1 Commits

Author SHA1 Message Date
Grail Finder
2687f38d00 Chore: remove unnecessary code 2026-03-05 00:28:47 +03:00
27 changed files with 667 additions and 1972 deletions

3
.gitignore vendored
View File

@@ -3,8 +3,6 @@
testlog
history/
*.db
*.db-shm
*.db-wal
config.toml
sysprompts/*
!sysprompts/alice_bob_carl.json
@@ -17,4 +15,3 @@ gflt
chat_exports/*.json
ragimport
.env
onnx/

101
Makefile
View File

@@ -1,4 +1,4 @@
.PHONY: setconfig run lint lintall install-linters setup-whisper build-whisper download-whisper-model docker-up docker-down docker-logs noextra-run installdelve checkdelve fetch-onnx install-onnx-deps
.PHONY: setconfig run lint lintall install-linters setup-whisper build-whisper download-whisper-model docker-up docker-down docker-logs noextra-run installdelve checkdelve
run: setconfig
go build -tags extra -o gf-lt && ./gf-lt
@@ -30,105 +30,6 @@ lint: ## Run linters. Use make install-linters first.
lintall: lint
noblanks ./...
fetch-onnx:
mkdir -p onnx/embedgemma && curl -o onnx/embedgemma/config.json -L https://huggingface.co/onnx-community/embeddinggemma-300m-ONNX/resolve/main/config.json && curl -o onnx/embedgemma/tokenizer.json -L https://huggingface.co/onnx-community/embeddinggemma-300m-ONNX/resolve/main/tokenizer.json && curl -o onnx/embedgemma/model_q4.onnx -L https://huggingface.co/onnx-community/embeddinggemma-300m-ONNX/resolve/main/onnx/model_q4.onnx && curl -o onnx/embedgemma/model_q4.onnx_data -L https://huggingface.co/onnx-community/embeddinggemma-300m-ONNX/resolve/main/onnx/model_q4.onnx_data?download=true
install-onnx-deps: ## Install ONNX Runtime with CUDA support (or CPU fallback)
@echo "=== ONNX Runtime Installer ===" && \
echo "" && \
echo "Checking for existing ONNX Runtime..." && \
if ldconfig -p 2>/dev/null | grep -q libonnxruntime.so.1; then \
echo "ONNX Runtime is already installed:" && \
ldconfig -p 2>/dev/null | grep libonnxruntime && \
echo "" && \
echo "Skipping installation. To reinstall, remove existing libs first:" && \
echo " sudo rm -f /usr/local/lib/libonnxruntime*.so*" && \
exit 0; \
fi && \
echo "No ONNX Runtime found. Proceeding with installation..." && \
echo "" && \
echo "Detecting CUDA version..." && \
HAS_CUDA=0 && \
if command -v nvidia-smi >/dev/null 2>&1; then \
CUDA_INFO=$$(nvidia-smi --query-gpu=driver_version --format=csv,noheader 2>/dev/null | head -1) && \
if [ -n "$$CUDA_INFO" ]; then \
echo "Found NVIDIA GPU with driver: $$CUDA_INFO" && \
HAS_CUDA=1; \
else \
echo "NVIDIA driver found but could not detect CUDA version"; \
fi; \
else \
echo "No NVIDIA GPU detected (nvidia-smi not found)"; \
fi && \
echo "" && \
echo "Determining ONNX Runtime version..." && \
ARCH=$$(uname -m) && \
if [ "$$ARCH" = "x86_64" ]; then \
ONNX_ARCH="x64"; \
elif [ "$$ARCH" = "aarch64" ] || [ "$$ARCH" = "arm64" ]; then \
ONNX_ARCH="aarch64"; \
else \
echo "Unsupported architecture: $$ARCH" && \
exit 1; \
fi && \
echo "Detected architecture: $$ARCH (ONNX runtime: $$ONNX_ARCH)" && \
if [ "$$HAS_CUDA" = "1" ]; then \
echo "Installing ONNX Runtime with CUDA support..."; \
ONNX_VERSION="1.24.2"; \
else \
echo "Installing ONNX Runtime (CPU version)..."; \
ONNX_VERSION="1.24.2"; \
fi && \
FILENAME="onnxruntime-linux-$${ONNX_ARCH}-${ONNX_VERSION}.tgz" && \
URL="https://github.com/microsoft/onnxruntime/releases/download/v$${ONNX_VERSION}/$${FILENAME}" && \
echo "Downloading $${URL}..." && \
mkdir -p /tmp/onnx-install && \
curl -L -o /tmp/onnx-install/$${FILENAME} "$${URL}" || { \
echo "Failed to download ONNX Runtime v$${ONNX_VERSION}. Trying v1.18.0..." && \
ONNX_VERSION="1.18.0" && \
FILENAME="onnxruntime-linux-$${ONNX_ARCH}-${ONNX_VERSION}.tgz" && \
URL="https://github.com/microsoft/onnxruntime/releases/download/v$${ONNX_VERSION}/$${FILENAME}" && \
curl -L -o /tmp/onnx-install/$${FILENAME} "$${URL}" || { \
echo "ERROR: Failed to download ONNX Runtime from GitHub" && \
echo "" && \
echo "Please install manually:" && \
echo " 1. Go to https://github.com/microsoft/onnxruntime/releases" && \
echo " 2. Download onnxruntime-linux-$${ONNX_ARCH}-VERSION.tgz" && \
echo " 3. Extract and copy to /usr/local/lib:" && \
echo " tar -xzf onnxruntime-linux-$${ONNX_ARCH}-VERSION.tgz" && \
echo " sudo cp -r onnxruntime-linux-$${ONNX_ARCH}-VERSION/lib/* /usr/local/lib/" && \
echo " sudo ldconfig" && \
exit 1; \
}; \
} && \
echo "Extracting..." && \
cd /tmp/onnx-install && tar -xzf $${FILENAME} && \
echo "Installing to /usr/local/lib..." && \
ONNX_DIR=$$(find /tmp/onnx-install -maxdepth 1 -type d -name "onnxruntime-linux-*") && \
if [ -d "$${ONNX_DIR}/lib" ]; then \
cp -r $${ONNX_DIR}/lib/* /usr/local/lib/ 2>/dev/null || sudo cp -r $${ONNX_DIR}/lib/* /usr/local/lib/; \
else \
echo "ERROR: Could not find lib directory in extracted archive" && \
exit 1; \
fi && \
echo "Updating library cache..." && \
sudo ldconfig 2>/dev/null || ldconfig && \
echo "" && \
echo "=== Installation complete! ===" && \
echo "" && \
echo "Installed libraries:" && \
ldconfig -p | grep libonnxruntime || echo "(libraries may require logout/relogin to appear)" && \
echo "" && \
if [ "$$HAS_CUDA" = "1" ]; then \
echo "NOTE: CUDA-enabled ONNX Runtime installed."; \
echo "Ensure you also have CUDA libraries installed:"; \
echo " - libcudnn, libcublas, libcurand"; \
else \
echo "NOTE: CPU-only ONNX Runtime installed."; \
echo "For GPU support, install CUDA and re-run this script."; \
fi && \
rm -rf /tmp/onnx-install
# Whisper STT Setup (in batteries directory)
setup-whisper: build-whisper download-whisper-model

View File

@@ -38,8 +38,3 @@ func RegisterA(toolNames []string, a AgenterA) {
func Get(toolName string) AgenterB {
return RegistryB[toolName]
}
// Register is a convenience wrapper for RegisterB.
func Register(toolName string, a AgenterB) {
RegisterB(toolName, a)
}

View File

@@ -32,10 +32,10 @@ func detectAPI(api string) (isCompletion, isChat, isDeepSeek, isOpenRouter bool)
type AgentClient struct {
cfg *config.Config
getToken func() string
log slog.Logger
log *slog.Logger
}
func NewAgentClient(cfg *config.Config, log slog.Logger, gt func() string) *AgentClient {
func NewAgentClient(cfg *config.Config, log *slog.Logger, gt func() string) *AgentClient {
return &AgentClient{
cfg: cfg,
getToken: gt,
@@ -44,7 +44,7 @@ func NewAgentClient(cfg *config.Config, log slog.Logger, gt func() string) *Agen
}
func (ag *AgentClient) Log() *slog.Logger {
return &ag.log
return ag.log
}
func (ag *AgentClient) FormMsg(sysprompt, msg string) (io.Reader, error) {
@@ -63,11 +63,9 @@ func (ag *AgentClient) buildRequest(sysprompt, msg string) ([]byte, error) {
{Role: "system", Content: sysprompt},
{Role: "user", Content: msg},
}
// Determine API type
isCompletion, isChat, isDeepSeek, isOpenRouter := detectAPI(api)
ag.log.Debug("agent building request", "api", api, "isCompletion", isCompletion, "isChat", isChat, "isDeepSeek", isDeepSeek, "isOpenRouter", isOpenRouter)
// Build prompt for completion endpoints
if isCompletion {
var sb strings.Builder
@@ -76,7 +74,6 @@ func (ag *AgentClient) buildRequest(sysprompt, msg string) ([]byte, error) {
sb.WriteString("\n")
}
prompt := strings.TrimSpace(sb.String())
switch {
case isDeepSeek:
// DeepSeek completion
@@ -95,7 +92,6 @@ func (ag *AgentClient) buildRequest(sysprompt, msg string) ([]byte, error) {
return json.Marshal(req)
}
}
// Chat completions endpoints
if isChat || !isCompletion {
chatBody := &models.ChatBody{
@@ -103,7 +99,6 @@ func (ag *AgentClient) buildRequest(sysprompt, msg string) ([]byte, error) {
Stream: false, // Agents don't need streaming
Messages: messages,
}
switch {
case isDeepSeek:
// DeepSeek chat
@@ -122,7 +117,6 @@ func (ag *AgentClient) buildRequest(sysprompt, msg string) ([]byte, error) {
return json.Marshal(req)
}
}
// Fallback (should not reach here)
ag.log.Warn("unknown API, using default chat completions format", "api", api)
chatBody := &models.ChatBody{
@@ -165,7 +159,6 @@ func (ag *AgentClient) LLMRequest(body io.Reader) ([]byte, error) {
ag.log.Error("agent LLM request failed", "status", resp.StatusCode, "response", string(responseBytes[:min(len(responseBytes), 1000)]))
return responseBytes, fmt.Errorf("HTTP %d: %s", resp.StatusCode, string(responseBytes[:min(len(responseBytes), 200)]))
}
// Parse response and extract text content
text, err := extractTextFromResponse(responseBytes)
if err != nil {
@@ -179,17 +172,16 @@ func (ag *AgentClient) LLMRequest(body io.Reader) ([]byte, error) {
// extractTextFromResponse parses common LLM response formats and extracts the text content.
func extractTextFromResponse(data []byte) (string, error) {
// Try to parse as generic JSON first
var genericResp map[string]interface{}
var genericResp map[string]any
if err := json.Unmarshal(data, &genericResp); err != nil {
// Not JSON, return as string
return string(data), nil
}
// Check for OpenAI chat completion format
if choices, ok := genericResp["choices"].([]interface{}); ok && len(choices) > 0 {
if firstChoice, ok := choices[0].(map[string]interface{}); ok {
if choices, ok := genericResp["choices"].([]any); ok && len(choices) > 0 {
if firstChoice, ok := choices[0].(map[string]any); ok {
// Chat completion: choices[0].message.content
if message, ok := firstChoice["message"].(map[string]interface{}); ok {
if message, ok := firstChoice["message"].(map[string]any); ok {
if content, ok := message["content"].(string); ok {
return content, nil
}
@@ -199,19 +191,17 @@ func extractTextFromResponse(data []byte) (string, error) {
return text, nil
}
// Delta format for streaming (should not happen with stream: false)
if delta, ok := firstChoice["delta"].(map[string]interface{}); ok {
if delta, ok := firstChoice["delta"].(map[string]any); ok {
if content, ok := delta["content"].(string); ok {
return content, nil
}
}
}
}
// Check for llama.cpp completion format
if content, ok := genericResp["content"].(string); ok {
return content, nil
}
// Unknown format, return pretty-printed JSON
prettyJSON, err := json.MarshalIndent(genericResp, "", " ")
if err != nil {
@@ -219,10 +209,3 @@ func extractTextFromResponse(data []byte) (string, error) {
}
return string(prettyJSON), nil
}
func min(a, b int) int {
if a < b {
return a
}
return b
}

18
bot.go
View File

@@ -1393,16 +1393,12 @@ func updateModelLists() {
}
}
// if llama.cpp started after gf-lt?
ml, err := fetchLCPModelsWithLoadStatus()
localModelsMu.Lock()
LocalModels, err = fetchLCPModelsWithLoadStatus()
localModelsMu.Unlock()
if err != nil {
logger.Warn("failed to fetch llama.cpp models", "error", err)
}
localModelsMu.Lock()
LocalModels = ml
localModelsMu.Unlock()
for statusLineWidget == nil {
time.Sleep(time.Millisecond * 100)
}
// set already loaded model in llama.cpp
if strings.Contains(cfg.CurrentAPI, "localhost") || strings.Contains(cfg.CurrentAPI, "127.0.0.1") {
localModelsMu.Lock()
@@ -1504,13 +1500,7 @@ func init() {
os.Exit(1)
return
}
ragger, err = rag.New(logger, store, cfg)
if err != nil {
logger.Error("failed to create RAG", "error", err)
}
if ragger != nil && ragger.FallbackMessage() != "" && app != nil {
showToast("RAG", "ONNX unavailable, using API: "+ragger.FallbackMessage())
}
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

@@ -13,9 +13,6 @@ OpenRouterChatAPI = "https://openrouter.ai/api/v1/chat/completions"
# embeddings
EmbedURL = "http://localhost:8082/v1/embeddings"
HFToken = ""
EmbedModelPath = "onnx/embedgemma/model_q4.onnx"
EmbedTokenizerPath = "onnx/embedgemma/tokenizer.json"
EmbedDims = 768
#
ShowSys = true
LogFile = "log.txt"
@@ -27,9 +24,9 @@ ChunkLimit = 100000
AutoScrollEnabled = true
AutoCleanToolCallsFromCtx = false
# rag settings
RAGEnabled = false
RAGBatchSize = 1
RAGWordLimit = 80
RAGOverlapWords = 16
RAGDir = "ragimport"
# extra tts
TTS_ENABLED = false

View File

@@ -34,16 +34,13 @@ type Config struct {
ImagePreview bool `toml:"ImagePreview"`
EnableMouse bool `toml:"EnableMouse"`
// embeddings
EmbedURL string `toml:"EmbedURL"`
HFToken string `toml:"HFToken"`
EmbedModelPath string `toml:"EmbedModelPath"`
EmbedTokenizerPath string `toml:"EmbedTokenizerPath"`
EmbedDims int `toml:"EmbedDims"`
EmbedURL string `toml:"EmbedURL"`
HFToken string `toml:"HFToken"`
// rag settings
RAGDir string `toml:"RAGDir"`
RAGBatchSize int `toml:"RAGBatchSize"`
RAGWordLimit uint32 `toml:"RAGWordLimit"`
RAGOverlapWords uint32 `toml:"RAGOverlapWords"`
RAGEnabled bool `toml:"RAGEnabled"`
RAGDir string `toml:"RAGDir"`
RAGBatchSize int `toml:"RAGBatchSize"`
RAGWordLimit uint32 `toml:"RAGWordLimit"`
// deepseek
DeepSeekChatAPI string `toml:"DeepSeekChatAPI"`
DeepSeekCompletionAPI string `toml:"DeepSeekCompletionAPI"`

View File

@@ -71,6 +71,9 @@ This document explains how to set up and configure the application using the `co
#### EmbedURL (`"http://localhost:8082/v1/embeddings"`)
- The endpoint for embedding API, used for RAG (Retrieval Augmented Generation) functionality.
#### RAGEnabled (`false`)
- Enable or disable RAG functionality for enhanced context retrieval.
#### RAGBatchSize (`1`)
- Number of documents to process in each RAG batch.

