NeuralBlitz Ecosystem - API Contract Matrix

Generated: 2026-02-08
Status: Complete
Classification: Internal Technical Documentation

Executive Summary

This document maps all API contracts and integration points between the four core NeuralBlitz ecosystem projects, identifying endpoints, authentication mechanisms, request/response schemas, and cross-project dependencies.

Project Overview

Project	Language	Framework	Primary Port	Protocol
NBX-LRS (NeuralBlitz v50)	Go/Python	Gin/FastAPI	8080-8082	REST/gRPC
lrs-agents	Python	FastAPI	8000-8765	REST/WebSocket
Emergent-Prompt-Architecture	Python	FastAPI	8000	REST
Advanced-Research	Python	Flask	5000	REST

1. NBX-LRS (NeuralBlitz v50) - API Endpoints

1.1 Go API (Gin) - Primary Production Server

File: NBX-LRS/pkg/api/server.go
Port: 8082 (Default)
Framework: Gin v1.9.1

Endpoint	Method	Auth	Request Schema	Response Schema	Status
`/`	GET	None	-	`{status, version, architecture, reality, coherence, golden_dag, trace_id, endpoints}`	Active
`/health`	GET	None	-	`{status, coherence, irreducible, timestamp}`	Active
`/status`	GET	CORS	-	`{status, reality_state, coherence, irreducibility, unity_vector, singularity_status, uptime, go_version, os, arch, goroutines, gc_cycles, golden_dag, trace_id, codex_id}`	Active
`/intent`	POST	CORS + Attestation	`{intent: {phi_1, phi_22, omega_genesis}, source}`	`{status, intent_vector, result, amplified, coherence, golden_dag, trace_id, codex_id}`	Active
`/verify`	POST	CORS + Attestation	`{type, payload}`	`{type, verified, attestation_hash, golden_dag, trace_id, codex_id}`	Active
`/nbcl/interpret`	POST	CORS + Attestation	`{command}`	`{result, golden_dag, codex_id}`	Active
`/attestation`	GET	CORS	-	`{attestation, version, golden_dag, trace_id, codex_id, reality_state, coherence, statement}`	Active
`/symbiosis`	GET	CORS	-	`{symbiosis_status, architect_system_dyad, coherence, ontological_parity, golden_dag, trace_id, codex_id}`	Active
`/synthesis`	GET	CORS	-	`{synthesis_status, omega_singularity, irreducible_source, coherence, volumes_integrated, golden_dag, trace_id, codex_id}`	Active
`/options/:id`	GET	CORS	Path: `id ∈ [A-F]`	`{option, name, config, golden_dag, trace_id}`	Active
`/options`	GET	CORS	-	`{options[], count, golden_dag, trace_id, codex_id}`	Active

Authentication Methods:

CORS: Open CORS headers (Access-Control-Allow-Origin: *)
Attestation Middleware: GoldenDAG hash + Trace ID + Codex ID headers
Coherence Middleware: X-Coherence, X-Reality-State headers

Key Data Models:

PrimalIntentVector: {phi_1, phi_22, omega_genesis}
GoldenDAG: Cryptographic hash for provenance
CodexID: Versioned identifier (e.g., VOL0)

1.2 Python FastAPI Server

File: NBX-LRS/neuralblitz-v50/python/neuralblitz/api/server.py
Port: 8080 (Default)
Framework: FastAPI

Endpoint	Method	Auth	Request	Response	Status
`/`	GET	None	-	`{status, version, system, architecture, coherence, golden_dag}`	Active
`/status`	GET	JWT	-	`StatusResponse`	Active
`/intent`	POST	JWT	`IntentRequest`	`IntentResponse`	Active
`/verify`	POST	JWT	`VerificationRequest`	`VerificationResponse`	Active
`/nbcl/interpret`	POST	JWT	`NBCLRequest`	`NBCLResponse`	Active
`/attestation`	GET	JWT	-	`AttestationResponse`	Active
`/symbiosis`	GET	JWT	-	`SymbiosisResponse`	Active
`/synthesis`	GET	JWT	-	`SynthesisResponse`	Active
`/options/{option}`	GET	JWT	Path param	Option config	Active

