Community Knowledge Sharing

AI-powered knowledge sharing for communities with graph visualization, conversational chat, and intelligent document analysis.

Overview

This system helps organizations avoid overlapping investments by making visible:

Ongoing initiatives and projects
Resources and capabilities
Connections between actors, legislation, and themes

Key Features:

Graph & visualization

Interactive canvas: React Flow graph with drag-and-drop, zoom, pan, and node groups
Schema-driven node types: Node types, colours, icons, and fields are all profile-configurable — no code changes needed
Subtypes: Optional sub-classification tags on any node type, with autocomplete from existing values
Save views: Snapshot and restore named canvas views, stored as nodes in the graph
Schema-driven context menu: Add custom right-click actions per node type via schema_config.json — open URLs with node field substitution or fire named callbacks
Interactive guides: Step-by-step onboarding tours triggered via URL parameter or AI assistant

AI chat & intelligence

AI-powered chat: Natural language interface (Claude or OpenAI) for exploring and managing the graph
Configurable model profiles: Define named chat/agent model profiles in schema_config.json; users can select enabled profiles while agents can bind to a profile by id
Multi-provider support: Switch between Claude (Anthropic), OpenAI, and any OpenAI-compatible endpoint (Ollama, Groq, Azure, etc.)
Document upload: Upload PDF, Word, or text documents for automatic entity extraction
Node proposals: LLM suggests entities with duplicate detection; user confirms before any node is added
Node marking: AI assistant can annotate nodes with colours and labels (session-only, never persisted)
Markdown rendering: Chat responses render Markdown (bold, lists, tables, code blocks)
AI Skills: Profile-configurable SKILL.md instructions injected into the agent system prompt; ships with generic impact analysis; ESS profile adds GSIM lineage and change-impact skills
Skill node type: Create and manage SKILL.md-compatible skill definitions directly in the graph

Integration & extensibility

MCP server: Full Model Context Protocol support — connect Claude, ChatGPT, or any MCP-compatible AI client directly to the graph
ChatGPT widget: Embeddable widget for use in ChatGPT or other interfaces
Event subscriptions & webhooks: Receive HTTP POST notifications when nodes are created, updated, or deleted
AI agent system: Event-triggered and schedule-triggered agents that act on graph mutations or run on a cron schedule
Federation: Connect to multiple remote graph instances with configurable depth, provenance labels, and node adoption

Operations & deployment

Runs without LLM keys: Graph API and MCP server work without any API key; AI chat is simply hidden
Multi-language: English and Swedish UI, selectable via URL, startup flag, or schema config
Authentication: Basic Auth for all endpoints or MCP-only (for Cloud Run + IAP setups)
Profile system: Run with different metadata models, AI prompts, and seed data per deployment profile
Data management: Example datasets with easy loading from local files or URLs

See docs/USER_GUIDE.md for a full user-facing walkthrough.

Tech Stack:

Frontend: React + React Flow + Zustand (monorepo with npm workspaces)
Backend: FastAPI + FastMCP (Python) with NetworkX + JSON
AI: Claude or OpenAI for natural language understanding and entity extraction
Graph storage: NetworkX in-memory + JSON persistence
Similarity search: sentence-transformers + RapidFuzz

