardware by providing an API key for authenticated Ollama instances or cloud services.
* fix: use VSCodeTextField for Ollama API key field
Remove non-existent ApiKeyField import and use standard VSCodeTextField with password type, matching other provider implementations
* Add missing translation keys for Ollama API key support
- Add providers.ollama.apiKey and providers.ollama.apiKeyHelp to all 18 language files
- Support for authenticated Ollama instances and cloud services
- Relates to PR #7425
* refactor: improve type safety for Ollama client configuration
- Replace 'any' type with proper OllamaOptions (Config) type
- Import Config type from ollama package for better type checking
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Co-authored-by: Roo Code <roomote@roocode.com>
Co-authored-by: Daniel Riccio <ricciodaniel98@gmail.com>
