pipecat-friday-agent

name	pipecat-friday-agent
description	Build a low-latency, Iron Man-inspired tactical voice assistant (F.R.I.D.A.Y.) using Pipecat, Gemini, and OpenAI.
type	skill
created	2026-02-27T00:00:00.000Z
domain	ai-ml
category	llm-agents
risk	safe
source	community
tags	["skill","ai-ml","llm-agents","pipecat","friday","agent"]

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 matches to avoid high-pitched or slowed audio.