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GetStream/Vision-Agents

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visionagents.ai↗

Vision Agents

Features

  • Multi-Modal Component Coordinators - Coordinates vision, audio, and language components into a single interactive agent for real-time video.
  • Local Agent Deployments - Runs AI agents on local hardware using microphone, speakers, and camera for development and demos.
  • Agent Knowledge Bases - Registers a search function that a language model can call to retrieve documents from a vector store.

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LLM Backend Attachments - Attaches a language model from a supported provider to a real-time video agent so it can process and respond to visual input.
  • Knowledge Base Retrieval - Queries a RAG backend in real time to supply the agent with relevant information while a call is active.
  • Component Metrics Collectors - Automatically collects latency, token usage, and error metrics from LLM, STT, TTS, and video processors.
  • Audio Stream Receivers - Receives audio data chunks from call participants for real-time analysis and processing.
  • Tool Call Configurations - Configures how many consecutive tool-calling rounds the language model may perform before returning control.
  • Cross-Session Conversation Memories - Stores conversation history and user state so the agent remembers past interactions across separate calls.
  • Conversational Turn Detection - Monitors silence gaps to signal when a speaker has finished talking.
  • Conversational Flow Controllers - Uses voice activity detection and diarization to create natural, interruption-aware dialogue flows.
  • Agent - Emits an event when the agent begins speaking, marking the start of an agent turn.
  • Turn Event Emitters - Notifies when a user or agent starts or stops speaking, allowing coordination of conversation flow.
  • Voice Agents - Creates a real-time voice assistant that users can talk to in a browser.
  • Custom Pipeline Assemblers - Assembles voice agents by plugging in separate STT, LLM, and TTS components from different providers for full pipeline control.
  • Speech-to-Text Provider Selection - Switches between different STT services like Deepgram or Wizper to balance accuracy, language support, and processing speed.
  • Speech Interruption Handlers - Detects when a user speaks over the agent and automatically stops the current response to listen to the new input.
  • Voice Activity Detection - Identifies when a person starts and stops speaking using configurable sensitivity and silence thresholds.
  • Programmatic Agent Spawning - Creates new agent sessions on demand via a POST endpoint for real-time call interactions.
  • OpenAI-Compatible APIs - Connects to any service that exposes an OpenAI-compatible API using the standard OpenAI plugin for integration.
  • MCP Server Connections - Attaches local or remote MCP servers so the agent can discover and use external tools.
  • Streaming Chat Responses - Sends model output incrementally as it is generated so users see results before the full response finishes.
  • AI Provider Integrations - Wraps provider APIs with a consistent interface so providers can be swapped without rewriting agent logic.
  • Twilio Voice Integrations - Handles inbound and outbound voice calls over Twilio with bidirectional audio streaming.
  • AI Voice and Video Integration - Connects any LLM, speech, or vision model from 25+ providers to create agents that process live audio and video streams.
  • Real-Time Transcription - Streams audio to a speech-to-text service via WebSocket and returns low-latency transcriptions with automatic language detection.
  • Local Object Detection - Runs object detection models on-device to avoid API calls and network latency.
  • Real-Time Object Detection - Identifies objects in real-time video frames using local detection models and emits events with bounding boxes and confidence scores.
  • Cross-Session Conversation Memories - Persists messages between interactions so the agent recalls prior exchanges and user details across separate calls.
  • External Tool Integration - Connects to external tools via the Model Context Protocol to extend the agent's capabilities.
  • Live Video - Identifies and registers known faces from a live camera feed using a face recognition model.
  • Function Calling Interfaces - Registers Python functions that the language model can invoke during a conversation to fetch data or perform actions.
  • Automatic Tool Executions - Automatically executes external tools when the language model decides to call a function.
  • LLM Model Integrations - Generates streamed text responses and handles function calling by implementing the LLM base class.
  • Expressive Synthesis - Generates natural-sounding speech from text with emotional nuance and vocal style.
