{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone","slug":"opensource-voice-dictation-agent-wispr-flow-clone","name":"🎙️ OpenSource Voice Dictation Agent (Wispr Flow clone)","type":"agent","url":"https://github.com/akshayaggarwal99/jarvis-ai-assistant","page_url":"https://unfragile.ai/opensource-voice-dictation-agent-wispr-flow-clone","categories":["automation"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_0","uri":"capability://automation.workflow.push.to.talk.voice.dictation.with.native.keyboard.interception","name":"push-to-talk voice dictation with native keyboard interception","description":"Captures audio input via Fn key (hold-to-record) or double-tap (hands-free toggle) using a native C++ module (fn_key_monitor.node) that hooks into macOS keyboard events at the system level, bypassing Electron's renderer process limitations. The native module runs in the main process and communicates via IPC to trigger audio recording without application focus requirements, enabling dictation in any macOS application.","intents":["I want to dictate text into any application without switching focus or using mouse","I need a keyboard shortcut that works globally across all macOS apps, even when my app isn't active","I want to toggle hands-free recording mode with a double-tap gesture"],"best_for":["macOS desktop users who spend time in multiple applications (email, documents, code editors)","accessibility-focused users who need hands-free text input","developers building privacy-first voice tools on Electron"],"limitations":["macOS-only implementation — no Windows or Linux support due to platform-specific keyboard event APIs","Requires accessibility permissions (macOS Security & Privacy settings) which users must manually grant","Native module must be recompiled for both Apple Silicon (M1/M2/M3/M4) and Intel architectures","Fn key binding conflicts with system shortcuts on some Mac models or keyboard layouts"],"requires":["macOS 10.13 or later","Accessibility permissions granted to application in System Preferences","Node.js 18+ for native module compilation","Electron runtime with native module support"],"input_types":["keyboard events (Fn key press/release, double-tap detection)","audio stream from system microphone"],"output_types":["audio buffer (WAV/PCM format)","trigger signals to transcription pipeline"],"categories":["automation-workflow","native-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_1","uri":"capability://data.processing.analysis.dual.path.transcription.with.local.whisper.or.cloud.deepgram","name":"dual-path transcription with local whisper or cloud deepgram","description":"Implements a pluggable transcription architecture that routes audio to either local Whisper models (tiny/base/small via whisper-node-addon) for offline processing or cloud Deepgram API for high-speed transcription. The system abstracts transcription provider selection through a configuration layer, allowing users to toggle between privacy-first local processing and speed-optimized cloud processing without code changes. Audio is buffered in the renderer process and sent to the main process via IPC, which routes to the selected provider.","intents":["I want to transcribe speech to text without sending audio to the cloud for privacy","I need fast, accurate transcription with support for multiple languages and accents","I want to switch between local and cloud transcription based on network availability or accuracy needs"],"best_for":["privacy-conscious users who cannot send audio to cloud services","teams with strict data residency requirements (HIPAA, GDPR)","developers building voice tools with configurable transcription backends","users in regions with poor internet connectivity who need offline fallback"],"limitations":["Local Whisper models (tiny/base/small) have lower accuracy than cloud providers — WER typically 10-15% higher than Deepgram","Local transcription adds 2-5 second latency on M1/M2 Macs due to model inference time; larger models (medium/large) require 8GB+ RAM and are not bundled","Deepgram API requires valid API key and internet connectivity; no offline fallback if network fails mid-session","whisper-node-addon must be compiled separately for Apple Silicon vs Intel; pre-built binaries not included in repo","No support for streaming transcription with local Whisper — entire audio buffer must be processed before returning results"],"requires":["For local path: Node.js 18+, whisper-node-addon dependency, 2GB+ free disk space for model files","For cloud path: Deepgram API key, active internet connection","macOS 10.13+ with compatible CPU (Apple Silicon or Intel x64)"],"input_types":["audio buffer (WAV/PCM format, 16kHz sample rate)","language code (e.g., 'en', 'es', 'fr')","transcription provider config (local vs cloud)"],"output_types":["transcribed text string","confidence scores per word (Deepgram only)","language detection results"],"categories":["data-processing-analysis","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_10","uri":"capability://safety.moderation.zero.telemetry.privacy.model.with.no.analytics.collection","name":"zero-telemetry privacy model with no analytics collection","description":"Implements a privacy-first architecture with