Build your own Perplexity clones, Devin clones, Agentic Workflow, and more
Building a Perplexity-style LLM answer engine: Front-to-Back-end tutorials
This warehouse has been popular for the past week
A wonderful introduction to building an answer engine from scratch!
Video:
Code: https://github.com/developersdigest/llm-answer-engine
Build an agent workflow from scratch🔁🤖
It’s tempting for AI engineers to use ready-made agents, but building your own agents is not scary (and limited to AI research papers only)!
In our new video tutorial, we show you how to build an agent in two intuitive steps:
1ˇ Define a single step that the agent performs: This is just a DAG that modifies state along the way. Link prompts, LLM, tool calls, and output parsing/processing together. Decide conditionally whether to call the tool or return.
2ˇ Insert this DAG into the proxy work program: The proxy work program will repeatedly call this DAG until it is completed!
All proxy flows can be decomposed in this way, making them easy to reason. In our tutorial, we show you how to build a ReAct agent from scratch.
Take a look:
Colab: https://colab.research.google.com/drive/1jRzrECJwqWY0bJWsTAVubsHW29ohFn-l? usp=sharing
Copilot in Excel allows anyone to do data analysis
@itsPaulAi for data analysis
It will provide you with recommendations about the data and process it for you.
Even if you don’t know anything about spreadsheets, how to use them are as follows:
X Original:https://x.com/itsPaulAi/status/1771570071212622006
If you want to learn more, you can click on the link below the video.
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Video: