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2 changes: 2 additions & 0 deletions go/go.mod
Original file line number Diff line number Diff line change
Expand Up @@ -49,7 +49,9 @@ require (
github.com/googleapis/enterprise-certificate-proxy v0.3.2 // indirect
github.com/googleapis/gax-go/v2 v2.12.4 // indirect
github.com/kr/text v0.2.0 // indirect
github.com/lib/pq v1.10.9 // indirect
github.com/mailru/easyjson v0.7.7 // indirect
github.com/pgvector/pgvector-go v0.1.1 // indirect
github.com/xeipuuv/gojsonpointer v0.0.0-20180127040702-4e3ac2762d5f // indirect
github.com/xeipuuv/gojsonreference v0.0.0-20180127040603-bd5ef7bd5415 // indirect
go.opencensus.io v0.24.0 // indirect
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4 changes: 4 additions & 0 deletions go/go.sum
Original file line number Diff line number Diff line change
Expand Up @@ -100,8 +100,12 @@ github.com/kr/pretty v0.3.1 h1:flRD4NNwYAUpkphVc1HcthR4KEIFJ65n8Mw5qdRn3LE=
github.com/kr/pretty v0.3.1/go.mod h1:hoEshYVHaxMs3cyo3Yncou5ZscifuDolrwPKZanG3xk=
github.com/kr/text v0.2.0 h1:5Nx0Ya0ZqY2ygV366QzturHI13Jq95ApcVaJBhpS+AY=
github.com/kr/text v0.2.0/go.mod h1:eLer722TekiGuMkidMxC/pM04lWEeraHUUmBw8l2grE=
github.com/lib/pq v1.10.9 h1:YXG7RB+JIjhP29X+OtkiDnYaXQwpS4JEWq7dtCCRUEw=
github.com/lib/pq v1.10.9/go.mod h1:AlVN5x4E4T544tWzH6hKfbfQvm3HdbOxrmggDNAPY9o=
github.com/mailru/easyjson v0.7.7 h1:UGYAvKxe3sBsEDzO8ZeWOSlIQfWFlxbzLZe7hwFURr0=
github.com/mailru/easyjson v0.7.7/go.mod h1:xzfreul335JAWq5oZzymOObrkdz5UnU4kGfJJLY9Nlc=
github.com/pgvector/pgvector-go v0.1.1 h1:kqJigGctFnlWvskUiYIvJRNwUtQl/aMSUZVs0YWQe+g=
github.com/pgvector/pgvector-go v0.1.1/go.mod h1:wLJgD/ODkdtd2LJK4l6evHXTuG+8PxymYAVomKHOWac=
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
github.com/prometheus/client_model v0.0.0-20190812154241-14fe0d1b01d4/go.mod h1:xMI15A0UPsDsEKsMN9yxemIoYk6Tm2C1GtYGdfGttqA=
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215 changes: 215 additions & 0 deletions go/samples/pgvector/main.go
Original file line number Diff line number Diff line change
@@ -0,0 +1,215 @@
// Copyright 2024 Google LLC
//
// 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.

// This program shows how to use Postgres's pgvector extension with Genkit.

// This program can be manually tested like so:
//
// In development mode (with the environment variable GENKIT_ENV="dev"):
// Start the server listening on port 3100:
//
// go run . -dbconn "$DBCONN" -apikey $API_KEY &
//
// Ask a question:
//
// curl -d '{"Show": "Best Friends", "Question": "Who does Alice love?"}' http://localhost:3400/askQuestion
package main

import (
"context"
"database/sql"
"errors"
"flag"
"fmt"
"log"

"github.com/firebase/genkit/go/ai"
"github.com/firebase/genkit/go/genkit"
"github.com/firebase/genkit/go/plugins/googleai"
_ "github.com/lib/pq"
pgv "github.com/pgvector/pgvector-go"
)

var (
connString = flag.String("dbconn", "", "database connection string")
apiKey = flag.String("apikey", "", "Gemini API key")
index = flag.Bool("index", false, "index the existing data")
)

func main() {
flag.Parse()
if err := run(); err != nil {
log.Fatal(err)
}
}

func run() error {
if *connString == "" {
return errors.New("need -dbconn")
}
if *apiKey == "" {
return errors.New("need -apikey")
}
ctx := context.Background()
_, ems, err := googleai.Init(ctx, googleai.Config{
APIKey: *apiKey,
Embedders: []string{"embedding-001"},
})
if err != nil {
return err
}
embedder := ems[0]

db, err := sql.Open("postgres", *connString)
if err != nil {
return err
}
defer db.Close()

if *index {
indexer := defineIndexer(db, embedder)
if err := indexExistingRows(ctx, db, indexer); err != nil {
return err
}
}

retriever := defineRetriever(db, embedder)

type input struct {
Question string
Show string
}

genkit.DefineFlow("askQuestion", func(ctx context.Context, in input, _ genkit.NoStream) (string, error) {
res, err := ai.Retrieve(ctx, retriever, &ai.RetrieverRequest{
Document: &ai.Document{Content: []*ai.Part{ai.NewTextPart(in.Question)}},
Options: in.Show,
})
if err != nil {
return "", err
}
for _, doc := range res.Documents {
fmt.Printf("%+v %q\n", doc.Metadata, doc.Content[0].Text)
}
// Use documents in RAG prompts.
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Is this a TODO? I'm not sure what the point of retrieving here is, as you don't actually answer the question asked.

