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6e1000dc8d
This change makes the ecosystem integrations cnosdb documentation more realistic and easy to understand. - change examples of question and table - modify typo and format
111 lines
3.8 KiB
Plaintext
111 lines
3.8 KiB
Plaintext
# CnosDB
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> [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.
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## Installation and Setup
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```python
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pip install cnos-connector
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```
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## Connecting to CnosDB
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You can connect to CnosDB using the `SQLDatabase.from_cnosdb()` method.
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### Syntax
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```python
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def SQLDatabase.from_cnosdb(url: str = "127.0.0.1:8902",
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user: str = "root",
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password: str = "",
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tenant: str = "cnosdb",
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database: str = "public")
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```
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Args:
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1. url (str): The HTTP connection host name and port number of the CnosDB
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service, excluding "http://" or "https://", with a default value
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of "127.0.0.1:8902".
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2. user (str): The username used to connect to the CnosDB service, with a
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default value of "root".
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3. password (str): The password of the user connecting to the CnosDB service,
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with a default value of "".
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4. tenant (str): The name of the tenant used to connect to the CnosDB service,
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with a default value of "cnosdb".
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5. database (str): The name of the database in the CnosDB tenant.
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## Examples
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```python
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# Connecting to CnosDB with SQLDatabase Wrapper
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from langchain import SQLDatabase
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db = SQLDatabase.from_cnosdb()
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```
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```python
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# Creating a OpenAI Chat LLM Wrapper
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from langchain.chat_models import ChatOpenAI
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llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo")
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```
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### SQL Database Chain
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This example demonstrates the use of the SQL Chain for answering a question over a CnosDB.
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```python
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from langchain import SQLDatabaseChain
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db_chain = SQLDatabaseChain.from_llm(llm, db, verbose=True)
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db_chain.run(
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"What is the average temperature of air at station XiaoMaiDao between October 19, 2022 and Occtober 20, 2022?"
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)
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```
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```shell
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> Entering new chain...
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What is the average temperature of air at station XiaoMaiDao between October 19, 2022 and Occtober 20, 2022?
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SQLQuery:SELECT AVG(temperature) FROM air WHERE station = 'XiaoMaiDao' AND time >= '2022-10-19' AND time < '2022-10-20'
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SQLResult: [(68.0,)]
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Answer:The average temperature of air at station XiaoMaiDao between October 19, 2022 and October 20, 2022 is 68.0.
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> Finished chain.
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```
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### SQL Database Agent
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This example demonstrates the use of the SQL Database Agent for answering questions over a CnosDB.
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```python
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from langchain.agents import create_sql_agent
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from langchain.agents.agent_toolkits import SQLDatabaseToolkit
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toolkit = SQLDatabaseToolkit(db=db, llm=llm)
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agent = create_sql_agent(llm=llm, toolkit=toolkit, verbose=True)
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```
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```python
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agent.run(
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"What is the average temperature of air at station XiaoMaiDao between October 19, 2022 and Occtober 20, 2022?"
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)
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```
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```shell
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> Entering new chain...
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Action: sql_db_list_tables
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Action Input: ""
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Observation: air
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Thought:The "air" table seems relevant to the question. I should query the schema of the "air" table to see what columns are available.
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Action: sql_db_schema
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Action Input: "air"
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Observation:
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CREATE TABLE air (
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pressure FLOAT,
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station STRING,
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temperature FLOAT,
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time TIMESTAMP,
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visibility FLOAT
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)
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/*
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3 rows from air table:
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pressure station temperature time visibility
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75.0 XiaoMaiDao 67.0 2022-10-19T03:40:00 54.0
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77.0 XiaoMaiDao 69.0 2022-10-19T04:40:00 56.0
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76.0 XiaoMaiDao 68.0 2022-10-19T05:40:00 55.0
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*/
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Thought:The "temperature" column in the "air" table is relevant to the question. I can query the average temperature between the specified dates.
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Action: sql_db_query
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Action Input: "SELECT AVG(temperature) FROM air WHERE station = 'XiaoMaiDao' AND time >= '2022-10-19' AND time <= '2022-10-20'"
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Observation: [(68.0,)]
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Thought:The average temperature of air at station XiaoMaiDao between October 19, 2022 and October 20, 2022 is 68.0.
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Final Answer: 68.0
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> Finished chain.
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```
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