taodengandClaude Opus 4.7 (noreply@anthropic.com) e2e67de23a feat(phase-1): land IR + plugin loader + server skeleton (D3)
Phase 1 Day 1. First executable code lands. Zero providers wired yet
(per ALIGNMENT.md "v0.1 ships 0 Enabled Providers"); the server starts
clean and POST /v1/chat/completions returns 503 with no_enabled_provider.

Files added:
  lib/ir/types.mjs            - IR v1.0 schema + validators (ADR 0003)
  lib/ir/openai-to-ir.mjs     - OpenAI Chat Completions to IR
  lib/ir/ir-to-openai.mjs     - IR chunks to OpenAI SSE / non-stream
  lib/providers/base.mjs      - Provider contract + validateProvider + ProviderError
  lib/providers/index.mjs     - Static empty registry stub (ADR 0002)
  server.mjs                  - HTTP listener with createOlpServer factory + main guard
  test-features.mjs           - 61 tests across 7 suites (IR / provider / HTTP)

Files modified:
  package.json - main and scripts.start/test added back; targets now exist.

Authority citations:
  IR fields and translation direction: ADR 0003 sections Decision and
    Translation direction model.
  Provider contract (9 fields): ADR 0002 section Provider contract v1.0
    interface.
  Entry surface routes (health, v1/models, v1/chat/completions): OLP v0.1
    spec section 4.1 single-protocol entry; ALIGNMENT.md Authority 2.
  Zero-Enabled-Providers behaviour: ALIGNMENT.md Provider Inventory.

Architectural decisions worth recording:
  1. server.mjs uses a createOlpServer factory plus an import.meta.url
     main guard. The factory returns an unbound http.Server; only the
     main-script invocation calls .listen(). Tests import the real
     server.mjs and exercise the real router. No parallel implementation
     in the test file.

     This pattern was a fold-in from the orchestration step. The initial
     sonnet draft put a top-level server.listen call in server.mjs, which
     forced test-features.mjs to reimplement the router inline (a false-
     confidence trap because the real server logic would never be tested).
     Refactored before reviewer dispatch.

  2. lib/providers/index.mjs ships an empty STATIC_REGISTRY array, not a
     placeholder with dummy entries. ALIGNMENT.md Provider Inventory says
     v0.1 ships zero Enabled Providers; the registry honors that exactly.
     Phase 1 Day 2 adds the first import (Anthropic) when its plugin lands.

  3. BadRequestError lives in openai-to-ir.mjs and ProviderError in
     base.mjs. Reviewer suggested relocating to a shared lib/errors.mjs
     once the count exceeds two; deferred to Phase 1 Day 2 to ship with
     the third typed error class.

  4. contractVersion: '1.0' on each provider plugin: not enforced at D3
     because no providers exist yet. Reviewer flagged for Phase 1 Day 2
     tightening when the first provider lands.

Reviewer chain (Iron Rule 10):
  Initial implementer: sonnet (general-purpose).
  Refactor (createOlpServer + main guard) by the orchestrator after
    catching the inline-router parallel-implementation issue.
  Fresh-context reviewer: opus (ecc:code-reviewer). Verdict
    APPROVE_WITH_MINOR.

Reviewer's two non-blocking findings folded in:
  F1: removed unused createServer import from test-features.mjs line 12,
      left over from the refactor.
  F2: replaced finish_reason value 'error' with 'stop' in both the
      streaming error chunk path (lib/ir/ir-to-openai.mjs line 72) and
      the non-streaming error aggregation path (lib/ir/ir-to-openai.mjs
      line 153). The 'error' value is not in OpenAI's documented
      finish_reason enum (stop / length / tool_calls / content_filter /
      function_call / null), so emitting it would violate ALIGNMENT.md
      Rule 2 (b). Provider errors are now surfaced via a top-level
      response.error object plus an inline content marker. The matching
      test assertion at test-features.mjs line 325 was updated to verify
      finish_reason stays within the OpenAI enum.

Note on the F2 fold-in:
  Reviewer pointed only at the streaming path (line 72). After applying
  that fix I ran grep across lib/ and test-features.mjs for the same
  invention pattern and caught a second hit at line 153 (non-streaming
  aggregation). This is the "fold-in must grep the full repo, not only
  the file the reviewer named" discipline from
  ~/.cc-rules/memory/feedback/evidence_first_under_speed_pressure.md.
  Both hits are fixed in this commit.

Verification:
  node --check on all 7 new files plus modified package.json plus
    server.mjs plus lib/ir/ir-to-openai.mjs - all clean.
  npm test - 61/61 pass in 209ms, no flakes, no skipped.
  OLP_PORT=14001 node server.mjs followed by curl /health returns
    proper JSON; curl /v1/models returns 200 empty list; server shuts
    down cleanly on signal.
  grep "finish_reason.*error" returns zero hits across lib/ and tests.

