Replace OpenAI-only STT with a dual-provider system mirroring the TTS
architecture (Edge TTS free / ElevenLabs paid):
STT: faster-whisper local (free, default) / OpenAI Whisper API (paid)
Changes:
- tools/transcription_tools.py: Full rewrite with provider dispatch,
config loading, local faster-whisper backend, and OpenAI API backend.
Auto-downloads model (~150MB for 'base') on first voice message.
Singleton model instance reused across calls.
- pyproject.toml: Add faster-whisper>=1.0.0 as core dependency
- hermes_cli/config.py: Expand stt config to match TTS pattern with
provider selection and per-provider model settings
- agent/context_compressor.py: Fix .strip() crash when LLM returns
non-string content (dict from llama.cpp, None). Fixes#1100 partially.
- tests/: 23 new tests for STT providers + 2 for compressor fix
- docs/: Updated Voice & TTS page with STT provider table, model sizes,
config examples, and fallback behavior
Fallback behavior:
- Local not installed → OpenAI API (if key set)
- OpenAI key not set → local whisper (if installed)
- Neither → graceful error message to user
Co-authored-by: Jah-yee <Jah-yee@users.noreply.github.com>
- Removed fallback to OPENAI_API_KEY in favor of exclusively using VOICE_TOOLS_OPENAI_KEY for improved clarity and consistency.
- Updated environment variable checks to ensure only VOICE_TOOLS_OPENAI_KEY is considered, enhancing error handling and messaging.
- Updated the README to include new badges, a detailed description of the Hermes Agent, and a table summarizing its features, improving clarity and presentation for users.
- Modified the API client initialization in `transcription_tools.py` and `tts_tool.py` to include a base URL, ensuring compatibility with the OpenAI API.
- Updated the environment variable name from HERMES_OPENAI_API_KEY to VOICE_TOOLS_OPENAI_KEY across multiple files to avoid interference with OpenRouter.
- Adjusted related error messages and configuration prompts to reflect the new variable name, ensuring consistency throughout the codebase.
- Introduced logging functionality in cli.py, run_agent.py, scheduler.py, and various tool modules to replace print statements with structured logging.
- Enhanced error handling and informational messages to improve debugging and monitoring capabilities.
- Ensured consistent logging practices across the codebase, facilitating better traceability and maintenance.