  • Stage Direction Controllers - Embeds natural-language instructions in text to control articulation, intonation, volume, pitch, speed, and non-verbal sounds during speech synthesis.
  • Voice Cloning Tools - Provides voice cloning tools that create custom voices from WAV file samples for speech generation.
  • Spoken Language Detection - Automatically identifies the spoken language from audio streams without manual selection.
  • Final Response Events - Emits an event when the language model finishes generating a complete response.
  • Security Activity Querying - Provides a conversational AI agent that answers spoken questions about security activity in real time.
  • Real-Time Frame Processors - Intercepts video frames to run object detection pose estimation or custom machine learning models and forwards results to the language model.
  • Voice Synthesis - Converts text to spoken audio using multiple expressive voices with configurable settings.
  • Tool Call Executions - Executes code or connects to MCP servers to perform actions like creating tickets or checking weather during a call.
  • Model Parameter Configurations - Sets temperature, top_p, and deep thinking mode for a language model with sensible defaults.
  • Local Execution - Executes object detection and vision-language tasks on-device without cloud API calls, using a local GPU.
  • OpenAI API Clients - Connects an agent to OpenAI's language models via the Responses API or ChatCompletions API for conversational reasoning.
  • Interruption Response Handling - Flags application-triggered speech so it can be stopped mid-utterance when the user interrupts.
  • Barge-In Handlers - Stops speech output at the provider when a barge-in event occurs during conversation.
  • Retrieval Agents - Pulls relevant information from a vector database or file search to ground the agent's responses.
  • Retrieval-Augmented Agents - Retrieves relevant document chunks from a managed store to provide context for an agent's responses.
  • End-of-Speech Detectors - Automatically determines when a caller has finished speaking to trigger the next response.
  • Voice Cloning Engines - Implements voice cloning engines that generate custom synthetic voices from reference audio for TTS.
  • Speech-to-Text Conversions - Converts real-time audio input into text using pluggable providers, emitting partial transcripts for responsive UI.
  • Speech-to-Text Integrations - Processes incoming audio and emits transcript events by implementing a single abstract method on the STT base class.
  • Text-to-Speech Integrations - Provides a TTS integration that converts text to audio chunks with interruption support via stream and stop methods.
  • Speech to Text Transcription - Converts spoken audio into written text with automatic language detection, usable alongside text-to-speech in the same agent.
  • Text Generation - Generates text responses from user input using language models, supporting both single-turn and conversational interactions.
  • Audio-to-Audio Conversational Loops - Routes real-time audio from a phone call through WebSocket to an AI agent for listening and speaking during the conversation.
  • Audio Track Publishers - Outputs a custom audio track that is heard by participants in the live session.
  • Text-to-Speech - Synthesizes text into lifelike spoken audio using a text-to-speech service.
  • Speech-to-Speech Models - Accepts spoken language as input and produces a spoken response without separate STT or TTS services.
  • Speech-to-Speech Frameworks - Streams real-time speech-to-speech with optional video over WebSocket eliminating separate speech services.
  • Integrated STT/TTS Audio Streams - Processes real-time audio input and output over WebSocket using integrated speech-to-text and text-to-speech eliminating external speech services.
  • OpenAI Model Integrations - Connects to OpenAI's Responses API or any OpenAI-compatible endpoint to power agent reasoning and tool use.
  • Live Video Outfit Swapping - Swaps a user's outfit on live video by combining a text prompt with a reference image, applied atomically to avoid partial frames.
  • YOLO Object Detectors - Runs YOLO object detection on video frames in real time to identify and track objects.
  • Visual Question Answering - Responds to natural-language questions about the content of video frames using a vision-language model.
  • Voice Cloning - Provides voice cloning from reference audio samples for personalized speech output in real-time agents.
  • Multimodal LLM Models - Connects a multimodal reasoning model via an OpenAI-compatible API to process video and audio in real time.
  • Video Language Model Integrations - Processes video frames alongside text by implementing a VideoLLM base class and managing a frame buffer.
