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docs: minor fix of the pgvector provider spec description (#2847)
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# What does this PR do?
<!-- Provide a short summary of what this PR does and why. Link to
relevant issues if applicable. -->

minor update of the pgvector doc, changing 'faiss' to 'pgvector'

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

## Test Plan
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summaries. *Provide clear instructions so the plan can be easily
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Jeremy Bonghwan Choi 2025-07-22 15:10:35 +10:00 • committed by GitHub
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2
docs/source/providers/vector_io/remote_pgvector.md
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@ -17,7 +17,7 @@ That means you'll get fast and efficient vector retrieval.
To use PGVector in your Llama Stack project, follow these steps:
1. Install the necessary dependencies.
2. Configure your Llama Stack project to use Faiss.
2. Configure your Llama Stack project to use pgvector. (e.g. remote::pgvector).
3. Start storing and querying vectors.
## Installation

2
llama_stack/providers/registry/vector_io.py
View file

@ -395,7 +395,7 @@ That means you'll get fast and efficient vector retrieval.
To use PGVector in your Llama Stack project, follow these steps:
1. Install the necessary dependencies.
2. Configure your Llama Stack project to use Faiss.
2. Configure your Llama Stack project to use pgvector. (e.g. remote::pgvector).
3. Start storing and querying vectors.
## Installation