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Author SHA1 Message Date
github-actions[bot]
900b13f08c chore(release): Update version to v1.4.291 2025-08-18 15:05:02 +00:00
Kayvan Sylvan
6824f0c0a7 Merge pull request #1715 from ksylvan/0818-openai-transcribe-using-openai-models
Add speech-to-text via OpenAI with transcription flags and completions
2025-08-18 08:02:36 -07:00
Kayvan Sylvan
a2481406db feat: add speech-to-text via OpenAI with transcription flags and completions
CHANGES
- Add --transcribe-file flag to transcribe audio or video
- Add --transcribe-model flag with model listing and completion
- Add --split-media-file flag to chunk files over 25MB
- Implement OpenAI transcription using Whisper and GPT-4o Transcribe
- Integrate transcription pipeline into CLI before readability processing
- Provide zsh, bash, fish completions for new transcription flags
- Validate media extensions and enforce 25MB upload limits
- Update README with release and corrected pattern link path
2025-08-18 07:59:50 -07:00
15 changed files with 277 additions and 7 deletions

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@@ -99,6 +99,7 @@
"mbed",
"metacharacters",
"Miessler",
"mpga",
"nometa",
"numpy",
"ollama",

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@@ -1,5 +1,15 @@
# Changelog
## v1.4.291 (2025-08-18)
### PR [#1715](https://github.com/danielmiessler/Fabric/pull/1715) by [ksylvan](https://github.com/ksylvan): feat: add speech-to-text via OpenAI with transcription flags and comp…
- Add --transcribe-file flag to transcribe audio or video
- Add --transcribe-model flag with model listing and completion
- Add --split-media-file flag to chunk files over 25MB
- Implement OpenAI transcription using Whisper and GPT-4o Transcribe
- Integrate transcription pipeline into CLI before readability processing
## v1.4.290 (2025-08-17)
### PR [#1714](https://github.com/danielmiessler/Fabric/pull/1714) by [ksylvan](https://github.com/ksylvan): feat: add per-pattern model mapping support via environment variables

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@@ -57,6 +57,7 @@ Below are the **new features and capabilities** we've added (newest first):
### Recent Major Features
- [v1.4.290](https://github.com/danielmiessler/fabric/releases/tag/v1.4.290) (Aug 18, 2025) — **Speech To Text**: Add OpenAI speech-to-text support with `--transcribe-file`, `--transcribe-model`, and `--split-media-file` flags.
- [v1.4.287](https://github.com/danielmiessler/fabric/releases/tag/v1.4.287) (Aug 16, 2025) — **AI Reasoning**: Add Thinking to Gemini models and introduce `readme_updates` python script
- [v1.4.286](https://github.com/danielmiessler/fabric/releases/tag/v1.4.286) (Aug 14, 2025) — **AI Reasoning**: Introduce Thinking Config Across Anthropic and OpenAI Providers
- [v1.4.285](https://github.com/danielmiessler/fabric/releases/tag/v1.4.285) (Aug 13, 2025) — **Extended Context**: Enable One Million Token Context Beta Feature for Sonnet-4
@@ -648,7 +649,7 @@ Fabric _Patterns_ are different than most prompts you'll see.
Here's an example of a Fabric Pattern.
```bash
https://github.com/danielmiessler/fabric/blob/main/patterns/extract_wisdom/system.md
https://github.com/danielmiessler/Fabric/blob/main/data/patterns/extract_wisdom/system.md
```
<img width="1461" alt="pattern-example" src="https://github.com/danielmiessler/fabric/assets/50654/b910c551-9263-405f-9735-71ca69bbab6d">

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@@ -1,3 +1,3 @@
package main
var version = "v1.4.290"
var version = "v1.4.291"

