本地OpenAI集成

Integration Configuration

After installation, configure the integration through Home Assistant's UI:

1. Go to Settings → Devices & Services.
2. Click Add Integration.
3. Search for Local OpenAI LLM.
4. Follow the setup wizard to configure your desired services.

---

Configuration Notes

• The Server URL must be a fully qualified URL pointing to an OpenAI-compatible API.
• This typically ends with /v1 but may differ depending on your server configuration.
• A Server Type configuration can be set to expose some additional options for different inference servers and providers, where they have been implemented.
• Assist requires a fairly lengthy context for tooling and entity definitions.
• It is strongly recommended to use at least 10k context size and to limit history length and exposed entities to avoid context overflow issues.
• This is not configurable through OpenAI-compatible APIs, and needs to be configured with the inference server directly.
• Tool calling must be enabled in your inference engine, eg:
• vLLM: https://docs.vllm.ai/en/latest/features/tool_calling/
• llama.cpp: https://github.com/ggml-org/llama.cpp/blob/master/docs/function-calling.md
• Parallel tool calling requires support from both your model and inference server.
• In some cases, control of this is handled by the server directly, in which case toggling this will not have any result.
• Chat Template Arguments allow you to provide custom arguments to your model
• Arguments are supplied as key/value pairs and provided to the chat_template_kwargs request parameter
• Values support Jinja2 templates, in order to provide non-string and more complex data structures
• Arguments differ per model, and not all models make use of user-provided arguments
• See your models documentation for what arguments are available to be used
• AI Task entities can be configured for Text and/or Image generation capabilities
• This capability uses the Images API spec and requires support from your chosen image generation server
• Support has been developed and tested with StableDiffusion.cpp

---

DeepSeek Cloud Configuration

Reasoning Effort

When the server type is set to DeepSeek Cloud, both conversation and AI task agents show a new DeepSeek Configuration section with a Reasoning Effort option. This option controls whether thinking is enabled, and what level of reasoning to perform on the request.

• Disabled (default) — no thinking tokens.
• High — enables thinking with standard reasoning effort.
• Max — enables thinking with maximum reasoning effort.

When enabled, thinking content returned by the model is also fed back into the conversation as reasoning content on supported Home Assistant versions (2026.4+).

---

llama.cpp Configuration

When the server type is set to llama.cpp, both conversation and AI task agents show a llama.cpp Configuration section with the following options.

Enable thinking

Passes enable_thinking=true via chat_template_kwargs to enable reasoning on supported models.

• Disabled (default) — no thinking tokens.
• Enabled — requests reasoning from the model.

When enabled, thinking content returned by the model is also fed back into the conversation as reasoning content on supported Home Assistant versions (2026.4+).

Note: This option completely overrides any existing enable_thinking option in your Chat Template Arguments.

Slot ID

Pins requests to a specific llama.cpp server slot for prompt-cache reuse. Leave empty to allow any slot to be used.

Model naming

llama.cpp exposes the value supplied via its --alias flag on the model object. When an alias is set it is used as the model's display name; otherwise the raw model id (typically the full model file path) is used, with the path and .gguf extension stripped for a cleaner name.

---

Weaviate Configuration

1. Install Weaviate locally
2. A pre-made docker-compose.yml is provided in the weaviate directory of this repository.
3. Weaviate Cloud is not supported: there is no free tier available and its cheapest pricing plan isn't attractive for personal/home use, and so I don't anticipate demand for this.
4. Reconfigure your LLM Server entity (not the Agent entity) in Home Assistant.
5. Expand the Weaviate configuration section and fill in the details server address and API key (homeassistant if using the supplied docker-compose.yml).
6. Optional: Reconfigure your AI Agent entities in Home Assistant.
7. This is only needed if you wish to change the default Weaviate values on a per-agent basis:
8. Object class name: Defaults to Homeassistant, can be changed if you want a different data store for the Agent. The integration will handle creating the required object class within Weaviate if it does not already exist.
9. Maximum number of results to use: Defaults to 2.
10. Result score threshold: Defaults to 0.9.
11. Hybrid search alpha: Defaults to 0.5. Balances the hybrid result scoring between 0 (fully text-matched) and 1 (fully vectorised) matching.

Local OpenAI LLM <small>_(Custom Integration for Home Assistant)_</small>

Allows use of generic OpenAI-compatible LLM services, such as (but not limited to):

• llama.cpp
• vLLM
• LM Studio
• Ollama
• OpenRouter
• Scaleway
• DeepSeek

This integration has been forked from Home Assistants OpenRouter integration, with the following changes:

• Added server URL to the initial server configuration
• Made the API Key optional during initial server configuration: can be left blank if your local server does not require one
• Uses streamed LLM responses
• Conversation Agents support TTS streaming
• Automatically strips <think> tags from responses
• Added support for image inputs for AI Task entities
• Added support for reconfiguring Conversation Agents
• Added option to trim conversation history to help stay within your context window
• Added temperature control
• Added option to strip emojis from responses
• Added support for parallel tool calling
• Added experimental Retrieval Augmented Generation capability
• Added chat template arguments support
• Added image generation support for AI Task entities
• Added tools support for Generate Data actions for AI Task entities

---