Speed up github workflows by not installing cuda server dependencies

- CI runners don't have GPUs
- Pytorch related Nvidia cuda packages are not required for testing,
  evals or pre-commit checks.
- Avoiding these massive downloads should speed up workflow run.

.github/workflows/pre-commit.yml

@@ -48,6 +48,10 @@ jobs:
           sudo apt update && sudo apt install -y libegl1
 
       - name: ⬇️ Install Application
+        env:
+          UV_INDEX: "https://download.pytorch.org/whl/cpu"
+          UV_INDEX_STRATEGY: "unsafe-best-match"
+          CUDA_VISIBLE_DEVICES: ""
         run: uv sync --all-extras
 
       - name: 🌡️ Validate Application

.github/workflows/run_evals.yml

@@ -135,6 +135,10 @@ jobs:
           git clone https://github.com/khoj-ai/terrarium.git && cd terrarium && npm install --legacy-peer-deps && mkdir pyodide_cache
 
       - name: ⬇️ Install Application
+        env:
+          UV_INDEX: "https://download.pytorch.org/whl/cpu"
+          UV_INDEX_STRATEGY: "unsafe-best-match"
+          CUDA_VISIBLE_DEVICES: ""
         run: |
           sed -i 's/dynamic = \["version"\]/version = "${{ steps.hatch.outputs.version }}"/' pyproject.toml
           uv sync --all-extras

.github/workflows/test.yml

@@ -76,7 +76,8 @@ jobs:
 
       - name: ⬇️ Install Application
         env:
-          PIP_EXTRA_INDEX_URL: "https://download.pytorch.org/whl/cpu https://abetlen.github.io/llama-cpp-python/whl/cpu"
+          UV_INDEX: "https://download.pytorch.org/whl/cpu"
+          UV_INDEX_STRATEGY: "unsafe-best-match"
           CUDA_VISIBLE_DEVICES: ""
         run: sed -i 's/dynamic = \["version"\]/version = "0.0.0"/' pyproject.toml && uv sync --all-extras