This document provides the architecture diagrams for Astromesh, designed in a style inspired by Kubernetes‑like control plane / data plane systems.
These diagrams are intended to be embedded directly in the project README or documentation.
Astromesh is designed as an Agent Runtime Platform with layered architecture.
┌───────────────────────────────────────────────────────────────────────────────┐
│ External Interfaces │
│ │
│ REST API WebSocket API WhatsApp Channel Future Channels│
│ /v1/agents /v1/ws/agent/* Meta Cloud API Slack/Telegram│
└───────────────────────────────────────────────────────────────────────────────┘
│
▼
┌───────────────────────────────────────────────────────────────────────────────┐
│ API / Channel Layer │
│ │
│ FastAPI Routes WebSocket Gateway Channel Adapters │
│ - Agents - Streaming tokens - WhatsApp │
│ - Memory - Live sessions - Future adapters │
│ - Tools │
│ - RAG │
└───────────────────────────────────────────────────────────────────────────────┘
│
▼
┌───────────────────────────────────────────────────────────────────────────────┐
│ Agent Runtime Control Plane │
│ │
│ AgentRuntime │
│ - Load YAML definitions │
│ - Bootstrap agents │
│ - Wire dependencies │
│ - Manage lifecycle │
│ │
│ Agent Execution Pipeline │
│ Query → Guardrails → Memory → Prompt Rendering → Orchestration │
│ → Model Routing → Tool Calls → Response → Persistence │
└───────────────────────────────────────────────────────────────────────────────┘
│
▼
┌───────────────────────────────────────────────────────────────────────────────┐
│ Core Services │
│ │
│ Model Router Memory Manager Tool Registry Guardrails │
│ - Provider select - Conversational - Internal tools - PII detect │
│ - Fallback - Semantic - MCP tools - Topic filter │
│ - Circuit breaker - Episodic - Webhooks - Cost limits │
│ - Capability match - Context build - RAG as tool - Content rules │
└───────────────────────────────────────────────────────────────────────────────┘
│
▼
┌───────────────────────────────────────────────────────────────────────────────┐
│ Orchestration / Reasoning Layer │
│ │
│ ReAct Plan & Execute Pipeline Parallel Fan-Out │
│ Supervisor Swarm │
└───────────────────────────────────────────────────────────────────────────────┘
│
▼
┌───────────────────────────────────────────────────────────────────────────────┐
│ Execution Plane │
│ │
│ LLM Providers Retrieval / Knowledge ML / Inference │
│ - Ollama - Chunking - ONNX models │
│ - OpenAI-compatible - Embeddings - PyTorch │
│ - vLLM - Vector search - Registries │
│ - llama.cpp - Reranking │
│ - HuggingFace TGI - pgvector / Chroma / Qdrant / FAISS │
└───────────────────────────────────────────────────────────────────────────────┘
│
▼
┌───────────────────────────────────────────────────────────────────────────────┐
│ Storage / Observability │
│ │
│ Redis PostgreSQL SQLite Prometheus OpenTelemetry │
│ pgvector ChromaDB Qdrant Grafana Cost Tracking │
└───────────────────────────────────────────────────────────────────────────────┘
This diagram shows how the runtime behaves similarly to distributed platforms such as Kubernetes.
┌────────────────────────────┐
│ Astromesh Control Plane │
│────────────────────────────│
│ AgentRuntime │
│ Config Loader (YAML) │
│ Dependency Wiring │
│ Routing Policies │
│ Guardrails Policies │
│ Tool Permissions │
│ Agent Lifecycle │
└──────────────┬─────────────┘
│
┌──────────────────────┼──────────────────────┐
│ │ │
▼ ▼ ▼
┌──────────────────┐ ┌──────────────────┐ ┌──────────────────┐
│ Agent Worker A │ │ Agent Worker B │ │ Agent Worker C │
│──────────────────│ │──────────────────│ │──────────────────│
│ ReAct │ │ Plan & Execute │ │ Supervisor/Swarm │
│ Tool Calls │ │ Memory Access │ │ Multi-Agent Flow │
│ Prompt Rendering │ │ Model Routing │ │ Delegation │
└────────┬─────────┘ └────────┬─────────┘ └────────┬─────────┘
│ │ │
└──────────────┬───────┴──────────────┬───────┘
│ │
▼ ▼
┌──────────────────────────┐ ┌──────────────────────────┐
│ Model Execution │ │ Tool / Knowledge │
│──────────────────────────│ │──────────────────────────│
│ Ollama │ │ Internal Python tools │
│ OpenAI-compatible APIs │ │ MCP tools │
│ vLLM │ │ Webhooks │
│ llama.cpp │ │ RAG pipelines │
│ HuggingFace TGI │ │ Vector retrieval │
│ ONNX Runtime │ │ Reranking │
└──────────────┬───────────┘ └──────────────┬───────────┘
│ │
└──────────────┬───────────────┘
│
▼
┌──────────────────────────────────────┐
│ State / Storage / Telemetry │
│──────────────────────────────────────│
│ Redis │
│ PostgreSQL / SQLite │
│ pgvector / ChromaDB / Qdrant / FAISS │
│ OpenTelemetry / Prometheus / Grafana │
│ Cost Tracking │
└──────────────────────────────────────┘
GitHub supports Mermaid diagrams natively.
flowchart TB
A[External Interfaces<br/>REST API / WebSocket / WhatsApp / Future Channels] --> B[API and Channel Layer<br/>FastAPI Routes / WebSocket Gateway / Channel Adapters]
B --> C[Agent Runtime Control Plane<br/>YAML Loader / Bootstrap / Lifecycle / Dependency Wiring]
C --> D[Agent Execution Pipeline<br/>Guardrails → Memory → Prompt → Orchestration → Routing → Tools → Persistence]
D --> E[Core Services]
E --> E1[Model Router]
E --> E2[Memory Manager]
E --> E3[Tool Registry]
E --> E4[Guardrails]
E --> F[Orchestration Layer]
F --> F1[ReAct]
F --> F2[Plan and Execute]
F --> F3[Pipeline]
F --> F4[Parallel Fan-Out]
F --> F5[Supervisor]
F --> F6[Swarm]
F --> G[Execution Plane]
G --> G1[LLM Providers<br/>Ollama / OpenAI-compatible / vLLM / llama.cpp / HF TGI / ONNX]
G --> G2[Knowledge Layer<br/>Chunking / Embeddings / Vector Search / Reranking]
G --> G3[Tools<br/>Internal / MCP / Webhooks / RAG]
G --> H[Storage and Observability]
H --> H1[Redis / PostgreSQL / SQLite]
H --> H2[pgvector / ChromaDB / Qdrant / FAISS]
H --> H3[Prometheus / Grafana / OpenTelemetry / Cost Tracking]
This architecture separates agent control, reasoning orchestration, and execution infrastructure into distinct layers.
Benefits include:
- Declarative agent definitions
- Swappable LLM providers
- Pluggable memory backends
- Multi-agent orchestration
- Built-in observability
- Channel integrations
- Safe tool execution
This design allows Astromesh to scale from single-agent applications to distributed agentic systems.