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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) + diff --git a/f/faiss-wheel/build_info.json b/f/faiss-wheel/build_info.json new file mode 100644 index 0000000000..fde2abba92 --- /dev/null +++ b/f/faiss-wheel/build_info.json @@ -0,0 +1,17 @@ +{ + "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" + } +} diff --git a/f/faiss-wheel/faiss_cpu_1.9.0.post1_ubi_9.6.sh b/f/faiss-wheel/faiss_cpu_1.9.0.post1_ubi_9.6.sh new file mode 100755 index 0000000000..12f705c22f --- /dev/null +++ b/f/faiss-wheel/faiss_cpu_1.9.0.post1_ubi_9.6.sh @@ -0,0 +1,74 @@ +#!/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 +# +# 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