feat: add Fireworks AI provider and fix model tier resolution#670
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feat: add Fireworks AI provider and fix model tier resolution#670
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Add Fireworks AI as a new LLM provider, enabling access to models like Kimi K2.5, DeepSeek V3P2, and GLM-5 via the Fireworks inference API. - New provider package at packages/providers/fireworks/ - Register provider in core schemas, runtime factory, and TUI config - Add known models with context window metadata - Add E2E provider test case and CI secret for FIREWORKS_API_KEY Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The default fallback was hardcoded to "middle" tier, which caused providers with only "high" tier models (e.g. Fireworks) to fail model resolution. Now cascades high → middle → low via resolveModelTierWithFallback, ensuring the best available model is always selected. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Summary
@perstack/fireworks-provider)Changes
Fireworks provider
packages/providers/fireworks/— adapter, error handling, unit tests"fireworks"toProviderName,FireworksProviderConfigFIREWORKS_API_KEYenv mapping and provider config builderFIREWORKS_API_KEYto CI workflowModel tier resolution
resolveModelTierWithFallback()that cascades high → middle → lowcoordinator-executor.tsanddelegation-executor.tsto use cascade fallbackdefaultModelTierdoesn't matchTest plan
bun run test)🤖 Generated with Claude Code