feat: initial FastAPI boilerplate setup
Set up Webber - multi-agent AI development system with: - Domain-based project structure (src/domains/, src/shared/) - BaseController pattern with lazy router instantiation - Pydantic Settings configuration with env file support - Logger decorator with temporal benchmarking and trace IDs - UserProvider singleton for request-scoped context - Custom exception hierarchy - Health endpoints (/, /health) Dependencies (CVE checked 2026-01-09): - FastAPI 0.128.0, Starlette 0.50.0, Uvicorn 0.40.0 - Pydantic 2.12.4, PydanticAI 1.40.0 - All packages at latest safe versions Placeholder domains for future implementation: - agents/ (explore, plan, task) - tools/ (file, shell, search) - auth/ (tatlock integration) Port: 8086 (per CONTAINERS.md allocation) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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# Webber Configuration
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# Copy to .env and customize
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# Application
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DEBUG=true
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LOG_LEVEL=DEBUG
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# Server
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HOST=0.0.0.0
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PORT=8086
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# CORS (comma-separated)
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CORS_ORIGINS=["http://localhost:3000","http://localhost:8080"]
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# LLM - Ollama (tower-of-joy)
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OLLAMA_URL=http://192.168.86.149:11434
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OLLAMA_AGENT_MODEL=mistral-nemo-large:latest
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OLLAMA_EMBED_MODEL=nomic-embed-text:latest
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# Auth - Tatlock integration (optional)
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# TATLOCK_API_URL=http://192.168.86.149:8000
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# INTERNAL_API_KEY=your-internal-key
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# Tool execution
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TOOL_TIMEOUT_SECONDS=120
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SANDBOX_ENABLED=true
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# ALLOWED_PATHS=["/home/user/projects","/tmp/webber"]
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# Sessions
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SESSION_TTL_HOURS=24
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MAX_CONTEXT_TOKENS=128000
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