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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 نجوم·471 تفرعات·Python·apache-2.0·7 مشاهدات

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    ما هي الميزات الرئيسية لـ getstream/vision-agents؟

    الميزات الرئيسية لـ getstream/vision-agents هي: 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.

    ما هي البدائل مفتوحة المصدر لـ getstream/vision-agents؟

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