View File

@@ -1,218 +0,0 @@
//go:build extra
// +build extra
package extra
import (
"fmt"
"gf-lt/models"
"io"
"log/slog"
"os/exec"
"strings"
"sync"
google_translate_tts "github.com/GrailFinder/google-translate-tts"
"github.com/neurosnap/sentences/english"
)
type GoogleTranslateOrator struct {
logger *slog.Logger
mu sync.Mutex
speech *google_translate_tts.Speech
// fields for playback control
cmd *exec.Cmd
cmdMu sync.Mutex
stopCh chan struct{}
// text buffer and interrupt flag
textBuffer strings.Builder
interrupt bool
Speed float32
}
func (o *GoogleTranslateOrator) stoproutine() {
for {
<-TTSDoneChan
o.logger.Debug("orator got done signal")
o.Stop()
for len(TTSTextChan) > 0 {
<-TTSTextChan
}
o.mu.Lock()
o.textBuffer.Reset()
o.interrupt = true
o.mu.Unlock()
}
}
func (o *GoogleTranslateOrator) readroutine() {
tokenizer, _ := english.NewSentenceTokenizer(nil)
for {
select {
case chunk := <-TTSTextChan:
o.mu.Lock()
o.interrupt = false
_, err := o.textBuffer.WriteString(chunk)
if err != nil {
o.logger.Warn("failed to write to stringbuilder", "error", err)
o.mu.Unlock()
continue
}
text := o.textBuffer.String()
sentences := tokenizer.Tokenize(text)
o.logger.Debug("adding chunk", "chunk", chunk, "text", text, "sen-len", len(sentences))
if len(sentences) <= 1 {
o.mu.Unlock()
continue
}
completeSentences := sentences[:len(sentences)-1]
remaining := sentences[len(sentences)-1].Text
o.textBuffer.Reset()
o.textBuffer.WriteString(remaining)
o.mu.Unlock()
for _, sentence := range completeSentences {
o.mu.Lock()
interrupted := o.interrupt
o.mu.Unlock()
if interrupted {
return
}
cleanedText := models.CleanText(sentence.Text)
if cleanedText == "" {
continue
}
o.logger.Debug("calling Speak with sentence", "sent", cleanedText)
if err := o.Speak(cleanedText); err != nil {
o.logger.Error("tts failed", "sentence", cleanedText, "error", err)
}
}
case <-TTSFlushChan:
o.logger.Debug("got flushchan signal start")
// lln is done get the whole message out
if len(TTSTextChan) > 0 { // otherwise might get stuck
for chunk := range TTSTextChan {
o.mu.Lock()
_, err := o.textBuffer.WriteString(chunk)
o.mu.Unlock()
if err != nil {
o.logger.Warn("failed to write to stringbuilder", "error", err)
continue
}
if len(TTSTextChan) == 0 {
break
}
}
}
o.mu.Lock()
remaining := o.textBuffer.String()
remaining = models.CleanText(remaining)
o.textBuffer.Reset()
o.mu.Unlock()
if remaining == "" {
continue
}
o.logger.Debug("calling Speak with remainder", "rem", remaining)
sentencesRem := tokenizer.Tokenize(remaining)
for _, rs := range sentencesRem { // to avoid dumping large volume of text
o.mu.Lock()
interrupt := o.interrupt
o.mu.Unlock()
if interrupt {
break
}
if err := o.Speak(rs.Text); err != nil {
o.logger.Error("tts failed", "sentence", rs.Text, "error", err)
}
}
}
}
}
func (o *GoogleTranslateOrator) GetLogger() *slog.Logger {
return o.logger
}
func (o *GoogleTranslateOrator) Speak(text string) error {
o.logger.Debug("fn: Speak is called", "text-len", len(text))
// Generate MP3 data directly as an io.Reader
reader, err := o.speech.GenerateSpeech(text)
if err != nil {
return fmt.Errorf("generate speech failed: %w", err)
}
// Wrap in io.NopCloser since GenerateSpeech returns io.Reader (no close needed)
body := io.NopCloser(reader)
defer body.Close()
// Build ffplay command with optional speed filter
args := []string{"-nodisp", "-autoexit"}
if o.Speed > 0.1 && o.Speed != 1.0 {
// atempo range is 0.5 to 2.0; you might clamp it here
args = append(args, "-af", fmt.Sprintf("atempo=%.2f", o.Speed))
}
args = append(args, "-i", "pipe:0")
cmd := exec.Command("ffplay", args...)
stdin, err := cmd.StdinPipe()
if err != nil {
return fmt.Errorf("failed to get stdin pipe: %w", err)
}
o.cmdMu.Lock()
o.cmd = cmd
o.stopCh = make(chan struct{})
o.cmdMu.Unlock()
if err := cmd.Start(); err != nil {
return fmt.Errorf("failed to start ffplay: %w", err)
}
copyErr := make(chan error, 1)
go func() {
_, err := io.Copy(stdin, body)
stdin.Close()
copyErr <- err
}()
done := make(chan error, 1)
go func() {
done <- cmd.Wait()
}()
select {
case <-o.stopCh:
if o.cmd != nil && o.cmd.Process != nil {
o.cmd.Process.Kill()
}
<-done
return nil
case copyErrVal := <-copyErr:
if copyErrVal != nil {
if o.cmd != nil && o.cmd.Process != nil {
o.cmd.Process.Kill()
}
<-done
return copyErrVal
}
return <-done
case err := <-done:
return err
}
}
func (o *GoogleTranslateOrator) Stop() {
o.cmdMu.Lock()
defer o.cmdMu.Unlock()
// Signal any running Speak to stop
if o.stopCh != nil {
select {
case <-o.stopCh: // already closed
default:
close(o.stopCh)
}
o.stopCh = nil
}
// Kill the external player process if it's still running
if o.cmd != nil && o.cmd.Process != nil {
o.cmd.Process.Kill()
o.cmd.Wait() // clean up zombie process
o.cmd = nil
}
// Also reset text buffer and interrupt flag (with o.mu)
o.mu.Lock()
o.textBuffer.Reset()
o.interrupt = true
o.mu.Unlock()
}

View File

@@ -1,259 +0,0 @@
//go:build extra
// +build extra
package extra
import (
"bytes"
"encoding/json"
"fmt"
"gf-lt/models"
"io"
"log/slog"
"net/http"
"os/exec"
"strings"
"sync"
"github.com/neurosnap/sentences/english"
)
type KokoroOrator struct {
logger *slog.Logger
mu sync.Mutex
URL string
Format models.AudioFormat
Stream bool
Speed float32
Language string
Voice string
// fields for playback control
cmd *exec.Cmd
cmdMu sync.Mutex
stopCh chan struct{}
// textBuffer, interrupt etc. remain the same
textBuffer strings.Builder
interrupt bool
}
func (o *KokoroOrator) GetLogger() *slog.Logger {
return o.logger
}
func (o *KokoroOrator) Speak(text string) error {
o.logger.Debug("fn: Speak is called", "text-len", len(text))
body, err := o.requestSound(text)
if err != nil {
return fmt.Errorf("request failed: %w", err)
}
defer body.Close()
cmd := exec.Command("ffplay", "-nodisp", "-autoexit", "-i", "pipe:0")
stdin, err := cmd.StdinPipe()
if err != nil {
return fmt.Errorf("failed to get stdin pipe: %w", err)
}
o.cmdMu.Lock()
o.cmd = cmd
o.stopCh = make(chan struct{})
o.cmdMu.Unlock()
if err := cmd.Start(); err != nil {
return fmt.Errorf("failed to start ffplay: %w", err)
}
// Copy audio in background
copyErr := make(chan error, 1)
go func() {
_, err := io.Copy(stdin, body)
stdin.Close()
copyErr <- err
}()
// Wait for player in background
done := make(chan error, 1)
go func() {
done <- cmd.Wait()
}()
// Wait for BOTH copy and player, but ensure we block until done
select {
case <-o.stopCh:
// Stop requested: kill player and wait for it to exit
if o.cmd != nil && o.cmd.Process != nil {
o.cmd.Process.Kill()
}
<-done // Wait for process to actually exit
return nil
case copyErrVal := <-copyErr:
if copyErrVal != nil {
// Copy failed: kill player and wait
if o.cmd != nil && o.cmd.Process != nil {
o.cmd.Process.Kill()
}
<-done
return copyErrVal
}
// Copy succeeded, now wait for playback to complete
return <-done
case err := <-done:
// Playback finished normally (copy must have succeeded or player would have exited early)
return err
}
}
func (o *KokoroOrator) requestSound(text string) (io.ReadCloser, error) {
if o.URL == "" {
return nil, fmt.Errorf("TTS URL is empty")
}
payload := map[string]interface{}{
"input": text,
"voice": o.Voice,
"response_format": o.Format,
"download_format": o.Format,
"stream": o.Stream,
"speed": o.Speed,
// "return_download_link": true,
"lang_code": o.Language,
}
payloadBytes, err := json.Marshal(payload)
if err != nil {
return nil, fmt.Errorf("failed to marshal payload: %w", err)
}
req, err := http.NewRequest("POST", o.URL, bytes.NewBuffer(payloadBytes)) //nolint:noctx
if err != nil {
return nil, fmt.Errorf("failed to create request: %w", err)
}
req.Header.Set("accept", "application/json")
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
return nil, fmt.Errorf("request failed: %w", err)
}
if resp.StatusCode != http.StatusOK {
defer resp.Body.Close()
return nil, fmt.Errorf("unexpected status code: %d", resp.StatusCode)
}
return resp.Body, nil
}
func (o *KokoroOrator) stoproutine() {
for {
<-TTSDoneChan
o.logger.Debug("orator got done signal")
// 1. Stop any ongoing playback (kills external player, closes stopCh)
o.Stop()
// 2. Drain any pending text chunks
for len(TTSTextChan) > 0 {
<-TTSTextChan
}
// 3. Reset internal state
o.mu.Lock()
o.textBuffer.Reset()
o.interrupt = true
o.mu.Unlock()
}
}
func (o *KokoroOrator) Stop() {
o.cmdMu.Lock()
defer o.cmdMu.Unlock()
// Signal any running Speak to stop
if o.stopCh != nil {
select {
case <-o.stopCh: // already closed
default:
close(o.stopCh)
}
o.stopCh = nil
}
// Kill the external player process if it's still running
if o.cmd != nil && o.cmd.Process != nil {
o.cmd.Process.Kill()
o.cmd.Wait() // clean up zombie process
o.cmd = nil
}
// Also reset text buffer and interrupt flag (with o.mu)
o.mu.Lock()
o.textBuffer.Reset()
o.interrupt = true
o.mu.Unlock()
}
func (o *KokoroOrator) readroutine() {
tokenizer, _ := english.NewSentenceTokenizer(nil)
for {
select {
case chunk := <-TTSTextChan:
o.mu.Lock()
o.interrupt = false
_, err := o.textBuffer.WriteString(chunk)
if err != nil {
o.logger.Warn("failed to write to stringbuilder", "error", err)
o.mu.Unlock()
continue
}
text := o.textBuffer.String()
sentences := tokenizer.Tokenize(text)
o.logger.Debug("adding chunk", "chunk", chunk, "text", text, "sen-len", len(sentences))
if len(sentences) <= 1 {
o.mu.Unlock()
continue
}
completeSentences := sentences[:len(sentences)-1]
remaining := sentences[len(sentences)-1].Text
o.textBuffer.Reset()
o.textBuffer.WriteString(remaining)
o.mu.Unlock()
for _, sentence := range completeSentences {
o.mu.Lock()
interrupted := o.interrupt
o.mu.Unlock()
if interrupted {
return
}
cleanedText := models.CleanText(sentence.Text)
if cleanedText == "" {
continue
}
o.logger.Debug("calling Speak with sentence", "sent", cleanedText)
if err := o.Speak(cleanedText); err != nil {
o.logger.Error("tts failed", "sentence", cleanedText, "error", err)
}
}
case <-TTSFlushChan:
o.logger.Debug("got flushchan signal start")
// lln is done get the whole message out
if len(TTSTextChan) > 0 { // otherwise might get stuck
for chunk := range TTSTextChan {
o.mu.Lock()
_, err := o.textBuffer.WriteString(chunk)
o.mu.Unlock()
if err != nil {
o.logger.Warn("failed to write to stringbuilder", "error", err)
continue
}
if len(TTSTextChan) == 0 {
break
}
}
}
// flush remaining text
o.mu.Lock()
remaining := o.textBuffer.String()
remaining = models.CleanText(remaining)
o.textBuffer.Reset()
o.mu.Unlock()
if remaining == "" {
continue
}
o.logger.Debug("calling Speak with remainder", "rem", remaining)
sentencesRem := tokenizer.Tokenize(remaining)
for _, rs := range sentencesRem { // to avoid dumping large volume of text
o.mu.Lock()
interrupt := o.interrupt
o.mu.Unlock()
if interrupt {
break
}
if err := o.Speak(rs.Text); err != nil {
o.logger.Error("tts failed", "sentence", rs, "error", err)
}
}
}
}
}

