TechSage 🤖

TechSage is a multi-agent LLM platform delivering daily insights on technology, programming, cloud architecture, and more. Utilize OpenAI's LLMs or local models via Ollama, powered by CrewAI's multi-agent system, to stay ahead in the tech world.

Prerequisites • Installation • Configure • Launch • Docker

Prerequisites 💡

• Python >= 3.10, <= 3.13
• ollama (if using a local model) install here
• May need to install the c++ build tool if you don't already have it

Installation 🛠️

To install TechSage, run:

pip install https://github.com/VictorGoubet/techsage/archive/refs/tags/v1.tar.gz

Replace v1 with the release you want to use.

Configure [optional] ⚙️

Execute this command only if you want to use the shell interface with specific configuration. For the Streamlit interface, you can configure everything directly within it.

configure-sage

Configuration Options:

• --model <your-model-name>: Name of the model to use (default: llama3:8b).
• --model_url <your-model-url>: API URL of the model to use (default: http://localhost:11434/v1).
• --verbose <1 or 0>: Verbose level during configuration (default: 0).
• --local <True or False>: Use a local model with Ollama or an OpenAI API model (default: True).
• --openai_api_key <key>: Your OpenAI API key (required if local mode is disabled or using crew memory).
• --google_search_api_key <key>: Delpha Google Search API key. If empty, a local Google search will be performed. Modify api_google_search method in tools.py to use another API. A DuckDuckGo tool is also available.

Launch 🚀

After setting up, launch the script with admin rights. If no configuration is provided, the default configuration will be used:

launch-sage

Note: Be sure to have ollama running if you intend to use local models

Launch Options:

• --streamlit <true or false>: If true, the Streamlit interface will be used; otherwise, a shell interface will appear.

Docker 🐋

Lazy to setup everything ? Just use the dedicated docker image and go to http://localhost:8501

CPU only

docker run -d -v ollama:/root/.ollama -p 8501:8501 victorgoubet/techsage:latest

Nvidia GPU

First install GPU drivers for docker:

• Linux: NVIDIA Container Toolkit⁠.
• Windows: Nvidia Cuda on WSL
• Mac: Not supported

docker run -d --gpus=all -v ollama:/root/.ollama -p 8501:8501 victorgoubet/techsage:latest

Note: GPU version not really stable

App preview

---