diff --git a/data/contoso_rules.csv b/data/contoso_rules.csv
new file mode 100644
index 0000000..18c9c8d
--- /dev/null
+++ b/data/contoso_rules.csv
@@ -0,0 +1,21 @@
+rule
+社内会議は必ず出席してください
+遅刻は月に2回まで許されます
+社内の機密情報は外部に漏らさないでください
+社員同士のトラブルは人事部に相談してください
+病気で休む場合は、必ず診断書を提出してください
+社内のイベントには積極的に参加してください
+社外の人との会食は、事前に上司の承認を得てください
+社内のドレスコードはビジネスカジュアルです
+社内の清掃は各自で行ってください
+全社員は健康診断を年1回受ける必要があります
+プロジェクトの締め切りは厳守してください
+社内のセキュリティポリシーを遵守してください
+社内の設備故障は速やかに報告してください
+有給休暇は最大20日です
+毎週金曜日はノー残業デーです
+社内の図書は貸出期間を守って返却してください
+社内のインターネット利用は業務に関連するものに限ります
+有給休暇の申請は1ヶ月前までに行ってください
+一日8時間勤労してください
+社内の飲食スペース以外での飲食は禁止です
diff --git a/poetry.lock b/poetry.lock
index 7bd6c64..26b5029 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1036,6 +1036,45 @@ files = [
 [package.extras]
 test = ["pytest (>=6)"]
 
+[[package]]
+name = "faiss-cpu"
+version = "1.8.0.post1"
+description = "A library for efficient similarity search and clustering of dense vectors."
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "faiss_cpu-1.8.0.post1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b78ff9079d15fd0f156bf5dd8a2975a8abffac1854a86ece263eec1500a2e836"},
+    {file = "faiss_cpu-1.8.0.post1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9de25c943d1789e35fe06a20884c88cd32aedbb1a33bb8da2238cdea7bd9633f"},
+    {file = "faiss_cpu-1.8.0.post1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:adae0f1b144e7216da696f14bc4991ca4300c94baaa59247c3d322588e661c95"},
+    {file = "faiss_cpu-1.8.0.post1-cp310-cp310-win_amd64.whl", hash = "sha256:00345290680a444a4b4cb2d98a3844bb5c401a2160fee547c7631d759fd2ec3e"},
+    {file = "faiss_cpu-1.8.0.post1-cp311-cp311-macosx_10_14_x86_64.whl", hash = "sha256:8d4bade10cb63e9f9ff261751edd7eb097b1f4bf30be4d0d25d6f688559d795e"},
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+    {file = "faiss_cpu-1.8.0.post1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8542a87743a7f94ac656fd3e9592ad57e58b04d961ad2fe654a22a8ca59defdb"},
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+    {file = "faiss_cpu-1.8.0.post1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2a70923b0fbbb40f647e20bcbcbfd472277e6d84bb23ff12d2a94b6841806b55"},
+    {file = "faiss_cpu-1.8.0.post1-cp38-cp38-win_amd64.whl", hash = "sha256:ce652df3c4dd50c88ac9235d072f30ce60694dc422c5f523bbbcab320e8f3097"},
+    {file = "faiss_cpu-1.8.0.post1-cp39-cp39-macosx_10_14_x86_64.whl", hash = "sha256:83ef04b17b19189dd6601a941bdf4bfa9de0740dbcd80305aeba51a1b1955f80"},
+    {file = "faiss_cpu-1.8.0.post1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c50c8697077470ede7f1939ef8dc8a846ec19cf1893b543f6b67f9af03b0a122"},
+    {file = "faiss_cpu-1.8.0.post1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:98ce428a7a67fe5c64047280e5e12a8dbdecf7002f9d127b26cf1db354e9fe76"},
+    {file = "faiss_cpu-1.8.0.post1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5f3b36b80380bae523e3198cfb4a137867055945ce7bf10d18fe9f0284f2fb47"},
+    {file = "faiss_cpu-1.8.0.post1-cp39-cp39-win_amd64.whl", hash = "sha256:4fcc67a2353f08a20c1ab955de3cde14ef3b447761b26244a5aa849c15cbc9b3"},
+    {file = "faiss_cpu-1.8.0.post1.tar.gz", hash = "sha256:5686af34414678c3d49c4fa8d774df7156e9cb48d7029071e56230e74b01cc13"},
+]
+
+[package.dependencies]
+numpy = ">=1.0,<2.0"
+packaging = "*"
+
 [[package]]
 name = "fastapi"
 version = "0.110.3"
@@ -1627,19 +1666,19 @@ referencing = ">=0.31.0"
 
