feat: [2026NewYearChallenge] Model Provider Extensions — Groq#224
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yeziR4 wants to merge 2 commits intoNevaMind-AI:mainfrom
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feat: [2026NewYearChallenge] Model Provider Extensions — Groq#224yeziR4 wants to merge 2 commits intoNevaMind-AI:mainfrom
yeziR4 wants to merge 2 commits intoNevaMind-AI:mainfrom
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- Implement GroqLLMBackend with OpenAI-compatible API - Register backend in HTTP client and backends module - Add comprehensive test suite with live API validation - Include example integration script - Support Llama 3.3, Mixtral, Gemma models (15+ total) - 10-100x faster inference with Groq LPU architecture
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Hi, the build for this PR is not passing yet. Please make the necessary updates, and we’ll review again after that. Thanks! @yeziR4 |
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On Wed, Jan 21, 2026 at 13:03 An Kaisen ***@***.***> wrote:
*ankaisen* left a comment (NevaMind-AI/memU#224)
<#224 (comment)>
@yeziR4 <https://github.com/yeziR4> Thanks for the contribution! The same
functionality (Grok AI support) has already been implemented and merged in
#236 <#236> , so we’re closing
this one.
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No this is for groq not Grok 😭please cross check
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this is for groq not grok |
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Summary
Adds complete Groq provider integration for ultra-fast LLM inference using Groq's LPU architecture, delivering 10-100x faster inference speeds.
Features
Implementation
Files Added
src/memu/llm/backends/groq.py- Groq backend implementation (100+ lines)tests/test_groq.py- Comprehensive test suiteexamples/example_groq_integration.py- Working example scriptFiles Modified
src/memu/llm/backends/__init__.py- Register GroqLLMBackendsrc/memu/llm/http_client.py- Add Groq to LLM_BACKENDS registryArchitecture
LLMBackendbase classTesting Results
Unit Tests ✅ ALL PASSED