# CnosDB
> [CnosDB](https://github.com/cnosdb/cnosdb) is an open source distributed time series database with high performance, high compression rate and high ease of use.

## Installation and Setup

```python
pip install cnos-connector
```

## Connecting to CnosDB
You can connect to CnosDB using the `SQLDatabase.from_cnosdb()` method.
### Syntax
```python
def SQLDatabase.from_cnosdb(url: str = "127.0.0.1:8902",
                              user: str = "root",
                              password: str = "",
                              tenant: str = "cnosdb",
                              database: str = "public")
```
Args:
1. 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".
2. user (str): The username used to connect to the CnosDB service, with a
                default value of "root".
3. password (str): The password of the user connecting to the CnosDB service,
                with a default value of "".
4. tenant (str): The name of the tenant used to connect to the CnosDB service,
                with a default value of "cnosdb".
5. database (str): The name of the database in the CnosDB tenant.
## Examples
```python
# Connecting to CnosDB with SQLDatabase Wrapper
from langchain import SQLDatabase

db = SQLDatabase.from_cnosdb()
```
```python
# Creating a OpenAI Chat LLM Wrapper
from langchain.chat_models import ChatOpenAI

llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo")
```

### SQL Database Chain
This example demonstrates the use of the SQL Chain for answering a question over a CnosDB.
```python
from langchain 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?"
)
```
```shell
> 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 Agent
This example demonstrates the use of the SQL Database Agent for answering questions over a CnosDB.
```python
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)
```
```python
agent.run(
    "What is the average temperature of air at station XiaoMaiDao between October 19, 2022 and Occtober 20, 2022?"
)
```
```shell
> 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.
```