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OmniNode document ingestion and semantic retrieval

Project description

OmniMemory

Python 3.12+ ONEX 4.0 Linting: ruff Type checked: mypy Pre-commit

Memory persistence, recall, and semantic retrieval for the OmniNode platform. OmniMemory provides ONEX-compliant nodes and handlers for storing agent context, indexing embeddings, querying intent graphs, and managing the full memory lifecycle across distributed omni agents.

Four-Node Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│     EFFECT      │───▶│     COMPUTE     │───▶│     REDUCER     │───▶│  ORCHESTRATOR   │
│  (store/fetch)  │    │ (embed/analyze) │    │  (consolidate)  │    │  (coordinate)   │
└─────────────────┘    └─────────────────┘    └─────────────────┘    └─────────────────┘
  • EFFECT: Memory storage, retrieval, and intent query against external backends
  • COMPUTE: Semantic analysis, similarity scoring, embedding generation
  • REDUCER: Memory consolidation, statistics aggregation, lifecycle state management
  • ORCHESTRATOR: Agent coordination, multi-step memory lifecycle workflows

What This Repo Provides

  • Memory nodesmemory_storage_effect, memory_retrieval_effect, intent_storage_effect, intent_query_effect, intent_event_consumer_effect
  • Compute nodessemantic_analyzer_compute, similarity_compute
  • Reducer nodesmemory_consolidator_reducer, statistics_reducer
  • Orchestrator nodesmemory_lifecycle_orchestrator, agent_coordinator_orchestrator
  • Intent handlershandler_intent, handler_subscription with protocol-driven adapters
  • Protocol interfaces — embedding provider, intent graph adapter, secrets provider
  • Audit layer — I/O audit logging via audit/
  • Runtime plugin — registered as onex.domain_plugins entry point (PluginMemory)

Infrastructure Ownership

OmniMemory's docker-compose.yml owns the memory-layer data services. These are the services you need to run omnimemory locally:

Service Container Default Port Purpose
Qdrant omnimemory-qdrant 6333 (HTTP), 6334 (gRPC) Vector database for semantic memory
Memgraph omnimemory-memgraph 7687 (Bolt), 7444 (HTTP) Graph database for relationship/intent queries
Valkey omnimemory-valkey 6379 In-memory cache and session storage
Kreuzberg omnimemory-kreuzberg-parser 8090 Document text extraction service

Not owned here — these services are managed by other repositories:

Service Owner Repository Why
Kafka / Redpanda omnibase_infra Platform-wide event bus, shared by all services
PostgreSQL omnibase_infra Platform-wide relational database, shared by all services

If you need Kafka or Postgres, start the omnibase_infra stack first:

docker compose -f /path/to/omnibase_infra/docker/docker-compose.infra.yml up -d

Quick Start

Memory services only

To run just the omnimemory data services (Qdrant, Memgraph, Valkey, Kreuzberg):

git clone https://github.com/OmniNode-ai/omnimemory.git
cd omnimemory

# Start memory data services
docker compose up -d

# Verify all services are healthy
docker compose ps

Default service ports (all configurable via .env):

  • Qdrant REST: localhost:6333
  • Memgraph Bolt: localhost:7687
  • Valkey: localhost:6379
  • Kreuzberg parser: localhost:8090

Install and run tests

uv sync
uv run pytest tests/ -m unit

For configuration options see docs/environment_variables.md.

Minimal example using the intent handler:

import asyncio
from uuid import uuid4

from omnibase_core.container import ModelONEXContainer
from omnimemory.handlers.adapters.models import ModelIntentClassificationOutput
from omnimemory.handlers.handler_intent import HandlerIntent


async def main() -> None:
    container = ModelONEXContainer()
    handler = HandlerIntent(container)

    await handler.initialize(connection_uri="bolt://localhost:7687")

    # Store an intent
    result = await handler.store_intent(
        session_id="session_123",
        intent_data=ModelIntentClassificationOutput(
            intent_category="debugging",
            confidence=0.92,
            keywords=["error", "traceback"],
        ),
        correlation_id=str(uuid4()),
    )

    # Query session intents
    query_result = await handler.query_session(
        session_id="session_123",
        min_confidence=0.5,
    )

    await handler.shutdown()


asyncio.run(main())

Directory Structure

src/omnimemory/
├── audit/              # I/O audit logging
├── enums/              # Domain enumerations (memory types, operation types, lifecycle states)
├── errors/             # Structured error types
├── handlers/           # HandlerIntent, HandlerSubscription + adapters
├── models/             # Pydantic models (core, memory, intelligence, service, container, contracts)
├── nodes/              # EFFECT, COMPUTE, REDUCER, ORCHESTRATOR node implementations
├── protocols/          # Protocol interfaces (embedding, intent graph, secrets)
├── runtime/            # Plugin registration, wiring, dispatch, introspection
├── tools/              # Contract linter and stubs
└── utils/              # Shared utilities (audit logger, PII detection, retry, health)

Development

Uses uv for package management.

uv sync
uv run pytest tests/ -m unit
uv run mypy src/omnimemory/ --strict
uv run ruff check src/ tests/
uv run ruff format src/ tests/

Documentation

Reference: docs/

Open an issue or email contact@omninode.ai.

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