## Quick Start

### Step 1: Environment Setup
```bash
cd ResearcherBench

# Install dependencies
conda create -n Researchbench python=3.10
conda activate Researchbench
pip install -r requirements.txt

# Set up environment variables
export OPENAI_API_KEY="your-openai-api-key"
export OPENAI_BASE_URL="https://api.openai.com/v1" 
export JINA_API_KEY="your-jina-api-key"  # For web content extraction
```

### Step 2: Prepare Your Data
You should prepare your responses of DARS in the [target format](#format).

```bash
# Add your model responses to data/user_data/
cp your_model_responses.json data/user_data/<model_name>.json

# Edit the model name in environment variables
export MODEL=<model_name>
```

### Step 3: Run Evaluation
```bash
./eval.sh
```

### Step 4: View Results
```bash
# Check results directory
ls results/

# View rubric evaluation summary
cat results/rubric_eval/<model_name>/<model_name>_evaluation_results.txt

# View factual evaluation summary
cat results/factual_eval/<model_name>/factual_analysis.json
```



## Output Files

Results will be saved to:
- **Factual Assessment Result** in `results/factual_eval/<model_name>/factual_analysis.json`, details in `results/factual_eval/<model_name>/factual_results.json`
- **Rubric Assessment Result** in `results/rubric_eval/<model_name>/<model_name>_evaluation_results.txt`, details in `results/rubric_eval/<model_name>/<model_name>_evaluation_results.json`

