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ci(node): run examples in CI (#1796)
This is done as setup for a PR that will fix the OpenAI dependency issue. * [x] FTS examples * [x] Setup mock openai * [x] Ran `npm audit fix` * [x] sentences embeddings test * [x] Double check formatting of docs examples
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@@ -47,9 +47,9 @@ Let's implement `SentenceTransformerEmbeddings` class. All you need to do is imp
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=== "TypeScript"
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```ts
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--8<--- "nodejs/examples/custom_embedding_function.ts:imports"
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--8<--- "nodejs/examples/custom_embedding_function.test.ts:imports"
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--8<--- "nodejs/examples/custom_embedding_function.ts:embedding_impl"
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--8<--- "nodejs/examples/custom_embedding_function.test.ts:embedding_impl"
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```
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@@ -78,7 +78,7 @@ Now you can use this embedding function to create your table schema and that's i
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=== "TypeScript"
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```ts
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--8<--- "nodejs/examples/custom_embedding_function.ts:call_custom_function"
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--8<--- "nodejs/examples/custom_embedding_function.test.ts:call_custom_function"
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```
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!!! note
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@@ -94,8 +94,8 @@ the embeddings at all:
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=== "@lancedb/lancedb"
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```ts
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--8<-- "nodejs/examples/embedding.ts:imports"
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--8<-- "nodejs/examples/embedding.ts:embedding_function"
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--8<-- "nodejs/examples/embedding.test.ts:imports"
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--8<-- "nodejs/examples/embedding.test.ts:embedding_function"
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```
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=== "vectordb (deprecated)"
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@@ -150,7 +150,7 @@ need to worry about it when you query the table:
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.toArray()
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```
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=== "vectordb (deprecated)
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=== "vectordb (deprecated)"
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```ts
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const results = await table
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@@ -51,8 +51,8 @@ LanceDB registers the OpenAI embeddings function in the registry as `openai`. Yo
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=== "TypeScript"
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```typescript
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--8<--- "nodejs/examples/embedding.ts:imports"
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--8<--- "nodejs/examples/embedding.ts:openai_embeddings"
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--8<--- "nodejs/examples/embedding.test.ts:imports"
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--8<--- "nodejs/examples/embedding.test.ts:openai_embeddings"
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```
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=== "Rust"
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@@ -121,12 +121,10 @@ class Words(LanceModel):
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vector: Vector(func.ndims()) = func.VectorField()
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table = db.create_table("words", schema=Words)
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table.add(
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[
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{"text": "hello world"},
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{"text": "goodbye world"}
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]
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)
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table.add([
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{"text": "hello world"},
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{"text": "goodbye world"}
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])
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query = "greetings"
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actual = table.search(query).limit(1).to_pydantic(Words)[0]
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