* fix: add explicit max_output_tokens for GPT-5 Responses API
- Added max_output_tokens parameter to GPT-5 request body using model.maxTokens
- This prevents GPT-5 from defaulting to very large token limits (e.g., 120k)
- Updated tests to expect max_output_tokens in GPT-5 request bodies
- Fixed test for handling unhandled stream events by properly mocking SDK fallback
* fix: add missing translations for reasoningEffort.minimal in Indonesian and Dutch locales
* fix: correct GPT-5 response ID persistence and usage
- Renamed metadata field from 'previous_response_id' to 'response_id' for clarity
- Fixed logic to correctly use the response_id from the previous message as previous_response_id for the next request
- This resolves the 'Previous response with id not found' errors that occurred after multiple turns in the same session
* feat: add robust error handling for GPT-5 previous_response_id failures
- Automatically retry without previous_response_id when it's not found (400 error)
- Clear stored lastResponseId to prevent reusing stale IDs
- Handle errors in both SDK and SSE fallback paths
- Log warnings when retrying to help with debugging
* fix: handle GPT-5 response ID race condition with nano model
- Add promise-based synchronization for response ID persistence
- Wait for pending response ID from previous request before using it
- Resolve promise when response ID is received or cleared
- Add 100ms timeout to avoid blocking too long on ID resolution
- Properly clean up resolver on errors to prevent memory leaks
This fixes the race condition where fast nano model responses could cause
the next request to be initiated before the response ID was fully persisted.
* fix: address PR review comments for GPT-5 implementation
- Extract usage normalization helper to reduce duplication
- Suppress conversation continuity for first message (but respect explicit metadata)
- Deduplicate response ID resolver logic
- Remove dead enableGpt5ReasoningSummary option references
- DRY up GPT-5 event/usage handling with normalizeGpt5Usage helper
- Centralize default GPT-5 reasoning effort using model info
- Fix Indonesian locale minimal string misplacement
- Add clarifying comments for Developer prefix usage
- Add TODO for future verbosity UI capability gating
- Fix failing test in reasoning.spec.ts
* fix(openai-native): address Roomote inline feedback\n\n- Delegate standard GPT-5 SSE event types to shared processor to reduce duplication\n- Add JSDoc for response ID accessors\n- Standardize key error messages for GPT-5 Responses API fallback\n- Extract persistGpt5Metadata() in Task to simplify metadata writes\n- Add malformed JSON SSE parsing test\n
* fix(openai-native,gpt5): correct usage cost calc (use calculateApiCostOpenAI incl. cache); enforce 'skip once' continuity via suppressPreviousResponseId; dedupe responseId resolver on SSE 400; feat: gate reasoning.summary by enableGpt5ReasoningSummary; centralize default reasoning effort; types/ui: add ModelInfo.supportsVerbosity and gate Verbosity UI by capability; refactor: avoid duplicate usage emission in SSE done/completed
* fix(gpt5): default enableGpt5ReasoningSummary=true to preserve tests and expected behavior
* fix(gpt5): canonicalize GPT-5 metadata key to previous_response_id and align enableGpt5ReasoningSummary default docs
* fix(openai-native): remove review artifact comments and guard GPT-5 in completePrompt
* feat: add GPT-5 model support
- Added GPT-5 models (gpt-5-2025-08-07, gpt-5-mini-2025-08-07, gpt-5-nano-2025-08-07)
- Added nectarine-alpha-new-reasoning-effort-2025-07-25 experimental model
- Set gpt-5-2025-08-07 as default OpenAI Native model
- Implemented GPT-5 specific handling with streaming and reasoning effort support
* fix: remove hardcoded temperature from GPT-5 handler
- Updated handleGPT5Message to use configurable temperature
- Now uses this.options.modelTemperature ?? OPENAI_NATIVE_DEFAULT_TEMPERATURE
- Maintains consistency with other model handlers
* feat: add reasoning effort support for all OpenAI models
* fix: update test to expect new default model gpt-5-2025-08-07
* feat: increase GPT-5 models context window to 400,000
- Updated context window from 256,000 to 400,000 for gpt-5-2025-08-07
- Updated context window from 256,000 to 400,000 for gpt-5-mini-2025-08-07
- Updated context window from 256,000 to 400,000 for gpt-5-nano-2025-08-07
- Updated context window from 256,000 to 400,000 for nectarine-alpha-new-reasoning-effort-2025-07-25
As requested by @daniel-lxs in PR #6819
* revert: remove GPT-5 models, keep only nectarine experimental model
- Removed gpt-5-2025-08-07, gpt-5-mini-2025-08-07, gpt-5-nano-2025-08-07
- Kept nectarine-alpha-new-reasoning-effort-2025-07-25 experimental model
- Reverted default model back to gpt-4o
- Updated tests and changeset accordingly
* feat: add GPT-5 models with updated context windows
- Added gpt-5-2025-08-07, gpt-5-mini-2025-08-07, gpt-5-nano-2025-08-07 models
- All GPT-5 models configured with 400,000 context window
- Updated nectarine model context window to 256,000
- All models configured with reasoning effort support
- Set gpt-5-2025-08-07 as default OpenAI Native model
- Added GPT-5 model handling in openai-native.ts
- Updated tests to reflect new default model
* fix: restore reasoning effort support for o1 series models
- Added supportsReasoningEffort: true to o1, o1-preview, and o1-mini models
- This restores the ability to use reasoning effort parameters with these models
- The existing code in openai-native.ts already handles reasoning effort correctly
* Revert "fix: restore reasoning effort support for o1 series models"
This reverts commit 7251237ae8.
