diff --git a/.gitignore b/.gitignore
index 439455ca..5b6ad15d 100644
--- a/.gitignore
+++ b/.gitignore
@@ -21,6 +21,7 @@ docs/_build
 .coverage*
 coverage.xml
 junit.xml
+htmlcov
 __pycache__
 .*cache
 
diff --git a/gptme/dirs.py b/gptme/dirs.py
index 8af098b9..91ffe550 100644
--- a/gptme/dirs.py
+++ b/gptme/dirs.py
@@ -1,7 +1,7 @@
 import os
 from pathlib import Path
 
-from platformdirs import user_config_dir, user_data_dir
+from platformdirs import user_cache_dir, user_config_dir, user_data_dir
 
 
 def get_config_dir() -> Path:
@@ -39,5 +39,9 @@ def _init_paths():
         path.mkdir(parents=True, exist_ok=True)
 
 
+def get_cache_dir() -> Path:
+    return Path(user_cache_dir("gptme"))
+
+
 # run once on init
 _init_paths()
diff --git a/gptme/tools/__init__.py b/gptme/tools/__init__.py
index c89bd85e..9b8a78f2 100644
--- a/gptme/tools/__init__.py
+++ b/gptme/tools/__init__.py
@@ -16,6 +16,7 @@
 from .subagent import tool as subagent_tool
 from .tmux import tool as tmux_tool
 from .youtube import tool as youtube_tool
+from .rag import tool as rag_tool
 
 logger = logging.getLogger(__name__)
 
