| --- |
| license: apache-2.0 |
| task_categories: |
| - question-answering |
| - text-generation |
| - summarization |
| language: |
| - zh |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # PRGB Benchmark |
| PRGB (Placeholder RAG Benchmark) is a benchmark tool focused on evaluating document faithfulness and external knowledge utilization efficiency in Retrieval-Augmented Generation (RAG) systems. |
| It comprehensively evaluates model performance through progressive dimensions such as multi-level filtering and cross-entity reasoning, using placeholders with noise-injected datasets to help researchers and developers analyze the performance of mainstream RAG models in complex scenarios. |
|
|
| For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to [PRGB GitHub](https://github.com/AQ-MedAI/PRGB) and PRGB Paper at [🤗 HuggingFace](https://huggingface.co/papers/2507.22927). |
|
|
| # Key Features |
| 🎯 Multi-Model Support: Supports multiple large language models with local VLLM inference |
|
|
| 📊 Standardized Evaluation: Provides unified evaluation metrics and processes |
|
|
| 🔧 Flexible Configuration: Supports noise configuration, placeholder configuration, and other parameter adjustments |
|
|
| 🌍 Multi-Language Support: Supports Chinese and English dataset evaluation |
|
|
| 📈 Detailed Reports: Generates comprehensive evaluation results and score reports |
|
|
| ## PRGB's Leaderboard |
|
|
| In our experiments, we uniformly set the following configurations: |
| `noise_config: '{"noise_doc_level1":4,"noise_doc_level2":4,"noise_doc_level3":1}'`, `num_iterations: 3`, and `shuffle: True`. |
|
|
| ### Chinese Dataset Performance Comparison |
|
|
| The table below presents the performance of various state-of-the-art models on Chinese datasets, sorted by Overall score from highest to lowest. **Bold** values indicate the best experimental results, and ***italic bold*** values indicate the second-best experimental results. |
|
|
| | Models | Overall | Multi-Level Filter | Composition | Reasoning | |
| | ----------------------------- | ------- | ------------------- | ------------------- | --------------- | |
| | `Gemini-2.5-pro-preview` | 87.33 | **97.92** | **94.20** | 70.18 | |
| | `DeepSeek-R1-0528` | 86.68 | 96.17 | ***93.69*** | **72.79** | |
| | `Claude-3.7-sonnet` | 85.74 | ***97.62*** | 90.59 | **70.39** | |
| | `Gemini-2.5-flash-preview` | 81.85 | 93.92 | 88.54 | 63.86 | |
| | `Qwen3-235B-A22B` | 80.76 | 94.92 | 88.18 | 60.23 | |
| | `Qwen3-30B-A3B` | 80.45 | 95.87 | 86.11 | 61.42 | |
| | `Deepseek-V3(241226)` | 77.54 | 94.58 | 81.00 | 60.32 | |
| | `Qwen3-235B-A22B w/o think` | 75.20 | 91.50 | 79.67 | 57.14 | |
| | `Qwen-2.5-MAX` | 74.43 | 93.25 | 78.28 | 55.37 | |
| | `Qwen3-30B-A3B w/o think` | 71.05 | 91.08 | 72.22 | 54.76 | |
| | `Gemma3_27b` | 70.24 | 73.09 | 92.21 | 50.24 | |
| | `Qwen3_32B` | 69.69 | 89.75 | 75.74 | 46.70 | |
| | `Hunyuan-80B-A13B` | 68.84 | 93.50 | 68.94 | 50.64 | |
| | `GPT4.1` | 66.26 | 89.75 | 71.95 | 41.27 | |
| | `Qwen2.5_72B` | 64.87 | 92.92 | 64.99 | 44.14 | |
| | `GPT4o-1120` | 64.58 | 88.50 | 70.21 | 39.35 | |
| | `Gemma3_12b` | 64.10 | 60.20 | 89.92 | 50.52 | |
