3 个仓库
Awesome GitHub RepositoriesInput Processing Logic
Logic for monitoring and handling incoming text messages to trigger agent responses.
Distinct from Text Input Managers: Focuses on the processing logic for chat-based input, distinct from UI text editing management.
Explore 3 awesome GitHub repositories matching user interface & experience · Input Processing Logic. Refine with filters or upvote what's useful.
Awesome Input Processing Logic GitHub Repositories
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- letta-ai/letta
letta-ai/letta
21,168在 GitHub 上查看Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com
Categorizes and processes incoming user data to manage interaction flow.
Pythonaiai-agentsllm - livekit/livekit
livekit/livekit
19,358在 GitHub 上查看LiveKit is a comprehensive framework for building and orchestrating real-time, multimodal AI agents that interact with users through voice, video, and text. It provides a centralized, event-driven architecture to manage the entire lifecycle of automated participants, from initialization and session state management to graceful shutdown. By utilizing a selective forwarding unit, the platform efficiently routes media streams between participants and agents, ensuring low-latency communication and secure, token-based authentication for all connections. The platform distinguishes itself through it
Monitors incoming chat messages to trigger agent responses and allows for custom handling logic.
Gogolangmedia-serversfu - livekit/agents
livekit/agents
9,379在 GitHub 上查看This project is a framework for developing multimodal AI agents that function as programmable participants in real-time communication rooms. It enables the construction of agents that can see, hear, and speak by integrating speech-to-text, large language models, and text-to-speech pipelines to facilitate low-latency, natural conversations. The system is distinguished by its advanced orchestration of real-time media and conversational flow, including support for full-duplex speech, preemptive response generation, and sophisticated interruption management. It further differentiates itself throu
Processes incoming text messages from room participants to trigger autonomous agent responses.
Pythonagentsaiopenai
