# LLM Blocks ๐ค


LLM Blocks is a Python library that provides a flexible and easy-to-use interface for interacting with OpenAI's GPT models. It provides a set of classes and methods to handle different types of interactions with the model, such as chat, template, and streamed responses.
## ๐ Table of Contents
- [Why Use LLM Blocks](#why-use-llm-blocks)
- [Repo Structure](#repo-structure)
- [Installation](#installation)
- [Usage](#usage)
- [Testing](#testing)
- [Contributing](#contributing)
## ๐ Why Use LLM Blocks
LLM Blocks simplifies the process of interacting with OpenAI's GPT models. It provides a set of classes and methods that abstract away the complexity of the underlying API calls, allowing you to focus on what matters most - building your application. Whether you're building a chatbot, a code generator, or any other application that leverages AI, LLM Blocks can help you get there faster.
## ๐ Repo Structure
```
llm_blocks
โโโ blocks.py
โโโ block_factory.py
โโโ __init__.py
โโโ requirements.dev.txt
tests
โโโ test_blocks.py
```
## ๐ป Installation
To install LLM Blocks, you can use pip:
```bash
pip install llm_blocks
```
## ๐ฏ Usage
Here's a simple example of how to use LLM Blocks:
```python
from llm_blocks import block_factory
# Create a block
block = block_factory.get('block')
# Execute the block with some content
response = block.execute("Hello, world!")
# or execute like a function
response = block("Hello, world!")
# Print the response
print(response)
```
## ๐งช Testing
To run the tests, navigate to the root directory of the project and run:
```bash
python -m unittest discover tests
```
## ๐ค Contributing
Contributions are welcome! Please read our [contributing guidelines](CONTRIBUTING.md) to get started.
## ๐ License
This project is licensed under the terms of the MIT license. See the [LICENSE](LICENSE.md) file for details.
## ๐ง Contact
If you have any questions, feel free to reach out to us at [contact@llmblocks.com](mailto:contact@llmblocks.com).
Raw data
{
"_id": null,
"home_page": "https://github.com/voynow/llm-blocks",
"name": "llm-blocks",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.6",
"maintainer_email": "",
"keywords": "",
"author": "Jamie Voynow",
"author_email": "voynow99@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/e6/d6/7ea8849ebbf74431ed67f5a32ca28396d4b6e193a22d4090d1edf7df0b46/llm-blocks-0.3.7.tar.gz",
"platform": null,
"description": "# LLM Blocks \ud83e\udd16\r\n\r\n\r\n\r\n\r\nLLM Blocks is a Python library that provides a flexible and easy-to-use interface for interacting with OpenAI's GPT models. It provides a set of classes and methods to handle different types of interactions with the model, such as chat, template, and streamed responses.\r\n\r\n## \ud83d\udcda Table of Contents\r\n- [Why Use LLM Blocks](#why-use-llm-blocks)\r\n- [Repo Structure](#repo-structure)\r\n- [Installation](#installation)\r\n- [Usage](#usage)\r\n- [Testing](#testing)\r\n- [Contributing](#contributing)\r\n\r\n## \ud83d\ude80 Why Use LLM Blocks\r\nLLM Blocks simplifies the process of interacting with OpenAI's GPT models. It provides a set of classes and methods that abstract away the complexity of the underlying API calls, allowing you to focus on what matters most - building your application. Whether you're building a chatbot, a code generator, or any other application that leverages AI, LLM Blocks can help you get there faster.\r\n\r\n## \ud83d\udcc2 Repo Structure\r\n```\r\nllm_blocks\r\n\u251c\u2500\u2500 blocks.py\r\n\u251c\u2500\u2500 block_factory.py\r\n\u251c\u2500\u2500 __init__.py\r\n\u251c\u2500\u2500 requirements.dev.txt\r\ntests\r\n\u2514\u2500\u2500 test_blocks.py\r\n```\r\n\r\n## \ud83d\udcbb Installation\r\nTo install LLM Blocks, you can use pip:\r\n```bash\r\npip install llm_blocks\r\n```\r\n\r\n## \ud83c\udfaf Usage\r\nHere's a simple example of how to use LLM Blocks:\r\n\r\n```python\r\nfrom llm_blocks import block_factory\r\n\r\n# Create a block\r\nblock = block_factory.get('block')\r\n\r\n# Execute the block with some content\r\nresponse = block.execute(\"Hello, world!\")\r\n# or execute like a function\r\nresponse = block(\"Hello, world!\")\r\n\r\n# Print the response\r\nprint(response)\r\n```\r\n\r\n## \ud83e\uddea Testing\r\nTo run the tests, navigate to the root directory of the project and run:\r\n\r\n```bash\r\npython -m unittest discover tests\r\n```\r\n\r\n## \ud83e\udd1d Contributing\r\nContributions are welcome! Please read our [contributing guidelines](CONTRIBUTING.md) to get started.\r\n\r\n## \ud83d\udcdd License\r\nThis project is licensed under the terms of the MIT license. See the [LICENSE](LICENSE.md) file for details.\r\n\r\n## \ud83d\udce7 Contact\r\nIf you have any questions, feel free to reach out to us at [contact@llmblocks.com](mailto:contact@llmblocks.com).\r\n",
"bugtrack_url": null,
"license": "",
"summary": "Simple interface for creating and managing LLM chains",
"version": "0.3.7",
"project_urls": {
"Homepage": "https://github.com/voynow/llm-blocks"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "43414b0f6faa7c990def206eb08562a8e25c503390245c3ae41d36f81edcd111",
"md5": "4a5163eb7d8cd3a849678c11920c34a0",
"sha256": "023a21ff6a2109d2b055ff0105908c3d5a4285c6d8b4e2f4a50ad18e4b28f988"
},
"downloads": -1,
"filename": "llm_blocks-0.3.7-py3-none-any.whl",
"has_sig": false,
"md5_digest": "4a5163eb7d8cd3a849678c11920c34a0",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.6",
"size": 5464,
"upload_time": "2023-09-10T13:49:01",
"upload_time_iso_8601": "2023-09-10T13:49:01.552570Z",
"url": "https://files.pythonhosted.org/packages/43/41/4b0f6faa7c990def206eb08562a8e25c503390245c3ae41d36f81edcd111/llm_blocks-0.3.7-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "e6d67ea8849ebbf74431ed67f5a32ca28396d4b6e193a22d4090d1edf7df0b46",
"md5": "381b7f4bd76f2e0144f75c74f0634d2e",
"sha256": "61c060af8b51fa45ea8b7ed8b373449712cce55fb7e347bd7a69f4443c96d0da"
},
"downloads": -1,
"filename": "llm-blocks-0.3.7.tar.gz",
"has_sig": false,
"md5_digest": "381b7f4bd76f2e0144f75c74f0634d2e",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.6",
"size": 4455,
"upload_time": "2023-09-10T13:49:03",
"upload_time_iso_8601": "2023-09-10T13:49:03.234259Z",
"url": "https://files.pythonhosted.org/packages/e6/d6/7ea8849ebbf74431ed67f5a32ca28396d4b6e193a22d4090d1edf7df0b46/llm-blocks-0.3.7.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-09-10 13:49:03",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "voynow",
"github_project": "llm-blocks",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"requirements": [],
"lcname": "llm-blocks"
}