Make Knowledgebase RAG functional (almost)

agent/agent.go

@@ -23,7 +23,6 @@ type Agent struct {
 	options       *options
 	Character     Character
 	client        *openai.Client
-	storeClient   *llm.StoreClient
 	jobQueue      chan *Job
 	actionContext *action.ActionContext
 	context       *action.ActionContext
@@ -37,6 +36,11 @@ type Agent struct {
 	newConversations chan openai.ChatCompletionMessage
 }
 
+type RAGDB interface {
+	Store(s string) error
+	Search(s string, similarEntries int) ([]string, error)
+}
+
 func New(opts ...Option) (*Agent, error) {
 	options, err := newOptions(opts...)
 	if err != nil {
@@ -44,7 +48,6 @@ func New(opts ...Option) (*Agent, error) {
 	}
 
 	client := llm.NewClient(options.LLMAPI.APIKey, options.LLMAPI.APIURL)
-	storeClient := llm.NewStoreClient(options.LLMAPI.APIURL, options.LLMAPI.APIKey)
 
 	c := context.Background()
 	if options.context != nil {
@@ -58,7 +61,6 @@ func New(opts ...Option) (*Agent, error) {
 		client:       client,
 		Character:    options.character,
 		currentState: &action.StateResult{},
-		storeClient:  storeClient,
 		context:      action.NewContext(ctx, cancel),
 	}
 
@@ -204,7 +206,7 @@ func (a *Agent) consumeJob(job *Job, role string) {
 	}
 
 	// RAG
-	if a.options.enableKB {
+	if a.options.enableKB && a.options.ragdb != nil {
 		// Walk conversation from bottom to top, and find the first message of the user
 		// to use it as a query to the KB
 		var userMessage string
@@ -216,7 +218,7 @@ func (a *Agent) consumeJob(job *Job, role string) {
 		}
 
 		if userMessage != "" {
-			results, err := llm.FindSimilarStrings(a.storeClient, a.client, userMessage, a.options.kbResults)
+			results, err := a.options.ragdb.Search(userMessage, a.options.kbResults)
 			if err != nil {
 				if a.options.debugMode {
 					fmt.Println("Error finding similar strings inside KB:", err)

agent/options.go

@@ -28,6 +28,7 @@ type options struct {
 	permanentGoal                                     string
 	periodicRuns                                      time.Duration
 	kbResults                                         int
+	ragdb                                             RAGDB
 
 	// callbacks
 	reasoningCallback func(ActionCurrentState) bool
@@ -102,6 +103,13 @@ var EnablePersonality = func(o *options) error {
 	return nil
 }
 
+func WithRAGDB(db RAGDB) Option {
+	return func(o *options) error {
+		o.ragdb = db
+		return nil
+	}
+}
+
 func WithLLMAPIURL(url string) Option {
 	return func(o *options) error {
 		o.LLMAPI.APIURL = url

example/webui/agentpool.go

@@ -48,6 +48,7 @@ type AgentPool struct {
 	agents        map[string]*Agent
 	managers      map[string]Manager
 	apiURL, model string
+	ragDB         RAGDB
 }
 
 type AgentPoolData map[string]AgentConfig
@@ -63,7 +64,7 @@ func loadPoolFromFile(path string) (*AgentPoolData, error) {
 	return poolData, err
 }
 
-func NewAgentPool(model, apiURL, directory string) (*AgentPool, error) {
+func NewAgentPool(model, apiURL, directory string, RagDB RAGDB) (*AgentPool, error) {
 	// if file exists, try to load an existing pool.
 	// if file does not exist, create a new pool.
 
@@ -76,6 +77,7 @@ func NewAgentPool(model, apiURL, directory string) (*AgentPool, error) {
 			pooldir:  directory,
 			apiURL:   apiURL,
 			model:    model,
+			ragDB:    RagDB,
 			agents:   make(map[string]*Agent),
 			pool:     make(map[string]AgentConfig),
 			managers: make(map[string]Manager),
@@ -90,6 +92,7 @@ func NewAgentPool(model, apiURL, directory string) (*AgentPool, error) {
 		file:     poolfile,
 		apiURL:   apiURL,
 		pooldir:  directory,
+		ragDB:    RagDB,
 		model:    model,
 		agents:   make(map[string]*Agent),
 		managers: make(map[string]Manager),
@@ -229,6 +232,7 @@ func (a *AgentPool) startAgentWithConfig(name string, config *AgentConfig) error
 		),
 		WithStateFile(stateFile),
 		WithCharacterFile(characterFile),
+		WithRAGDB(a.ragDB),
 		WithAgentReasoningCallback(func(state ActionCurrentState) bool {
 			fmt.Println("Reasoning", state.Reasoning)
 			manager.Send(

example/webui/main.go

@@ -12,6 +12,8 @@ import (
 	fiber "github.com/gofiber/fiber/v2"
 
 	. "github.com/mudler/local-agent-framework/agent"
+	"github.com/mudler/local-agent-framework/llm"
+	"github.com/mudler/local-agent-framework/llm/rag"
 )
 
 type (
@@ -24,6 +26,9 @@ type (
 var testModel = os.Getenv("TEST_MODEL")
 var apiURL = os.Getenv("API_URL")
 var apiKey = os.Getenv("API_KEY")
+var vectorStore = os.Getenv("VECTOR_STORE")
+
+const defaultChunkSize = 4098
 
 func init() {
 	if testModel == "" {
@@ -50,12 +55,27 @@ func main() {
 	stateDir := cwd + "/pool"
 	os.MkdirAll(stateDir, 0755)
 
-	pool, err := NewAgentPool(testModel, apiURL, stateDir)
+	var dbStore RAGDB
+	lai := llm.NewClient(apiKey, apiURL+"/v1")
+
+	switch vectorStore {
+	case "localai":
+		laiStore := rag.NewStoreClient(apiURL, apiKey)
+		dbStore = rag.NewLocalAIRAGDB(laiStore, lai)
+	default:
+		var err error
+		dbStore, err = rag.NewChromemDB("local-agent-framework", stateDir, lai)
+		if err != nil {
+			panic(err)
+		}
+	}
+
+	pool, err := NewAgentPool(testModel, apiURL, stateDir, dbStore)
 	if err != nil {
 		panic(err)
 	}
 
-	db, err := NewInMemoryDB(stateDir)
+	db, err := NewInMemoryDB(stateDir, dbStore)
 	if err != nil {
 		panic(err)
 	}
@@ -144,6 +164,10 @@ func (a *App) KnowledgeBase(db *InMemoryDatabase) func(c *fiber.Ctx) error {
 		if website == "" {
 			return fmt.Errorf("please enter a URL")
 		}
+		chunkSize := defaultChunkSize
+		if payload.ChunkSize > 0 {
+			chunkSize = payload.ChunkSize
+		}
 
 		go func() {
 			content, err := Sitemap(website)
@@ -151,9 +175,10 @@ func (a *App) KnowledgeBase(db *InMemoryDatabase) func(c *fiber.Ctx) error {
 				fmt.Println("Error walking sitemap for website", err)
 			}
 			fmt.Println("Found pages: ", len(content))
+			fmt.Println("ChunkSize: ", chunkSize)
 
 			for _, c := range content {
-				chunks := splitParagraphIntoChunks(c, payload.ChunkSize)
+				chunks := splitParagraphIntoChunks(c, chunkSize)
 				fmt.Println("chunks: ", len(chunks))
 				for _, chunk := range chunks {
 					db.AddEntry(chunk)
@@ -162,7 +187,7 @@ func (a *App) KnowledgeBase(db *InMemoryDatabase) func(c *fiber.Ctx) error {
 				db.SaveDB()
 			}
 