zero telemetry — no analytics libraries, no tracking pixels, no data collection beyond what's necessary for core functionality. The app does not send usage data, crash reports, or user behavior analytics to any external service. All processing (transcription, LLM post-processing) can be done locally without cloud connectivity, and cloud processing (Deepgram, LLM APIs) only sends audio/text when explicitly configured by the user.","intents":["I want to use a voice dictation app that doesn't track my usage or send data to analytics services","I need assurance that my voice recordings and transcripts are not collected or stored by the app developer","I want to use the app entirely offline without any telemetry or phone-home behavior"],"best_for":["privacy-conscious users who avoid commercial voice tools (Otter, Fireflies) due to data collection concerns","organizations with strict data privacy policies (HIPAA, GDPR, SOC 2)","developers building privacy-first voice applications","users in regions with strict data residency requirements"],"limitations":["No crash reporting — if the app crashes, users must manually report bugs without automatic error telemetry","No usage analytics — developers cannot track feature adoption or user behavior to inform product decisions","No error tracking service (Sentry, Rollbar) — bugs may go unnoticed if users don't report them","No opt-in analytics option — users cannot voluntarily share usage data to help improve the app","Offline-only mode requires users to manage their own Ollama server — no cloud fallback if local processing fails"],"requires":["No external dependencies for analytics or telemetry","Local-only processing (Whisper + Ollama) for full privacy, or cloud processing (Deepgram + LLM APIs) with user consent"],"input_types":["user configuration (provider selection)","audio input (microphone)","text input (settings)"],"output_types":["transcribed text","processed text","no telemetry data sent externally"],"categories":["safety-moderation","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_11","uri":"capability://automation.workflow.ios.beta.support.with.testflight.distribution","name":"ios beta support with testflight distribution","description":"Extends Jarvis to iOS via a beta version distributed through Apple TestFlight, enabling voice dictation on iPhone and iPad. The iOS implementation (ios/README.md) uses native iOS APIs for audio capture and keyboard integration, with the same dual-path architecture (local Whisper or cloud Deepgram) as the macOS version. TestFlight allows beta testing with up to 10,000 external testers before App Store release.","intents":["I want to use voice dictation on my iPhone or iPad, not just my Mac","I want to test the iOS version before it's released on the App Store","I want the same privacy-first, dual-path architecture on mobile as on desktop"],"best_for":["iOS users who want privacy-focused voice dictation on mobile","beta testers willing to provide feedback on iOS version","developers building cross-platform voice tools"],"limitations":["iOS version is in beta — features may be incomplete or unstable compared to macOS version","TestFlight distribution limits testing to 10,000 external testers — not available to general public","iOS native APIs differ significantly from macOS — code sharing between platforms is limited to business logic (LLM prompts, provider abstraction)","Local Whisper processing on iOS requires significant memory and CPU — may not work well on older devices (iPhone 11 or earlier)","iOS keyboard integration is more limited than macOS — no global Fn key equivalent, must use app-specific push-to-talk button","App Store review process may reject privacy claims if not fully substantiated — requires careful documentation"],"requires":["iOS 14+ (typical for modern iOS apps)","TestFlight app installed on iOS device","Apple ID for TestFlight access","Xcode 14+ for building iOS version"],"input_types":["audio input (microphone)","provider configuration (local vs cloud)","API keys (if using cloud providers)"],"output_types":["transcribed text","processed text","text insertion into active text field"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_2","uri":"capability://text.generation.language.ai.powered.post.processing.with.filler.removal.and.grammar.correction","name":"ai-powered post-processing with filler removal and grammar correction","description":"Chains transcribed text through an LLM-based post-processing pipeline that removes filler words ('um', 'like', 'uh'), corrects grammar, adds punctuation, and enhances readability. The system supports dual-path LLM routing: local Ollama server (models: sam860/LFM2:1.2b, llama3, mistral) for offline processing or cloud LLMs (Gemini, Claude, OpenAI) for higher quality. Post-processing is triggered automatically after transcription completes, with results cached to avoid re-processing identical transcripts.","intents":["I want my raw speech-to-text output cleaned up automatically — remove filler words and fix grammar","I need punctuation and capitalization added to my transcripts without manual editing","I want to choose between fast local processing or high-quality cloud LLM enhancement based on my needs"],"best_for":["users