Devops attempt 3

Author: Ghost---Shadow

.github/workflows/python_ci.yml

@@ -31,7 +31,8 @@ jobs:
 
     - name: Install dependencies
       run: |
-        source devops/install.sh
+        chmod +x devops/install.sh
+        ./devops/install.sh
 
     - name: Check code formatting with black
       run: |

README.md

@@ -2,7 +2,7 @@
 
 [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
 [![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/release/python-390/)
-[![CI](https://github.com/Ghost---Shadow/quaild/actions/workflows/python_ci.yml/badge.svg)](https://github.com/Ghost---Shadow/quaild/actions/workflows/python_ci.yml)
+[![CI](https://github.com/Ghost---Shadow/InSQuaD/actions/workflows/python_ci.yml/badge.svg)](https://github.com/Ghost---Shadow/InSQuaD/actions/workflows/python_ci.yml)
 
 InSQuaD is a research framework for efficient in-context learning that leverages submodular mutual information to optimize the quality-diversity tradeoff in example selection for large language models. This implementation supports various retrieval methods, subset selection strategies, and generative models for comprehensive evaluation across multiple datasets.
 
@@ -25,16 +25,22 @@ InSQuaD is a research framework for efficient in-context learning that leverages
 
 1. **Clone the repository**:
    ```bash
-   git clone https://github.com/Ghost---Shadow/quaild.git
-   cd quaild
+   git clone https://github.com/Ghost---Shadow/InSQuaD.git
+   cd InSQuaD
    ```
 
-2. **Install dependencies**:
+2. **Create conda environment** (recommended):
    ```bash
-   source ./devops/install.sh
+   conda create -n InSQuaD python=3.9 -y
+   conda activate InSQuaD
    ```
 
-3. **Set up environment variables**:
+3. **Install dependencies**:
+   ```bash
+   ./devops/install.sh
+   ```
+
+4. **Set up environment variables**:
    Create a `.env` file in the root directory with your API keys:
    ```bash
    OPENAI_API_KEY=your_openai_key_here
@@ -47,7 +53,7 @@ InSQuaD is a research framework for efficient in-context learning that leverages
 
 1. **Single experiment**:
    ```bash
-   python src/train.py experiments/tests/quaild_test_experiment.yaml
+   python src/train.py experiments/tests/InSQuaD_test_experiment.yaml
    ```
 
 2. **Full experiment suite**:
@@ -162,7 +168,7 @@ If you use this code in your research, please cite:
   booktitle={Proceedings of the 2025 IEEE International Conference on Data Mining (ICDM)},
   year={2025},
   organization={IEEE},
-  url={https://github.com/Ghost---Shadow/quaild}
+  url={https://github.com/Ghost---Shadow/InSQuaD}
 }
 ```
 

devops/install.sh

@@ -1,5 +1,17 @@
-conda create -n quaild python=3.9 -y
-conda activate quaild
+#!/bin/bash
+set -e
+
+echo "Installing dependencies..."
 pip install -r requirements-torch.txt --index-url https://download.pytorch.org/whl/cu121
-conda install -c pytorch faiss-cpu=1.7.4 mkl=2021 blas=1.0=mkl -y
-pip install -e . --user
+
+echo "Installing FAISS..."
+# Try system package first, fallback to pip
+if command -v apt-get &> /dev/null; then
+    sudo apt-get update && sudo apt-get install -y libfaiss-dev
+fi
+pip install faiss-cpu==1.7.4
+
+echo "Installing project..."
+pip install -e .
+
+echo "Installation complete!"