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Create a seperate providers/db2.mdx for the check.

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docs/docs/integrations/providers/db2.mdx Normal file
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# IBM DB2
## Vector stores
### IBM DB2 Vector Store and Vector Search
The IBM DB2 relational database v12.1.2 and above offers the abilities of vector store and vector search. Installation of `langchain-db2` package will give Langchain users the support of DB2 vector store and vector search.
See detailed usage example in Jupyter Notebook [/docs/integrations/vectorstores/db2.ipynb](/docs/integrations/vectorstores/db2.ipynb).
Installation: This is a seperate package for vector store feature only and can be run without the `langchain-ibm` package.
```python
pip install langchain-db2
```
Usage:
```
from langchain_db2 import db2vs
from langchain_db2.db2vs import DB2VS
```

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docs/docs/integrations/providers/ibm.mdx
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@ -77,20 +77,3 @@ See a [usage example](/docs/integrations/tools/ibm_watsonx).
```python
from langchain_ibm import WatsonxToolkit
```
## Vector stores
### IBM DB2 Vector Store and Vector Search
The IBM DB2 relational database v12.1.2+ offer the
See detailed usage example in Jupyter Notebook [/docs/integrations/vectorstores/db2.ipynb](/docs/integrations/vectorstores/db2.ipynb).
Installation: This is a seperate package for vector store feature only and can be run without the `langchain-ibm` package.
```python
pip install langchain-db2
```
Usage:
```
from langchain_db2 import db2vs
from langchain_db2.db2vs import DB2VS
```

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docs/docs/integrations/vectorstores/db2.ipynb
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"id": "452c4bd6",
"metadata": {},
"source": [
"LangChain's DB2 integration (langchain-db2) provides vector store and vector search capabilities for working with IBM relational database DB2 version v12.1.2 and above, distributed under the MIT license. Users can use the provided implementations as-is or customize them for specific needs.\n",
"LangChain's DB2 integration (langchain-db2) provides vector store and vector search capabilities from IBM relational database DB2 version v12.1.2 and above. It is distributed under the MIT license, users can use the provided implementations as-is or customize them for specific needs.\n",
" \n",
" Key features include:\n",
"\n",
" * Vector storage with metadata\n",