### Quick Start
#### 1. Install `FlagEmbedding` and `faiss`
```bash
pip3 install FlagEmbedding
pip3 install faiss-cpu
```

#### 2. Preprocess Train and Eval dataset
```bash
# Run the preprocessing script
python examples/data_preprocess/Process_ToolCall_Train_FormatData_closed.py
python examples/data_preprocess/Process_ToolCall_Train_FormatData_open.py

python examples/data_preprocess/Process_ToolCall_Test_FormatData_closed.py
python examples/data_preprocess/Process_ToolCall_Test_FormatData_open.py
```

#### 3. Build google search
```bash
# Replace the search API key with your own.
vim meta_researcher/tool/tools/search_engine/base_search.py

# Select the search engine interface to use.
vim train_bash/MutiNode_ToolCall_qwq32B_grpo_researcher_gpqa_tool.sh
export OPTIONAL_SEARCH_ENGINE = "Search engine interface you want to use"
```

#### 4. Run GRPO training with Qwen2.5-1.5B-Instruct
```bash
# Run the GRPO training script
cd train_bash
bash MutiNode_ToolCall_qwq32B_grpo_researcher_gpqa_tool.sh
```