-			if err := db.SaveToStore(apiKey, apiURL); err != nil {
+			if err := db.SaveToStore(); err != nil {
 				fmt.Println("Error storing in the KB", err)
 			}
 		}()

example/webui/rag.go

@@ -10,9 +10,9 @@ import (
 	"strings"
 	"sync"
 
+	. "github.com/mudler/local-agent-framework/agent"
 	"jaytaylor.com/html2text"
 
-	"github.com/mudler/local-agent-framework/llm"
 	sitemap "github.com/oxffaa/gopher-parse-sitemap"
 )
 
@@ -20,6 +20,7 @@ type InMemoryDatabase struct {
 	sync.Mutex
 	Database []string
 	path     string
+	rag      RAGDB
 }
 
 func loadDB(path string) ([]string, error) {
@@ -33,7 +34,7 @@ func loadDB(path string) ([]string, error) {
 	return poolData, err
 }
 
-func NewInMemoryDB(knowledgebase string) (*InMemoryDatabase, error) {
+func NewInMemoryDB(knowledgebase string, store RAGDB) (*InMemoryDatabase, error) {
 	// if file exists, try to load an existing pool.
 	// if file does not exist, create a new pool.
 
@@ -44,6 +45,7 @@ func NewInMemoryDB(knowledgebase string) (*InMemoryDatabase, error) {
 		return &InMemoryDatabase{
 			Database: []string{},
 			path:     poolfile,
+			rag:      store,
 		}, nil
 	}
 
@@ -54,15 +56,17 @@ func NewInMemoryDB(knowledgebase string) (*InMemoryDatabase, error) {
 	return &InMemoryDatabase{
 		Database: poolData,
 		path:     poolfile,
+		rag:      store,
 	}, nil
 }
 
-func (db *InMemoryDatabase) SaveToStore(apiKey string, apiURL string) error {
+func (db *InMemoryDatabase) SaveToStore() error {
 	for _, d := range db.Database {
-		lai := llm.NewClient(apiKey, apiURL+"/v1")
+		if d == "" {
-		laiStore := llm.NewStoreClient(apiURL, apiKey)
+			// skip empty chunks
-
+			continue
-		err := llm.StoreStringEmbeddingInVectorDB(laiStore, lai, d)
+		}
+		err := db.rag.Store(d)
 		if err != nil {
 			return fmt.Errorf("Error storing in the KB: %w", err)
 		}
@@ -119,8 +123,6 @@ func Sitemap(url string) (res []string, err error) {
 // and returns a slice of strings where each string is a chunk of the paragraph
 // that is at most maxChunkSize long, ensuring that words are not split.
 func splitParagraphIntoChunks(paragraph string, maxChunkSize int) []string {
-	// Check if the paragraph length is less than or equal to maxChunkSize.
-	// If so, return the paragraph as the only chunk.
 	if len(paragraph) <= maxChunkSize {
 		return []string{paragraph}
 	}
@@ -131,11 +133,14 @@ func splitParagraphIntoChunks(paragraph string, maxChunkSize int) []string {
 	words := strings.Fields(paragraph) // Splits the paragraph into words.
 
 	for _, word := range words {
-		// Check if adding the next word would exceed the maxChunkSize.
+		// If adding the next word would exceed maxChunkSize (considering a space if not the first word in a chunk),
-		// If so, add the currentChunk to the chunks slice and start a new chunk.
+		// add the currentChunk to chunks, and reset currentChunk.
-		if currentChunk.Len()+len(word) > maxChunkSize {
+		if currentChunk.Len() > 0 && currentChunk.Len()+len(word)+1 > maxChunkSize { // +1 for the space if not the first word
 			chunks = append(chunks, currentChunk.String())
 			currentChunk.Reset()
+		} else if currentChunk.Len() == 0 && len(word) > maxChunkSize { // Word itself exceeds maxChunkSize, split the word
+			chunks = append(chunks, word)
+			continue
 		}
 
