intelisys

Name	intelisys JSON
Version	0.5.6 JSON
	download
home_page	https://github.com/lifsys/intelisys
Summary	Intelligence/AI services for the Lifsys Enterprise with enhanced max_history_words, efficient history trimming, and improved document processing
upload_time	2024-08-27 22:53:42
maintainer	None
docs_url	None
author	Lifsys Enterprise
requires_python	>=3.7
license	MIT License Copyright (c) 2024 Lifsys Enterprise 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.
keywords	ai intelligence openai anthropic google groq openrouter document processing
VCS
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            # Intelisys: Your Advanced AI Assistant Library

Welcome to Intelisys, a powerful and versatile AI assistant library that provides a unified interface for interacting with various AI models and providers. Intelisys is designed to make AI integration seamless and efficient for developers of all levels.

## What's New in Version 0.5.6

- Enhanced `max_history_words` functionality for improved conversation management
- Optimized history trimming for efficient memory usage
- Improved asynchronous support with better error handling
- Added support for structured output with OpenAI provider using Pydantic models
- Expanded reference capabilities, now supporting various document types (PDF, Word, Excel, PowerPoint)
- Improved performance for long-running conversations

## Key Features

- Multi-provider support (OpenAI, Anthropic, OpenRouter, Groq)
- Asynchronous operations for improved performance
- Template-based chat for easy customization
- Structured output support using Pydantic models (OpenAI only)
- Image processing capabilities
- Efficient conversation history management
- Reference information support from various sources

## Installation

Install Intelisys using pip:

```bash
pip install intelisys
```

## Quick Start

Here's a simple example to get you started:

```python
from intelisys import Intelisys

# Create an Intelisys instance
ai = Intelisys(provider="openai", model="gpt-4")

# Chat with the AI
response = ai.chat("What is the capital of France?")
print(response)
```

## Advanced Usage

### Template-Based Chat

Use templates for more structured interactions:

```python
ai = Intelisys(provider="anthropic", model="claude-3-5-sonnet-20240620")
ai.set_default_template("Explain {{topic}} in simple terms.")
response = ai.template_chat(render_data={"topic": "quantum computing"})
print(response)
```

### Asynchronous Operations

Perform asynchronous chats for improved efficiency:

```python
import asyncio

async def async_chat():
    ai = Intelisys(provider="openai", model="gpt-4", use_async=True)
    response = await ai.chat_async("Discuss the future of AI")
    print(response)

asyncio.run(async_chat())
```

### Structured Output

Get structured responses using Pydantic models (OpenAI only):

```python
from pydantic import BaseModel

class MovieReview(BaseModel):
    title: str
    rating: float
    summary: str

ai = Intelisys(provider="openai", model="gpt-4")
ai.set_output_model(MovieReview)
result = ai.chat("Review the movie 'Inception'")
print(result)  # This will be a MovieReview instance
```

### Reference Information

Provide context to your AI assistant:

```python
ai = Intelisys(provider="openai", model="gpt-4")
ai.reference("https://example.com/article.html")
ai.reference("/path/to/local/document.pdf")
response = ai.chat("Summarize the referenced information")
print(response)
```

## API Reference

For a complete API reference, please refer to our [documentation](https://intelisys.readthedocs.io/).

## Contributing

We welcome contributions to Intelisys! Please see our [Contributing Guidelines](CONTRIBUTING.md) for more details.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Changelog

For a detailed list of changes and version history, please refer to the [CHANGELOG.md](CHANGELOG.md) file.

            

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    "description": "# Intelisys: Your Advanced AI Assistant Library\n\nWelcome to Intelisys, a powerful and versatile AI assistant library that provides a unified interface for interacting with various AI models and providers. Intelisys is designed to make AI integration seamless and efficient for developers of all levels.\n\n## What's New in Version 0.5.6\n\n- Enhanced `max_history_words` functionality for improved conversation management\n- Optimized history trimming for efficient memory usage\n- Improved asynchronous support with better error handling\n- Added support for structured output with OpenAI provider using Pydantic models\n- Expanded reference capabilities, now supporting various document types (PDF, Word, Excel, PowerPoint)\n- Improved performance for long-running conversations\n\n## Key Features\n\n- Multi-provider support (OpenAI, Anthropic, OpenRouter, Groq)\n- Asynchronous operations for improved performance\n- Template-based chat for easy customization\n- Structured output support using Pydantic models (OpenAI only)\n- Image processing capabilities\n- Efficient conversation history management\n- Reference information support from various sources\n\n## Installation\n\nInstall Intelisys using pip:\n\n```bash\npip install intelisys\n```\n\n## Quick Start\n\nHere's a simple example to get you started:\n\n```python\nfrom intelisys import Intelisys\n\n# Create an Intelisys instance\nai = Intelisys(provider=\"openai\", model=\"gpt-4\")\n\n# Chat with the AI\nresponse = ai.chat(\"What is the capital of France?\")\nprint(response)\n```\n\n## Advanced Usage\n\n### Template-Based Chat\n\nUse templates for more structured interactions:\n\n```python\nai = Intelisys(provider=\"anthropic\", model=\"claude-3-5-sonnet-20240620\")\nai.set_default_template(\"Explain {{topic}} in simple terms.\")\nresponse = ai.template_chat(render_data={\"topic\": \"quantum computing\"})\nprint(response)\n```\n\n### Asynchronous Operations\n\nPerform asynchronous chats for improved efficiency:\n\n```python\nimport asyncio\n\nasync def async_chat():\n    ai = Intelisys(provider=\"openai\", model=\"gpt-4\", use_async=True)\n    response = await ai.chat_async(\"Discuss the future of AI\")\n    print(response)\n\nasyncio.run(async_chat())\n```\n\n### Structured Output\n\nGet structured responses using Pydantic models (OpenAI only):\n\n```python\nfrom pydantic import BaseModel\n\nclass MovieReview(BaseModel):\n    title: str\n    rating: float\n    summary: str\n\nai = Intelisys(provider=\"openai\", model=\"gpt-4\")\nai.set_output_model(MovieReview)\nresult = ai.chat(\"Review the movie 'Inception'\")\nprint(result)  # This will be a MovieReview instance\n```\n\n### Reference Information\n\nProvide context to your AI assistant:\n\n```python\nai = Intelisys(provider=\"openai\", model=\"gpt-4\")\nai.reference(\"https://example.com/article.html\")\nai.reference(\"/path/to/local/document.pdf\")\nresponse = ai.chat(\"Summarize the referenced information\")\nprint(response)\n```\n\n## API Reference\n\nFor a complete API reference, please refer to our [documentation](https://intelisys.readthedocs.io/).\n\n## Contributing\n\nWe welcome contributions to Intelisys! Please see our [Contributing Guidelines](CONTRIBUTING.md) for more details.\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## Changelog\n\nFor a detailed list of changes and version history, please refer to the [CHANGELOG.md](CHANGELOG.md) file.\n",
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