  • Video Pose Estimation - Identifies key body joints and draws skeleton overlays on video frames in real time using a pre-trained pose model.
  • Voice AI Agents - Builds a voice AI agent that listens, processes with an LLM, and responds with natural-sounding speech.
  • Lifecycle Managers - Manages the avatar's connection, audio consumption, and teardown sequence for real-time interaction.
  • Information Retrieval - Answers queries by searching over uploaded documents using automatic chunking and retrieval.
  • Cross-Node State Sharing - Shares session state across multiple servers via a shared key-value store for distributed agent management.
  • Agent-Integrated Functions - Attaches custom Python functions to the agent that the language model can invoke as tools.
  • Tool Function Registrations - Attaches Python functions to the agent that the language model can automatically invoke as tool calls during a conversation.
  • Production Deployments - Runs as an HTTP server with Prometheus metrics, horizontal scaling, and Kubernetes support.
  • AI Agent Deployments - Ships a Helm chart for deploying multi-modal AI agents to any Kubernetes cluster.
  • Lip-Sync Stream Synchronization - Streams a real-time interactive avatar with lip-sync, delivering synchronized video and audio.
  • Speech Synthesis & TTS - Converts text to natural-sounding speech using cloud-based neural or standard engines.
  • Frame-Based Question Answering - Receives video frames as input and processes them to answer questions or provide descriptions about what is visible in the footage.
  • Real-Time Video Analysis - Processes each frame of a participant's video track through custom or built-in analysis routines at a configurable frame rate.
  • Object Detection and Transformations - Detects objects, analyzes video content, and applies transformations like style transfer in real time.
  • Vision-Language Model Analyses - Processes live video frames through a vision-language model to extract understanding and generate responses.
  • Real-Time Stream Transformations - Applies visual transformations to a video stream and publishes the modified frames back into the call for other participants to see.
  • Real-Time Style Transfer - Transforms a live video stream by applying a chosen artistic style or prompt-based visual effect during the call.
  • Vision-Language Video Agents - Combines vision models with LLMs to watch, listen, and respond to live video streams with low latency.
  • Frame Buffering Pipelines - Buffers video frames as JPEGs and sends them alongside text prompts for multimodal reasoning and analysis.
  • Pluggable Processing Pipelines - Runs custom computer vision models like YOLO or Roboflow on video frames before or after an LLM call.
  • Real-Time Model Inference on Frames - Runs YOLO, Roboflow, or user-defined models on every frame of a live video stream for real-time detection and analysis.
  • Human Pose Detections - Runs a YOLO pose model on each video frame to identify keypoints and draw skeleton overlays as the stream arrives.
  • Live Video Stream Monitoring - Processes real-time video feeds to detect and track people, packages, and events as they happen.
  • Bidirectional Audio Streaming - Transmits audio in both directions over WebSocket to enable real-time voice interaction between caller and agent.
  • Custom Video Track Publishers - Outputs a custom video track (e.g., AI-generated content or avatars) that participants see in the live session.
  • Programmatic Call Joiners - Joins a video call as an async context manager, waiting for participants before proceeding with the conversation.
  • Twilio Call Connectors - Links a voice agent to Twilio for handling both inbound and outbound telephone calls.
  • Agent Performance Monitoring - Tracks latency, token usage, and errors across all components using OpenTelemetry, Prometheus, and Jaeger.
  • Interactive Video Avatar Generators - Drives an animated avatar that sees, hears, and responds via real-time audio and video streams.
  • Interruption Handlers - Pauses avatar output when the user speaks, enabling natural conversational turn-taking.
  • Synchronization Pipelines - Streams TTS audio to generate lip-synced avatar video and audio frames for call participants.
  • Lip Synchronization Engines - Produces a real-time visual character with lip movements synchronized to agent speech.
  • Provider-Agnostic LLM Routing - Sends requests to any supported language model provider through a single OpenAI-compatible interface, switching models without code changes.
  • Conversational Coaching Generators - Generates real-time coaching or guidance tailored to a conversation by analyzing transcribed speech.
