- Removed `vertex-compat` executor and related configuration.
- Consolidated Vertex compatibility checks into `vertex` handling with `apikey`-based model resolution.
- Streamlined model generation logic for Vertex API key entries.
Extract applyThinkingMetadata and applyThinkingMetadataCLI helpers to
payload_helpers.go and use them across all four Gemini-based executors:
- gemini_executor.go (Execute, ExecuteStream, CountTokens)
- gemini_cli_executor.go (Execute, ExecuteStream, CountTokens)
- aistudio_executor.go (translateRequest)
- antigravity_executor.go (Execute, ExecuteStream)
This eliminates code duplication introduced in the -reasoning suffix PR
and centralizes the thinking config application logic.
Net reduction: 28 lines of code.
Adds support for the `-reasoning` model name suffix which enables
thinking/reasoning mode with dynamic budget. This allows clients to
request reasoning-enabled inference using model names like
`gemini-2.5-flash-reasoning` without explicit configuration.
The suffix is normalized to the base model (e.g., gemini-2.5-flash)
with thinkingBudget=-1 (dynamic) and include_thoughts=true.
Follows the existing pattern established by -nothinking and
-thinking-N suffixes.
- Updated `usage_helpers.go` to call `EnsureIndex()` for proper index assignment in reporter initialization.
- Adjusted `auth/manager.go` to assign auth indices inside a locked section when they are unassigned, ensuring thread safety and consistency.
Fixes an issue where Claude thinking models would return 400 errors when
the thinking.budget_tokens was greater than or equal to max_tokens.
Changes:
- Add MaxCompletionTokens: 128000 to all Claude thinking model definitions
- Add ensureMaxTokensForThinking() function in claude_executor.go that:
- Checks if thinking is enabled with a budget_tokens value
- Looks up the model's MaxCompletionTokens from the registry
- Ensures max_tokens is set to at least the model's MaxCompletionTokens
- Falls back to budget_tokens + 4000 buffer if registry lookup fails
This ensures Anthropic API constraint (max_tokens > thinking.budget_tokens)
is always satisfied when using extended thinking features.
Fixes: #339🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
**feat(handlers, executor): add Gemini 3 Pro Preview support and refine Claude system instructions**
- Added support for the new "Gemini 3 Pro Preview" action in Gemini handlers, including detailed metadata and configuration.
- Removed redundant `cache_control` field from Claude system instructions for cleaner payload structure.
**fix(executor): replace redundant commented code with `checkSystemInstructions` helper**
- Replaced commented-out `sjson.SetRawBytes` lines with the new `checkSystemInstructions` function.
- Centralized system instruction handling for better code clarity and reuse.
- Ensured consistent logic for managing `system` field across Claude executor flows.
- Commented out multiple instances of `sjson.SetRawBytes` for setting `system` key to Claude instructions as they are redundant.
- Code cleanup to improve clarity and maintainability without affecting functionality.
- Add Claude thinking model definitions (sonnet-4-5-thinking, opus-4-5-thinking variants)
- Add Thinking support for antigravity models with -thinking suffix
- Add injectThinkingConfig() for automatic thinking budget based on model suffix
- Add resolveUpstreamModel() mappings for thinking variants to actual Claude models
- Add extractAndRemoveBetas() to convert betas array to anthropic-beta header
- Update applyClaudeHeaders() to merge custom betas from request body
Closes#324
- Added additional metadata fields (`Name`, `Description`, `DisplayName`, `Version`) to `ModelInfo` struct initialization for better model representation.
- Removed unnecessary whitespace in the code.
- Restored `thoughtSignature` validator bypass for model-specific parts in Gemini content processing.
- Removed redundant logic from the `executor` for cleaner handling.
Remove generationConfig.maxOutputTokens, generationConfig.responseMimeType and generationConfig.responseJsonSchema from the Gemini payload in translateRequest so we no longer send unsupported or conflicting response configuration fields. This lets the backend or caller control response formatting and output limits and helps prevent potential API errors caused by these keys.
- Updated `defaultAntigravityAgent` to version `1.11.5`.
- Adjusted const value formatting for improved readability.
**feat(executor): introduce fallback mechanism for Antigravity base URLs**
- Added retry logic with fallback order for Antigravity base URLs to handle request errors and rate limits.
- Refactored base URL handling with `antigravityBaseURLFallbackOrder` and related utilities.
- Enhanced error handling in non-streaming and streaming requests with retry support and improved metadata reporting.
- Updated `buildRequest` to support dynamic base URL assignment.
- Improved Antigravity executor to handle `thinkingConfig` adjustments and default `thinkingBudget` when `thinkingLevel` is removed.
- Updated translator response handling to set default values for output token counts when specific token data is missing.
- Introduced `modelName2Alias` and `alias2ModelName` functions for mapping between model names and aliases.
- Improved Antigravity payload transformation to include alias-to-model name conversion.
- Enhanced processing for Claude Sonnet models to adjust template parameters based on schema presence.
**feat(executor): enhance WebSocket error handling and metadata logging**
- Added handling for stream closure before start with appropriate error recording.
- Improved metadata logging for non-OK HTTP status codes in WebSocket responses.
- Consolidated event processing logic with `processEvent` for better error handling and payload management.
- Refactored stream initialization to include the first event handling for smoother execution flow.
- Introduced request and response translation functions to enable compatibility between OpenAI Chat Completions API and Antigravity.
- Registered translation utilities for both streaming and non-streaming scenarios.
- Added support for reasoning content, tool calls, and metadata handling.
- Established request normalization and embedding for Antigravity-compatible payloads.
- Added new fields to `Params` struct for better tracking of finish reasons, usage metadata, and tool usage.
- Refactored handling of response transitions, final events, and state-driven logic in `ConvertAntigravityResponseToClaude`.
