In root directory, run docker compose --profile backend-dev up --build --attach-dependencies to start a database. The default settings are already configured to connect to the database at localhost:5432. (See FAQ if you face any docker problems).

Note: when running on MacOS with an M1 chip you have to use: DB_PLATFORM=linux/x86_64 docker compose ...

Python 3.10 is required. It is recommended to use pyenv which will recognise the .python-version in the project root directory.

Next, to install all requirements, You can run

1. pip install -r backend/requirements.txt
2. pip install -e ./oasst-shared/.
3. pip install -e ./oasst-data/.
4. ./scripts/backend-development/run-local.sh to run the backend. This will start the backend server at http://localhost:8080.

• Generate a new environment variable file .env by coping the content of the .env.example file.

• Update the values of the environment variables in the .env file by setting the DATABASE_URI to you local database URI.

• Update the rest of the environment variables according to your needs.

Have a look into the main README.md file for more information on how to set up the backend for development. Use the scripts within the scripts/backend-development folder to run the BE API locally.

To create an Alembic database migration script after sql-models were modified run alembic revision --autogenerate -m "..." ("..." is what you did) in the /backend directory. Then edit the newly created file. See here for more information.

Once you have successfully started the backend server, you can access the default api docs at localhost:8080/docs. If you need to update the exported openapi.json in the docs/ folder you can run below command to wget them from the relevant local fastapi endpoint. This will enable anyone to just see API docs via something like Swagger.io without having to actually set up and run a development backend.

# save openapi.json to docs/docs/api/
wget localhost:8080/api/v1/openapi.json -O docs/docs/api/backend-openapi.json

Note: The api docs should be automatically updated by the test-api-contract.yaml workflow. (TODO)

Celery workers are used for Huggingface API calls like toxicity and feature extraction. Celery Beat along with worker is used for periodic tasks like user streak update

To run APIs locally

• update HUGGING_FACE_API_KEY in backend/oasst_backend/config.py with the correct API_KEY
• export DEBUG_SKIP_TOXICITY_CALCULATION=False and export DEBUG_SKIP_EMBEDDING_COMPUTATION=Falsein scripts/backend-development/run-local.sh
• run start_worker.sh in backend dir
• to see logs , use tail -f celery.log and tail -f celery.beat.log

In CI

• set DEBUG_SKIP_TOXICITY_CALCULATION=False and DEBUG_SKIP_EMBEDDING_COMPUTATION=False in docker-compose.yaml
• Two Docker instances are created. One for Beat and other for the worker
• Logs can be viewed like other docker instances

When you have collected some data in the backend database, you can export it using the export.py script provided in this directory. This can be run from the command line using an Python environment with the same requirements as the backend itself. The script connects to the database in the same manner as the backend and therefore uses the same environmental variables.

A simple usage of the script, to export all English trees which successfully passed the review process, may look like:

python export.py --lang en --export-file output.jsonl

There are many options available to filter the data which can be found in the help message of the script: python export.py --help.

Why isn't my export working?

Common issues include (WIP):

• The messages have not passed the review process yet so the trees are not ready for export. This can be solved by including the --include-spam flag.