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It's deliberately a sketch. So yeah it's a TODO, but not for us, for whoever copies the sample.

I based it off of https://github.com/firebase/genkit/blob/main/docs/templates/pgvector.md.
I decided to write actual code rather than a markdown file so I could be sure it actually worked.

return "", nil
})

return genkit.StartFlowServer("")
}

const provider = "pgvector"

func defineRetriever(db *sql.DB, embedder *ai.EmbedderAction) *ai.RetrieverAction {
f := func(ctx context.Context, req *ai.RetrieverRequest) (*ai.RetrieverResponse, error) {
vals, err := ai.Embed(ctx, embedder, &ai.EmbedRequest{Document: req.Document})
if err != nil {
return nil, err
}
rows, err := db.QueryContext(ctx, `
SELECT episode_id, season_number, chunk as content
FROM embeddings
WHERE show_id = $1
ORDER BY embedding <#> $2
LIMIT 2`,
req.Options, pgv.NewVector(vals))
if err != nil {
return nil, err
}
defer rows.Close()

res := &ai.RetrieverResponse{}
for rows.Next() {
var eid, sn int
var content string
if err := rows.Scan(&eid, &sn, &content); err != nil {
return nil, err
}
meta := map[string]any{
"episode_id": eid,
"season_number": sn,
}
doc := &ai.Document{
Content: []*ai.Part{ai.NewTextPart(content)},
Metadata: meta,
}
res.Documents = append(res.Documents, doc)
}
if err := rows.Err(); err != nil {
return nil, err
}
return res, nil
}
return ai.DefineRetriever(provider, "shows", f)
}

func defineIndexer(db *sql.DB, embedder *ai.EmbedderAction) *ai.IndexerAction {
// The indexer assumes that each Document has a single part, to be embedded, and metadata fields
// for the table primary key: show_id, season_number, episode_id.
const query = `
UPDATE embeddings
SET embedding = $4
WHERE show_id = $1 AND season_number = $2 AND episode_id = $3
`
return ai.DefineIndexer(provider, "shows", func(ctx context.Context, req *ai.IndexerRequest) error {
for i, doc := range req.Documents {
vals, err := ai.Embed(ctx, embedder, &ai.EmbedRequest{Document: doc})
if err != nil {
return err
}
args := make([]any, 4)
for j, k := range []string{"show_id", "season_number", "episode_id"} {
if a, ok := doc.Metadata[k]; ok {
args[j] = a
} else {
return fmt.Errorf("doc[%d]: missing metadata key %q", i, k)
}
}
args[3] = pgv.NewVector(vals)
if _, err := db.ExecContext(ctx, query, args...); err != nil {
return err
}
}
return nil
})
}

func indexExistingRows(ctx context.Context, db *sql.DB, indexer *ai.IndexerAction) error {
rows, err := db.QueryContext(ctx, `SELECT show_id, season_number, episode_id, chunk FROM embeddings`)
if err != nil {
return err
}
defer rows.Close()

req := &ai.IndexerRequest{}
for rows.Next() {
var sid, chunk string
var sn, eid int
if err := rows.Scan(&sid, &sn, &eid, &chunk); err != nil {
return err
}
req.Documents = append(req.Documents, &ai.Document{
Content: []*ai.Part{ai.NewTextPart(chunk)},
Metadata: map[string]any{
"show_id": sid,
"season_number": sn,
"episode_id": eid,
},
})
}
if err := rows.Err(); err != nil {
return err
}
return ai.Index(ctx, indexer, req)
}
22 changes: 22 additions & 0 deletions go/samples/pgvector/pgvector.sql
Original file line number Diff line number Diff line change
@@ -0,0 +1,22 @@
-- This SQL enables the vector extension and creates the table and data used
-- in the accompanying sample.

CREATE EXTENSION IF NOT EXISTS vector;

CREATE TABLE embeddings (
show_id TEXT NOT NULL,
season_number INTEGER NOT NULL,
episode_id INTEGER NOT NULL,
chunk TEXT,
embedding vector(768),
PRIMARY KEY (show_id, season_number, episode_id)
);

INSERT INTO embeddings (show_id, season_number, episode_id, chunk) VALUES
('La Vie', 1, 1, 'Natasha confesses her love for Pierre.'),
('La Vie', 1, 2, 'Pierre and Natasha become engaged.'),
('La Vie', 1, 3, 'Margot and Henri divorce.'),
('Best Friends', 1, 1, 'Alice confesses her love for Oscar.'),
('Best Friends', 1, 2, 'Oscar and Alice become engaged.'),
('Best Friends', 1, 3, 'Bob and Pat divorce.')
;