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1d2787766e72b1f9042f6dfd4ab85d3fddf2c71b
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6 Commits

Author SHA1 Message Date
Alvis
1f5e272600 Switch from Bifrost to LiteLLM; add Matrix channel; update rules 
Infrastructure:
- docker-compose.yml: replace bifrost container with LiteLLM proxy
  (host.docker.internal:4000); complex model → deepseek-r1:free via
  OpenRouter; add Matrix URL env var; mount logs volume
- bifrost-config.json: add auth_config + postgres config_store (archived)

Routing:
- router.py: full semantic 3-tier classifier rewrite — nomic-embed-text
  centroids for light/medium/complex; regex pre-classifiers for all tiers;
  Russian utterance sets expanded
- agent.py: wire LiteLLM URL; add dry_run support; add Matrix channel

Channels:
- channels.py: add Matrix adapter (_matrix_send via mx- session prefix)

Rules / docs:
- agent-pipeline.md: remove /think prefix requirement; document automatic
  complex tier classification
- llm-inference.md: update BIFROST_URL → LITELLM_URL references; add
  remote model note for complex tier
- ARCHITECTURE.md: deleted (superseded by README.md)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-03-24 02:14:13 +00:00
Alvis
3ae1cefbd4 WeatherTool: fetch open-meteo directly, skip LLM for fast tool replies 
- Replace SearXNG search with direct open-meteo.com API call (no key needed)
- WeatherTool now returns a ready-to-deliver reply string
- agent.py: short-circuit router+LLM when fast tools return a result (tier=fast)
- router.py: fast tool match no longer triggers light reply generation

Weather latency: 105-190s → ~1s

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-03-15 09:42:55 +00:00
Alvis
f5fc2e9bfb Introduce FastTools: pre-flight classifier + context enrichment 
New fast_tools.py module:
- FastTool base class (matches + run interface)
- RealTimeSearchTool: SearXNG search for weather/news/prices/scores
- FastToolRunner: classifier that checks all tools, runs matching
  ones concurrently and returns combined context

Router accepts FastToolRunner; any_matches() forces medium tier
before LLM classification (replaces _MEDIUM_FORCE_PATTERNS regex).

agent.py: _REALTIME_RE and _searxng_search_async removed; pre-flight
gather now includes fast_tool_runner.run_matching() alongside URL
fetch and memory retrieval.

To add a new fast tool: subclass FastTool, add to the list in agent.py.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-03-13 05:18:44 +00:00
Alvis
436299f7e2 Add real-time query handling: pre-search enrichment + routing fix 
- router.py: add _MEDIUM_FORCE_PATTERNS to block weather/news/price
  queries from light tier regardless of LLM classification
- agent.py: add _REALTIME_RE and _searxng_search_async(); real-time
  queries now run SearXNG search concurrently with URL fetch + memory
  retrieval, injecting snippets into medium system prompt
- tests/use_cases/weather_now.md: use case test for weather queries

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-03-13 05:08:08 +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