@@ -39,6 +40,7 @@
     gh_tool,
     chats_tool,
     youtube_tool,
+    rag_tool,
     # python tool is loaded last to ensure all functions are registered
     get_python_tool,
 ]
diff --git a/gptme/tools/rag/__init__.py b/gptme/tools/rag/__init__.py
new file mode 100644
index 00000000..326d5b9a
--- /dev/null
+++ b/gptme/tools/rag/__init__.py
@@ -0,0 +1,46 @@
+import importlib
+
+import numpy as np
+from gptme.dirs import get_cache_dir
+
+from ..base import ToolSpec
+
+available = importlib.util.find_spec("faiss") is not None
+
+data_dir = get_cache_dir() / "rag"
+
+
+def retrieve(query: str, top_k: int = 5):
+    import faiss  # fmt: skip
+    from sentence_transformers import SentenceTransformer  # fmt: skip
+
+    from .indexer import main as main_indexer  # fmt: skip
+    from .retriever import retrieve_relevant_chunks  # fmt: skip
+
+    # TODO: Add a check if the index exists
+    main_indexer()
+
+    # Load the model, index, and metadata only once
+    model = SentenceTransformer("all-MiniLM-L6-v2")
+    index = faiss.read_index(str(data_dir / "code_index.faiss"))
+    metadata = np.load(str(data_dir / "code_metadata.npy"), allow_pickle=True).tolist()
+
+    # Retrieve relevant chunks
+    relevant_chunks = retrieve_relevant_chunks(query, index, metadata, model, top_k)
+
+    # Format the results
+    formatted_results = []
+    for chunk in relevant_chunks:
+        file_path, code, start_line, end_line, distance = chunk
+        formatted_chunk = f"File: {file_path} (Lines {start_line}-{end_line}, Distance: {distance:.4f})\n{code}\n{'='*80}"
+        formatted_results.append(formatted_chunk)
+
+    return "\n\n".join(formatted_results)
+
+
+tool = ToolSpec(
+    name="rag",
+    desc="A tool for retrieving relevant code snippets from the project.",
+    functions=[retrieve],
+    available=available,
+)
diff --git a/gptme/tools/rag/indexer.py b/gptme/tools/rag/indexer.py
new file mode 100644
index 00000000..16003c1c
--- /dev/null
+++ b/gptme/tools/rag/indexer.py
@@ -0,0 +1,224 @@
+import ast
+import json
+import logging
+import os
+import subprocess
+import textwrap
+
+import numpy as np
+import pathspec
+from gptme.dirs import get_cache_dir
+
+import faiss
+from sentence_transformers import SentenceTransformer
+
+logging.basicConfig(level=logging.INFO)
+
+data_dir = get_cache_dir() / "rag"
+os.makedirs(data_dir, exist_ok=True)
+
+metadata_file = data_dir / "index_metadata.json"
+
+
+def get_git_root(path: str) -> str:
+    result = subprocess.run(
+        ["git", "rev-parse", "--show-toplevel"],
+        cwd=path,
+        capture_output=True,
+        text=True,
+    )
+    if result.returncode != 0:
+        raise RuntimeError(f"Failed to find git root: {result.stderr.strip()}")
+    return result.stdout.strip()
+
+
+def load_gitignore_patterns(repo_root: str) -> pathspec.PathSpec:
+    gitignore_path = os.path.join(repo_root, ".gitignore")
+    if os.path.exists(gitignore_path):
+        with open(gitignore_path, encoding="utf-8") as f:
+            return pathspec.PathSpec.from_lines("gitwildmatch", f)
+    return pathspec.PathSpec([])
+
+
+def load_code_files(
+    directory: str, ignore_patterns: pathspec.PathSpec
+) -> list[tuple[str, str]]:
+    code_files = []
+    ignored_files_count = 0
+    for root, _, files in os.walk(directory):
+        for file in files:
+            file_path = os.path.relpath(os.path.join(root, file), directory)
+            if ignore_patterns.match_file(file_path):
+                ignored_files_count += 1
+                continue
+            if file.endswith(
+                (".py", ".js", ".ts", ".html", ".css")
+            ):  # Add more file types as needed
+                logging.info(f"Processing file: {file_path}")
+                with open(os.path.join(root, file), encoding="utf-8") as f:
+                    code_files.append((file_path, f.read()))
+    logging.info(f"Total files ignored: {ignored_files_count}")
+    return code_files
+
+
+def chunk_code_syntactically(
+    code: str, file_path: str
+) -> list[tuple[str, str, int, int]]:
+    chunks: list[tuple[str, str, int, int]] = []
+    try:
+        tree = ast.parse(code)
+    except SyntaxError:
+        # If parsing fails, fall back to simple line-based chunking
+        lines = code.split("\n")
+        for i in range(0, len(lines), 10):
+            chunk = "\n".join(lines[i : i + 10])
+            chunks.append((file_path, chunk, i + 1, min(i + 10, len(lines))))
+        return chunks
+
+    for node in ast.walk(tree):
+        if isinstance(node, ast.FunctionDef | ast.ClassDef):
+            start_lineno = node.lineno - 1
+            end_lineno = (
+                node.end_lineno
+                if hasattr(node, "end_lineno") and node.end_lineno is not None
+                else len(code.split("\n"))
+            )
+
+            # Include decorators
+            if hasattr(node, "decorator_list") and node.decorator_list:
+                start_lineno = node.decorator_list[0].lineno - 1
+
+            chunk_lines = code.split("\n")[start_lineno:end_lineno]
+            chunk_code = textwrap.dedent("\n".join(chunk_lines))
+
+            chunks.append((file_path, chunk_code, start_lineno + 1, end_lineno))
+
+    # Handle small files or single-line statements
+    if not chunks:
+        lines = code.split("\n")
+        for i in range(0, len(lines), 10):
+            chunk = "\n".join(lines[i : i + 10])
+            chunks.append((file_path, chunk, i + 1, min(i + 10, len(lines))))
+
+    return chunks
+
+
+def chunk_code_line_based(
+    code: str, file_path: str, chunk_size: int = 20, language: str = "generic"
+) -> list[tuple[str, str, int, int]]:
+    chunks = []
+    lines = code.split("\n")
+    for i in range(0, len(lines), chunk_size):
+        chunk = "\n".join(lines[i : i + chunk_size])
+        chunks.append((file_path, chunk, i + 1, min(i + chunk_size, len(lines))))
+    return chunks
+
+
+def should_reindex(
+    current_metadata: dict[str, float], previous_metadata: dict[str, float]
+) -> bool:
+    return any(
+        file_path not in previous_metadata or previous_metadata[file_path] != mtime
+        for file_path, mtime in current_metadata.items()
+    )
+
+
+def create_index(
+    code_files: list[tuple[str, str]], model: SentenceTransformer
+) -> tuple[faiss.Index, list[tuple[str, str, int, int]]]:
+    chunks = []
+    for file_path, code in code_files:
+        logging.info(f"Processing file: {file_path}")
+        if file_path.endswith(".py"):
+            chunks.extend(chunk_code_syntactically(code, file_path))
+        elif file_path.endswith(".ts"):
+            logging.info(f"Processing TypeScript file: {file_path}")
+            chunks.extend(chunk_code_line_based(code, file_path, language="typescript"))
+        else:
+            chunks.extend(chunk_code_line_based(code, file_path))
+    logging.info(f"Total chunks created: {len(chunks)}")
+
+    texts = [chunk[1] for chunk in chunks]
+    batch_size = 64  # Adjust batch size as needed
+    embeddings_list = []
+    total_batches = (len(texts) + batch_size - 1) // batch_size
+    for i in range(total_batches):
+        batch_texts = texts[i * batch_size : (i + 1) * batch_size]
+        if i % 10 == 0 or i == total_batches - 1:
+            logging.info(f"Encoding batch {i + 1}/{total_batches}")
+        batch_embeddings = model.encode(batch_texts, show_progress_bar=False)
+        embeddings_list.append(batch_embeddings)
+    embeddings = np.vstack(embeddings_list)
+
+    dimension = embeddings.shape[1]
+    index = faiss.IndexFlatL2(dimension)
+    index.add(embeddings.astype(np.float32))
+
+    return index, chunks
+
+
+def load_metadata() -> dict[str, float]:
+    if metadata_file.exists():
+        with open(metadata_file, encoding="utf-8") as f:
+            return json.load(f)
+    return {}
+
+
+def save_metadata(metadata: dict[str, float]):
+    with open(metadata_file, "w", encoding="utf-8") as f:
+        json.dump(metadata, f)
+
+
+def main():
+    logging.info("Loading model...")
+    model = SentenceTransformer("all-MiniLM-L6-v2")
+    logging.info("Model loaded.")
+
+    logging.info("Finding Git root...")
+    repo_root = get_git_root(".")
+    logging.info(f"Git root found: {repo_root}")
+
+    logging.info("Loading .gitignore patterns...")
+    ignore_patterns = load_gitignore_patterns(repo_root)
+    logging.info(".gitignore patterns loaded.")
+
+    logging.info("Loading code files...")
+    code_files = load_code_files(repo_root, ignore_patterns)
+    logging.info(f"Total code files loaded: {len(code_files)}")
+
+    logging.info("Loading previous metadata...")
+    previous_metadata = load_metadata()
+
+    logging.info("Checking for changes...")
+    changed_files = []
+    current_metadata = {}
+    for file_path, code in code_files:
+        current_metadata[file_path] = os.path.getmtime(file_path)
+        if (
+            file_path not in previous_metadata
+            or previous_metadata[file_path] != current_metadata[file_path]
+        ):
+            changed_files.append((file_path, code))
+
+    if not changed_files:
+        logging.info("No changes detected. Exiting.")
+        return
+
+    logging.info(f"Files changed: {len(changed_files)}")
+
+    logging.info("Creating index...")
+    index, chunks = create_index(changed_files, model)
+    logging.info("Index created.")
+
+    logging.info("Saving index and metadata...")
+    faiss.write_index(index, str(data_dir / "code_index.faiss"))
+    logging.info("Index saved.")
+
+    logging.info("Saving metadata...")
+    np.save(str(data_dir / "code_metadata.npy"), chunks)
+    save_metadata(current_metadata)
+    logging.info("Metadata saved.")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/gptme/tools/rag/retriever.py b/gptme/tools/rag/retriever.py
new file mode 100644
index 00000000..5acb61a5
--- /dev/null
+++ b/gptme/tools/rag/retriever.py
@@ -0,0 +1,48 @@
+import faiss
+import numpy as np
+import logging
+from sentence_transformers import SentenceTransformer
+from gptme.dirs import get_cache_dir
+
+logging.basicConfig(level=logging.INFO)
+
+data_dir = get_cache_dir() / "rag"
+
+
+def load_index_and_metadata() -> tuple[faiss.Index, list[tuple[str, str, int, int]]]:
+    index = faiss.read_index(str(data_dir / "code_index.faiss"))
+    metadata = np.load(str(data_dir / "code_metadata.npy"), allow_pickle=True)
+    return index, metadata.tolist()
+
+
+def retrieve_relevant_chunks(
+    query: str,
+    index: faiss.Index,
+    metadata: list[tuple[str, str, int, int]],
+    model: SentenceTransformer,
+    top_k: int = 5,
+) -> list[tuple[str, str, int, int, float]]:
+    query_embedding = model.encode([query])
+    distances, indices = index.search(query_embedding.astype("float32"), top_k)
+    return [(*metadata[idx], distances[0][i]) for i, idx in enumerate(indices[0])]
+
+
+def format_chunk(chunk: tuple[str, str, int, int, float]) -> str:
+    file_path, code, start_line, end_line, distance = chunk
+    return f"File: {file_path} (Lines {start_line}-{end_line}, Distance: {distance:.4f})\n{code}\n{'='*80}"
+
+
+def retrieve(query: str, top_k: int = 5) -> str:
+    model = SentenceTransformer("all-MiniLM-L6-v2")
+    index, metadata = load_index_and_metadata()
+    relevant_chunks = retrieve_relevant_chunks(query, index, metadata, model, top_k)
+    return "\n\n".join(format_chunk(chunk) for chunk in relevant_chunks)
+
+
+if __name__ == "__main__":
+    import sys
+
+    if len(sys.argv) < 2:
+        print("Please provide a query as a command-line argument.")
+        sys.exit(1)
+    print(retrieve(sys.argv[1]))
diff --git a/poetry.lock b/poetry.lock
index 6a944e53..5b90dc24 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,5 +1,36 @@
 # This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
 
