| --- |
| base_model: N/A (Dataset Card) |
| datasets: |
| - u-10bei/sft_alfworld_trajectory_dataset_v4 |
| - u-10bei/dbbench_sft_dataset_react_v2 |
| language: |
| - en |
| license: mit |
| tags: |
| - dataset |
| - agent |
| - trajectory |
| - alfworld |
| - dbbench |
| --- |
| |
| # Dataset: pgsyttch/dbv2_and_alfv4 |
|
|
| This repository hosts a combined dataset designed for Supervised Fine-Tuning (SFT) of agent models. |
| It merges two distinct trajectory datasets: ALFWorld (household tasks) and DBBench (database operations). |
|
|
| ## Dataset Description |
|
|
| This dataset is a concatenation of agent trajectories from: |
| - **ALFWorld**: Provides multi-turn interaction data for household tasks. |
| - **DBBench**: Offers multi-turn interaction data for database operation tasks, often in ReAct style. |
|
|
| The data is pre-processed into the OpenAI `messages` format, suitable for training conversational AI agents. |
|
|
| ## Data Fields |
|
|
| The dataset contains a single primary field: |
| - `messages`: A list of dictionaries, where each dictionary represents a turn in a conversation. Each turn has `role` (e.g., `system`, `user`, `assistant`, `tool`) and `content`. |
|
|
| ## Usage (Example for Loading) |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("pgsyttch/dbv2_and_alfv4", split="train") |
| print(dataset[0]) |
| ``` |
|
|
| ## Sources & Terms |
|
|
| Training data originates from: |
| - u-10bei/sft_alfworld_trajectory_dataset_v4 |
| - u-10bei/dbbench_sft_dataset_react_v2 |
|
|
| Dataset License: mit License. This dataset is used and distributed under the terms of the mit License. |
|
|
