diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 0000000..95a4d5a --- /dev/null +++ b/.editorconfig @@ -0,0 +1,9 @@ +root = true + +[*.py] +indent_style = space +indent_size = 4 +end_of_line = lf +charset = utf-8 +trim_trailing_whitespace = true +insert_final_newline = true diff --git a/.flake8 b/.flake8 new file mode 100644 index 0000000..8558e59 --- /dev/null +++ b/.flake8 @@ -0,0 +1,4 @@ +[flake8] +max-line-length = 88 +ignore = E203, W503 +exclude = .git,__pycache__,env,.venv,venv diff --git a/.github/workflows/cd.yaml b/.github/workflows/cd.yaml new file mode 100644 index 0000000..3aaa3e3 --- /dev/null +++ b/.github/workflows/cd.yaml @@ -0,0 +1,71 @@ +name: "CD" + +on: + workflow_dispatch: + inputs: + branch: + description: "Target branch for release" + required: true + default: "main" + release-type: + description: "Type of release?" + required: true + type: choice + options: + - patch + - minor + - major + +jobs: + release: + name: "Release" + if: github.event.inputs.branch == 'main' + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v3 + + - uses: actions/setup-python@v4 + with: + python-version: "3.11" + + - uses: Gr1N/setup-poetry@v8 + with: + poetry-version: "1.2.2" + + - name: "Bump `git_vector.__version__`" + run: sed -i 's/^__version__ *=.*/__version__ = "${{ steps.bump.outputs.version }}"/' git_vector/__init__.py + + - name: "Update the changelog" + # Find the first line that starts with `###` or `## [` from the CHANGELOG and insert the new version header before it. + run: sed -i "0,/^\(###\|## *\[[0-9]\).*/{s//## [${{ steps.bump.outputs.version }}] - $(date -u '+%Y-%m-%d')\n\n&/}" CHANGELOG.md + + - name: "Extract version's changelog for release notes" + # 1. Find the lines between the first `## [` and the second `## [`. + # 2. Remove all leading and trailing newlines from the output. + run: sed '1,/^## *\[[0-9]/d;/^## *\[[0-9]/Q' CHANGELOG.md | sed -e :a -e '/./,$!d;/^\n*$/{$d;N;};/\n$/ba' > release_notes.txt + + - name: "Commit and tag the changes" + run: | + git config user.name 'github-actions' + git config user.email '41898282+github-actions[bot]@users.noreply.github.com' + git add pyproject.toml git_vector/__init__.py CHANGELOG.md + git commit --message='Release ${{ steps.bump.outputs.version }}' + git tag --annotate --message='' v${{ steps.bump.outputs.version }} + + - name: "Build the wheel" + run: poetry build + + - name: "Publish to PyPI" + run: poetry publish + env: + POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_TOKEN }} + + - name: "Push the changes" + run: git push --follow-tags + + - name: "Create a GitHub release" + uses: softprops/action-gh-release@1e07f4398721186383de40550babbdf2b84acfc5 # v1 + with: + tag_name: v${{ steps.bump.outputs.version }} + name: v${{ steps.bump.outputs.version }} + body_path: release_notes.txt diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml new file mode 100644 index 0000000..b57560c --- /dev/null +++ b/.github/workflows/ci.yaml @@ -0,0 +1,132 @@ +name: CI + +on: + push: + branches: [main] + pull_request: + branches: [main] + +jobs: + linters: + name: "Linters" + runs-on: ubuntu-latest + steps: + - name: "Checkout code" + uses: actions/checkout@v3 + + - name: "Set up Python" + uses: actions/setup-python@v4 + with: + python-version: "3.11" + + - name: "Install Poetry" + uses: Gr1N/setup-poetry@v8 + + - name: "Load cached venv" + uses: actions/cache@v2 + with: + path: ~/.cache/pypoetry/virtualenvs + key: ${{ runner.os }}-poetry-${{ hashFiles('poetry.lock') }} + + - name: "Install dependencies" + if: steps.cached-poetry-dependencies.outputs.cache-hit != 'true' + run: poetry install --no-root + + - name: "Set VENV variable" + run: | + if [ "${{ runner.os }}" == "Windows" ]; then + echo "VENV=$(poetry env info -p)\\Scripts\\activate" >> $GITHUB_ENV + else + echo "VENV=$(poetry env info -p)/bin/activate" >> $GITHUB_ENV + fi + shell: bash + + - name: "Run linters" + run: | + source "$VENV" + isort --check-only --diff . + flake8 . + black --check --diff . + + build: + name: "Build" + runs-on: ubuntu-latest + steps: + - name: "Checkout code" + uses: actions/checkout@v3 + + - name: "Set up Python" + uses: actions/setup-python@v4 + with: + python-version: "3.11" + + - name: "Install Poetry" + uses: Gr1N/setup-poetry@v8 + + - name: "Build the wheel" + run: poetry build + + - name: "Install from the wheel" + run: pip install dist/*.whl + + tests: + name: "Tests" + needs: [linters, build] + strategy: + fail-fast: true + matrix: + python-version: ["3.7", "3.8", "3.9", "3.10", "3.11"] + os: [ubuntu-latest, macos-latest, windows-latest] + defaults: + run: + shell: bash + runs-on: ${{ matrix.os }} + steps: + - name: "Checkout code" + uses: actions/checkout@v3 + + - name: "Set up Python" + uses: actions/setup-python@v4 + with: + python-version: "3.11" + + - name: "Install Poetry" + uses: Gr1N/setup-poetry@v8 + + - name: "Load cached venv" + uses: actions/cache@v2 + with: + path: ~/.cache/pypoetry/virtualenvs + key: ${{ runner.os }}-poetry-${{ hashFiles('poetry.lock') }} + + - name: "Install dependencies" + if: steps.cached-poetry-dependencies.outputs.cache-hit != 'true' + run: poetry install --no-root + + - name: "Install the package" + run: poetry install + + - name: "Set VENV variable" + run: | + if [ "${{ runner.os }}" == "Windows" ]; then + echo "VENV=$(poetry env info -p)\\Scripts\\activate" >> $GITHUB_ENV + else + echo "VENV=$(poetry env info -p)/bin/activate" >> $GITHUB_ENV + fi + shell: bash + + - name: "Run type-checking" + run: | + source "$VENV" + mypy . + + - name: "Run tests" + run: | + source "$VENV" + pytest --verbose --cov=. --cov-report=xml . + + - name: "Upload coverage" + if: matrix.python-version == '3.11' && matrix.os == 'ubuntu-latest' + uses: codecov/codecov-action@f32b3a3741e1053eb607407145bc9619351dc93b # v2.1.0 + with: + files: coverage.xml diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..59b6f98 --- /dev/null +++ b/.gitignore @@ -0,0 +1,164 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/latest/usage/project/#working-with-version-control +.pdm.toml +.pdm-python +.pdm-build/ + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ + +embeddings_cache/ diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000..918eda8 --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,25 @@ +repos: + - repo: https://github.com/pre-commit/mirrors-mypy + rev: v1.5.1 + hooks: + - id: mypy + - repo: https://github.com/psf/black + rev: 24.8.0 + hooks: + - id: black + - repo: https://github.com/PyCQA/isort + rev: 5.13.2 + hooks: + - id: isort + - repo: https://github.com/PyCQA/flake8 + rev: 7.1.1 + hooks: + - id: flake8 + args: [--max-line-length=88, "--ignore=E203,W503"] + - repo: local + hooks: + - id: run-tests + name: Run Tests + entry: scripts/run_tests.sh + language: script + pass_filenames: false diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 0000000..d89a78f --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,14 @@ +# Changelog + +All notable changes to this project will be documented in this file. + +The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), +and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). + +## [Unreleased] + +## [0.1.0] - 2024-10-27 + +### Added + +- Add initial implementation. diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..be09e16 --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2024 Markus Blomqvist + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/README.md b/README.md new file mode 100644 index 0000000..cea8007 --- /dev/null +++ b/README.md @@ -0,0 +1,72 @@ +# Git-Vector + +[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE) + +**Git-Vector** is a command-line tool that allows developers to interact with their Git repositories using OpenAI models. It provides a conversational interface to help you understand and navigate your codebase by leveraging the full context of your repository. + +## Table of Contents + +- [Git-Vector](#git-vector) + - [Table of