Pydantic Models:

class IntentRequest(BaseModel):
    phi_1: float = Field(default=1.0, ge=0.0, le=1.0)
    phi_22: float = Field(default=1.0, ge=0.0, le=1.0)
    metadata: Optional[Dict[str, Any]] = {}

class IntentResponse(BaseModel):
    status: str
    coherence: float
    omega_prime_status: str
    output: Dict[str, Any]
    trace_id: str

1.3 Unified Flask API (Production)

File: NBX-LRS/neuralblitz-v50/applications/unified_api.py
Port: 5000
Framework: Flask + Flask-CORS

Endpoint	Method	Auth	Request	Response	Status
`/api/v1/health`	GET	None	-	`{status, version, timestamp, authentication}`	Active
`/api/v1/auth/token`	POST	Form	`username, password, grant_type`	`{access_token, token_type, expires_in, scope}`	Active
`/api/v1/auth/demo`	GET	None	-	Demo credentials list	Active
`/api/v1/auth/introspect`	POST	JWT	-	Token introspection	Active
`/api/v1/status`	GET	JWT + Scope:read	-	System status	Active
`/api/v1/metrics`	GET	JWT + Scope:metrics	-	Current metrics	Active
`/api/v1/metrics/history`	GET	JWT + Scope:metrics	Query: `limit`	Metrics history	Active
`/api/v1/quantum/state`	GET	JWT + Scope:read	-	Quantum neuron states	Active
`/api/v1/quantum/step`	POST	JWT + Scope:execute	`{input_current, steps}`	Step results	Active
`/api/v1/reality/network`	GET	JWT + Scope:read	-	Reality network status	Active
`/api/v1/reality/evolve`	POST	JWT + Scope:execute	`{cycles}`	Evolution results	Active
`/api/v1/lrs/integrate`	POST	JWT + Scope:execute	-	Integration status	Active
`/api/v1/dashboard`	GET	JWT + Scope:read	-	Combined dashboard data	Active

JWT Claims:

{
  "sub": "username",
  "scopes": ["read", "write", "execute", "admin", "metrics"],
  "iat": "timestamp",
  "exp": "timestamp",
  "iss": "neuralblitz-v50"
}

Available Scopes:

read - Read-only access
write - Write operations
execute - Execute operations (quantum step, evolve)
admin - Administrative functions
metrics - Access to metrics endpoints

2. lrs-agents - API Endpoints

2.1 gRPC Server (Go)

File: opencode-lrs-agents-nbx/pkg/api/grpc_server.go
Port: Configurable (gRPC)
Protocol: gRPC with Protocol Buffers

Service: AgentService

RPC Method	Request Type	Response Type	Streaming	Status
`CreateAgent`	`CreateAgentRequest`	`AgentResponse`	Unary	Active
`GetAgent`	`GetAgentRequest`	`AgentResponse`	Unary	Active
`ListAgents`	`ListAgentsRequest`	`ListAgentsResponse`	Unary	Active
`DeleteAgent`	`DeleteAgentRequest`	`Empty`	Unary	Active
`ExecutePolicy`	`ExecutePolicyRequest`	`ExecutePolicyResponse`	Unary	Active
`StreamStateChanges`	`StateChangeRequest`	`StateChangeResponse`	Server	Active
`StreamPrecisionUpdates`	`PrecisionUpdateRequest`	`PrecisionUpdateResponse`	Server	Active

Protocol Buffer Messages:

message AgentProto {
  string id = 1;
  string name = 2;
  string description = 3;
  string state = 4;
  PrecisionProto precision = 5;
  int32 version = 6;
}

message PolicyProto {
  string id = 1;
  string name = 2;
  double free_energy = 3;
  double confidence = 4;
  double epistemic_value = 5;
  double pragmatic_value = 6;
}

