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This is awesome, I've been following time series forecasting a ton so build a zero-shot time series model that allows you to pass in historical data and provide a 98% accurate forecast compared to custom training your own model with custom dataset. https://jigsawstack.com/ai-prediction

if you find it interesting, you could add it to your articles too as a comparison :)


How do you solve the access control part? Did you build the layer ontop or more like a auth redirect?


Using OAuth2.0 standard for authentication & authorization then using the access token from that to call our APIs to track usage!


I think you can try the model


I ran Mistral AI OCR against JigsawStack OCR and beat their model in every category. Full breakdown here: https://jigsawstack.com/blog/mistral-ocr-vs-jigsawstack-vocr


Just a small fyi, as viewed on an iPhone in Safari your tables don’t allow horizontal scrolling, cutting off the right column


Looks great!! I would love to move to this as my go-to API client but my fear is it stops getting maintained overtime like httpie.io but at least this is open source so a great win!


Are there plans for future integrations into messaging platforms like Whatsapp or Telegram?


Cool stuff!


Multimodal is the ability to handle different type of inputs like images, pdf, text... You can do a quick google if you'd like to understand the meaning. Here is an article if it helps: https://www.splunk.com/en_us/blog/learn/multimodal-ai.html


I love the simplicity and wish there was more users to make this the true alternative


It's a framework that uses the best part of each LLM, e.g. multimodal support from gemini with tool calling from gpt-4o and reasoning from o3-mini by chaining them dynamically. From a user perspective, there is no model selection or routing, just write the prompt or upload a file and it works so it feels like you're working with a single LLM but under the hood it does all this work to get you the best output :) Sorry if you felt it's misleading but I hope you give it a shot!


The problem with that phrasing is that there is actual model merging, where you merge the weights. So people reading the title might (and apparently do) expect that, less so an LLM router.


Makes sense but the problem is that you're using words that already have specific meanings in the space, all related to creating one model with multiple functionalities. Merging meaning merging models into one model. Multi modal meaning one llm that handles multiple modes. The term you want is probably agent or framework or chain or something. Basically, what you describe is when it feels like you're only working with one model. What your title says is when you engineer specifically actually only one model, which is a distinct technical challenge.


I 100% agree, this simulates a multimodal input and automatically handles the rest along with model selection by using a variation of techniques. It doesn't do this natively on the model level


You are still not getting it. The use of the word multimodal does nothing good for your software. It is an LLM router. I get it that your software does support some multimodal LLMs, but that is incidental.

Secondly, the use of the word "merging" is also grossly misleading. You are not merging LLMs, only routing requests.


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