Refactor: rag to sep package

This commit is contained in:
Grail Finder
2025-01-05 20:51:31 +03:00
parent 4736e43631
commit b822b3a161
6 changed files with 282 additions and 248 deletions

21
bot.go
View File

@@ -5,6 +5,7 @@ import (
"bytes"
"elefant/config"
"elefant/models"
"elefant/rag"
"elefant/storage"
"encoding/json"
"fmt"
@@ -33,6 +34,7 @@ var (
defaultStarter = []models.RoleMsg{}
defaultStarterBytes = []byte{}
interruptResp = false
ragger *rag.RAG
)
// ====
@@ -129,26 +131,34 @@ func chatRagUse(qText string) (string, error) {
for i, q := range questionsS {
questions[i] = q.Text
}
respVecs := []*models.VectorRow{}
respVecs := []models.VectorRow{}
for i, q := range questions {
emb, err := lineToVector(q)
emb, err := ragger.LineToVector(q)
if err != nil {
logger.Error("failed to get embs", "error", err, "index", i, "question", q)
continue
}
vec, err := searchEmb(emb)
// e := &models.EmbeddingResp{
// Embedding: emb,
// }
// vecs, err := ragger.SearchEmb(e)
vecs, err := store.SearchClosest(emb)
if err != nil {
logger.Error("failed to get embs", "error", err, "index", i, "question", q)
logger.Error("failed to query embs", "error", err, "index", i, "question", q)
continue
}
respVecs = append(respVecs, vec)
respVecs = append(respVecs, vecs...)
// logger.Info("returned vector from query search", "question", q, "vec", vec)
}
// get raw text
resps := []string{}
logger.Info("sqlvec resp", "vecs", respVecs)
for _, rv := range respVecs {
resps = append(resps, rv.RawText)
}
if len(resps) == 0 {
return "No related results from vector storage.", nil
}
return strings.Join(resps, "\n"), nil
}
@@ -326,6 +336,7 @@ func init() {
if store == nil {
os.Exit(1)
}
ragger = rag.New(logger, store, cfg)
// https://github.com/coreydaley/ggerganov-llama.cpp/blob/master/examples/server/README.md
// load all chats in memory
if _, err := loadHistoryChats(); err != nil {

View File

@@ -10,7 +10,7 @@ var (
botRespMode = false
editMode = false
selectedIndex = int(-1)
indexLine = "F12 to show keys help; bot resp mode: %v; char: %s; chat: %s; RAGEnabled: %v"
indexLine = "F12 to show keys help; bot resp mode: %v; char: %s; chat: %s; RAGEnabled: %v; EmbedURL: %s"
focusSwitcher = map[tview.Primitive]tview.Primitive{}
)

