Add Ollama LLM integration with rule-based fallback
- engine/llm.py: Ollama /api/chat client with OpenAI-style tool schema
- engine/reasoning.py: LLM path with 4-tier validation:
1. tool exists in registry
2. tool passes location-gating
3. args parse cleanly
4. otherwise fall back to rule-based engine
- env vars: EMERGENCE_LLM_{URL,MODEL,TIMEOUT,ENABLED}
- Default model: llama3.2:3b (best speed/quality tradeoff for tool use)
- 11 new mock tests in tests/test_llm.py (no network)
- smoke_test_llm.py: live smoke against real Ollama
- README: 'LLM Integration' section with model table + setup
Live-verified: 4/4 decisions via llama3.2:3b in 1-3s, character-consistent
('facilitate honest debate', 'work together', 'urgency and collaboration').
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