View File

@@ -4,13 +4,25 @@
package extra
import (
"bytes"
"encoding/json"
"fmt"
"gf-lt/config"
"gf-lt/models"
"io"
"log/slog"
"net/http"
"os"
"strings"
"sync"
"time"
google_translate_tts "github.com/GrailFinder/google-translate-tts"
"github.com/GrailFinder/google-translate-tts/handlers"
"github.com/gopxl/beep/v2"
"github.com/gopxl/beep/v2/mp3"
"github.com/gopxl/beep/v2/speaker"
"github.com/neurosnap/sentences/english"
)
var (
@@ -27,6 +39,142 @@ type Orator interface {
GetLogger() *slog.Logger
}
// impl https://github.com/remsky/Kokoro-FastAPI
type KokoroOrator struct {
logger *slog.Logger
mu sync.Mutex
URL string
Format models.AudioFormat
Stream bool
Speed float32
Language string
Voice string
currentStream *beep.Ctrl // Added for playback control
currentDone chan bool
textBuffer strings.Builder
interrupt bool
// textBuffer bytes.Buffer
}
// Google Translate TTS implementation
type GoogleTranslateOrator struct {
logger *slog.Logger
mu sync.Mutex
speech *google_translate_tts.Speech
currentStream *beep.Ctrl
currentDone chan bool
textBuffer strings.Builder
interrupt bool
}
func (o *KokoroOrator) stoproutine() {
for {
<-TTSDoneChan
o.logger.Debug("orator got done signal")
o.Stop()
// drain the channel
for len(TTSTextChan) > 0 {
<-TTSTextChan
}
o.mu.Lock()
o.textBuffer.Reset()
if o.currentDone != nil {
select {
case o.currentDone <- true:
default:
// Channel might be closed, ignore
}
}
o.interrupt = true
o.mu.Unlock()
}
}
func (o *KokoroOrator) readroutine() {
tokenizer, _ := english.NewSentenceTokenizer(nil)
for {
select {
case chunk := <-TTSTextChan:
o.mu.Lock()
o.interrupt = false
_, err := o.textBuffer.WriteString(chunk)
if err != nil {
o.logger.Warn("failed to write to stringbuilder", "error", err)
o.mu.Unlock()
continue
}
text := o.textBuffer.String()
sentences := tokenizer.Tokenize(text)
o.logger.Debug("adding chunk", "chunk", chunk, "text", text, "sen-len", len(sentences))
if len(sentences) <= 1 {
o.mu.Unlock()
continue
}
completeSentences := sentences[:len(sentences)-1]
remaining := sentences[len(sentences)-1].Text
o.textBuffer.Reset()
o.textBuffer.WriteString(remaining)
o.mu.Unlock()
for _, sentence := range completeSentences {
o.mu.Lock()
interrupted := o.interrupt
o.mu.Unlock()
if interrupted {
return
}
cleanedText := models.CleanText(sentence.Text)
if cleanedText == "" {
continue
}
o.logger.Debug("calling Speak with sentence", "sent", cleanedText)
if err := o.Speak(cleanedText); err != nil {
o.logger.Error("tts failed", "sentence", cleanedText, "error", err)
}
}
case <-TTSFlushChan:
o.logger.Debug("got flushchan signal start")
// lln is done get the whole message out
if len(TTSTextChan) > 0 { // otherwise might get stuck
for chunk := range TTSTextChan {
o.mu.Lock()
_, err := o.textBuffer.WriteString(chunk)
o.mu.Unlock()
if err != nil {
o.logger.Warn("failed to write to stringbuilder", "error", err)
continue
}
if len(TTSTextChan) == 0 {
break
}
}
}
// flush remaining text
o.mu.Lock()
remaining := o.textBuffer.String()
remaining = models.CleanText(remaining)
o.textBuffer.Reset()
o.mu.Unlock()
if remaining == "" {
continue
}
o.logger.Debug("calling Speak with remainder", "rem", remaining)
sentencesRem := tokenizer.Tokenize(remaining)
for _, rs := range sentencesRem { // to avoid dumping large volume of text
o.mu.Lock()
interrupt := o.interrupt
o.mu.Unlock()
if interrupt {
break
}
if err := o.Speak(rs.Text); err != nil {
o.logger.Error("tts failed", "sentence", rs, "error", err)
}
}
}
}
}
func NewOrator(log *slog.Logger, cfg *config.Config) Orator {
provider := cfg.TTS_PROVIDER
if provider == "" {
@@ -56,14 +204,270 @@ func NewOrator(log *slog.Logger, cfg *config.Config) Orator {
Language: language,
Proxy: "", // Proxy not supported
Speed: cfg.TTS_SPEED,
Handler: &handlers.Beep{},
}
orator := &GoogleTranslateOrator{
logger: log,
speech: speech,
Speed: cfg.TTS_SPEED,
}
go orator.readroutine()
go orator.stoproutine()
return orator
}
}
func (o *KokoroOrator) GetLogger() *slog.Logger {
return o.logger
}
func (o *KokoroOrator) requestSound(text string) (io.ReadCloser, error) {
if o.URL == "" {
return nil, fmt.Errorf("TTS URL is empty")
}
payload := map[string]interface{}{
"input": text,
"voice": o.Voice,
"response_format": o.Format,
"download_format": o.Format,
"stream": o.Stream,
"speed": o.Speed,
// "return_download_link": true,
"lang_code": o.Language,
}
payloadBytes, err := json.Marshal(payload)
if err != nil {
return nil, fmt.Errorf("failed to marshal payload: %w", err)
}
req, err := http.NewRequest("POST", o.URL, bytes.NewBuffer(payloadBytes)) //nolint:noctx
if err != nil {
return nil, fmt.Errorf("failed to create request: %w", err)
}
req.Header.Set("accept", "application/json")
req.Header.Set("Content-Type", "application/json")
resp, err := http.DefaultClient.Do(req)
if err != nil {
return nil, fmt.Errorf("request failed: %w", err)
}
if resp.StatusCode != http.StatusOK {
defer resp.Body.Close()
return nil, fmt.Errorf("unexpected status code: %d", resp.StatusCode)
}
return resp.Body, nil
}
func (o *KokoroOrator) Speak(text string) error {
o.logger.Debug("fn: Speak is called", "text-len", len(text))
body, err := o.requestSound(text)
if err != nil {
o.logger.Error("request failed", "error", err)
return fmt.Errorf("request failed: %w", err)
}
defer body.Close()
// Decode the mp3 audio from response body
streamer, format, err := mp3.Decode(body)
if err != nil {
o.logger.Error("mp3 decode failed", "error", err)
return fmt.Errorf("mp3 decode failed: %w", err)
}
defer streamer.Close()
// here it spams with errors that speaker cannot be initialized more than once, but how would we deal with many audio records then?
if err := speaker.Init(format.SampleRate, format.SampleRate.N(time.Second/10)); err != nil {
o.logger.Debug("failed to init speaker", "error", err)
}
done := make(chan bool)
o.mu.Lock()
o.currentDone = done
o.currentStream = &beep.Ctrl{Streamer: beep.Seq(streamer, beep.Callback(func() {
o.mu.Lock()
close(done)
o.currentStream = nil
o.currentDone = nil
o.mu.Unlock()
})), Paused: false}
o.mu.Unlock()
speaker.Play(o.currentStream)
<-done
return nil
}
func (o *KokoroOrator) Stop() {
// speaker.Clear()
o.logger.Debug("attempted to stop orator", "orator", o)
speaker.Lock()
defer speaker.Unlock()
o.mu.Lock()
defer o.mu.Unlock()
if o.currentStream != nil {
// o.currentStream.Paused = true
o.currentStream.Streamer = nil
}
}
func (o *GoogleTranslateOrator) stoproutine() {
for {
<-TTSDoneChan
o.logger.Debug("orator got done signal")
o.Stop()
// drain the channel
for len(TTSTextChan) > 0 {
<-TTSTextChan
}
o.mu.Lock()
o.textBuffer.Reset()
if o.currentDone != nil {
select {
case o.currentDone <- true:
default:
// Channel might be closed, ignore
}
}
o.interrupt = true
o.mu.Unlock()
}
}
func (o *GoogleTranslateOrator) readroutine() {
tokenizer, _ := english.NewSentenceTokenizer(nil)
for {
select {
case chunk := <-TTSTextChan:
o.mu.Lock()
o.interrupt = false
_, err := o.textBuffer.WriteString(chunk)
if err != nil {
o.logger.Warn("failed to write to stringbuilder", "error", err)
o.mu.Unlock()
continue
}
text := o.textBuffer.String()
sentences := tokenizer.Tokenize(text)
o.logger.Debug("adding chunk", "chunk", chunk, "text", text, "sen-len", len(sentences))
if len(sentences) <= 1 {
o.mu.Unlock()
continue
}
completeSentences := sentences[:len(sentences)-1]
remaining := sentences[len(sentences)-1].Text
o.textBuffer.Reset()
o.textBuffer.WriteString(remaining)
o.mu.Unlock()
for _, sentence := range completeSentences {
o.mu.Lock()
interrupted := o.interrupt
o.mu.Unlock()
if interrupted {
return
}
cleanedText := models.CleanText(sentence.Text)
if cleanedText == "" {
continue
}
o.logger.Debug("calling Speak with sentence", "sent", cleanedText)
if err := o.Speak(cleanedText); err != nil {
o.logger.Error("tts failed", "sentence", cleanedText, "error", err)
}
}
case <-TTSFlushChan:
o.logger.Debug("got flushchan signal start")
// lln is done get the whole message out
if len(TTSTextChan) > 0 { // otherwise might get stuck
for chunk := range TTSTextChan {
o.mu.Lock()
_, err := o.textBuffer.WriteString(chunk)
o.mu.Unlock()
if err != nil {
o.logger.Warn("failed to write to stringbuilder", "error", err)
continue
}
if len(TTSTextChan) == 0 {
break
}
}
}
o.mu.Lock()
remaining := o.textBuffer.String()
remaining = models.CleanText(remaining)
o.textBuffer.Reset()
o.mu.Unlock()
if remaining == "" {
continue
}
o.logger.Debug("calling Speak with remainder", "rem", remaining)
sentencesRem := tokenizer.Tokenize(remaining)
for _, rs := range sentencesRem { // to avoid dumping large volume of text
o.mu.Lock()
interrupt := o.interrupt
o.mu.Unlock()
if interrupt {
break
}
if err := o.Speak(rs.Text); err != nil {
o.logger.Error("tts failed", "sentence", rs.Text, "error", err)
}
}
}
}
}
func (o *GoogleTranslateOrator) GetLogger() *slog.Logger {
return o.logger
}
func (o *GoogleTranslateOrator) Speak(text string) error {
o.logger.Debug("fn: Speak is called", "text-len", len(text))
// Generate MP3 data using google-translate-tts
reader, err := o.speech.GenerateSpeech(text)
if err != nil {
o.logger.Error("generate speech failed", "error", err)
return fmt.Errorf("generate speech failed: %w", err)
}
// Decode the mp3 audio from reader (wrap with NopCloser for io.ReadCloser)
streamer, format, err := mp3.Decode(io.NopCloser(reader))
if err != nil {
o.logger.Error("mp3 decode failed", "error", err)
return fmt.Errorf("mp3 decode failed: %w", err)
}
defer streamer.Close()
playbackStreamer := beep.Streamer(streamer)
speed := o.speech.Speed
if speed <= 0 {
speed = 1.0
}
if speed != 1.0 {
playbackStreamer = beep.ResampleRatio(3, float64(speed), streamer)
}
// Initialize speaker with the format's sample rate
if err := speaker.Init(format.SampleRate, format.SampleRate.N(time.Second/10)); err != nil {
o.logger.Debug("failed to init speaker", "error", err)
}
done := make(chan bool)
o.mu.Lock()
o.currentDone = done
o.currentStream = &beep.Ctrl{Streamer: beep.Seq(playbackStreamer, beep.Callback(func() {
o.mu.Lock()
close(done)
o.currentStream = nil
o.currentDone = nil
o.mu.Unlock()
})), Paused: false}
o.mu.Unlock()
speaker.Play(o.currentStream)
<-done // wait for playback to complete
return nil
}
func (o *GoogleTranslateOrator) Stop() {
o.logger.Debug("attempted to stop google translate orator")
speaker.Lock()
defer speaker.Unlock()
o.mu.Lock()
defer o.mu.Unlock()
if o.currentStream != nil {
o.currentStream.Streamer = nil
}
// Also stop the speech handler if possible
if o.speech != nil {
_ = o.speech.Stop()
}
}

16
go.mod
View File

@@ -4,41 +4,39 @@ go 1.25.1
require (
github.com/BurntSushi/toml v1.5.0
github.com/GrailFinder/google-translate-tts v0.1.4
github.com/GrailFinder/google-translate-tts v0.1.3
github.com/GrailFinder/searchagent v0.2.0
github.com/PuerkitoBio/goquery v1.11.0
github.com/deckarep/golang-set/v2 v2.8.0
github.com/gdamore/tcell/v2 v2.13.2
github.com/glebarez/go-sqlite v1.22.0
github.com/gopxl/beep/v2 v2.1.1
github.com/gordonklaus/portaudio v0.0.0-20250206071425-98a94950218b
github.com/jmoiron/sqlx v1.4.0
github.com/ledongthuc/pdf v0.0.0-20250511090121-5959a4027728
github.com/neurosnap/sentences v1.1.2
github.com/playwright-community/playwright-go v0.5700.1
github.com/rivo/tview v0.42.0
github.com/sugarme/tokenizer v0.3.0
github.com/yalue/onnxruntime_go v1.27.0
github.com/yuin/goldmark v1.4.13
)
require (
github.com/andybalholm/cascadia v1.3.3 // indirect
github.com/deckarep/golang-set/v2 v2.8.0 // indirect
github.com/dustin/go-humanize v1.0.1 // indirect
github.com/emirpasic/gods v1.18.1 // indirect
github.com/ebitengine/oto/v3 v3.4.0 // indirect
github.com/ebitengine/purego v0.9.1 // indirect
github.com/gdamore/encoding v1.0.1 // indirect
github.com/go-jose/go-jose/v3 v3.0.4 // indirect
github.com/go-stack/stack v1.8.1 // indirect
github.com/google/uuid v1.6.0 // indirect
github.com/hajimehoshi/go-mp3 v0.3.4 // indirect
github.com/hajimehoshi/oto/v2 v2.3.1 // indirect
github.com/lucasb-eyer/go-colorful v1.3.0 // indirect
github.com/mattn/go-isatty v0.0.20 // indirect
github.com/mitchellh/colorstring v0.0.0-20190213212951-d06e56a500db // indirect
github.com/ncruces/go-strftime v1.0.0 // indirect
github.com/patrickmn/go-cache v2.1.0+incompatible // indirect
github.com/pkg/errors v0.9.1 // indirect
github.com/remyoudompheng/bigfft v0.0.0-20230129092748-24d4a6f8daec // indirect
github.com/rivo/uniseg v0.4.7 // indirect
github.com/schollz/progressbar/v2 v2.15.0 // indirect
github.com/sugarme/regexpset v0.0.0-20200920021344-4d4ec8eaf93c // indirect
golang.org/x/exp v0.0.0-20251209150349-8475f28825e9 // indirect
golang.org/x/net v0.48.0 // indirect
golang.org/x/sys v0.39.0 // indirect