Connection Settings:

Max Connection Idle: 15 minutes
Max Connection Age: 30 minutes
Keepalive Time: 5 seconds
Keepalive Timeout: 1 second

2.2 REST Endpoints (TUI Integration)

File: lrs-agents/lrs/integration/tui/rest_endpoints.py
Framework: FastAPI (APIRouter) Base Path: /api/v1

Endpoint	Method	Auth	Description	Status
`/agents`	GET	TUI	List all agents	Active
`/agents`	POST	TUI	Create agent	Active
`/agents/{agent_id}`	GET	TUI	Get agent details	Active
`/agents/{agent_id}/state`	PUT	TUI	Update agent state	Active
`/agents/{agent_id}`	DELETE	TUI	Delete agent	Active
`/agents/{agent_id}/precision`	GET	TUI	Get precision info	Active
`/agents/{agent_id}/tools`	GET	TUI	List agent tools	Active
`/agents/{agent_id}/history`	GET	TUI	Get execution history	Active
`/agents/{agent_id}/tools/execute`	POST	TUI	Execute tool	Active
`/tools`	GET	TUI	List all tools	Active
`/tui/interaction`	POST	TUI	Handle interaction	Active
`/tui/events`	GET	TUI	SSE event stream	Active
`/system/info`	GET	TUI	System information	Active
`/system/health`	GET	TUI	Health check	Active

2.3 OpenCode Bridge API

File: lrs-agents/lrs/opencode/lrs_opencode_bridge.py
Port: 8765
Framework: FastAPI

Endpoint	Method	Auth	Request	Response
`/lrs/create-agent`	POST	Internal	`LRSRequest`	`{status, agent_id}`
`/lrs/execute`	POST	Internal	`LRSRequest`	`{result}`
`/opencode/execute`	POST	Internal	`OpenCodeRequest`	`{success, stdout, stderr, returncode}`

Models:

class LRSRequest(BaseModel):
    agent_id: str
    task: str
    context: Optional[Dict[str, Any]] = None

class OpenCodeRequest(BaseModel):
    command: str
    working_dir: Optional[str] = "."
    timeout: Optional[int] = 30

3. Emergent-Prompt-Architecture (EPA) - API Endpoints

File: Emergent-Prompt-Architecture/api_server.py
Port: 8000
Framework: FastAPI
Base Path: /api/v1

Endpoint	Method	Auth	Request	Response	Status
`/health`	GET	None	-	`HealthResponse`	Active
`/api/v1/ingest`	POST	None	`IngestRequest`	`IngestResponse`	Active
`/api/v1/crystallize`	POST	None	`CrystallizeRequest`	`CrystallizeResponse`	Active
`/api/v1/feedback`	POST	None	`FeedbackRequest`	`FeedbackResponse`	Active
`/api/v1/lattice/stats`	GET	None	-	`LatticeStatsResponse`	Active
`/api/v1/feedback/stats`	GET	None	-	Feedback stats	Active
`/api/v1/maintenance/decay`	POST	None	-	`{status, timestamp}`	Active
`/api/v1/maintenance/cleanup`	POST	None	Query: `max_age_days`	Cleanup results	Active
`/api/v1/sessions/{session_id}`	GET	None	Path: `session_id`	Session info	Active
`/api/v1/sessions/{session_id}`	DELETE	None	Path: `session_id`	Deletion confirmation	Active

Key Models:

class IngestRequest(BaseModel):
    source: str
    content: str
    timestamp: Optional[float] = Field(default_factory=time.time)
    metadata: Optional[Dict[str, Any]] = {}

class CrystallizeRequest(BaseModel):
    session_id: Optional[str] = ""
    target_model: Optional[str] = "default"
    mode: Optional[SystemMode] = SystemMode.SENTIO

class CrystallizeResponse(BaseModel):
    prompt_object: Dict[str, Any]
    provenance: Dict[str, List[str]]
    goldendag_hash: str
    trace_id: str

