LlamaIndex is a data framework for building LLM-powered applications over your data. It provides tools for data ingestion, indexing, and querying, making it ideal for RAG (Retrieval-Augmented Generation) applications. Since MARA Cloud is OpenAI-compatible, you can use LlamaIndex's OpenAI integration with a custom base URL.
Prerequisites
- Python 3.9+
- A MARA Cloud API key. See API Keys and URLs to generate one.
Setup
Install LlamaIndex with the OpenAI integration:
bash
pip install llama-index llama-index-llms-openai-likeConfiguration
Point LlamaIndex to MARA Cloud using the
OpenAILike class:python
from llama_index.llms.openai_like import OpenAILike
llm = OpenAILike(
api_base="https://api.cloud.mara.com/v1",
api_key="your-mara-api-key",
model="MiniMax-M2.5",
is_chat_model=True,
)
response = llm.complete("Explain what RAG is in two sentences.")
print(response)Using with a query engine
Once configured, you can use the LLM with LlamaIndex's indexing and querying capabilities:
python
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, Settings
Settings.llm = llm
documents = SimpleDirectoryReader("./data").load_data()
index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine()
response = query_engine.query("What are the key points in this document?")
print(response)Learn more
- Model Catalog - Browse all available models.
- LlamaIndex Documentation - Official LlamaIndex docs.