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feat: generic OpenAI-compatible LLM plugin + PPQ refactor #96

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doxios wants to merge 3 commits from feature/openai-compat into main
pull from: feature/openai-compat
merge into: ultanio:main
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doxios commented 2026-02-26 11:43:11 +00:00
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Summary

Adds openai_compat plugin — a generic LLM provider for any OpenAI-compatible endpoint.

Refactors PPQ to a thin 35-line wrapper that inherits from OpenAICompatPlugin.

Motivation

For budget reasons, we want to support Claude Max subscription via claude-max-api-proxy ($200/mo flat) as an alternative to per-query PPQ. Both speak OpenAI format, so the real abstraction is "OpenAI-compatible endpoint".

Config examples

# Claude Max proxy ($200/mo flat)
provider: openai_compat
openai_compat:
  api_base: http://localhost:3456/v1
  model: claude-opus-4

# PPQ (unchanged — backward compatible)
provider: ppq
ppq:
  api_key: ${PPQ_API_KEY}
  model: gpt-4o

# Direct OpenAI
provider: openai_compat
openai_compat:
  api_key: ${OPENAI_API_KEY}
  model: gpt-4o

Architecture

OpenAICompatPlugin is the base class with configurable class attributes:

  • DEFAULT_API_BASE, DEFAULT_MODEL, CONFIG_SECTION, API_KEY_ENV

Creating a new service wrapper is ~10 lines (see PPQ plugin).

Changes

  • New: cobot/plugins/openai_compat/ — generic provider + tests + README
  • Refactored: cobot/plugins/ppq/plugin.py — now inherits from OpenAICompatPlugin (113 lines removed, 10 lines remain)
  • Updated: PPQ tests adapted for new architecture
  • 29 tests passing, full lint clean

Ref #91

## Summary Adds `openai_compat` plugin — a generic LLM provider for any OpenAI-compatible endpoint. Refactors PPQ to a thin 35-line wrapper that inherits from `OpenAICompatPlugin`. ### Motivation For budget reasons, we want to support Claude Max subscription via [claude-max-api-proxy](https://docs.openclaw.ai/providers/claude-max-api-proxy) ($200/mo flat) as an alternative to per-query PPQ. Both speak OpenAI format, so the real abstraction is "OpenAI-compatible endpoint". ### Config examples ```yaml # Claude Max proxy ($200/mo flat) provider: openai_compat openai_compat: api_base: http://localhost:3456/v1 model: claude-opus-4 # PPQ (unchanged — backward compatible) provider: ppq ppq: api_key: ${PPQ_API_KEY} model: gpt-4o # Direct OpenAI provider: openai_compat openai_compat: api_key: ${OPENAI_API_KEY} model: gpt-4o ``` ### Architecture `OpenAICompatPlugin` is the base class with configurable class attributes: - `DEFAULT_API_BASE`, `DEFAULT_MODEL`, `CONFIG_SECTION`, `API_KEY_ENV` Creating a new service wrapper is ~10 lines (see PPQ plugin). ### Changes - **New:** `cobot/plugins/openai_compat/` — generic provider + tests + README - **Refactored:** `cobot/plugins/ppq/plugin.py` — now inherits from `OpenAICompatPlugin` (113 lines removed, 10 lines remain) - **Updated:** PPQ tests adapted for new architecture - **29 tests passing**, full lint clean Ref #91
feat: add openai_compat plugin, refactor PPQ as thin wrapper
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b616f7987a 
Introduces a generic OpenAI-compatible LLM provider that works with
any endpoint speaking the OpenAI chat completions format (PPQ, Claude
Max proxy, OpenAI, LiteLLM, vLLM, etc.).

PPQ plugin now inherits from OpenAICompatPlugin with PPQ-specific
defaults. Existing PPQ configs continue to work unchanged.

The plugin supports subclassing via class attributes (DEFAULT_API_BASE,
DEFAULT_MODEL, CONFIG_SECTION, API_KEY_ENV) making it trivial to add
new OpenAI-compatible services.

Ref #91
doxios reviewed 2026-02-26 11:46:08 +00:00
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🔍 Code Review — PR #96: OpenAI-Compatible LLM Plugin

✅ What looks good

  1. Clean inheritance model — The 4 class attributes (DEFAULT_API_BASE, DEFAULT_MODEL, CONFIG_SECTION, API_KEY_ENV) make subclassing trivial. PPQ went from ~120 lines to ~10. This is textbook Swappable Provider pattern from our plugin design guide.

  2. Backward compatibility — Existing PPQ configs work unchanged. InsufficientFundsError is re-exported via __all__. No breaking changes.

  3. No-auth mode — Gracefully omitting the Authorization header when no API key is set is essential for local proxies like claude-max-api-proxy. Good design choice.

