Summary
Contributors are encountering dependency resolution errors (e.g., TensorFlow pip errors) because the repository does not declare a supported Python runtime. This causes installations to fail on modern Python versions (>=3.11). We should declare a supported Python version, provide an .env.example, and add a minimal CI check to prevent environment friction for contributors.
Problem / Reproduction
- On a machine running Python 3.11+:
python --version
pip install -r backend/requirements.txt
- pip fails with messages such as:
Could not find a version that satisfies the requirement tensorflow==2.17.0
Ignored the following versions that require a different python version:
- This blocks new contributors from running the project locally and submitting PRs.
Proposal (minimal, high-impact)
- Add a runtime declaration file:
.python-version (content: 3.9.19) OR runtime.txt to explicitly declare the supported Python runtime (like: 3.9 or 3.10).
- Add
.env.example at repo root listing required environment variables (no secrets).
- Update
CONTRIBUTING.md or SETUP.md with one-line setup steps for conda/pyenv/venv so contributors can reproduce a working environment.
Summary
Contributors are encountering dependency resolution errors (e.g., TensorFlow pip errors) because the repository does not declare a supported Python runtime. This causes installations to fail on modern Python versions (>=3.11). We should declare a supported Python version, provide an
.env.example, and add a minimal CI check to prevent environment friction for contributors.Problem / Reproduction
Proposal (minimal, high-impact)
.python-version(content:3.9.19) ORruntime.txtto explicitly declare the supported Python runtime (like: 3.9 or 3.10)..env.exampleat repo root listing required environment variables (no secrets).CONTRIBUTING.mdorSETUP.mdwith one-line setup steps forconda/pyenv/venvso contributors can reproduce a working environment.