|
| 1 | +# WebWalkerQA |
| 2 | + |
| 3 | +MiroFlow's evaluation on the WebWalkerQA benchmark demonstrates web navigation and question-answering capabilities across diverse domains. |
| 4 | + |
| 5 | +More details: [WebWalkerQA on HuggingFace](https://huggingface.co/datasets/MiromindAI/WebWalkerQA) |
| 6 | + |
| 7 | +--- |
| 8 | + |
| 9 | +## Dataset Overview |
| 10 | + |
| 11 | +!!! abstract "Key Dataset Characteristics" |
| 12 | + |
| 13 | + - **Total Tasks**: 680 tasks in the main split |
| 14 | + - **Language**: English |
| 15 | + - **Domains**: Conference, game, academic, business, and more |
| 16 | + - **Task Types**: Web navigation, information retrieval, multi-hop reasoning |
| 17 | + - **Difficulty Levels**: Easy, medium, hard |
| 18 | + - **Evaluation**: Automated comparison with ground truth answers |
| 19 | + |
| 20 | +--- |
| 21 | + |
| 22 | +## Quick Start Guide |
| 23 | + |
| 24 | +### Step 1: Prepare the WebWalkerQA Dataset |
| 25 | + |
| 26 | +```bash title="Download WebWalkerQA Dataset" |
| 27 | +uv run main.py prepare-benchmark get webwalkerqa |
| 28 | +``` |
| 29 | + |
| 30 | +This will create the standardized dataset at `data/webwalkerqa/standardized_data.jsonl`. |
| 31 | + |
| 32 | +### Step 2: Configure API Keys |
| 33 | + |
| 34 | +=== "Claude 3.7 Sonnet" |
| 35 | + |
| 36 | + ```env title=".env Configuration" |
| 37 | + # Search and web scraping |
| 38 | + SERPER_API_KEY="xxx" |
| 39 | + JINA_API_KEY="xxx" |
| 40 | + |
| 41 | + # Code execution |
| 42 | + E2B_API_KEY="xxx" |
| 43 | + |
| 44 | + # LLM (Claude 3.7 Sonnet via OpenRouter) |
| 45 | + OPENROUTER_API_KEY="xxx" |
| 46 | + OPENROUTER_BASE_URL="https://openrouter.ai/api/v1" |
| 47 | + |
| 48 | + # Evaluation and hint generation |
| 49 | + OPENAI_API_KEY="xxx" |
| 50 | + |
| 51 | + # Vision capabilities |
| 52 | + ANTHROPIC_API_KEY="xxx" |
| 53 | + GEMINI_API_KEY="xxx" |
| 54 | + ``` |
| 55 | + |
| 56 | +=== "MiroThinker" |
| 57 | + |
| 58 | + ```env title=".env Configuration" |
| 59 | + # Search and web scraping |
| 60 | + SERPER_API_KEY="xxx" |
| 61 | + JINA_API_KEY="xxx" |
| 62 | + |
| 63 | + # Code execution |
| 64 | + E2B_API_KEY="xxx" |
| 65 | + |
| 66 | + # LLM (MiroThinker via SGLang) |
| 67 | + OAI_MIROTHINKER_API_KEY="dummy_key" |
| 68 | + OAI_MIROTHINKER_BASE_URL="http://localhost:61005/v1" |
| 69 | + |
| 70 | + # Evaluation and final answer extraction |
| 71 | + OPENAI_API_KEY="xxx" |
| 72 | + |
| 73 | + # Vision capabilities |
| 74 | + ANTHROPIC_API_KEY="xxx" |
| 75 | + GEMINI_API_KEY="xxx" |
| 76 | + ``` |
| 77 | + |
| 78 | +### Step 3: Run the Evaluation |
| 79 | + |
| 80 | +```bash title="Run WebWalkerQA Evaluation" |
| 81 | +uv run main.py common-benchmark --config_file_name=agent_webwalkerqa_claude37sonnet output_dir="logs/webwalkerqa/$(date +"%Y%m%d_%H%M")" |
| 82 | +``` |
| 83 | + |
| 84 | +!!! tip "Progress Monitoring and Resume" |
| 85 | + To check the progress while running: |
| 86 | + |
| 87 | + ```bash title="Check Progress" |
| 88 | + ls -lh logs/webwalkerqa/YOUR_RUN_DIR/ |
| 89 | + ``` |
| 90 | + |
| 91 | + If you need to resume an interrupted evaluation, specify the same output directory: |
| 92 | + |
| 93 | + ```bash title="Resume Evaluation" |
| 94 | + uv run main.py common-benchmark --config_file_name=agent_webwalkerqa_claude37sonnet output_dir=${PATH_TO_LOG} |
| 95 | + ``` |
| 96 | + |
| 97 | +Results are automatically generated in the output directory: |
| 98 | +- `benchmark_results.jsonl` - Detailed results for each task |
| 99 | +- `benchmark_results_pass_at_1_accuracy.txt` - Summary accuracy statistics |
| 100 | + |
| 101 | +--- |
| 102 | + |
| 103 | +## Usage Examples |
| 104 | + |
| 105 | +```bash title="Limited Task Testing" |
| 106 | +# Test with 10 tasks only |
| 107 | +uv run main.py common-benchmark --config_file_name=agent_webwalkerqa_claude37sonnet benchmark.execution.max_tasks=10 output_dir="logs/webwalkerqa/test" |
| 108 | +``` |
| 109 | + |
| 110 | +```bash title="Custom Concurrency" |
| 111 | +# Run with 10 concurrent tasks |
| 112 | +uv run main.py common-benchmark --config_file_name=agent_webwalkerqa_claude37sonnet benchmark.execution.max_concurrent=10 output_dir="logs/webwalkerqa/$(date +"%Y%m%d_%H%M")" |
| 113 | +``` |
| 114 | + |
| 115 | +```bash title="Using MiroThinker Model" |
| 116 | +uv run main.py common-benchmark --config_file_name=agent_webwalkerqa_mirothinker output_dir="logs/webwalkerqa/$(date +"%Y%m%d_%H%M")" |
| 117 | +``` |
| 118 | + |
| 119 | +--- |
| 120 | + |
| 121 | +## Available Agent Configurations |
| 122 | + |
| 123 | +| Agent Configuration | Model | Use Case | |
| 124 | +|-------------------|-------|----------| |
| 125 | +| `agent_webwalkerqa_claude37sonnet` | Claude 3.7 Sonnet | Recommended for best performance | |
| 126 | +| `agent_webwalkerqa_mirothinker` | MiroThinker | For local deployment | |
| 127 | + |
| 128 | +--- |
| 129 | + |
| 130 | +!!! info "Documentation Info" |
| 131 | + **Last Updated:** October 2025 · **Doc Contributor:** Team @ MiroMind AI |
| 132 | + |
0 commit comments