28
go.sum
View File

@@ -2,8 +2,8 @@ filippo.io/edwards25519 v1.1.0 h1:FNf4tywRC1HmFuKW5xopWpigGjJKiJSV0Cqo0cJWDaA=
filippo.io/edwards25519 v1.1.0/go.mod h1:BxyFTGdWcka3PhytdK4V28tE5sGfRvvvRV7EaN4VDT4=
github.com/BurntSushi/toml v1.5.0 h1:W5quZX/G/csjUnuI8SUYlsHs9M38FC7znL0lIO+DvMg=
github.com/BurntSushi/toml v1.5.0/go.mod h1:ukJfTF/6rtPPRCnwkur4qwRxa8vTRFBF0uk2lLoLwho=
github.com/GrailFinder/google-translate-tts v0.1.4 h1:NJoPZUGfBrmouQMN19MUcNPNUx4tmf4a8OZRME4E4Mg=
github.com/GrailFinder/google-translate-tts v0.1.4/go.mod h1:YIOLKR7sObazdUCrSex3u9OVBovU55eYgWa25vsQJ18=
github.com/GrailFinder/google-translate-tts v0.1.3 h1:Mww9tNzTWjjSh+OCbTPl/+21oMPKcUecXZfU7nTB/lA=
github.com/GrailFinder/google-translate-tts v0.1.3/go.mod h1:YIOLKR7sObazdUCrSex3u9OVBovU55eYgWa25vsQJ18=
github.com/GrailFinder/searchagent v0.2.0 h1:U2GVjLh/9xZt0xX9OcYk9Q2fMkyzyTiADPUmUisRdtQ=
github.com/GrailFinder/searchagent v0.2.0/go.mod h1:d66tn5+22LI8IGJREUsRBT60P0sFdgQgvQRqyvgItrs=
github.com/PuerkitoBio/goquery v1.11.0 h1:jZ7pwMQXIITcUXNH83LLk+txlaEy6NVOfTuP43xxfqw=
@@ -17,8 +17,10 @@ github.com/deckarep/golang-set/v2 v2.8.0 h1:swm0rlPCmdWn9mESxKOjWk8hXSqoxOp+Zlfu
github.com/deckarep/golang-set/v2 v2.8.0/go.mod h1:VAky9rY/yGXJOLEDv3OMci+7wtDpOF4IN+y82NBOac4=
github.com/dustin/go-humanize v1.0.1 h1:GzkhY7T5VNhEkwH0PVJgjz+fX1rhBrR7pRT3mDkpeCY=
github.com/dustin/go-humanize v1.0.1/go.mod h1:Mu1zIs6XwVuF/gI1OepvI0qD18qycQx+mFykh5fBlto=
github.com/emirpasic/gods v1.18.1 h1:FXtiHYKDGKCW2KzwZKx0iC0PQmdlorYgdFG9jPXJ1Bc=
github.com/emirpasic/gods v1.18.1/go.mod h1:8tpGGwCnJ5H4r6BWwaV6OrWmMoPhUl5jm/FMNAnJvWQ=
github.com/ebitengine/oto/v3 v3.4.0 h1:br0PgASsEWaoWn38b2Goe7m1GKFYfNgnsjSd5Gg+/bQ=
github.com/ebitengine/oto/v3 v3.4.0/go.mod h1:IOleLVD0m+CMak3mRVwsYY8vTctQgOM0iiL6S7Ar7eI=
github.com/ebitengine/purego v0.9.1 h1:a/k2f2HQU3Pi399RPW1MOaZyhKJL9w/xFpKAg4q1s0A=
github.com/ebitengine/purego v0.9.1/go.mod h1:iIjxzd6CiRiOG0UyXP+V1+jWqUXVjPKLAI0mRfJZTmQ=
github.com/gdamore/encoding v1.0.1 h1:YzKZckdBL6jVt2Gc+5p82qhrGiqMdG/eNs6Wy0u3Uhw=
github.com/gdamore/encoding v1.0.1/go.mod h1:0Z0cMFinngz9kS1QfMjCP8TY7em3bZYeeklsSDPivEo=
github.com/gdamore/tcell/v2 v2.13.2 h1:5j4srfF8ow3HICOv/61/sOhQtA25qxEB2XR3Q/Bhx2g=
@@ -37,10 +39,13 @@ github.com/google/pprof v0.0.0-20250317173921-a4b03ec1a45e h1:ijClszYn+mADRFY17k
github.com/google/pprof v0.0.0-20250317173921-a4b03ec1a45e/go.mod h1:boTsfXsheKC2y+lKOCMpSfarhxDeIzfZG1jqGcPl3cA=
github.com/google/uuid v1.6.0 h1:NIvaJDMOsjHA8n1jAhLSgzrAzy1Hgr+hNrb57e+94F0=
github.com/google/uuid v1.6.0/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
github.com/gopxl/beep/v2 v2.1.1 h1:6FYIYMm2qPAdWkjX+7xwKrViS1x0Po5kDMdRkq8NVbU=
github.com/gopxl/beep/v2 v2.1.1/go.mod h1:ZAm9TGQ9lvpoiFLd4zf5B1IuyxZhgRACMId1XJbaW0E=
github.com/gordonklaus/portaudio v0.0.0-20250206071425-98a94950218b h1:WEuQWBxelOGHA6z9lABqaMLMrfwVyMdN3UgRLT+YUPo=
github.com/gordonklaus/portaudio v0.0.0-20250206071425-98a94950218b/go.mod h1:esZFQEUwqC+l76f2R8bIWSwXMaPbp79PppwZ1eJhFco=
github.com/hajimehoshi/go-mp3 v0.3.4 h1:NUP7pBYH8OguP4diaTZ9wJbUbk3tC0KlfzsEpWmYj68=
github.com/hajimehoshi/go-mp3 v0.3.4/go.mod h1:fRtZraRFcWb0pu7ok0LqyFhCUrPeMsGRSVop0eemFmo=
github.com/hajimehoshi/oto/v2 v2.3.1 h1:qrLKpNus2UfD674oxckKjNJmesp9hMh7u7QCrStB3Rc=
github.com/hajimehoshi/oto/v2 v2.3.1/go.mod h1:seWLbgHH7AyUMYKfKYT9pg7PhUu9/SisyJvNTT+ASQo=
github.com/hashicorp/golang-lru/v2 v2.0.7 h1:a+bsQ5rvGLjzHuww6tVxozPZFVghXaHOwFs4luLUK2k=
github.com/hashicorp/golang-lru/v2 v2.0.7/go.mod h1:QeFd9opnmA6QUJc5vARoKUSoFhyfM2/ZepoAG6RGpeM=
@@ -56,14 +61,12 @@ github.com/mattn/go-isatty v0.0.20 h1:xfD0iDuEKnDkl03q4limB+vH+GxLEtL/jb4xVJSWWE
github.com/mattn/go-isatty v0.0.20/go.mod h1:W+V8PltTTMOvKvAeJH7IuucS94S2C6jfK/D7dTCTo3Y=
github.com/mattn/go-sqlite3 v1.14.22 h1:2gZY6PC6kBnID23Tichd1K+Z0oS6nE/XwU+Vz/5o4kU=
github.com/mattn/go-sqlite3 v1.14.22/go.mod h1:Uh1q+B4BYcTPb+yiD3kU8Ct7aC0hY9fxUwlHK0RXw+Y=
github.com/mitchellh/colorstring v0.0.0-20190213212951-d06e56a500db h1:62I3jR2EmQ4l5rM/4FEfDWcRD+abF5XlKShorW5LRoQ=
github.com/mitchellh/colorstring v0.0.0-20190213212951-d06e56a500db/go.mod h1:l0dey0ia/Uv7NcFFVbCLtqEBQbrT4OCwCSKTEv6enCw=
github.com/ncruces/go-strftime v1.0.0 h1:HMFp8mLCTPp341M/ZnA4qaf7ZlsbTc+miZjCLOFAw7w=
github.com/ncruces/go-strftime v1.0.0/go.mod h1:Fwc5htZGVVkseilnfgOVb9mKy6w1naJmn9CehxcKcls=
github.com/neurosnap/sentences v1.1.2 h1:iphYOzx/XckXeBiLIUBkPu2EKMJ+6jDbz/sLJZ7ZoUw=
github.com/neurosnap/sentences v1.1.2/go.mod h1:/pwU4E9XNL21ygMIkOIllv/SMy2ujHwpf8GQPu1YPbQ=
github.com/patrickmn/go-cache v2.1.0+incompatible h1:HRMgzkcYKYpi3C8ajMPV8OFXaaRUnok+kx1WdO15EQc=
github.com/patrickmn/go-cache v2.1.0+incompatible/go.mod h1:3Qf8kWWT7OJRJbdiICTKqZju1ZixQ/KpMGzzAfe6+WQ=
github.com/pkg/errors v0.9.1 h1:FEBLx1zS214owpjy7qsBeixbURkuhQAwrK5UwLGTwt4=
github.com/pkg/errors v0.9.1/go.mod h1:bwawxfHBFNV+L2hUp1rHADufV3IMtnDRdf1r5NINEl0=
github.com/playwright-community/playwright-go v0.5700.1 h1:PNFb1byWqrTT720rEO0JL88C6Ju0EmUnR5deFLvtP/U=
github.com/playwright-community/playwright-go v0.5700.1/go.mod h1:MlSn1dZrx8rszbCxY6x3qK89ZesJUYVx21B2JnkoNF0=
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
@@ -74,19 +77,10 @@ github.com/rivo/tview v0.42.0 h1:b/ftp+RxtDsHSaynXTbJb+/n/BxDEi+W3UfF5jILK6c=
github.com/rivo/tview v0.42.0/go.mod h1:cSfIYfhpSGCjp3r/ECJb+GKS7cGJnqV8vfjQPwoXyfY=
github.com/rivo/uniseg v0.4.7 h1:WUdvkW8uEhrYfLC4ZzdpI2ztxP1I582+49Oc5Mq64VQ=
github.com/rivo/uniseg v0.4.7/go.mod h1:FN3SvrM+Zdj16jyLfmOkMNblXMcoc8DfTHruCPUcx88=
github.com/schollz/progressbar/v2 v2.15.0 h1:dVzHQ8fHRmtPjD3K10jT3Qgn/+H+92jhPrhmxIJfDz8=
github.com/schollz/progressbar/v2 v2.15.0/go.mod h1:UdPq3prGkfQ7MOzZKlDRpYKcFqEMczbD7YmbPgpzKMI=
github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=
github.com/stretchr/testify v1.7.0/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
github.com/stretchr/testify v1.10.0 h1:Xv5erBjTwe/5IxqUQTdXv5kgmIvbHo3QQyRwhJsOfJA=
github.com/stretchr/testify v1.10.0/go.mod h1:r2ic/lqez/lEtzL7wO/rwa5dbSLXVDPFyf8C91i36aY=
github.com/sugarme/regexpset v0.0.0-20200920021344-4d4ec8eaf93c h1:pwb4kNSHb4K89ymCaN+5lPH/MwnfSVg4rzGDh4d+iy4=
github.com/sugarme/regexpset v0.0.0-20200920021344-4d4ec8eaf93c/go.mod h1:2gwkXLWbDGUQWeL3RtpCmcY4mzCtU13kb9UsAg9xMaw=
github.com/sugarme/tokenizer v0.3.0 h1:FE8DYbNSz/kSbgEo9l/RjgYHkIJYEdskumitFQBE9FE=
github.com/sugarme/tokenizer v0.3.0/go.mod h1:VJ+DLK5ZEZwzvODOWwY0cw+B1dabTd3nCB5HuFCItCc=
github.com/yalue/onnxruntime_go v1.27.0 h1:c1YSgDNtpf0WGtxj3YeRIb8VC5LmM1J+Ve3uHdteC1U=
github.com/yalue/onnxruntime_go v1.27.0/go.mod h1:b4X26A8pekNb1ACJ58wAXgNKeUCGEAQ9dmACut9Sm/4=
github.com/yuin/goldmark v1.4.13 h1:fVcFKWvrslecOb/tg+Cc05dkeYx540o0FuFt3nUVDoE=
github.com/yuin/goldmark v1.4.13/go.mod h1:6yULJ656Px+3vBD8DxQVa3kxgyrAnzto9xy5taEt/CY=
golang.org/x/crypto v0.0.0-20190308221718-c2843e01d9a2/go.mod h1:djNgcEr1/C05ACkg1iLfiJU5Ep61QUkGW8qpdssI0+w=

View File

@@ -521,7 +521,7 @@ func updateFlexLayout() {
if shellMode {
flex.AddItem(shellInput, 0, 10, false)
} else {
flex.AddItem(bottomFlex, 0, 10, true)
flex.AddItem(textArea, 0, 10, false)
}
if positionVisible {
flex.AddItem(statusLineWidget, 0, 2, false)

View File

@@ -115,6 +115,9 @@ func makePropsTable(props map[string]float32) *tview.Table {
row++
}
// Add checkboxes
addCheckboxRow("RAG use", cfg.RAGEnabled, func(checked bool) {
cfg.RAGEnabled = checked
})
addCheckboxRow("Inject role", injectRole, func(checked bool) {
injectRole = checked
})

View File

@@ -9,13 +9,6 @@ import (
"gf-lt/models"
"log/slog"
"net/http"
"os"
"sync"
"time"
"github.com/sugarme/tokenizer"
"github.com/sugarme/tokenizer/pretrained"
"github.com/yalue/onnxruntime_go"
)
// Embedder defines the interface for embedding text
@@ -34,10 +27,8 @@ type APIEmbedder struct {
func NewAPIEmbedder(l *slog.Logger, cfg *config.Config) *APIEmbedder {
return &APIEmbedder{
logger: l,
client: &http.Client{
Timeout: 30 * time.Second,
},
cfg: cfg,
client: &http.Client{},
cfg: cfg,
}
}
@@ -143,302 +134,11 @@ func (a *APIEmbedder) EmbedSlice(lines []string) ([][]float32, error) {
return embeddings, nil
}
// TODO: ONNXEmbedder implementation would go here
// This would require:
// 1. Loading ONNX models locally
// 2. Using a Go ONNX runtime (like gorgonia/onnx or similar)
// 3. Converting text to embeddings without external API calls
type ONNXEmbedder struct {
session *onnxruntime_go.DynamicAdvancedSession
tokenizer *tokenizer.Tokenizer
tokenizerPath string
dims int
logger *slog.Logger
mu sync.Mutex
modelPath string
}
var onnxInitOnce sync.Once
var onnxReady bool
var onnxLibPath string
var cudaLibPath string
var onnxLibPaths = []string{
"/usr/lib/libonnxruntime.so",
"/usr/lib/libonnxruntime.so.1.24.2",
"/usr/local/lib/libonnxruntime.so",
"/usr/lib/x86_64-linux-gnu/libonnxruntime.so",
"/opt/onnxruntime/lib/libonnxruntime.so",
}
var cudaLibPaths = []string{
"/usr/lib/libonnxruntime_providers_cuda.so",
"/usr/local/lib/libonnxruntime_providers_cuda.so",
"/opt/onnxruntime/lib/libonnxruntime_providers_cuda.so",
}
func findONNXLibrary() string {
for _, path := range onnxLibPaths {
if _, err := os.Stat(path); err == nil {
return path
}
}
return ""
}
func findCUDALibrary() string {
for _, path := range cudaLibPaths {
if _, err := os.Stat(path); err == nil {
return path
}
}
return ""
}
func NewONNXEmbedder(modelPath, tokenizerPath string, dims int, logger *slog.Logger) (*ONNXEmbedder, error) {
// Check if model and tokenizer files exist
if _, err := os.Stat(modelPath); err != nil {
return nil, fmt.Errorf("ONNX model not found: %w", err)
}
if _, err := os.Stat(tokenizerPath); err != nil {
return nil, fmt.Errorf("tokenizer not found: %w", err)
}
// Find ONNX library
onnxLibPath = findONNXLibrary()
if onnxLibPath == "" {
return nil, errors.New("ONNX runtime library not found in standard locations")
}
// Find CUDA provider library (optional)
cudaLibPath = findCUDALibrary()
if cudaLibPath == "" {
fmt.Println("WARNING: CUDA provider library not found, will use CPU")
}
emb := &ONNXEmbedder{
tokenizerPath: tokenizerPath,
dims: dims,
logger: logger,
modelPath: modelPath,
}
return emb, nil
}
func (e *ONNXEmbedder) ensureInitialized() error {
if e.session != nil {
return nil
}
e.mu.Lock()
defer e.mu.Unlock()
if e.session != nil {
return nil
}
// Load tokenizer lazily
if e.tokenizer == nil {
tok, err := pretrained.FromFile(e.tokenizerPath)
if err != nil {
return fmt.Errorf("failed to load tokenizer: %w", err)
}
e.tokenizer = tok
}
onnxInitOnce.Do(func() {
onnxruntime_go.SetSharedLibraryPath(onnxLibPath)
if err := onnxruntime_go.InitializeEnvironment(); err != nil {
e.logger.Error("failed to initialize ONNX runtime", "error", err)
onnxReady = false
return
}
// Register CUDA provider if available
if cudaLibPath != "" {
if err := onnxruntime_go.RegisterExecutionProviderLibrary("CUDA", cudaLibPath); err != nil {
e.logger.Warn("failed to register CUDA provider", "error", err)
}
}
onnxReady = true
})
if !onnxReady {
return errors.New("ONNX runtime not ready")
}
// Create session options
opts, err := onnxruntime_go.NewSessionOptions()
if err != nil {
return fmt.Errorf("failed to create session options: %w", err)
}
defer func() {
_ = opts.Destroy()
}()
// Try to add CUDA provider
useCUDA := cudaLibPath != ""
if useCUDA {
cudaOpts, err := onnxruntime_go.NewCUDAProviderOptions()
if err != nil {
e.logger.Warn("failed to create CUDA provider options, falling back to CPU", "error", err)
useCUDA = false
} else {
defer func() {
_ = cudaOpts.Destroy()
}()
if err := cudaOpts.Update(map[string]string{"device_id": "0"}); err != nil {
e.logger.Warn("failed to update CUDA options, falling back to CPU", "error", err)
useCUDA = false
} else if err := opts.AppendExecutionProviderCUDA(cudaOpts); err != nil {
e.logger.Warn("failed to append CUDA provider, falling back to CPU", "error", err)
useCUDA = false
}
}
}
if useCUDA {
e.logger.Info("Using CUDA for ONNX inference")
} else {
e.logger.Info("Using CPU for ONNX inference")
}
// Create session with options
session, err := onnxruntime_go.NewDynamicAdvancedSession(
e.getModelPath(),
[]string{"input_ids", "attention_mask"},
[]string{"sentence_embedding"},
opts,
)
if err != nil {
return fmt.Errorf("failed to create ONNX session: %w", err)
}
e.session = session
return nil
}
func (e *ONNXEmbedder) getModelPath() string {
return e.modelPath
}
func (e *ONNXEmbedder) Destroy() error {
e.mu.Lock()
defer e.mu.Unlock()
if e.session != nil {
if err := e.session.Destroy(); err != nil {
return fmt.Errorf("failed to destroy ONNX session: %w", err)
}
e.session = nil
e.logger.Info("ONNX session destroyed, VRAM freed")
}
return nil
}
func (e *ONNXEmbedder) Embed(text string) ([]float32, error) {
if err := e.ensureInitialized(); err != nil {
return nil, err
}
// 1. Tokenize
encoding, err := e.tokenizer.EncodeSingle(text)
if err != nil {
return nil, fmt.Errorf("tokenization failed: %w", err)
}
// 2. Convert to int64 and create attention mask
ids := encoding.Ids
inputIDs := make([]int64, len(ids))
attentionMask := make([]int64, len(ids))
for i, id := range ids {
inputIDs[i] = int64(id)
attentionMask[i] = 1
}
// 3. Create input tensors (shape: [1, seq_len])
seqLen := int64(len(inputIDs))
inputIDsTensor, err := onnxruntime_go.NewTensor[int64](
onnxruntime_go.NewShape(1, seqLen),
inputIDs,
)
if err != nil {
return nil, fmt.Errorf("failed to create input_ids tensor: %w", err)
}
defer func() { _ = inputIDsTensor.Destroy() }()
maskTensor, err := onnxruntime_go.NewTensor[int64](
onnxruntime_go.NewShape(1, seqLen),
attentionMask,
)
if err != nil {
return nil, fmt.Errorf("failed to create attention_mask tensor: %w", err)
}
defer func() { _ = maskTensor.Destroy() }()
// 4. Create output tensor
outputTensor, err := onnxruntime_go.NewEmptyTensor[float32](
onnxruntime_go.NewShape(1, int64(e.dims)),
)
if err != nil {
return nil, fmt.Errorf("failed to create output tensor: %w", err)
}
defer func() { _ = outputTensor.Destroy() }()
// 5. Run inference
err = e.session.Run(
[]onnxruntime_go.Value{inputIDsTensor, maskTensor},
[]onnxruntime_go.Value{outputTensor},
)
if err != nil {
return nil, fmt.Errorf("inference failed: %w", err)
}
// 6. Copy output data
outputData := outputTensor.GetData()
embedding := make([]float32, len(outputData))
copy(embedding, outputData)
return embedding, nil
}
func (e *ONNXEmbedder) EmbedSlice(texts []string) ([][]float32, error) {
if err := e.ensureInitialized(); err != nil {
return nil, err
}
encodings := make([]*tokenizer.Encoding, len(texts))
maxLen := 0
for i, txt := range texts {
enc, err := e.tokenizer.EncodeSingle(txt)
if err != nil {
return nil, err
}
encodings[i] = enc
if l := len(enc.Ids); l > maxLen {
maxLen = l
}
}
batchSize := len(texts)
inputIDs := make([]int64, batchSize*maxLen)
attentionMask := make([]int64, batchSize*maxLen)
for i, enc := range encodings {
ids := enc.Ids
offset := i * maxLen
for j, id := range ids {
inputIDs[offset+j] = int64(id)
attentionMask[offset+j] = 1
}
// Remaining positions are already zero (padding)
}
// Create tensors with shape [batchSize, maxLen]
inputTensor, _ := onnxruntime_go.NewTensor[int64](
onnxruntime_go.NewShape(int64(batchSize), int64(maxLen)),
inputIDs,
)
defer func() { _ = inputTensor.Destroy() }()
maskTensor, _ := onnxruntime_go.NewTensor[int64](
onnxruntime_go.NewShape(int64(batchSize), int64(maxLen)),
attentionMask,
)
defer func() { _ = maskTensor.Destroy() }()
outputTensor, _ := onnxruntime_go.NewEmptyTensor[float32](
onnxruntime_go.NewShape(int64(batchSize), int64(e.dims)),
)
defer func() { _ = outputTensor.Destroy() }()
err := e.session.Run(
[]onnxruntime_go.Value{inputTensor, maskTensor},
[]onnxruntime_go.Value{outputTensor},
)
if err != nil {
return nil, err
}
// Extract embeddings per batch item
data := outputTensor.GetData()
embeddings := make([][]float32, batchSize)
for i := 0; i < batchSize; i++ {
start := i * e.dims
emb := make([]float32, e.dims)
copy(emb, data[start:start+e.dims])
embeddings[i] = emb
}
return embeddings, nil
}
//
// For now, we'll focus on the API implementation which is already working in the current system,
// and can be extended later when we have ONNX runtime integration