* fix: restore reasoning effort support for o3 and o4 models
- Added supportsReasoningEffort: true to o3, o3-high, o3-low models
- Added supportsReasoningEffort: true to o4-mini, o4-mini-high, o4-mini-low models
- Added supportsReasoningEffort: true to o3-mini, o3-mini-high, o3-mini-low models
- These models have both supportsReasoningEffort and reasoningEffort properties
* Revert "fix: restore reasoning effort support for o3 and o4 models"
This reverts commit a75a2b8a69.
* fix: restore reasoning effort support for o3 and o4 models
- Added supportsReasoningEffort: true to o3, o3-high, o3-low models
- Added supportsReasoningEffort: true to o4-mini, o4-mini-high, o4-mini-low models
- Added supportsReasoningEffort: true to o3-mini, o3-mini-high, o3-mini-low models
* fix: adjust reasoning effort support for o3/o4 models
- Keep supportsReasoningEffort only for base o3, o4-mini, and o3-mini models
- Remove supportsReasoningEffort from -high and -low variants
- Position supportsReasoningEffort right before reasoningEffort property
* fix: remove nectarine experimental model
- Removed nectarine-alpha-new-reasoning-effort-2025-07-25 from openai.ts
- Removed nectarine handling from openai-native.ts (renamed to handleGpt5Message)
- Removed associated changeset file
- Keep GPT-5 models with developer role handling
* feat: implement full GPT-5 support with verbosity and minimal reasoning
- Add all three GPT-5 models with accurate pricing (.25/0 for gpt-5, /bin/sh.25/ for mini, /bin/sh.05//bin/sh.40 for nano)
- Implement verbosity control (low/medium/high) that passes through to API
- Add minimal reasoning effort support for fastest response times
- GPT-5 models use developer role instead of system role
- Set gpt-5-2025-08-07 as default OpenAI Native model
- Add Responses API infrastructure for future migration
- Update tests to verify all GPT-5 features
- All 27 tests passing
Note: UI controls for verbosity still need to be added in a follow-up PR
* feat: add verbosity setting for GPT-5 models
- Add VerbosityLevel type definition to model types
- Add verbosity field to ProviderSettings schema
- Create Verbosity UI component for settings
- Add verbosity labels to all localization files
- Integrate verbosity handling in model parameters transformation
- Update OpenAI native handler to support verbosity for GPT-5
- Add comprehensive tests for verbosity setting
- Update existing GPT-5 tests to use verbosity from settings
* Delete .roorules
---------
Co-authored-by: Roo Code <roomote@roocode.com>
Co-authored-by: hannesrudolph <hrudolph@gmail.com>
Co-authored-by: Daniel Riccio <ricciodaniel98@gmail.com>
Co-authored-by: Daniel <57051444+daniel-lxs@users.noreply.github.com>
* feat: add GLM-4.5 and OpenAI gpt-oss models to Fireworks provider
- Added GLM-4.5 (355B/32B active) and GLM-4.5-Air (106B/12B active) models from Z.ai
- Added gpt-oss-20b and gpt-oss-120b models from OpenAI
- All models configured with 128K context window
- Added comprehensive test coverage for all new models
Fixes#6753
* fix: update GLM-4.5 model IDs to use p instead of hyphen
- Changed glm-4-5 to glm-4p5
- Changed glm-4-5-air to glm-4p5-air
- Updated corresponding test cases
---------
Co-authored-by: Roo Code <roomote@roocode.com>
feat: increase Claude Code default max output tokens from 8k to 16k
- Changed CLAUDE_CODE_DEFAULT_MAX_OUTPUT_TOKENS from 8000 to 16000
- Users can still lower it to 8k via environment variable if needed
- Addresses issue #6125 regarding output token limits
Co-authored-by: Roo Code <roomote@roocode.com>
* feat: add prompt caching support for LiteLLM (#5791)
- Add litellmUsePromptCache configuration option to provider settings
- Implement cache control headers in LiteLLM handler when enabled
- Add UI checkbox for enabling prompt caching (only shown for supported models)
- Track cache read/write tokens in usage data
- Add comprehensive test for prompt caching functionality
- Reuse existing translation keys for consistency across languages
This allows LiteLLM users to benefit from prompt caching with supported models
like Claude 3.7, reducing costs and improving response times.
* fix: improve LiteLLM prompt caching to work for multi-turn conversations
- Convert system message to structured format with cache_control
- Handle both string and array content types for user messages
- Apply cache_control to content items, not just message level
- Update tests to match new message structure
This ensures prompt caching works correctly for all messages in a conversation,
not just the initial system prompt and first user message.
* fix: resolve TypeScript linter error for cache_control property
Use type assertion to handle cache_control property that's not in OpenAI types