dictating long-form content (emails, documents, notes) who want publication-ready text","non-native English speakers who benefit from grammar correction","teams with strict data privacy requirements who need local LLM processing","developers building voice-to-text workflows that require text quality assurance"],"limitations":["Local Ollama models (1.2B-7B parameters) produce lower quality output than GPT-4 or Claude — grammar correction may miss complex syntax errors","Post-processing adds 1-3 second latency for local models, 2-5 seconds for cloud LLMs depending on text length and API response time","Ollama server must be running separately and configured with correct port (default 11434) — no built-in Ollama lifecycle management","Cloud LLM processing requires valid API keys (OpenAI, Anthropic, Google) and internet connectivity","Filler word removal is rule-based (hardcoded list) rather than context-aware — may incorrectly remove 'like' when used as a verb or comparison","No support for domain-specific terminology or custom vocabulary — LLM uses generic English model"],"requires":["For local path: Ollama installed and running, Node.js 18+, 4GB+ RAM for model inference","For cloud path: API key for OpenAI, Anthropic, or Google Gemini; active internet connection","macOS 10.13+"],"input_types":["raw transcribed text string","language code","LLM provider config (local Ollama vs cloud API)","optional: custom system prompt for LLM"],"output_types":["cleaned, punctuated text string","confidence score (cloud providers only)","processing metadata (latency, token count)"],"categories":["text-generation-language","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_3","uri":"capability://tool.use.integration.ipc.based.main.renderer.process.communication.with.security.sandboxing","name":"ipc-based main-renderer process communication with security sandboxing","description":"Implements a secure inter-process communication (IPC) bridge between Electron's main process (native module access, file I/O, API calls) and renderer process (UI, user interactions) using ipcMain and ipcRenderer with preload script isolation. The preload script (src/preload.ts) exposes a whitelist of safe IPC channels (e.g., 'start-recording', 'transcribe-audio', 'update-settings') to the renderer, preventing direct access to Node.js APIs and enforcing context isolation. Audio buffers and settings are marshaled through IPC as serialized JSON or binary data.","intents":["I need to safely communicate between the Electron main process (native modules, file system) and renderer process (UI) without exposing Node.js APIs","I want to ensure the renderer process cannot directly access sensitive operations like file I/O or native module calls","I need to pass audio buffers and configuration data between processes efficiently"],"best_for":["Electron developers building secure desktop applications with native module integration","teams implementing defense-in-depth security with process isolation","developers maintaining large Electron codebases with multiple renderer processes"],"limitations":["IPC message passing adds ~5-10ms latency per round-trip due to serialization and process boundary crossing","Large audio buffers (>10MB) may cause performance degradation or memory spikes if not streamed","Preload script whitelist must be manually maintained — adding new IPC channels requires code changes and app rebuild","No built-in request-response timeout mechanism — hung IPC calls can block UI indefinitely if not handled with Promise.race()","Binary data (audio buffers) must be converted to Base64 or ArrayBuffer for IPC serialization, adding ~33% overhead vs direct memory access"],"requires":["Electron 12+ (context isolation and preload script support)","Node.js 18+","TypeScript or JavaScript with async/await for IPC promise handling"],"input_types":["IPC channel name (string)","message payload (JSON-serializable object or binary data)","optional: callback function for async responses"],"output_types":["response data (JSON or binary)","error objects on IPC failure","event emitter for streaming responses"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_4","uri":"capability://automation.workflow.settings.persistence.with.electron.store.and.onboarding.flow","name":"settings persistence with electron-store and onboarding flow","description":"Persists user configuration (transcription provider, LLM choice, API keys, keyboard shortcuts) to disk using electron-store, a lightweight JSON-based key-value store that encrypts sensitive data (API keys) at rest. The onboarding interface (Onboarding Interface component) guides first-time users through provider selection (local vs cloud), API key configuration, and keyboard shortcut customization. Settings are loaded on app startup and cached in memory; changes trigger IPC updates to all processes and persist immediately to disk.","intents":["I want my transcription provider choice, API keys, and keyboard shortcuts to persist across app restarts","I want a guided setup flow that helps me choose between local and cloud processing on first launch","I want to update settings without restarting the app and have changes take effect immediately"],"best_for":["users who want to configure