# Hugging Face Space requirements (Streamlit SDK).
#
# Shape: Streamlit UI + in-process agent loop, where the agent talks to Qwen
# via HF Inference Providers. GPU-touching tools (profile_run, benchmark)
# fall back to FakeRunner — no GPU on the Space, no torch needed.
#
# Notably ABSENT:
#   * `sentence-transformers` / `torch` / `transformers`
#     We ship a pre-built embeddings cache at `kb/.embeddings_cache_<sha>.npy`
#     keyed on the YAML's sha256, so query_rocm_kb hits the cache instead of
#     loading the embedding model. If you edit `kb/rocm_rules.yaml` and push
#     without rebuilding the cache locally, query_rocm_kb returns ok=False
#     with a clear message and the rest of the agent loop keeps working.
#   * `fastapi` / `uvicorn` / `sse-starlette`
#     The Space embeds the agent loop in-process; no HTTP backend needed.
#   * `anthropic`
#     Qwen-only since Phase 3.
#
# For the full developer install (FastAPI backend, KB rebuild, ROCm runner)
# use `pip install -e ".[dev]"` against `pyproject.toml`.
streamlit>=1.32
altair>=5.2
pandas>=2.2
pydantic>=2.6
requests>=2.31
huggingface_hub>=0.28
openai>=1.30
numpy>=1.26
PyYAML>=6.0