View File

@@ -1,7 +1,6 @@
package rag
import (
"context"
"errors"
"fmt"
"gf-lt/config"
@@ -10,168 +9,51 @@ import (
"log/slog"
"path"
"regexp"
"runtime"
"sort"
"strings"
"sync"
"time"
"github.com/neurosnap/sentences/english"
)
const ()
var (
// Status messages for TUI integration
LongJobStatusCh = make(chan string, 100) // Increased buffer size for parallel batch updates
LongJobStatusCh = make(chan string, 10) // Increased buffer size to prevent blocking
FinishedRAGStatus = "finished loading RAG file; press Enter"
LoadedFileRAGStatus = "loaded file"
ErrRAGStatus = "some error occurred; failed to transfer data to vector db"
)
type RAG struct {
logger *slog.Logger
store storage.FullRepo
cfg *config.Config
embedder Embedder
storage *VectorStorage
mu sync.RWMutex
idleMu sync.Mutex
fallbackMsg string
idleTimer *time.Timer
idleTimeout time.Duration
logger *slog.Logger
store storage.FullRepo
cfg *config.Config
embedder Embedder
storage *VectorStorage
mu sync.Mutex
}
// batchTask represents a single batch to be embedded
type batchTask struct {
batchIndex int
paragraphs []string
filename string
totalBatches int
}
// batchResult represents the result of embedding a batch
type batchResult struct {
batchIndex int
embeddings [][]float32
paragraphs []string
filename string
}
// sendStatusNonBlocking sends a status message without blocking
func (r *RAG) sendStatusNonBlocking(status string) {
select {
case LongJobStatusCh <- status:
default:
r.logger.Warn("LongJobStatusCh channel is full or closed, dropping status message", "message", status)
}
}
func New(l *slog.Logger, s storage.FullRepo, cfg *config.Config) (*RAG, error) {
var embedder Embedder
var fallbackMsg string
if cfg.EmbedModelPath != "" && cfg.EmbedTokenizerPath != "" {
emb, err := NewONNXEmbedder(cfg.EmbedModelPath, cfg.EmbedTokenizerPath, cfg.EmbedDims, l)
if err != nil {
l.Error("failed to create ONNX embedder, falling back to API", "error", err)
fallbackMsg = err.Error()
embedder = NewAPIEmbedder(l, cfg)
} else {
embedder = emb
l.Info("using ONNX embedder", "model", cfg.EmbedModelPath, "dims", cfg.EmbedDims)
}
} else {
embedder = NewAPIEmbedder(l, cfg)
l.Info("using API embedder", "url", cfg.EmbedURL)
}
func New(l *slog.Logger, s storage.FullRepo, cfg *config.Config) *RAG {
// Initialize with API embedder by default, could be configurable later
embedder := NewAPIEmbedder(l, cfg)
rag := &RAG{
logger: l,
store: s,
cfg: cfg,
embedder: embedder,
storage: NewVectorStorage(l, s),
fallbackMsg: fallbackMsg,
idleTimeout: 30 * time.Second,
logger: l,
store: s,
cfg: cfg,
embedder: embedder,
storage: NewVectorStorage(l, s),
}
// Note: Vector tables are created via database migrations, not at runtime
return rag, nil
return rag
}
func createChunks(sentences []string, wordLimit, overlapWords uint32) []string {
if len(sentences) == 0 {
return nil
}
if overlapWords >= wordLimit {
overlapWords = wordLimit / 2
}
var chunks []string
i := 0
for i < len(sentences) {
var chunkWords []string
wordCount := 0
j := i
for j < len(sentences) && wordCount <= int(wordLimit) {
sentence := sentences[j]
words := strings.Fields(sentence)
chunkWords = append(chunkWords, sentence)
wordCount += len(words)
j++
// If this sentence alone exceeds limit, still include it and stop
if wordCount > int(wordLimit) {
break
}
}
if len(chunkWords) == 0 {
break
}
chunk := strings.Join(chunkWords, " ")
chunks = append(chunks, chunk)
if j >= len(sentences) {
break
}
// Move i forward by skipping overlap
if overlapWords == 0 {
i = j
continue
}
// Calculate how many sentences to skip to achieve overlapWords
overlapRemaining := int(overlapWords)
newI := i
for newI < j && overlapRemaining > 0 {
words := len(strings.Fields(sentences[newI]))
overlapRemaining -= words
if overlapRemaining >= 0 {
newI++
}
}
if newI == i {
newI = j
}
i = newI
}
return chunks
}
func sanitizeFTSQuery(query string) string {
// Remove double quotes and other problematic characters for FTS5
query = strings.ReplaceAll(query, "\"", " ")
query = strings.ReplaceAll(query, "'", " ")
query = strings.ReplaceAll(query, ";", " ")
query = strings.ReplaceAll(query, "\\", " ")
query = strings.TrimSpace(query)
if query == "" {
return "*" // match all
}
return query
func wordCounter(sentence string) int {
return len(strings.Split(strings.TrimSpace(sentence), " "))
}
func (r *RAG) LoadRAG(fpath string) error {
return r.LoadRAGWithContext(context.Background(), fpath)
}
func (r *RAG) LoadRAGWithContext(ctx context.Context, fpath string) error {
r.mu.Lock()
defer r.mu.Unlock()
fileText, err := ExtractText(fpath)
@@ -179,9 +61,11 @@ func (r *RAG) LoadRAGWithContext(ctx context.Context, fpath string) error {
return err
}
r.logger.Debug("rag: loaded file", "fp", fpath)
// Send initial status (non-blocking with retry)
r.sendStatusNonBlocking(LoadedFileRAGStatus)
select {
case LongJobStatusCh <- LoadedFileRAGStatus:
default:
r.logger.Warn("LongJobStatusCh channel is full or closed, dropping status message", "message", LoadedFileRAGStatus)
}
tokenizer, err := english.NewSentenceTokenizer(nil)
if err != nil {
return err
@@ -191,9 +75,31 @@ func (r *RAG) LoadRAGWithContext(ctx context.Context, fpath string) error {
for i, s := range sentences {
sents[i] = s.Text
}
// Create chunks with overlap
paragraphs := createChunks(sents, r.cfg.RAGWordLimit, r.cfg.RAGOverlapWords)
// Group sentences into paragraphs based on word limit
paragraphs := []string{}
par := strings.Builder{}
for i := 0; i < len(sents); i++ {
if strings.TrimSpace(sents[i]) != "" {
if par.Len() > 0 {
par.WriteString(" ")
}
par.WriteString(sents[i])
}
if wordCounter(par.String()) > int(r.cfg.RAGWordLimit) {
paragraph := strings.TrimSpace(par.String())
if paragraph != "" {
paragraphs = append(paragraphs, paragraph)
}
par.Reset()
}
}
// Handle any remaining content in the paragraph buffer
if par.Len() > 0 {
paragraph := strings.TrimSpace(par.String())
if paragraph != "" {
paragraphs = append(paragraphs, paragraph)
}
}
// Adjust batch size if needed
if len(paragraphs) < r.cfg.RAGBatchSize && len(paragraphs) > 0 {
r.cfg.RAGBatchSize = len(paragraphs)
@@ -201,348 +107,91 @@ func (r *RAG) LoadRAGWithContext(ctx context.Context, fpath string) error {
if len(paragraphs) == 0 {
return errors.New("no valid paragraphs found in file")
}
totalBatches := (len(paragraphs) + r.cfg.RAGBatchSize - 1) / r.cfg.RAGBatchSize
r.logger.Debug("starting parallel embedding", "total_batches", totalBatches, "batch_size", r.cfg.RAGBatchSize)
// Determine concurrency level
concurrency := runtime.NumCPU()
if concurrency > totalBatches {
concurrency = totalBatches
}
if concurrency < 1 {
concurrency = 1
}
// If using ONNX embedder, limit concurrency to 1 due to mutex serialization
var isONNX bool
if _, isONNX = r.embedder.(*ONNXEmbedder); isONNX {
concurrency = 1
}
embedderType := "API"
if isONNX {
embedderType = "ONNX"
}
r.logger.Debug("parallel embedding setup",
"total_batches", totalBatches,
"concurrency", concurrency,
"embedder", embedderType,
"batch_size", r.cfg.RAGBatchSize)
// Create context with timeout (30 minutes) and cancellation for error handling
ctx, cancel := context.WithTimeout(ctx, 30*time.Minute)
defer cancel()
// Channels for task distribution and results
taskCh := make(chan batchTask, totalBatches)
resultCh := make(chan batchResult, totalBatches)
errorCh := make(chan error, totalBatches)
// Start worker goroutines
var wg sync.WaitGroup
for w := 0; w < concurrency; w++ {
wg.Add(1)
go r.embeddingWorker(ctx, w, taskCh, resultCh, errorCh, &wg)
}
// Close task channel after all tasks are sent (by separate goroutine)
go func() {
// Ensure task channel is closed when this goroutine exits
defer close(taskCh)
r.logger.Debug("task distributor started", "total_batches", totalBatches)
for i := 0; i < totalBatches; i++ {
start := i * r.cfg.RAGBatchSize
end := start + r.cfg.RAGBatchSize
if end > len(paragraphs) {
end = len(paragraphs)
}
batch := paragraphs[start:end]
// Filter empty paragraphs
nonEmptyBatch := make([]string, 0, len(batch))
for _, p := range batch {
if strings.TrimSpace(p) != "" {
nonEmptyBatch = append(nonEmptyBatch, strings.TrimSpace(p))
}
}
task := batchTask{
batchIndex: i,
paragraphs: nonEmptyBatch,
filename: path.Base(fpath),
totalBatches: totalBatches,
}
select {
case taskCh <- task:
r.logger.Debug("task distributor sent batch", "batch", i, "paragraphs", len(nonEmptyBatch))
case <-ctx.Done():
r.logger.Debug("task distributor cancelled", "batches_sent", i+1, "total_batches", totalBatches)
return
// Process paragraphs in batches synchronously
batchCount := 0
for i := 0; i < len(paragraphs); i += r.cfg.RAGBatchSize {
end := i + r.cfg.RAGBatchSize
if end > len(paragraphs) {
end = len(paragraphs)
}
batch := paragraphs[i:end]
batchCount++
// Filter empty paragraphs
nonEmptyBatch := make([]string, 0, len(batch))
for _, p := range batch {
if strings.TrimSpace(p) != "" {
nonEmptyBatch = append(nonEmptyBatch, strings.TrimSpace(p))
}
}
r.logger.Debug("task distributor finished", "batches_sent", totalBatches)
}()
// Wait for workers to finish and close result channel
go func() {
wg.Wait()
close(resultCh)
}()
// Process results in order and write to database
nextExpectedBatch := 0
resultsBuffer := make(map[int]batchResult)
filename := path.Base(fpath)
batchesProcessed := 0
for {
select {
case <-ctx.Done():
return ctx.Err()
case err := <-errorCh:
// First error from any worker, cancel everything
cancel()
r.logger.Error("embedding worker failed", "error", err)
r.sendStatusNonBlocking(ErrRAGStatus)
return fmt.Errorf("embedding failed: %w", err)
case result, ok := <-resultCh:
if !ok {
// All results processed
resultCh = nil
r.logger.Debug("result channel closed", "batches_processed", batchesProcessed, "total_batches", totalBatches)
continue
}
// Store result in buffer
resultsBuffer[result.batchIndex] = result
// Process buffered results in order
for {
if res, exists := resultsBuffer[nextExpectedBatch]; exists {
// Write this batch to database
if err := r.writeBatchToStorage(ctx, res, filename); err != nil {
cancel()
return err
}
batchesProcessed++
// Send progress update
statusMsg := fmt.Sprintf("processed batch %d/%d", batchesProcessed, totalBatches)
r.sendStatusNonBlocking(statusMsg)
delete(resultsBuffer, nextExpectedBatch)
nextExpectedBatch++
} else {
break
}
}
default:
// No channels ready, check for deadlock conditions
if resultCh == nil && nextExpectedBatch < totalBatches {
// Missing batch results after result channel closed
r.logger.Error("missing batch results",
"expected", totalBatches,
"received", nextExpectedBatch,
"missing", totalBatches-nextExpectedBatch)
// Wait a short time for any delayed errors, then cancel
select {
case <-time.After(5 * time.Second):
cancel()
return fmt.Errorf("missing batch results: expected %d, got %d", totalBatches, nextExpectedBatch)
case <-ctx.Done():
return ctx.Err()
case err := <-errorCh:
cancel()
r.logger.Error("embedding worker failed after result channel closed", "error", err)
r.sendStatusNonBlocking(ErrRAGStatus)
return fmt.Errorf("embedding failed: %w", err)
}
}
// If we reach here, no deadlock yet, just busy loop prevention
time.Sleep(100 * time.Millisecond)
}
// Check if we're done
if resultCh == nil && nextExpectedBatch >= totalBatches {
r.logger.Debug("all batches processed successfully", "total", totalBatches)
break
}
}
r.logger.Debug("finished writing vectors", "batches", batchesProcessed)
r.resetIdleTimer()
r.sendStatusNonBlocking(FinishedRAGStatus)
return nil
}
// embeddingWorker processes batch embedding tasks
func (r *RAG) embeddingWorker(ctx context.Context, workerID int, taskCh <-chan batchTask, resultCh chan<- batchResult, errorCh chan<- error, wg *sync.WaitGroup) {
defer wg.Done()
r.logger.Debug("embedding worker started", "worker", workerID)
// Panic recovery to ensure worker doesn't crash silently
defer func() {
if rec := recover(); rec != nil {
r.logger.Error("embedding worker panicked", "worker", workerID, "panic", rec)
// Try to send error, but don't block if channel is full
select {
case errorCh <- fmt.Errorf("worker %d panicked: %v", workerID, rec):
default:
r.logger.Warn("error channel full, dropping panic error", "worker", workerID)
}
}
}()
for task := range taskCh {
select {
case <-ctx.Done():
r.logger.Debug("embedding worker cancelled", "worker", workerID)
return
default:
}
r.logger.Debug("worker processing batch", "worker", workerID, "batch", task.batchIndex, "paragraphs", len(task.paragraphs), "total_batches", task.totalBatches)
// Skip empty batches
if len(task.paragraphs) == 0 {
select {
case resultCh <- batchResult{
batchIndex: task.batchIndex,
embeddings: nil,
paragraphs: nil,
filename: task.filename,
}:
case <-ctx.Done():
r.logger.Debug("embedding worker cancelled while sending empty batch", "worker", workerID)
