├── tests └── __init__.py ├── ai_docs ├── __init__.py ├── generate_docs.py ├── extract_repo.py └── api.py ├── .gitignore ├── assets └── image.png ├── pyproject.toml ├── README.md └── poetry.lock /tests/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /ai_docs/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .env 2 | *.txt 3 | *.zip 4 | __pycache__ 5 | *.pyc -------------------------------------------------------------------------------- /assets/image.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/connor-john/ai-docs/HEAD/assets/image.png -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [tool.poetry] 2 | name = "ai_docs" 3 | version = "0.1.0" 4 | description = "" 5 | authors = ["Connor (Cub) "] 6 | readme = "README.md" 7 | 8 | [tool.poetry.dependencies] 9 | python = "^3.9" 10 | python-dotenv = "^1.0.1" 11 | anthropic = "^0.21.3" 12 | transformers = "^4.39.1" 13 | 14 | 15 | [build-system] 16 | requires = ["poetry-core"] 17 | build-backend = "poetry.core.masonry.api" 18 | -------------------------------------------------------------------------------- /ai_docs/generate_docs.py: -------------------------------------------------------------------------------- 1 | import sys 2 | 3 | from .api import ( 4 | BASIC_DOCS_SYSTEM_PROMPT, 5 | REFINED_DOCS_FOLLOW_UP_PROMPT, 6 | check_prompt_token_size, 7 | read_file, 8 | request_message, 9 | ) 10 | from ai_docs.extract_repo import extract_local_directory 11 | 12 | SIGNATURE = """ 13 | > [!NOTE] 14 | > Documentation auto-generated by [ai-docs.](https://github.com/connor-john/ai-docs) 15 | 16 | """ 17 | 18 | 19 | def _extend_docs(repo_name: str, messages: list[dict[str, str]], message: str) -> None: 20 | """Prompt further to refine the documentation for niche insights""" 21 | proceed_check = input( 22 | f"Please check the file generated at: {repo_name}-docs.md. Do you wish to further refine documentation? (Y/N)" 23 | ) 24 | if str(proceed_check).upper() != "Y": 25 | print("Exiting") 26 | sys.exit(1) 27 | 28 | messages.extend( 29 | [ 30 | {"role": "assistant", "content": message}, 31 | {"role": "user", "content": REFINED_DOCS_FOLLOW_UP_PROMPT}, 32 | ] 33 | ) 34 | response = request_message(BASIC_DOCS_SYSTEM_PROMPT, messages) 35 | 36 | message = response.content[0].text 37 | with open(f"{repo_name}-further-docs.md", "w", encoding="utf-8") as file: 38 | file.write(message) 39 | 40 | 41 | def generate_docs_from_local_repo(directory_path): 42 | """Generate docs for the provided repo using Claude Opus.""" 43 | 44 | code_file_path = extract_local_directory(directory_path) 45 | file_content = read_file(code_file_path) 46 | input_prompt = f"Given this repo. \n{file_content}\ncomplete your instruction" 47 | token_size = check_prompt_token_size(input_prompt) 48 | 49 | proceed_check = input( 50 | f"Input token size is: {token_size}. Do you wish to proceed? (Y/N)" 51 | ) 52 | if str(proceed_check).upper() != "Y": 53 | print("Exiting") 54 | sys.exit(1) 55 | 56 | messages = [ 57 | {"role": "user", "content": input_prompt}, 58 | ] 59 | response = request_message(BASIC_DOCS_SYSTEM_PROMPT, messages) 60 | 61 | message = response.content[0].text 62 | readme_text = SIGNATURE + message 63 | readme_path = f"{directory_path}/README.md" 64 | with open(readme_path, "w", encoding="utf-8") as file: 65 | file.write(readme_text) 66 | 67 | 68 | if __name__ == "__main__": 69 | if len(sys.argv) != 2: 70 | print("Usage: python generate_docs.py ") 71 | sys.exit(1) 72 | 73 | directory_path = sys.argv[1] 74 | generate_docs_from_local_repo(directory_path) 75 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # AI Docs 2 | 3 | > [!NOTE] 4 | > Documentation auto-generated by [ai-docs.](https://github.com/connor-john/ai-docs) 5 | 6 | ## Introduction 7 | AI Docs is a Python project that generates technical documentation for code repositories using the Anthropic Claude AI model. The project aims to automate the process of creating comprehensive documentation by analyzing the codebase and generating readable, structured content. It can be particularly useful for quickly documenting projects and facilitating knowledge transfer among development teams. 