--- license: apache-2.0 task_categories: - text-generation language: - en configs: - config_name: simple data_files: "simple.parquet" default: true - config_name: parallel data_files: "parallel.parquet" - config_name: multiple data_files: "multiple.parquet" - config_name: parallel_multiple data_files: "parallel_multiple.parquet" --- # [PARSED] BFCL V1 AST (non-live python) The data in this dataset is a _**subset**_ of the original [gorilla-llm/Berkeley-Function-Calling-Leaderboard](https://huggingface.co/datasets/gorilla-llm/Berkeley-Function-Calling-Leaderboard) | Subset name | multi-turn | parallel | multiple definition | Last turn type | number of dataset | | ----------------- | ---------- | -------- | ------------------- | -------------- | ----------------- | | simple | no | no | no | tool_calls | 400 | | multiple | no | no | yes | tool_calls | 200 | | parallel | no | yes | no | tool_calls | 200 | | parallel_multiple | no | yes | yes | tool_calls | 200 | This is a re-parsing formatting dataset for Python AST parts from V1 of the official dataset of BFCL. --- **Simple (400 AST)**: Single function evaluation contains the simplest but most commonly seen format, where the user supplies a single JSON function document, with one and only one function call being invoked. **Multiple Function (200 AST)**: Multiple function category contains a user question that only invokes one function call out of 2 to 4 JSON function documentations. The model needs to be capable of selecting the best function to invoke according to user-provided context. **Parallel Function (200 AST)**: Parallel function is defined as invoking multiple function calls in parallel with one user query. The model needs to digest how many function calls need to be made and the question to model can be a single sentence or multiple sentence. **Parallel Multiple Function (200 AST)**: Parallel Multiple function is the combination of parallel function and multiple function. In other words, the model is provided with multiple function documentation, and each of the corresponding function calls will be invoked zero or more times. ## Load the dataset ```python from datasets import load_dataset ds = load_dataset("minpeter/bfcl-v1-non-live-ast-parsed", data_files="*.parquet") print(ds) # DatasetDict({ # train: Dataset({ # features: ['messages', 'tools', 'extra'], # num_rows: 1000 # }) # }) ```