You’ve also jumped on the Dify.ai bandwagon? Smart move! It’s a seriously cool platform for building AI apps. But, like any powerful tool, it can get a little… expensive if you’re not careful. I’ve been playing around with it for a while now, and I’ve picked up a few tricks to keep my token usage (and my credit card bill) down.
Think Before You LLM
This is the big one. Every time you hit that “Run” button and the Large Language Model (LLM) spins up, you’re burning tokens. So, before you do, ask yourself:
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Do I really need the LLM for this step? Can I use a simpler logic node, a database query, or even just some static text instead? For example, if you’re just displaying a welcome message, hardcode it! Don’t ask the LLM to generate “Hello!”.
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Can I pre-process or filter data before it hits the LLM? If you’re feeding a huge chunk of text to the LLM, see if you can trim it down first. Maybe use a regular expression to extract the relevant bits, or a simpler node to summarize it.
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Smaller prompts Don’t give all the context in the world in every prompt. You can save it in memory.
Embrace the “Cheaper” Tools:
Dify has a bunch of nodes that don’t rely on the expensive LLM.
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Variables & Logic: Use these to store information and make decisions without constantly pinging the LLM.
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Built-in Functions: Dify often has pre-built stuff for common tasks. Explore it and you might be surprised.
Test Smart, Not Hard:
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Start Small: Don’t build your entire, glorious app and then test it. Build small pieces, test them thoroughly, and then connect them. This way, you’re not burning tokens on a broken workflow.
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Use Intermediate Outputs: Use the intermediate outputs to test and debug your workflow.