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@@ -59,6 +59,13 @@ _fabric_gemini_voices() {
compadd -X "Gemini TTS Voices:" ${voices}
}
_fabric_transcription_models() {
local -a models
local cmd=${words[1]}
models=(${(f)"$($cmd --list-transcription-models --shell-complete-list 2>/dev/null)"})
compadd -X "Transcription Models:" ${models}
}
_fabric() {
local curcontext="$curcontext" state line
typeset -A opt_args
@@ -135,6 +142,9 @@ _fabric() {
'(--think-start-tag)--think-start-tag[Start tag for thinking sections (default: <think>)]:start tag:' \
'(--think-end-tag)--think-end-tag[End tag for thinking sections (default: </think>)]:end tag:' \
'(--disable-responses-api)--disable-responses-api[Disable OpenAI Responses API (default: false)]' \
'(--transcribe-file)--transcribe-file[Audio or video file to transcribe]:audio file:_files -g "*.mp3 *.mp4 *.mpeg *.mpga *.m4a *.wav *.webm"' \
'(--transcribe-model)--transcribe-model[Model to use for transcription (separate from chat model)]:transcribe model:_fabric_transcription_models' \
'(--split-media-file)--split-media-file[Split audio/video files larger than 25MB using ffmpeg]' \
'(--notification)--notification[Send desktop notification when command completes]' \
'(--notification-command)--notification-command[Custom command to run for notifications]:notification command:' \
'(-h --help)'{-h,--help}'[Show this help message]' \

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@@ -13,7 +13,7 @@ _fabric() {
_get_comp_words_by_ref -n : cur prev words cword
# Define all possible options/flags
local opts="--pattern -p --variable -v --context -C --session --attachment -a --setup -S --temperature -t --topp -T --stream -s --presencepenalty -P --raw -r --frequencypenalty -F --listpatterns -l --listmodels -L --listcontexts -x --listsessions -X --updatepatterns -U --copy -c --model -m --vendor -V --modelContextLength --output -o --output-session --latest -n --changeDefaultModel -d --youtube -y --playlist --transcript --transcript-with-timestamps --comments --metadata --yt-dlp-args --language -g --scrape_url -u --scrape_question -q --seed -e --thinking --wipecontext -w --wipesession -W --printcontext --printsession --readability --input-has-vars --no-variable-replacement --dry-run --serve --serveOllama --address --api-key --config --search --search-location --image-file --image-size --image-quality --image-compression --image-background --suppress-think --think-start-tag --think-end-tag --disable-responses-api --voice --list-gemini-voices --notification --notification-command --version --listextensions --addextension --rmextension --strategy --liststrategies --listvendors --shell-complete-list --help -h"
local opts="--pattern -p --variable -v --context -C --session --attachment -a --setup -S --temperature -t --topp -T --stream -s --presencepenalty -P --raw -r --frequencypenalty -F --listpatterns -l --listmodels -L --listcontexts -x --listsessions -X --updatepatterns -U --copy -c --model -m --vendor -V --modelContextLength --output -o --output-session --latest -n --changeDefaultModel -d --youtube -y --playlist --transcript --transcript-with-timestamps --comments --metadata --yt-dlp-args --language -g --scrape_url -u --scrape_question -q --seed -e --thinking --wipecontext -w --wipesession -W --printcontext --printsession --readability --input-has-vars --no-variable-replacement --dry-run --serve --serveOllama --address --api-key --config --search --search-location --image-file --image-size --image-quality --image-compression --image-background --suppress-think --think-start-tag --think-end-tag --disable-responses-api --transcribe-file --transcribe-model --split-media-file --voice --list-gemini-voices --notification --notification-command --version --listextensions --addextension --rmextension --strategy --liststrategies --listvendors --shell-complete-list --help -h"
# Helper function for dynamic completions
_fabric_get_list() {
@@ -74,8 +74,12 @@ _fabric() {
COMPREPLY=($(compgen -W "$(_fabric_get_list --list-gemini-voices)" -- "${cur}"))
return 0
;;
--transcribe-model)
COMPREPLY=($(compgen -W "$(_fabric_get_list --list-transcription-models)" -- "${cur}"))
return 0
;;
# Options requiring file/directory paths
-a | --attachment | -o | --output | --config | --addextension | --image-file)
-a | --attachment | -o | --output | --config | --addextension | --image-file | --transcribe-file)
_filedir
return 0
;;