return
}
r.logger.Debug("worker sent empty batch", "worker", workerID, "batch", task.batchIndex)
if len(nonEmptyBatch) == 0 {
continue
}
// Embed with retry for API embedder
embeddings, err := r.embedWithRetry(ctx, task.paragraphs, 3)
// Embed the batch
embeddings, err := r.embedder.EmbedSlice(nonEmptyBatch)
if err != nil {
// Try to send error, but don't block indefinitely
r.logger.Error("failed to embed batch", "error", err, "batch", batchCount)
select {
case errorCh <- fmt.Errorf("worker %d batch %d: %w", workerID, task.batchIndex, err):
case <-ctx.Done():
r.logger.Debug("embedding worker cancelled while sending error", "worker", workerID)
case LongJobStatusCh <- ErrRAGStatus:
default:
r.logger.Warn("LongJobStatusCh channel full, dropping message")
}
return
return fmt.Errorf("failed to embed batch %d: %w", batchCount, err)
}
// Send result with context awareness
if len(embeddings) != len(nonEmptyBatch) {
err := errors.New("embedding count mismatch")
r.logger.Error("embedding mismatch", "expected", len(nonEmptyBatch), "got", len(embeddings))
return err
}
// Write vectors to storage
filename := path.Base(fpath)
for j, text := range nonEmptyBatch {
vector := models.VectorRow{
Embeddings: embeddings[j],
RawText: text,
Slug: fmt.Sprintf("%s_%d_%d", filename, batchCount, j),
FileName: filename,
}
if err := r.storage.WriteVector(&vector); err != nil {
r.logger.Error("failed to write vector to DB", "error", err, "slug", vector.Slug)
select {
case LongJobStatusCh <- ErrRAGStatus:
default:
r.logger.Warn("LongJobStatusCh channel full, dropping message")
}
return fmt.Errorf("failed to write vector: %w", err)
}
}
r.logger.Debug("wrote batch to db", "batch", batchCount, "size", len(nonEmptyBatch))
// Send progress status
statusMsg := fmt.Sprintf("processed batch %d/%d", batchCount, (len(paragraphs)+r.cfg.RAGBatchSize-1)/r.cfg.RAGBatchSize)
select {
case resultCh <- batchResult{
batchIndex: task.batchIndex,
embeddings: embeddings,
paragraphs: task.paragraphs,
filename: task.filename,
}:
case <-ctx.Done():
r.logger.Debug("embedding worker cancelled while sending result", "worker", workerID)
return
}
r.logger.Debug("worker completed batch", "worker", workerID, "batch", task.batchIndex, "embeddings", len(embeddings))
}
r.logger.Debug("embedding worker finished", "worker", workerID)
}
// embedWithRetry attempts embedding with exponential backoff for API embedder
func (r *RAG) embedWithRetry(ctx context.Context, paragraphs []string, maxRetries int) ([][]float32, error) {
var lastErr error
for attempt := 0; attempt < maxRetries; attempt++ {
if attempt > 0 {
// Exponential backoff
backoff := time.Duration(attempt*attempt) * time.Second
if backoff > 10*time.Second {
backoff = 10 * time.Second
}
select {
case <-time.After(backoff):
case <-ctx.Done():
return nil, ctx.Err()
}
r.logger.Debug("retrying embedding", "attempt", attempt, "max_retries", maxRetries)
}
embeddings, err := r.embedder.EmbedSlice(paragraphs)
if err == nil {
// Validate embedding count
if len(embeddings) != len(paragraphs) {
return nil, fmt.Errorf("embedding count mismatch: expected %d, got %d", len(paragraphs), len(embeddings))
}
return embeddings, nil
}
lastErr = err
// Only retry for API embedder errors (network/timeout)
// For ONNX embedder, fail fast
if _, isAPI := r.embedder.(*APIEmbedder); !isAPI {
break
case LongJobStatusCh <- statusMsg:
default:
r.logger.Warn("LongJobStatusCh channel full, dropping message")
}
}
return nil, fmt.Errorf("embedding failed after %d attempts: %w", maxRetries, lastErr)
}
// writeBatchToStorage writes a single batch of vectors to the database
func (r *RAG) writeBatchToStorage(ctx context.Context, result batchResult, filename string) error {
if len(result.embeddings) == 0 {
// Empty batch, skip
return nil
}
// Check context before starting
r.logger.Debug("finished writing vectors", "batches", batchCount)
select {
case <-ctx.Done():
return ctx.Err()
case LongJobStatusCh <- FinishedRAGStatus:
default:
r.logger.Warn("LongJobStatusCh channel is full or closed, dropping status message", "message", FinishedRAGStatus)
}
// Build all vectors for batch write
vectors := make([]*models.VectorRow, 0, len(result.paragraphs))
for j, text := range result.paragraphs {
vectors = append(vectors, &models.VectorRow{
Embeddings: result.embeddings[j],
RawText: text,
Slug: fmt.Sprintf("%s_%d_%d", filename, result.batchIndex+1, j),
FileName: filename,
})
}
// Write all vectors in a single transaction
if err := r.storage.WriteVectors(vectors); err != nil {
r.logger.Error("failed to write vectors batch to DB", "error", err, "batch", result.batchIndex+1, "size", len(vectors))
r.sendStatusNonBlocking(ErrRAGStatus)
return fmt.Errorf("failed to write vectors batch: %w", err)
}
r.logger.Debug("wrote batch to db", "batch", result.batchIndex+1, "size", len(result.paragraphs))
return nil
}
func (r *RAG) LineToVector(line string) ([]float32, error) {
r.resetIdleTimer()
return r.embedder.Embed(line)
}
func (r *RAG) searchEmb(emb *models.EmbeddingResp, limit int) ([]models.VectorRow, error) {
r.resetIdleTimer()
return r.storage.SearchClosest(emb.Embedding, limit)
}
func (r *RAG) searchKeyword(query string, limit int) ([]models.VectorRow, error) {
r.resetIdleTimer()
sanitized := sanitizeFTSQuery(query)
return r.storage.SearchKeyword(sanitized, limit)
func (r *RAG) SearchEmb(emb *models.EmbeddingResp) ([]models.VectorRow, error) {
return r.storage.SearchClosest(emb.Embedding)
}
func (r *RAG) ListLoaded() ([]string, error) {
r.mu.RLock()
defer r.mu.RUnlock()
return r.storage.ListFiles()
}
func (r *RAG) RemoveFile(filename string) error {
r.mu.Lock()
defer r.mu.Unlock()
r.resetIdleTimer()
return r.storage.RemoveEmbByFileName(filename)
}
@@ -562,13 +211,10 @@ func (r *RAG) RefineQuery(query string) string {
return original
}
query = strings.ToLower(query)
words := strings.Fields(query)
if len(words) >= 3 {
for _, stopWord := range stopWords {
wordPattern := `\b` + stopWord + `\b`
re := regexp.MustCompile(wordPattern)
query = re.ReplaceAllString(query, "")
}
for _, stopWord := range stopWords {
wordPattern := `\b` + stopWord + `\b`
re := regexp.MustCompile(wordPattern)
query = re.ReplaceAllString(query, "")
}
query = strings.TrimSpace(query)
if len(query) < 5 {
@@ -600,7 +246,7 @@ func (r *RAG) extractImportantPhrases(query string) string {
break
}
}
if isImportant || len(word) >= 3 {
if isImportant || len(word) > 3 {
important = append(important, word)
}
}
@@ -619,36 +265,6 @@ func (r *RAG) GenerateQueryVariations(query string) []string {
if len(parts) == 0 {
return variations
}
// Get loaded filenames to filter out filename terms
filenames, err := r.storage.ListFiles()
if err == nil && len(filenames) > 0 {
// Convert to lowercase for case-insensitive matching
lowerFilenames := make([]string, len(filenames))
for i, f := range filenames {
lowerFilenames[i] = strings.ToLower(f)
}
filteredParts := make([]string, 0, len(parts))
for _, part := range parts {
partLower := strings.ToLower(part)
skip := false
for _, fn := range lowerFilenames {
if strings.Contains(fn, partLower) || strings.Contains(partLower, fn) {
skip = true
break
}
}
if !skip {
filteredParts = append(filteredParts, part)
}
}
// If filteredParts not empty and different from original, add filtered query
if len(filteredParts) > 0 && len(filteredParts) != len(parts) {
filteredQuery := strings.Join(filteredParts, " ")
if len(filteredQuery) >= 5 {
variations = append(variations, filteredQuery)
}
}
}
if len(parts) >= 2 {
trimmed := strings.Join(parts[:len(parts)-1], " ")
if len(trimmed) >= 5 {
@@ -712,14 +328,9 @@ func (r *RAG) RerankResults(results []models.VectorRow, query string) []models.V
})
unique := make([]models.VectorRow, 0)
seen := make(map[string]bool)
fileCounts := make(map[string]int)
for i := range scored {
if !seen[scored[i].row.Slug] {
if fileCounts[scored[i].row.FileName] >= 2 {
continue
}
seen[scored[i].row.Slug] = true
fileCounts[scored[i].row.FileName]++
unique = append(unique, scored[i].row)
}
}
@@ -730,9 +341,6 @@ func (r *RAG) RerankResults(results []models.VectorRow, query string) []models.V
}
func (r *RAG) SynthesizeAnswer(results []models.VectorRow, query string) (string, error) {
r.mu.RLock()
defer r.mu.RUnlock()
r.resetIdleTimer()
if len(results) == 0 {
return "No relevant information found in the vector database.", nil
}
@@ -761,7 +369,7 @@ func (r *RAG) SynthesizeAnswer(results []models.VectorRow, query string) (string
Embedding: emb,
Index: 0,
}
topResults, err := r.searchEmb(embResp, 1)
topResults, err := r.SearchEmb(embResp)
if err != nil {
r.logger.Error("failed to search for synthesis context", "error", err)
return "", err
@@ -788,14 +396,9 @@ func truncateString(s string, maxLen int) string {
}
func (r *RAG) Search(query string, limit int) ([]models.VectorRow, error) {
r.mu.RLock()
defer r.mu.RUnlock()
r.resetIdleTimer()
refined := r.RefineQuery(query)
variations := r.GenerateQueryVariations(refined)
// Collect embedding search results from all variations
var embResults []models.VectorRow
allResults := make([]models.VectorRow, 0)
seen := make(map[string]bool)
for _, q := range variations {
emb, err := r.LineToVector(q)
@@ -803,78 +406,29 @@ func (r *RAG) Search(query string, limit int) ([]models.VectorRow, error) {
r.logger.Error("failed to embed query variation", "error", err, "query", q)
continue
}
embResp := &models.EmbeddingResp{
Embedding: emb,
Index: 0,
}
results, err := r.searchEmb(embResp, limit*2) // Get more candidates
results, err := r.SearchEmb(embResp)
if err != nil {
r.logger.Error("failed to search embeddings", "error", err, "query", q)
continue
}
for _, row := range results {
if !seen[row.Slug] {
seen[row.Slug] = true
embResults = append(embResults, row)
allResults = append(allResults, row)
}
}
}
// Sort embedding results by distance (lower is better)
sort.Slice(embResults, func(i, j int) bool {
return embResults[i].Distance < embResults[j].Distance
})
// Perform keyword search
kwResults, err := r.searchKeyword(refined, limit*2)
if err != nil {
r.logger.Warn("keyword search failed, using only embeddings", "error", err)
kwResults = nil
reranked := r.RerankResults(allResults, query)
if len(reranked) > limit {
reranked = reranked[:limit]
}
// Sort keyword results by distance (already sorted by BM25 score)
// kwResults already sorted by distance (lower is better)
// Combine using Reciprocal Rank Fusion (RRF)
const rrfK = 60
type scoredRow struct {
row models.VectorRow
score float64
}
scoreMap := make(map[string]float64)
// Add embedding results
for rank, row := range embResults {
score := 1.0 / (float64(rank) + rrfK)
scoreMap[row.Slug] += score
}
// Add keyword results
for rank, row := range kwResults {
score := 1.0 / (float64(rank) + rrfK)
scoreMap[row.Slug] += score
// Ensure row exists in combined results
if _, exists := seen[row.Slug]; !exists {
embResults = append(embResults, row)
}
}
// Create slice of scored rows
scoredRows := make([]scoredRow, 0, len(embResults))
for _, row := range embResults {
score := scoreMap[row.Slug]
scoredRows = append(scoredRows, scoredRow{row: row, score: score})
}
// Sort by descending RRF score
sort.Slice(scoredRows, func(i, j int) bool {
return scoredRows[i].score > scoredRows[j].score
})
// Take top limit
if len(scoredRows) > limit {
scoredRows = scoredRows[:limit]
}
// Convert back to VectorRow
finalResults := make([]models.VectorRow, len(scoredRows))
for i, sr := range scoredRows {
finalResults[i] = sr.row
}
// Apply reranking heuristics
reranked := r.RerankResults(finalResults, query)
return reranked, nil
}
@@ -883,58 +437,16 @@ var (
ragOnce sync.Once
)
func (r *RAG) FallbackMessage() string {
return r.fallbackMsg
}
func Init(c *config.Config, l *slog.Logger, s storage.FullRepo) error {
var err error
ragOnce.Do(func() {
if c == nil || l == nil || s == nil {
return
}
ragInstance, err = New(l, s, c)
ragInstance = New(l, s, c)
})
return err
return nil
}
func GetInstance() *RAG {
return ragInstance
}
func (r *RAG) resetIdleTimer() {
r.idleMu.Lock()
defer r.idleMu.Unlock()
if r.idleTimer != nil {
r.idleTimer.Stop()
}
r.idleTimer = time.AfterFunc(r.idleTimeout, func() {
r.freeONNXMemory()
})
}
func (r *RAG) freeONNXMemory() {
r.mu.Lock()
defer r.mu.Unlock()
if onnx, ok := r.embedder.(*ONNXEmbedder); ok {
if err := onnx.Destroy(); err != nil {
r.logger.Error("failed to free ONNX memory", "error", err)
} else {
r.logger.Info("freed ONNX VRAM after idle timeout")
}
}
}
func (r *RAG) Destroy() {
r.mu.Lock()
defer r.mu.Unlock()
if r.idleTimer != nil {
r.idleTimer.Stop()
r.idleTimer = nil
}
if onnx, ok := r.embedder.(*ONNXEmbedder); ok {
if err := onnx.Destroy(); err != nil {
r.logger.Error("failed to destroy ONNX embedder", "error", err)
}
}
}