 		// Add a space before the word if it's not the beginning of a new chunk.
@@ -147,7 +152,7 @@ func splitParagraphIntoChunks(paragraph string, maxChunkSize int) []string {
 		currentChunk.WriteString(word)
 	}
 
-	// Add the last chunk if it's not empty.
+	// After the loop, add any remaining content in currentChunk to chunks.
 	if currentChunk.Len() > 0 {
 		chunks = append(chunks, currentChunk.String())
 	}

go.mod

@@ -35,6 +35,7 @@ require (
 	github.com/mattn/go-runewidth v0.0.15 // indirect
 	github.com/olekukonko/tablewriter v0.0.5 // indirect
 	github.com/oxffaa/gopher-parse-sitemap v0.0.0-20191021113419-005d2eb1def4 // indirect
+	github.com/philippgille/chromem-go v0.5.0 // indirect
 	github.com/rivo/uniseg v0.2.0 // indirect
 	github.com/ssor/bom v0.0.0-20170718123548-6386211fdfcf // indirect
 	github.com/stretchr/testify v1.9.0 // indirect

go.sum

@@ -59,6 +59,8 @@ github.com/onsi/gomega v1.31.1 h1:KYppCUK+bUgAZwHOu7EXVBKyQA6ILvOESHkn/tgoqvo=
 github.com/onsi/gomega v1.31.1/go.mod h1:y40C95dwAD1Nz36SsEnxvfFe8FFfNxzI5eJ0EYGyAy0=
 github.com/oxffaa/gopher-parse-sitemap v0.0.0-20191021113419-005d2eb1def4 h1:2vmb32OdDhjZf2ETGDlr9n8RYXx7c+jXPxMiPbwnA+8=
 github.com/oxffaa/gopher-parse-sitemap v0.0.0-20191021113419-005d2eb1def4/go.mod h1:2JQx4jDHmWrbABvpOayg/+OTU6ehN0IyK2EHzceXpJo=
+github.com/philippgille/chromem-go v0.5.0 h1:bryX0F3N6jnN/21iBd8i2/k9EzPTZn3nyiqAti19si8=
+github.com/philippgille/chromem-go v0.5.0/go.mod h1:hTd+wGEm/fFPQl7ilfCwQXkgEUxceYh86iIdoKMolPo=
 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/rivo/uniseg v0.2.0 h1:S1pD9weZBuJdFmowNwbpi7BJ8TNftyUImj/0WQi72jY=

llm/rag/rag_chromem.go

@@ -0,0 +1,88 @@
+package rag
+
+import (
+	"context"
+	"fmt"
+	"runtime"
+
+	"github.com/philippgille/chromem-go"
+	"github.com/sashabaranov/go-openai"
+)
+
+type ChromemDB struct {
+	collectionName string
+	collection     *chromem.Collection
+	index          int
+}
+
+func NewChromemDB(collection, path string, openaiClient *openai.Client) (*ChromemDB, error) {
+	// db, err := chromem.NewPersistentDB(path, true)
+	// if err != nil {
+	// 	return nil, err
+	// }
+	db := chromem.NewDB()
+
+	embeddingFunc := chromem.EmbeddingFunc(
+		func(ctx context.Context, text string) ([]float32, error) {
+			fmt.Println("Creating embeddings")
+			resp, err := openaiClient.CreateEmbeddings(ctx,
+				openai.EmbeddingRequestStrings{
+					Input: []string{text},
+					Model: openai.AdaEmbeddingV2,
+				},
+			)
+			if err != nil {
+				return []float32{}, fmt.Errorf("error getting keys: %v", err)
+			}
+
+			if len(resp.Data) == 0 {
+				return []float32{}, fmt.Errorf("no response from OpenAI API")
+			}
+
+			embedding := resp.Data[0].Embedding
+
+			return embedding, nil
+		},
+	)
+
+	c, err := db.GetOrCreateCollection(collection, nil, embeddingFunc)
+	if err != nil {
+		return nil, err
+	}
+
+	return &ChromemDB{
+		collectionName: collection,
+		collection:     c,
+		index:          1,
+	}, nil
+}
+
+func (c *ChromemDB) Store(s string) error {
+	defer func() {
+		c.index++
+	}()
+	if s == "" {
+		return fmt.Errorf("empty string")
+	}
+	fmt.Println("Trying to store", s)
+	return c.collection.AddDocuments(context.Background(), []chromem.Document{
+		{
+			Content: s,
+			ID:      fmt.Sprint(c.index),
+		},
+	}, runtime.NumCPU())
+}
+
+func (c *ChromemDB) Search(s string, similarEntries int) ([]string, error) {
+	res, err := c.collection.Query(context.Background(), s, similarEntries, nil, nil)
+	if err != nil {
+		return nil, err
+	}
+
+	var results []string
+	for _, r := range res {
+		results = append(results, r.Content)
+	}
+
+	return results, nil
+}