222
rag.go
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@@ -1,222 +0,0 @@
package main
import (
"bytes"
"context"
"elefant/models"
"encoding/json"
"errors"
"fmt"
"net/http"
"os"
"github.com/neurosnap/sentences/english"
)
func loadRAG(fpath string) error {
data, err := os.ReadFile(fpath)
if err != nil {
return err
}
fileText := string(data)
tokenizer, err := english.NewSentenceTokenizer(nil)
if err != nil {
return err
}
sentences := tokenizer.Tokenize(fileText)
sents := make([]string, len(sentences))
for i, s := range sentences {
sents[i] = s.Text
}
var (
// TODO: to config
workers = 5
batchSize = 200
//
left = 0
right = batchSize
batchCh = make(chan map[int][]string)
vectorCh = make(chan []models.VectorRow)
errCh = make(chan error)
)
if len(sents) < batchSize {
batchSize = len(sents)
}
// fill input channel
for {
if right > len(sents) {
batchCh <- map[int][]string{left: sents[left:]}
break
}
batchCh <- map[int][]string{left: sents[left:right]}
left, right = right, right+batchSize
}
// TODO: cancel complains, replace ctx with done chan
ctx, cancel := context.WithCancel(context.Background())
for w := 0; w < workers; w++ {
go batchToVectorHFAsync(ctx, cancel, len(sents), batchCh, vectorCh, errCh)
}
// write to db
return writeVectors(vectorCh)
}
func writeVectors(vectorCh <-chan []models.VectorRow) error {
for batch := range vectorCh {
for _, vector := range batch {
if err := store.WriteVector(&vector); err != nil {
return err
}
}
}
return nil
}
func batchToVectorHFAsync(ctx context.Context, close context.CancelFunc, limit int,
inputCh <-chan map[int][]string, vectorCh chan<- []models.VectorRow, errCh chan error) {
for {
select {
case linesMap := <-inputCh:
for leftI, v := range linesMap {
FecthEmbHF(v, errCh, vectorCh, fmt.Sprintf("test_%d", leftI))
if leftI+200 >= limit { // last batch
close()
return
}
}
case <-ctx.Done():
logger.Error("got ctx done")
return
case err := <-errCh:
logger.Error("got an error", "error", err)
close()
return
}
}
}
func FecthEmbHF(lines []string, errCh chan error, vectorCh chan<- []models.VectorRow, slug string) {
payload, err := json.Marshal(
map[string]any{"inputs": lines, "options": map[string]bool{"wait_for_model": true}},
)
if err != nil {
logger.Error("failed to marshal payload", "err:", err.Error())
errCh <- err
return
}
req, err := http.NewRequest("POST", cfg.EmbedURL, bytes.NewReader(payload))
req.Header.Add("Authorization", fmt.Sprintf("Bearer %s", cfg.HFToken))
resp, err := httpClient.Do(req)
// nolint
// resp, err := httpClient.Post(cfg.EmbedURL, "application/json", bytes.NewReader(payload))
if err != nil {
logger.Error("failed to embedd line", "err:", err.Error())
errCh <- err
return
}
defer resp.Body.Close()
if resp.StatusCode != 200 {
logger.Error("non 200 resp", "code", resp.StatusCode)
errCh <- err
return
}
emb := [][]float32{}
if err := json.NewDecoder(resp.Body).Decode(&emb); err != nil {
logger.Error("failed to embedd line", "err:", err.Error())
errCh <- err
return
}
if len(emb) == 0 {
logger.Error("empty emb")
err = errors.New("empty emb")
errCh <- err
return
}
vectors := make([]models.VectorRow, len(emb))
for i, e := range emb {
vector := models.VectorRow{
Embeddings: e,
RawText: lines[i],
Slug: slug,
}
vectors[i] = vector
}
vectorCh <- vectors
}
func batchToVectorHF(lines []string) ([][]float32, error) {
payload, err := json.Marshal(
map[string]any{"inputs": lines, "options": map[string]bool{"wait_for_model": true}},
)
if err != nil {
logger.Error("failed to marshal payload", "err:", err.Error())
return nil, err
}
req, err := http.NewRequest("POST", cfg.EmbedURL, bytes.NewReader(payload))
req.Header.Add("Authorization", fmt.Sprintf("Bearer %s", cfg.HFToken))
resp, err := httpClient.Do(req)
// nolint
// resp, err := httpClient.Post(cfg.EmbedURL, "application/json", bytes.NewReader(payload))
if err != nil {
logger.Error("failed to embedd line", "err:", err.Error())
return nil, err
}
defer resp.Body.Close()
if resp.StatusCode != 200 {
logger.Error("non 200 resp", "code", resp.StatusCode)
return nil, err
}
emb := [][]float32{}
if err := json.NewDecoder(resp.Body).Decode(&emb); err != nil {
logger.Error("failed to embedd line", "err:", err.Error())
return nil, err
}
if len(emb) == 0 {
logger.Error("empty emb")
err = errors.New("empty emb")
return nil, err
}
return emb, nil
}
func lineToVector(line string) (*models.EmbeddingResp, error) {
payload, err := json.Marshal(map[string]string{"content": line})
if err != nil {
logger.Error("failed to marshal payload", "err:", err.Error())
return nil, err
}
// nolint
resp, err := httpClient.Post(cfg.EmbedURL, "application/json", bytes.NewReader(payload))
if err != nil {
logger.Error("failed to embedd line", "err:", err.Error())
return nil, err
}
defer resp.Body.Close()
if resp.StatusCode != 200 {
logger.Error("non 200 resp", "code", resp.StatusCode)
return nil, err
}
emb := models.EmbeddingResp{}
if err := json.NewDecoder(resp.Body).Decode(&emb); err != nil {
logger.Error("failed to embedd line", "err:", err.Error())
return nil, err
}
if len(emb.Embedding) == 0 {
logger.Error("empty emb")
err = errors.New("empty emb")
return nil, err
}
return &emb, nil
}
func saveLine(topic, line string, emb *models.EmbeddingResp) error {
row := &models.VectorRow{
Embeddings: emb.Embedding,
Slug: topic,
RawText: line,
}
return store.WriteVector(row)
}
func searchEmb(emb *models.EmbeddingResp) (*models.VectorRow, error) {
return store.SearchClosest(emb.Embedding)
}

