Adding milvus/zilliz into docs (#2686)

Adding Milvus and Zilliz to integrations.md and creating an ecosystems
doc for Zilliz.

Signed-off-by: Filip Haltmayer <filip.haltmayer@zilliz.com>
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Filip Haltmayer 2023-04-10 18:08:41 -07:00 committed by GitHub
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# Zilliz
This page covers how to use the Zilliz Cloud ecosystem within LangChain.
Zilliz uses the Milvus integration.
It is broken into two parts: installation and setup, and then references to specific Milvus wrappers.
## Installation and Setup
- Install the Python SDK with `pip install pymilvus`
## Wrappers
### VectorStore
There exists a wrapper around Zilliz indexes, allowing you to use it as a vectorstore,
whether for semantic search or example selection.
To import this vectorstore:
```python
from langchain.vectorstores import Milvus
```
For a more detailed walkthrough of the Miluvs wrapper, see [this notebook](../modules/indexes/vectorstores/examples/zilliz.ipynb)

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- _LlamaCpp_:
- Install requirements with `pip install llama-cpp-python`
- Download model and convert following [llama.cpp instructions](https://github.com/ggerganov/llama.cpp)
- _Milvus_:
- Install requirements with `pip install pymilvus`
- In order to setup a local cluster, take a look [here](https://milvus.io/docs).
- _Zilliz_:
- Install requirements with `pip install pymilvus`
- To get up and running, take a look [here](https://zilliz.com/doc/quick_start).
If you are using the `NLTKTextSplitter` or the `SpacyTextSplitter`, you will also need to install the appropriate models. For example, if you want to use the `SpacyTextSplitter`, you will need to install the `en_core_web_sm` model with `python -m spacy download en_core_web_sm`. Similarly, if you want to use the `NLTKTextSplitter`, you will need to install the `punkt` model with `python -m nltk.downloader punkt`.