how I can use agent with APIs and with react?

Thanks for reaching out, Umair. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

could I use with fastapi?

Absolutely, LiveKit Agents work wonderfully with FastAPI! For instance, the

avatar_agents/audio_wave

example in the LiveKit Agents repository shows how FastAPI can serve as a dispatcher to launch and manage agent worker processes. Here’s a quick overview of how this works: • FastAPI sets up an HTTP server to handle requests for launching agents. • The server runs the FastAPI app using

uvicorn

. • There’s an endpoint (like

/launch

) that triggers the launch of an agent worker process whenever it receives an HTTP request. On top of that, LiveKit Agents can also connect with FastAPI-based services, such as using the OpenAI-compatible endpoint of Kokoro-FastAPI for text-to-speech (TTS) capabilities. If you'd like, I’m here to help guide you through setting this up—just let me know! Sources: examples/voice_agents/email_example.py

is retell ai using livekit?

Absolutely, Retell AI is using LiveKit. They made the switch from their own WebSocket setup to LiveKit Cloud, which really helps them connect smoothly with telephony systems, offer low-latency calls all around the world, and provide a seamless export interface for both web and phone calls. If you'd like, I’m here to share more details or answer any questions you have! Sources: AI voice agents | LiveKit Docs | LiveKit

how I can create my platform like theirs so users can create agents and then run it

I'm happy to guide you through creating a platform like Retell AI where users can create and run agents using LiveKit. Here’s a friendly step-by-step overview to get you started: 1. Build the Agent Backend • Start by using LiveKit's agent framework to define how your agents will behave. You can easily integrate helpful plugins like STT (for example, Deepgram), TTS (like ElevenLabs), and LLM (such as OpenAI) to enhance functionality. • Write your agent logic in Python or Node.js. For instance, you can define an entrypoint function that connects the agent to a LiveKit room and handles user interactions smoothly. • You have the flexibility to run the agent locally or deploy it on your own infrastructure—whichever works best for you. 2. Develop the Frontend • Try using the agent-starter-react template to build a React-based frontend. It supports voice, transcription, and AI avatars, making it a great starting point. • Alternatively, you can self-host the Agents Playground if you want a ready-to-use interface. • Feel free to customize the UI and features so your users can easily create and manage their agents. 3. Deploy and Scale • Consider deploying your platform using LiveKit Cloud—it offers elastic scaling, stateful load balancing, and operational observability to keep things running smoothly. • If you prefer full control, you can self-host the LiveKit server on your own infrastructure. 4. Additional Features • Think about enabling multi-agent handoffs to allow seamless conversation transfers between agents. • Integrate telephony with LiveKit SIP so agents can connect to phone calls effortlessly. • Writing automated tests can be a great way to ensure your agents behave as expected. If you’d like, I’m here to help with detailed guidance on any specific step—just let me know! Sources: LiveKit | Agents Overview | LiveKit Docs | TEMPLATE.md | Agents Playground | LiveKit Docs | Agents Playground | LiveKit Docs

How I can create the similar platform lite rettel ai

I'm excited to help you create a platform similar to Retell AI using LiveKit! Let's walk through the steps together: 1. Build the Agent Backend • Start by using LiveKit's agent framework to define how your agent will behave. You can integrate plugins for speech-to-text (STT), text-to-speech (TTS), and language models (LLM) to make your agent really come alive. • Write the agent logic in Python or Node.js. For example, you can define an entrypoint function that connects your agent to a LiveKit room and handles user interactions smoothly. • You have the flexibility to run your agent locally or deploy it on your own infrastructure—whichever works best for you. 2. Develop the Frontend • Try using the agent-starter-react template to build a React-based frontend. It supports voice, transcription, and AI avatars right out of the box. • If you prefer, you can also self-host the Agents Playground for a ready-to-use interface. • Feel free to customize the UI and features so your users can easily create and manage their agents. 3. Deploy and Scale • When you're ready, deploy your platform using LiveKit Cloud for elastic scaling, stateful load balancing, and great operational observability. • If you want full control, self-hosting the LiveKit server is a solid option too. 4. Additional Features • Consider enabling multi-agent handoffs to make conversations flow seamlessly between agents. • Integrate telephony with LiveKit SIP to connect your agents to phone calls effortlessly. • Don't forget to write automated tests to keep your agent behavior reliable and smooth. If you'd like, I'm here to provide more detailed guidance on any of these steps—just let me know how I can support you!

platform where users can signup and then create their own agents by adding nodes and tools who ever they want how we can do that when we dont know and user have option to create complete agent and then use users configuration to run the agent/publish it

I'd love to help you out! To make sure I understand exactly what you need, could you please share a bit more about the following? • How much customization would you like users to have when creating agents? For instance, should they be able to pick specific tools like STT, TTS, LLM, or even set up their own workflows? • Are you looking for advice on building a user-friendly interface for configuring agents, or is your main focus on the backend logic that runs these user-defined agents? • Would you like the platform to support real-time updates, or should it allow users to publish agents for use at a later time? Your answers will really help me guide you better and make sure we get everything just right.

• yes they can pick specific tools like STT, TTS, LLM, or even set up their own workflows? • yes • yes

I'm excited to help you create a platform where users can sign up, configure their own agents with tools like STT, TTS, and LLM, and set up workflows. Here’s a friendly step-by-step guide to get you started: 1. User Management • Start by implementing a user authentication and authorization system so users can easily sign up and manage their accounts. • Make sure to store user-specific configurations in a database, like their chosen tools and workflows, to keep everything personalized. 2. Agent Configuration Interface • Create a user-friendly interface where users can select tools (such as STT, TTS, LLM) and define workflows. Consider using drag-and-drop or form-based UI components to make it intuitive. • Offer options for users to input API keys or credentials for any third-party services they want to connect. 3. Backend Logic for Dynamic Agents • Build a backend service that dynamically generates agent configurations based on what users input. • Leverage LiveKit's agent framework to instantiate agents with the user-defined tools and workflows. For example, dynamically load plugins for STT, TTS, and LLM depending on user choices. 4. Publishing and Running Agents • Allow users to publish their agents, saving their configurations and preparing them for deployment. • When a user runs an agent, use their saved setup to initialize it and connect to a LiveKit room seamlessly. 5. Real-Time Updates • Enable real-time updates to agent configurations using WebSocket or similar technologies, so users can see changes right away. 6. Deployment and Scaling • Deploy the platform on scalable infrastructure like LiveKit Cloud to smoothly handle multiple users and agents at once. • Set up monitoring and logging to keep an eye on agent performance and user activity, ensuring everything runs smoothly. This approach empowers your users to fully customize their agents and workflows while taking full advantage of LiveKit's real-time features. If you’d like, I’m here to help with more detailed guidance on any of these steps—just let me know!

could you generate staging level code

I don't have the answer you're looking for. You could also try asking your question: • in one of the other Slack channels or • to https://deepwiki.com/livekit/livekit_composite which is trained on all LiveKit source code If you find the answer, please post it here to help others!