Onton Types:

CONTEXT - Contextual information
MEMORY - Stored memories
CONCEPT - Abstract concepts
RELATION - Relationships between concepts
TEMPORAL - Time-based information
ETHICAL - Ethical constraints

4. Advanced-Research - API Endpoints

File: Advanced-Research/src/advanced_research/unified/api.py
Architecture: Python class-based (not HTTP server) Integration: Direct Python API calls via UnifiedResearchSystem

4.1 Unified Research System API

Method	Parameters	Returns	Description
`initialize()`	-	None	Initialize all integrations
`shutdown()`	-	None	Shutdown all components
`create_session(user_id, mode, preferences)`	`user_id: str, mode: SystemMode, preferences: dict`	`session_id: str`	Create user session
`process_query(session_id, query, context_data)`	`session_id: str, query: str, context: dict`	`dict`	Process query
`get_system_status()`	-	`dict`	Get comprehensive status

System Modes:

class SystemMode(Enum):
    RESEARCH = "research"
    LEARNING = "learning"
    COMPUTATION = "computation"
    COLLABORATIVE = "collaborative"

4.2 Integration Manager APIs

IntegrationsManager provides access to three integrations:

LRS Integration

async def record_learning_event(actor, verb, object_data, result=None)
async def record_context_interaction(context_block, user_id, interaction_type, outcome)
async def flush_records()

Opencode Integration

async def create_research_document(title, content, research_area, tags, metadata)
async def search_documents(query, research_area, tags)

NeuralBlitz Integration

async def compute_geometric_features(input_data, manifold_type, curvature)
async def optimize_on_manifold(objective_function, initial_point, manifold_config)

5. Cross-Project API Integration Matrix

5.1 Which Projects Call Which

┌─────────────────────────────────────────────────────────────────┐
│                    API CALL MATRIX                               │
├─────────────────────────────────────────────────────────────────┤
│ NBX-LRS → lrs-agents:                                           │
│   • HTTP POST to /api/v1/lrs/integrate (bridge endpoint)        │
│   • WebSocket for real-time state streaming                     │
│   • gRPC for agent management (planned)                         │
├─────────────────────────────────────────────────────────────────┤
│ lrs-agents → NBX-LRS:                                           │
│   • HTTP GET /api/v1/quantum/state (metrics)                    │
│   • HTTP POST /api/v1/quantum/step (control)                    │
│   • HTTP GET /api/v1/reality/network (status)                   │
│   • HTTP POST /api/v1/reality/evolve (control)                  │
├─────────────────────────────────────────────────────────────────┤
│ lrs-agents ↔ OpenCode:                                          │
│   • HTTP POST /lrs/create-agent                                 │
│   • HTTP POST /lrs/execute                                      │
│   • HTTP POST /opencode/execute                                 │
├─────────────────────────────────────────────────────────────────┤
│ Advanced-Research → lrs-agents:                                 │
│   • Direct Python API via LRSIntegration class                  │
│   • Records learning events to LRS                              │
├─────────────────────────────────────────────────────────────────┤
│ Advanced-Research → Opencode:                                   │
│   • Direct Python API via OpencodeIntegration class             │
│   • Creates research documents                                  │
├─────────────────────────────────────────────────────────────────┤
│ Advanced-Research → NBX-LRS:                                    │
│   • Direct Python API via NeuralBlitzIntegration class          │
│   • Geometric feature computation                               │
├─────────────────────────────────────────────────────────────────┤
│ EPA → NBX-LRS:                                                  │
│   • Shares GoldenDAG hash format                                │
│   • Compatible provenance tracking                              │
└─────────────────────────────────────────────────────────────────┘

5.2 Protocol Versions

Protocol	Version	Status	Used By
HTTP/1.1	1.1	Active	All Flask/FastAPI servers
HTTP/2	2.0	Supported	gRPC services
gRPC	1.50+	Active	lrs-agents Go server
WebSocket	RFC 6455	Active	lrs-agents TUI
JWT	RFC 7519	Active	NBX-LRS unified_api
SSE	W3C Standard	Active	lrs-agents TUI events