Project Structure

/backend                          # Python backend directory
  /api_host                       # FastAPI server host
    server.py                     # Main server with REST, MCP, and static files
    config.py                     # Server configuration
  /core                           # Core graph data structures
    storage.py                    # NetworkX graph operations
    storage_backends.py           # Persistence backend abstraction
    models.py                     # Node/Edge data models
    vector_store.py               # Similarity search
    /events                       # Graph mutation event / webhook system
  /service                        # Graph service layer
    service.py                    # High-level graph operations
    rest_api.py                   # REST API router
    mcp_tools.py                  # MCP tool definitions
  /ui                             # Chat and document handling
    chat_service.py               # LLM chat with tool execution
    chat_logic.py                 # Chat processing logic
    document_service.py           # Document parsing
    document_processor.py         # Document text extraction (PDF/Word/text)
    rest_api.py                   # Chat REST endpoints
  /llm                            # LLM provider abstraction
    llm_providers.py              # LLM provider abstraction
    language_policy.py            # Language-policy prompt helpers
  /runtime                        # Request/authorization/config runtime context
    authorization.py              # Graph authorization context
    request_context.py            # Actor/scope request context
    config_context.py             # Config path resolution context
  /skills                         # Skills loader system
    loader.py                     # SkillsLoader — fetches/parses SKILL.md files
  /config                         # Schema/config loading
    config_loader.py              # Schema and config loading
  /agents                         # Agent execution (event- and schedule-triggered)
  /federation                     # Federated graph cache and search
  /tests                          # Cross-cutting backend tests
/config                           # Configuration profiles
  /default                        # Default profile (base, always required)
    schema_config.json            # Node types, relationships, presentation
    federation_config.json        # Federation graph connections
    .env.example                  # Environment variable template
    /skills                       # Skills loaded for all profiles (fallback)
      /impact-analysis            # Generic graph dependency impact analysis
  /stat-metadata                  # European Statistical System metadata profile
    schema_config.json            # ESS node types (NSIs, programmes, variables…)
    graph.json                    # ESS seed data
    /skills                       # ESS-specific skills (loaded in addition to default)
      /graph-analysis             # Generic graph pattern analysis
      /gsim-lineage-impact        # GSIM lineage tracing and change impact assessment
  /scb                            # SCB (Statistics Sweden) demo profile
    schema_config.json            # Statistical metadata model
  /test                           # Test profile
    schema_config.json            # Minimal config for testing
  profile-utils.sh                # Shared profile resolution utilities
/data                             # Graph data
  /examples                       # Example datasets (tracked in git)
    default.json                  # Default example dataset
  /active                         # Active data used at runtime (git-ignored)
    graph.json                    # Currently active graph file
/frontend                         # Frontend applications
  /web                            # React web application
    /src/components               # UI components (ChatPanel, etc.)
    /src/i18n                     # Internationalization (en, sv)
    /src/services                 # API client
    /src/store                    # Zustand state
    /tests                        # Unit and e2e tests
  /widget                         # ChatGPT embeddable widget
  /xr                             # WebXR immersive client for Quest (spike)
/packages                         # Shared packages
  /ui-graph-canvas                # Shared React Flow component
/services                         # Standalone auxiliary services
  /mcp_oauth_gateway              # OAuth 2.1 gateway wrapping the MCP endpoint
/scripts                          # Utility scripts
/docs                             # Documentation (see docs/README.md for a status-tagged index)
  README.md                       # Documentation index: current / design / historical
  DATA_MANAGEMENT.md              # Graph data management guide
  EVENT_SUBSCRIPTIONS.md          # Webhook/event system docs
  PROFILES.md                     # Configuration profiles guide
  DEPLOYMENT_GUIDE.md             # Deployment documentation
  FEDERATED_GRAPH_DESIGN.md       # Federated multi-graph architecture
  CORE_RUNTIME_AND_EXTENSION_ENABLEMENT.md  # Public core plan for runtime modes and extension seams
  CORE_ENABLEMENT_IMPLEMENTATION_PLAN.md # Concrete public implementation slices for runtime and extension readiness
start-dev.sh                      # Development startup script
LLM_PROVIDERS.md                  # LLM configuration guide

Metamodel

The metamodel defines two categories of node types. Node types, relationships, colors, icons, and AI prompts are all configurable per profile via schema_config.json. See docs/PROFILES.md for the full guide.

Domain Node Types (configurable via profile)

The default profile includes these domain types:

Actor (blue) - Organizations, agencies, individuals
Initiative (green) - Projects, programs, collaborative activities
Capability (orange) - Capabilities, competencies, skills
Resource (yellow) - Reports, software, tools, datasets
Legislation (red) - Laws, directives (NIS2, GDPR, etc.)
Theme (teal) - AI strategies, data strategies, themes
Goal (indigo) - Strategic objectives and targets
Event (fuchsia) - Conferences, workshops, milestones
Data (cyan) - Datasets, registers, APIs, data sources
Risk (red) - Identified risks, threats, or vulnerabilities

Other profiles can add domain-specific types. For example, the stat-metadata profile adds: StatisticalProgramme, DataSet, DataStructure, InstanceVariable, Concept, UnitType, CodeList, Questionnaire, ProductionSolution, SubjectField. The scb profile adds: Dataset, Hållpunkt, Undersökning, Variabel, Värdemängd, Population, Klassifikation.