  • Transport-Agnostic Agent Launchers - Uses the transport-agnostic agent launcher directly to serve agents via gRPC, WebSocket, or other protocols.
  • Agent Deployment Servers - Starts the agent as a server handling session creation, health checks, authentication, and metrics.
  • HTTP Agent Servers - Hosts the agent logic as an HTTP server for companion applications to connect and exchange data.
  • Idle Resource Terminators - Closes agent sessions automatically after a configurable idle timeout or maximum duration.
  • Tool Execution Observers - Emits start and end events for every tool call, reporting its name, arguments, success, and duration.
  • Regional Latency Optimizations - Optimizes end-to-end latency in Asia by pairing MiniMax with Tencent RTC edge transport.
  • Anthropic Claude Connections - Connects Claude models to agents for streaming text responses and function-calling decisions.
  • Regional Language Model Integrations - Connects to Sarvam AI's endpoint to use language models optimized for Hindi, English, and other Indian languages.
  • Hybrid Search Retrievers - Combines vector similarity and BM25 keyword matching using Reciprocal Rank Fusion for document retrieval.
  • Local Document Indexing - Ingests all files in a local folder, chunks them, and indexes them into a vector database for later retrieval.
  • Personality Configurators - Sets up the behavior and tone of the AI agent to match the desired interaction style.
  • Participant Join-Leave Emitters - Emits events when human participants join or leave a call for lifecycle tracking.
  • Interruption Sensitivity Configuration - Adjusts turn detection parameters to control how readily the agent stops speaking when the user starts talking.
  • Native Speech-to-Speech Agents - Uses OpenAI's speech-to-speech model over WebRTC to handle both speech recognition and synthesis without separate services.
  • Realtime Speech-to-Speech Agents - Creates a voice agent using a speech-to-speech model that handles audio input and output natively without separate components.
  • Agent Speech Turn Detections - Emits an event when the agent stops speaking, indicating whether the turn was interrupted by the user.
  • Storytelling Narrators - Ships a voice agent that listens to prompts, generates creative stories with an LLM, and speaks them back expressively.
  • Audio Filter Sensitivity Tunings - Adjusts the speech detection threshold and silence release duration to match the acoustic environment and expected pause lengths.
  • Tool Execution Event Reactions - Emits events at the start and end of a function or tool call, providing visibility into tool usage and performance.
  • URL Content Fetchers - Fetches and incorporates text from specific URLs to inform the agent's responses.
  • Web Search Tools - Augments agent replies by retrieving real-time information from the web through a built-in search tool.
  • Model Request Routing - Directs requests to a custom model deployed on a specific endpoint by providing the model's unique URL and API key.
  • Provider-Specific Model Selectors - Chooses among three model sizes from Sarvam AI to balance capability and performance for the agent's task.
  • AI Agent Plugins - Wraps any AI provider's API with a consistent interface so the agent framework can use it for speech, text, or video processing.
  • Meeting Transcriptions - Transcribes multi-speaker conversations in real time, identifying each speaker using a speech-to-text provider.
  • Final Transcript Subscriptions - Fires a handler when a user's speech transcription or the agent's LLM response is finalized, supporting logging or UI updates.
  • Agent Workflow Scripting - Runs arbitrary Python scripts within the agent's workflow for computations and data processing.
  • Cloud-Hosted Inference - Uses hosted inference to run pre-trained object-detection models without a local GPU.
  • Natural Language Object Detections - Identifies objects in video frames by describing them in natural language, without requiring pre-trained object classes.
  • Call Infrastructure Integrations - Adds a real-time conversational AI into existing call infrastructure without separate audio channels or complex routing.
  • Model Tier Selectors - Provides a configuration interface for selecting among MiniMax model tiers with different context windows and speeds.
  • Audio Routing Queues - Routes audio from each participant through a separate queue and uses a first-speaker-wins filter to decide whose speech reaches the agent.