llm/rag/rag_localai.go

@@ -1,4 +1,4 @@
-package llm
+package rag
 
 import (
 	"context"
@@ -7,8 +7,20 @@ import (
 	"github.com/sashabaranov/go-openai"
 )
 
-func StoreStringEmbeddingInVectorDB(client *StoreClient, openaiClient *openai.Client, s string) error {
+type LocalAIRAGDB struct {
-	resp, err := openaiClient.CreateEmbeddings(context.TODO(),
+	client       *StoreClient
+	openaiClient *openai.Client
+}
+
+func NewLocalAIRAGDB(storeClient *StoreClient, openaiClient *openai.Client) *LocalAIRAGDB {
+	return &LocalAIRAGDB{
+		client:       storeClient,
+		openaiClient: openaiClient,
+	}
+}
+
+func (db *LocalAIRAGDB) Store(s string) error {
+	resp, err := db.openaiClient.CreateEmbeddings(context.TODO(),
 		openai.EmbeddingRequestStrings{
 			Input: []string{s},
 			Model: openai.AdaEmbeddingV2,
@@ -28,7 +40,7 @@ func StoreStringEmbeddingInVectorDB(client *StoreClient, openaiClient *openai.Cl
 		Keys:   [][]float32{embedding},
 		Values: []string{s},
 	}
-	err = client.Set(setReq)
+	err = db.client.Set(setReq)
 	if err != nil {
 		return fmt.Errorf("error setting keys: %v", err)
 	}
@@ -36,9 +48,8 @@ func StoreStringEmbeddingInVectorDB(client *StoreClient, openaiClient *openai.Cl
 	return nil
 }
 
-func FindSimilarStrings(client *StoreClient, openaiClient *openai.Client, s string, similarEntries int) ([]string, error) {
+func (db *LocalAIRAGDB) Search(s string, similarEntries int) ([]string, error) {
-
+	resp, err := db.openaiClient.CreateEmbeddings(context.TODO(),
-	resp, err := openaiClient.CreateEmbeddings(context.TODO(),
 		openai.EmbeddingRequestStrings{
 			Input: []string{s},
 			Model: openai.AdaEmbeddingV2,
@@ -58,7 +69,7 @@ func FindSimilarStrings(client *StoreClient, openaiClient *openai.Client, s stri
 		TopK: similarEntries, // Number of similar entries you want to find
 		Key:  embedding,      // The key you're looking for similarities to
 	}
-	findResp, err := client.Find(findReq)
+	findResp, err := db.client.Find(findReq)
 	if err != nil {
 		return []string{}, fmt.Errorf("error finding keys: %v", err)
 	}

llm/rag/store.go

@@ -1,4 +1,4 @@
-package llm
+package rag
 
 import (
 	"bytes"