the app once and have settings persist","teams deploying Jarvis across multiple machines who need consistent configuration","developers building Electron apps with persistent user preferences"],"limitations":["electron-store uses unencrypted JSON by default — API keys are only encrypted if explicitly configured with a custom encryption key","No built-in settings versioning or migration — upgrading app versions may break settings if schema changes","Settings stored in user's home directory (~/.config/jarvis-ai-assistant on Linux/macOS) — no centralized settings server for team management","No conflict resolution for concurrent settings updates from multiple processes — last write wins","Onboarding flow is linear and cannot be skipped — users must complete all steps even if they only want to change one setting"],"requires":["Electron 12+","electron-store dependency (included in package.json)","Write access to user home directory","Node.js 18+"],"input_types":["setting key (string)","setting value (string, number, boolean, object)","optional: encryption key for sensitive data"],"output_types":["persisted setting value","settings object (all settings)","IPC event notification on settings change"],"categories":["automation-workflow","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_5","uri":"capability://data.processing.analysis.native.audio.capture.with.system.microphone.integration","name":"native audio capture with system microphone integration","description":"Captures audio from the system microphone using Web Audio API (in renderer process) or native audio APIs (via native modules in main process), with automatic gain control and noise suppression. Audio is buffered in memory as PCM samples at 16kHz sample rate, then sent to the transcription pipeline via IPC. The system handles microphone permission requests (macOS Privacy & Security) and gracefully degrades if microphone is unavailable or denied.","intents":["I want to record audio from my Mac's microphone when I press the Fn key","I need audio to be captured at high quality (16kHz, 16-bit PCM) for accurate transcription","I want the app to ask for microphone permissions on first launch and remember my choice"],"best_for":["macOS users who want to dictate using their built-in or external microphone","users in noisy environments who benefit from automatic gain control","developers building voice-input features in Electron apps"],"limitations":["Web Audio API (renderer process) has higher latency (~100-200ms) than native audio APIs due to browser security sandboxing","Automatic gain control and noise suppression are basic implementations — may not match quality of professional audio processing tools","Microphone must be granted permission in macOS System Preferences (Privacy & Security > Microphone) — no in-app permission prompt","Audio is buffered entirely in memory — very long recordings (>10 minutes) may cause memory pressure on machines with <4GB RAM","No support for selecting alternative audio input devices (external microphones, USB audio interfaces) — always uses system default"],"requires":["macOS 10.13+","Microphone permission granted in System Preferences","Electron runtime with Web Audio API support (all modern versions)","Node.js 18+ if using native audio modules"],"input_types":["microphone device (system default)","recording duration (seconds)","optional: audio processing settings (gain, noise suppression)"],"output_types":["audio buffer (PCM, 16kHz, 16-bit)","audio metadata (duration, sample count, format)"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_6","uri":"capability://automation.workflow.multi.architecture.native.module.compilation.for.apple.silicon.and.intel","name":"multi-architecture native module compilation for apple silicon and intel","description":"Builds and distributes native C++ modules (fn_key_monitor.node, whisper-node-addon) as separate binaries for Apple Silicon (ARM64) and Intel (x64) architectures using node-gyp and electron-builder. The build process compiles native code with platform-specific optimizations, signs binaries with Apple developer certificate, and packages both architectures into a universal macOS app. At runtime, the app loads the correct binary based on process.arch, ensuring optimal performance on each architecture.","intents":["I want to build native modules that work on both M1/M2 Macs and Intel Macs without users having to compile","I need to distribute pre-compiled native binaries that are signed and notarized by Apple","I want to ensure native modules run with optimal performance on each CPU architecture"],"best_for":["Electron developers shipping native modules across multiple macOS architectures","teams with CI/CD pipelines that need to build and sign binaries for distribution","open-source projects that want to avoid requiring users to compile native code"],"limitations":["Build process requires separate compilation for each architecture — cannot use cross-compilation, must build on native hardware or use CI/CD with architecture-specific runners","Native modules must be recompiled and re-signed whenever dependencies update (e.g., Whisper library updates) — no binary caching across versions","Apple notarization process adds 5-15 minutes to build