Contents](#table-of-contents) + - [Features](#features) + - [Installation](#installation) + - [Usage](#usage) + - [Configuration](#configuration) + - [License](#license) + - [Author](#author) + - [Acknowledgments](#acknowledgments) + +## Features + +- **Conversational Interface**: Interactively ask questions about your codebase and receive detailed explanations. +- **Full Repository Context**: The tool indexes your entire Git repository to provide context-aware responses. +- **Caching Mechanism**: Embeddings are cached to improve performance on subsequent runs. +- **Customizable Models**: Supports different OpenAI models for both embeddings and chat completions. +- **Configurable Parameters**: Adjust maximum tokens for prompts and responses to suit your needs. + +## Installation + +```bash +pip install git-vector +``` + +## Usage + +1. **Set Up Environment Variables**: + + Export your OpenAI API key as an environment variable (or use a `.env` file): + + ``` + export OPENAI_API_KEY=your_api_key_here + ``` + +2. **Run the Application**: + + ``` + git-vector --repo-dir /path/to/your/git/repository + ``` + + This will start the intera`tive CLI for the user to chat with the codebase. + +## Configuration + +- `--repo-dir`: (Required) The path to the Git repository. +- `--embedding-model`: The OpenAI model to use for embeddings (default: `text-embedding-3-small`). +- `--chat-model`: The OpenAI model to use for chat completions (default: `gpt-4o-mini`). +- `--max-prompt-tokens`: Maximum number of tokens for the prompt (default: `2000`). +- `--max-response-tokens`: Maximum number of tokens for the response (default: `500`). + +## License + +This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details. + +## Author + +- Markus Blomqvist - [blomqvist_markus@hotmail.com](mailto:blomqvist_markus@hotmail.com) + +## Acknowledgments + +- [OpenAI](https://openai.com) for providing the API that powers this tool. +- [GitPython](https://gitpython.readthedocs.io/en/stable/) for interacting with Git repositories. +- [NumPy](https://numpy.org/) and [scikit-learn](https://scikit-learn.org/) for numerical and machine learning + 2024-09-25 00:12:15,639 [INFO] Response provided to the user. diff --git a/git_vector/__init__.py b/git_vector/__init__.py new file mode 100644 index 0000000..fceb681 --- /dev/null +++ b/git_vector/__init__.py @@ -0,0 +1,5 @@ +__version__ = "0.1.0" + +from .git_vector import main + +__all__ = ["main"] diff --git a/git_vector/git_vector.py b/git_vector/git_vector.py new file mode 100644 index 0000000..ec876a6 --- /dev/null +++ b/git_vector/git_vector.py @@ -0,0 +1,416 @@ +import hashlib +import logging +import mimetypes +import os +import pickle +import time +from typing import Any, Dict, List, Tuple + +import click +import git +import numpy as np +from dotenv import load_dotenv +from openai import OpenAI, RateLimitError +from sklearn.metrics.pairwise import cosine_similarity # type: ignore [import-untyped] +from tqdm import tqdm + +load_dotenv() +client = OpenAI(api_key=os.getenv("OPENAI_API_KEY")) + +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s [%(levelname)s] %(message)s", + handlers=[logging.FileHandler("codebase_assistant.log"), logging.StreamHandler()], +) + +logger = logging.getLogger(__name__) + + +def get_repo_hash(repo_dir: str) -> str: + """Generate a unique hash for the repository directory path.""" + repo_path_bytes = repo_dir.encode("utf-8") + return hashlib.md5(repo_path_bytes).hexdigest() + + +def load_embeddings_cache(cache_file: str) -> Dict[str, Any]: + """Load the embeddings cache from a file or initialize an empty cache.""" + if os.path.exists(cache_file): + with open(cache_file, "rb") as f: + cache = pickle.load(f) + logger.info("Embeddings cache loaded.") + else: + cache = {} + logger.info("Initialized empty embeddings cache.") + return cache + + +def save_embeddings_cache(cache: Dict[str, Any], cache_file: str) -> None: + """Save the embeddings cache to a file.""" + with open(cache_file, "wb") as f: + pickle.dump(cache, f) + logger.info("Embeddings