Feature/Dynamic OpenAI compatible model fetching on front page#5562
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crazyrabbit0 wants to merge 4 commits intoKilo-Org:mainfrom
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Feature/Dynamic OpenAI compatible model fetching on front page#5562crazyrabbit0 wants to merge 4 commits intoKilo-Org:mainfrom
crazyrabbit0 wants to merge 4 commits intoKilo-Org:mainfrom
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January 30, 2026 22:44
Add support for dynamically fetching and displaying models from OpenAI-compatible providers. - Add openAiModels field to ExtensionState and context - Implement debounced model fetching request in ExtensionStateContext - Update useProviderModels hook to prioritize fetched models for OpenAI providers
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- Add .reviews/README.md: case study framing for AI-assisted PR review - Add 6 test evidence logs (combined batches + mega-combined) - Copy evidence logs to 13 individual PR directories - Update 13 status.json files with test_results + evidence_log refs - Total: ~38,000 lines of raw terminal output as proof of work Test runs (all fresh, turbo cache cleared): Batch 1: PRs Kilo-Org#5370+5660+5704 — 7,859 passed Individual: PR Kilo-Org#5562 — 7,803 passed Batch 2: PRs Kilo-Org#5739+5817 — 7,938 passed Batch 3: PRs Kilo-Org#5331+5568 — 7,935 passed Batch 4: PRs Kilo-Org#5667+5728+5807+5865+5869 — 7,935 passed Mega-combined: 11 PRs merged — 7,938 passed Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Dynamic OpenAI-Compatible Model Fetching on Front Page
Context
This PR implements dynamic model fetching for OpenAI-compatible providers on the front page. Previously, users had to open model provider settings to view all available models. With this change, Kilo Code now automatically queries the provider's
/modelsendpoint to retrieve available models on the front page whenever the configuration is updated, providing a more seamless and responsive experience. This is especially useful for local providers like LM Studio, Ollama, or custom OpenAI-compatible gateways where the available models frequently change.Implementation
The solution involves both frontend and backend changes to fetch and propagate model lists:
requestOpenAiModelsthat uses the provider's base URL and API key to fetch models from the standard OpenAI-compatible/modelsendpoint.ExtensionStateContext.tsxto include auseDebouncehook that triggers arequestOpenAiModelsmessage whenever the OpenAI configuration (Base URL, API Key, Headers) changes.useProviderModels.tsto consume theopenAiModelslist from the extension state.getModelsByProviderto transform the fetched string array intoModelRecordobjects using sane defaults for model info (context window, cost, etc.).Screenshots
How to Test
http://localhost:1234/v1)./modelsendpoint.