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models.yaml
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models.yaml
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---
# This is the model configuration file used by the `home-assistant-datasets`
# tool. Each entry is a ConfigEntry that configures a specific model type
# with whatever integration is needed (either core integration or custom component).
#
# Some models require secrets such as API keys or urls that are specific to you
# and not checked into the repository and referenced in this file like `!secret openai_api_key`.
# Create a file called `secrets.yaml` and include the necessary keys.
models:
- model_id: assistant
domain: homeassistant
description: The Home Assisatnt NLP assistant pipeline
urls:
- https://github.com/home-assistant/hassil
#
# Large Cloud Models
#
- model_id: gpt-3.5
domain: openai_conversation
description: Open AI Conversation integration using gpt-3.5 (175B)
urls:
- https://platform.openai.com/docs/models/gpt-3-5-turbo
config_entry_data:
api_key: !secret openai_api_key
config_entry_options:
chat_model: gpt-3.5-turbo-1106
llm_hass_api: assist
- model_id: gpt-4o
domain: openai_conversation
description: Open AI Conversation integration using gpt-4o
urls:
- https://platform.openai.com/docs/models/gpt-4o
config_entry_data:
api_key: !secret openai_api_key
config_entry_options:
chat_model: gpt-4o
llm_hass_api: assist
- model_id: gpt-4o-mini
domain: openai_conversation
description: Open AI Conversation integration using gpt-4o-mini
urls:
- https://platform.openai.com/docs/models/gpt-4o-mini
config_entry_data:
api_key: !secret openai_api_key
config_entry_options:
chat_model: gpt-4o-mini
llm_hass_api: assist
- model_id: gemini-pro
domain: google_generative_ai_conversation
description: Google Generative AI integration using gemini pro (v1)
urls:
- https://deepmind.google/technologies/gemini/pro/
config_entry_data:
api_key: !secret google_api_key
config_entry_options:
chat_model: models/gemini-pro
llm_hass_api: assist
- model_id: gemini-1.5-flash
domain: google_generative_ai_conversation
description: Google Generative AI integration using gemini flash (v1.5)
urls:
- https://blog.google/products/gemini/google-gemini-new-features-july-2024/
config_entry_data:
api_key: !secret google_api_key
config_entry_options:
chat_model: models/gemini-1.5-flash-latest
llm_hass_api: assist
- model_id: claude-3-5-sonnet
domain: anthropic
description: Anthropic integration using Claude 3.5 Sonnet
urls:
- https://www.anthropic.com/news/claude-3-5-sonnet
config_entry_data:
api_key: !secret anthropic_api_key
config_entry_options:
chat_model: claude-3-5-sonnet-20240620
llm_hass_api: assist
- model_id: claude-3-haiku
domain: anthropic
description: Anthropic integration using Claude 3 Haiku
urls:
- https://www.anthropic.com/news/claude-3-haiku
config_entry_data:
api_key: !secret anthropic_api_key
config_entry_options:
chat_model: claude-3-haiku-20240307
llm_hass_api: assist
#
# Open Source smaller function calling models
#
# Using an openai compatible custom component
# https://github.com/allenporter/hass-openai-custom-conversation
- model_id: functionary-small-v2.5
description: A custom open AI integration using functionary small v2.5 (8B) with a modified pre-release llama cpp python server.
domain: vicuna_conversation
urls:
- https://huggingface.co/meetkai/functionary-small-v2.5
- https://github.com/abetlen/llama-cpp-python
- https://github.com/allenporter/functionary-server
config_entry_data:
api_key: sk-0000000000000000000
# Update with your openai compatible functionary url
base_url: http://functionary.functionary:8000/v1
config_entry_options:
chat_model: functionary-small-v2.5
llm_hass_api: assist
- model_id: mistral-v3
domain: ollama
description: Mistral V3 (7B) using Ollama
urls:
- https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3
- https://ollama.com/library/mistral
- https://mistral.ai/news/announcing-mistral-7b/
config_entry_data:
url: !secret ollama_url
model: mistral:latest
config_entry_options:
llm_hass_api: assist
- model_id: mistral-nemo
domain: ollama
description: A state-of-the-art 12B model with 128k context length, built by Mistral AI in collaboration with NVIDIA.
urls:
- https://mistral.ai/news/mistral-nemo/
- https://ollama.com/library/mistral-nemo
config_entry_data:
url: !secret ollama_url
model: mistral-nemo
config_entry_options:
llm_hass_api: assist
num_ctx: 8192 # Note: Model has 128k context length
- model_id: qwen2.5
domain: ollama
description: Qwen2.5 models are pretrained on Alibaba's latest large-scale dataset, encompassing up to 18 trillion tokens. The model supports up to 128K tokens and has multilingual support.
urls:
- https://qwenlm.github.io/blog/qwen2.5/
- https://ollama.com/library/qwen2.5
config_entry_data:
url: !secret ollama_url
model: qwen2.5
config_entry_options:
llm_hass_api: assist
num_ctx: 8192
- model_id: llama3-groq-tool-use
domain: ollama
description: Groq tool use model fine tuned from llama3 (8B) using Ollama
urls:
- https://ollama.com/library/llama3-groq-tool-use
- https://console.groq.com/docs/tool-use
config_entry_data:
url: !secret ollama_url
model: llama3-groq-tool-use:latest
config_entry_options:
llm_hass_api: assist
- model_id: llama3.1
domain: ollama
description: Llama 3.1 (8B) from Meta using Ollama with 8k t window.