  • Event-Triggered Notifications - Triggers notifications when face recognition, package detection, or other frame-level events are detected in a live feed.
  • MiniMax Connections - Configures MiniMax large language models as the agent's reasoning engine with multiple model tiers.
  • xAI Grok Connections - Connects to xAI's Grok models for conversation memory, streaming responses, and function calling.
  • Local Model Execution - Runs open-weight text language models on local hardware with streaming and function calling.
  • Local Speech-to-Text - Transcribes speech to text on the local machine using an accelerated Whisper model, with no API key required.
  • Pre-Deployed Endpoint Callers - Uses ready-made API endpoints for popular open-source models without requiring any deployment setup.
  • Voice Identity Selections - Provides voice identity selections for configuring engine and speaker identity to control speech tone.
  • Media Transport Connections - Accepts any transport layer for sending and receiving media, allowing the agent to work outside the default video pipeline.
  • AI Provider Interfaces - Switches between different AI models for video processing with a single configuration change.
  • Hot-Swappable Providers - Enables hot-swapping between different realtime AI models with a single configuration change.
  • HuggingFace Evaluations - Routes text-only language model requests through HuggingFace's unified API with streaming and function calling.
  • Runtime Provider Switching - Changes the backend provider for model inference by setting a single configuration parameter.
  • Hand - Highlights wrist positions and draws hand skeleton connections on detected poses during live video processing.
  • Real-Time Speech Translation - Translates transcribed speech into over 99 languages in real time, supporting ISO-639-1 language codes.
  • LLM Swap Integrations - Swaps LLM backends for avatars by subscribing to TTS and realtime audio without changing the avatar setup.
  • Session Connect-Disconnect Emitters - Emits events when realtime sessions connect or disconnect with session identifiers and reasons.
  • Grok Model Integrations - Connects to xAI's Grok models for advanced reasoning and real-time knowledge in AI agent pipelines.
  • Self-Hosted AI Models - Hosts open-source inference model routing and vector search on self-managed hardware.
  • Custom STT/LLM/TTS Pipeline Assemblers - Assembles speech-to-text, language model, and text-to-speech components into a custom processing pipeline.
  • Accelerated Transcriptions - Transcribes speech 2-4 times faster than standard methods by using optimized CPU and GPU compute engines.
  • Local Speech Synthesis - Generates speech from text locally on a CPU with ~200ms latency, no GPU or external API required.
  • Speech Synthesis Markup - Controls vocal delivery by inserting tags for emotions, pauses, and emphasis into text before it is spoken aloud.
  • Speech Parameter Configuration - Sets voice identity, language, and AWS region for text-to-speech generation through standard credential resolution.
  • Speech Synthesis Markup Controls - Generates natural-sounding speech from text with inline tags for whisper, laughter, and emotional tone adjustments.
  • AWS Bedrock Speech-to-Speech Streams - Transcribes and synthesizes speech in real time using Amazon Nova models with automatic session management.
  • Indian Language Speech Streams - Generates natural-sounding speech from text using Sarvam's Bulbul model for Indian languages.
  • Vision-Language Speech Integrations - Integrates separate STT and TTS providers alongside a vision language model for full conversational control.
  • Speech-to-Speech with Video Streams - Sends and receives real-time audio and optional video over WebSocket without separate speech recognition or synthesis services.
  • Vocal Nuance Controllers - Inserts pauses, breaths, laughs, and other vocal cues directly into text for fine-grained timing and expression.
  • Tool Execution Trackers - Emits events when a tool call starts and completes providing the tool name arguments result and execution time.
  • Unified API Text Inference - Routes text-only language model requests through HuggingFace's unified API with streaming and function calling.
  • Video Captioning - Generates descriptive text captions automatically for each video frame as it is processed.
  • Mid-Call Reference Image Swaps - Updates the reference image used for visual transformation atomically while the video stream is active.
  • Voice-Triggered Outfit Changes - Listens for spoken requests and triggers a costume swap on the video feed based on the voice input.
