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

# vLLM

> Using vLLM for local high-throughput LLM serving with Upsonic

## Overview

vLLM is a high-throughput serving engine for large language models that provides an OpenAI-compatible API. Perfect for running models locally with excellent performance and throughput.

**Model Class:** `OpenAIChatModel` (OpenAI-compatible API)

## Authentication

```bash theme={null}
export VLLM_BASE_URL="http://localhost:8000/v1"  # Required
export VLLM_API_KEY="your-api-key"  # Optional, vLLM doesnt not require authentication
```

## Examples

```python theme={null}
from upsonic import Agent, Task
from upsonic.models.vllm import VLLMModel

model = VLLMModel(model_name="Qwen/Qwen2.5-0.5B-Instruct")

agent = Agent(model=model)
task = Task("Hello, how are you?")
result = agent.do(task)

print(result)
```

## Model Settings

You can set model parameters in two ways: on the model or on the Agent.

**On the model:**

```python theme={null}
from upsonic import Agent, Task
from upsonic.models.vllm import VLLMModel, VLLMModelSettings

model = VLLMModel(
    model_name="Qwen/Qwen2.5-0.5B-Instruct",
    settings=VLLMModelSettings(max_tokens=1024, temperature=0.7)
)
agent = Agent(model=model)
```

**On the Agent:**

```python theme={null}
from upsonic import Agent, Task
from upsonic.models.vllm import VLLMModelSettings

agent = Agent(
    model="vllm/Qwen/Qwen2.5-0.5B-Instruct",
    settings=VLLMModelSettings(max_tokens=1024, temperature=0.7)
)
```

## Parameters

| Parameter             | Type        | Description                | Default       | Source |
| --------------------- | ----------- | -------------------------- | ------------- | ------ |
| `max_tokens`          | `int`       | Maximum tokens to generate | Model default | Base   |
| `temperature`         | `float`     | Sampling temperature       | Model default | Base   |
| `top_p`               | `float`     | Nucleus sampling           | Model default | Base   |
| `seed`                | `int`       | Random seed                | None          | Base   |
| `stop_sequences`      | `list[str]` | Stop sequences             | None          | Base   |
| `presence_penalty`    | `float`     | Token presence penalty     | 0.0           | Base   |
| `frequency_penalty`   | `float`     | Token frequency penalty    | 0.0           | Base   |
| `parallel_tool_calls` | `bool`      | Allow parallel tools       | True          | Base   |
| `timeout`             | `float`     | Request timeout (seconds)  | Model default | Base   |