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Unverified Commit f08c46c0 authored by Ofer Mendelevitch's avatar Ofer Mendelevitch Committed by GitHub
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Vectara - minor update (#7954)

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......@@ -99,6 +99,17 @@ See [Storage guide](https://gpt-index.readthedocs.io/en/latest/how_to/storage.ht
---
#### Managed Index
A managed index is used to represent an index that's managed via an API, exposing API calls to index documents and query documents.
Currently we support the [VectaraIndex](https://github.com/run-llama/llama_index/tree/ca09272af000307762d301c99da46ddc70d3bfd2/llama_index/indices/managed/vectara).
Open to contributions!
See [Managed Index docs](https://gpt-index.readthedocs.io/en/stable/community/integrations/managed_indices.html) for details.
---
#### Vector Stores
Our vector store classes store embeddings and support lookup via similarity search.
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......@@ -14,8 +14,8 @@ Below we show how to use it.
**Vectara Index Construction/Querying**
Use the [Vectara Console](https://console.vectara.com/login) to create a corpus (aka Index), and add an API key for access.
Then put the customer id, corpus id, and API key in your environment as shown below.
First, [sign up](https://vectara.com/integrations/llama_index) and use the Vectara Console to create a corpus (aka Index), and add an API key for access.
Then put the customer id, corpus id, and API key in your environment.
Then construct the Vectara Index and query it as follows:
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......@@ -113,6 +113,7 @@ class VectaraIndex(BaseManagedIndex):
"x-api-key": self._vectara_api_key,
"customer-id": self._vectara_customer_id,
"Content-Type": "application/json",
"X-Source": "llama_index",
}
def _delete_doc(self, doc_id: str) -> bool:
......
......@@ -57,6 +57,7 @@ class VectaraRetriever(BaseRetriever):
"x-api-key": self._index._vectara_api_key,
"customer-id": self._index._vectara_customer_id,
"Content-Type": "application/json",
"X-Source": "llama_index",
}
def _retrieve(
......
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