- Introduced `appendFinalEvents` and `resolveStopReason` helper functions for cleaner separation of concerns.
- Added `TotalTokenCount` field to `Params` struct for enhanced token tracking.
- Updated token count calculations to fallback on `TotalTokenCount` when specific counts are missing.
- Introduced `hasNonZeroUsageMetadata` function to validate presence of token data in `usage_metadata`.
- Implemented OAuth login flow for the Antigravity provider in `auth/antigravity.go`.
- Added `AntigravityExecutor` for handling requests and streaming via Antigravity APIs.
- Created `antigravity_login.go` command for triggering Antigravity authentication.
- Introduced OpenAI-to-Antigravity translation logic in `translator/antigravity/openai/chat-completions`.
**refactor(translator, executor): update Gemini CLI response translation and add Antigravity payload customization**
- Renamed Gemini CLI translation methods to align with response handling (`ConvertGeminiCliResponseToGemini` and `ConvertGeminiCliResponseToGeminiNonStream`).
- Updated `init.go` to reflect these method changes.
- Introduced `geminiToAntigravity` function to embed metadata (`model`, `userAgent`, `project`, etc.) into Antigravity payloads.
- Added random project, request, and session ID generators for enhanced tracking.
- Streamlined `buildRequest` to use `geminiToAntigravity` transformation before request execution.
**feat(executor): add thinking level to budget conversion utility**
- Introduced `ConvertThinkingLevelToBudget` to map thinking level ("high"/"low") to corresponding budget values.
- Applied the utility in `aistudio_executor.go` before stripping unsupported configs.
- Updated dependencies to include `tidwall/gjson` for JSON parsing.
Fix critical bug where ExecuteStream would create a streaming channel
from a failed (non-2xx) response after exhausting all retries with no
fallback models available.
When retries were exhausted on the last model, the code would break from
the inner loop but fall through to streaming channel creation (line 401),
immediately returning at line 461. This made the error handling code at
lines 464-471 unreachable, causing clients to receive an empty/closed
stream instead of a proper error response.
Solution: Check if httpResp is non-2xx before creating the streaming
channel. If failed, continue the outer loop to reach error handling.
Identified by: codex-bot review
Ref: https://github.com/router-for-me/CLIProxyAPI/pull/280#pullrequestreview-3484560423
Fix critical bug where ExecuteStream would create a streaming channel
using a 429 error response instead of continuing to the next fallback
model after exhausting retries.
When 429 retries were exhausted and a fallback model was available,
the inner retry loop would break but immediately fall through to the
streaming channel creation, attempting to stream from the failed 429
response instead of trying the next model.
Solution: Add shouldContinueToNextModel flag to explicitly skip the
streaming logic and continue the outer model loop when appropriate.
Identified by: codex-bot review
Ref: https://github.com/router-for-me/CLIProxyAPI/pull/280#pullrequestreview-3484479106
Implement Google RetryInfo.retryDelay support for handling 429 rate
limit errors. Retries same model up to 3 times using exact delays
from Google's API before trying fallback models.
- Add parseRetryDelay() to extract Google's retry guidance
- Implement inner retry loop in Execute() and ExecuteStream()
- Context-aware waiting with cancellation support
- Cap delays at 60s maximum for safety
- Introduced `gpt-5.1-codex-max` variants to model definitions (`low`, `medium`, `high`, `xhigh`).
- Updated executor logic to map effort levels for Codex Max models.
- Added `lastCodexMaxPrompt` processing for `gpt-5.1-codex-max` prompts.
- Defined instructions for `gpt-5.1-codex-max` in a new file: `codex_instructions/gpt-5.1-codex-max_prompt.md`.
Extract reasoning effort mapping into a reusable function `setReasoningEffortByAlias` to reduce redundancy and improve maintainability. Introduce support for the "gpt-5.1-none" variant in the registry and runtime executor.
Stop advertising and mapping the unsupported gpt-5.1-minimal variant in the model registry and Codex executor, and align bare gpt-5.1 requests to use medium reasoning effort like Codex CLI while preserving minimal for gpt-5.
Expand executor logic to handle GPT-5.1 Codex family and its variants, including reasoning effort configurations for minimal, low, medium, and high levels. Ensure proper mapping of models to payload parameters.
Introduce `PayloadConfig` in the configuration to define default and override rules for modifying payload parameters. Implement `applyPayloadConfig` and `applyPayloadConfigWithRoot` to apply these rules across various executors, ensuring consistent parameter handling for different models and protocols. Update all relevant executors to utilize this functionality.
feat(runtime): add support for GPT-5.1 models and variants
Introduce GPT-5.1 model family, including minimal, low, medium, high, Codex, and Codex Mini variants. Update tokenization and reasoning effort handling to accommodate new models in executor and registry.
Introduce support for multi-project Gemini CLI logins, including shared and virtual credential management. Enhance runtime, metadata handling, and token updates for better project granularity and consistency across virtual and shared credentials. Extend onboarding to allow activating all available projects.
Extend `resolveUsageSource` to support Vertex projects by extracting and normalizing `project_id` or `project` from the metadata for accurate source resolution.
Extend `vertexAccessToken` to support proxy-aware HTTP clients and update calls accordingly for better configurability. Add `deleteTokenRecord` to handle token cleanup, improving management of authentication files.
Introduce Vertex AI Gemini integration with support for service account-based authentication, credential storage, and import functionality. Added new executor for Vertex AI requests, including execution and streaming paths, and integrated it into the core manager. Enhanced CLI with `--vertex-import` flag for importing service account keys.
Add `ensurePublished` to guarantee request counting even when usage fields (e.g., tokens) are absent in OpenAI-compatible executor responses, particularly for streaming paths.