All domain nodes support subtypes for finer sub-classification within each node type (e.g., an Actor can be tagged as "Government agency", "Municipality", "Steering group"). Subtypes are optional, stored as a list, and the UI provides autocomplete with case normalization based on existing subtypes in the graph.

System Node Types (foundational to the application)

These are integral to core application functionality:

SavedView / VisualizationView (gray) - Saved graph view snapshots
EventSubscription (violet) - Webhook subscriptions for graph mutation events
Agent (pink) - AI agent configurations (runtime not implemented)
Skill (violet) - SKILL.md-compatible agent skill definitions stored in the graph; uses a specialized creation form
Groups - Visual grouping of nodes in the canvas

Relationships

Default: BELONGS_TO, IMPLEMENTS, PRODUCES, GOVERNED_BY, RELATES_TO, PART_OF, AIMS_FOR
Profiles can define additional relationship types (e.g., MEASURES, DESCRIBES, USES, DERIVED_FROM)

Quick Start

Running behind a reverse proxy

The app works out of the box behind any path-stripping reverse proxy. The frontend automatically detects the proxy path prefix from the browser URL — no extra configuration is needed.

If Node.js is not pre-installed (managed cloud environments, sandboxes)

Install Node.js via nvm — no root access required:

curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash
source ~/.bashrc
nvm install 20

Then start the app normally:

export ANTHROPIC_API_KEY=sk-ant-xxxxx  # or OPENAI_API_KEY
./start-dev.sh

The app will be reachable at whatever URL your environment exposes for port 8000, e.g.: https://<your-host>/proxy/8000/web/

Note: Make sure port 8000 is publicly accessible in your environment's network or port settings.

Development Mode (Recommended)

Start all services with a single command:

# Set your API key (pick one)
export OPENAI_API_KEY=sk-xxxxx        # For OpenAI
export ANTHROPIC_API_KEY=sk-ant-xxxxx # For Claude

# Start everything (default profile, English)
./start-dev.sh

# Start with a specific profile
./start-dev.sh --profile stat-metadata   # European Statistical System
./start-dev.sh --profile scb             # Statistics Sweden

# Start with Swedish UI
./start-dev.sh --lang sv

# Combine profile, language, and data
./start-dev.sh --profile stat-metadata --lang en

# Start with data from a URL
./start-dev.sh --data https://example.github.io/data/graph.json

The script will:

Check for and set up active graph data (copies example data on first run)
Set up Python virtual environment and install dependencies
Install npm dependencies (workspaces)
Build web app and widget
Start FastAPI server on http://localhost:8000

Available endpoints after startup:

Endpoint	Description
http://localhost:8000/web/	Web application
http://localhost:8000/widget/	ChatGPT widget
http://localhost:8000/api/	REST API
http://localhost:8000/ui/	Chat API
http://localhost:8000/mcp	MCP endpoint
http://localhost:8000/health	Health check
http://localhost:8000/federation/status	Federation cache/status
http://localhost:8000/federation/sync	Trigger federation sync (POST)

Manual Start

If you prefer to start services separately:

Backend:

python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r backend/requirements.txt
uvicorn backend.api_host.server:get_app --factory --reload --port 8000

Frontend (development with hot reload):

npm install
npm run dev  # Starts Vite dev server on http://localhost:5173

Note: In development mode, the frontend runs on port 5173 with hot reload. For production, run npm run build and access via /web/ on the backend server.

Language Configuration

The application supports English and Swedish. Language can be set in three ways:

URL parameter (highest priority): http://localhost:8000/web/?lang=sv
Startup flag: ./start-dev.sh --lang sv
Schema config (config/default/schema_config.json): "default_language": "en"

The language setting affects the UI labels, chat placeholders, notifications, and welcome message. The AI chat assistant responds in whatever language the user writes in.

Configuration Profiles

Profiles allow you to run the application with different metadata models, node types, and AI prompts. Each profile is a directory under config/ that can override the default configuration.

