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This is what AI collaboration should have been from day one. A comprehensive cognitive layer that solves the fundamental problems of context loss, information silos, and coordination chaos. ## Core Components **Intent Graph** - Tracks WHY things happen - Every goal, task, and decision has a rationale - Relationships between objectives are explicit - Context is never lost **Semantic File System** - Files that know what they ARE - Auto-classification based on content and purpose - Semantic search (find by meaning, not just name) - Auto-organization (no more downloads folder chaos) - Files suggest where they belong **Living Documents** - Self-updating documentation - Code-aware: understands what code it documents - Detects when code changes and docs are stale - Can auto-generate from code - Always in sync **Context Engine** - Right information at the right time - Provides relevant context based on current task - Integrates intent, code, docs, and decisions - Proactive intelligence (suggests next actions) - Answers: "Why does this exist?" "What's related?" **Agent Coordination Protocol** - Multi-agent collaboration that works - Shared context via cognitive layer - Clear task ownership and handoffs - No duplicate work - Conflict resolution - Progress tracking **Smart Documents** - OCR, templates, auto-formatting - Extract text from PDFs and images - Identify document types automatically - ATS-friendly resume formatting - Business plan templates - Auto-filing based on content - Template matching and application ## What This Solves Traditional problems: ❌ Files in arbitrary folders ❌ Context lives in people's heads ❌ Docs get out of sync ❌ Multi-agent chaos ❌ Downloads folder anarchy ❌ Lost decisions and rationale Cognitive OS solutions: ✅ Files organize by meaning and purpose ✅ Context is captured and connected ✅ Docs update themselves ✅ Agents coordinate cleanly ✅ Everything auto-organizes ✅ Every decision is recorded with WHY ## Architecture cognitive/ ├── __init__.py # Main CognitiveOS integration ├── intent_graph.py # Goals, tasks, decisions, relationships ├── semantic_fs.py # Content-aware file organization ├── living_docs.py # Self-updating documentation ├── context_engine.py # Intelligent context retrieval ├── agent_coordination.py # Multi-agent collaboration ├── smart_documents.py # OCR, templates, auto-format ├── README.md # Vision and philosophy ├── USAGE.md # Complete usage guide ├── quickstart.py # Interactive demo └── requirements.txt # Optional dependencies ## Quick Start ```python from cognitive import CognitiveOS # Initialize cog = CognitiveOS() # Create a goal with rationale goal = cog.create_goal( "Build user authentication", rationale="Users need secure access" ) # Process a document (auto-classify, auto-organize) cog.process_new_file("~/Downloads/resume.pdf") # Get context for what you're working on context = cog.get_context(task_id="current-task") ``` ## Philosophy This is how AI and data should have been handled from the start: - **Semantic over Hierarchical**: Organize by meaning, not folders - **Intent-Preserving**: Capture WHY, not just WHAT - **Auto-Linking**: Related things connect automatically - **Context-Aware**: System knows what you're trying to do - **Agent-First**: Designed for AI-human collaboration Combines the best of Notion + Asana + actual code awareness + auto-organization + OCR + business planning + ATS-friendly formatting. No more hoping the world doesn't catch on fire. No more downloads folder chaos. No more lost context. This is the cognitive layer every OS should have had.
254 lines
7.9 KiB
Python
254 lines
7.9 KiB
Python
"""
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Cognitive Layer for BlackRoad OS
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The missing layer that should have existed from day one.
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This module integrates:
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- Intent Graph: WHY things happen
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- Semantic FS: WHAT files are and WHERE they belong
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- Living Docs: Documentation that updates itself
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- Context Engine: RIGHT information at the RIGHT time
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- Agent Coordination: Multi-agent collaboration that works
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- Smart Documents: OCR, ATS-friendly, auto-organizing documents
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"""
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from .intent_graph import IntentGraph, IntentNode, IntentType, IntentStatus
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from .semantic_fs import SemanticFileSystem, DocumentType, DocumentPurpose
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from .living_docs import DocManager, LivingDocument, DocType
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from .context_engine import ContextEngine, ContextBundle, ContextItem
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from .agent_coordination import AgentCoordinator, AgentInfo, AgentRole, Handoff
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from .smart_documents import DocumentProcessor, SmartDocument, DocumentTemplate
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__version__ = "0.1.0"
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__all__ = [
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# Intent Graph
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'IntentGraph',
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'IntentNode',
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'IntentType',
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'IntentStatus',
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# Semantic FS
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'SemanticFileSystem',
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'DocumentType',
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'DocumentPurpose',
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# Living Docs
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'DocManager',
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'LivingDocument',
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'DocType',
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# Context Engine
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'ContextEngine',
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'ContextBundle',
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'ContextItem',
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# Agent Coordination
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'AgentCoordinator',
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'AgentInfo',
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'AgentRole',
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'Handoff',
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# Smart Documents
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'DocumentProcessor',
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'SmartDocument',
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'DocumentTemplate',
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# Main integration
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'CognitiveOS',
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]
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class CognitiveOS:
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"""
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The Cognitive Operating System - integrates all cognitive components.
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This is the main entry point for using the cognitive layer.
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"""
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def __init__(self, workspace_path: str = "."):
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"""
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Initialize the Cognitive OS.
