feat(translator): improve system message handling and content indexing across translators
- Updated logic for processing system messages in `claude`, `gemini`, `gemini-cli`, and `antigravity` translators.
- Introduced indexing for `systemInstruction.parts` to ensure proper ordering and handling of multi-part content.
- Added safeguards for accurate content transformation and serialization.
This change removes the translation logic for several non-standard, proprietary extensions used to configure thinking/reasoning. Specifically, support for `extra_body.google.thinking_config` and the Anthropic-style `thinking` object has been dropped from the OpenAI request translators.
This simplification streamlines the translators, focusing them on the standard `reasoning_effort` parameter. It also removes the need to look up model information from the registry within these components.
BREAKING CHANGE: Support for non-standard thinking configurations via `extra_body.google.thinking_config` and the Anthropic-style `thinking` object has been removed. Clients should now use the standard `reasoning_effort` parameter to control reasoning.
Enhanced node structure by including `thoughtSignature` for inline data parts in Gemini OpenAI, Gemini CLI, and Antigravity request handlers to improve traceability of thought processes.
Updated Antigravity, Gemini, and Gemini-CLI translators to process `systemResult` of type `string` for system instructions. Ensures properly formatted JSON with dynamic content assignment.
fix(antigravity): validate function arguments before serialization
Ensure `function.arguments` is a valid JSON before setting raw bytes, fallback to setting as parameterized content if invalid.
feat: handle array input for system instructions in translators
Enhanced Gemini, Gemini-CLI, and Antigravity translators to process array content for system instructions. Adds support for assigning roles and handling multiple content parts dynamically.
Optimized the handling of JSON serialization and deserialization by replacing redundant `json.Marshal` and `json.Unmarshal` calls with `sjson` and `gjson`. Introduced a `marshalJSONValue` utility for compact JSON encoding, improving performance and code simplicity. Removed unused `encoding/json` imports.
Improve parsing of tool call inputs and Antigravity compatibility to avoid invalid thinking/tool_use errors.
- Parse tool call inputs robustly by accepting both object and JSON-string formats and only produce a functionCall part when valid args exist, reducing spurious or malformed parts.
- Preserve the skip_thought_signature_validator approach for calls without a valid thinking signature but stop toggling/tracking a separate "disable thinking" flag; this prevents unnecessary removal of thinkingConfig.
- Sanitize tool input schemas before attaching them to the Antigravity request to improve compatibility.
- Append the interleaved-thinking hint as a new parts entry instead of overwriting/setting text directly, preserving structure.
- Remove unused tracking logic and related comments to simplify flow.
These changes reduce errors related to missing/invalid thinking signatures, improve schema compatibility, and make hint injection safer and more consistent.
Prefer cached signatures and avoid injecting dummy thinking blocks; instead remove unsigned thinking blocks and add a skip sentinel for tool calls without a valid signature. Generate stable session IDs from the first user message, apply schema cleaning only for Claude models, and reorder thinking parts so thinking appears first. For Gemini, remove thinking blocks and attach a skip sentinel to function calls. Simplify response handling by passing raw function args through (remove special Bash conversion). Update and add tests to reflect the new behavior.
These changes prevent rejected dummy signatures, improve compatibility with Antigravity’s signature validation, provide more stable session IDs for conversation grouping, and make request/response translation more robust.
Refactors the reasoning effort conversion logic for Gemini models.
The update specifically addresses how `reasoning_effort` is translated into Gemini 3 specific thinking configurations (`thinkingLevel`, `includeThoughts`) and ensures that numeric budgets are not incorrectly applied to level-based models.
Changes include:
- Differentiating conversion logic for Gemini 3 models versus other models.
- Handling `none`, `auto`, and validated thinking levels for Gemini 3.
- Maintaining existing conversion for models not using discrete thinking levels.
Improve the cache eviction routine to sort entries by timestamp using the standard library sort routine (stable, clearer and faster than the prior manual selection/bubble logic), and remove a redundant request-derived session ID helper in favor of the centralized session ID function. Also drop now-unused crypto/encoding imports.
This yields clearer, more maintainable eviction logic and removes duplicated/unused code and imports to reduce surface area and potential inconsistencies.
Improve robustness when handling "thinking" content by using a dedicated helper to extract the thinking text. This ensures wrapped or nested thinking objects are handled correctly instead of relying on a direct string extraction, reducing parsing errors for complex payloads.
Normalize Bash tool arguments by converting a "command" key into "cmd" using JSON-aware parsing, avoiding brittle string replacements that could corrupt values. Apply this conversion in both streaming and non-streaming response paths so bash-style tool calls are emitted with the expected "cmd" field.
Add support for accumulating thinking text and carrying session identifiers to enable signature caching/restore for unsigned thinking blocks, improving handling of thinking-state continuity across requests/responses.
Also perform small cleanups: import logging, tidy comments and test descriptions. These changes make tool-argument handling more robust and enable reliable signature restoration for thinking blocks.
Move OpenAI `reasoning_effort` -> Gemini `thinkingConfig` budget logic into
shared helpers used by Gemini, Gemini CLI, and antigravity translators.
Normalize Claude thinking handling by preferring positive budgets, applying
budget token normalization, and gating by model support.
Always convert Gemini `thinkingBudget` back to OpenAI `reasoning_effort` to
support allowCompat models, and update tests for normalization behavior.