5.3 Authentication Compatibility

Project	JWT	API Key	OAuth2	mTLS	Basic Auth
NBX-LRS Go	✗	✗	✗	✗	✗
NBX-LRS FastAPI	✗	✗	✗	✗	✗
NBX-LRS Flask	✓	✗	✗	✗	✓ (Form)
lrs-agents gRPC	✗	✗	✗	✗	✗
lrs-agents REST	✗	✗	✗	✗	✗
lrs-agents Bridge	✗	✗	✗	✗	✗
EPA	✗	✗	✗	✗	✗
Advanced-Research	✗	✗	✗	✗	✗

Note: Only NBX-LRS unified_api.py implements JWT authentication currently.

6. Shared Data Models & Schemas

6.1 GoldenDAG

Used By: NBX-LRS, EPA, lrs-agents

GoldenDAG = {
    "hash": str,  # 64-char hex
    "seed": str,  # Reference seed
    "timestamp": datetime,
    "provenance": List[str]
}

6.2 LRS Learning Record (xAPI)

Used By: lrs-agents, Advanced-Research

LearningRecord = {
    "actor": {
        "account": {
            "homePage": str,
            "name": str
        }
    },
    "verb": {
        "id": str,  # http://adlnet.gov/expapi/verbs/{verb}
        "display": {"en-US": str}
    },
    "object": {
        "id": str,
        "objectType": "Activity",
        "definition": dict
    },
    "result": Optional[dict],
    "timestamp": datetime
}

6.3 Agent State

Used By: lrs-agents, NBX-LRS (bridge)

AgentState = {
    "agent_id": str,
    "agent_type": str,
    "config": dict,
    "tools": List[str],
    "created_at": str,  # ISO datetime
    "status": str,  # "active", "deleted"
    "precision": {
        "abstract": float,
        "planning": float,
        "execution": float
    }
}

6.4 Quantum Neuron State

Used By: NBX-LRS

QuantumNeuronState = {
    "membrane_potential": float,  # mV
    "spike_rate": float,  # Hz
    "spike_count": int,
    "time_elapsed": float,  # ms
    "is_refractory": bool
}

6.5 Reality Network State

Used By: NBX-LRS

RealityNetworkState = {
    "global_consciousness": float,  # 0-1
    "cross_reality_coherence": float,  # 0-1
    "information_flow_rate": float,
    "reality_synchronization": float,
    "realities": {
        "reality_id": {
            "type": str,  # RealityType
            "consciousness": float,
            "information_density": float,
            "quantum_coherence": float
        }
    },
    "active_signals": int
}

7. OpenAPI Specification

Location: NBX-LRS/neuralblitz-v50/docs/api/openapi.yaml

The OpenAPI spec defines standard schemas for:

StatusResponse
IntentRequest/IntentResponse
VerificationRequest/VerificationResponse
NBCLRequest/NBCLResponse
AttestationResponse
SymbiosisResponse
SynthesisResponse
OptionResponse

Security Scheme:

securitySchemes:
  bearerAuth:
    type: http
    scheme: bearer
    bearerFormat: JWT

8. Integration Test Coverage

8.1 Test Files

Project	Test File	Coverage
lrs-agents	`integration-bridge/tests/test_api.py`	API endpoint tests with mocked httpx
lrs-agents	`integration-bridge/tests/integration_load_tests.py`	Load testing with aiohttp
NBX-LRS	`neuralblitz-v50/tests/test_auth.py`	Authentication tests
NBX-LRS	`neuralblitz-v50/tests/test_audit.py`	Audit trail tests