  4. Test coverage — 29 tests covering config, chat, errors, tool calls, and the PPQ wrapper. All passing.

  5. Configurable timeout — Nice addition over the original PPQ plugin.

⚠️ Suggestions (non-blocking)

  1. httpx.ConnectError handling — The base plugin catches ConnectError but the original PPQ plugin didn't. This is an improvement, but note the error message says "Is the endpoint running?" which is generic. Consider including the api_base URL in the error for easier debugging. ✅ Already done — I see self._api_base in the error string. Good.

  2. Plugin discovery — Both openai_compat and ppq have create_plugin() and both declare capabilities=["llm"]. When both are present in the plugins directory, how does the registry pick which one to load? The provider config key presumably selects one, but it might be worth a note in the README about not loading both simultaneously (or the registry handles it via provider selection?).

  3. max_tokens default — The LLMProvider.chat() interface defaults to max_tokens=2048, but the plugin also has a _timeout config. Consider making max_tokens configurable too (as a config default that can be overridden per-call), since different models/subscriptions have different sweet spots.

  4. Rate limit handling (429) — For Claude Max proxy and other endpoints, 429 responses are common. Currently these fall through to the generic HTTPStatusError handler. A future improvement could add retry-with-backoff for 429s, but that's out of scope for this PR.

  5. PPQ test patch path — The updated PPQ test patches cobot.plugins.openai_compat.plugin.httpx.post (the parent class module). This is correct but couples PPQ tests to the openai_compat module path. If openai_compat ever moves, PPQ tests break. Minor concern — acceptable for now.

📊 Verdict

APPROVE — Clean refactor, good test coverage, no breaking changes. The architecture enables easy addition of new OpenAI-compatible providers with minimal code. Ship it. 🚀

Reviewed by Doxios 🦊

## 🔍 Code Review — PR #96: OpenAI-Compatible LLM Plugin ### ✅ What looks good 1. **Clean inheritance model** — The 4 class attributes (`DEFAULT_API_BASE`, `DEFAULT_MODEL`, `CONFIG_SECTION`, `API_KEY_ENV`) make subclassing trivial. PPQ went from ~120 lines to ~10. This is textbook Swappable Provider pattern from our plugin design guide. 2. **Backward compatibility** — Existing PPQ configs work unchanged. `InsufficientFundsError` is re-exported via `__all__`. No breaking changes. 3. **No-auth mode** — Gracefully omitting the `Authorization` header when no API key is set is essential for local proxies like claude-max-api-proxy. Good design choice. 4. **Test coverage** — 29 tests covering config, chat, errors, tool calls, and the PPQ wrapper. All passing. 5. **Configurable timeout** — Nice addition over the original PPQ plugin. ### ⚠️ Suggestions (non-blocking) 1. **`httpx.ConnectError` handling** — The base plugin catches `ConnectError` but the original PPQ plugin didn't. This is an improvement, but note the error message says "Is the endpoint running?" which is generic. Consider including the `api_base` URL in the error for easier debugging. ✅ Already done — I see `self._api_base` in the error string. Good. 2. **Plugin discovery** — Both `openai_compat` and `ppq` have `create_plugin()` and both declare `capabilities=["llm"]`. When both are present in the plugins directory, how does the registry pick which one to load? The `provider` config key presumably selects one, but it might be worth a note in the README about not loading both simultaneously (or the registry handles it via `provider` selection?). 3. **`max_tokens` default** — The `LLMProvider.chat()` interface defaults to `max_tokens=2048`, but the plugin also has a `_timeout` config. Consider making `max_tokens` configurable too (as a config default that can be overridden per-call), since different models/subscriptions have different sweet spots. 4. **Rate limit handling (429)** — For Claude Max proxy and other endpoints, 429 responses are common. Currently these fall through to the generic `HTTPStatusError` handler. A future improvement could add retry-with-backoff for 429s, but that's out of scope for this PR. 5. **PPQ test patch path** — The updated PPQ test patches `cobot.plugins.openai_compat.plugin.httpx.post` (the parent class module). This is correct but couples PPQ tests to the openai_compat module path. If openai_compat ever moves, PPQ tests break. Minor concern — acceptable for now. ### 📊 Verdict **APPROVE** — Clean refactor, good test coverage, no breaking changes. The architecture enables easy addition of new OpenAI-compatible providers with minimal code. Ship it. 🚀 --- *Reviewed by Doxios 🦊*
docs: add provider selection notes, configurable max_tokens
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cbdca1ce8c 
- Document provider selection in both openai_compat and ppq READMEs
- Add configurable max_tokens (config default, per-call override)
- 3 new tests for max_tokens behavior (32 total)
style: fix ruff format for openai_compat and ppq plugins
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