 [[package]]
 name = "langchain"
-version = "0.2.5"
+version = "0.2.10"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain-0.2.5-py3-none-any.whl", hash = "sha256:9aded9a65348254e1c93dcdaacffe4d1b6a5e7f74ef80c160c88ff78ad299228"},
-    {file = "langchain-0.2.5.tar.gz", hash = "sha256:ffdbf4fcea46a10d461bcbda2402220fcfd72a0c70e9f4161ae0510067b9b3bd"},
+    {file = "langchain-0.2.10-py3-none-any.whl", hash = "sha256:b4fb58c7faf4f4999cfe3325474979a7121a1737dd101655a723a1d957ef0617"},
+    {file = "langchain-0.2.10.tar.gz", hash = "sha256:1f861c1b59ac9c91b02bb0fa58d3adad1c1d0686636872b5b357bbce3ce41d06"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
 async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
-langchain-core = ">=0.2.7,<0.3.0"
+langchain-core = ">=0.2.22,<0.3.0"
 langchain-text-splitters = ">=0.2.0,<0.3.0"
 langsmith = ">=0.1.17,<0.2.0"
 numpy = [
@@ -1650,7 +1689,7 @@ pydantic = ">=1,<3"
 PyYAML = ">=5.3"
 requests = ">=2,<3"
 SQLAlchemy = ">=1.4,<3"
-tenacity = ">=8.1.0,<9.0.0"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
 [[package]]
 name = "langchain-community"
@@ -1680,37 +1719,40 @@ tenacity = ">=8.1.0,<9.0.0"
 
 [[package]]
 name = "langchain-core"
-version = "0.2.8"
+version = "0.2.22"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_core-0.2.8-py3-none-any.whl", hash = "sha256:172c81c858dc1f3123cc72b7e44e10f44c92f8a761cae18c364081f6c208e9f6"},
-    {file = "langchain_core-0.2.8.tar.gz", hash = "sha256:2db866a4514672c4875b69d5590aa2ed50aa0d144874268bef68d74b5e7f33f9"},
+    {file = "langchain_core-0.2.22-py3-none-any.whl", hash = "sha256:7731a86440c0958b3186c003fb9b26b2d5a682a6344bda7bfb9174e2898f8b43"},
+    {file = "langchain_core-0.2.22.tar.gz", hash = "sha256:582d6f929a43b830139444e4124123cd415331ad62f25757b1406252958cdcac"},
 ]
 
 [package.dependencies]
 jsonpatch = ">=1.33,<2.0"
 langsmith = ">=0.1.75,<0.2.0"
 packaging = ">=23.2,<25"
-pydantic = ">=1,<3"
+pydantic = [
+    {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
+]
 PyYAML = ">=5.3"
-tenacity = ">=8.1.0,<9.0.0"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
 [[package]]
 name = "langchain-openai"
-version = "0.1.8"
+version = "0.1.17"
 description = "An integration package connecting OpenAI and LangChain"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_openai-0.1.8-py3-none-any.whl", hash = "sha256:8125c84223e9f43b05defbca64eedbcf362fd78a680de6c25e64f973b34a8063"},
-    {file = "langchain_openai-0.1.8.tar.gz", hash = "sha256:a11fcce15def7917c44232abda6baaa63dfc79fe44be1531eea650d39a44cd95"},
+    {file = "langchain_openai-0.1.17-py3-none-any.whl", hash = "sha256:30bef5574ecbbbb91b8025b2dc5a1bd81fd62157d3ad1a35d820141f31c5b443"},
+    {file = "langchain_openai-0.1.17.tar.gz", hash = "sha256:c5d70ddecdcb93e146f376bdbadbb6ec69de9ac0f402cd5b83de50b655ba85ee"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.2.2,<0.3"
-openai = ">=1.26.0,<2.0.0"
+langchain-core = ">=0.2.20,<0.3.0"
+openai = ">=1.32.0,<2.0.0"
 tiktoken = ">=0.7,<1"
 