  • Detection Event Emitters - Emits an event when a video processor completes object detection, providing model ID, inference time, and detection count.
  • Vision-Language Inference - Processes video frames with vision-language models through HuggingFace's API with automatic frame buffering.
  • HuggingFace - Routes vision-language model requests through HuggingFace's unified API with automatic video frame buffering.
  • Multi-Voice Synthesis Engines - Generates spoken responses from text using cloud or local models from expressive to ultra-low latency.
  • Engine Selection Configurations - Ships engine selection configurations for choosing between standard and neural speech synthesis engines.
  • Lip-Sync Animations - Provides lip-sync animation for digital avatars to match spoken responses.
  • Provider-Backed Characters - Provides an abstract base class for implementing custom provider-backed animated characters.
  • Real-Time Video Overlayers - Receives a video stream, applies modifications or overlays (like bounding boxes), and publishes the altered frames back to the call.
  • NVIDIA Vision Model Integrations - Processes real-time video frames through NVIDIA's vision language models buffering frames automatically for continuous understanding.
  • Direct Text Speaking Utilities - Speaks a given text string using text-to-speech, bypassing the language model entirely.
  • Conversation History Backends - Accepts a user-defined storage backend by implementing an abstract conversation interface for message operations.
  • Transcription Term Boosts - Accepts a list of domain-specific words or phrases to improve transcription accuracy for those terms.
  • Vector Similarity Search - Finds documents by semantic meaning, returning results even when query words differ from the indexed text.
  • TTS Provider Selectors - Selects a voice from supported services like ElevenLabs or Cartesia and routes audio through the call automatically.
  • Session Concurrency Limiters - Caps the number of simultaneous agents and sessions per call to prevent resource exhaustion.
  • Keyword Matching - Matches exact query terms against indexed documents using BM25 for precise technical lookups.
  • Containerized Agent Packages - Packages a multi-modal AI agent into a container using CPU or GPU Dockerfiles for production.
  • Docker Image Building - Builds a containerized version of the agent for CPU or GPU environments to run anywhere.
  • Redis-Backed Session Stores - Adds a Redis-backed session store so multiple replicas can manage any session across nodes.
  • Edge Network Deployment - Deploys agents on distributed edge infrastructure to minimize latency for real-time voice interaction.
  • Tool Execution Round Limits - Configures how many consecutive tool-calling rounds the language model may perform before returning control.
  • Package Presence Detections - Monitors video for packages using a custom object detection model and alerts when packages are moved or stolen.
  • Packet-Level Audio Receivers - Emits events for each audio packet received from participants for custom processing.
  • Audio-Video Synchronization - Delays video frames to match audio buffer depth for accurate lip-sync.
  • Sports Swing Analyses - Uses pose detection to track body position from live video and provides spoken coaching feedback on the swing.
  • Media Track Management - Emits events when audio or video tracks are added to or removed from a call.
  • Real-Time Suggestion Overlays - Shows real-time suggestions on a semi-transparent overlay that stays visible without interrupting other applications.
  • Content Moderation Filters - Detects offensive gestures using a custom model running locally and applies a Gaussian blur to censor the video stream.
  • Play-by-Play Narration Generations - Feeds object-tracking data from a video stream to an LLM to produce live, spoken play-by-play narration.
  • Sports Commentary Generations - Combines object detection with real-time AI models to annotate live video and trigger commentary based on detected game events.
  • Chained Vision Processors - Runs a sequence of computer vision processors on video frames and passes annotated results to the language model.
  • Edge Network Routings - Routes audio and video through a global edge network with sub-500ms latency and frontend SDKs.
  • Native Vision Model Streams - Sends live video frames directly to a model with native vision support over WebRTC or WebSocket for the lowest latency.
  • Live Style Swaps - Alters the active visual style of a video stream on the fly through a function-calling interface.
  • Join-Leave Reactions - Triggers custom logic when participants join or leave a call for personalized interactions.
  • AI-Powered Inbound Call Answerers - Answers incoming phone calls with an AI agent that uses a knowledge base to provide product information.
