- Updated `SDKConfig` to use `nonstream-keepalive-interval` (seconds) instead of the boolean `nonstream-keepalive`.
- Refactored handlers and logic to incorporate the new interval-based configuration.
- Updated config diff, tests, and example YAML to reflect the changes.
- Introduced `StartNonStreamingKeepAlive` to emit periodic blank lines during non-streaming responses.
- Added `nonstream-keepalive` configuration option in `SDKConfig`.
- Updated handlers to utilize `StartNonStreamingKeepAlive` and ensure proper cleanup.
- Extended config diff and tests to include `nonstream-keepalive` changes.
Refactor model management to include an optional `prefix` field for model credentials, enabling better namespace handling. Update affected configuration files, APIs, and handlers to support prefix normalization and routing. Remove unused OpenAI compatibility provider logic to simplify processing.
The WriteErrorResponse function now caches the error response body in the gin context.
The deferred request logger checks for this cached response. If an error response is found, it bypasses the standard response logging. This prevents scenarios where an error is logged twice or an empty payload log overwrites the original, more detailed error log.
The API error handling is updated to return a structured JSON payload
instead of a plain text message. This provides more context and allows
clients to programmatically handle different error types.
The new error response has the following structure:
{
"error": {
"message": "...",
"type": "..."
}
}
The `type` field is determined by the HTTP status code, such as
`authentication_error`, `rate_limit_error`, or `server_error`.
If the underlying error message from an upstream service is already a
valid JSON string, it will be preserved and returned directly.
BREAKING CHANGE: API error responses are now in a structured JSON
format instead of plain text. Clients expecting plain text error
messages will need to be updated to parse the new JSON body.
- Added support for parsing and normalizing dynamic thinking model suffixes.
- Centralized budget resolution across executors and payload helpers.
- Retired legacy Gemini-specific thinking handlers in favor of unified logic.
- Updated executors to use metadata-based thinking configuration.
- Added `ResolveOriginalModel` utility for resolving normalized upstream models using request metadata.
- Updated executors (Gemini, Codex, iFlow, OpenAI, Qwen) to incorporate upstream model resolution and substitute model values in payloads and request URLs.
- Ensured fallbacks handle cases with missing or malformed metadata to derive models robustly.
- Refactored upstream model resolution to dynamically incorporate metadata for selecting and normalizing models.
- Improved handling of thinking configurations and model overrides in executors.
- Removed hardcoded thinking model entries and migrated logic to metadata-based resolution.
- Updated payload mutations to always include the resolved model.
- Introduced `appendAPIResponse` helper to preserve and append data to existing API responses.
- Ensured newline inclusion when appending, if necessary.
- Improved `nil` and data type checks for response handling.
- Updated middleware to skip request logging for `GET` requests.
- add fallback handler that forwards Amp provider requests to ampcode.com when the provider isn’t configured locally
- wrap AMP provider routes with the fallback so requests always have a handler
- share Gemini thinking model normalization helper between core handlers and AMP fallback
- Add 'created' field to model registry for tracking model creation time
- Implement GetFirstAvailableModel() to find the first available model by newest creation timestamp
- Add ResolveAutoModel() utility function to resolve "auto" model name to actual available model
- Update request handler to resolve "auto" model before processing requests
- Ensures automatic model selection when "auto" is specified as model name
This enables dynamic model selection based on availability and creation time, improving the user experience when no specific model is requested.
Implements functionality to parse model names with provider information in the format "provider://model" This allows dynamic provider selection rather than relying only on predefined mappings.
The change affects all execution methods to properly handle these dynamic model specifications while maintaining compatibility with the existing approach for standard model names.
- Updated Execute methods to include enhanced error handling via `StatusCode` and `Headers` extraction.
- Introduced structured error responses for cooling down scenarios, providing additional metadata and retry suggestions.
- Refined quota management, allowing for differentiation between cool-down, disabled, and other block reasons.
- Improved model filtering logic based on client availability and suspension criteria.
feat(gemini): add Gemini thinking configuration support and metadata normalization
- Introduced logic to parse and apply `thinkingBudget` and `include_thoughts` configurations from metadata.
- Enhanced request handling to include normalized Gemini model metadata, preserving the original model identifier.
- Updated Gemini and Gemini-CLI executors to apply thinking configuration based on metadata overrides.
- Refactored handlers to support metadata extraction and cloning during request preparation.
- Replaced `config.Config` with `config.SDKConfig` across components for simpler configuration management.
- Updated proxy setup functions and handlers to align with `SDKConfig` improvements.
- Reorganized handler imports to match new SDK structure.
