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// _ _
// __ _____ __ ___ ___ __ _| |_ ___
// \ \ /\ / / _ \/ _` \ \ / / |/ _` | __/ _ \
// \ V V / __/ (_| |\ V /| | (_| | || __/
// \_/\_/ \___|\__,_| \_/ |_|\__,_|\__\___|
//
// Copyright © 2016 - 2024 Weaviate B.V. All rights reserved.
//
// CONTACT: [email protected]
//
package vectorizer
import (
"context"
"testing"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
// as used in the nearText searcher
func TestVectorizingTexts(t *testing.T) {
type testCase struct {
name string
input []string
expectedJinaAIModel string
jinaAIModel string
}
tests := []testCase{
{
name: "single word",
input: []string{"hello"},
jinaAIModel: "jina-embedding-v2",
expectedJinaAIModel: "jina-embedding-v2",
},
{
name: "multiple words",
input: []string{"hello world, this is me!"},
jinaAIModel: "jina-embedding-v2",
expectedJinaAIModel: "jina-embedding-v2",
},
{
name: "multiple sentences (joined with a dot)",
input: []string{"this is sentence 1", "and here's number 2"},
jinaAIModel: "jina-embedding-v2",
expectedJinaAIModel: "jina-embedding-v2",
},
{
name: "multiple sentences already containing a dot",
input: []string{"this is sentence 1.", "and here's number 2"},
jinaAIModel: "jina-embedding-v2",
expectedJinaAIModel: "jina-embedding-v2",
},
{
name: "multiple sentences already containing a question mark",
input: []string{"this is sentence 1?", "and here's number 2"},
jinaAIModel: "jina-embedding-v2",
expectedJinaAIModel: "jina-embedding-v2",
},
{
name: "multiple sentences already containing an exclamation mark",
input: []string{"this is sentence 1!", "and here's number 2"},
jinaAIModel: "jina-embedding-v2",
expectedJinaAIModel: "jina-embedding-v2",
},
{
name: "multiple sentences already containing comma",
input: []string{"this is sentence 1,", "and here's number 2"},
jinaAIModel: "jina-embedding-v2",
expectedJinaAIModel: "jina-embedding-v2",
},
}
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
client := &fakeClient{}
v := New(client)
settings := &fakeClassConfig{
jinaAIModel: test.jinaAIModel,
}
vec, err := v.Texts(context.Background(), test.input, settings)
require.Nil(t, err)
assert.Equal(t, []float32{0.1, 1.1, 2.1, 3.1}, vec)
assert.Equal(t, test.input, client.lastInput)
assert.Equal(t, client.lastConfig.Model, test.expectedJinaAIModel)
})
}
}
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