Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

docs: add redis examples, lower implOptions #66

Open
wants to merge 2 commits into
base: main
Choose a base branch
from
Open
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Original file line number Diff line number Diff line change
@@ -0,0 +1,83 @@
/*
* Copyright 2025 CloudWeGo Authors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package main
N3kox marked this conversation as resolved.
Show resolved Hide resolved

import (
"context"
"fmt"

"github.com/redis/go-redis/v9"
)

const (
keyPrefix = "eino_doc_customized:" // keyPrefix should be the prefix of keys you write to redis and want to retrieve.
indexName = "test_index_customized" // indexName should be used in redis retriever.

customContentFieldName = "my_content_field"
customContentVectorFieldName = "my_vector_content_field"
customExtraFieldName = "extra_field_number"
)

func createIndex() {
ctx := context.Background()
client := redis.NewClient(&redis.Options{
Addr: "localhost:6379",
})

// below use FT.CREATE to create an index.
// see: https://redis.io/docs/latest/commands/ft.create/

// schemas should match DocumentToHashes configured in IndexerConfig.
schemas := []*redis.FieldSchema{
{
FieldName: customContentFieldName,
FieldType: redis.SearchFieldTypeText,
},
{
FieldName: customContentVectorFieldName,
FieldType: redis.SearchFieldTypeVector,
VectorArgs: &redis.FTVectorArgs{
// FLAT index: https://redis.io/docs/latest/develop/interact/search-and-query/advanced-concepts/vectors/#flat-index
// Choose the FLAT index when you have small datasets (< 1M vectors) or when perfect search accuracy is more important than search latency.
FlatOptions: &redis.FTFlatOptions{
Type: "FLOAT32", // BFLOAT16 / FLOAT16 / FLOAT32 / FLOAT64. BFLOAT16 and FLOAT16 require v2.10 or later.
Dim: 1024, // keeps same with dimensions of Embedding
DistanceMetric: "COSINE", // L2 / IP / COSINE
},
// HNSW index: https://redis.io/docs/latest/develop/interact/search-and-query/advanced-concepts/vectors/#hnsw-index
// HNSW, or hierarchical navigable small world, is an approximate nearest neighbors algorithm that uses a multi-layered graph to make vector search more scalable.
HNSWOptions: nil,
},
},
{
FieldName: customExtraFieldName,
FieldType: redis.SearchFieldTypeNumeric,
},
}

options := &redis.FTCreateOptions{
OnHash: true,
Prefix: []any{keyPrefix},
}

result, err := client.FTCreate(ctx, indexName, options, schemas...).Result()
if err != nil {
panic(err)
}

fmt.Println(result) // OK
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,119 @@
/*
* Copyright 2025 CloudWeGo Authors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package main
N3kox marked this conversation as resolved.
Show resolved Hide resolved

import (
"context"
"encoding/json"
"fmt"
"os"
"strconv"
"strings"

ri "github.com/cloudwego/eino-ext/components/indexer/redis"
"github.com/cloudwego/eino/components/embedding"
"github.com/cloudwego/eino/schema"
"github.com/redis/go-redis/v9"
)

// This example is related to example in https://github.com/cloudwego/eino-ext/tree/main/components/retriever/redis/examples/customized_retriever

func main() {
ctx := context.Background()
client := redis.NewClient(&redis.Options{
Addr: "localhost:6379",
})

b, err := os.ReadFile("./examples/embeddings.json")
if err != nil {
panic(err)
}

var dense [][]float64
if err = json.Unmarshal(b, &dense); err != nil {
panic(err)
}

indexer, err := ri.NewIndexer(ctx, &ri.IndexerConfig{
Client: client,
KeyPrefix: keyPrefix,
DocumentToHashes: func(ctx context.Context, doc *schema.Document) (*ri.Hashes, error) {
f2v := map[string]ri.FieldValue{
// write doc.Content to field "my_content_field"
// write vector of doc.Content to field "my_vector_content_field"
customContentFieldName: {
Value: doc.Content,
EmbedKey: customContentVectorFieldName,
Stringify: nil,
},
// write doc.Metadata["ext"] to field "extra_field_number"
customExtraFieldName: {
Value: doc.MetaData["ext"],
},
}

return &ri.Hashes{
Key: doc.ID + "_suffix",
Field2Value: f2v,
}, nil
},
BatchSize: 5,
Embedding: &mockEmbedding{dense}, // replace with real embedding
})
if err != nil {
panic(err)
}

