Builds low-latency Iron Man-inspired voice assistant (F.R.I.D.A.Y.) using Pipecat pipelines, Gemini LLM, OpenAI STT/TTS. For real-time local voice agents with VAD and multi-provider integration.
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scripts/friday_agent.pyDesigns and optimizes AI agent action spaces, tool definitions, observation formats, error recovery, and context for higher task completion rates.
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This skill provides a blueprint for building F.R.I.D.A.Y. (Replacement Integrated Digital Assistant Youth), a local voice assistant inspired by the tactical AI from the Iron Man films. It uses the Pipecat framework to orchestrate a low-latency pipeline:
whisper-1) or gpt-4o-transcribenova voice)You will need the Pipecat framework and its service providers installed:
pip install pipecat-ai[openai,google,silero] python-dotenv
Create a .env file with your API keys:
OPENAI_API_KEY=your_openai_key
GOOGLE_API_KEY=your_google_key
Execute the provided Python script to start the interface:
python scripts/friday_agent.py
The agent follows a linear pipeline: Mic -> VAD -> STT -> LLM -> TTS -> Speaker. This allows for granular control over each stage, unlike end-to-end speech-to-speech models.
Since Google's Gemini API has a different message format than OpenAI's standard (which Pipecat aggregators expect), the script includes a GoogleSafeContext and GoogleSafeMessage class to bridge the gap.
audio_out_sample_rate matches to avoid high-pitched or slowed audio.OUTPUT_DEVICE index. Run a script like test_audio_output.py to find the correct hardware index for your OS.GoogleSafeContext shim is correctly translating OpenAI-style dicts to Gemini-style schema.@voice-agents - General principles of voice AI.@agent-tool-builder - Add tools (Search, Lights, etc.) to your Friday agent.@llm-architect - Optimizing the LLM layer.