8 | 9 | ## Codebase Overview 10 | The AI Docs codebase is organized into a few key modules: 11 | 12 | - `api.py`: Contains the main functionality for interacting with the Anthropic API, sending prompts, and receiving generated documentation. 13 | - `extract_repo.py`: Responsible for extracting relevant code files from a local repository and converting them into a single text file for processing. 14 | - `generate_docs.py`: Provides a high-level function to generate documentation for a given local repository directory. 15 | 16 | The project uses the `anthropic` library for communicating with the Claude AI model and the `transformers` library for token counting. It also utilizes the `python-dotenv` library for managing environment variables, such as the Anthropic API key. 17 | 18 | ## Development Environment Setup 19 | To set up the development environment for AI Docs, follow these steps: 20 | 21 | 1. Ensure you have Python 3.9 or higher installed on your system. 22 | 2. Clone the AI Docs repository from the version control system. 23 | 3. Navigate to the project directory. 24 | 4. Install Poetry, the dependency management tool used by the project, by following the official installation guide: https://python-poetry.org/docs/#installation 25 | 5. Run `poetry install` to install the project dependencies. 26 | 6. Set up your Anthropic API key as an environment variable named `ANTHROPIC_API_KEY`. You can use a `.env` file for this purpose. 27 | 28 | ## Code Repository Structure 29 | The AI Docs repository has the following structure: 30 | 31 | - `pyproject.toml`: The Poetry configuration file that defines the project's dependencies and metadata. 32 | - `ai_docs/`: The main package directory containing the Python modules. 33 | - `api.py`: Contains the core functionality for interacting with the Anthropic API. 34 | - `extract_repo.py`: Handles the extraction of code files from a local repository. 35 | - `generate_docs.py`: Provides a high-level function to generate documentation for a given repository. 36 | 37 | ## Key Points of Complexity 38 | 1. Token Management: 39 | - The `check_prompt_token_size` function in `api.py` uses the GPT-2 tokenizer to estimate the number of tokens in a prompt. This is important to ensure that the prompt does not exceed the maximum token limit of the Claude model. 40 | - Handling token limits and efficiently constructing prompts is crucial for effectively utilizing the AI model. 41 | 42 | 2. Extracting Relevant Code Files: 43 | - The `extract_repo.py` module contains functions to determine which files in a repository are relevant for documentation generation. 44 | - It filters out unnecessary files and directories based on predefined criteria, such as file extensions, directory names, and file contents. 45 | - Extracting only the relevant code files helps reduce noise and focuses the documentation on the core aspects of the project. 46 | 47 | ## Installation and Setup 48 | To install and set up AI Docs, follow these steps: 49 | 50 | 1. Clone the AI Docs repository from the version control system. 51 | 2. Navigate to the project directory. 52 | 3. Ensure you have Python 3.9 or higher installed on your system. 53 | 4. Install Poetry by following the official installation guide: https://python-poetry.org/docs/#installation 54 | 5. Run `poetry install` to install the project dependencies. 55 | 6. Set up your Anthropic API key as an environment variable named `ANTHROPIC_API_KEY`. You can use a `.env` file for this purpose. 56 | 57 | ## Getting Started 58 | To generate documentation for a code repository using AI Docs, follow these steps: 59 | 60 | 1. Ensure you have completed the installation and setup process. 61 | 2. Open a terminal and navigate to the AI Docs project directory. 62 | 3. Run the following command, replacing `` with the path to your code repository: 63 | ``` 64 | python -m ai_docs.generate_docs 65 | ``` 66 | 4. The script will extract the relevant code files, send them to the Claude AI model for processing, and generate a `README.md` file inside the specified repository directory. 