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Installation guide

ChemCoScientist depends on several services: ChromaDB, embedding and reranker services, MinIO (S3), AutoML, and generative models. Each runs in its own separate Docker container.

Installation

Project Components Setup

  1. ChromaDB, reranker service, embedding service:

    1. Clone/update the repository (use /home/chem-paper-assistant/ location on the server)
    2. Run cd infrastructure/chroma
    3. Run docker compose up

  2. AutoML

    1. cd infrastructure/automl

    2. path/to/python3.10.exe -m venv env

    3. pip install -r requirements.txt

    4. source env/Scripts/activate

    5. python automl_api.py

    6. In automl_api.py script you should set port where you want to run server.

  3. Generative models

    1. Instructions for build and run container with generative models

      The easiest way to work with this part of the project is to build a container on a server with an available video card.

      git clone https://github.com/ITMO-NSS-team/MADD.git

      You need to specify the required parameters in the DockerFile, such as:

      GEN_APP_PORT (the port on which you plan to deploy the container with generative models),
ML_MODEL_URL (The address (IP and port) where you plan to host the server with predictive models), 
HF_TOK (for downloading trained models), 
GITHUB_TOKEN (for the ability to make commits to the code).

      cd infrastructure/generative_models

docker build -t generative_model_backend .

    2. Running a container

      The container may take quite a long time to build, since the environment for its operation requires a long installation and time. However, this is done quite simply.

      Next, after you have created an image on your server (or locally), you need to run the container with the command:

      docker run --name molecule_generator --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=<your device ID> -it --init generative_model_backend:latest bash

OR 

docker run --name molecule_generator --runtime=nvidia -e --gpus all -it --init generative_model_backend:latest bash

      The container should automatically launch a server with the FastAPI and generative models. However, if this doesn't happen, you should manually run the code

      bash /projects/MADD/infrastructure/generative_models/api.sh

  4. ChemCoScientist app:

    1. Clone/update the repository (use /home/chem-paper-assistant/ location on the server)
    2. Create a config.env file in the root of the project based on example_config.env
    3. Adjust the path to the volume if necessary in docker-compose.yml
    4. Run cd docker
    5. Run docker compose up