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@@ -47,6 +47,11 @@ function __fabric_get_gemini_voices
$cmd --list-gemini-voices --shell-complete-list 2>/dev/null
end
function __fabric_get_transcription_models
set cmd (commandline -opc)[1]
$cmd --list-transcription-models --shell-complete-list 2>/dev/null
end
# Main completion function
function __fabric_register_completions
set cmd $argv[1]
@@ -92,6 +97,8 @@ function __fabric_register_completions
complete -c $cmd -l think-start-tag -d "Start tag for thinking sections (default: <think>)"
complete -c $cmd -l think-end-tag -d "End tag for thinking sections (default: </think>)"
complete -c $cmd -l voice -d "TTS voice name for supported models (e.g., Kore, Charon, Puck)" -a "(__fabric_get_gemini_voices)"
complete -c $cmd -l transcribe-file -d "Audio or video file to transcribe" -r -a "*.mp3 *.mp4 *.mpeg *.mpga *.m4a *.wav *.webm"
complete -c $cmd -l transcribe-model -d "Model to use for transcription (separate from chat model)" -a "(__fabric_get_transcription_models)"
complete -c $cmd -l notification-command -d "Custom command to run for notifications (overrides built-in notifications)"
# Boolean flags (no arguments)
@@ -127,6 +134,7 @@ function __fabric_register_completions
complete -c $cmd -l shell-complete-list -d "Output raw list without headers/formatting (for shell completion)"
complete -c $cmd -l suppress-think -d "Suppress text enclosed in thinking tags"
complete -c $cmd -l disable-responses-api -d "Disable OpenAI Responses API (default: false)"
complete -c $cmd -l split-media-file -d "Split audio/video files larger than 25MB using ffmpeg"
complete -c $cmd -l notification -d "Send desktop notification when command completes"
complete -c $cmd -s h -l help -d "Show this help message"
end

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@@ -74,6 +74,15 @@ func Cli(version string) (err error) {
return
}
// Handle transcription if specified
if currentFlags.TranscribeFile != "" {
var transcriptionMessage string
if transcriptionMessage, err = handleTranscription(currentFlags, registry); err != nil {
return
}
currentFlags.Message = AppendMessage(currentFlags.Message, transcriptionMessage)
}
// Process HTML readability if needed
if currentFlags.HtmlReadability {
if msg, cleanErr := converter.HtmlReadability(currentFlags.Message); cleanErr != nil {

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@@ -92,8 +92,12 @@ type Flags struct {
ThinkStartTag string `long:"think-start-tag" yaml:"thinkStartTag" description:"Start tag for thinking sections" default:"<think>"`
ThinkEndTag string `long:"think-end-tag" yaml:"thinkEndTag" description:"End tag for thinking sections" default:"</think>"`
DisableResponsesAPI bool `long:"disable-responses-api" yaml:"disableResponsesAPI" description:"Disable OpenAI Responses API (default: false)"`
TranscribeFile string `long:"transcribe-file" yaml:"transcribeFile" description:"Audio or video file to transcribe"`
TranscribeModel string `long:"transcribe-model" yaml:"transcribeModel" description:"Model to use for transcription (separate from chat model)"`
SplitMediaFile bool `long:"split-media-file" yaml:"splitMediaFile" description:"Split audio/video files larger than 25MB using ffmpeg"`
Voice string `long:"voice" yaml:"voice" description:"TTS voice name for supported models (e.g., Kore, Charon, Puck)" default:"Kore"`
ListGeminiVoices bool `long:"list-gemini-voices" description:"List all available Gemini TTS voices"`
ListTranscriptionModels bool `long:"list-transcription-models" description:"List all available transcription models"`
Notification bool `long:"notification" yaml:"notification" description:"Send desktop notification when command completes"`
NotificationCommand string `long:"notification-command" yaml:"notificationCommand" description:"Custom command to run for notifications (overrides built-in notifications)"`
Thinking domain.ThinkingLevel `long:"thinking" yaml:"thinking" description:"Set reasoning/thinking level (e.g., off, low, medium, high, or numeric tokens for Anthropic or Google Gemini)"`

