Files
Multi_Swarm_Coevolutive/.env.example
T
Adriano 9c53995f23 feat(config): align tier defaults to cost-conscious models + qwen3-235b on tier C
- Tier S → google/gemini-3-flash-preview ($0.50/$3.00)
- Tier A/B → deepseek/deepseek-v4-flash ($0.14/$0.28)
- Tier C → qwen/qwen3-235b-a22b-2507 ($0.071/$0.10) — Phase 2 target
- Tier D → openai/gpt-oss-20b ($0.03/$0.14)

Aggiornato cost_tracker con prezzi reali per tier. Defaults config.py
ora rispecchiano .env corrente per evitare divergenze dead-code.

Tier S/A/B/D restano cablati ma non ancora invocati nel loop Phase 2
(solo Hypothesis tier C attivo).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-11 22:13:49 +02:00

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# Cerbero MCP — VPS endpoint per dati storici reali
CERBERO_BASE_URL=https://cerbero-mcp.tielogic.xyz
# NOTE: per dati storici reali Phase 1 (BTC-PERPETUAL Deribit) serve il MAINNET_TOKEN.
# Il TESTNET_TOKEN punta agli endpoint testnet degli exchange — utile solo per smoke test.
CERBERO_TESTNET_TOKEN=
CERBERO_MAINNET_TOKEN=
CERBERO_BOT_TAG=swarm-poc-phase1
# LLM provider (single endpoint via OpenRouter — supports anthropic/openai/qwen/llama models)
OPENROUTER_API_KEY=
OPENROUTER_BASE_URL=https://openrouter.ai/api/v1
# Models per tier (override Phase 1 defaults if needed)
LLM_MODEL_TIER_S=google/gemini-3-flash-preview
LLM_MODEL_TIER_A=deepseek/deepseek-v4-flash
LLM_MODEL_TIER_B=deepseek/deepseek-v4-flash
LLM_MODEL_TIER_C=qwen/qwen3-235b-a22b-2507
LLM_MODEL_TIER_D=openai/gpt-oss-20b
# Run config
RUN_NAME=phase1-spike-001
DATA_DIR=./data
SERIES_DIR=./series
DB_PATH=./runs.db