- Remove BIFROST constant and fetch_bifrost_logs() from common.py
- Add LITELLM constant (localhost:4000)
- Replace test_memory.py test 4 (Bifrost pass-through) with LiteLLM health check
Fixes#5
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Pre-routing URL fetch: any message with URLs gets content fetched
async (httpx.AsyncClient) before routing via _fetch_urls_from_message()
- URL context and memories gathered concurrently with asyncio.gather
- Light tier upgraded to medium when URL content is present
- url_context injected into system prompt for medium and complex agents
- Complex agent retains web_search/fetch_url tools + receives pre-fetched content
- Medium model restored to qwen3:4b (was temporarily qwen2.5:1.5b)
- Unit tests added for _extract_urls
- ARCHITECTURE.md: added Tool Handling, Crawl4AI Integration, Memory Pipeline sections
- CLAUDE.md: updated request flow and Crawl4AI integration docs
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- 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>