time and requires valid Apple developer certificate and credentials","Pre-built binaries increase app size by 50-100MB depending on native module complexity","No automatic fallback if native module fails to load — app crashes with cryptic error if binary is corrupted or incompatible"],"requires":["Node.js 18+ with node-gyp installed","Xcode command-line tools (xcode-select --install)","Apple developer certificate for code signing","electron-builder for packaging and notarization","macOS 10.13+ for building (can cross-compile with additional setup)"],"input_types":["C++ source code","binding.gyp configuration file","platform target (arm64 or x64)"],"output_types":["compiled .node binary file","signed and notarized macOS app bundle","DMG installer for distribution"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_7","uri":"capability://automation.workflow.hands.free.toggle.mode.with.double.tap.gesture.detection","name":"hands-free toggle mode with double-tap gesture detection","description":"Implements a dual-mode interaction model where users can either hold Fn to record (single-press mode) or double-tap Fn to toggle hands-free recording on/off (toggle mode). The native keyboard module (fn_key_monitor.node) detects double-tap timing (two presses within 300ms) and switches recording state accordingly. In hands-free mode, the app continues recording until the user double-taps again, enabling dictation without holding a key.","intents":["I want to record hands-free by double-tapping Fn, so I can dictate while typing or using both hands","I need visual feedback (UI indicator) showing when hands-free recording is active","I want to quickly toggle hands-free mode on/off without switching to the app window"],"best_for":["users who dictate long passages and want to keep their hands free for other tasks","accessibility users who cannot hold a key continuously","developers building voice-first interfaces with toggle-based recording"],"limitations":["Double-tap detection is timing-based (300ms window) — may fail if user presses Fn slowly or with variable timing","No visual feedback in the app window if it's not focused — users cannot see hands-free status without switching to app","Hands-free mode has no automatic timeout — if user forgets to double-tap to stop, recording continues indefinitely until manual stop","Double-tap can conflict with accidental rapid key presses — may trigger hands-free mode unintentionally","No haptic feedback on Mac (unlike iOS) — users rely solely on visual UI indicator or audio cue"],"requires":["macOS 10.13+","Fn key available (not remapped to other function)","Accessibility permissions granted","Native module (fn_key_monitor.node) compiled and loaded"],"input_types":["keyboard events (Fn key press/release with timing)","double-tap threshold (milliseconds, default 300ms)"],"output_types":["hands-free mode state (boolean: on/off)","IPC event to update UI indicator","audio recording start/stop signals"],"categories":["automation-workflow","planning-reasoning"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_8","uri":"capability://automation.workflow.settings.ui.with.provider.selection.and.api.key.configuration","name":"settings ui with provider selection and api key configuration","description":"Provides a React-based settings interface (Settings Interface component) where users can select transcription provider (local Whisper vs Deepgram), LLM provider (local Ollama vs cloud APIs), and configure API keys securely. The settings UI is rendered in a separate Electron window and communicates with the main process via IPC to read/write settings to electron-store. Sensitive fields (API keys) are masked in the UI and encrypted at rest in the settings file.","intents":["I want a user-friendly UI to choose between local and cloud transcription without editing config files","I need to securely enter and store my API keys (Deepgram, OpenAI, Anthropic) in the app","I want to see which provider is currently active and easily switch providers"],"best_for":["non-technical users who want to configure the app via UI rather than config files","users managing multiple API keys for different providers","teams deploying Jarvis with standardized provider configurations"],"limitations":["Settings UI is modal and blocks main app interaction while open — no live preview of settings changes","API key validation is client-side only — invalid keys are not detected until first use","No support for multiple API key profiles or switching between accounts — only one key per provider stored","Settings changes require app restart for some options (e.g., Ollama server URL) — no hot-reload of configuration","UI is built with React but not integrated with a component library — styling is custom CSS, may have inconsistencies"],"requires":["Electron 12+","React 18+ (included in package.json)","electron-store for settings persistence","Valid API keys for cloud providers (optional if using local-only mode)"],"input_types":["provider selection (dropdown: 'local-whisper', 'deepgram', 'ollama', 'openai', etc.)","API key (text input, masked)","Ollama server URL (text input, default 'http://localhost:11434')","keyboard shortcut configuration"],"output_types":["updated settings object","IPC