View File

@@ -1,7 +1,6 @@
package rag
import (
"database/sql"
"encoding/binary"
"fmt"
"gf-lt/models"
@@ -63,17 +62,6 @@ func (vs *VectorStorage) WriteVector(row *models.VectorRow) error {
if err != nil {
return err
}
embeddingSize := len(row.Embeddings)
// Start transaction
tx, err := vs.sqlxDB.Beginx()
if err != nil {
return err
}
defer func() {
if err != nil {
_ = tx.Rollback()
}
}()
// Serialize the embeddings to binary
serializedEmbeddings := SerializeVector(row.Embeddings)
@@ -81,102 +69,10 @@ func (vs *VectorStorage) WriteVector(row *models.VectorRow) error {
"INSERT INTO %s (embeddings, slug, raw_text, filename) VALUES (?, ?, ?, ?)",
tableName,
)
if _, err := tx.Exec(query, serializedEmbeddings, row.Slug, row.RawText, row.FileName); err != nil {
if _, err := vs.sqlxDB.Exec(query, serializedEmbeddings, row.Slug, row.RawText, row.FileName); err != nil {
vs.logger.Error("failed to write vector", "error", err, "slug", row.Slug)
return err
}
// Insert into FTS table
ftsQuery := `INSERT INTO fts_embeddings (slug, raw_text, filename, embedding_size) VALUES (?, ?, ?, ?)`
if _, err := tx.Exec(ftsQuery, row.Slug, row.RawText, row.FileName, embeddingSize); err != nil {
vs.logger.Error("failed to write to FTS table", "error", err, "slug", row.Slug)
return err
}
err = tx.Commit()
if err != nil {
vs.logger.Error("failed to commit transaction", "error", err)
return err
}
return nil
}
// WriteVectors stores multiple embedding vectors in a single transaction
func (vs *VectorStorage) WriteVectors(rows []*models.VectorRow) error {
if len(rows) == 0 {
return nil
}
// SQLite has limit of 999 parameters per statement, each row uses 4 parameters
const maxBatchSize = 200 // 200 * 4 = 800 < 999
if len(rows) > maxBatchSize {
// Process in chunks
for i := 0; i < len(rows); i += maxBatchSize {
end := i + maxBatchSize
if end > len(rows) {
end = len(rows)
}
if err := vs.WriteVectors(rows[i:end]); err != nil {
return err
}
}
return nil
}
// All rows should have same embedding size (same model)
firstSize := len(rows[0].Embeddings)
for i, row := range rows {
if len(row.Embeddings) != firstSize {
return fmt.Errorf("embedding size mismatch: row %d has size %d, expected %d", i, len(row.Embeddings), firstSize)
}
}
tableName, err := vs.getTableName(rows[0].Embeddings)
if err != nil {
return err
}
// Start transaction
tx, err := vs.sqlxDB.Beginx()
if err != nil {
return err
}
defer func() {
if err != nil {
_ = tx.Rollback()
}
}()
// Build batch insert for embeddings table
embeddingPlaceholders := make([]string, 0, len(rows))
embeddingArgs := make([]any, 0, len(rows)*4)
for _, row := range rows {
embeddingPlaceholders = append(embeddingPlaceholders, "(?, ?, ?, ?)")
embeddingArgs = append(embeddingArgs, SerializeVector(row.Embeddings), row.Slug, row.RawText, row.FileName)
}
embeddingQuery := fmt.Sprintf(
"INSERT INTO %s (embeddings, slug, raw_text, filename) VALUES %s",
tableName,
strings.Join(embeddingPlaceholders, ", "),
)
if _, err := tx.Exec(embeddingQuery, embeddingArgs...); err != nil {
vs.logger.Error("failed to write vectors batch", "error", err, "batch_size", len(rows))
return err
}
// Build batch insert for FTS table
ftsPlaceholders := make([]string, 0, len(rows))
ftsArgs := make([]any, 0, len(rows)*4)
embeddingSize := len(rows[0].Embeddings)
for _, row := range rows {
ftsPlaceholders = append(ftsPlaceholders, "(?, ?, ?, ?)")
ftsArgs = append(ftsArgs, row.Slug, row.RawText, row.FileName, embeddingSize)
}
ftsQuery := "INSERT INTO fts_embeddings (slug, raw_text, filename, embedding_size) VALUES " +
strings.Join(ftsPlaceholders, ", ")
if _, err := tx.Exec(ftsQuery, ftsArgs...); err != nil {
vs.logger.Error("failed to write FTS batch", "error", err, "batch_size", len(rows))
return err
}
err = tx.Commit()
if err != nil {
vs.logger.Error("failed to commit transaction", "error", err)
return err
}
vs.logger.Debug("wrote vectors batch", "batch_size", len(rows))
return nil
}
@@ -202,25 +98,30 @@ func (vs *VectorStorage) getTableName(emb []float32) (string, error) {
}
// SearchClosest finds vectors closest to the query vector using efficient cosine similarity calculation
func (vs *VectorStorage) SearchClosest(query []float32, limit int) ([]models.VectorRow, error) {
if limit <= 0 {
limit = 10
}
func (vs *VectorStorage) SearchClosest(query []float32) ([]models.VectorRow, error) {
tableName, err := vs.getTableName(query)
if err != nil {
return nil, err
}
// For better performance, instead of loading all vectors at once,
// we'll implement batching and potentially add L2 distance-based pre-filtering
// since cosine similarity is related to L2 distance for normalized vectors
querySQL := "SELECT embeddings, slug, raw_text, filename FROM " + tableName
rows, err := vs.sqlxDB.Query(querySQL)
if err != nil {
return nil, err
}
defer rows.Close()
// Use a min-heap or simple slice to keep track of top 3 closest vectors
type SearchResult struct {
vector models.VectorRow
distance float32
}
var topResults []SearchResult
// Process vectors one by one to avoid loading everything into memory
for rows.Next() {
var (
embeddingsBlob []byte
@@ -231,9 +132,12 @@ func (vs *VectorStorage) SearchClosest(query []float32, limit int) ([]models.Vec
vs.logger.Error("failed to scan row", "error", err)
continue
}
storedEmbeddings := DeserializeVector(embeddingsBlob)
// Calculate cosine similarity (returns value between -1 and 1, where 1 is most similar)
similarity := cosineSimilarity(query, storedEmbeddings)
distance := 1 - similarity
distance := 1 - similarity // Convert to distance where 0 is most similar
result := SearchResult{
vector: models.VectorRow{
@@ -245,14 +149,20 @@ func (vs *VectorStorage) SearchClosest(query []float32, limit int) ([]models.Vec
distance: distance,
}
// Add to top results and maintain only top 3
topResults = append(topResults, result)
// Sort and keep only top 3
sort.Slice(topResults, func(i, j int) bool {
return topResults[i].distance < topResults[j].distance
})
if len(topResults) > limit {
topResults = topResults[:limit]
if len(topResults) > 3 {
topResults = topResults[:3] // Keep only closest 3
}
}
// Convert back to VectorRow slice
results := make([]models.VectorRow, 0, len(topResults))
for _, result := range topResults {
result.vector.Distance = result.distance
@@ -261,100 +171,6 @@ func (vs *VectorStorage) SearchClosest(query []float32, limit int) ([]models.Vec
return results, nil
}
// GetVectorBySlug retrieves a vector row by its slug
func (vs *VectorStorage) GetVectorBySlug(slug string) (*models.VectorRow, error) {
embeddingSizes := []int{384, 768, 1024, 1536, 2048, 3072, 4096, 5120}
for _, size := range embeddingSizes {
table := fmt.Sprintf("embeddings_%d", size)
query := fmt.Sprintf("SELECT embeddings, slug, raw_text, filename FROM %s WHERE slug = ?", table)
row := vs.sqlxDB.QueryRow(query, slug)
var (
embeddingsBlob []byte
retrievedSlug, rawText, fileName string
)
if err := row.Scan(&embeddingsBlob, &retrievedSlug, &rawText, &fileName); err != nil {
// No row in this table, continue to next size
continue
}
storedEmbeddings := DeserializeVector(embeddingsBlob)
return &models.VectorRow{
Embeddings: storedEmbeddings,
Slug: retrievedSlug,
RawText: rawText,
FileName: fileName,
}, nil
}
return nil, fmt.Errorf("vector with slug %s not found", slug)
}
// SearchKeyword performs full-text search using FTS5
func (vs *VectorStorage) SearchKeyword(query string, limit int) ([]models.VectorRow, error) {
// Use FTS5 bm25 ranking. bm25 returns negative values where more negative is better.
// We'll order by bm25 (ascending) and limit.
ftsQuery := `SELECT slug, raw_text, filename, bm25(fts_embeddings) as score
FROM fts_embeddings
WHERE fts_embeddings MATCH ?
ORDER BY score
LIMIT ?`
// Try original query first
rows, err := vs.sqlxDB.Query(ftsQuery, query, limit)
if err != nil {
return nil, fmt.Errorf("FTS search failed: %w", err)
}
results, err := vs.scanRows(rows)
rows.Close()
if err != nil {
return nil, err
}
// If no results and query contains multiple terms, try OR fallback
if len(results) == 0 && strings.Contains(query, " ") && !strings.Contains(strings.ToUpper(query), " OR ") {
// Build OR query: term1 OR term2 OR term3
terms := strings.Fields(query)
if len(terms) > 1 {
orQuery := strings.Join(terms, " OR ")
rows, err := vs.sqlxDB.Query(ftsQuery, orQuery, limit)
if err != nil {
// Return original empty results rather than error
return results, nil
}
orResults, err := vs.scanRows(rows)
rows.Close()
if err == nil {
results = orResults
}
}
}
return results, nil
}
// scanRows converts SQL rows to VectorRow slice
func (vs *VectorStorage) scanRows(rows *sql.Rows) ([]models.VectorRow, error) {
var results []models.VectorRow
for rows.Next() {
var slug, rawText, fileName string
var score float64
if err := rows.Scan(&slug, &rawText, &fileName, &score); err != nil {
vs.logger.Error("failed to scan FTS row", "error", err)
continue
}
// Convert BM25 score to distance-like metric (lower is better)
// BM25 is negative, more negative is better. We'll normalize to positive distance.
distance := float32(-score) // Make positive (since score is negative)
if distance < 0 {
distance = 0
}
results = append(results, models.VectorRow{
Slug: slug,
RawText: rawText,
FileName: fileName,
Distance: distance,
})
}
return results, nil
}
// ListFiles returns a list of all loaded files
func (vs *VectorStorage) ListFiles() ([]string, error) {
fileLists := make([][]string, 0)
@@ -399,10 +215,6 @@ func (vs *VectorStorage) ListFiles() ([]string, error) {
// RemoveEmbByFileName removes all embeddings associated with a specific filename
func (vs *VectorStorage) RemoveEmbByFileName(filename string) error {
var errors []string
// Delete from FTS table first
if _, err := vs.sqlxDB.Exec("DELETE FROM fts_embeddings WHERE filename = ?", filename); err != nil {
errors = append(errors, err.Error())
}
embeddingSizes := []int{384, 768, 1024, 1536, 2048, 3072, 4096, 5120}
for _, size := range embeddingSizes {
table := fmt.Sprintf("embeddings_%d", size)

View File

@@ -1,2 +0,0 @@
-- Drop FTS5 virtual table
DROP TABLE IF EXISTS fts_embeddings;

View File

@@ -1,15 +0,0 @@
-- Create FTS5 virtual table for full-text search
CREATE VIRTUAL TABLE IF NOT EXISTS fts_embeddings USING fts5(
slug UNINDEXED,
raw_text,
filename UNINDEXED,
embedding_size UNINDEXED,
tokenize='porter unicode61' -- Use porter stemmer and unicode61 tokenizer
);
-- Create triggers to maintain FTS table when embeddings are inserted/deleted
-- Note: We'll handle inserts/deletes programmatically for simplicity
-- but triggers could be added here if needed.
-- Indexes for performance (FTS5 manages its own indexes)
-- No additional indexes needed for FTS5 virtual table.

