README.md

aMMare Implementation Guide

Welcome to the step-by-step implementation guide for the Asymmetric Multi-Model AI Routing Engine (aMMare). This directory contains detailed execution plans, file scaffolds, configurations, and validation criteria for each of the 13 roadmap phases outlined in the aMMare Architecture Document.

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Directory Structure Overview

During the implementation process, you will build and organize the repository into the following structure:

aMMare-Asymmetric-Multi-Model-AI-Routing-Engine/
├── architecture/          # High-level architecture docs and assets
├── config/                # Service-specific configuration files (.yaml, .json, etc.)
│   ├── langchain/
│   ├── litellm/
│   ├── headroom/
│   └── ...
├── containers/            # Dockerfiles and container-specific definitions
│   ├── langchain/
│   ├── litellm/
│   └── ...
├── env/                   # Environment example templates (*.env.example) and local overrides (*.env)
├── implementation/        # Step-by-step implementation guide markdown files (this directory)
├── scripts/               # Operational, deployment, validation, and helper scripts
│   ├── deploy.sh          # Top-level orchestrator deployment script
│   ├── uninstall.sh       # Clean reset script
│   └── ...
├── tests/                 # Integration and unit tests
└── logs/                  # Ignored log files directory

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Implementation Principles

When implementing any phase, strictly adhere to these core architectural constraints:

1. Physical Service-Chain Gateway: Do not hardcode service URLs directly in code. Services must communicate using environment variables. The primary endpoint for model access is configured via AMMARE_MODEL_GATEWAY_URL.
2. Idempotent Scripting: All deployment, reset, and validation scripts must be safe to run repeatedly without causing side effects or corrupting state.
3. Externalized Configuration: All variables, keys, and paths must live in the env/ directory. Create a <service>.env.example template for every config file. The actual <service>.env files containing secrets or system-specific details must be git-ignored.
4. Validation First: Do not progress to a new phase until the validation script for the current phase executes successfully and returns a PASS status.
5. No Monolithic Scripts: The top-level deploy.sh script should only orchestrate component deployment scripts (e.g., scripts/deploy-local-llm.sh).

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Roadmap Phases

Below is the execution path. Each phase is self-contained and must be validated before moving to the next.

Foundational Layers

• Phase 0: Repository Scaffold and Baseline Standards
  • Set up repository directories, .gitignore rules, pre-commit hooks, linting rules, and foundational operational scripts.
• Phase 1: Local LLM Endpoint
  • Spin up the local vLLM container with multi-GPU tensor parallelism for the laboratory dual RTX 3060 GPUs.
• Phase 2: LangChain Middleware Layer
  • Set up the core LangChain orchestration middleware with logging, health checkpoints, and initial schema validation.
• Phase 3: Direct Local Model Workflow Validation
  • Validate the minimal end-to-end service chain (User -> LangChain -> Local LLM) under normal operation and recovery.

Routing & Cloud Integration

• Phase 4: LiteLLM Routing Layer
  • Integrate the LiteLLM proxy to abstract model endpoint targets and configure virtual keys.
• Phase 5: Cloud Model Provider Integration
  • Add frontier cloud model providers (Claude, GPT-4, Gemini) to the LiteLLM proxy with externalized credentials.
• Phase 6: Routing and Escalation Logic
  • Implement configuration-driven logic (models.yaml and routing.yaml) to route tasks based on complexity and fallback on failures.

Optimization & Agent Workspaces

• Phase 7: Headroom Integration
  • Deploy the Headroom proxy inline for token payload compression and context optimization, complete with bypass rules.
• Phase 8: OpenHands Integration
  • Deploy the OpenHands coding agent workspace container with mount restrictions and tool safety profiles.
• Phase 9: Memory, Context, and Retrieval
  • Integrate vector database indexing, embedding engines, and RAG injection rules into the LangChain middleware.

Verification & Deployment Packaging

• Phase 10: Full Service Chain Validation
  • Execute end-to-end functional and failure tests across the entire chain.
• Phase 11: One-Click Modular Deployment
  • Build the top-level deploy/uninstall script orchestrators supporting modular profiles (minimal-local, hybrid, full).
• Phase 12: Documentation, Hardening, and Release Packaging
  • Complete operational playbooks, perform security hardening reviews, and package release archives.

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Global Environment Naming Conventions

All environment configurations should follow this unified naming standard:

Variable	Description
AMMARE_DEPLOY_PROFILE	Controls which services are deployed (minimal-local, hybrid, full)
AMMARE_BASE_DIR	Absolute path to the repository root directory
AMMARE_DATA_DIR	Directory containing persistent storage volumes (data/models/, data/vector-db/, etc.)
AMMARE_MODEL_GATEWAY_URL	The current active logical endpoint URL for LLM access
AMMARE_GATEWAY_URL	The client-facing port of ammare-langchain (e.g. http://localhost:8080)
AMMARE_LOG_LEVEL	Default logging verbosity (DEBUG, INFO, WARNING, ERROR)