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Args:
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workspace_path: Root path for the workspace
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"""
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# Initialize all systems
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self.intent_graph = IntentGraph()
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self.semantic_fs = SemanticFileSystem(f"{workspace_path}/.semantic_fs_index.json")
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self.doc_manager = DocManager(f"{workspace_path}/.living_docs_index.json")
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self.context_engine = ContextEngine(
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intent_graph=self.intent_graph,
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semantic_fs=self.semantic_fs,
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doc_manager=self.doc_manager
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)
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self.agent_coordinator = AgentCoordinator(
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intent_graph=self.intent_graph,
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context_engine=self.context_engine
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)
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self.doc_processor = DocumentProcessor(
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semantic_fs=self.semantic_fs,
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doc_manager=self.doc_manager,
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intent_graph=self.intent_graph
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)
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self.workspace_path = workspace_path
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def process_new_file(self, file_path: str) -> None:
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"""
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Process a new file through the cognitive layer.
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This is the magic - a file gets:
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- Analyzed and classified (Semantic FS)
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- Auto-organized (suggested location)
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- Linked to intent (why does it exist?)
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- OCR'd if needed (Smart Docs)
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- Template-matched (Smart Docs)
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"""
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# 1. Index in semantic FS
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metadata = self.semantic_fs.index_file(file_path)
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print(f"✓ Indexed: {metadata.document_type.value}")
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# 2. Suggest where it should go
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suggested_path = self.semantic_fs.suggest_location(file_path)
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print(f"✓ Suggested location: {suggested_path}")
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# 3. Process with smart docs if it's a document
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if metadata.document_type in [DocumentType.RESUME, DocumentType.BUSINESS_PLAN,
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DocumentType.MEETING_NOTES]:
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doc = self.doc_processor.process_document(file_path, auto_organize=False)
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print(f"✓ Processed with template: {doc.suggested_template.value if doc.suggested_template else 'none'}")
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print()
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def create_goal(self, title: str, description: str = "", rationale: str = "") -> IntentNode:
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"""Create a new goal with full cognitive integration"""
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goal = self.intent_graph.create_goal(title, description, rationale)
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print(f"✓ Created goal: {title}")
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if rationale:
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print(f" Why: {rationale}")
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return goal
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def create_task(self, title: str, goal_id: str = None, rationale: str = "") -> IntentNode:
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"""Create a task linked to a goal"""
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task = self.intent_graph.create_task(title, parent_id=goal_id, rationale=rationale)
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print(f"✓ Created task: {title}")
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return task
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def get_context(self, query: str = None, task_id: str = None, file_path: str = None):
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"""
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Get relevant context based on what you're asking about.
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This is the intelligence - provide the right info at the right time.
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"""
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if query:
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return self.context_engine.get_context_for_query(query)
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elif task_id:
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return self.context_engine.get_context_for_task(task_id)
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elif file_path:
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return self.context_engine.get_context_for_file(file_path)
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else:
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return self.context_engine.get_current_context()
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def show_current_state(self) -> None:
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"""Show the current state of the cognitive OS"""
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print("\n" + "=" * 60)
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print("COGNITIVE OS STATE")
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print("=" * 60)
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# Intent graph summary
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print("\n" + self.intent_graph.get_summary())
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# Active context
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print("\nCURRENT CONTEXT")
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print("-" * 60)
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current = self.context_engine.get_current_context()
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for item in current.get_top_items(5):
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print(f" [{item.type}] {item.title} (relevance: {item.relevance_score:.2f})")
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# File system stats
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print("\nSEMANTIC FILE SYSTEM")
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print("-" * 60)
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print(f" Indexed files: {len(self.semantic_fs.files)}")
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# Document stats
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print("\nLIVING DOCUMENTS")
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print("-" * 60)
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print(f" Tracked documents: {len(self.doc_manager.documents)}")
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out_of_sync = self.doc_manager.check_all_docs()
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if out_of_sync:
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print(f" ⚠ Out of sync: {len(out_of_sync)}")
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# Agent stats
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print("\nAGENT COORDINATION")
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print("-" * 60)
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print(f" Registered agents: {len(self.agent_coordinator.agents)}")
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print(f" Active sessions: {len(self.agent_coordinator.sessions)}")
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print("\n" + "=" * 60 + "\n")
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def export_all(self, export_dir: str = ".cognitive_export") -> None:
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"""Export all cognitive data"""
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from pathlib import Path
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Path(export_dir).mkdir(exist_ok=True)
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# Export intent graph
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self.intent_graph.export_json(f"{export_dir}/intent_graph.json")
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# Export semantic FS
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self.semantic_fs.save_index()
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# Export living docs
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self.doc_manager.export_index()
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# Export agent coordination
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self.agent_coordinator.export_coordination_state(f"{export_dir}/agent_coordination.json")
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print(f"✓ Exported all cognitive data to {export_dir}/")
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# Quick start example
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def demo():
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"""Demonstration of the Cognitive OS"""
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print("\n" + "=" * 60)
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print("COGNITIVE OS - DEMONSTRATION")
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print("=" * 60 + "\n")
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# Initialize
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cog = CognitiveOS()
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# Create a goal
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goal = cog.create_goal(
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title="Build a smart document management system",
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rationale="Current file management is chaos. Need semantic organization."
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)
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# Create tasks
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task1 = cog.create_task(
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"Implement OCR for document scanning",
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goal_id=goal.id,
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rationale="Extract structured data from PDFs"
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)
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task2 = cog.create_task(
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"Build auto-filing system",
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goal_id=goal.id,
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rationale="Documents should organize themselves"
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)
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# Show state
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cog.show_current_state()
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# Get context for the first task
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print("\nCONTEXT FOR: Implement OCR")
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print("-" * 60)
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context = cog.get_context(task_id=task1.id)
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for item in context.get_top_items(3):
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print(f" [{item.type}] {item.title}")
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print("\n✓ Cognitive OS is ready!\n")
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if __name__ == "__main__":
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demo()
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