View File

@@ -1,2 +0,0 @@
-- Clear FTS table (optional)
DELETE FROM fts_embeddings;

View File

@@ -1,26 +0,0 @@
-- Populate FTS table with existing embeddings
DELETE FROM fts_embeddings;
INSERT INTO fts_embeddings (slug, raw_text, filename, embedding_size)
SELECT slug, raw_text, filename, 384 FROM embeddings_384;
INSERT INTO fts_embeddings (slug, raw_text, filename, embedding_size)
SELECT slug, raw_text, filename, 768 FROM embeddings_768;
INSERT INTO fts_embeddings (slug, raw_text, filename, embedding_size)
SELECT slug, raw_text, filename, 1024 FROM embeddings_1024;
INSERT INTO fts_embeddings (slug, raw_text, filename, embedding_size)
SELECT slug, raw_text, filename, 1536 FROM embeddings_1536;
INSERT INTO fts_embeddings (slug, raw_text, filename, embedding_size)
SELECT slug, raw_text, filename, 2048 FROM embeddings_2048;
INSERT INTO fts_embeddings (slug, raw_text, filename, embedding_size)
SELECT slug, raw_text, filename, 3072 FROM embeddings_3072;
INSERT INTO fts_embeddings (slug, raw_text, filename, embedding_size)
SELECT slug, raw_text, filename, 4096 FROM embeddings_4096;
INSERT INTO fts_embeddings (slug, raw_text, filename, embedding_size)
SELECT slug, raw_text, filename, 5120 FROM embeddings_5120;

View File

@@ -102,22 +102,6 @@ func NewProviderSQL(dbPath string, logger *slog.Logger) FullRepo {
logger.Error("failed to open db connection", "error", err)
return nil
}
// Enable WAL mode for better concurrency and performance
if _, err := db.Exec("PRAGMA journal_mode = WAL;"); err != nil {
logger.Warn("failed to enable WAL mode", "error", err)
}
if _, err := db.Exec("PRAGMA synchronous = NORMAL;"); err != nil {
logger.Warn("failed to set synchronous mode", "error", err)
}
// Increase cache size for better performance
if _, err := db.Exec("PRAGMA cache_size = -2000;"); err != nil {
logger.Warn("failed to set cache size", "error", err)
}
// Log actual journal mode for debugging
var journalMode string
if err := db.QueryRow("PRAGMA journal_mode;").Scan(&journalMode); err == nil {
logger.Debug("SQLite journal mode", "mode", journalMode)
}
p := ProviderSQL{db: db, logger: logger}
if err := p.Migrate(); err != nil {
logger.Error("migration failed, app cannot start", "error", err)

View File

@@ -4,7 +4,6 @@ import (
"encoding/binary"
"fmt"
"gf-lt/models"
"sort"
"unsafe"
"github.com/jmoiron/sqlx"
@@ -12,7 +11,7 @@ import (
type VectorRepo interface {
WriteVector(*models.VectorRow) error
SearchClosest(q []float32, limit int) ([]models.VectorRow, error)
SearchClosest(q []float32) ([]models.VectorRow, error)
ListFiles() ([]string, error)
RemoveEmbByFileName(filename string) error
DB() *sqlx.DB
@@ -80,7 +79,7 @@ func (p ProviderSQL) WriteVector(row *models.VectorRow) error {
return err
}
func (p ProviderSQL) SearchClosest(q []float32, limit int) ([]models.VectorRow, error) {
func (p ProviderSQL) SearchClosest(q []float32) ([]models.VectorRow, error) {
tableName, err := fetchTableName(q)
if err != nil {
return nil, err
@@ -95,7 +94,7 @@ func (p ProviderSQL) SearchClosest(q []float32, limit int) ([]models.VectorRow,
vector models.VectorRow
distance float32
}
var allResults []SearchResult
var topResults []SearchResult
for rows.Next() {
var (
embeddingsBlob []byte
@@ -120,19 +119,28 @@ func (p ProviderSQL) SearchClosest(q []float32, limit int) ([]models.VectorRow,
},
distance: distance,
}
allResults = append(allResults, result)
}
// Sort by distance
sort.Slice(allResults, func(i, j int) bool {
return allResults[i].distance < allResults[j].distance
})
// Truncate to limit
if len(allResults) > limit {
allResults = allResults[:limit]
// Add to top results and maintain only top results
topResults = append(topResults, result)
// Sort and keep only top results
// We'll keep the top 3 closest vectors
if len(topResults) > 3 {
// Simple sort and truncate to maintain only 3 best matches
for i := 0; i < len(topResults); i++ {
for j := i + 1; j < len(topResults); j++ {
if topResults[i].distance > topResults[j].distance {
topResults[i], topResults[j] = topResults[j], topResults[i]
}
}
}
topResults = topResults[:3]
}
}
// Convert back to VectorRow slice
results := make([]models.VectorRow, len(allResults))
for i, result := range allResults {
results := make([]models.VectorRow, len(topResults))
for i, result := range topResults {
result.vector.Distance = result.distance
results[i] = result.vector
}

7
sysprompts/cluedo.json Normal file
View File

@@ -0,0 +1,7 @@
{
"sys_prompt": "A game of cluedo. Players are {{user}}, {{char}}, {{char2}};\n\nrooms: hall, lounge, dinning room kitchen, ballroom, conservatory, billiard room, library, study;\nweapons: candlestick, dagger, lead pipe, revolver, rope, spanner;\npeople: miss Scarlett, colonel Mustard, mrs. White, reverend Green, mrs. Peacock, professor Plum;\n\nA murder happened in a mansion with 9 rooms. Victim is dr. Black.\nPlayers goal is to find out who commited a murder, in what room and with what weapon.\nWeapons, people and rooms not involved in murder are distributed between players (as cards) by tool agent.\nThe objective of the game is to deduce the details of the murder. There are six characters, six murder weapons, and nine rooms, leaving the players with 324 possibilities. As soon as a player enters a room, they may make a suggestion as to the details, naming a suspect, the room they are in, and the weapon. For example: \"I suspect Professor Plum, in the Dining Room, with the candlestick\".\nOnce a player makes a suggestion, the others are called upon to disprove it.\nBefore the player's move, tool agent will remind that players their cards. There are two types of moves: making a suggestion (suggestion_move) and disproving other player suggestion (evidence_move);\nIn this version player wins when the correct details are named in the suggestion_move.\n\n<example_game>\n{{user}}:\nlet's start a game of cluedo!\ntool: cards of {{char}} are 'LEAD PIPE', 'BALLROOM', 'CONSERVATORY', 'STUDY', 'Mrs. White'; suggestion_move;\n{{char}}:\n(putting miss Scarlet into the Hall with the Revolver) \"I suspect miss Scarlett, in the Hall, with the revolver.\"\ntool: cards of {{char2}} are 'SPANNER', 'DAGGER', 'Professor Plum', 'LIBRARY', 'Mrs. Peacock'; evidence_move;\n{{char2}}:\n\"No objections.\" (no cards matching the suspicion of {{char}})\ntool: cards of {{user}} are 'Colonel Mustard', 'Miss Scarlett', 'DINNING ROOM', 'CANDLESTICK', 'HALL'; evidence_move;\n{{user}}:\n\"I object. Miss Scarlett is innocent.\" (shows card with 'Miss Scarlett')\ntool: cards of {{char2}} are 'SPANNER', 'DAGGER', 'Professor Plum', 'LIBRARY', 'Mrs. Peacock'; suggestion_move;\n{{char2}}:\n*So it was not Miss Scarlett, good to know.*\n(moves Mrs. White to the Billiard Room) \"It might have been Mrs. White, in the Billiard Room, with the Revolver.\"\ntool: cards of {{user}} are 'Colonel Mustard', 'Miss Scarlett', 'DINNING ROOM', 'CANDLESTICK', 'HALL'; evidence_move;\n{{user}}:\n(no matching cards for the assumption of {{char2}}) \"Sounds possible to me.\"\ntool: cards of {{char}} are 'LEAD PIPE', 'BALLROOM', 'CONSERVATORY', 'STUDY', 'Mrs. White'; evidence_move;\n{{char}}:\n(shows Mrs. White card) \"No. Was not Mrs. White\"\ntool: cards of {{user}} are 'Colonel Mustard', 'Miss Scarlett', 'DINNING ROOM', 'CANDLESTICK', 'HALL'; suggestion_move;\n{{user}}:\n*So not Mrs. White...* (moves Reverend Green into the Billiard Room) \"I suspect Reverend Green, in the Billiard Room, with the Revolver.\"\ntool: Correct. It was Reverend Green in the Billiard Room, with the revolver. {{user}} wins.\n</example_game>",
"role": "CluedoPlayer",
"role2": "CluedoEnjoyer",
"filepath": "sysprompts/cluedo.json",
"first_msg": "Hey guys! Want to play cluedo?"
}

View File

@@ -278,25 +278,13 @@ func updateToolCapabilities() {
// getWebAgentClient returns a singleton AgentClient for web agents.
func getWebAgentClient() *agent.AgentClient {
webAgentClientOnce.Do(func() {
if cfg == nil {
if logger != nil {
logger.Warn("web agent client unavailable: config not initialized")
}
return
}
if logger == nil {
if logger != nil {
logger.Warn("web agent client unavailable: logger not initialized")
}
return
}
getToken := func() string {
if chunkParser == nil {
return ""
}
return chunkParser.GetToken()
}
webAgentClient = agent.NewAgentClient(cfg, *logger, getToken)
webAgentClient = agent.NewAgentClient(cfg, logger, getToken)
})
return webAgentClient
}
@@ -306,13 +294,13 @@ func registerWebAgents() {
webAgentsOnce.Do(func() {
client := getWebAgentClient()
// Register rag_search agent
agent.Register("rag_search", agent.NewWebAgentB(client, ragSearchSysPrompt))
agent.RegisterB("rag_search", agent.NewWebAgentB(client, ragSearchSysPrompt))
// Register websearch agent
agent.Register("websearch", agent.NewWebAgentB(client, webSearchSysPrompt))
agent.RegisterB("websearch", agent.NewWebAgentB(client, webSearchSysPrompt))
// Register read_url agent
agent.Register("read_url", agent.NewWebAgentB(client, readURLSysPrompt))
agent.RegisterB("read_url", agent.NewWebAgentB(client, readURLSysPrompt))
// Register summarize_chat agent
agent.Register("summarize_chat", agent.NewWebAgentB(client, summarySysPrompt))
agent.RegisterB("summarize_chat", agent.NewWebAgentB(client, summarySysPrompt))
})
}

118
tui.go
View File

@@ -29,8 +29,6 @@ var (
statusLineWidget *tview.TextView
helpView *tview.TextView
flex *tview.Flex
bottomFlex *tview.Flex
notificationWidget *tview.TextView
imgView *tview.Image
defaultImage = "sysprompts/llama.png"
indexPickWindow *tview.InputField
@@ -38,7 +36,6 @@ var (
roleEditWindow *tview.InputField
shellInput *tview.InputField
confirmModal *tview.Modal
toastTimer *time.Timer
confirmPageName = "confirm"
fullscreenMode bool
positionVisible bool = true
@@ -140,8 +137,8 @@ func setShellMode(enabled bool) {
}()
}
// showToast displays a temporary notification in the bottom-right corner.
// It auto-hides after 3 seconds.
// showToast displays a temporary message in the topright corner.
// It autohides after 3 seconds and disappears when clicked.
func showToast(title, message string) {
sanitize := func(s string, maxLen int) string {
sanitized := strings.Map(func(r rune) rune {
@@ -157,68 +154,33 @@ func showToast(title, message string) {
}
title = sanitize(title, 50)
message = sanitize(message, 197)
if toastTimer != nil {
toastTimer.Stop()
}
// show blocking notification to not mess up flex
if fullscreenMode {
notification := tview.NewTextView().
SetTextAlign(tview.AlignCenter).
SetDynamicColors(true).
SetRegions(true).
SetText(fmt.Sprintf("[yellow]%s[-]\n", message)).
SetChangedFunc(func() {
app.Draw()
})
notification.SetTitleAlign(tview.AlignLeft).
SetBorder(true).
SetTitle(title)
// Wrap it in a fullscreen Flex to position it in the topright corner.
// Outer Flex (row) pushes content to the top; inner Flex (column) pushes to the right.
background := tview.NewFlex().SetDirection(tview.FlexRow).
AddItem(nil, 0, 1, false). // top spacer
AddItem(tview.NewFlex().SetDirection(tview.FlexColumn).
AddItem(nil, 0, 1, false). // left spacer
AddItem(notification, 40, 1, true), // notification width 40
5, 1, false) // notification height 5
// Generate a unique page name (e.g., using timestamp) to allow multiple toasts.
pageName := fmt.Sprintf("toast-%d", time.Now().UnixNano())
pages.AddPage(pageName, background, true, true)
// Autodismiss after 2 seconds, since blocking is more annoying
time.AfterFunc(2*time.Second, func() {
app.QueueUpdateDraw(func() {
if pages.HasPage(pageName) {
pages.RemovePage(pageName)
}
})
notification := tview.NewTextView().
SetTextAlign(tview.AlignCenter).
SetDynamicColors(true).
SetRegions(true).
SetText(fmt.Sprintf("[yellow]%s[-]\n", message)).
SetChangedFunc(func() {
app.Draw()
})
return
}
notificationWidget.SetTitle(title)
notificationWidget.SetText(fmt.Sprintf("[yellow]%s[-]", message))
go func() {
notification.SetTitleAlign(tview.AlignLeft).
SetBorder(true).
SetTitle(title)
// Wrap it in a fullscreen Flex to position it in the topright corner.
// Outer Flex (row) pushes content to the top; inner Flex (column) pushes to the right.
background := tview.NewFlex().SetDirection(tview.FlexRow).
AddItem(nil, 0, 1, false). // top spacer
AddItem(tview.NewFlex().SetDirection(tview.FlexColumn).
AddItem(nil, 0, 1, false). // left spacer
AddItem(notification, 40, 1, true), // notification width 40
5, 1, false) // notification height 5
// Generate a unique page name (e.g., using timestamp) to allow multiple toasts.
pageName := fmt.Sprintf("toast-%d", time.Now().UnixNano())
pages.AddPage(pageName, background, true, true)
// Autodismiss after 3 seconds.
time.AfterFunc(3*time.Second, func() {
app.QueueUpdateDraw(func() {
flex.RemoveItem(bottomFlex)
flex.RemoveItem(statusLineWidget)
bottomFlex = tview.NewFlex().SetDirection(tview.FlexColumn).
AddItem(textArea, 0, 1, true).
AddItem(notificationWidget, 40, 1, false)
flex.AddItem(bottomFlex, 0, 10, true)
if positionVisible {
flex.AddItem(statusLineWidget, 0, 2, false)
}
})
}()
toastTimer = time.AfterFunc(3*time.Second, func() {
app.QueueUpdateDraw(func() {
flex.RemoveItem(bottomFlex)
flex.RemoveItem(statusLineWidget)
bottomFlex = tview.NewFlex().SetDirection(tview.FlexColumn).
AddItem(textArea, 0, 1, true).
AddItem(notificationWidget, 0, 0, false)
flex.AddItem(bottomFlex, 0, 10, true)
if positionVisible {
flex.AddItem(statusLineWidget, 0, 2, false)
if pages.HasPage(pageName) {
pages.RemovePage(pageName)
}
})
})
@@ -273,7 +235,7 @@ func init() {
shellHistoryPos = -1
}
// Handle Tab key for @ file completion
if event.Key() == tcell.KeyTab && shellMode {
if event.Key() == tcell.KeyTab {
currentText := shellInput.GetText()
atIndex := strings.LastIndex(currentText, "@")
if atIndex >= 0 {
@@ -324,26 +286,12 @@ func init() {
SetDynamicColors(true).
SetRegions(true).
SetChangedFunc(func() {
// INFO:
// https://github.com/rivo/tview/wiki/Concurrency#event-handlers
// although already called by default per tview specs
// calling it explicitly makes text streaming to look more smooth
app.Draw()
})
notificationWidget = tview.NewTextView().
SetTextAlign(tview.AlignCenter).
SetDynamicColors(true).
SetRegions(true).
SetChangedFunc(func() {
})
notificationWidget.SetBorder(true).SetTitle("notification")
bottomFlex = tview.NewFlex().SetDirection(tview.FlexColumn).
AddItem(textArea, 0, 1, true).
AddItem(notificationWidget, 0, 0, false)
//
flex = tview.NewFlex().SetDirection(tview.FlexRow).
AddItem(textView, 0, 40, false).
AddItem(bottomFlex, 0, 10, true)
AddItem(textArea, 0, 10, true) // Restore original height
if positionVisible {
flex.AddItem(statusLineWidget, 0, 2, false)
}
@@ -412,14 +360,10 @@ func init() {
// y += h / 2
// return x, y, w, h
// })
notificationWidget.SetDrawFunc(func(screen tcell.Screen, x, y, w, h int) (int, int, int, int) {
y += h / 2
return x, y, w, h
})
// Initially set up flex without search bar
flex = tview.NewFlex().SetDirection(tview.FlexRow).
AddItem(textView, 0, 40, false).
AddItem(bottomFlex, 0, 10, true)
AddItem(textArea, 0, 10, true) // Restore original height
if positionVisible {
flex.AddItem(statusLineWidget, 0, 2, false)
}
@@ -1151,7 +1095,7 @@ func init() {
chatRoundChan <- &models.ChatRoundReq{Role: persona, UserMsg: msgText}
return nil
}
if event.Key() == tcell.KeyTab && !shellMode {
if event.Key() == tcell.KeyTab {
currentF := app.GetFocus()
if currentF == textArea {
currentText := textArea.GetText()