Important
Hi people, i just woke up to 1k stars haha. I really appreciate the interest in my project, but its going to take some time for me to go through everything. Hope you understand :) Please open Issues (not dms / emails), i promise i will get to them asap
This is a completely locally running search engine using LLM Agents. The user can ask a question and the system will use a chain of LLMs to find the answer. The user can see the progress of the agents and the final answer. No OpenAI or Google API keys are needed.
Now with follow-up questions:
demo.mp4
- 🕵️ Completely local (no need for API keys)
- 💸 Runs on "low end" LLM Hardware (demo video uses a 7b model)
- 🤓 Progress logs, allowing for a better understanding of the search process
- 🤔 Follow-up questions
- 📱 Mobile friendly interface
- 🚀 Fast and easy to deploy with Docker Compose
- 🌐 Web interface, allowing for easy access from any device
- 💮 Handcrafted UI with light and dark mode
This project is still in its very early days. Expect some bugs.
Please read infra to get the most up-to-date idea.
- A running Ollama server, reachable from the container
- GPU is not needed, but recommended
- Docker Compose
Recommended, if you don't intend to develop on this project.
git clone https://github.com/nilsherzig/LLocalSearch.git
cd ./LLocalSearch
# 🔴 check the env vars inside the compose file and add your ollama servers host:port
docker-compose up 🎉 You should now be able to open the web interface on http://localhost:3000. Nothing else is exposed by default.
Newer features, but potentially less stable.
git clone https://github.com/nilsherzig/LLocalsearch.git
# 1. make sure to check the env vars inside the `docker-compose.dev.yaml`.
# 2. Make sure you've really checked the dev compose file not the normal one.
# 3. build the containers and start the services
make dev
# Both front and backend will hot reload on code changes. If you don't have make installed, you can run the commands inside the Makefile manually.
Now you should be able to access the frontend on http://localhost:3000.
Kinda looks like im botting haha