240
rag/main.go Normal file
View File

@@ -0,0 +1,240 @@
package rag
import (
"bytes"
"elefant/config"
"elefant/models"
"elefant/storage"
"encoding/json"
"errors"
"fmt"
"log/slog"
"net/http"
"os"
"github.com/neurosnap/sentences/english"
)
type RAG struct {
logger *slog.Logger
store storage.FullRepo
cfg *config.Config
}
func New(l *slog.Logger, s storage.FullRepo, cfg *config.Config) *RAG {
return &RAG{
logger: l,
store: s,
cfg: cfg,
}
}
func (r *RAG) LoadRAG(fpath string) error {
data, err := os.ReadFile(fpath)
if err != nil {
return err
}
r.logger.Info("rag: loaded file", "fp", fpath)
fileText := string(data)
tokenizer, err := english.NewSentenceTokenizer(nil)
if err != nil {
return err
}
sentences := tokenizer.Tokenize(fileText)
sents := make([]string, len(sentences))
r.logger.Info("rag: sentences", "#", len(sents))
for i, s := range sentences {
sents[i] = s.Text
}
// TODO: maybe better to decide batch size based on sentences len
var (
// TODO: to config
workers = 5
batchSize = 200
maxChSize = 1000
//
left = 0
right = batchSize
batchCh = make(chan map[int][]string, maxChSize)
vectorCh = make(chan []models.VectorRow, maxChSize)
errCh = make(chan error, 1)
doneCh = make(chan bool, 1)
)
if len(sents) < batchSize {
batchSize = len(sents)
}
// fill input channel
ctn := 0
for {
if right > len(sents) {
batchCh <- map[int][]string{left: sents[left:]}
break
}
batchCh <- map[int][]string{left: sents[left:right]}
left, right = right, right+batchSize
ctn++
}
r.logger.Info("finished batching", "batches#", len(batchCh))
for w := 0; w < workers; w++ {
go r.batchToVectorHFAsync(len(sents), batchCh, vectorCh, errCh, doneCh)
}
// write to db
return r.writeVectors(vectorCh, doneCh)
}
func (r *RAG) writeVectors(vectorCh <-chan []models.VectorRow, doneCh <-chan bool) error {
for {
select {
case batch := <-vectorCh:
for _, vector := range batch {
if err := r.store.WriteVector(&vector); err != nil {
return err
}
}
r.logger.Info("wrote batch to db", "size", len(batch))
case <-doneCh:
r.logger.Info("rag finished")
return nil
}
}
}
func (r *RAG) batchToVectorHFAsync(limit int, inputCh <-chan map[int][]string,
vectorCh chan<- []models.VectorRow, errCh chan error, doneCh chan bool) {
r.logger.Info("to vector batches", "batches#", len(inputCh))
for {
select {
case linesMap := <-inputCh:
// r.logger.Info("batch from ch")
for leftI, v := range linesMap {
// r.logger.Info("fetching", "index", leftI)
r.fecthEmbHF(v, errCh, vectorCh, fmt.Sprintf("test_%d", leftI))
if leftI+200 >= limit { // last batch
doneCh <- true
return
}
// r.logger.Info("done feitching", "index", leftI)
}
case <-doneCh:
r.logger.Info("got done")
close(errCh)
close(doneCh)
return
case err := <-errCh:
r.logger.Error("got an error", "error", err)
return
}
}
}
func (r *RAG) fecthEmbHF(lines []string, errCh chan error, vectorCh chan<- []models.VectorRow, slug string) {
payload, err := json.Marshal(
map[string]any{"inputs": lines, "options": map[string]bool{"wait_for_model": true}},