Co-Authored-By: Claude Opus 4.7 (noreply@anthropic.com)
2026-05-23 17:06:30 +10:00

OLP — Open LLM Proxy

A personal- and family-scale multi-provider LLM proxy. One HTTP endpoint, many subscriptions behind it, automatic routing, automatic fallback, content-addressed caching — so your IDEs and family clients keep working as long as any of your subscriptions has quota left.

Status: v0.1 — bootstrap. Most of this README is a skeleton; sections marked placeholder land alongside the relevant phase of work (see phase plan).


Why OLP

On 2026-05-14, Anthropic announced (effective 2026-06-15) that claude -p, the Agent SDK, and third-party agent traffic move out of the Pro/Max subscription pool into a separate fixed monthly Agent SDK Credit pool. OCP, OLP's predecessor, was a proxy around a single CLI — its core assumption was "subscription = unlimited within rate limits". That assumption breaks for Anthropic on the effective date.

The structural response is to stop relying on one provider's subscription terms remaining favourable. OLP spreads risk across multiple providers whose subscriptions still include CLI/programmatic use, routes intelligently between them, and caches aggressively so every request that does spawn a CLI counts.

OLP is not: a commercial multi-tenant SaaS; an enterprise gateway competing with LiteLLM / OpenCode / CLIProxyAPI on breadth; a model-capability router ("route to the smartest model" — you pick the model); a conversation-state store (your client handles that).

See ALIGNMENT.md for OLP's constitution and docs/adr/ for the founding ADRs.


Quick Start

placeholder — lands with Phase 1.

Anticipated shape:

# install
npm install -g @dtzp555-max/olp

# run setup (writes ~/.olp/config.json, asks which providers to enable)
olp setup

# start the proxy (default port 3456 — same as OCP if you migrate)
olp start

# point your IDE at http://localhost:3456/v1/chat/completions with the OLP API key from `olp keys list`.

Supported Providers

Source of truth: models-registry.json. This table is regenerated from the registry per the release_kit overlay; do not edit it out of sync.

OLP distinguishes Candidate Providers (declared as intended, not yet pinned) from Enabled Providers (authority pin filled + plugin landed + Phase audit passed). The v0.1 founding commit ships zero Enabled Providers — enablement is a Phase audit deliverable, not a bootstrap claim. See ALIGNMENT.md § Provider Inventory for the transition gate.

Candidate Providers

Provider key CLI Subscription / auth Anticipated Tier Anticipated Phase
anthropic claude -p Pro / Max OAuth (pre-2026-06-15); Agent SDK Credit pool after D (re-eval post-2026-06-15) Phase 1
openai codex exec --json ChatGPT Pro OAuth or API key D Phase 2
mistral vibe --prompt --output json Le Chat Pro API key D Phase 3
grok grok -p --output-format streaming-json xAI Build xai-... API key C Phase 8+
kimi kimi -p --output-format stream-json Moonshot Kimi API key C Phase 8+
minimax TBD MiniMax Token Plan (¥29+/mo) B Phase 8+
glm TBD Zhipu Coding Plan ($10+/mo) B Phase 8+
qwen TBD Alibaba Coding Plan ($50/mo) B Phase 8+

Risk tier guide. D = permissive / safe (eligible for default-enabled); C = tightening signal, no enforcement history (opt-in); B = service-level key revocation risk (opt-in + consent); A = excluded by default (cannot be opt-in enabled). Tier B providers prompt for explicit consent on first enable and record consent in ~/.olp/config.json. See ALIGNMENT.md § Risk Tier Framework.

Excluded by default (Tier A — evidence-backed, pending primary-source pin). Google Antigravity. See ADR 0006 for the named-prohibition + no-cost-advantage + reinstatement-friction rationale, and for the primary-source pinning follow-up that may force a Tier reconsideration if the Google FAQ language cannot be sourced within 90 days of 2026-05-23.


Configuration

placeholder — full configuration reference lands with Phase 4 (fallback engine).

OLP reads its config from ~/.olp/config.json. The minimum useful shape:

{
  "routing": {
    "chains": {
      "<requested-model>": [
        { "provider": "<key>", "model": "<provider-model-id>" },
        { "provider": "<key>", "model": "<provider-model-id>" }
      ]
    },
    "soft_triggers": {
      "<provider-key>": { "<trigger>": <threshold> }
    }
  }
}

Trigger types, fallback safety, idempotency rules, and the full example config land here when Phase 4 ships. See ADR 0004 (Fallback Engine Semantics & Safety) for the design.


API Endpoints

placeholder — full table lands as each endpoint lands.

Endpoint Method Phase Description
/v1/chat/completions POST 1 OpenAI-compatible Chat Completions entry. Internally normalized to IR, dispatched to a provider plugin, response shape converted back.
/v1/models GET 1 Lists models from models-registry.json.
/health GET 1 Per-provider health snapshot (owner-only).
/cache/stats GET 5 Cache hit rate, by-provider breakdown.
/v0/management/quota GET 6 Per-provider quota / credit pool status (best-effort).
/dashboard GET 6 Owner-only dashboard (localhost-bound by default).