cache saved.") + + +def get_tracked_files(repo_dir: str) -> List[str]: + """Get a list of all tracked files in the Git repository using GitPython.""" + try: + repo = git.Repo(repo_dir) + tracked_files = [ + os.path.join(repo_dir, item.path) # type: ignore [union-attr] + for item in repo.tree().traverse() + ] + logger.info(f"Found {len(tracked_files)} tracked files using GitPython.") + return tracked_files + except git.exc.InvalidGitRepositoryError: + logger.error("Invalid Git repository.") + click.echo("The specified directory is not a valid Git repository.") + return [] + except Exception as e: + logger.error(f"Error accessing Git repository: {e}") + click.echo("An error occurred while accessing the Git repository.") + return [] + + +def is_text_file(file_path: str) -> bool: + """Check if a file is a text file.""" + mime_type, _ = mimetypes.guess_type(file_path) + if mime_type and "text" in mime_type: + return True + else: + # Fallback for files without a MIME type + try: + with open(file_path, "r", encoding="utf-8") as f: + f.read(1024) + return True + except Exception: + return False + + +def collect_code_files(repo_dir: str) -> List[str]: + """Collect all text-based code files in the repository.""" + code_files = [] + tracked_files = get_tracked_files(repo_dir) + + if not tracked_files: + return [] + + logger.info("Filtering text files...") + + for file_path in tqdm(tracked_files, desc="Filtering files"): + if is_text_file(file_path): + code_files.append(file_path) + + logger.info(f"Collected {len(code_files)} text files for processing.") + return code_files + + +def split_into_chunks(text: str, max_tokens: int = 500) -> List[str]: + """Split text into chunks of approximately max_tokens tokens.""" + tokens = text.split() + chunks = [ + " ".join(tokens[i : i + max_tokens]) for i in range(0, len(tokens), max_tokens) + ] + return chunks + + +def generate_embeddings( + text_list: List[str], model_name: str, batch_size: int = 100 +) -> List[List[float]]: + """Generate embeddings for a list of texts using the specified model.""" + embeddings = [] + logger.info(f"Generating embeddings with model: {model_name}") + + for i in tqdm(range(0, len(text_list), batch_size), desc="Embedding chunks"): + batch = text_list[i : i + batch_size] + max_retries = 5 + retry_count = 0 + while retry_count < max_retries: + try: + response = client.embeddings.create(input=batch, model=model_name) + batch_embeddings = [data.embedding for data in response.data] + embeddings.extend(batch_embeddings) + break # Exit the retry loop on success + except RateLimitError: + retry_count += 1 + wait_time = 2**retry_count # Exponential backoff + logger.warning( + f"Rate limit exceeded. Retrying in {wait_time} seconds..." + ) + time.sleep(wait_time) + except Exception as e: + logger.error(f"Error generating embeddings: {e}") + break # Exit the loop on non-rate-limit errors + else: + logger.error(f"Max retries exceeded for batch starting at index {i}") + raise Exception("Max retries exceeded") + + return embeddings + + +def chunk_and_embed_files( + file_paths: List[str], cache: Dict[str, Any], cache_file: str, model_name: str +) -> Tuple[List[Dict[str, str]], List[List[float]]]: + """Chunk the code files and generate embeddings, using cache.""" + code_chunks = [] + embeddings = [] + logger.info("Processing files and generating embeddings...") + + for file_path in tqdm(file_paths, desc="Processing files"): + try: + last_modified = os.path.getmtime(file_path) + cache_entry = cache.get(file_path) + + if cache_entry and cache_entry["last_modified"] == last_modified: + code_chunks.extend(cache_entry["chunks"]) + embeddings.extend(cache_entry["embeddings"]) + logger.debug(f"Loaded cached embeddings for {file_path}") + else: + with open(file_path, "r", encoding="utf-8", errors="ignore") as f: + content = f.read() + + if not content.strip(): + continue + + chunks = split_into_chunks(content) + chunk_embeddings = generate_embeddings(chunks, model_name) + + for