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It's a RAG model (retrieval augmented generation). So what it does is it advises people to invest in a particular commodity or not. It basically is an advisor for commodity traders. Since, It's an rag model it gives the data extract fromm the data it has been given to analyze the past trends. You can ingest it with pdf for sentiment analysis and csv for past pricing trends. Just for Reviewers: The demo link isn't the fully functional actual project because what it requires isn't fulfilled by hack club like the computational requirements.

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@praneel23o on Ask AgPulse · about 3 hours ago

I made an AI advisor for commodity trading. So, my father works in finance field, I came to know about commodity trading. And then this idea hit me to revolutionise the field. Instead of randomly guessing what to invest in you ask the advisor about it. What I personally found challenging was connecting the data ingestion pipeline (I failed in it couple of times). Though it requires a little more of computational requirements. Then what nest could provide me, yet I got a symbolic representative demo. To use it download source code from GitHub and follow steps in readme.md. Hope y’all like it. Thanks for reading me.

1 devlog
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@praneel23o on Ask AgPulse · about 3 hours ago

23h 8m 10s logged

I am making a RAG model (retrieval augmented generation). So, what it does is it advises people to invest in a particular commodity or not. It basically is an advisor for commodity traders. Since It’s a rag model it gives the data extract fromm the data it has been given to analyze the past trends. You can ingest it with pdf for sentiment analysis and csv for past pricing trends.