@Sumanth_077: Open-source framework for building real-time voice AI agents! Pipecat is a Python framework for orchestrating audio, vi…

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Summary

Pipecat is an open-source Python framework for building real-time voice AI agents, handling speech recognition, text-to-speech, conversation logic, and supporting multiple AI service providers.

Open-source framework for building real-time voice AI agents! Pipecat is a Python framework for orchestrating audio, video, AI services, transports, and conversation pipelines. Voice-first architecture with pluggable components. What you can build: voice assistants, AI companions, multimodal interfaces, interactive storytelling, business agents (customer support, intake), and complex dialog systems. The framework handles speech recognition, text-to-speech, conversation logic, and real-time interaction. WebRTC and WebSocket transport built in. Ultra-low latency for natural conversations. Why Pipecat: • Voice-first: Integrates STT, TTS, and conversation handling in one framework • Pluggable: Supports multiple AI service providers for each capability • Composable pipelines: Build complex behavior from modular components • Real-time: Low-latency interaction with streaming audio/video Supported services: • Speech-to-Text: Deepgram, AssemblyAI, OpenAI Whisper, Groq, Azure, AWS, Google, and more • LLMs: OpenAI, Anthropic, Gemini, Groq, Mistral, Ollama, AWS, Azure, and more • Text-to-Speech: OpenAI, ElevenLabs, Deepgram, Cartesia, Azure, AWS, Google, and more • Speech-to-Speech: OpenAI Realtime, Gemini Multimodal Live, AWS Nova Sonic, Ultravox, Grok Voice Agent I've wrote a detailed tutorial on building a production customer support voice agent recently - covering turn detection, interruption handling, telephony codecs, and how to inject live business context into every call. I've quoted the article!
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Open-source framework for building real-time voice AI agents!

Pipecat is a Python framework for orchestrating audio, video, AI services, transports, and conversation pipelines. Voice-first architecture with pluggable components.

What you can build: voice assistants, AI companions, multimodal interfaces, interactive storytelling, business agents (customer support, intake), and complex dialog systems.

The framework handles speech recognition, text-to-speech, conversation logic, and real-time interaction. WebRTC and WebSocket transport built in. Ultra-low latency for natural conversations.

Why Pipecat:

• Voice-first: Integrates STT, TTS, and conversation handling in one framework • Pluggable: Supports multiple AI service providers for each capability • Composable pipelines: Build complex behavior from modular components • Real-time: Low-latency interaction with streaming audio/video

Supported services:

• Speech-to-Text: Deepgram, AssemblyAI, OpenAI Whisper, Groq, Azure, AWS, Google, and more • LLMs: OpenAI, Anthropic, Gemini, Groq, Mistral, Ollama, AWS, Azure, and more • Text-to-Speech: OpenAI, ElevenLabs, Deepgram, Cartesia, Azure, AWS, Google, and more • Speech-to-Speech: OpenAI Realtime, Gemini Multimodal Live, AWS Nova Sonic, Ultravox, Grok Voice Agent

I’ve wrote a detailed tutorial on building a production customer support voice agent recently - covering turn detection, interruption handling, telephony codecs, and how to inject live business context into every call.

I’ve quoted the article!

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