)
if err != nil {
r.logger.Error("failed to marshal payload", "err:", err.Error())
errCh <- err
return
}
req, err := http.NewRequest("POST", r.cfg.EmbedURL, bytes.NewReader(payload))
if err != nil {
r.logger.Error("failed to create new req", "err:", err.Error())
errCh <- err
return
}
req.Header.Add("Authorization", fmt.Sprintf("Bearer %s", r.cfg.HFToken))
resp, err := http.DefaultClient.Do(req)
// nolint
// resp, err := httpClient.Post(cfg.EmbedURL, "application/json", bytes.NewReader(payload))
if err != nil {
r.logger.Error("failed to embedd line", "err:", err.Error())
errCh <- err
return
}
defer resp.Body.Close()
if resp.StatusCode != 200 {
r.logger.Error("non 200 resp", "code", resp.StatusCode)
return
// err = fmt.Errorf("non 200 resp; url: %s; code %d", r.cfg.EmbedURL, resp.StatusCode)
// errCh <- err
// return
}
emb := [][]float32{}
if err := json.NewDecoder(resp.Body).Decode(&emb); err != nil {
r.logger.Error("failed to embedd line", "err:", err.Error())
errCh <- err
return
}
if len(emb) == 0 {
r.logger.Error("empty emb")
err = errors.New("empty emb")
errCh <- err
return
}
vectors := make([]models.VectorRow, len(emb))
for i, e := range emb {
vector := models.VectorRow{
Embeddings: e,
RawText: lines[i],
Slug: slug,
}
vectors[i] = vector
}
vectorCh <- vectors
}
func (r *RAG) LineToVector(line string) ([]float32, error) {
// payload, err := json.Marshal(map[string]string{"content": line})
lines := []string{line}
payload, err := json.Marshal(
map[string]any{"inputs": lines, "options": map[string]bool{"wait_for_model": true}},
)
if err != nil {
r.logger.Error("failed to marshal payload", "err:", err.Error())
return nil, err
}
// nolint
req, err := http.NewRequest("POST", r.cfg.EmbedURL, bytes.NewReader(payload))
if err != nil {
r.logger.Error("failed to create new req", "err:", err.Error())
return nil, err
}
req.Header.Add("Authorization", fmt.Sprintf("Bearer %s", r.cfg.HFToken))
resp, err := http.DefaultClient.Do(req)
// resp, err := req.Post(r.cfg.EmbedURL, "application/json", bytes.NewReader(payload))
if err != nil {
r.logger.Error("failed to embedd line", "err:", err.Error())
return nil, err
}
defer resp.Body.Close()
if resp.StatusCode != 200 {
err = fmt.Errorf("non 200 resp; code: %v\n", resp.StatusCode)
r.logger.Error(err.Error())
return nil, err
}
// emb := models.EmbeddingResp{}
emb := [][]float32{}
if err := json.NewDecoder(resp.Body).Decode(&emb); err != nil {
r.logger.Error("failed to embedd line", "err:", err.Error())
return nil, err
}
if len(emb) == 0 || len(emb[0]) == 0 {
r.logger.Error("empty emb")
err = errors.New("empty emb")
return nil, err
}
return emb[0], nil
}
func (r *RAG) saveLine(topic, line string, emb *models.EmbeddingResp) error {
row := &models.VectorRow{
Embeddings: emb.Embedding,
Slug: topic,
RawText: line,
}
return r.store.WriteVector(row)
}
func (r *RAG) SearchEmb(emb *models.EmbeddingResp) ([]models.VectorRow, error) {
return r.store.SearchClosest(emb.Embedding)
}

