.env.example

# Openai info. All these fields are required for the engine to work.
OPENAI_API_KEY = #This field is required for the engine to work.
ORG_ID =
LLM_MODEL = 'gpt-4-1106-preview' #the openAI llm model that you want to use. possible values: gpt-4-1106-preview.

# All of our SQL generation agents are using different tools to generate SQL queries, in order to limit the number of times that agents can
# use different tools you can set the "AGENT_MAX_ITERATIONS" env variable. By default it is set to 20 iterations.

FINETUNED_MODEL = '' # The id of the LLM model you fine-tuned and you want to use inside DataheraldFinetuningAgent agent.

DH_ENGINE_TIMEOUT = #timeout in seconds for the engine to return a response
UPPER_LIMIT_QUERY_RETURN_ROWS = #The upper limit on number of rows returned from the query engine (equivalent to using LIMIT N in PostgreSQL/MySQL/SQlite). Defauls to 50

#Encryption key for storing DB connection data in Mongo
ENCRYPT_KEY = 


GOLDEN_RECORD_COLLECTION = 'my-golden-records'
#Pinecone info. These fields are required if the vector store used is Pinecone
PINECONE_API_KEY =
PINECONE_ENVIRONMENT =

# Module implementations to be used names for each required component. You can use the default ones or create your own
API_SERVER = "dataherald.api.fastapi.FastAPI"
SQL_GENERATOR = "dataherald.sql_generator.dataherald_sqlagent.DataheraldSQLAgent"
EVALUATOR = "dataherald.eval.simple_evaluator.SimpleEvaluator"
DB = "dataherald.db.mongo.MongoDB"
VECTOR_STORE = 'dataherald.vector_store.chroma.Chroma' 
CONTEXT_STORE = 'dataherald.context_store.default.DefaultContextStore' # Set a context store class, the default one is DefaultContextStore
DB_SCANNER = 'dataherald.db_scanner.sqlalchemy.SqlAlchemyScanner'

# mongo database information
MONGODB_URI = "mongodb://admin:admin@mongodb:27017"
MONGODB_DB_NAME = 'dataherald'
MONGODB_DB_USERNAME = 'admin'
MONGODB_DB_PASSWORD = 'admin'


# The enncryption key is used to encrypt database connection info before storing in Mongo. Please refer to the README on how to set it.
S3_AWS_ACCESS_KEY_ID=
S3_AWS_SECRET_ACCESS_KEY=
ONLY_STORE_CSV_FILES_LOCALLY = False # Set to True if only want to save generated CSV files locally instead of S3. Note that if stored locally they should be treated as ephemeral, i.e., they will disappear when the engine is restarted.