 [[package]]
@@ -2408,13 +2450,13 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 
 [[package]]
 name = "openai"
-version = "1.30.5"
+version = "1.36.1"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
 files = [
-    {file = "openai-1.30.5-py3-none-any.whl", hash = "sha256:2ad95e926de0d2e09cde632a9204b0a6dca4a03c2cdcc84329b01f355784355a"},
-    {file = "openai-1.30.5.tar.gz", hash = "sha256:5366562eb2c5917e6116ae0391b7ae6e3acd62b0ae3f565ada32b35d8fcfa106"},
+    {file = "openai-1.36.1-py3-none-any.whl", hash = "sha256:d399b9d476dbbc167aceaac6bc6ed0b2e2bb6c9e189c7f7047f822743ae62e64"},
+    {file = "openai-1.36.1.tar.gz", hash = "sha256:41be9e0302e95dba8a9374b885c5cb1cec2202816a70b98736fee25a2cadd1f2"},
 ]
 
 [package.dependencies]
@@ -3043,109 +3085,229 @@ files = [
 
 [[package]]
 name = "pydantic"
-version = "2.7.1"
+version = "2.7.4"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pydantic-2.7.1-py3-none-any.whl", hash = "sha256:e029badca45266732a9a79898a15ae2e8b14840b1eabbb25844be28f0b33f3d5"},
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+    {file = "pydantic-2.7.4-py3-none-any.whl", hash = "sha256:ee8538d41ccb9c0a9ad3e0e5f07bf15ed8015b481ced539a1759d8cc89ae90d0"},
+    {file = "pydantic-2.7.4.tar.gz", hash = "sha256:0c84efd9548d545f63ac0060c1e4d39bb9b14db8b3c0652338aecc07b5adec52"},
 ]
 
 [package.dependencies]
 annotated-types = ">=0.4.0"
-pydantic-core = "2.18.2"
+pydantic-core = "2.18.4"
 typing-extensions = ">=4.6.1"
 
 [package.extras]
 email = ["email-validator (>=2.0.0)"]
 
+[[package]]
+name = "pydantic"
+version = "2.8.2"
+description = "Data validation using Python type hints"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+annotated-types = ">=0.4.0"
+pydantic-core = "2.20.1"
+typing-extensions = {version = ">=4.6.1", markers = "python_version < \"3.13\""}
+
+[package.extras]
+email = ["email-validator (>=2.0.0)"]
+
+[[package]]
+name = "pydantic-core"
+version = "2.18.4"
+description = "Core functionality for Pydantic validation and serialization"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "PyMuPDFb-1.24.6-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e1f7657353529ae3f88575c83ee49eac9adea311a034b9c97248a65cee7df0e5"},
+    {file = "PyMuPDFb-1.24.6-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:cebc2cedb870d1e1168e2f502eb06f05938f6df69103b0853a2b329611ec19a7"},
+    {file = "PyMuPDFb-1.24.6-py3-none-win32.whl", hash = "sha256:ac4b865cd1e239db04674f85e02844a0e405f8255ee7a74dfee0d86aad0d3576"},
+    {file = "PyMuPDFb-1.24.6-py3-none-win_amd64.whl", hash = "sha256:9224e088a0d3c188dea03831807789e245b812fbd071c8d498da8f7cc33142b2"},
+    {file = "PyMuPDFb-1.24.6.tar.gz", hash = "sha256:f5a40b1732d65a1e519916d698858b9ce7473e23edf9001ddd085c5293d59d30"},
+]
+
 [[package]]
 name = "pysocks"
 version = "1.7.1"
@@ -4747,4 +4974,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "3e929d6d0801aed3d58e5adc1c521b8e20aee6e8b886afc4362537ed1f99f6dd"
+content-hash = "31557844a2a2f6b36d6a98e504a877d97611a82face9c60f4dd509817f36a413"
diff --git a/pyproject.toml b/pyproject.toml
index 827ccb5..f00067d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -61,6 +61,14 @@ openai = "^1.30.5"
 [tool.poetry.group.azure-functions.dependencies]
 azure-functions = "^1.19.0"
 