  • RAG-Enhanced Call Answerers - Answers Twilio-powered voice calls and responds using knowledge retrieved from a RAG-backed vector store.
  • Webhook-Based Call Acceptors - Accepts incoming phone calls via webhook, validates the request, and starts a bidirectional media stream for AI processing.
  • Outbound Call Initiators - Programmatically places phone calls through the REST API and connects them to a media stream for real-time AI interaction.
  • Automated Outbound Dialers - Places phone calls automatically for tasks such as booking reservations without human initiation.
  • WebSocket PCM Audio Streams - Delivers synthesized speech as a continuous 16-bit PCM audio stream over a bidirectional WebSocket connection at a configurable sample rate.
  • Call Lifecycle Management - Emits events when the agent joins or leaves a call, and when the call itself ends.
  • Custom Session Storage Providers - Lets you plug in any TTL-capable key-value backend by implementing a small abstract interface for session data.
  • Performance Metrics Querying - Returns real-time performance data for running agent sessions including latency and token counts.
  • Session Access Controllers - Uses FastAPI permission callbacks to control who can start, view, close, or inspect sessions.
  • Agent Error Handlers - Captures errors from specific components and wraps handler exceptions into a unified error event.
  • Non-Realtime Error Events - Emits an event when a non-realtime language model error occurs with details and recoverability status.
  • Event Subscriber Exception Catchers - Catches unhandled exceptions from event subscribers and emits them as a single error event.
  • Escalating Verbal Warning Issuers - Generates spoken warnings that increase in severity with each offense using text-to-speech synthesis.
  • Agent Execution Tracing - Traces requests across agent components to debug latency issues using OpenTelemetry and Jaeger.
  • Security Event Notifications - Creates and posts notifications, including suspect images, to external services when a security event is detected.
  • Prometheus-Based Metric Exporters - Exports OpenTelemetry metrics to Prometheus for dashboarding and alerting on agent performance.
  • Video Feed Adjustments - Provides configurable video feed parameters for avatar appearance customization.
  • Audio Routing Pipelines - Implements audio routing through LLM pipelines for avatar video generation.
  • Plugin Event Emissions - Fires typed events from a plugin to communicate transcripts, errors, or custom data back to the agent framework.
  • Video Processing Event Emissions - Fires application-defined events during frame processing so other parts of the system can react to detected objects or conditions.
  • Component Events - Listens to events from all components in a single place using their respective event types.
  • Turn Completion Detection - Uses neural models to predict when a speaker has finished their conversational turn, enabling natural and intelligent turn-taking.
  • Realtime Connection State Listeners - Emits events when a realtime session connects or disconnects, providing session configuration and disconnection reason.
    • 6,029 Stars·471 Forks·Python·apache-2.0·7 Aufrufe

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    Häufig gestellte Fragen

    Was sind die Hauptfunktionen von getstream/vision-agents?

    Die Hauptfunktionen von getstream/vision-agents sind: Multi-Modal Component Coordinators, Local Agent Deployments, Agent Knowledge Bases, LLM Backend Attachments, Knowledge Base Retrieval, Component Metrics Collectors, Audio Stream Receivers, Tool Call Configurations.

    Welche Open-Source-Alternativen gibt es zu getstream/vision-agents?

    Open-Source-Alternativen zu getstream/vision-agents sind unter anderem: livekit/agents — This project is a framework for developing multimodal AI agents that function as programmable participants in… strands-agents/sdk-python — This is an open-source Python SDK for building and orchestrating production-grade AI agents. It provides a unified… pipecat-ai/pipecat — Pipecat is a framework and software development kit for building real-time multimodal AI agents and speech-to-speech… voltagent/voltagent. basedhardware/omi — Omi is an open-source wearable AI platform that captures audio and screen data to provide real-time conversational… mervinpraison/praisonai — PraisonAI is an autonomous AI agent platform that coordinates multiple LLM-powered agents for research, planning, and…