View File

@@ -4,7 +4,6 @@ import (
"elefant/models"
"errors"
"fmt"
"log"
"unsafe"
sqlite_vec "github.com/asg017/sqlite-vec-go-bindings/ncruces"
@@ -12,7 +11,7 @@ import (
type VectorRepo interface {
WriteVector(*models.VectorRow) error
SearchClosest(q []float32) (*models.VectorRow, error)
SearchClosest(q []float32) ([]models.VectorRow, error)
}
var (
@@ -79,7 +78,11 @@ func decodeUnsafe(bs []byte) []float32 {
return unsafe.Slice((*float32)(unsafe.Pointer(&bs[0])), len(bs)/4)
}
func (p ProviderSQL) SearchClosest(q []float32) (*models.VectorRow, error) {
func (p ProviderSQL) SearchClosest(q []float32) ([]models.VectorRow, error) {
tableName, err := fetchTableName(q)
if err != nil {
return nil, err
}
stmt, _, err := p.s3Conn.Prepare(
fmt.Sprintf(`SELECT
id,
@@ -91,35 +94,35 @@ func (p ProviderSQL) SearchClosest(q []float32) (*models.VectorRow, error) {
WHERE embedding MATCH ?
ORDER BY distance
LIMIT 4
`, vecTableName))
`, tableName))
if err != nil {
log.Fatal(err)
return nil, err
}
query, err := sqlite_vec.SerializeFloat32(q[:])
if err != nil {
log.Fatal(err)
return nil, err
}
if err := stmt.BindBlob(1, query); err != nil {
p.logger.Error("failed to bind", "error", err)
return nil, err
}
resp := make([]models.VectorRow, 4)
i := 0
resp := []models.VectorRow{}
for stmt.Step() {
resp[i].ID = uint32(stmt.ColumnInt64(0))
resp[i].Distance = float32(stmt.ColumnFloat(1))
res := models.VectorRow{}
res.ID = uint32(stmt.ColumnInt64(0))
res.Distance = float32(stmt.ColumnFloat(1))
emb := stmt.ColumnRawText(2)
resp[i].Embeddings = decodeUnsafe(emb)
resp[i].Slug = stmt.ColumnText(3)
resp[i].RawText = stmt.ColumnText(4)
i++
res.Embeddings = decodeUnsafe(emb)
res.Slug = stmt.ColumnText(3)
res.RawText = stmt.ColumnText(4)
resp = append(resp, res)
}
if err := stmt.Err(); err != nil {
log.Fatal(err)
return nil, err
}
err = stmt.Close()
if err != nil {
log.Fatal(err)
return nil, err
}
return nil, nil
return resp, nil
}

8
tui.go
View File

@@ -5,6 +5,7 @@ import (
"elefant/pngmeta"
"fmt"
"os"
"path"
"strconv"
"strings"
"time"
@@ -169,8 +170,9 @@ func makeRAGTable(fileList []string) *tview.Table {
// notification := fmt.Sprintf("chat: %s; action: %s", fpath, tc.Text)
switch tc.Text {
case "load":
if err := loadRAG(fpath); err != nil {
logger.Error("failed to read history file", "chat", fpath)
fpath = path.Join(cfg.RAGDir, fpath)
if err := ragger.LoadRAG(fpath); err != nil {
logger.Error("failed to embed file", "chat", fpath, "error", err)
pages.RemovePage(RAGPage)
return
}
@@ -228,7 +230,7 @@ func colorText() {
}
func updateStatusLine() {
position.SetText(fmt.Sprintf(indexLine, botRespMode, cfg.AssistantRole, activeChatName, cfg.RAGEnabled))
position.SetText(fmt.Sprintf(indexLine, botRespMode, cfg.AssistantRole, activeChatName, cfg.RAGEnabled, cfg.EmbedURL))
}
func initSysCards() ([]string, error) {