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@@ -5,6 +5,8 @@ import (
"os"
"strconv"
openai "github.com/openai/openai-go"
"github.com/danielmiessler/fabric/internal/core"
"github.com/danielmiessler/fabric/internal/plugins/ai"
"github.com/danielmiessler/fabric/internal/plugins/ai/gemini"
@@ -70,5 +72,30 @@ func handleListingCommands(currentFlags *Flags, fabricDb *fsdb.Db, registry *cor
return true, nil
}
if currentFlags.ListTranscriptionModels {
listTranscriptionModels(currentFlags.ShellCompleteOutput)
return true, nil
}
return false, nil
}
// listTranscriptionModels lists all available transcription models
func listTranscriptionModels(shellComplete bool) {
models := []string{
string(openai.AudioModelWhisper1),
string(openai.AudioModelGPT4oMiniTranscribe),
string(openai.AudioModelGPT4oTranscribe),
}
if shellComplete {
for _, model := range models {
fmt.Println(model)
}
} else {
fmt.Println("Available transcription models:")
for _, model := range models {
fmt.Printf(" %s\n", model)
}
}
}

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@@ -0,0 +1,35 @@
package cli
import (
"context"
"fmt"
"github.com/danielmiessler/fabric/internal/core"
)
type transcriber interface {
TranscribeFile(ctx context.Context, filePath, model string, split bool) (string, error)
}
func handleTranscription(flags *Flags, registry *core.PluginRegistry) (message string, err error) {
vendorName := flags.Vendor
if vendorName == "" {
vendorName = "OpenAI"
}
vendor, ok := registry.VendorManager.VendorsByName[vendorName]
if !ok {
return "", fmt.Errorf("vendor %s not configured", vendorName)
}
tr, ok := vendor.(transcriber)
if !ok {
return "", fmt.Errorf("vendor %s does not support audio transcription", vendorName)
}
model := flags.TranscribeModel
if model == "" {
return "", fmt.Errorf("transcription model is required (use --transcribe-model)")
}
if message, err = tr.TranscribeFile(context.Background(), flags.TranscribeFile, model, flags.SplitMediaFile); err != nil {
return
}
return
}

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@@ -81,8 +81,10 @@ func TestGetChatter_WarnsOnAmbiguousModel(t *testing.T) {
if err != nil {
t.Fatalf("GetChatter() error = %v", err)
}
if chatter.vendor.GetName() != "VendorA" {
t.Fatalf("expected vendor VendorA, got %s", chatter.vendor.GetName())
// Verify that one of the valid vendors was selected (don't care which one due to map iteration randomness)
vendorName := chatter.vendor.GetName()
if vendorName != "VendorA" && vendorName != "VendorB" {
t.Fatalf("expected vendor VendorA or VendorB, got %s", vendorName)
}
if !strings.Contains(string(warning), "multiple vendors provide model shared-model") {
t.Fatalf("expected warning about multiple vendors, got %q", string(warning))

