docs : add cnosdb to Ecosystem Integrations (#7316)

- Implement a `from_cnosdb` method for the `SQLDatabase` class
  - Write CnosDB documentation and add it to Ecosystem Integrations

docs/extras/ecosystem/integrations/cnosdb.mdx

@@ -0,0 +1,108 @@
+# 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 cnosdb_connector import make_cnosdb_langchain_uri
+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 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 fa of test table that time between November 3,2022 and November 4, 2022?"
+)
+```
+```shell
+> Entering new  chain...
+What is the average fa of test table that time between November 3, 2022 and November 4, 2022?
+SQLQuery:SELECT AVG(fa) FROM test WHERE time >= '2022-11-03' AND time < '2022-11-04'
+SQLResult: [(2.0,)]
+Answer:The average fa of the test table between November 3, 2022, and November 4, 2022, is 2.0.
+> 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 fa of test table that time between November 3, 2022 and November 4, 2022?"
+)
+```
+```shell
+> Entering new  chain...
+Action: sql_db_list_tables
+Action Input: ""
+Observation: test
+Thought:The relevant table is "test". I should query the schema of this table to see the column names.
+Action: sql_db_schema
+Action Input: "test"
+Observation:
+CREATE TABLE test (
+	time TIMESTAMP,
+	fa BIGINT
+)
+
+/*
+3 rows from test table:
+fa	time
+1	2022-11-03T06:20:11
+2	2022-11-03T06:20:11.000000001
+3	2022-11-03T06:20:11.000000002
+*/
+Thought:The relevant column is "fa" in the "test" table. I can now construct the query to calculate the average "fa" between the specified time range.
+Action: sql_db_query
+Action Input: "SELECT AVG(fa) FROM test WHERE time >= '2022-11-03' AND time < '2022-11-04'"
+Observation: [(2.0,)]
+Thought:The average "fa" of the "test" table between November 3, 2022 and November 4, 2022 is 2.0.
+Final Answer: 2.0
+
+> Finished chain.
+```

langchain/sql_database.py

@@ -222,6 +222,47 @@ class SQLDatabase:
         )
         return cls.from_uri(database_uri=uri, engine_args=engine_args, **kwargs)
 
+    @classmethod
+    def from_cnosdb(
+        cls,
+        url: str = "127.0.0.1:8902",
+        user: str = "root",
+        password: str = "",
+        tenant: str = "cnosdb",
+        database: str = "public",
+    ) -> SQLDatabase:
+        """
+        Class method to create an SQLDatabase instance from a CnosDB connection.
+        This method requires the 'cnos-connector' package. If not installed, it
+        can be added using `pip install cnos-connector`.
+
+        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.
+
+        Returns:
+            SQLDatabase: An instance of SQLDatabase configured with the provided
+            CnosDB connection details.
+        """
+        try:
+            from cnosdb_connector import make_cnosdb_langchain_uri
+
+            uri = make_cnosdb_langchain_uri(url, user, password, tenant, database)
+            return cls.from_uri(database_uri=uri)
+        except ImportError:
+            raise ValueError(
+                "cnos-connector package not found, please install with"
+                " `pip install cnos-connector`"
+            )
+
     @property
     def dialect(self) -> str:
         """Return string representation of dialect to use."""