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############################################################
### Dataset / Eval Items
############################################################
# The JSON list of prompts / golden SQLs and eval attributes for the run
dataset_config: datasets/bat/prompts.json
# Number of trials for multi-trial evaluation
num_trials: 2
### Database Info
# List of paths to the YAML files that provide the database connection details
database_configs:
- datasets/bat/db_configs/sqlite.yaml
# The dialects that the dataset_config will be filtered by. If not provided,
# all dialects found in the dataset_config json file will be used.
dialects:
- sqlite
query_types:
- dql
#
#
############################################################
### Prompt and Generation Modules
############################################################
# The YAML config for the model to be used for generation.
model_config: datasets/model_configs/gemini_2.5_pro_model.yaml
# The prompt generator module id for prompt generation.
prompt_generator: 'SQLGenBasePromptGenerator'
#
#
############################################################
### Optional - Setup / Teardown related configs (Required for testing DDL)
############################################################
# Used for setup / teardown, the directory path to the sql files used for setting up
# / tearing down a database instance. This is required for running DDL
setup_directory: datasets/bat/setup
#
#
############################################################
### Scorer Related Configs - See /scorers directory for each scorer.
############################################################
scorers:
exact_match: null
llmrater:
model_config: datasets/model_configs/gemini_2.5_pro_model.yaml
returned_sql: null
set_match: null
executable_sql: null
exact_match_consistency: null
llm_consistency:
model_config: datasets/model_configs/gemini_2.5_pro_model.yaml
#
#
############################################################
### Reporting Related Configs
############################################################
reporting:
csv:
output_directory: 'results'
# bigquery:
# gcp_project_id: cloud-db-nl2sql
gcs_artifacts:
bucket: 'evalbench-sessions-cloud-db-nl2sql'