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[docs] small fixes (#308)

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Closes #288 and #287
This commit is contained in:
Leon Yee
2023-07-14 12:46:31 -07:00
committed by GitHub
parent 6dfe7fabc2
commit a8a50591d7
2 changed files with 7 additions and 3 deletions
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4
docs/src/embedding.md
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@@ -46,7 +46,7 @@ You can also use an external API like OpenAI to generate embeddings
def embed_func(c): def embed_func(c):
rs = openai.Embedding.create(input=c, engine="text-embedding-ada-002") rs = openai.Embedding.create(input=c, engine="text-embedding-ada-002")
return [record["embedding"] for record in rs["data"]] return [record["embedding"] for record in rs["data"]]
``` ```
=== "Javascript" === "Javascript"
@@ -126,7 +126,7 @@ belong in the same latent space and your results will be nonsensical.
=== "Javascript" === "Javascript"
```javascript ```javascript
const results = await table const results = await table
.search('What's the best pizza topping?') .search("What's the best pizza topping?")
.limit(10) .limit(10)
.execute() .execute()
``` ```

6
docs/src/examples/transformerjs_embedding_search_nodejs.md
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@@ -1,4 +1,8 @@
# Vector embedding search using TransformersJS and NodeJS # Vector embedding search using TransformersJS
## Embed and query data from LacneDB using TransformersJS
<img id="splash" width="400" alt="transformersjs" src="https://github.com/lancedb/lancedb/assets/43097991/88a31e30-3d6f-4eef-9216-4b7c688f1b4f">
This example shows how to use the [transformers.js](https://github.com/xenova/transformers.js) library to perform vector embedding search using LanceDB's Javascript API. This example shows how to use the [transformers.js](https://github.com/xenova/transformers.js) library to perform vector embedding search using LanceDB's Javascript API.