LlamaIndex

RAG and query engines via OpenAILike

LlamaIndex

LlamaIndex provides OpenAILike for third-party OpenAI-compatible APIs. Use it to connect a LlamaIndex application to Radium.

Before you start

You need Python 3.10 or newer, a Radium API key, and a terminal or PowerShell window.

1. Create a project and install LlamaIndex

macOS or Linux

mkdir radium-llamaindex && cd radium-llamaindex
python3 -m venv .venv
source .venv/bin/activate
python -m pip install llama-index-llms-openai-like

2. Set your Radium credentials

macOS or Linux

export RADIUM_API_KEY="your-radium-api-key"
export RADIUM_MODEL="hal-1.0"

3. Create main.py

import os
from llama_index.core.llms import ChatMessage
from llama_index.llms.openai_like import OpenAILike

api_key = os.getenv("RADIUM_API_KEY")
if not api_key:
    raise SystemExit("Set RADIUM_API_KEY before running this program.")

llm = OpenAILike(
    model=os.getenv("RADIUM_MODEL", "hal-1.0"),
    api_key=api_key,
    api_base="https://api.radium.cloud/v1",
    is_chat_model=True,
    max_tokens=512,
    temperature=0,
    timeout=90,
)

response = llm.chat(
    [
        ChatMessage(role="system", content="Follow the user's instruction exactly."),
        ChatMessage(role="user", content="Reply with exactly: Radium connected."),
    ]
)

content = response.message.content
if not content or not content.strip():
    raise RuntimeError("Radium returned no visible text.")
print(f"RADIUM_RESPONSE: {content.strip()}")

LlamaIndex calls the endpoint setting api_base, not base_url.

4. Run it

python main.py

Expected output:

RADIUM_RESPONSE: Radium connected.

Choose a model

export RADIUM_MODEL="clarke-1.0"  # or hal-1.0 or tycho-1.0
python main.py

Migrate an existing LlamaIndex app

Replace its current LLM object:

llm = OpenAILike(
    model="hal-1.0",
    api_key=os.environ["RADIUM_API_KEY"],
    api_base="https://api.radium.cloud/v1",
    is_chat_model=True,
    max_tokens=512,
)

Pass llm to the existing index, query engine, workflow, or agent. A RAG application still needs a separate embedding model; do not use these chat model IDs as embedding model IDs.

Troubleshooting

Problem	Fix
Authentication errors	Check RADIUM_API_KEY in the active terminal
404	Keep /v1 in api_base and use an exact Radium model ID
Empty output	Use at least 512 output tokens
Import errors	Activate .venv and reinstall the pinned package

Validation

These instructions were verified with Python 3.12.7 and llama-index-llms-openai-like==0.7.2 on August 20, 2026. You do not need that exact package version.

Text generation and FunctionAgent tool calling passed with hal-1.0, clarke-1.0, and tycho-1.0.

Next steps

API quickstart

Call Radium directly

Tool calling

The tool_use and tool_result contract