contents := `1. Eiffel Tower: Located in Paris, France, it is one of the most famous landmarks in the world, designed by Gustave Eiffel and built in 1889.
2. The Great Wall: Located in China, it is one of the Seven Wonders of the World, built from the Qin Dynasty to the Ming Dynasty, with a total length of over 20000 kilometers.
3. Grand Canyon National Park: Located in Arizona, USA, it is famous for its deep canyons and magnificent scenery, which are cut by the Colorado River.
4. The Colosseum: Located in Rome, Italy, built between 70-80 AD, it was the largest circular arena in the ancient Roman Empire.
5. Taj Mahal: Located in Agra, India, it was completed by Mughal Emperor Shah Jahan in 1653 to commemorate his wife and is one of the New Seven Wonders of the World.
6. Sydney Opera House: Located in Sydney Harbour, Australia, it is one of the most iconic buildings of the 20th century, renowned for its unique sailboat design.
7. Louvre Museum: Located in Paris, France, it is one of the largest museums in the world with a rich collection, including Leonardo da Vinci's Mona Lisa and Greece's Venus de Milo.
8. Niagara Falls: located at the border of the United States and Canada, consisting of three main waterfalls, its spectacular scenery attracts millions of tourists every year.
9. St. Sophia Cathedral: located in Istanbul, Türkiye, originally built in 537 A.D., it used to be an Orthodox cathedral and mosque, and now it is a museum.
10. Machu Picchu: an ancient Inca site located on the plateau of the Andes Mountains in Peru, one of the New Seven Wonders of the World, with an altitude of over 2400 meters.`

var docs []*schema.Document
for idx, str := range strings.Split(contents, "\n") {
docs = append(docs, &schema.Document{
ID: strconv.FormatInt(int64(idx+1), 10),
Content: str,
MetaData: map[string]any{
"ext": 10001 + idx, // additional field to write
},
})
}

ids, err := indexer.Store(ctx, docs)
if err != nil {
panic(err)
}

fmt.Println(ids) // [1 2 3 4 5 6 7 8 9 10]
// redis hashes keys are eino_doc_customized:1, eino_doc_customized:2 ...
}

// mockEmbedding returns embeddings with 1024 dimensions
type mockEmbedding struct {
dense [][]float64
}

func (m mockEmbedding) EmbedStrings(ctx context.Context, texts []string, opts ...embedding.Option) ([][]float64, error) {
return m.dense, nil
}
78 changes: 78 additions & 0 deletions components/indexer/redis/examples/default_indexer/create_index.go
Original file line number Diff line number Diff line change
@@ -0,0 +1,78 @@
/*
* Copyright 2025 CloudWeGo Authors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package main
N3kox marked this conversation as resolved.
Show resolved Hide resolved

import (
"context"
"fmt"

"github.com/redis/go-redis/v9"
)

func createIndex() {
ctx := context.Background()
client := redis.NewClient(&redis.Options{
Addr: "localhost:6379",
})

// below use FT.CREATE to create an index.
// see: https://redis.io/docs/latest/commands/ft.create/

keyPrefix := "eino_doc:" // keyPrefix should be the prefix of keys you write to redis and want to retrieve.
indexName := "test_index" // indexName should be used in redis retriever.

// schemas should match DocumentToHashes configured in IndexerConfig.
schemas := []*redis.FieldSchema{
{
FieldName: "content",
FieldType: redis.SearchFieldTypeText,
Weight: 1,
},
{
FieldName: "vector_content",
FieldType: redis.SearchFieldTypeVector,
VectorArgs: &redis.FTVectorArgs{
// FLAT index: https://redis.io/docs/latest/develop/interact/search-and-query/advanced-concepts/vectors/#flat-index
// Choose the FLAT index when you have small datasets (< 1M vectors) or when perfect search accuracy is more important than search latency.
FlatOptions: &redis.FTFlatOptions{
Type: "FLOAT32", // BFLOAT16 / FLOAT16 / FLOAT32 / FLOAT64. BFLOAT16 and FLOAT16 require v2.10 or later.
Dim: 1024, // keeps same with dimensions of Embedding
DistanceMetric: "COSINE", // L2 / IP / COSINE
},
// HNSW index: https://redis.io/docs/latest/develop/interact/search-and-query/advanced-concepts/vectors/#hnsw-index
// HNSW, or hierarchical navigable small world, is an approximate nearest neighbors algorithm that uses a multi-layered graph to make vector search more scalable.
HNSWOptions: nil,
},
},
{
FieldName: "extra_field_number",
FieldType: redis.SearchFieldTypeNumeric,
},
}