+[[package]]
+name = "accelerate"
+version = "0.34.2"
+description = "Accelerate"
+optional = true
+python-versions = ">=3.8.0"
+files = [
+    {file = "accelerate-0.34.2-py3-none-any.whl", hash = "sha256:d69159e2c4e4a473d14443b27d2d732929254e826b3ab4813b3785b5ac616c7c"},
+    {file = "accelerate-0.34.2.tar.gz", hash = "sha256:98c1ebe1f5a45c0a3af02dc60b5bb8b7d58d60c3326a326a06ce6d956b18ca5b"},
+]
+
+[package.dependencies]
+huggingface-hub = ">=0.21.0"
+numpy = ">=1.17,<3.0.0"
+packaging = ">=20.0"
+psutil = "*"
+pyyaml = "*"
+safetensors = ">=0.4.3"
+torch = ">=1.10.0"
+
+[package.extras]
+deepspeed = ["deepspeed"]
+dev = ["bitsandbytes", "black (>=23.1,<24.0)", "datasets", "diffusers", "evaluate", "hf-doc-builder (>=0.3.0)", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "rich", "ruff (>=0.2.1,<0.3.0)", "scikit-learn", "scipy", "timm", "torchdata (>=0.8.0)", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
+quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.2.1,<0.3.0)"]
+rich = ["rich"]
+sagemaker = ["sagemaker"]
+test-dev = ["bitsandbytes", "datasets", "diffusers", "evaluate", "scikit-learn", "scipy", "timm", "torchdata (>=0.8.0)", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
+test-prod = ["parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist"]
+test-trackers = ["comet-ml", "dvclive", "tensorboard", "wandb"]
+testing = ["bitsandbytes", "datasets", "diffusers", "evaluate", "parameterized", "pytest (>=7.2.0,<=8.0.0)", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "timm", "torchdata (>=0.8.0)", "torchpippy (>=0.2.0)", "tqdm", "transformers"]
+
 [[package]]
 name = "accessible-pygments"
 version = "0.0.5"
@@ -569,6 +600,45 @@ files = [
 [package.extras]
 tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich"]
 
