In an earlier post I wrote about using Semantic Kernel to create an Agentic AI solution, all using C#. Of course, similar flows can be created with Python. To try this, I’ve created a sample solution to update a resume so it’s more likely to pass the ATS requirements used by various companies nowadays.
My sample is heavilly inspired by Gian Paolo Santopaolo his CV-Pilot repository, which I was not able to use due to the CrewAI tooling phoning home and my DNS (PiHole) blocking those requests.
Read more →When working on a project that’s being distributed you are often required to create a NOTICE file giving the necessary attribution to work you rely on. As written on the Apache site on this topic:
If the Work includes a “NOTICE” text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear.
Read more →The current large language models, like GPT-4, GPT-4 Turbo and GPT-4o are great when you need some output generated based on data you feed in the prompt. Even the small language models, like Phi-3, are doing a great job at this. However, these models often don’t know a lot about the data within your company. Because of this, they can’t do a good job at answering questions that required data from your organization.
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