Environment Variables

placeholder — full table lands per-phase as variables are introduced.

Variable Default Description
OLP_PORT 3456 HTTP listener port.
OLP_HOME ~/.olp Config, providers, keys, cache, logs root.
OLP_LOG_LEVEL info One of error, warn, info, debug.

Further variables (per-provider auth path overrides, cache size limits, fallback-engine knobs) land with the relevant phase.


Response Headers

Every response served through OLP carries:

  • X-OLP-Provider-Used: <provider-key> — which provider's plugin served the request.
  • X-OLP-Model-Used: <model-id> — which model the served provider used.
  • X-OLP-Fallback-Hops: <n> — number of fallback hops (0 if served by the primary chain entry).
  • X-OLP-Cache: hit | miss | bypass — cache layer outcome.
  • X-OLP-Latency-Ms: <ms> — end-to-end latency observed at the proxy.

If a fallback chain is exhausted, X-OLP-Fallback-Exhausted lists the tried providers in order.


Architecture

OLP is a Node.js (ESM, .mjs) HTTP proxy with no build step and minimal dependencies. The high-level shape:

  • Entry surfaceserver.mjs handles /v1/chat/completions and the administrative endpoints. Governed by OpenAI's /v1/chat/completions specification as the wire authority. See ALIGNMENT.md § Authorities.
  • Intermediate Representation (IR)lib/ir/ normalizes between the entry surface and provider-native shapes. The IR is the lingua franca; any extension is an ADR 0003 amendment.
  • Provider pluginslib/providers/<name>.mjs. Each plugin implements the contract in ADR 0002 (Plugin Architecture for Providers), spawns its CLI, and translates between IR and provider-native IO.
  • Cache layerlib/cache/ is a content-addressed cache keyed on (provider, model, messages, tools, temperature, response_format, cache_control). Per-key isolation, prompt-caching bypass, chunked stream replay, and singleflight. See ADR 0005 (Cache Layer Cross-Provider Design).
  • Fallback enginelib/fallback/ advances a configured chain one provider at a time on configured triggers, never retrying after the first response chunk has been emitted to the client. See ADR 0004.
  • Multi-key authlib/keys.mjs carries OCP's per-OLP-key namespace isolation forward. Each OLP API key has independent quota, cache namespace, and audit log; each key declares which providers it can access.

Read the ADRs in docs/adr/ in order before proposing structural changes.


Phase plan

OLP lands in phases. Each phase has its own PR series and Iron-Rule-10 reviewer; this README's placeholders are filled per-phase via the release_kit overlay.

  • Phase 0 — Repo bootstrap, ALIGNMENT.md, founding ADRs, CI workflows, PR template. (current)
  • Phase 1 — server.mjs skeleton, IR, Anthropic plugin, cache D1+D4. Port from OCP.
  • Phase 2 — OpenAI Codex plugin.
  • Phase 3 — Mistral Vibe plugin.
  • Phase 4 — Fallback engine + routing chains config + quota poll worker.
  • Phase 5 — Cache cross-provider hardening (D2+D3).
  • Phase 6 — Dashboard + observability (/v0/management/quota).
  • Phase 7 — Release v0.1, OCP enters maintenance.
  • Phase 8+ — Optional Grok / Kimi / tier-2 plugins; provider-native protocol endpoints; deterministic triggers.

Full spec (decision rationale, open questions, risks): ~/.cc-rules/memory/projects/olp_v0_1_spec.md on the maintainer's workstations.


Migration from OCP

placeholder — scripts/migrate-from-ocp.mjs lands with Phase 7.

Anticipated user-facing flow (target: <5 minutes):

  1. Stop OCP (launchctl bootout the OCP service or ocp stop).
  2. Install OLP.
  3. Run olp migrate-from-ocp — copies ~/.ocp/keys/ to ~/.olp/keys/ and points provider plugins at OCP's existing auth artifacts where applicable.
  4. Start OLP. Clients pointing at port 3456 keep working; their existing OLP API keys remain valid.

OCP's cache directory is not migrated: OLP's cache key format includes provider+model and warms cold naturally. OCP enters maintenance mode (stability fixes only) when OLP v0.1 ships; new development happens in OLP.


License

MIT.


Acknowledgements

OLP evolved from OCP (Open Claude Proxy). OCP's per-key isolation model, cache-layer design (D1D4), dashboard, and alignment-constitution discipline are all carried forward. The structural generalization from single-CLI to multi-provider is what makes this a new project rather than an OCP minor version — see ALIGNMENT.md § Reference: How OCP's cli.js discipline maps to OLP.

Authors: project maintainer (with AI drafting assistance).

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