Configure LLM¶
Index¶
Configure the LLM model¶
Modules that use LLM model¶
Most of the modules that using LLM model can take llm
parameter to specify the LLM model.
The following modules can use generator module, which including llama_index_llm
.
Supporting LLM Models¶
We support most of the LLMs that LlamaIndex supports. You can use different types of LLM interfaces by configuring the llm
parameter:
LLM Model Type |
llm parameter |
Description |
---|---|---|
OpenAI |
openai |
For OpenAI models (GPT-3.5, GPT-4) |
OpenAILike |
openailike |
For models with OpenAI-compatible APIs (e.g., Mistral, Claude) |
Ollama |
ollama |
For locally running Ollama models |
Bedrock |
bedrock |
For AWS Bedrock models |
For example, if you want to use OpenAILike
model, you can set llm
parameter to openailike
.
nodes:
- node_line_name: node_line_1
nodes:
- node_type: generator
modules:
- module_type: llama_index_llm
llm: openailike
model: mistralai/Mistral-7B-Instruct-v0.2
api_base: your_api_base
api_key: your_api_key
At the above example, you can see model
parameter.
This is the parameter for the LLM model.
You can set the model parameter for LlamaIndex LLM initialization.
The most frequently used parameters are model
, max_token
, and temperature
.
Please check what you can set for the model parameter
at LlamaIndex LLM.
Common Parameters¶
The most frequently used parameters for LLM configuration are:
model
: The model identifier or namemax_tokens
: Maximum number of tokens in the responsetemperature
: Controls randomness in the output (0.0 to 1.0)api_base
: API endpoint URL (for hosted models)api_key
: Authentication key (if required)
For a complete list of available parameters, please refer to the LlamaIndex LLM documentation.
Add more LLM models¶
You can add more LLM models for AutoRAG.
You can add it by simply calling autorag.generator_models
and add new key and value.
For example, if you want to add MockLLM
model for testing, execute the following code.
Attention
It was major update for LlamaIndex to v0.10.0. The integration of llms must be installed to different packages. So, before add your model, you should find and install the right package for your model. You can find the package at here.
import autorag
from llama_index.core.llms.mock import MockLLM
autorag.generator_models['mockllm'] = MockLLM
Then you can use mockllm
at config YAML file.
Caution
When you add new LLM model, you should add class itself, not the instance.
Plus, it must follow LlamaIndex LLM’s interface.