Add build script for OpenRAG 0.5.1 on UBI 10

f/faiss-wheel/LICENSE

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f/faiss-wheel/app.py

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+import faiss
+import numpy as np
+from sentence_transformers import SentenceTransformer
+
+# 1. Initialize the embedding model (converts text to 384-dimensional vectors)
+print("Loading text embedding model...")
+model = SentenceTransformer("all-MiniLM-L6-v2")
+
+# 2. Define your knowledge base / document inventory
+documents = [
+    "Python is a versatile programming language used for AI and web development.",
+    "The golden retriever puppy barked excitedly at the red ball.",
+    "Global stock markets experienced a minor downturn early this morning.",
+    "To bake a perfect chocolate cake, ensure your eggs are room temperature.",
+    "Machine learning models rely heavily on high-quality training datasets.",
+    "The local cafe serves incredible espresso and fresh croissants every day.",
+]
+
+# 3. Generate embeddings and convert them to float32 NumPy arrays (required by FAISS)
+print("Generating document embeddings...")
+doc_embeddings = model.encode(documents)
+doc_embeddings = np.array(doc_embeddings).astype("float32")
+
+# 4. Initialize the FAISS index using basic L2 (Euclidean) distance
+# The 'dimension' parameter must match the output size of the embedding model (384)
+dimension = doc_embeddings.shape[1]
+index = faiss.IndexFlatL2(dimension)
+
+# 5. Populate the index with the document vectors
+index.add(doc_embeddings)
+print(f"Successfully indexed {index.ntotal} documents.\n")
+
+
+# 6. Define a reusable function to search the index
+def search_knowledge_base(query_text: str, top_k: int = 2):
+    # Encode the user's query into the exact same vector space
+    query_embedding = model.encode([query_text])
+    query_embedding = np.array(query_embedding).astype("float32")
+
+    # Perform the vector search
+    # distances: L2 distance scores (lower scores = closer match)
+    # indices: The corresponding numerical position of the matched item
+    distances, indices = index.search(query_embedding, top_k)
+
+    print(f'🔍 Query: "{query_text}"')
+    print("-" * 50)
+    for i in range(top_k):
+        match_idx = indices[0][i]
+        distance_score = distances[0][i]
+        # Ignore fallback indices (-1) if top_k exceeds dataset size
+        if match_idx != -1:
+            print(f"Match #{i+1} (Distance: {distance_score:.4f}):")
+            print(f"  -> {documents[match_idx]}")
+    print("\n")
+
+
+# 7. Run real test cases showing semantic understanding (not just keyword matching)
+search_knowledge_base("Tell me about software engineering or artificial intelligence", top_k=2)
+search_knowledge_base("I want some delicious morning breakfast and coffee", top_k=1)
+search_knowledge_base("Is the economy doing well today?", top_k=1)
+

f/faiss-wheel/build_info.json

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+{
+    "maintainer": "Amir Sanjar",
+    "package_name": "faiss-wheel",
+    "github_url": "https://github.com/faiss-wheels/faiss-wheels.git",
+    "version": "1.9.0.post1",
+    "default_branch": "main",
+    "build_script": "faiss_cpu_1.9.0.post1_ubi_9.6.sh",
+    "package_dir": "f/faiss-wheel",
+    "docker_build": true,
+    "validate_build_script": true,
+    "use_non_root_user": false,
+    "wheel_build": true,
+
+    "*": {
+        "build_script": "faiss_cpu_1.9.0.post1_ubi_9.6.sh"
+    }
+}

f/faiss-wheel/faiss_cpu_1.9.0.post1_ubi_9.6.sh

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+#!/bin/bash
+# -----------------------------------------------------------------------------
+#
+# Package           : faiss
+# Version           : 1.9.0-post1
+# Source repo       : https://github.com/faiss-wheels/faiss-wheels
+# Tested on         : UBI 9.6
+# Language          : C++, Python
+# Ci-Check      : True
+# Script License    : Apache License Version 2.0
+# Maintainer        : Amir Sanjar <amir.sanjar@ibm.com>
+#
+# Disclaimer: This script has been tested in root mode on the given
+# ==========  platform using the mentioned version of the package.
+#             It may not work as expected with newer versions of the
+#             package and/or distribution. In such cases, please
+#             contact the "Maintainer" of this script.
+#
+
+# set -e
+
+PACKAGE_NAME=faiss-cpu
+PACKAGE_DIR=faiss-wheels
+PACKAGE_VERSION=${1:-1.9.0.post1}
+PACKAGE_URL=https://github.com/faiss-wheels/faiss-wheels.git
+SOURCE_ROOT="$(pwd)"
+
+
+
+echo "Installing dependencies..."
+curl -O https://dl.fedoraproject.org/pub/epel/epel-release-latest-9.noarch.rpm
+dnf install -y epel-release-latest-9.noarch.rpm
+dnf update -y 
+dnf install -y  \
+     python3.13 python3.13-devel python3.13-pip \
+     openblas-devel make gcc g++ cmake git automake autoconf
+
+echo "Upgrading Python tools..."
+python3.13 -m pip install --upgrade setuptools wheel build  uv
+
+git clone --recursive ${PACKAGE_URL}
+cd ${PACKAGE_DIR}
+echo -e "\n[tool.uv]\nenvironments = [\"python_version == '3.13'\"]" >> pyproject.toml
+uv python pin 3.13
+sed -i "s/.version=.*/version='"$PACKAGE_VERSION"',/" third-party/faiss/faiss/python/setup.py
+export INDEX_URL_DEVPY="https://wheels.developerfirst.ibm.com/ppc64le/linux/+simple"
+sed -i '/^\[project\]/,/^$/ {s/version = "[^"]*"/version = "'"$PACKAGE_VERSION"'"/}' pyproject.toml
+CP=$(python3.13 -c "import sysconfig; print(sysconfig.get_config_var('py_version_nodot'))")
+uv build --wheel --config-setting wheel.py-api=cp$CP --extra-index-url $INDEX_URL_DEVPY
+
+if ! (python3.13 -m pip install dist/faiss_cpu-$PACKAGE_VERSION-cp$CP-abi3-linux_ppc64le.whl ); then 
+   echo "------------------$PACKAGE_NAME:Failed to build wheel-------------------------------------"
+   echo "$PACKAGE_URL $PACKAGE_NAME"
+   echo "$PACKAGE_NAME  |  $PACKAGE_URL | $PACKAGE_VERSION | GitHub | Fail |  Install_Fails"
+fi
+# Run tests
+python3.13 -m pip install  scipy==1.17.0 sentence-transformers  --extra-index-url $INDEX_URL_DEVPY 
+#find test case called app.py
+TEST_PATH=$(find "${SOURCE_ROOT}" -name app.py | head -1)
+if [ -z "${TEST_PATH}" ]; then
+    echo "ERROR: test case not found"
+    exit 1
+fi
+if ! (python3.13 $TEST_PATH); then
+     echo "--------------------$PACKAGE_NAME:Install_success_but_test_fails--------------------"
+     echo "$PACKAGE_URL $PACKAGE_NAME"
+     echo "$PACKAGE_NAME  |  $PACKAGE_URL | $PACKAGE_VERSION | GitHub | Fail |  Install_success_but_test_Fails"
+     exit 2
+else
+     echo "------------------$PACKAGE_NAME:Install_&_test_both_success-------------------------"
+     echo "$PACKAGE_URL $PACKAGE_NAME"
+     echo "$PACKAGE_NAME  |  $PACKAGE_URL | $PACKAGE_VERSION | GitHub  | Pass |  Both_Install_and_Import_Success"
+     exit 0
+fi