Solutions to simplify the configuration of your environment
For the problem of complex configuration of local running AI chatbot environment, DeepSeek-RAG-Chatbot provides a variety of simplified solutions. Firstly, we recommend the use of Docker containerized deployment, this way you can avoid the complex Python environment configuration, you only need to install Docker and then run thedocker-compose upcommand to install all dependencies and configure the environment.
The specific steps are as follows:
- 1. Install Docker Desktop (Windows/Mac) or Docker Engine (Linux)
- 2. Run in the project root directory
docker-compose upcommand - 3. Wait for Docker to pull the Ollama and chatbot service images automatically.
- 4. After the service has been activated, it is available at http://localhost:8501访问.
If Docker is not available, a Python virtual environment solution can be used:
- 1. Create a Python virtual environment to isolate dependencies
- 2. Utilization
pip install -r requirements.txtAutomatically install all dependencies - 3. Streamlining large model deployment through Ollama
For users with limited hardware, smaller model versions (e.g. 1.5B) are also available to reduce configuration requirements.
This answer comes from the articleDeepSeek-RAG-Chatbot: a locally running DeepSeek RAG chatbotThe
May not be reproduced without permission:AI productivity tools " How to solve the complexity of environment configurations encountered when running AI chatbots locally?
