---
type: concept
title: "Streaming Responses"
description: "Streaming tokens and intermediate agent output to the user in real time instead of waiting for the full response."
tags: [streaming, ux, real-time]
videos: [ag-ui-just-released-the-new-wave-of-ai-agent-apps, 10x-your-ai-agents-with-this-one-agent-architecture, i-created-the-best-ai-agent-platform-in-just-2-months, weve-been-building-ai-agents-wrong-until-now, dont-sleep-on-the-ultimate-ai-agent-combo-n8n-langchain-python, the-best-tool-for-ai-agent-workflows-langgraph-full-guide, build-a-hilarious-ai-game-from-scratch-in-10-minutes, ai-agents-just-got-sexy-ai-agents-masterclass-3, i-made-a-custom-ai-chatbot-site-in-47-lines-of-code]
created: 2026-07-21
updated: 2026-07-21
---

# Streaming Responses

Streaming means pushing the agent's output to the user token by token as it is generated, instead of blocking until the full answer is ready. Cole treats it as table stakes: "it's definitely an expectation at this point that your AI agent will produce the output in real time. It'll actually look like the agent is typing out the answer to you, just like you've seen in things like Claude or GPT." The payoff is felt more than measured: "I think a lot of you appreciate having streamed output it just makes the agent feel snappier and more responsive." Streaming is not limited to plain text either, "now it's researching the web and you can see that in real time it gives me updates as to what it is searching the web with," so the user sees "every step of the way... in real time so I don't have to wait for the whole NN workflow to finish."

Mechanically, streaming is a loop over chunks that the front end accumulates. "we're going to loop over all the chunks that we're getting back as we're getting the output in real time... So our front end can build up that response over time, displaying it in real time to the user." In Python the idiom is a generator: "I have a little bit of code here to go through all the chunks as it is producing the stream in the typewriter format and I am Gathering that all together and also yielding these chunks as a generator." Frameworks expose this as async event streams, "we're going to use the asynchronous stream events function so every single time there's a new Chunk from the AI we're going to get this in this asynchronous for Loop," which is why streaming nodes must be async, "this is going to be in a synchronous node because we want to stream out the responses so that we have that nice typewriter style." On the UI side a helper often just writes the stream out, in Streamlit "we now get a stream that we write out to Streamlit using the nice built-in component st. right stream."

Streaming also composes with structured output, though with a caveat. When an agent streams a typed response "the output that you get over time as it streams out the tokens is going to look something like this where it slowly builds up the values in the dictionary," a partial object growing field by field. Where the app needs the whole object before acting, true token streaming has to be faked: "we can't use OpenAI stream because we need to get the Json do something with it and then give it to the user but we can mimic that kind of streaming through this nice little helper function."

## Builds on

- [The Agent Loop (Reason-Act-Observe)](./agent-loop.md) - streaming surfaces each observe/act step as it happens.
- [Structured Outputs](./structured-outputs.md) - a streamed structured response builds up the dictionary value by value.

## Related

- [Generative UI](./generative-ui.md) - streamed tokens and tool activity feed the live UI.
- [Frontend-Agnostic Agents](./frontend-agnostic-agent.md) - the chunk stream is the contract any front end consumes.
- [Tool Design](./tool-design.md) - streaming intermediate tool progress back to the user.
- [Agentic RAG](./agentic-rag.md) and [Agentic Search](./agentic-search.md) - live "now searching..." updates during multi-step retrieval.
- [Memory Systems](./memory-systems.md) - the streamed message is appended to conversation history.

## Tools

- [LangGraph](../entities/tools/langgraph.md) - async `stream_events` for chunk-by-chunk output from graph nodes.
- [LangChain](../entities/tools/langchain.md) - streaming primitives used in the n8n + Python combo.
- [Streamlit](../entities/tools/streamlit.md) - `st.write_stream` renders the typewriter effect.
- [n8n](../entities/tools/n8n.md) - streams intermediate workflow steps back to the user.
- [OpenAI](../entities/organizations/openai.md) - the stream API behind many of these builds.

## Sources

- [AG-UI Just Released: The NEW WAVE of AI Agent Apps](../sources/ag-ui-just-released-the-new-wave-of-ai-agent-apps.md) - "[0:02:26] it's definitely an expectation at this point that your AI agent will produce the output in real time. It'll actually look like the agent is typing out the answer to you, just like you've seen in things like Claude or GPT."
- [AG-UI Just Released: The NEW WAVE of AI Agent Apps](../sources/ag-ui-just-released-the-new-wave-of-ai-agent-apps.md) - "[0:11:34] we're going to loop over all the chunks that we're getting back as we're getting the output in real time... So our front end can build up that response over time, displaying it in real time to the user."
- [10x Your AI Agents with this ONE Agent Architecture](../sources/10x-your-ai-agents-with-this-one-agent-architecture.md) - "[0:27:32] when you run an agent in stream mode and it outputs a structured response the output that you get over time as it streams out the tokens is going to look something like this where it slowly builds up the values in the dictionary."
- [THE BEST Tool for AI Agent Workflows - LangGraph FULL Guide](../sources/the-best-tool-for-ai-agent-workflows-langgraph-full-guide.md) - "[0:19:49] we're going to use the asynchronous stream events function so every single time there's a new Chunk from the AI we're going to get this in this asynchronous for Loop."
- [Don't Sleep on the ULTIMATE AI Agent Combo (n8n, LangChain, Python)](../sources/dont-sleep-on-the-ultimate-ai-agent-combo-n8n-langchain-python.md) - "[0:18:42] I have a little bit of code here to go through all the chunks as it is producing the stream in the typewriter format and I am Gathering that all together and also yielding these chunks as a generator."
- [We've Been Building AI Agents WRONG Until Now](../sources/weve-been-building-ai-agents-wrong-until-now.md) - "[0:16:00] I also implemented text streaming and so we'll see in typewriter style the output coming out from the llm in real time so we don't have to wait for it to fully finish."
- [I Created the BEST AI Agent Platform in Just 2 MONTHS!](../sources/i-created-the-best-ai-agent-platform-in-just-2-months.md) - "[0:10:28] it's just so cool how like every step of the way it's updating me in real time so I don't have to wait for the whole NN workflow to finish."
- [AI Agents Just Got Sexy - AI Agents Masterclass #3](../sources/ai-agents-just-got-sexy-ai-agents-masterclass-3.md) - "[0:11:05] we now get a stream that we write out to Streamlit using the nice built-in component st. right stream."
- [Build a Hilarious AI Game from SCRATCH in 10 Minutes](../sources/build-a-hilarious-ai-game-from-scratch-in-10-minutes.md) - "[0:03:43] we can't use OpenAI stream because we need to get the Json do something with it and then give it to the user but we can mimic that kind of streaming through this nice little helper function."
- [I Made a Custom AI Chatbot Site in 47 Lines of Code](../sources/i-made-a-custom-ai-chatbot-site-in-47-lines-of-code.md) - "[0:07:17] you could see it typing out the response... you can see that it wasn't just instantaneously the entire response thrown into the UI."
