agent.network() Streaming Performance Issues: Batching Instead of Real-time
I'm experiencing a critical streaming performance issue with agent.network() while using the snapshot version 0.0.0-ai-sdk-network-text-delta-20251017172601.
I’m trying to stream responses using agent.network() to my frontend with the AI SDK v5's useChat() hook, similar to how agent.stream() provides character-by-character streaming. My goal is to display hundreds of text-delta chunks in real-time as they arrive.
What’s working:
✅ My backend sends hundreds of text-delta chunks, confirmed via the network tab.
✅ agent.stream() works flawlessly, providing smooth character-by-character streaming.
✅ All chunks are arriving at the browser and can be seen in DevTools.
What’s NOT working:
❌ agent.network() is batching chunks into 2-3 large groups instead of streaming them incrementally.
❌ Text appears all at once or in huge batches, lacking the desired character-by-character flow.
❌ The frontend indicates "2 big chunks" even though the backend is sending over 300 individual chunks.
Current implementation:
const networkStream = await agent.network(content, { /* options */ });
// Utilizing toAISdkFormat() with manual iteration
const { toAISdkFormat } = await import("@mastra/ai-sdk");
const { createUIMessageStream } = await import("ai");
const uiMessageStream = createUIMessageStream({
execute: async ({ writer }) => {
for await (const part of toAISdkFormat(networkStream, { from: 'network' })) {
writer.write(part); // Chunks are batched here!
}
}
});
return createUIMessageStreamResponse({ stream: uiMessageStream });
Root cause analysis:
The for await loop is batching the chunks before they are written. In contrast, with agent.stream(), I can simply use:
return streamResult.toUIMessageStreamResponse(); // Works perfectly!
However, MastraAgentNetworkStream lacks the .toUIMessageStreamResponse() method.
Questions:
- Will
.toUIMessageStreamResponse()be added to MastraAgentNetworkStream in a future snapshot? - Is there a method to read from MastraAgentNetworkStream directly without batching using
toAISdkFormat()? - Should I utilize
networkStream.getReader()to read chunks synchronously instead of async iteration?
Environment:
- Mastra snapshot:
0.0.0-ai-sdk-network-text-delta-20251017172601 - AI SDK: v5
- Next.js 15 (App Router)
- Frontend:
useChat()hook withstreamProtocol: 'data'
The network tab confirms that chunks are being received perfectly, indicating this issue is strictly related to backend transformation and batching. Any guidance would be immensely appreciated! 🙏
AI-Suggested Solution
To resolve the streaming issue with **agent.network()**, first, consider implementing Server-Sent Events (SSE) as an alternative to handle real-time updates more effectively. Ensure that the backend is appropriately optimized for streaming so that there is minimal delay in processing the individual chunks. Additionally, investigate the potential for utilizing the **toUIMessageStreamResponse()** method to facilitate a smoother integration of response data into the frontend. Lastly, review the network setup to identify any external factors, such as bandwidth constraints or VPN configurations, that may be impacting data transmission speed.
AI Research Summary
The user's complaint regarding the performance of agent.network() highlights a critical issue where streaming is not occurring as expected, instead resulting in batched responses that disrupt the desired character-by-character delivery. Many factors can contribute to such problems, as noted in various sources. Document 1 parallels this situation with a similar bug affecting content streaming speed in another framework, indicating that backend infrastructure may be a root cause. Meanwhile, Document 2 elaborates on the capabilities of the AI SDK v5 and mentions the toUIMessageStreamResponse() method, which could offer greater control over the streaming process. Performance issues can also stem from network connectivity, as discussed in Document 3, which provides troubleshooting steps relevant to this user's case. Further, Document 4 emphasizes the impact of environmental factors, such as the quality of Wi-Fi signals and network congestion, which may contribute to the user's experience of batching in response delivery. In alignment with this, Document 5 outlines specific issues associated with using VPNs that could exacerbate performance deficiencies akin to what the user is facing. Evaluating the routing and potential encapsulation problems highlighted in the network may prove beneficial in diagnosing ongoing challenges. The information provided in Document 6 stresses that even a fast internet connection does not guarantee efficient streaming, reinforcing the need for systemic optimizations. This sentiment is echoed in Document 7, which details common causes of slow media streaming—many of which could be explored to identify the source of the issue in agent.network(). Lastly, Document 8 presents SSE as a viable solution for streaming AI agents' responses, showcasing the effectiveness of alternative methods that emphasize real-time updates. Overall, these sources underscore the importance of addressing both backend optimization and user-side configuration to enhance streaming capabilities and meet expectations.
Frequently Asked Questions
Q: What could be causing the chunks to be batched instead of streamed?
A: The batching of chunks could be due to backend optimizations, network issues, or the way data is being processed in the frontend. Factors such as network latency, infrastructure limitations, and the usage of certain methods like **toAISdkFormat()** can all contribute to this problem.
Q: How can I achieve real-time streaming for my data?
A: Consider using Server-Sent Events (SSE) or similar non-batching streaming techniques to ensure continuous updates are sent as they are generated. Additionally, utilizing methods like **toUIMessageStreamResponse()** may also help in obtaining real-time results.
Q: Is there a workaround for the limitations of **agent.network()**?
A: Exploring the **toUIMessageStreamResponse()** method or directly reading from the stream using `networkStream.getReader()` could offer solutions to handle chunks more granularly. Adjusting backend processes is also crucial to ensure minimal batching.
Related Sources Found by AI
Our AI found 9 relevant sources related to this frustration:
This document reports on a bug related to the delayed character-by-character streaming in Open WebUI after an upgrade. It parallels the user's complaint by discussing issues with chunking responses and delays in streaming, indicating infrastructure might be a root cause.
This source provides guidance on integrating AI SDK v5 with features like the **streamText** API and discusses streaming response handling. It suggests using **toUIMessageStreamResponse()**, which is a relevant method that the user seeks for improved streaming performance.
This document addresses general performance issues related to network connectivity. It provides troubleshooting steps that might help the user assess whether their issue with **agent.network()** is related to backend processing or network latency, making it relevant for diagnosing the user’s complaint.
This article discusses various factors that contribute to streaming buffering, such as Wi-Fi signal strength and network congestion, providing a troubleshooting guide relevant to the user's issues with **agent.network()**. It underlines the necessity of evaluating local network conditions and hardware setups to enhance streaming performance, integrating well with the user’s complaint.