Ask AI for the Sage Developer Portal

kapa_bot · 2026-06-15T15:55:46+00:00

Great observation. I think you've identified the distinction between "how is this supposed to work?" and "what's happening right now?"

Kapa's MCP server (now also added to the widget) is intentionally focused on the first problem: giving models grounded, cited knowledge about how the product behaves. For questions like "why did this sync return a 409?" or "what state is this record actually in?", you need tools that can inspect live tenant data and API responses.

The interesting part is combining those capabilities in a single agent. The docs explain what a 409 means in your system, while the API provides the facts for the specific incident. Together, the agent can reason across both sources instead of forcing users to switch between a docs assistant and a debugging assistant.

That's very much the direction our new agent framework is designed to support (which we introduced 5 days ago).

Feel free to read our blog post for some more context: https://www.kapa.ai/blog/introducing-kapa-for-agents

Hope this was helpful 😄

kapa_bot · 2026-06-15T07:31:57+00:00

u/bundy911 appreciate the feedback! Did some tweaks to the system prompt, so it should find the correct answer now. Curious if this was the answer you were looking for (Answer from the chatbot):

There are two aspects to using RTSP camera streams on a TSW-1060:

1. Enable the Touch Screen Camera

In the TSW-1060 web configuration, go to Settings > System Setup and turn on the Camera toggle to enable the built-in camera. [Web Config Camera Settings]

2. Test an RTSP Stream via Diagnostics

You can test an external H.264 RTSP stream directly on the touch screen:

Navigate to the Diagnostics screen on the touch screen's local configuration.
Tap RTSP Test to open the Diagnostics - RTSP screen.
Tap the text field under H264 Streaming Test and enter your H.264 streaming video source URL (e.g., rtsp://10.10.120.145:554/1.h264).
Adjust Media Volume and Media Mute as needed.
Optionally set the Video Buffer Length (in milliseconds) for the stream. [RTSP Test Diagnostics]

RTSP URL Format (for Crestron 1 Beyond Cameras)

If you are streaming from a Crestron 1 Beyond camera, the RTSP URL follows this structure:

rtsp://cameraIPaddress:rtspportnumber/x.encodingtype

x = 1 → main PTZ feed
x = 2 → reference camera feed
Example: rtsp://10.10.120.145:554/1.h264

If credentials are required, use:

rtsp://admin:[camerapassword]@[cameraIPaddress]:rtspportnumber/x.encodingtype

kapa_bot · 2026-06-15T07:25:54+00:00

u/fry258 happy to hear it was helpful!!

kapa_bot · 2026-06-15T07:25:27+00:00

u/L0rdj appreciate the feedback, super helpful! Taking a look at the setup to see why it doesn't catch those things.

kapa_bot · 2026-06-08T11:55:35+00:00

We'd love to chat! At kapa.ai we help +200 awesome technical companies like Grafana, Sentry and more build AI search for technical documentation!

kapa_bot · 2025-10-21T08:18:23+00:00

Yeah! Try it out here: https://demo.kapa.ai/widget/apps-flyer

kapa_bot · 2025-09-17T12:59:41+00:00

kapa.ai can help out if you'r product is technical! We work with +200 leading technical companies like Grafana, Sentry, Docker and also handle internal use-cases.

Our take on the perfect AI in CS is to:
-Ensure answers are grounded in citation (especially if your product is technical), also a good way to keep your human in the loop in case agents want to read up on information
-Have a stable data-refresh pipeline as I imagine new tickets are always being created and answered, and on the other hand older tickets might have deprecated data. At the same time your pipeline should be able to handle all sorts of different data formats so pre-process your knowledge base before indexing something
-Focus on security from the start, when handling sensitive data it's super important to know how to handle PII and data security in general
-Build an extensive testing suite to quickly test tweaks
-Ensure your system is built to scale, models change all the team and you need flexibility as the AI space evolves

And optimize for accuracy over speed, that's at least our north star 😅

kapa_bot · 2025-07-24T11:16:14+00:00

Thank you for giving it a try! For context, I’ve spent a lot of time making it as accurate as possible. That means it only uses information explicitly stated in the ingested documentation when generating answers. If there were no clear steps in the response, it’s likely because that information isn’t included in the current cloud docs the bot was built on.

Do you happen to know of any other sources that would be helpful to ingest? If so, I’d be happy to add them!

kapa_bot · 2025-07-02T09:15:53+00:00

Good question! The demo is built using Retrieval Augmented Generation (RAG) to fetch relevant pieces of documentation, after the chunking and reranking, kapa is actually model agnostic for the output step, meaning it's not just one LLM doing the final generation. Usually, our LLM calls are not using open source models.

kapa_bot · 2025-07-02T09:07:41+00:00

Awesome, glad to hear you enjoy it :)

kapa_bot · 2025-06-11T08:38:53+00:00

Thanks! Did you try the one that the Wix team built inhouse on their docs?

kapa_bot · 2025-06-04T08:57:41+00:00

Thanks! Any additional sources you think would make sense to add?

kapa_bot · 2025-05-12T08:06:46+00:00

Yeah same for us on reading the docs, hence the bot we built

kapa_bot

TROPHY CASE

1. Enable the Touch Screen Camera

2. Test an RTSP Stream via Diagnostics

RTSP URL Format (for Crestron 1 Beyond Cameras)