event to main process with new configuration","validation errors (if any)"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-opensource-voice-dictation-agent-wispr-flow-clone__cap_9","uri":"capability://automation.workflow.macos.app.signing.and.notarization.for.distribution","name":"macos app signing and notarization for distribution","description":"Automates code signing and Apple notarization of the macOS app bundle using electron-builder and custom build scripts. The build process signs the app with a valid Apple developer certificate, submits it to Apple's notarization service, and waits for approval before packaging the DMG installer. Notarized apps display no security warnings when users download and launch them, improving trust and reducing support burden.","intents":["I want to distribute a macOS app that doesn't show 'unidentified developer' warnings when users download it","I need to automate the code signing and notarization process in CI/CD so releases are fast and reliable","I want users to trust the app is legitimate and hasn't been tampered with"],"best_for":["open-source projects distributing macOS apps to end users","teams with CI/CD pipelines that need automated app signing and notarization","developers shipping Electron apps on macOS who want to avoid security warnings"],"limitations":["Requires valid Apple developer certificate ($99/year) and Apple ID credentials — not available for free or open-source developers without paying Apple","Notarization process is asynchronous and can take 5-15 minutes — build time is unpredictable","If notarization fails (e.g., malware detected), the entire build fails and must be retried — no partial success","Notarization credentials must be stored securely in CI/CD (environment variables or secrets) — risk of credential exposure","Revoked or expired certificates invalidate all previously notarized apps — users may see warnings on old versions"],"requires":["Apple developer account with valid certificate","Apple ID and app-specific password for notarization","electron-builder 24.0+","macOS 10.13+ for building","CI/CD environment with secure credential storage"],"input_types":["app bundle (Electron app directory)","Apple developer certificate (p12 file)","Apple ID credentials","notarization team ID"],"output_types":["signed app bundle","notarization ticket (UUID)","DMG installer ready for distribution"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":31,"verified":false,"data_access_risk":"high","permissions":["macOS 10.13 or later","Accessibility permissions granted to application in System Preferences","Node.js 18+ for native module compilation","Electron runtime with native module support","For local path: Node.js 18+, whisper-node-addon dependency, 2GB+ free disk space for model files","For cloud path: Deepgram API key, active internet connection","macOS 10.13+ with compatible CPU (Apple Silicon or Intel x64)","No external dependencies for analytics or telemetry","Local-only processing (Whisper + Ollama) for full privacy, or cloud processing (Deepgram + LLM APIs) with user consent","iOS 14+ (typical for modern iOS apps)"],"failure_modes":["macOS-only implementation — no Windows or Linux support due to platform-specific keyboard event APIs","Requires accessibility permissions (macOS Security & Privacy settings) which users must manually grant","Native module must be recompiled for both Apple Silicon (M1/M2/M3/M4) and Intel architectures","Fn key binding conflicts with system shortcuts on some Mac models or keyboard layouts","Local Whisper models (tiny/base/small) have lower accuracy than cloud providers — WER typically 10-15% higher than Deepgram","Local transcription adds 2-5 second latency on M1/M2 Macs due to model inference time; larger models (medium/large) require 8GB+ RAM and are not bundled","Deepgram API requires valid API key and internet connectivity; no offline fallback if network fails mid-session","whisper-node-addon must be compiled separately for Apple Silicon vs Intel; pre-built binaries not included in repo","No support for streaming transcription with local Whisper — entire audio buffer must be processed before returning results","No crash reporting — if the app crashes, users must manually report bugs without automatic error telemetry","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.34,"ecosystem":0.3,"match_graph":0.25,"freshness":0.9,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.28,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:21.010Z","last_scraped_at":"2026-05-03T14:00:07.640Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=opensource-voice-dictation-agent-wispr-flow-clone","compare_url":"https://unfragile.ai/compare?artifact=opensource-voice-dictation-agent-wispr-flow-clone"}},"signature":"YoaFtnC036G86UxtLv3h/6T0MT5zY9681NFgtSR8Iz1+OWYX5DQOcLVXqNnRNS1xSwdMMdiHFxA6UEJFVlABBA==","signedAt":"2026-06-15T18:36:04.174Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/opensource-voice-dictation-agent-wispr-flow-clone","artifact":"https://unfragile.ai/opensource-voice-dictation-agent-wispr-flow-clone","verify":"https://unfragile.ai/api/v1/verify?slug=opensource-voice-dictation-agent-wispr-flow-clone","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}