67 | 5. Review the generated documentation and make any necessary adjustments or additions. 68 | 69 | That's it! You have now generated technical documentation for your code repository using AI Docs. 70 | -------------------------------------------------------------------------------- /ai_docs/extract_repo.py: -------------------------------------------------------------------------------- 1 | import os 2 | import sys 3 | import ast 4 | import shutil 5 | 6 | 7 | def make_zip_file(directory_path: str, output_file_name: str) -> str: 8 | """Zip the given directory of a local repository""" 9 | shutil.make_archive(output_file_name, "zip", directory_path) 10 | return f"{output_file_name}.zip" 11 | 12 | 13 | def is_desired_file(file_path: str) -> bool: 14 | """Check if the file is a relevant coding file or a key project file.""" 15 | # Check for specific file types 16 | if file_path.endswith((".ts", ".tsx", ".prisma", ".py")): 17 | return True 18 | 19 | # Check for specific file names 20 | if os.path.basename(file_path) in ("package.json", "pyproject.toml"): 21 | return True 22 | 23 | return False 24 | 25 | 26 | def is_likely_useful_file(file_path: str) -> bool: 27 | """Determine if the file is likely to be useful by excluding certain directories and specific file types.""" 28 | excluded_dirs = [ 29 | "docs", 30 | "examples", 31 | "tests", 32 | "test", 33 | "__pycache__", 34 | "scripts", 35 | "benchmarks", 36 | "node_modules", 37 | ".venv", 38 | ] 39 | utility_or_config_files = ["hubconf.py", "setup.py", "package-lock.json"] 40 | github_workflow_or_docs = ["stale.py", "gen-card-", "write_model_card"] 41 | 42 | check_path = file_path.replace("\\", "/") 43 | parts = check_path.split(os.sep)[1:] 44 | if any(part.startswith(".") for part in parts): 45 | return False 46 | if "test" in check_path.lower(): 47 | return False 48 | for excluded_dir in excluded_dirs: 49 | if f"/{excluded_dir}/" in check_path or check_path.startswith( 50 | f"{excluded_dir}/" 51 | ): 52 | return False 53 | for file_name in utility_or_config_files: 54 | if file_name in check_path: 55 | return False 56 | if not all(doc_file not in check_path for doc_file in github_workflow_or_docs): 57 | return False 58 | 59 | return True 60 | 61 | 62 | def has_sufficient_content(file_content: list[str], min_line_count: int = 5) -> bool: 63 | """Check if the file has a minimum number of substantive lines.""" 64 | lines = [ 65 | line 66 | for line in file_content 67 | if line.strip() and not line.strip().startswith("//") 68 | ] 69 | return len(lines) >= min_line_count 70 | 71 | 72 | def remove_comments_and_docstrings(source): 73 | """Remove comments and docstrings from the Python source code.""" 74 | tree = ast.parse(source) 75 | for node in ast.walk(tree): 76 | if isinstance( 77 | node, (ast.FunctionDef, ast.ClassDef, ast.AsyncFunctionDef) 78 | ) and ast.get_docstring(node): 79 | node.body = node.body[1:] # Remove docstring 80 | elif isinstance(node, ast.Expr) and isinstance(node.value, ast.Str): 81 | node.value.s = "" # Remove comments 82 | return ast.unparse(tree) 83 | 84 | 85 | def extract_local_directory(directory_path: str) -> None: 86 | """Walks through a local directory and converts relevant code files to a .txt file""" 87 | repo_name = os.path.basename(directory_path) 88 | output_file = f"{repo_name}_code.txt" 89 | 90 | with open(output_file, "w", encoding="utf-8") as outfile: 91 | for root, _, files in os.walk(directory_path): 92 | for file in files: 93 | file_path = os.path.join(root, file) 94 | # Skip directories, non-code files, less likely useful files, hidden directories, and test files 95 | if ( 96 | file_path.endswith("/") 97 | or not is_desired_file(file_path) 98 | or not is_likely_useful_file(file_path) 99 | ): 100 | continue 101 | with open(file_path, "r", encoding="utf-8") as file_content: 102 | # Skip test files based on content and files with insufficient substantive content 103 | file_lines = file_content.readlines() 104 | if is_desired_file(file_path) and has_sufficient_content( 105 | file_lines 106 | ): 107 | outfile.write(f"# File: {file_path}\n") 108 | outfile.writelines(file_lines) 109 | outfile.write("\n\n") 110 | 111 | return output_file 112 | 113 | 114 | if __name__ == "__main__": 115 | if len(sys.argv) != 2: 116 | print("Usage: python extract_repo.py ") 117 | sys.exit(1) 118 | 119 | directory_path = sys.argv[1] 120 | extract_local_directory(directory_path) 121 | -------------------------------------------------------------------------------- /ai_docs/api.