- Add minimax to KnownProvider and Api types
- Add MINIMAX_API_KEY to getEnvApiKey()
- Generate MiniMax-M2 and MiniMax-M2.1 models
- Add context overflow detection pattern
- Add tests to all required test files
- Update README and CHANGELOG with attribution
Also fixes:
- Bedrock duplicate toolResult ID when content has multiple blocks
- Sandbox extension unused parameter lint warning
Improve Gemini CLI provider retries and headers
- Add Antigravity endpoint fallback (tries daily sandbox then prod when baseUrl is unset)
- Parse retry delays from headers (Retry-After, x-ratelimit-reset, x-ratelimit-reset-after) before body parsing
- Derive stable sessionId from first user message for cache affinity
- Retry empty SSE streams with backoff without duplicate start/done events
- Add anthropic-beta header for Claude thinking models only
* Improve Cloud Code Assist error messages
- Extract just the message from verbose JSON error responses
- Extract cause from generic 'fetch failed' errors for better diagnostics
* Make 'other side closed' network error retryable
* Make 'other side closed' network error retryable
Adds cache points to system prompt and last user message for:
- Claude 3.5 Haiku
- Claude 3.7 Sonnet
- Claude 4.x models (Opus, Sonnet, Haiku)
Uses Bedrock's cachePoint blocks with 5-minute TTL.
Adds support for Amazon Bedrock with Claude models including:
- Full streaming support via Converse API
- Reasoning/thinking support for Claude models
- Cross-region inference model ID handling
- Multiple AWS credential sources (profile, IAM keys, API keys)
- Image support in messages and tool results
- Unicode surrogate sanitization
Also adds 'Adding a New Provider' documentation to AGENTS.md and README.
Co-authored-by: nickchan2 <nickchan2@users.noreply.github.com>
When running from source with tsx, the jiti aliases pointed to .js files
that don't exist (only .ts files exist). This caused jiti to fall back to
different module resolution, loading a separate instance of theme.ts where
initTheme() was never called, resulting in undefined theme.
Now checks if .js exists and falls back to .ts for dev mode compatibility.
Prevents undefined theme when extensions call ctx.ui.custom() in edge cases
where module resolution could cause the theme variable to be accessed before
initTheme() is called.
Claude models accessed through Google Cloud Code Assist API require
explicit id fields in both functionCall and functionResponse parts.
Without these IDs, the API returns 'tool_use.id: Field required' error.
Add requiresToolCallId() helper to centralize the Claude model detection
and include IDs in both tool call and tool result message conversions.
* Avoid cross-provider thought signatures
* Fix Google thought signature replay
Filter thought signatures to same provider with base64 validation and rename the transform helper for clarity.
- Store thoughtSignature on text blocks during streaming (all 3 providers)
- Replay textSignature as thoughtSignature in convertMessages
- Remove redundant conditional since retainThoughtSignature handles undefined
Per Google docs, text part signatures are optional but recommended for
high-quality reasoning in multi-turn conversations.
- isThinkingPart now only checks thought === true, not thoughtSignature
- thoughtSignature is for context replay and can appear on any part type
- Store thoughtSignature on text blocks as textSignature for proper replay
- Remove id from functionCall/functionResponse (unsupported by Vertex/Cloud Code Assist)
Refs: https://ai.google.dev/gemini-api/docs/thought-signatures
Co-authored-by: Amp <amp@ampcode.com>
Renamed from supportsStreamOptions to clarify this controls stream_options: { include_usage: true }.
Defaults to true (no behavioral change for existing providers).
Providers like gatewayz.ai that reject this parameter can set supportsUsageInStreaming: false in model config.
Based on #596 by @XesGaDeus
OpenRouter with models like openai/gpt-5.2 enforces strict mode which
requires all properties in the required array. Setting strict: false
allows optional parameters without null unions, matching the approach
already used in openai-responses.ts.