| | `Qwen3_8B` | 63.04 | 86.87 | 67.49 | 39.47 | |
| | `Qwen3_32B w/o think` | 60.73 | 59.53 | 89.50 | 41.30 | |
| | `Qwen2.5_32B` | 58.76 | 92.00 | 51.33 | 44.60 | |
| | `Qwen2.5_14B` | 55.94 | 89.42 | 52.69 | 35.87 | |
| | `Qwen2.5_7B` | 49.31 | 83.29 | 47.47 | 26.92 | |
| | `Qwen3_8B w/o think` | 50.02 | 47.83 | 83.96 | 28.17 | |
| | `Gemma3_4b` | 47.67 | 37.41 | 78.33 | 39.26 | |
|
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|
|
|
|
| ## Installation |
|
|
| ### Requirements |
|
|
| - Python 3.7+ |
| - CUDA (if using GPU inference) |
|
|
| ### Installation Steps |
|
|
| 1. Clone the repository |
|
|
| ```bash |
| git clone https://github.com/Alipay-Med/PRGB.git |
| cd PRGB |
| ``` |
|
|
| 2. Install dependencies |
|
|
| ```bash |
| pip install -r requirements.txt |
| ``` |
|
|
| 3. Verify installation |
|
|
| ```bash |
| python test_imports.py |
| ``` |
|
|
| ## Usage |
|
|
| ### Verify Imports |
|
|
| Before running evaluations, it's recommended to verify that imports work correctly: |
|
|
| ```bash |
| python test_imports.py |
| ``` |
|
|
| ### Three Ways to Run Evaluation |
|
|
| #### Method 1: Using Makefile (Recommended) |
|
|
| If you only need to modify the model path, using Makefile is recommended |
|
|
| ```bash |
| # View all available commands |
| make help |
| |
| # Set environment variables and run evaluation |
| export EVAL_MODEL_PATH=/path/to/your/model |
| make eval |
| |
| # Or set environment variables in one line |
| EVAL_MODEL_PATH=/path/to/your/model make eval |
| |
| # Chinese evaluation (using data/zh.jsonl) |
| # Chinese evaluation with inference mode (using data/zh.jsonl) |
| EVAL_MODEL_PATH=/path/to/your/model make eval-ch-infer |
| |
| # English evaluation (using data/en.jsonl) |
| # English evaluation with inference mode (using data/en.jsonl) |
| EVAL_MODEL_PATH=/path/to/your/model make eval-en-infer |
| |
| # Test evaluation (no real model needed) |
| make eval-test |
| |
| # Export error samples (requires evaluation result file path) |
| EVAL_RESULT_FILE=results/model_eval_result.jsonl make export-errors |
| ``` |
|
|
| #### Method 2: Using Shell Script |
|
|
| If you need to modify other parameters, using the shell is recommended. |
|
|
| ```bash |
| # Run with default parameters (requires model path) |
| ./run_eval.sh /path/to/your/model |
| |
| # Pass all parameters |
| ./run_eval.sh /path/to/your/model data/zh.jsonl Qwen3_infer ./results |
| ``` |
|
|
| #### Method 3: Using Python Command |
|
|
| ```bash |
| # Basic usage |
| python eval.py \ |
| --model-name "Qwen3" \ |
| --model-path "/path/to/your/model" \ |
| --data-path "tests/test.jsonl" \ |
| --output-path "./results" |
| |
| # Complete parameter example |
| python eval.py \ |
| --model-name "Qwen3" \ |
| --model-path "/path/to/your/model" \ |
| --data-path "your_data.jsonl" \ |
| --output-path "./results" \ |
| --batch-size 16 \ |
| --temperature 0.7 \ |
| --noise-config '{"noise_doc_level1":4,"noise_doc_level2":4,"noise_doc_level3":1}' \ |
| --custom_config "config/default_prompt_config.json" \ |
| --shuffle True \ |
| --num-iterations 3 \ |
| --verbose |
| ``` |
|
|