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import anthropic 3 | import os 4 | from dotenv import load_dotenv, find_dotenv 5 | from transformers import GPT2Tokenizer 6 | 7 | load_dotenv(find_dotenv()) 8 | 9 | ANTHROPIC_API_KEY = os.environ.get("ANTHROPIC_API_KEY") 10 | 11 | CLIENT = anthropic.Anthropic(api_key=ANTHROPIC_API_KEY) 12 | 13 | PULL_REQUEST_SYSTEM_PROMPT = """Your job is to act as a expert software engineer and provide outlined comprehensive feedback for merge requests in a appraochable and understanding way. 14 | Key criteria outlined are: 15 | Does this code change accomplish what it is supposed to do? 16 | Can this solution be simplified? 17 | Does this change add unwanted compile-time or run-time dependencies? 18 | Is a framework, API, library, or service used that should not be used? 19 | Could an additional framework, API, library, or service improve the solution? 20 | Is the code at the right abstraction level? 21 | Is the code modular enough? 22 | Can a better solution be found in terms of maintainability, readability, performance, or security? 23 | Does similar functionality already exist in the codebase? If yes, why isnt it reused? 24 | Are there any best practices, design patterns or language-specific patterns that could substantially improve this code? 25 | Does this code adhere to Object-Oriented Analysis and Design Principles, like the Single Responsibility Principle, Open-Close Principle, Liskov Substitution Principle, Interface Segregation, or Dependency Injection? 26 | Can you think of any use case in which the code does not behave as intended? 27 | Can you think of any inputs or external events that could break the code? 28 | You will receive both a description of the changes, an outline of the changes and the existing codebase. 29 | """ 30 | 31 | BASIC_DOCS_SYSTEM_PROMPT = """Your job is to act as the expert software engineer and provide detailed technical documentation broken into readbile formats. 32 | You will be able to read the majority of a code repository given as a converted single text with the Prefix "#File:" declaring the start of the new file e.g., # File: masters-and-sons-main/src/components/ArrowTable.tsx. 33 | Typescipt projects are required to use pnpm for commands, python project if they have a pyproject.toml will be using poetry. MySQL databases are typically planetscale, and in that case we follow planetscales recommended use of prisma (if prisms ORM is used). 34 | Documentation should be broken down into: 35 | Introduction: 36 | - Provide a brief overview of the project. 37 | - Mention the purpose and core functionality of the code repository. 38 | - Highlight the key features and potential use cases. 39 | Codebase Overview: 40 | - Provide an in-depth overview of the codebase architecture and design patterns used. 41 | - Detail the modules, components, and their interactions within the application. 42 | Development Environment Setup: 43 | - Step-by-step instructions for setting up the development environment, including necessary tools and dependencies. 44 | - Include guidelines for configuring IDEs, linters, and other development tools. 45 | Code Repository Structure: 46 | - Explain the repository structure, detailing the purpose of different directories and files. 47 | - Document naming conventions, file organization, and any specific standards followed in the codebase. 48 | Key Points of Complexity: 49 | - Outline each keypoint of complexity 50 | - Breakdown each keypoint 51 | Installation and Setup: 52 | - Offer detailed instructions on installing and setting up the project. 53 | - Include any prerequisites or dependencies required. 54 | Getting Started: 55 | - Guide users through a simple, initial setup or quick-start process. 