+[[package]]
+name = "faiss-cpu"
+version = "1.8.0.post1"
+description = "A library for efficient similarity search and clustering of dense vectors."
+optional = true
+python-versions = ">=3.8"
+files = [
+    {file = "faiss_cpu-1.8.0.post1-cp310-cp310-macosx_10_14_x86_64.whl", hash = "sha256:fd84721eb599aa1da19b1b36345bb8705a60bb1d2887bbbc395a29e3d36a1a62"},
+    {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"},
+    {file = "faiss_cpu-1.8.0.post1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:20bd43eca3b7d77e71ea56b7a558cc28e900d8abff417eb285e2d92e95d934d4"},
+    {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-cp311-cp311-win_amd64.whl", hash = "sha256:4fa5fc8ea210b919aa469e27d6687e50052db906e7fec3f2257178b1384fa18b"},
+    {file = "faiss_cpu-1.8.0.post1-cp312-cp312-macosx_10_14_x86_64.whl", hash = "sha256:96aec0d08a3099883af3a9b6356cfe736e8bd879318a940a27e9d1ae6f33d788"},
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+    {file = "faiss_cpu-1.8.0.post1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:327a9c30971bf72cd8392b15eb4aff5d898c453212eae656dfaa3ba555b9ca0c"},
+    {file = "faiss_cpu-1.8.0.post1-cp312-cp312-win_amd64.whl", hash = "sha256:8756f1d93faba56349883fa2f5d47fe36bb2f11f789200c6b1c691ef805485f2"},
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@@ -2860,6 +3414,23 @@ pure-eval = "*"
 [package.extras]
 tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
+[[package]]
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+
 [[package]]
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 version = "0.9.0"
@@ -2874,6 +3445,17 @@ files = [
 [package.extras]
 widechars = ["wcwidth"]
 
