# Open Source Implementation Roadmap ## Phase 0: Sanitize And Productize Goal: make the current codebase safe to publish and understandable outside Context-X. Tasks: - Add OSS name and package naming decision. - Move Context-X-only files into `examples/profiles/context-x/`. - Add `.env.example` without private domains or secrets. - Replace hardcoded defaults with generated config. - Add license, contributing guide, security policy, and public README. - Run secret scan and dependency/license audit. - Decide which training data can be published. Exit criteria: - Fresh clone can install without private services. - No private domains or internal IPs are required for default startup. - Public README explains local-only setup. ## Phase 1: Adaptive Init Goal: detect the user's AI environment and create config. Packages: - `packages/cli` - `packages/discovery` - `packages/config-writer` Commands: ```bash adaptive-llm-gateway init adaptive-llm-gateway doctor adaptive-llm-gateway integrate adaptive-llm-gateway mode offline adaptive-llm-gateway simulate ``` Detection targets: - Ollama - LM Studio - LocalAI - llama.cpp server - vLLM - Open WebUI - OpenAI-compatible endpoints - OpenAI/Anthropic/Groq/Mistral/OpenRouter env keys - Claude Code - Codex - Cursor - VS Code - Continue.dev - n8n - Docker containers - Git/Gitea availability Exit criteria: - `init` writes `~/.adaptive-llm-gateway/config.yaml`. - No external integration is enabled without approval. - `doctor` reports actionable health and setup status. ## Phase 2: Trust, Consent, Receipts Goal: every request goes through policy and produces an audit artifact. Packages: - `packages/trust-router` - `packages/policy-engine` - `packages/consent-ledger` - `packages/context-receipts` - `packages/run-ledger` - `packages/provider-router` Features: - four trust levels: public, internal, confidential, secret - local-only/offline routing mode - simulation mode with no execution - provider router route constraints and fallbacks - append-only consent ledger - receipt for context used, blocked, redacted, routed - reproducible run folder Exit criteria: - External providers are blocked for confidential/secret data by default. - Receipts can be viewed from CLI and dashboard. - Consent changes are append-only and reversible. ## Phase 3: Shared Memory And MCP Goal: make the gateway the shared memory and tool layer for all AI clients. Packages: - `packages/memory-sync` - `packages/handoff` - `packages/mcp-server` - `packages/route-reflector-memory` Features: - local memory repo - Git/Gitea sync - typed memory folders - MCP tools for memory and gateway calls - AI Handoff Protocol - Route Reflector Memory for routing outcomes - conflict-safe append-first writes MCP tools: - `gateway.complete` - `gateway.chat` - `gateway.health` - `gateway.route_preview` - `memory.search` - `memory.read` - `memory.write` - `memory.append_session` - `memory.record_decision` - `memory.record_task` - `memory.pull` - `memory.push` Exit criteria: - Claude Code and Codex can access the same memory through MCP. - Handoffs are stored in Git/Gitea. - Memory sync refuses to commit secrets. ## Phase 4: Compression And Knowledge Goal: reduce token use and retrieve only the right context. Packages: - `packages/context-compression` - `packages/connectors` - `packages/cache` Features: - token budget manager - session compaction - repo/doc summarization - memory dedupe - semantic cache - SQLite vector default - Postgres/Qdrant optional - approved data source connectors Exit criteria: - Context packages include budget, source refs, and compression stats. - Receipts show compressed-from and final token counts. - Indexing requires explicit allowed roots. ## Phase 5: Benchmarking And Reputation Goal: route based on evidence instead of static assumptions. Packages: - `packages/benchmark-lab` - `packages/agent-reputation` Features: - model capability tests - agent scorecards - latency/cost/quality tracking - JSON reliability test - code patch/test benchmark - local vs hosted comparison Exit criteria: - Trust Router can use benchmark scores. - Dashboard shows model and agent strengths. - Routing decisions explain benchmark influence. ## Phase 6: Product UI Goal: turn the operational dashboard into a usable OSS app. UI areas: - Topology - Models - Agents - Memory - Policies - Receipts - Benchmarks - Costs - Integrations - Doctor - Settings Exit criteria: - First screen is topology/status. - User can enable integrations from UI with diff preview. - User can inspect receipts and memory sync status.