.env-template

# This is a template for the .env file.
# Copy this file to .env and fill in the values you want to override.
# Lines starting with # are comments and are ignored.

#----------------------------------------
# Question Generation LLM Settings
#----------------------------------------
# The base URL for the LLM used for generating questions.
# QUESTION_GENERATION_LLM_URL=http://localhost:11434

# The model name for the question generation LLM.
# QUESTION_GENERATION_LLM_MODEL=gemma3:12b

# The temperature setting for the question generation LLM (0 for deterministic).
# QUESTION_GENERATION_TEMPERATURE=0

#----------------------------------------
# API Settings for RAG Tool (DugBot/BdcBot)
#----------------------------------------
# The base URL for the RAG tool's API.
# API_BASE_URL=https://search-dev.biodatacatalyst.renci.org

# The specific endpoint for the API.
# API_ENDPOINT=/agent/invoke_test

# Timeout in seconds for API requests.
# API_TIMEOUT=120

# Delay in seconds between consecutive API requests.
# API_DELAY=1

#----------------------------------------
# Output Directories
#----------------------------------------
# Directory to save result files.
# RESULTS_DIR=results

# Directory to save dataset files.
# DATASETS_DIR=datasets

#----------------------------------------
# Question Generation Settings
#----------------------------------------
# The default total number of questions to generate.
# DEFAULT_NUM_QUESTIONS=400

# The number of questions for each type.
# Must be a valid JSON string.
# QUESTION_TYPES='{"factual": 100, "analytical": 100, "comparative": 100, "unanswerable": 100}'

#----------------------------------------
# CSV Settings
#----------------------------------------
# The column name for the accession number in the input CSV.
# CSV_ACCESSION_COLUMN=Accession

# The column name for the description in the input CSV.
# CSV_DESCRIPTION_COLUMN=Description

#----------------------------------------
# RAGAS Evaluation LLM Settings
#----------------------------------------
# The provider for the evaluation LLM ("openai" or "ollama").
# RAGAS_EVALUATION_LLM_PROVIDER=openai

# The API key for the evaluation LLM (e.g., for OpenAI).
# RAGAS_EVALUATION_LLM_API_KEY=EMPTY

# The URL for the evaluation LLM (e.g., for a local Ollama instance).
# RAGAS_EVALUATION_LLM_URL=http://localhost:9091/v1

# The model name for the evaluation LLM.
# RAGAS_EVALUATION_LLM_MODEL=google/gemma-3-12b-it

# The temperature for the evaluation LLM.
# RAGAS_EVALUATION_TEMPERATURE=0

# A comma-separated list of RAGAS metrics to use for evaluation.
# RAGAS_METRICS=factual_correctness