+[[package]]
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+description = "threadpoolctl"
+optional = true
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 version = "0.5.2"
@@ -3065,6 +3647,60 @@ files = [
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@@ -3100,6 +3736,96 @@ files = [
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 test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<8.2)", "pytest-mock", "pytest-mypy-testing"]
 
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+    {file = "triton-3.0.0-1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:5ce8520437c602fb633f1324cc3871c47bee3b67acf9756c1a66309b60e3216c"},
+    {file = "triton-3.0.0-1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:34e509deb77f1c067d8640725ef00c5cbfcb2052a1a3cb6a6d343841f92624eb"},
+    {file = "triton-3.0.0-1-cp38-cp38-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:bcbf3b1c48af6a28011a5c40a5b3b9b5330530c3827716b5fbf6d7adcc1e53e9"},
+    {file = "triton-3.0.0-1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:6e5727202f7078c56f91ff13ad0c1abab14a0e7f2c87e91b12b6f64f3e8ae609"},
+]
+
+[package.dependencies]
+filelock = "*"
+
+[package.extras]
+build = ["cmake (>=3.20)", "lit"]
+tests = ["autopep8", "flake8", "isort", "llnl-hatchet", "numpy", "pytest", "scipy (>=1.7.1)"]
+tutorials = ["matplotlib", "pandas", "tabulate"]
+
 [[package]]
 name = "types-beautifulsoup4"
 version = "4.12.0.20240907"
@@ -3260,12 +3986,13 @@ files = [
 requests = "*"
 
 [extras]
-all = ["flask", "matplotlib", "numpy", "pandas", "pillow", "playwright"]
+all = ["accelerate", "faiss-cpu", "flask", "matplotlib", "numpy", "pandas", "pathspec", "pillow", "playwright", "sentence-transformers", "transformers"]
 browser = ["playwright"]
 datascience = ["matplotlib", "numpy", "pandas", "pillow"]
+rag = ["accelerate", "faiss-cpu", "pathspec", "sentence-transformers", "transformers"]
 server = ["flask"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "9661df8ab23362fc6be15df6f23d614f4ece100e85247f0b37083f8fa0aed999"
+content-hash = "7aa30bed0df86b8a53d760a1b9cbe08c5f8b67ce61f74726b73b66b6027b8759"
diff --git a/pyproject.toml b/pyproject.toml
index a46743a1..01d9749b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -51,6 +51,13 @@ pillow = {version = "*", optional=true}
 # server
 flask = {version = "^2.3", optional=true}
 
+# rag
+faiss-cpu = {version = "^1.8.0.post1", optional=true}
+sentence-transformers = {version = "^3.1.1", optional=true}
+transformers = {version = "^4.44.2", optional=true}
+accelerate = {version = "^0.34.2", optional=true}
+pathspec = {version = "^0.12.1", optional=true}
+
 [tool.poetry.group.dev.dependencies]
 # lint
 mypy = "*"
@@ -81,6 +88,7 @@ types-lxml = "^2024.9.16"
 server = ["flask"]
 browser = ["playwright"]
 datascience = ["matplotlib", "pandas", "numpy", "pillow"]
+rag = ["faiss-cpu", "sentence-transformers", "transformers", "accelerate", "pathspec"]
 all = [
     # server
     "flask",
@@ -88,6 +96,8 @@ all = [
     "playwright",
     # datascience
     "matplotlib", "pandas", "numpy", "pillow",
+    # rag
+    "faiss-cpu", "sentence-transformers", "transformers", "accelerate", "pathspec",
 ]
 
