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This release is a pre-release and may not be stable for production use.

OVOS OpenAI Plugin

This package uses the OpenAI Chat Completions API to provide OpenAI-compatible plugins for OpenVoiceOS. It works with any server that exposes the OpenAI /chat/completions contract, such as OpenAI, ollama, llama.cpp, vLLM, or LocalAI. Point api_url at the server's /v1 base to use it.

This package provides:

Plugin Entry point Type Purpose
ovos-chat-openai-plugin opm.agents.chat ChatEngine Multi-turn chat agent (native tool/function calling) for ovos-persona
ovos-openai-rag-memory-plugin opm.agents.memory AgentContextManager RAG memory: inject vector-store context from an ovos-persona-server
ovos-summarizer-openai-plugin opm.agents.summarizer SummarizerEngine Summarize text for other plugins/skills
ovos-translate-openai-plugin opm.lang.translate LanguageTranslator LLM-backed text translation
ovos-lang-detect-openai-plugin opm.lang.detect LanguageDetector LLM-backed language detection
ovos-dialog-transformer-openai-plugin opm.transformer.dialog DialogTransformer Rewrite OVOS dialogs just before TTS in ovos-audio

Breaking change: solver plugins are deprecated in ovos-plugin-manager. This release migrates from the legacy QuestionSolver/ChatMessageSolver to the new agents framework (AbstractAgentEngine). The old ovos-solver-openai-plugin entry point and the OpenAIChatCompletionsSolver and OpenAIPersonaSolver classes have been removed. Personas must now reference ovos-chat-openai-plugin. This release requires ovos-plugin-manager>=2.2.3a1 and ovos-persona>=0.9.0a1.

Install

pip install ovos-openai-plugin

Persona Usage

To create your own persona using an OpenAI-compatible server, create a .json in ~/.config/ovos_persona/llm.json:

{
  "name": "My Local LLM",
  "solvers": [
    "ovos-chat-openai-plugin"
  ],
  "ovos-chat-openai-plugin": {
    "api_url": "https://llama.smartgic.io/v1",
    "key": "sk-xxxx",
    "system_prompt": "You are a helpful assistant who gives very short and factual answers in maximum twenty words and you don't use emojis",
    "model": "llama3.1:8b"
  }
}

The solvers key name is kept for backwards compatibility with persona JSON files. It now accepts agent plugin names (chat engines) in addition to legacy solvers.

An OpenAI-compatible endpoint is not OpenAI, and the parameters that matter differ per provider and per model. extra_params is a mapping merged into the request body last, so it can add a field the plugin has no setting for (reasoning_effort, thinking, top_k, repetition_penalty...) or override one it always sends (max_tokens, temperature, stop...). A key set to null removes the field from the request instead of sending it, for a provider that rejects it. The conversation itself (messages) cannot be replaced or removed this way; that key is ignored and logged. A value that is not a mapping is ignored and logged rather than taking the assistant down mid-conversation.

{
  "ovos-chat-openai-plugin": {
    "api_url": "https://llama.smartgic.io/v1",
    "model": "llama3.1:8b",
    "extra_params": {
      "reasoning_effort": "none",
      "top_k": 40,
      "stop": null
    }
  }
}

Say "Chat with {name_from_json}" to enable it. See the ovos-persona README for more details.

This plugin also provides a default "Remote LLama" demo persona, pointing to a public server hosted by @goldyfruit.

RAG memory

ovos-openai-rag-memory-plugin (PersonaServerRAGMemory) is a persona memory plugin. Before each turn, it searches a vector store on an ovos-persona-server and injects the retrieved chunks into the conversation context. The persona's chat engine then answers. This plugin composes with any chat backend instead of owning the chat round-trip.

Set it as the persona's memory_module:

{
  "name": "kb-assistant",
  "solvers": ["ovos-chat-openai-plugin"],
  "memory_module": "ovos-openai-rag-memory-plugin",
  "ovos-openai-rag-memory-plugin": {
    "api_url": "http://localhost:8337/openai/v1",
    "vector_store_id": "vs_...",
    "inject_mode": "system",
    "retrieval": {"max_num_results": 5}
  }
}

inject_mode selects how retrieved context enters the prompt: system (separate system message, default), system_prompt, developer, user, or tool (a synthetic search_knowledge_base tool-call result). Retrieval (max_num_results, min_score, query_mode) and context formatting are configurable. This feature requires an ovos-persona version that passes config to memory plugins. See docs/rag-memory.md for the full configuration reference, how to build the vector store this plugin searches (files + embeddings, local or hosted), and its failure modes.

Dialog Transformer

Rewrite text dynamically based on a persona, such as simplifying explanations or mimicking a tone.

Example:

  • rewrite_prompt: "rewrite the text as if you were explaining it to a 5-year-old"
  • Input: "Quantum mechanics is a branch of physics that describes the behavior of particles at the smallest scales."
  • Output: "Quantum mechanics is like a special kind of science that helps us understand really tiny things."

To enable this plugin, add the following to your mycroft.conf:

"dialog_transformers": {
    "ovos-dialog-transformer-openai-plugin": {
        "api_url": "https://api.openai.com/v1",
        "key": "sk-xxxx",
        "model": "gpt-4o-mini",
        "system_prompt": "Your task is to rewrite text as if it was spoken by a different character",
        "rewrite_prompt": "rewrite the text as if you were explaining it to a 5-year-old"
    }
}

The actual dialog text is appended after rewrite_prompt in the request.

Direct Usage

from ovos_openai_plugin import OpenAIChatEngine
from ovos_plugin_manager.templates.agents import AgentMessage, MessageRole

bot = OpenAIChatEngine({
    "key": "sk-XXX",
    "model": "gpt-4o-mini",
    "system_prompt": "You are helpful, creative, clever, and very friendly",
})

# one-shot answer
print(bot.get_response("describe quantum mechanics in simple terms"))

# multi-turn chat
reply = bot.continue_chat([
    AgentMessage(MessageRole.USER, "what is the capital of France?")
])
print(reply.content)

# stream complete sentences (TTS friendly)
for sentence in bot.stream_sentences([AgentMessage(MessageRole.USER, "tell me a short story")]):
    print(sentence)

Translation and summarization:

from ovos_openai_plugin import OpenAITextTranslator, OpenAISummarizer

tx = OpenAITextTranslator({"key": "sk-XXX", "model": "gpt-4o-mini"})
print(tx.translate("hello world", target="es-es"))

summary = OpenAISummarizer({"key": "sk-XXX", "model": "gpt-4o-mini"})
print(summary.summarize("a very long document ..."))

Remote Persona / Proxies

You can run any persona behind an OpenAI-compatible server with ovos-persona-server. This moves the workload to a standalone server, either for performance or to keep API keys in a single safe place. Then configure this plugin to point at your persona server as if it were OpenAI.

Documentation


Credits

Developed by TigreGótico for OpenVoiceOS.

NGI0 Commons Fund

This project was funded through the NGI0 Commons Fund, a fund established by NLnet with financial support from the European Commission's Next Generation Internet programme, under the aegis of DG Communications Networks, Content and Technology under grant agreement No 101135429.

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