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Phase 1: Sahel-Voice-Lab — The Memory Loop
jefffffff9 +1: Claude Sonnet 4.6New project pivot: self-learning voice assistant for Bambara/Fula using 100% non-Meta tech stack. New files: - app_lab.py — Gradio UI: push-to-talk + last 5 words panel - src/memory/memory_manager.py — persists vocabulary.jsonl to HF Hub - src/llm/gemma_client.py — Gemma via HF Serverless Inference API - data/vocabulary.jsonl — empty initial vocabulary store Flow: audio → Whisper STT → Gemma (with vocabulary context) → teaching intent → MemoryManager.add_word_pair() → Hub push question intent → answer from vocabulary conversation → natural reply README.md updated: app_file changed to app_lab.py, stack documented. Stack: openai/whisper-large-v3-turbo (STT), google/gemma-3-4b-it (LLM), Waxal TTS (Phase 2), HF Dataset for memory. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>096b19d