Solutions Engineer Companion Tool

This is a tool I made to help HashiCorp Solutions Engineers in their day-to-day work. It supports the following use cases:

• Helping to write self-reflections, Feature Requests or generally improve writing.
• Perform RAG on custom documents. Please see inside ./docs for further instructions.
• Perform RAG on public website information, created via the run_embed.sh script.

Dependencies

Hardware recommended

Mac with M1 Pro

Software dependencies

• Ollama - https://ollama.com/
• Docker
• Github access, to clone this repo
• Python 3.11

Usage

1. Clone the repo
2. Go to https://ollama.com/library and download some models. For example:
   • ollama pull mistral:7b
   • ollama pull llama3:8b

With Docker

1. Have Ollama running -> see run_ollama.sh.
2. Set OLLAMA_HOST in docker-compose.yaml to the IP of your machine.
3. Run docker compose up -d.

Note: Once I have a docker container published, this will be easier

Without docker

1. Have Ollama running -> see run_ollama.sh
2. Run from source with run_streamlit.sh

Using own documentation

You can drop multiple files into the ./docs folder and the app will load and create temporary in-memory embeddings for them, when loading the LLM. Currently supported file extensions are:

• csv
• pdf
• doc or docx
• ppt or pptx
• xls or xlsx
• md or mdx

Creating embeddings

The quality of the answers only goes as far as the quality of the LLM, prompt and embeddings.

For RAG, create embeddings with the run_embed.sh script or, if you work for HashiCorp, contact me directly.

See run_embed.sh and edit the environment variables accordingly.