> ## Documentation Index
> Fetch the complete documentation index at: https://docs.modelslab.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Using with Coding Tools

> Use ModelsLab's LLM API with Claude Code, OpenAI Codex, Cursor, Continue, Aider, and other AI coding assistants.

ModelsLab's LLM API is compatible with popular AI coding tools. Since it supports both OpenAI and Anthropic API formats, you can use it as a drop-in backend for most AI coding assistants.

## Claude Code

[Claude Code](https://docs.anthropic.com/en/docs/claude-code) is Anthropic's agentic CLI coding tool. You can point it at ModelsLab's API to use any of 200+ LLM models.

### Quick Start

```bash theme={null}
ANTHROPIC_BASE_URL="https://modelslab.com/api/v7/llm" \
ANTHROPIC_AUTH_TOKEN="YOUR_MODELSLAB_API_KEY" \
claude --model "Qwen/Qwen2.5-VL-72B-Instruct-together"
```

### Persistent Configuration

Add to your shell profile (`~/.bashrc`, `~/.zshrc`, etc.):

```bash theme={null}
export ANTHROPIC_BASE_URL="https://modelslab.com/api/v7/llm"
export ANTHROPIC_AUTH_TOKEN="YOUR_MODELSLAB_API_KEY"
```

Then run Claude Code with any model:

```bash theme={null}
claude --model "Qwen/Qwen2.5-VL-72B-Instruct-together"
claude --model "meta-llama/Llama-3.1-70B-Instruct"
claude --model "deepseek-ai/DeepSeek-R1"
```

### Non-Interactive / Scripting

```bash theme={null}
ANTHROPIC_BASE_URL="https://modelslab.com/api/v7/llm" \
ANTHROPIC_AUTH_TOKEN="YOUR_MODELSLAB_API_KEY" \
claude --model "Qwen/Qwen2.5-VL-72B-Instruct-together" \
  -p "Explain this codebase" \
  --dangerously-skip-permissions
```

***

## OpenAI Codex CLI

[Codex CLI](https://github.com/openai/codex) is OpenAI's open-source coding agent. It works with any OpenAI-compatible API.

### Setup

```bash theme={null}
OPENAI_API_KEY="YOUR_MODELSLAB_API_KEY" \
OPENAI_BASE_URL="https://modelslab.com/api/v7/llm" \
codex --model "Qwen/Qwen2.5-VL-72B-Instruct-together"
```

### With Environment Variables

```bash theme={null}
export OPENAI_API_KEY="YOUR_MODELSLAB_API_KEY"
export OPENAI_BASE_URL="https://modelslab.com/api/v7/llm"

codex --model "Qwen/Qwen2.5-VL-72B-Instruct-together" "refactor this function"
```

***

## Cursor

[Cursor](https://cursor.sh) is an AI-powered code editor. You can configure it to use ModelsLab as a custom OpenAI-compatible provider.

### Setup

1. Open Cursor Settings (`Cmd+,` / `Ctrl+,`)
2. Go to **Models** > **OpenAI API Key**
3. Set your API key to your ModelsLab API key
4. Set the base URL to `https://modelslab.com/api/v7/llm`
5. Add your preferred model IDs (e.g., `Qwen/Qwen2.5-VL-72B-Instruct-together`)

You can now select ModelsLab models from Cursor's model dropdown.

***

## Continue (VS Code / JetBrains)

[Continue](https://continue.dev) is an open-source AI code assistant for VS Code and JetBrains.

### Configuration

Edit your `~/.continue/config.yaml`:

```yaml theme={null}
models:
  - name: ModelsLab Qwen 72B
    provider: openai
    model: Qwen/Qwen2.5-VL-72B-Instruct-together
    apiBase: https://modelslab.com/api/v7/llm
    apiKey: YOUR_MODELSLAB_API_KEY

  - name: ModelsLab DeepSeek R1
    provider: openai
    model: deepseek-ai/DeepSeek-R1
    apiBase: https://modelslab.com/api/v7/llm
    apiKey: YOUR_MODELSLAB_API_KEY
```

***

## Aider

[Aider](https://aider.chat) is a terminal-based AI pair programming tool.

### Setup

```bash theme={null}
OPENAI_API_KEY="YOUR_MODELSLAB_API_KEY" \
OPENAI_API_BASE="https://modelslab.com/api/v7/llm" \
aider --model "openai/Qwen/Qwen2.5-VL-72B-Instruct-together"
```

### With `.aider.conf.yml`

```yaml theme={null}
openai-api-key: YOUR_MODELSLAB_API_KEY
openai-api-base: https://modelslab.com/api/v7/llm
model: openai/Qwen/Qwen2.5-VL-72B-Instruct-together
```

***

## LangChain

Use ModelsLab as the LLM backend in your LangChain applications:

```python theme={null}
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="Qwen/Qwen2.5-VL-72B-Instruct-together",
    openai_api_key="YOUR_MODELSLAB_API_KEY",
    openai_api_base="https://modelslab.com/api/v7/llm",
    temperature=0.7,
)

response = llm.invoke("Explain the Builder pattern in Python")
print(response.content)
```

***

## LiteLLM

[LiteLLM](https://litellm.ai) provides a unified API for 100+ LLM providers. Add ModelsLab as a custom provider:

```python theme={null}
import litellm

response = litellm.completion(
    model="openai/Qwen/Qwen2.5-VL-72B-Instruct-together",
    messages=[{"role": "user", "content": "Hello!"}],
    api_key="YOUR_MODELSLAB_API_KEY",
    api_base="https://modelslab.com/api/v7/llm",
)

print(response.choices[0].message.content)
```

***

## General OpenAI-Compatible Tools

Any tool that supports a custom OpenAI base URL works with ModelsLab:

| Setting      | Value                                              |
| ------------ | -------------------------------------------------- |
| **API Key**  | Your ModelsLab API key                             |
| **Base URL** | `https://modelslab.com/api/v7/llm`                 |
| **Model**    | Any model from [List Models](/llm-api/list-models) |

<Tip>
  Browse all available models at [modelslab.com/models/category/llmaster](https://modelslab.com/models/category/llmaster) and use the model ID directly in any compatible tool.
</Tip>