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Takura 7b9b1095d0 pipecat-friday-agent — Iron Man-inspired tactical voice assistant (F.R.I.D.A.Y.) with Pipecat, Gemini, and OpenAI. (#261 )

* feat: add pipecat-friday-agent skill and sync generated files

* chore: sync generated files and update changelog for pipecat-friday-agent

* fix: normalize path separators in data registry for cross-platform CI

* chore: sync generated registry files and resolve CI drift

* feat: Add initial skill catalog, aliases, and bundles data files and update README.

* fix: normalize path separators in skill utils and resolve CI drift

* feat: Introduce skill catalog, aliases, and bundles with a new utility and updated documentation.

* feat: Add new skill catalog data files for aliases, bundles, and the main catalog, and update total skill count.

* feat: Update skill and star counts, and registry sync metadata in README.md.

* chore: sync generated registry files

* chore: fix drift

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Co-authored-by: sck_0 <samujackson1337@gmail.com>

2026-03-10 19:13:49 +01:00

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description

Pipecat Friday Agent

Overview

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:

STT: OpenAI Whisper (whisper-1) or gpt-4o-transcribe
LLM: Google Gemini 2.5 Flash (via a compatibility shim)
TTS: OpenAI TTS (nova voice)
Transport: Local Audio (Hardware Mic/Speakers)

When to Use This Skill

Use when you want to build a real-time, conversational voice agent.
Use when working with the Pipecat framework for pipeline-based AI.
Use when you need to integrate multiple providers (Google and OpenAI) into a single voice loop.
Use when building Iron Man-themed or tactical-themed voice applications.

How It Works

Step 1: Install Dependencies

You will need the Pipecat framework and its service providers installed:

pip install pipecat-ai[openai,google,silero] python-dotenv

Step 2: Configure Environment

Create a .env file with your API keys:

OPENAI_API_KEY=your_openai_key
GOOGLE_API_KEY=your_google_key

Step 3: Run the Agent

Execute the provided Python script to start the interface:

python scripts/friday_agent.py

Core Concepts

Pipeline Architecture

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.

Google Compatibility Shim

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.

Best Practices

✅ Use Silero VAD: It is robust for local hardware and prevents background noise from triggering the LLM.
✅ Concise Prompts: Tactical agents should give short, data-dense responses to minimize latency.
✅ Sample Rate Match: OpenAI TTS outputs at 24kHz; ensure your audio_out_sample_rate matches to avoid high-pitched or slowed audio.
❌ No Polite Fillers: Avoid "Hello, how can I help you today?" Instead, use "Systems nominal. Ready for commands."

Troubleshooting

Problem: Audio is choppy or delayed.
- Solution: Check your OUTPUT_DEVICE index. Run a script like test_audio_output.py to find the correct hardware index for your OS.
Problem: "Validation error" for message format.
- Solution: Ensure the 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.

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