56 | - Include basic examples or a simple tutorial to help users begin using the project quickly. 57 | The output should be detailed in standard markdown, using headers to improve readability. 58 | """ 59 | 60 | REFINED_DOCS_FOLLOW_UP_PROMPT = """You are instructed to further refine the documentation, there is no need to repeat basic content. Focus on delivering expert value insights for internal development handover outlined in the below criteria. 61 | In-Depth Architecture Overview: 62 | - Provide comprehensive diagrams and descriptions of the system architecture, including data flow, service interactions, and external dependencies. 63 | - Detail the critical architectural decisions and their justifications, discussing the trade-offs and alternatives considered. 64 | Advanced Codebase Insights: 65 | - Delve into complex modules and components, explaining intricate details that are crucial for understanding system behavior. 66 | - Document any non-obvious implementation strategies and optimizations, explaining why they were necessary and how they impact the system. 67 | Environment and Toolchain Deep Dive: 68 | - Offer a detailed guide on the development, testing, and production environments, including specific configurations, underlying infrastructure details, and environment parity practices. 69 | - Describe the complete toolchain, including build systems, deployment pipelines, and any custom tooling. 70 | Critical Dependency Analysis: 71 | - Provide an exhaustive overview of external libraries, frameworks, and services the system depends on, including versioning, patching strategies, and known issues. 72 | - Discuss how dependencies are managed, potential risks associated with them, and mitigation strategies. 73 | Performance Considerations: 74 | - Document performance benchmarks, profiling methods, and optimization strategies. 75 | - Include case studies of past performance issues, their analysis, and the solutions implemented. 76 | Security Protocols: 77 | - Detail the security measures and protocols in place, including authentication, authorization, data encryption, and any proprietary security frameworks or libraries. 78 | - Discuss security best practices, known vulnerabilities (and their mitigations), and any relevant security audits. 79 | Testing and Quality Assurance: 80 | - Elaborate on the testing strategy, including unit, integration, and end-to-end tests, highlighting any test-driven development (TDD) practices. 81 | - Document the approach to continuous integration/continuous deployment (CI/CD), test automation, and quality benchmarks. 82 | Troubleshooting and Debugging Guide: 83 | - Provide a detailed guide for troubleshooting common issues, including debugging tips, logging best practices, and monitoring tools used. 84 | - Share real-world incidents or outages, post-mortem analyses, and lessons learned. 85 | Data Management and Migration: 86 | - Explain the data architecture, schema design, and any data migration strategies or scripts. 87 | - Discuss backup strategies, data integrity checks, and disaster recovery plans. 88 | Developer Onboarding: 89 | - Create a comprehensive onboarding guide for new developers, including step-by-step setup instructions, key contacts, and resources for getting up to speed. 90 | - Include a glossary of terms, acronyms, and jargon used within the project to aid in understanding the documentation and codebase. 91 | """ 92 | 93 | 94 | def check_prompt_token_size(prompt: str) -> None: 95 | """Use GPT-2 to check the approximate number of tokens in a prompt""" 96 | tokenizer = GPT2Tokenizer.from_pretrained("gpt2") 97 | tokens = tokenizer.encode(prompt, add_special_tokens=False) 98 | # Token count 99 | return len(tokens) 100 | 101 | 102 | def request_message( 103 | system_prompt: str, messages: list[dict[str, str]] 104 | ) -> anthropic.types.Message: 105 | """Send message to Anthropic.""" 106 | response = CLIENT.messages.create( 107 | model="claude-3-opus-20240229", 108 | system=system_prompt, 109 | max_tokens=4096, 110 | messages=messages, 111 | ) 112 | 113 | return response 114 | 115 | 116 | def read_file(file_path): 117 | """Read the text file containing the repo content.""" 