chunk, embedding in zip(chunks, chunk_embeddings): + code_chunks.append({"content": chunk, "file_path": file_path}) + embeddings.append(embedding) + + cache[file_path] = { + "last_modified": last_modified, + "chunks": [ + {"content": chunk, "file_path": file_path} for chunk in chunks + ], + "embeddings": chunk_embeddings, + } + except Exception as e: + logger.warning(f"Failed to process {file_path}: {e}") + + save_embeddings_cache(cache, cache_file) + + if not code_chunks: + logger.warning("No code chunks to process.") + + return code_chunks, embeddings + + +def get_top_k_similar_chunks( + query: str, + code_chunks: List[Dict[str, str]], + embeddings: List[List[float]], + embedding_model: str, + k: int = 5, +) -> List[Dict[str, str]]: + """Retrieve the top k code chunks most similar to the query.""" + response = client.embeddings.create(input=[query], model=embedding_model) + + query_embedding = response.data[0].embedding + similarities = cosine_similarity([query_embedding], embeddings)[0] + top_k_indices = similarities.argsort()[-k:][::-1] + top_k_chunks = [code_chunks[i] for i in top_k_indices] + return top_k_chunks + + +def construct_prompt( + question: str, code_contexts: List[Dict[str, str]], max_prompt_tokens: int +) -> str: + """Construct the prompt for the OpenAI API.""" + context_texts = [] + + for context in code_contexts: + context_text = f"File: {context['file_path']}\nContent:\n{context['content']}\n" + context_texts.append(context_text) + + context_combined = "\n".join(context_texts) + prompt = f""" +You are an AI assistant helping a developer understand their codebase. + +Code Context: +{context_combined} + +Question: +{question} + +Answer: +""" + + # Handle token limits + prompt_tokens_estimate = len(prompt) // 4 # Approximate token count + if prompt_tokens_estimate > max_prompt_tokens: + # Truncate context to fit within token limit + allowed_context_tokens = ( + max_prompt_tokens - len(question) // 4 - 100 + ) # Reserve tokens + # Truncate context_combined + context_combined = context_combined[: allowed_context_tokens * 4] + prompt = f""" +You are an AI assistant helping a developer understand their codebase. + +Code Context: +{context_combined} + +Question: +{question} + +Answer: +""" + return prompt + + +def interactive_cli( + code_chunks: List[Dict[str, str]], + embeddings: List[List[float]], + chat_model: str, + embedding_model: str, + max_prompt_tokens: int, + max_response_tokens: int, +) -> None: + """Start the interactive CLI for the user to chat with the codebase.""" + click.echo( + "Welcome to the Codebase Assistant. Type your questions below (type 'exit' to quit)." # noqa: E501 + ) + while True: + question = click.prompt("\nYour question", type=str) + if question.lower() == "exit": + click.echo("Goodbye!") + break + logger.info(f"User question: {question}") + try: + top_chunks = get_top_k_similar_chunks( + query=question, + code_chunks=code_chunks, + embeddings=embeddings, + embedding_model=embedding_model, + ) + prompt = construct_prompt( + question=question, + code_contexts=top_chunks, + max_prompt_tokens=max_prompt_tokens, + ) + response = None + max_retries = 5 + retry_count = 0 + while retry_count < max_retries: + try: + response = client.chat.completions.create( + model=chat_model, + messages=[{"role": "user", "content": prompt}], + max_tokens=max_response_tokens, + temperature=0.2, + ) + break # Exit the retry loop on success + except RateLimitError: + retry_count += 1 + wait_time = 2**retry_count # Exponential backoff + logger.warning( + f"Rate limit exceeded. Retrying in {wait_time} seconds..." + ) + time.sleep(wait_time) + except Exception as e: + logger.error(f"Error during API call: {e}") + click.echo("An error occurred while processing your request.") + break # Exit the loop on non-rate-limit errors + if response: + answer = response.choices[0].message.content + click.echo(f"\nAssistant:\n{answer}") + logger.info("Response provided to the user.") + else: + logger.error("Failed to get