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@@ -0,0 +1,159 @@
package openai
import (
"bytes"
"context"
"fmt"
"os"
"os/exec"
"path/filepath"
"slices"
"sort"
"strings"
openai "github.com/openai/openai-go"
)
// MaxAudioFileSize defines the maximum allowed size for audio uploads (25MB).
const MaxAudioFileSize int64 = 25 * 1024 * 1024
// AllowedTranscriptionModels lists the models supported for transcription.
var AllowedTranscriptionModels = []string{
string(openai.AudioModelWhisper1),
string(openai.AudioModelGPT4oMiniTranscribe),
string(openai.AudioModelGPT4oTranscribe),
}
// allowedAudioExtensions defines the supported input file extensions.
var allowedAudioExtensions = map[string]struct{}{
".mp3": {},
".mp4": {},
".mpeg": {},
".mpga": {},
".m4a": {},
".wav": {},
".webm": {},
}
// TranscribeFile transcribes the given audio file using the specified model. If the file
// exceeds the size limit, it can optionally be split into chunks using ffmpeg.
func (o *Client) TranscribeFile(ctx context.Context, filePath, model string, split bool) (string, error) {
if ctx == nil {
ctx = context.Background()
}
if !slices.Contains(AllowedTranscriptionModels, model) {
return "", fmt.Errorf("model '%s' is not supported for transcription", model)
}
ext := strings.ToLower(filepath.Ext(filePath))
if _, ok := allowedAudioExtensions[ext]; !ok {
return "", fmt.Errorf("unsupported audio format '%s'", ext)
}
info, err := os.Stat(filePath)
if err != nil {
return "", err
}
debug := os.Getenv("FABRIC_STT_DEBUG") != ""
var files []string
var cleanup func()
if info.Size() > MaxAudioFileSize {
if !split {
return "", fmt.Errorf("file %s exceeds 25MB limit; use --split-media-file to enable automatic splitting", filePath)
}
if debug {
fmt.Fprintf(os.Stderr, "File %s is larger than the size limit... breaking it up into chunks...\n", filePath)
}
if files, cleanup, err = splitAudioFile(filePath, ext, MaxAudioFileSize, debug); err != nil {
return "", err
}
defer cleanup()
} else {
files = []string{filePath}
}
var builder strings.Builder
for i, f := range files {
if debug {
fmt.Fprintf(os.Stderr, "Using model %s to transcribe part %d (file name: %s)...\n", model, i+1, f)
}
var chunk *os.File
if chunk, err = os.Open(f); err != nil {
return "", err
}
params := openai.AudioTranscriptionNewParams{
File: chunk,
Model: openai.AudioModel(model),
}
var resp *openai.Transcription
resp, err = o.ApiClient.Audio.Transcriptions.New(ctx, params)
chunk.Close()
if err != nil {
return "", err
}
if i > 0 {
builder.WriteString(" ")
}
builder.WriteString(resp.Text)
}
return builder.String(), nil
}
// splitAudioFile splits the source file into chunks smaller than maxSize using ffmpeg.
// It returns the list of chunk file paths and a cleanup function.
func splitAudioFile(src, ext string, maxSize int64, debug bool) (files []string, cleanup func(), err error) {
if _, err = exec.LookPath("ffmpeg"); err != nil {
return nil, nil, fmt.Errorf("ffmpeg not found: please install it")
}
var dir string
if dir, err = os.MkdirTemp("", "fabric-audio-*"); err != nil {
return nil, nil, err
}
cleanup = func() { os.RemoveAll(dir) }
segmentTime := 600 // start with 10 minutes
for {
pattern := filepath.Join(dir, "chunk-%03d"+ext)
if debug {
fmt.Fprintf(os.Stderr, "Running ffmpeg to split audio into %d-second chunks...\n", segmentTime)
}
cmd := exec.Command("ffmpeg", "-y", "-i", src, "-f", "segment", "-segment_time", fmt.Sprintf("%d", segmentTime), "-c", "copy", pattern)
var stderr bytes.Buffer
cmd.Stderr = &stderr
if err = cmd.Run(); err != nil {
return nil, cleanup, fmt.Errorf("ffmpeg failed: %v: %s", err, stderr.String())
}
if files, err = filepath.Glob(filepath.Join(dir, "chunk-*"+ext)); err != nil {
return nil, cleanup, err
}
sort.Strings(files)
tooBig := false
for _, f := range files {
var info os.FileInfo
if info, err = os.Stat(f); err != nil {
return nil, cleanup, err
}
if info.Size() > maxSize {
tooBig = true
break
}
}
if !tooBig {
return files, cleanup, nil
}
for _, f := range files {
_ = os.Remove(f)
}
if segmentTime <= 1 {
return nil, cleanup, fmt.Errorf("unable to split file into acceptable size chunks")
}
segmentTime /= 2
}
}

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@@ -1 +1 @@
"1.4.290"
"1.4.291"