CnosDB
CnosDB is an open-source distributed time series database with high performance, high compression rate and high ease of use.
Installation and Setupβ
pip install cnos-connector
Connecting to CnosDBβ
You can connect to CnosDB using the SQLDatabase.from_cnosdb()
method.
Syntaxβ
def SQLDatabase.from_cnosdb(url: str = "127.0.0.1:8902",
user: str = "root",
password: str = "",
tenant: str = "cnosdb",
database: str = "public")
Args:
- url (str): The HTTP connection host name and port number of the CnosDB service, excluding "http://" or "https://", with a default value of "127.0.0.1:8902".
- user (str): The username used to connect to the CnosDB service, with a default value of "root".
- password (str): The password of the user connecting to the CnosDB service, with a default value of "".
- tenant (str): The name of the tenant used to connect to the CnosDB service, with a default value of "cnosdb".
- database (str): The name of the database in the CnosDB tenant.
Examplesβ
# Connecting to CnosDB with SQLDatabase Wrapper
from langchain.utilities import SQLDatabase
db = SQLDatabase.from_cnosdb()
# Creating a OpenAI Chat LLM Wrapper
from langchain.chat_models import ChatOpenAI
llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo")
SQL Database Chainβ
This example demonstrates the use of the SQL Chain for answering a question over a CnosDB.
from langchain.utilities import SQLDatabaseChain
db_chain = SQLDatabaseChain.from_llm(llm, db, verbose=True)
db_chain.run(
"What is the average temperature of air at station XiaoMaiDao between October 19, 2022 and Occtober 20, 2022?"
)
> Entering new chain...
What is the average temperature of air at station XiaoMaiDao between October 19, 2022 and Occtober 20, 2022?
SQLQuery:SELECT AVG(temperature) FROM air WHERE station = 'XiaoMaiDao' AND time >= '2022-10-19' AND time < '2022-10-20'
SQLResult: [(68.0,)]
Answer:The average temperature of air at station XiaoMaiDao between October 19, 2022 and October 20, 2022 is 68.0.
> Finished chain.
SQL Database Agentβ
This example demonstrates the use of the SQL Database Agent for answering questions over a CnosDB.
from langchain.agents import create_sql_agent
from langchain.agents.agent_toolkits import SQLDatabaseToolkit
toolkit = SQLDatabaseToolkit(db=db, llm=llm)
agent = create_sql_agent(llm=llm, toolkit=toolkit, verbose=True)
agent.run(
"What is the average temperature of air at station XiaoMaiDao between October 19, 2022 and Occtober 20, 2022?"
)
> Entering new chain...
Action: sql_db_list_tables
Action Input: ""
Observation: air
Thought:The "air" table seems relevant to the question. I should query the schema of the "air" table to see what columns are available.
Action: sql_db_schema
Action Input: "air"
Observation:
CREATE TABLE air (
pressure FLOAT,
station STRING,
temperature FLOAT,
time TIMESTAMP,
visibility FLOAT
)
/*
3 rows from air table:
pressure station temperature time visibility
75.0 XiaoMaiDao 67.0 2022-10-19T03:40:00 54.0
77.0 XiaoMaiDao 69.0 2022-10-19T04:40:00 56.0
76.0 XiaoMaiDao 68.0 2022-10-19T05:40:00 55.0
*/
Thought:The "temperature" column in the "air" table is relevant to the question. I can query the average temperature between the specified dates.
Action: sql_db_query
Action Input: "SELECT AVG(temperature) FROM air WHERE station = 'XiaoMaiDao' AND time >= '2022-10-19' AND time <= '2022-10-20'"
Observation: [(68.0,)]
Thought:The average temperature of air at station XiaoMaiDao between October 19, 2022 and October 20, 2022 is 68.0.
Final Answer: 68.0
> Finished chain.