# Start with a specific profile
./start-dev.sh --profile stat-metadata   # ESS statistical metadata (recommended for ESS use)
./start-dev.sh --profile scb             # Statistics Sweden (Swedish language)

# Profiles available out of the box:
#   default        - General community knowledge graph
#   stat-metadata  - European Statistical System metadata (NSIs, programmes, datasets, variables)
#   scb            - Statistics Sweden (Dataset, Undersökning, Variabel, etc.)
#   test           - Minimal config for testing

For cloud environments (SSPCloud), run ./scripts/start-sprint.sh — it auto-installs all dependencies and loads the stat-metadata profile. See docs/SSPCloud-setup.md.

Each profile can contain:

schema_config.json — Node types, relationships, colors, icons, and AI prompts
federation_config.json — Federation topology
.env — Secrets and environment overrides (git-ignored)
graph.json — Seed data for initial setup

Missing files fall back to config/default/. See docs/PROFILES.md for the complete guide on creating custom profiles.

Federation topology can be configured at startup with FEDERATION_FILE (default: config/default/federation_config.json). This is admin-only configuration and is not editable via GUI/chat tools.

Example federation depth setup (installation policy):

{
  "federation": {
    "enabled": true,
    "max_traversal_depth": 4,
    "depth_levels": [1, 2, 4],
    "graphs": [
      {
        "graph_id": "esam-main",
        "display_name": "eSam",
        "enabled": true,
        "max_depth_override": 2,
        "endpoints": { "graph_json_url": "https://example.org/graph.json" }
      }
    ]
  }
}

UI behavior:

Only configured selectable levels are shown (bounded by effective max depth).
If only one level is available, the depth selector is hidden.
Search labels show <GraphName>: <NodeName> only when multiple graphs are available.

You can also name the local graph in graph.json metadata:

{
  "metadata": {
    "graph_name": "My Local Collaboration Graph"
  }
}

Data Management

Graph data is stored separately from the codebase:

Example data lives in data/examples/ (tracked in git)
Active data lives in data/active/graph.json (git-ignored)

On first run, the default example data is automatically copied to the active location. Use --data to load different datasets. See docs/DATA_MANAGEMENT.md for details. For upcoming multi-instance capabilities, see docs/FEDERATED_GRAPH_DESIGN.md.

LLM Provider Configuration

The system automatically detects which provider to use based on available API keys:

# Just set your API key - provider is auto-detected
export OPENAI_API_KEY=sk-xxxxx           # Auto-selects OpenAI
# OR
export ANTHROPIC_API_KEY=sk-ant-xxxxx    # Auto-selects Claude

Manual selection:

export LLM_PROVIDER=claude   # Force Claude
export LLM_PROVIDER=openai   # Force OpenAI

See LLM_PROVIDERS.md for detailed configuration.

Running without LLM keys

The application starts and operates fully without any LLM API keys. When no key is configured the built-in AI chat assistant is hidden in the UI, and background agent workers remain inactive. The MCP server, graph API, and all read/write operations work normally. This allows teams to run the knowledge graph as a standalone data platform and add AI capabilities later by setting an API key and restarting.

Authentication

Full Basic Auth (all endpoints)

export AUTH_ENABLED=true
export AUTH_USERNAME=admin
export AUTH_PASSWORD=secret

MCP-only Basic Auth (for Google Cloud Run / IAP deployments)

When running behind Google Cloud Run with IAP, the web GUI and REST API are already protected by Google login. Use MCP_BASIC_AUTH to add Basic Auth only to MCP endpoints (/mcp/* and /execute_tool), which are called by external MCP clients that cannot use IAP:

export AUTH_ENABLED=false
export MCP_BASIC_AUTH=true
export AUTH_USERNAME=mcp-client
export AUTH_PASSWORD=secret

Variable	Default	Description
`AUTH_ENABLED`	`false`	Enable Basic Auth on all endpoints (except `/health`, `/info`)
`MCP_BASIC_AUTH`	`false`	Enable Basic Auth only on `/mcp/*` and `/execute_tool`
`AUTH_USERNAME`	`admin`	Username for Basic Auth
`AUTH_PASSWORD`	(none)	Password for Basic Auth (required for either mode to activate)

If both AUTH_ENABLED and MCP_BASIC_AUTH are true, AUTH_ENABLED takes precedence and all endpoints require auth.