a response from the API.") + click.echo("Failed to get a response from the API.") + except Exception as e: + logger.error(f"Error processing your question: {e}") + click.echo("An error occurred while processing your question.") + + +@click.command() +@click.option( + "--repo-dir", prompt="Repository path", help="The path to the Git repository." +) +@click.option( + "--embedding-model", + default="text-embedding-3-small", + show_default=True, + help="The OpenAI model to use for embeddings.", +) +@click.option( + "--chat-model", + default="gpt-4o-mini", + show_default=True, + help="The OpenAI model to use for chat completions.", +) +@click.option( + "--max-prompt-tokens", + default=128_000, + show_default=True, + help="Maximum number of tokens for the prompt.", +) +@click.option( + "--max-response-tokens", + default=16_384, + show_default=True, + help="Maximum number of tokens for the response.", +) +def main( + repo_dir: str, + embedding_model: str, + chat_model: str, + max_prompt_tokens: int, + max_response_tokens: int, +) -> None: + """Main function to run the CLI tool.""" + logger.info("Starting Codebase Assistant...") + + current_file_path = os.path.abspath(__file__) + current_dir = os.path.dirname(current_file_path) + cli_dir = os.path.dirname(current_dir) + cache_dir = os.path.join(cli_dir, "embeddings_cache") + os.makedirs(cache_dir, exist_ok=True) + + repo_dir = os.path.abspath(repo_dir) + repo_hash = get_repo_hash(repo_dir) + + cache_file = os.path.join(cache_dir, f"embeddings_cache_{repo_hash}.pkl") + logger.info(f"Using cache file: {cache_file}") + + if not os.path.isdir(repo_dir): + logger.error("Invalid repository path.") + click.echo("The specified repository path is invalid.") + return + + cache = load_embeddings_cache(cache_file) + click.echo("Collecting code files...") + code_files = collect_code_files(repo_dir) + + if not code_files: + logger.error("No code files found.") + click.echo( + "No code files found in the repository or failed to access the repository." + ) + return + + code_chunks, embeddings = chunk_and_embed_files( + file_paths=code_files, + cache=cache, + cache_file=cache_file, + model_name=embedding_model, + ) + if not code_chunks or not embeddings: + logger.error("Failed to process code files for embeddings.") + click.echo("Failed to process code files.") + return + + embeddings_array = np.array(embeddings) + interactive_cli( + code_chunks=code_chunks, + embeddings=embeddings_array, # type: ignore [arg-type] + chat_model=chat_model, + embedding_model=embedding_model, + 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--hash=sha256:2f6da418d1f1e0fddd844478f41680e794e6051915791a034ff65e5f100525a2 \ + --hash=sha256:f4324edc670a0f49750a81b895f35c3adb843cca46f0530f79fc1babb23789dc +threadpoolctl==3.5.0 ; python_version >= "3.12" and python_version < "4.0" \ + --hash=sha256:082433502dd922bf738de0d8bcc4fdcbf0979ff44c42bd40f5af8a282f6fa107 \ + --hash=sha256:56c1e26c150397e58c4926da8eeee87533b1e32bef131bd4bf6a2f45f3185467 +tqdm==4.66.5 ; python_version >= "3.12" and python_version < "4.0" \ + --hash=sha256:90279a3770753eafc9194a0364852159802111925aa30eb3f9d85b0e805ac7cd \ + --hash=sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad +typing-extensions==4.12.2 ; python_version >= "3.12" and python_version < "4.0" \ + --hash=sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d \ + --hash=sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8 diff --git a/scripts/run_tests.sh b/scripts/run_tests.sh new file mode 100755 index 0000000..6b1a2ff --- /dev/null +++ b/scripts/run_tests.sh @@ -0,0 +1,2 @@ +#!/bin/bash +poetry run pytest diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/test_git_vector.py b/tests/test_git_vector.py new file mode 100644 index 0000000..e5d3c5c --- /dev/null +++ b/tests/test_git_vector.py @@ -0,0 +1,6 @@ +def test_version(mocker): + mocker.patch.dict("os.environ", {"OPENAI_API_KEY": "dummy-api-key"}) + + from git_vector import __version__ + + assert __version__ == "0.1.0"