a2bc6347fc
Architecture: - Graph engine (engine.py) loads graph definitions, instantiates nodes - Versioned nodes: input_v1, thinker_v1, output_v1, memorizer_v1, director_v1 - NODE_REGISTRY for dynamic node lookup by name - Graph API: /api/graph/active, /api/graph/list, /api/graph/switch - Graph definition: graphs/v1_current.py (7 nodes, 13 edges, 3 edge types) S3* Audit system: - Workspace mismatch detection (server vs browser controls) - Code-without-tools retry (Thinker wrote code but no tool calls) - Intent-without-action retry (request intent but Thinker only produced text) - Dashboard feedback: browser sends workspace state on every message - Sensor continuous comparison on 5s tick State machines: - create_machine / add_state / reset_machine / destroy_machine via function calling - Local transitions (go:) resolve without LLM round-trip - Button persistence across turns Database tools: - query_db tool via pymysql to MariaDB K3s pod (eras2_production) - Table rendering in workspace (tab-separated parsing) - Director pre-planning with Opus for complex data requests - Error retry with corrected SQL Frontend: - Cytoscape.js pipeline graph with real-time node animations - Overlay scrollbars (CSS-only, no reflow) - Tool call/result trace events - S3* audit events in trace Testing: - 167 integration tests (11 test suites) - 22 node-level unit tests (test_nodes/) - Three test levels: node unit, graph integration, scenario Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
51 lines
1.5 KiB
Python
51 lines
1.5 KiB
Python
"""Message types flowing between nodes."""
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from dataclasses import dataclass, field, asdict
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@dataclass
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class Envelope:
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"""What flows between nodes."""
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text: str
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user_id: str = "anon"
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session_id: str = ""
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timestamp: str = ""
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@dataclass
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class InputAnalysis:
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"""Structured classification from Input node."""
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who: str = "unknown"
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language: str = "en"
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intent: str = "request" # question | request | social | action | feedback
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topic: str = ""
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tone: str = "casual" # casual | frustrated | playful | urgent
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complexity: str = "simple" # trivial | simple | complex
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context: str = ""
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@dataclass
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class Command:
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"""Input node's structured perception of what was heard."""
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analysis: InputAnalysis
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source_text: str
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metadata: dict = field(default_factory=dict)
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@property
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def instruction(self) -> str:
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"""Backward-compatible summary string for logging/thinker."""
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a = self.analysis
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return f"{a.who} ({a.intent}, {a.tone}): {a.topic}"
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@dataclass
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class ThoughtResult:
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"""Thinker node's output — either a direct answer or tool results."""
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response: str
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tool_used: str = ""
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tool_output: str = ""
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actions: list = field(default_factory=list) # [{label, action, payload?}]
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state_updates: dict = field(default_factory=dict) # {key: value} from set_state
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display_items: list = field(default_factory=list) # [{type, label, value?, style?}] from emit_display
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machine_ops: list = field(default_factory=list) # [{op, id, ...}] from machine tools
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