options := &redis.FTCreateOptions{
OnHash: true,
Prefix: []any{keyPrefix},
}

result, err := client.FTCreate(ctx, indexName, options, schemas...).Result()
if err != nil {
panic(err)
}

fmt.Println(result) // OK
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,97 @@
/*
* Copyright 2025 CloudWeGo Authors
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package main
N3kox marked this conversation as resolved.
Show resolved Hide resolved

import (
"context"
"encoding/json"
"fmt"
"os"
"strconv"
"strings"

ri "github.com/cloudwego/eino-ext/components/indexer/redis"
"github.com/cloudwego/eino/components/embedding"
"github.com/cloudwego/eino/schema"
"github.com/redis/go-redis/v9"
)

// This example is related to example in https://github.com/cloudwego/eino-ext/tree/main/components/retriever/redis/examples/default_retriever

func main() {
ctx := context.Background()
client := redis.NewClient(&redis.Options{
Addr: "localhost:6379",
})

b, err := os.ReadFile("./examples/embeddings.json")
if err != nil {
panic(err)
}

var dense [][]float64
if err = json.Unmarshal(b, &dense); err != nil {
panic(err)
}

indexer, err := ri.NewIndexer(ctx, &ri.IndexerConfig{
Client: client,
KeyPrefix: "eino_doc:",
DocumentToHashes: nil, // use default convert method
BatchSize: 5,
Embedding: &mockEmbedding{dense}, // replace with real embedding
})
if err != nil {
panic(err)
}

contents := `1. Eiffel Tower: Located in Paris, France, it is one of the most famous landmarks in the world, designed by Gustave Eiffel and built in 1889.
2. The Great Wall: Located in China, it is one of the Seven Wonders of the World, built from the Qin Dynasty to the Ming Dynasty, with a total length of over 20000 kilometers.
3. Grand Canyon National Park: Located in Arizona, USA, it is famous for its deep canyons and magnificent scenery, which are cut by the Colorado River.
4. The Colosseum: Located in Rome, Italy, built between 70-80 AD, it was the largest circular arena in the ancient Roman Empire.
5. Taj Mahal: Located in Agra, India, it was completed by Mughal Emperor Shah Jahan in 1653 to commemorate his wife and is one of the New Seven Wonders of the World.
6. Sydney Opera House: Located in Sydney Harbour, Australia, it is one of the most iconic buildings of the 20th century, renowned for its unique sailboat design.
7. Louvre Museum: Located in Paris, France, it is one of the largest museums in the world with a rich collection, including Leonardo da Vinci's Mona Lisa and Greece's Venus de Milo.
8. Niagara Falls: located at the border of the United States and Canada, consisting of three main waterfalls, its spectacular scenery attracts millions of tourists every year.
9. St. Sophia Cathedral: located in Istanbul, Türkiye, originally built in 537 A.D., it used to be an Orthodox cathedral and mosque, and now it is a museum.
10. Machu Picchu: an ancient Inca site located on the plateau of the Andes Mountains in Peru, one of the New Seven Wonders of the World, with an altitude of over 2400 meters.`

var docs []*schema.Document
for idx, str := range strings.Split(contents, "\n") {
docs = append(docs, &schema.Document{
ID: strconv.FormatInt(int64(idx+1), 10),
Content: str,
})
}

ids, err := indexer.Store(ctx, docs)
if err != nil {
panic(err)
}

fmt.Println(ids) // [1 2 3 4 5 6 7 8 9 10]
// redis hashes keys are eino_doc:1, eino_doc:2 ...
}

// mockEmbedding returns embeddings with 1024 dimensions
type mockEmbedding struct {
dense [][]float64
}

func (m mockEmbedding) EmbedStrings(ctx context.Context, texts []string, opts ...embedding.Option) ([][]float64, error) {
return m.dense, nil
}
1 change: 1 addition & 0 deletions components/indexer/redis/examples/embeddings.json

Large diffs are not rendered by default.

Loading
Loading