urls:
- https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct
- https://ollama.com/library/llama3.1
config_entry_data:
url: !secret ollama_url
model: llama3.1:latest
config_entry_options:
llm_hass_api: assist
num_ctx: 8192
- model_id: llama3.2-3b
domain: ollama
description: Meta's Llama 3.2 goes small with 1B and 3B models.
urls:
- https://huggingface.co/meta-llama/Llama-3.2-3B
- https://ollama.com/library/llama3.2:3b
config_entry_data:
url: !secret ollama_url
model: llama3.2:3b
config_entry_options:
llm_hass_api: assist
num_ctx: 8192
- model_id: llama3.2-1b
domain: ollama
description: Meta's Llama 3.2 goes small with 1B and 3B models.
urls:
- https://huggingface.co/meta-llama/Llama-3.2-1B
- https://ollama.com/library/llama3.2:1b
config_entry_data:
url: !secret ollama_url
model: llama3.2:1b
config_entry_options:
llm_hass_api: assist
num_ctx: 8192
- model_id: xlam-7b
domain: ollama
description: XLam (7B) model from Salesforce using Ollama with 4k context window.
urls:
- https://huggingface.co/Salesforce/xLAM-7b-fc-r
- https://github.com/SalesforceAIResearch/xLAM
- https://ollama.com/allenporter/xlam:7b
config_entry_data:
url: !secret ollama_url
model: allenporter/xlam:7b
config_entry_options:
llm_hass_api: assist
num_ctx: 4096
- model_id: assist-llm
domain: ollama
description: Assist LLM fine tuned on Home Assistant Assist intents based on Llama 3.1 (8B)
urls:
- https://ollama.com/allenporter/assist-llm
- https://huggingface.co/allenporter/assist-llm
- https://huggingface.co/allenporter/assist-llm-GGUF
config_entry_data:
url: !secret ollama_url
model: allenporter/assist-llm
config_entry_options:
llm_hass_api: assist
num_ctx: 8192
#
# Open Source smaller models
#
# Configuration for home-llm custom component https://github.com/acon96/home-llm
- model_id: home-llm
domain: llama_conversation
description: The home-llm v3 model based on Phi (3B) and custom component using service calls to control Home Assistant.
urls:
- https://github.com/acon96/home-llm/
- https://huggingface.co/acon96/Home-3B-v3-GGUF
- https://ollama.com/fixt/home-3b-v3
version: 2
# Home LLM has a very complex configuration that depends on the specific backend
# and model used. You're on your own to figure out the valid values to enter here.
config_entry_data:
model_backend: ollama
host: ollama.ollama
port: "11434"
ssl: false
huggingface_model: fixt/home-3b-v3:latest
config_entry_options:
llm_hass_api: home-llm-service-api
prompt: "You are 'Al', a helpful AI Assistant that controls the devices in a house. Complete the following task as instructed with the information provided only.\nThe current time and date is {{ (as_timestamp(now()) | timestamp_custom(\"%I:%M %p on %A %B %d, %Y\", \"\")) }}\nServices: {{ formatted_tools }}\nDevices:\n{{ formatted_devices }}"
prompt_template: "zephyr"
tool_format: "min_tool_format"
tool_multi_turn_chat: false
in_context_examples: false
in_context_examples_file: "in_context_examples.csv"
num_in_context_examples: 4.0
max_new_tokens: 128
context_length: 2048.0
top_k: 40.0
temperature: 0.1
top_p: 1.0
typical_p: 1.0
ollama_json_mode: false
request_timeout: 90.0
ollama_keep_alive: 30.0
remote_use_chat_endpoint: false
extra_attributes_to_expose:
- rgb_color
- brightness
- temperature
- humidity
- fan_mode
- media_title
- volume_level
- item
- wind_speed
service_call_regex: "```homeassistant\\n([\\S \\t\\n]*?)```"
refresh_prompt_per_turn: true
remember_conversation: true
remember_num_interactions: 5
- model_id: xlam-1b
domain: ollama
description: XLam (1B) model from Salesforce using Ollama
urls:
- https://huggingface.co/Salesforce/xLAM-1b-fc-r
- https://github.com/SalesforceAIResearch/xLAM
- https://ollama.com/allenporter/xlam:1b
config_entry_data:
url: !secret ollama_url
model: allenporter/xlam:1b
config_entry_options:
llm_hass_api: assist
#
# Non function calling models
#
- model_id: llama3
domain: ollama
description: Llama 3 (8B) from Meta using Ollama
urls:
- https://ollama.com/library/llama3
config_entry_data:
url: !secret ollama_url
model: llama3:latest
- model_id: gemma
domain: ollama
description: Gemma (7B) from Google using Ollama
urls:
- https://ollama.com/library/gemma
- https://ai.google.dev/gemma/docs/model_card
config_entry_data:
url: !secret ollama_url
model: gemma:7b