Anukool: My job hunting assistant

Hey everyone!

I’ve been applying for jobs and found that writing a cover letter for each position was tedious. I also delved into LLM and Langchain, hoping to leverage them for a project to aid in my job hunting. So, I developed Anukool under the GPL license. While it’s far from perfect, it has proven very useful to me, and I hope it benefits you as well. All I have to do is provide it with a PDF containing information about me such as my experience, skills, projects, etc and it will use this information along with the job description to generate a cover letter for me. Since I’m new to ML and LLM, any advice or feedback is greatly appreciated, and contributions are also welcome. I plan to utilize Llama-2 soon to further open-source the project.

Check out the GitHub link, and please star it if you find the project interesting: GitHub - dakshesh14/anukool: An AI powered project to help job seekers by crafting cover letters.


Hi Anukool,

My name is Oladayo. I am excited with what you are doing with infusing AI into SaaS. I would like to collaborate with you on cool projects.

Kindly reach out.



Sure! Let’s connect

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Hello everyone! I just added a few more features to the project like llama-2 support and PDF generation.


That’s great.



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Very nice project, such simple but does what it has to do!

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Awesome Project Dakshesh, I’m also working on a similar kind of project, I need your assistance. I messaged you

That’s the goal

Yep replied.

cool idea. I plan on checking it out and in the meantime I have a question about its use of local models. Currently I have gguf models that are shared by a couple of llama.cpp applications as well as through python. What model formats does your application support?

I tried out the llama-2 7b model by TheBloke. The project should support all the models supported by the CTransformers class by long-chain. Please free to contribute to the project if you have any optimization/changes in mind.

yes I finally got around to trying and can confirm gguf model format is compatible. This means I can reuse downloaded models.

There are some considerations to using local models if one doesn’t want to use your model directory but I dropped you some github issues for them.

Now I need to figure out how to offload inference to gpu, at least some layers.

For personal use I can’t see the advantage over using my chat-gpt subscription as I get gpt4 performance at no additional api call costs. But I do appreciate seeing and learning from what you have put together. I had been playing with llama-index and gradio for similar rag and webui capabilities rather than fastai and langchain/huggingface so it was cool to see things done another way.

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I’m glad to hear that you’re able to use the project finally!

I’ve already started addressing the considerations you mentioned in the GitHub issue, and I believe I’ve found a way to tackle them. I’ll submit a PR for it as soon as possible.

Regarding the device choice for embedding & generation, I initially wanted to implement something for Nvidia GPUs, but lacking access to one, I’ve set the project to utilize CPU only. If you could figure out a way to configure this based on the user’s PC, that would be fantastic. Perhaps you could submit a PR for it.

While the project primarily serves as a learning tool, it offers several advantages over using just GPT-4:

  1. I’m able to utilize local models on my PC, ensuring all data remains on my device.
  2. I can upload huge PDF files about myself without worrying too much about token length.
  3. The existing API allows me to set up a cron job for automated job applications without manual intervention.

Above all, this project serves as a foundation for both myself and others navigating through LLMs and ML, providing a platform to build various interesting projects.

I want to express my gratitude for your time and valuable insights!

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