+
+[tool.poetry.group.scripts.dependencies]
+pymupdf = "^1.24.7"
+faiss-cpu = "^1.8.0.post1"
+langchain = "^0.2.10"
+langchain-openai = "^0.1.17"
+pandas = "^2.2.2"
+
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"
diff --git a/scripts/build_vector_store.env.sample b/scripts/build_vector_store.env.sample
new file mode 100644
index 0000000..9c65659
--- /dev/null
+++ b/scripts/build_vector_store.env.sample
@@ -0,0 +1,5 @@
+AZURE_OPENAI_ENDPOINT = "https://<your-aoai-name>.openai.azure.com/"
+AZURE_OPENAI_API_KEY = "<api-key>"
+AZURE_OPENAI_API_VERSION = "2024-05-01-preview"
+AZURE_OPENAI_MODEL_EMBEDDING = "text-embedding-3-large"
+AZURE_OPENAI_MODEL_CHAT = "gpt-4o"
diff --git a/scripts/build_vector_store.py b/scripts/build_vector_store.py
new file mode 100644
index 0000000..4cbb4cf
--- /dev/null
+++ b/scripts/build_vector_store.py
@@ -0,0 +1,99 @@
+import logging
+from os import getenv
+from typing import Annotated
+
+import pandas as pd
+import typer
+from dotenv import load_dotenv
+from langchain_community.vectorstores import FAISS
+from langchain_openai import AzureOpenAIEmbeddings
+
+
+def get_log_level(debug: bool) -> int:
+    return logging.DEBUG if debug else logging.INFO
+
+
+def setup_logging(debug: bool = False):
+    logging.basicConfig(
+        format="[%(asctime)s] %(levelname)7s from %(name)s in %(pathname)s:%(lineno)d: " "%(message)s",
+        level=get_log_level(debug),
+        force=True,
+    )
+
+
+app = typer.Typer()
+
+
+def get_embeddings():
+    return AzureOpenAIEmbeddings(
+        api_key=getenv("AZURE_OPENAI_API_KEY"),
+        api_version=getenv("AZURE_OPENAI_API_VERSION"),
+        azure_endpoint=getenv("AZURE_OPENAI_ENDPOINT"),
+        model=getenv("AZURE_OPENAI_MODEL_EMBEDDING"),
+    )
+
+
+def load_qa_vectorstore(vectorstore_path: str):
+    return FAISS.load_local(
+        folder_path=vectorstore_path,
+        embeddings=get_embeddings(),
+        allow_dangerous_deserialization=True,
+    )
+
+
+@app.command()
+def build(
+    file_path: Annotated[
+        str, typer.Option(help="Path to the CSV file with questions and answers")
+    ] = "./data/contoso_rules.csv",
+    output_path: Annotated[
+        str, typer.Option(help="Path to save the vector store")
+    ] = "./artifacts/vectorstore/contoso_rules",
+    debug: Annotated[bool, typer.Option(help="Enable debug mode")] = False,
+):
+    setup_logging(debug)
+
+    df = pd.read_csv(file_path)
+
+    if "rule" not in df.columns:
+        raise ValueError("The CSV file must have 'rule' column")
+
+    texts = []
+    for _, row in df.iterrows():
+        texts.append(f"{row['rule']}")
+
+    embeddings = get_embeddings()
+    db = FAISS.from_texts(texts, embeddings)
+    db.save_local(output_path)
+
+
+@app.command()
+def search(
+    vectorstore_path: Annotated[
+        str, typer.Option(help="Path to the vector store")
+    ] = "./artifacts/vectorstore/contoso_rules",
+    query: Annotated[str, typer.Option(help="Query to search")] = "社内の機密情報は外部に漏らさないでください",
+    debug: Annotated[bool, typer.Option(help="Enable debug mode")] = False,
+):
+    setup_logging(debug)
+    docs = load_qa_vectorstore(
+        vectorstore_path=vectorstore_path,
+    ).similarity_search_with_score(
+        query=query,
+        k=5,
+        score_threshold=0.5,
+    )
+    result = [
+        {
+            "similarity": 1 - similarity,
+            "content": i.page_content,
+        }
+        for i, similarity in docs
+    ]
+    for r in result:
+        print(r)
+
+
+if __name__ == "__main__":
+    load_dotenv()
+    app()