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

# LLM

To quickly demonstrate Large Language Model (LLM) capabilities in UltraRAG UI, we provide a preset Pipeline. Before formal operation, please complete Pipeline compilation and parameter configuration.

## 1. Pipeline Structure Overview

```yaml examples/LLM.yaml icon="https://mintcdn.com/ultrarag/T7GffHzZitf6TThi/images/yaml.svg?fit=max&auto=format&n=T7GffHzZitf6TThi&q=85&s=69b41e79144bc908039c2ee3abbb1c3b" theme={null}
# LLM Demo for UltraRAG UI

# MCP Server
servers:
  benchmark: servers/benchmark
  prompt: servers/prompt
  generation: servers/generation

# MCP Client Pipeline
pipeline:
- benchmark.get_data
- prompt.qa_boxed
- generation.generation_init
- generation.generate
```

## 2. Compile Pipeline File

Execute the following command in the terminal to compile:

```shell theme={null}
ultrarag build examples/LLM.yaml
```

## 3. Configure Running Parameters

Modify `examples/parameter/LLM_parameter.yaml` according to your environment needs. The following example shows how to switch the backend from `vLLM` to `OpenAI API` standard interface and adjust the model name and system prompt.

```yaml examples/parameter/LLM_parameter.yaml icon="https://mintcdn.com/ultrarag/T7GffHzZitf6TThi/images/yaml.svg?fit=max&auto=format&n=T7GffHzZitf6TThi&q=85&s=69b41e79144bc908039c2ee3abbb1c3b"  theme={null}
benchmark:
  benchmark:
    key_map:
      gt_ls: golden_answers
      q_ls: question
    limit: -1
    name: nq
    path: data/sample_nq_10.jsonl
    seed: 42
    shuffle: false
generation:
  backend: vllm  # [!code --]
  backend: openai # [!code ++]
  backend_configs:
    hf:
      batch_size: 8
      gpu_ids: 2,3
      model_name_or_path: openbmb/MiniCPM4-8B
      trust_remote_code: true
    openai:
      api_key: abc
      base_delay: 1.0
      base_url: http://localhost:8000/v1 # [!code --]
      base_url: http://localhost:65503/v1 # [!code ++]
      concurrency: 8
      model_name: MiniCPM4-8B # [!code --]
      model_name: qwen3-32b # [!code ++]
      retries: 3
    vllm:
      dtype: auto
      gpu_ids: 2,3
      gpu_memory_utilization: 0.9
      model_name_or_path: openbmb/MiniCPM4-8B
      trust_remote_code: true
  extra_params:
    chat_template_kwargs:
      enable_thinking: false
  sampling_params:
    max_tokens: 2048
    temperature: 0.7
    top_p: 0.8
  system_prompt: '' # [!code --]
  system_prompt: 'You are a professional UltraRAG Q&A assistant.' # [!code ++]
prompt:
  template: prompt/qa_boxed.jinja # [!code --]
  template: prompt/qa_simple.jinja # [!code ++]
```

## 4. Effect Demonstration

After configuration is complete, start UltraRAG UI and select LLM Pipeline in the interface to start interaction.

<img src="https://mintcdn.com/ultrarag/IABOmU0X4dsRK1Rp/images/demo/LLM.png?fit=max&auto=format&n=IABOmU0X4dsRK1Rp&q=85&s=259ee913f8a452f055a87d3f1d3b438a" alt="" width="3320" height="2096" data-path="images/demo/LLM.png" />