AI BriefingOpen Source Agent Frameworks and a Guide to Using ElevenAgents
Key point
This covers how to connect open source agent frameworks with ElevenLabs' Custom LLM to build voice-based agents.
Details
You can connect existing text-based agent orchestration to ElevenLabs's Custom LLM interface, building a flexible architecture that layers on voice capabilities while preserving state management and tool-use abilities.
To do this, you need to use a proxy layer to convert OpenAI-style messages into framework inputs, and stream the agent's voice output in SSE (Server-Sent Events) format. The entire process follows a three-step pattern: creating the generation request, extracting the final text response, and reformatting it into OpenAI-compatible SSE format.
The major frameworks include LangGraph, Google ADK, CrewAI, and LlamaIndex, and for real-time voice interaction, streaming chunks as soon as the model generates them is key to reducing latency.
In particular, LangGraph manages agent state through a graph model, and for real-time conversation flows, the messages streaming mode—which progressively delivers message chunks—is recommended over the values mode, which passes the entire state.
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