cillin
16b54d5ccc
Migrate all agent roles from Legacy to EvoAgent architecture: - fundamentals_analyst, technical_analyst, sentiment_analyst, valuation_analyst - risk_manager, portfolio_manager Key changes: - EvoAgent now supports Portfolio Manager compatibility methods (_make_decision, get_decisions, get_portfolio_state, load_portfolio_state, update_portfolio) - Add UnifiedAgentFactory for centralized agent creation - ToolGuard with batch approval API and WebSocket broadcast - Legacy agents marked deprecated (AnalystAgent, RiskAgent, PMAgent) - Remove backend/agents/compat.py migration shim - Add run_id alongside workspace_id for semantic clarity - Complete integration test coverage (13 tests) - All smoke tests passing for 6 agent roles Constraint: Must maintain backward compatibility with existing run configs Constraint: Memory support must work with EvoAgent (no fallback to Legacy) Rejected: Separate PM implementation for EvoAgent | unified approach cleaner Confidence: high Scope-risk: broad Directive: EVO_AGENT_IDS env var still respected but defaults to all roles Not-tested: Kubernetes sandbox mode for skill execution
35 lines
1.3 KiB
Bash
Executable File
35 lines
1.3 KiB
Bash
Executable File
#!/usr/bin/env bash
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# COMPATIBILITY_SURFACE: stable
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# OWNER: ops-team
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# SEE: docs/legacy-inventory.md#gateway-first-production-example
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#
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# Gateway-first production launch script.
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# This is the current checked-in production example, running the gateway
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# directly and proxying /ws instead of exposing every split FastAPI service.
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# For split-service topology, see start-dev.sh and docs/current-architecture.md
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set -euo pipefail
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cd /root/code/evotraders
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export PYTHONPATH=/root/code/evotraders/.pydeps:.
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export TICKERS="${TICKERS:-AAPL,MSFT,GOOGL,AMZN,NVDA,META,TSLA,AMD,NFLX,AVGO,PLTR,COIN}"
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# 技能沙盒配置（生产环境建议使用 docker）
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export SKILL_SANDBOX_MODE="${SKILL_SANDBOX_MODE:-docker}"
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export SKILL_SANDBOX_IMAGE="${SKILL_SANDBOX_IMAGE:-python:3.11-slim}"
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export SKILL_SANDBOX_MEMORY_LIMIT="${SKILL_SANDBOX_MEMORY_LIMIT:-512m}"
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export SKILL_SANDBOX_CPU_LIMIT="${SKILL_SANDBOX_CPU_LIMIT:-1.0}"
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export SKILL_SANDBOX_NETWORK="${SKILL_SANDBOX_NETWORK:-none}"
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export SKILL_SANDBOX_TIMEOUT="${SKILL_SANDBOX_TIMEOUT:-60}"
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# "production" here is an explicit deployment run label, not a required
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# root-level runtime directory name.
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exec python3 -m backend.main \
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--mode live \
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--config-name production \
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--host 127.0.0.1 \
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--port 8765 \
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--trigger-time now \
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--poll-interval 15
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