* Add native tool calling support to OpenAI-compatible
* Fix OpenAI strict mode schema validation by adding converter methods to BaseProvider
- Add convertToolsForOpenAI() and convertToolSchemaForOpenAI() methods to BaseProvider
- These methods ensure all properties are in required array and convert nullable types
- Remove line_ranges from required array in read_file tool (converter handles it)
- Update OpenAiHandler and BaseOpenAiCompatibleProvider to use helper methods
- Eliminates code duplication across multiple tool usage sites
- Fixes: OpenAI completion error: 400 Invalid schema for function 'read_file'
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Co-authored-by: daniel-lxs <ricciodaniel98@gmail.com>
openai-native: include reasoning.encrypted_content only when reasoningEffort is set; prevent Responses API error on non-reasoning models. types: remove supportsVerbosity from gpt-5-chat-latest to avoid invalid verbosity error. Fixes#9225
* Migrate conversation continuity to plugin-side encrypted reasoning items (Responses API)
Summary
We moved continuity off OpenAI servers and now maintain conversation state locally by persisting and replaying encrypted reasoning items. Requests are stateless (store=false) while retaining the performance/caching benefits of the Responses API.
Why
This aligns with how Roo manages context and simplifies our Responses API implementation while keeping all the benefits of continuity, caching, and latency improvements.
What changed
- All OpenAI models now use the Responses API; system instructions are passed via the top-level instructions field; requests include store=false and include=["reasoning.encrypted_content"].
- We persist encrypted reasoning items (type: "reasoning", encrypted_content, optional id) into API history and replay them on subsequent turns.
- Reasoning summaries default to summary: "auto" when supported; text.verbosity only when supported.
- Atomic persistence via safeWriteJson.
Removed
- previous_response_id flows, suppressPreviousResponseId/skipPrevResponseIdOnce, persistGpt5Metadata(), and GPT‑5 response ID metadata in UI messages.
Kept
- taskId and mode metadata for cross-provider features.
Result
- ZDR-friendly, stateless continuity with equal or better performance and a simpler codepath.
* fix(webview): remove unused metadata prop from ReasoningBlock render
* Responses API: retain response id for troubleshooting (not continuity)
Continuity is stateless via encrypted reasoning items that we persist and replay. We now capture the top-level response id in OpenAiNativeHandler and persist the assistant message id into api_conversation_history.json solely for debugging/correlation with provider logs; it is not used for continuity or control flow.
Also: silence request-body debug logging to avoid leaking prompts.
* remove DEPRECATED tests
* chore: remove unused Task types file to satisfy knip CI
* fix(task): properly type cleanConversationHistory and createMessage args in Task to address Dan's review
* feat: convert Chutes to dynamic/router provider
- Add chutes to dynamicProviders array in provider-settings
- Add chutes entry to dynamicProviderExtras in api.ts
- Create fetcher function for Chutes models API
- Convert ChutesHandler to extend RouterProvider
- Update tests to work with dynamic provider setup
- Export chutesDefaultModelInfo for RouterProvider constructor
* fix: address security and code quality issues from review
- Fix potential API key leakage in error logging
- Add temperature support check before setting temperature
- Improve code consistency with RouterProvider patterns
* fix: add chutes to routerModels initialization
- Fix TypeScript error in webviewMessageHandler
- Ensure chutes is included in RouterName Record type
* Fixes
* Support reasoning
* Fix tests
* Remove reasoning checkbox
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Co-authored-by: Roo Code <roomote@roocode.com>
Co-authored-by: Matt Rubens <mrubens@users.noreply.github.com>
* 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
