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DOCS: doc-string - langchain.vectorstores.dashvector.DashVector (#13502)
- **Description:** There are several mistakes in the sample code in the doc-string of `DashVector` class, and this pull request aims to correct them. The correction code has been tested against latest version (at the time of creation of this pull request) of: `langchain==0.0.336` `dashvector==1.0.6` . - **Issue:** No issue is created for this. - **Dependencies:** No dependency is required for this change, <!-- - **Tag maintainer:** for a quicker response, tag the relevant maintainer (see below), --> - **Twitter handle:** `zeyanglin` <!-- Please make sure your PR is passing linting and testing before submitting. Run `make format`, `make lint` and `make test` to check this locally. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. It lives in `docs/extras` directory. If no one reviews your PR within a few days, please @-mention one of @baskaryan, @eyurtsev, @hwchase17. -->
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@ -29,15 +29,15 @@ class DashVector(VectorStore):
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Example:
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.. code-block:: python
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from langchain.vectorstores import dashvector
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from langchain.vectorstores import DashVector
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from langchain.embeddings.openai import OpenAIEmbeddings
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import dashvector
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client = dashvector.Client.init(api_key="***")
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client.create("langchain")
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client = dashvector.Client(api_key="***")
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client.create("langchain", dimension=1024)
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collection = client.get("langchain")
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embeddings = OpenAIEmbeddings()
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vectorstore = Dashvector(collection, embeddings.embed_query, "text")
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vectorstore = DashVector(collection, embeddings.embed_query, "text")
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"""
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def __init__(
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