118 | # read txt file 119 | if os.path.exists(file_path): 120 | with open(file_path, "r", encoding="utf-8") as file: 121 | repo_content = file.read() 122 | else: 123 | print("Error: The file does not exist.") 124 | 125 | return repo_content 126 | 127 | 128 | def _generate_docs(file_path): 129 | """Generate docs for the provided repo using Claude Opus.""" 130 | repo_name = str(os.path.splitext(os.path.basename(file_path))[0]).replace( 131 | "_code", "" 132 | ) 133 | file_content = read_file(file_path) 134 | input_prompt = f"Given this repo. \n{file_content}\ncomplete your instruction" 135 | token_size = check_prompt_token_size(input_prompt) 136 | 137 | proceed_check = input( 138 | f"Input token size is: {token_size}. Do you wish to proceed? (Y/N)" 139 | ) 140 | if str(proceed_check).upper() != "Y": 141 | print("Exiting") 142 | sys.exit(1) 143 | 144 | messages = [ 145 | {"role": "user", "content": input_prompt}, 146 | ] 147 | response = request_message(BASIC_DOCS_SYSTEM_PROMPT, messages) 148 | 149 | message = response.content[0].text 150 | with open(f"{repo_name}-docs.md", "w", encoding="utf-8") as file: 151 | file.write(message) 152 | 153 | 154 | if __name__ == "__main__": 155 | if len(sys.argv) != 2: 156 | print("Usage: python api.py ") 157 | sys.exit(1) 158 | 159 | _generate_docs(sys.argv[1]) 160 | -------------------------------------------------------------------------------- /poetry.lock: -------------------------------------------------------------------------------- 1 | # This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 2 | 3 | [[package]] 4 | name = "annotated-types" 5 | version = "0.6.0" 6 | description = "Reusable constraint types to use with typing.Annotated" 7 | optional = false 8 | python-versions = ">=3.8" 9 | files = [ 10 | {file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"}, 11 | {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"}, 12 | ] 13 | 14 | [[package]] 15 | name = "anthropic" 16 | version = "0.21.3" 17 | description = "The official Python library for the anthropic API" 18 | optional = false 19 | python-versions = ">=3.7" 20 | files = [ 21 | {file = "anthropic-0.21.3-py3-none-any.whl", hash = "sha256:5869115453b543a46ded6515c9f29b8d610b6e94bbba3230ad80ac947d2b0862"}, 22 | {file = "anthropic-0.21.3.tar.gz", hash = "sha256:02f1ab5694c497e2b2d42d30d51a4f2edcaca92d2ec86bb64fe78a9c7434a869"}, 23 | ] 24 | 25 | [package.dependencies] 26 | anyio = ">=3.5.0,<5" 27 | distro = ">=1.7.0,<2" 28 | httpx = ">=0.23.0,<1" 29 | pydantic = ">=1.9.0,<3" 30 | sniffio = "*" 31 | tokenizers = ">=0.13.0" 32 | typing-extensions = ">=4.7,<5" 33 | 34 | [package.extras] 35 | bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"] 36 | vertex = ["google-auth (>=2,<3)"] 37 | 38 | [[package]] 39 | name = "anyio" 40 | version = "4.3.0" 41 | description = "High level compatibility layer for multiple asynchronous event loop implementations" 42 | optional = false 43 | python-versions = ">=3.8" 44 | files = [ 45 | {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"}, 46 | {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"}, 47 | ] 48 | 49 | [package.dependencies] 50 | exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""} 51 | idna = ">=2.8" 52 | sniffio = ">=1.1" 53 | typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""} 54 | 55 | [package.extras] 56 | doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"] 57 | test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"] 58 | trio = ["trio (>=0.23)"] 59 | 60 | [[package]] 61 | name = "certifi" 62 | version = "2024.2.2" 63 | description = "Python package for providing Mozilla's CA Bundle." 64 | optional = false 65 | python-versions = ">=3.6" 66 | files = [ 67 | {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"}, 68 | {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"}, 69 | ] 70 | 71 | [[package]] 72 | name = "charset-normalizer" 73 | version = "3.3.2" 74 | description = "The Real First Universal Charset Detector. 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