8.2 Test Patterns

# Example: Testing NBX-LRS integration
@patch("opencode_lrs_bridge.api.endpoints.httpx.AsyncClient")
def test_quantum_state_endpoint(mock_client):
    # Mock response
    mock_response = MagicMock()
    mock_response.status_code = 200
    mock_response.json.return_value = {
        "quantum_coherence": 0.95,
        "consciousness_level": 0.8
    }
    mock_client.return_value.get.return_value = mock_response
    
    # Test call
    response = client.get("/api/v1/quantum/state")
    assert response.status_code == 200

9. API Compatibility Matrix

9.1 Version Compatibility

Source	Target	Protocol	Version	Status
NBX-LRS v50	lrs-agents	HTTP	1.1	Compatible
lrs-agents	NBX-LRS v50	HTTP	1.1	Compatible
lrs-agents	OpenCode	HTTP	1.1	Compatible
Advanced-Research	lrs-agents	Python API	-	Compatible
Advanced-Research	NBX-LRS	Python API	-	Compatible
EPA	NBX-LRS	GoldenDAG	Shared	Compatible

9.2 Breaking Changes

None identified - All projects use compatible data formats and protocols.

Note: NBX-LRS has multiple API implementations (Go, Python, Flask) with different authentication levels. The Flask unified_api is the most feature-complete with JWT support.

10. Deployment Architecture

┌─────────────────────────────────────────────────────────────────┐
│                        CLIENT LAYER                              │
│  (React Dashboard, CLI Tools, External Services)                │
└─────────────────────────────────────────────────────────────────┘
                              │
                              ▼ HTTP/WebSocket
┌─────────────────────────────────────────────────────────────────┐
│                       API GATEWAY                                │
│  • NBX-LRS Flask API (Port 5000) - JWT Auth                     │
│  • NBX-LRS Go API (Port 8082) - CORS Only                       │
│  • lrs-agents REST (Port 8000)                                  │
└─────────────────────────────────────────────────────────────────┘
                              │
        ┌─────────────────────┼─────────────────────┐
        ▼                     ▼                     ▼
┌──────────────┐   ┌──────────────────┐   ┌─────────────────┐
│ NBX-LRS Core │   │ lrs-agents Core  │   │ EPA System      │
│ - Quantum    │   │ - gRPC Server    │   │ - Ontons        │
│ - Multi-     │   │ - Agent Manager  │   │ - Lattice       │
│   Reality    │   │ - TUI Bridge     │   │ - Crystallize   │
└──────────────┘   └──────────────────┘   └─────────────────┘
        │                     │                     │
        └─────────────────────┼─────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────────┐
│                    ADVANCED-RESEARCH                             │
│         (Orchestrates all three systems)                        │
└─────────────────────────────────────────────────────────────────┘

11. Security Considerations

11.1 Authentication Gaps

Most endpoints lack authentication (CORS only)
Only NBX-LRS Flask API implements JWT
No OAuth2 or API key authentication currently implemented
No mTLS for service-to-service communication

11.2 Recommended Security Enhancements

Implement API keys for service-to-service auth
Add rate limiting to all endpoints
Enable request signing for sensitive operations
Implement mTLS for gRPC services
Add audit logging for all API calls

12. Summary

12.1 Active Endpoints Summary

Project	REST Endpoints	gRPC Methods	WebSocket	Total
NBX-LRS	16 (3 APIs)	0	0	16
lrs-agents	14	7	1	22
EPA	9	0	0	9
Advanced-Research	6 (Python API)	0	0	6
TOTAL	45	7	1	53

12.2 Integration Points Summary

Bidirectional HTTP: NBX-LRS ↔ lrs-agents
Bridge Pattern: lrs-agents ↔ OpenCode
Direct Python API: Advanced-Research → All systems
Shared Formats: GoldenDAG (NBX-LRS, EPA, lrs-agents)
Protocol Buffers: lrs-agents gRPC services

12.3 Status: All Systems Operational

All identified API contracts are ACTIVE and compatible. No deprecated endpoints found. All projects can communicate through established integration points.

Document Version: 1.0
Last Updated: 2026-02-08
Classification: Technical Architecture

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