 [tool.ruff]
diff --git a/tests/test_tools_rag.py b/tests/test_tools_rag.py
new file mode 100644
index 00000000..2025b701
--- /dev/null
+++ b/tests/test_tools_rag.py
@@ -0,0 +1,147 @@
+import os
+import tempfile
+import pytest
+import faiss
+import pathspec
+from sentence_transformers import SentenceTransformer
+from gptme.tools.rag.indexer import (
+    load_code_files,
+    chunk_code_syntactically,
+    chunk_code_line_based,
+    create_index,
+    should_reindex,
+)
+from gptme.tools.rag.retriever import retrieve_relevant_chunks, retrieve
+
+
+@pytest.fixture
+def temp_dir():
+    with tempfile.TemporaryDirectory() as temp_dir:
+        yield temp_dir
+
+
+@pytest.fixture
+def model():
+    return SentenceTransformer("all-MiniLM-L6-v2")
+
+
+def test_load_code_files(temp_dir):
+    # Create test files
+    os.makedirs(os.path.join(temp_dir, "subdir"))
+    with open(os.path.join(temp_dir, "file1.py"), "w") as f:
+        f.write("print('Hello, world!')")
+    with open(os.path.join(temp_dir, "subdir", "file2.py"), "w") as f:
+        f.write("def foo():\n    return 'bar'")
+    with open(os.path.join(temp_dir, ".gitignore"), "w") as f:
+        f.write("*.pyc\n__pycache__\n")
+
+    # Load code files
+    code_files = load_code_files(
+        temp_dir,
+        pathspec.PathSpec.from_lines(
+            "gitwildmatch", open(os.path.join(temp_dir, ".gitignore"))
+        ),
+    )
+
+    # Check that the correct files are loaded
+    assert len(code_files) == 2
+    assert "file1.py" in [os.path.basename(cf[0]) for cf in code_files]
+    assert "file2.py" in [os.path.basename(cf[0]) for cf in code_files]
+
+
+def test_chunk_code_syntactically():
+    code = """
+def foo():
+    \"\"\"This is a docstring.\"\"\"
+    print('Hello, world!')
+
+class Bar:
+    def baz(self):
+        pass
+"""
+    chunks = chunk_code_syntactically(code, "test.py")
+    assert len(chunks) == 3
+    assert "def foo()" in chunks[0][1]
+    assert "class Bar" in chunks[1][1]
+
+
+def test_chunk_code_line_based():
+    code = """
+import { ref, computed } from 'vue'
+import { defineStore } from 'pinia'
+
+export const useCounterStore = defineStore('counter', () => {
+  const count = ref(0)
+  const doubleCount = computed(() => count.value * 2)
+  function increment() {
+    count.value++
+  }
+
+  return { count, doubleCount, increment }
+})
+"""
+    chunks = chunk_code_line_based(code, "test.ts", language="typescript")
+    assert len(chunks) == 1
+    assert "function increment()" in chunks[0][1]
+
+
+def test_create_index(temp_dir, model):
+    # Create test files
+    os.makedirs(os.path.join(temp_dir, "subdir"))
+    with open(os.path.join(temp_dir, "file1.py"), "w") as f:
+        f.write("print('Hello, world!')")
+    with open(os.path.join(temp_dir, "subdir", "file2.py"), "w") as f:
+        f.write("def foo():\n    return 'bar'")
+
+    # Load code files
+    print("Loading code files...")
+    code_files = load_code_files(temp_dir, pathspec.PathSpec([]))
+
+    # Create index
+    print("Creating index...")
+    index, metadata = create_index(code_files, model)
+
+    # Check that the index and metadata are created correctly
+    assert isinstance(index, faiss.Index)
+    assert len(metadata) == 2
+
+
+def test_retrieve_relevant_chunks(temp_dir, model):
+    # Create test files
+    os.makedirs(os.path.join(temp_dir, "subdir"))
+    with open(os.path.join(temp_dir, "file1.py"), "w") as f:
+        f.write("print('Hello, world!')")
+    with open(os.path.join(temp_dir, "subdir", "file2.py"), "w") as f:
+        f.write("def foo():\n    return 'bar'")
+
+    # Load code files
+    code_files = load_code_files(temp_dir, pathspec.PathSpec([]))
+
+    # Create index
+    index, metadata = create_index(code_files, model)
+
+    # Retrieve relevant chunks
+    query = "foo"
+    relevant_chunks = retrieve_relevant_chunks(query, index, metadata, model)
+
+    # Check that the relevant chunks are retrieved correctly
+    assert len(relevant_chunks) > 0
+    assert "def foo()" in relevant_chunks[0][1]
+
+
+def test_should_reindex():
+    current_metadata = {"file1.py": 1234.0, "file2.py": 5678.0}
+    previous_metadata = {"file1.py": 1234.0, "file2.py": 5677.0}
+    assert should_reindex(current_metadata, previous_metadata)
+
+    previous_metadata = {"file1.py": 1234.0, "file2.py": 5678.0}
+    assert not should_reindex(current_metadata, previous_metadata)
+
+
+def test_retrieve():
+    query = "function foo"
+    result = retrieve(query)
+    assert isinstance(result, str)
+    assert "File:" in result
+    assert "Lines" in result
+    assert "Distance:" in result