3 Commits

Author	SHA1	Message	Date
Alvis	f9618a9bbf	Integrate Bifrost LLM gateway, add test suite, implement memory pipeline ... - Add Bifrost (maximhq/bifrost) as LLM gateway: all inference routes through bifrost:8080/v1 with retry logic and observability; VRAMManager keeps direct Ollama access for VRAM flush/prewarm operations - Switch medium model from qwen3:4b to qwen2.5:1.5b (direct call, no tools) via _DirectModel wrapper; complex keeps create_deep_agent with qwen3:8b - Implement out-of-agent memory pipeline: _retrieve_memories pre-fetches relevant context (injected into all tiers), _store_memory runs as background task after each reply writing to openmemory/Qdrant - Add tests/unit/ with 133 tests covering router, channels, vram_manager, agent helpers; move integration test to tests/integration/ - Add bifrost-config.json with GPU Ollama (qwen2.5:0.5b/1.5b, qwen3:4b/8b, gemma3:4b) and CPU Ollama providers - Integration test 28/29 pass (only grammy fails — no TELEGRAM_BOT_TOKEN) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-03-12 13:50:12 +00:00
Alvis	ec45d255f0	wiki search people tested pipeline	2026-03-05 11:22:34 +00:00
Alvis	ea77b2308b	Add three-tier model routing with VRAM management and benchmark suite ... - Three-tier routing: light (router answers directly ~3s), medium (qwen3:4b + tools ~60s), complex (/think prefix → qwen3:8b + subagents ~140s) - Router: qwen2.5:1.5b, temp=0, regex pre-classifier + raw-text LLM classify - VRAMManager: explicit flush/poll/prewarm to prevent Ollama CPU-spill bug - agent_factory: build_medium_agent and build_complex_agent using deepagents (TodoListMiddleware + SubAgentMiddleware with research/memory subagents) - Fix: split Telegram replies >4000 chars into multiple messages - Benchmark: 30 questions (easy/medium/hard) — 10/10/10 verified passing easy→light, medium→medium, hard→complex with VRAM flush confirmed Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-02-28 17:54:51 +00:00