Which is more popular, agents or Pipecat?

Pipecat has more GitHub stars (16,142 vs 14,447).

Which is more actively developed, agents or Pipecat?

Pipecat had more commits in the last 90 days (2,861 vs 528).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

agents is growing faster: +1,358 GitHub stars in the last 30 days vs +833 for Pipecat.
Pick agents for: a framework for building realtime voice AI agents. Pick Pipecat for: open Source framework for voice and multimodal conversational AI.

From GitHub data refreshed daily.

agentsopen-source

A framework for building realtime voice AI agents 🤖🎙️📹

Open Source framework for voice and multimodal conversational AI

+Comprehensive multi-modal capabilities with flexible integrations for STT, LLM, TTS, and Realtime APIs in a single framework
+Built-in telephony integration allows agents to make and receive phone calls through LiveKit's telephony stack
+Advanced semantic turn detection using transformer models helps reduce interruptions and improve conversation flow

+Voice-first architecture with built-in speech recognition and text-to-speech integration for natural conversational experiences
+Comprehensive ecosystem with client SDKs for multiple platforms and additional tools for structured conversations and UI components
+Modular, composable pipeline system that supports integration with various AI services and transport protocols for flexible development

-Requires server infrastructure and technical expertise to deploy and maintain realtime voice agents
-Complex setup with multiple integration points may have a steep learning curve for newcomers
-Real-time voice processing demands significant computational resources and low-latency networking

-Python-only framework which may limit developers working primarily in other languages
-Real-time voice processing complexity may require significant learning curve for developers new to audio/video handling

•Customer service automation with voice-enabled agents that can handle phone calls and web-based interactions
•Virtual assistants for healthcare or education that need to see, hear, and respond in real-time conversations
•Interactive voice response (IVR) systems that integrate with existing telephony infrastructure for business applications

•Building voice assistants and AI companions for customer support, coaching, or meeting assistance applications
•Creating multimodal interfaces that combine voice, video, and images for interactive storytelling or creative content generation
•Developing business automation agents for customer intake, support workflows, or guided user interactions with structured dialog systems

Which is more popular, agents or Pipecat?: Pipecat has more GitHub stars (16,142 vs 14,447).
Which is more actively developed, agents or Pipecat?: Pipecat had more commits in the last 90 days (2,861 vs 528).
Should I use agents or Pipecat?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.