feat: Add DeepSeek as supported LLM provider #32
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- Add DEEPSEEK to LLMVendor enum - Update API key pattern detection for DeepSeek keys - Add deepseek-chat as default model for DeepSeek - Configure LLM client to properly handle DeepSeek API - Update README with DeepSeek as supported provider - Add tests for DeepSeek integration
OtherVibes
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Sep 25, 2025
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OtherVibes
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Hi @groxaxo 👋
Please focus on LLM_BASE_URL - it will be a great enhancement for this project
Thanks,
Zvi and the OtherVibes team
| LLMVendor.GROQ: re.compile(r"^gsk_[a-zA-Z0-9]{50,}"), | ||
| LLMVendor.XAI: re.compile(r"^xai-[a-zA-Z0-9]{40,}"), | ||
| LLMVendor.OPENROUTER: re.compile(r"^sk-or-[a-zA-Z0-9_-]{48}"), | ||
| LLMVendor.DEEPSEEK: re.compile(r"^sk-[a-zA-Z0-9]{20,}-deeplearning-ai$"), # DeepSeek API keys end with -deeplearning-ai |
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this regex does not seem to be valid for DeepSeek keys.
| self._litellm.aws_access_key_id = api_key | ||
| elif vendor == LLMVendor.VERTEX_AI: | ||
| # Vertex AI uses service account JSON | ||
| self._litellm.vertex_ai_key = api_key |
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As written in the note, DeepSeek are OpenAI compatible.
It would make much more sense to refactor this PR to add support to LLM_BASE_URL so users can use DeepSeek using customized URL - this would be excellent contribution.
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This PR adds DeepSeek as a supported LLM provider for MCP as a Judge.\n\n## Summary of Changes\n- Add DEEPSEEK to LLMVendor enum\n- Add API key pattern detection for DeepSeek (keys ending with -deeplearning-ai)\n- Add deepseek-chat as default model for DeepSeek\n- Configure LLM client to properly handle DeepSeek API calls\n- Update README to include DeepSeek as a supported provider\n- Add comprehensive tests for DeepSeek integration\n\n## Testing\n- All existing tests continue to pass (179/179)\n- New DeepSeek-specific tests added (4/4 passing)\n- Integration verified with mock API key patterns\n\nThis allows users to configure MCP as a Judge with DeepSeek API keys, providing another powerful LLM option for code evaluation and review.