Testing

# All Python tests
python -m pytest backend

# JavaScript tests
npm test

# E2E tests
npm run test:e2e

# All tests
npm run test:all

User Scenarios

Document Analysis

Upload a project description (PDF/Word)
Ask "which organizations are mentioned?"
AI extracts entities with duplicate detection
Review and approve suggested additions
New nodes appear in the graph

Finding Similar Projects

Upload your project proposal
Ask "are there similar projects?"
System shows matching projects with similarity scores
Decide to add your project or join existing initiative

Exploring the Graph

Use the chat panel to search: "search AI projects"
Graph displays matching nodes
Click nodes to see details and connections
Save custom views for later

ChatGPT Widget Integration

The widget can be embedded in ChatGPT or other platforms:

<script src="https://your-server/widget/widget.iife.js"></script>
<link rel="stylesheet" href="https://your-server/widget/style.css">
<community-graph-widget api-url="https://your-server"></community-graph-widget>

The widget provides:

Graph visualization
Chat interface
MCP tool execution

Event Subscriptions & Webhooks

The system supports webhook notifications for graph mutations:

EventSubscription nodes define webhook targets and filters
Events are generated when nodes are created, updated, or deleted
Loop prevention via event_origin and event_session_id tracking
Retry logic with exponential backoff for failed deliveries

Create subscriptions via the web UI (right-click on canvas) or API. See docs/EVENT_SUBSCRIPTIONS.md for detailed documentation.

Security

Max 10 nodes per delete operation
Confirmation required for deletions
Community-based isolation
No personal data handling

Development

See backend/DEVELOPMENT.md for detailed development guide including:

Architecture overview
Adding new MCP tools
Testing strategies
API documentation

License

MIT License - see LICENSE for details

Name		Name	Last commit message	Last commit date
.devcontainer		.devcontainer
.github		.github
.vscode		.vscode
backend		backend
config		config
data		data
docs		docs
frontend		frontend
packages/ui-graph-canvas		packages/ui-graph-canvas
scripts		scripts
services/mcp_oauth_gateway		services/mcp_oauth_gateway
.dockerignore		.dockerignore
.env.example		.env.example
.gitignore		.gitignore
.nvmrc		.nvmrc
.prettierignore		.prettierignore
.prettierrc.json		.prettierrc.json
CLAUDE.md		CLAUDE.md
Dockerfile		Dockerfile
LICENSE		LICENSE
LLM_PROVIDERS.md		LLM_PROVIDERS.md
README.md		README.md
SECURITY.md		SECURITY.md
SMALL_FIXES.md		SMALL_FIXES.md
STRUCTURE_REVIEW.md		STRUCTURE_REVIEW.md
docker-compose.prod.yml		docker-compose.prod.yml
docker-compose.yml		docker-compose.yml
eslint.config.mjs		eslint.config.mjs
package-lock.json		package-lock.json
package.json		package.json
pyproject.toml		pyproject.toml
start-dev.sh		start-dev.sh

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Community Knowledge Sharing

Overview

Project Structure

Metamodel

Domain Node Types (configurable via profile)

System Node Types (foundational to the application)

Relationships

Quick Start

Running behind a reverse proxy

Development Mode (Recommended)

Manual Start

Language Configuration

Configuration Profiles

Data Management

LLM Provider Configuration

Running without LLM keys

Authentication

Full Basic Auth (all endpoints)

MCP-only Basic Auth (for Google Cloud Run / IAP deployments)

Testing

User Scenarios

Document Analysis

Finding Similar Projects

Exploring the Graph

ChatGPT Widget Integration

Event Subscriptions & Webhooks

Security

Development

License

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Community Knowledge Sharing

Overview

Project Structure

Metamodel

Domain Node Types (configurable via profile)

System Node Types (foundational to the application)

Relationships

Quick Start

Running behind a reverse proxy

Development Mode (Recommended)

Manual Start

Language Configuration

Configuration Profiles

Data Management

LLM Provider Configuration

Running without LLM keys

Authentication

Full Basic Auth (all endpoints)

MCP-only Basic Auth (for Google Cloud Run / IAP deployments)

Testing

User Scenarios

Document Analysis

Finding Similar Projects

Exploring the Graph

ChatGPT Widget Integration

Event Subscriptions & Webhooks

Security

Development

License

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