forked from Archives/langchain
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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docs/ecosystem/zilliz.md
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docs/ecosystem/zilliz.md
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# Zilliz
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This page covers how to use the Zilliz Cloud ecosystem within LangChain.
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Zilliz uses the Milvus integration.
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It is broken into two parts: installation and setup, and then references to specific Milvus wrappers.
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## Installation and Setup
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- Install the Python SDK with `pip install pymilvus`
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## Wrappers
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### VectorStore
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There exists a wrapper around Zilliz indexes, allowing you to use it as a vectorstore,
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whether for semantic search or example selection.
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To import this vectorstore:
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```python
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from langchain.vectorstores import Milvus
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```
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For a more detailed walkthrough of the Miluvs wrapper, see [this notebook](../modules/indexes/vectorstores/examples/zilliz.ipynb)
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@ -55,6 +55,12 @@ The following use cases require specific installs and api keys:
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- _LlamaCpp_:
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- Install requirements with `pip install llama-cpp-python`
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- Download model and convert following [llama.cpp instructions](https://github.com/ggerganov/llama.cpp)
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- _Milvus_:
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- Install requirements with `pip install pymilvus`
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- In order to setup a local cluster, take a look [here](https://milvus.io/docs).
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- _Zilliz_:
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- Install requirements with `pip install pymilvus`
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- To get up and running, take a look [here](https://zilliz.com/doc/quick_start).
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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`.
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