PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration. Chat with your ENTIRE Codebase.
Praison AI, leveraging both AutoGen and CrewAI or any other agent framework, represents a low-code, centralised framework designed to simplify the creation and orchestration of multi-agent systems for various LLM applications, emphasizing ease of use, customization, and human-agent interaction.
## Different User Interfaces:
| Interface | Description | URL |
|---|---|---|
| **UI** | Multi Agents such as CrewAI or AutoGen | [https://docs.praison.ai/ui/ui](https://docs.praison.ai/ui/ui) |
| **Chat** | Chat with 100+ LLMs, single AI Agent | [https://docs.praison.ai/ui/chat](https://docs.praison.ai/ui/chat) |
| **Code** | Chat with entire Codebase, single AI Agent | [https://docs.praison.ai/ui/code](https://docs.praison.ai/ui/code) |
| Other Features | Description | Docs |
|---|---|---|
| **Train** | Fine-tune LLMs using your custom data | [https://docs.praison.ai/train](https://docs.praison.ai/train) |
## Google Colab Multi Agents
| | Cookbook | Open in Colab |
| ------------- | --------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Basic | PraisonAI | |
| Include Tools | PraisonAI Tools | |
## Install
| | Installation |
|---|---|
| **PraisonAI** | `pip install praisonai` |
| **PraisonAI Code** | `pip install "praisonai[code]"` |
| **PraisonAI Chat** | `pip install "praisonai[chat]"` |
| **PraisonAI Train** | `pip install "praisonai[train]"` |
## Key Features
- Automated AI Agents Creation
- Use CrewAI or AutoGen Framework
- 100+ LLM Support
- Chat with ENTIRE Codebase
- Interactive UIs
- YAML-based Configuration
- Custom Tool Integration
- Internet Search Capability (using Crawl4AI and Tavily)
- Vision Language Model (VLM) Support
## TL;DR Multi Agents
```bash
pip install praisonai
export OPENAI_API_KEY="Enter your API key"
praisonai --init create a movie script about dog in moon
praisonai
```
## Table of Contents
- [Installation](#installation)
- [Initialise](#initialise)
- [Run](#run)
- [Full Automatic Mode](#full-automatic-mode)
- [User Interface](#user-interface)
- [Praison AI Chat](#praison-ai-chat)
- [Create Custom Tools](#create-custom-tools)
- [Agents Playbook](#agents-playbook)
- [Include praisonai package in your project](#include-praisonai-package-in-your-project)
- [Commands to Install Dev Dependencies](#commands-to-install-dependencies)
- [Other Models](#other-models)
- [Contributing](#contributing)
- [Star History](#star-history)
## Installation Multi Agents
```bash
pip install praisonai
```
## Initialise
```bash
export OPENAI_API_KEY="Enter your API key"
```
Generate your OPENAI API KEY from here: https://platform.openai.com/api-keys
Note: You can use other providers such as Ollama, Mistral ... etc. Details are provided at the bottom.
```bash
praisonai --init create a movie script about dog in moon
```
This will automatically create agents.yaml file in the current directory.
### To initialise with a specific agent framework (Optional):
```bash
praisonai --framework autogen --init create movie script about cat in mars
```
## Run
```bash
praisonai
```
or
```bash
python -m praisonai
```
### Specify the agent framework (Optional):
```bash
praisonai --framework autogen
```
### Full Automatic Mode
```bash
praisonai --auto create a movie script about Dog in Moon
```
## User Interface
## PraisonAI User Interfaces:
| Interface | Description | URL |
| --------- | ------------------------------------------ | --------------------------------------------------------------------- |
| **UI** | Multi Agents such as CrewAI or AutoGen | [https://docs.praisonai.com/ui/ui](https://docs.praison.ai/ui/ui) |
| **Chat** | Chat with 100+ LLMs, single AI Agent | [https://docs.praisonai.com/ui/chat](https://docs.praison.ai/ui/chat) |
| **Code** | Chat with entire Codebase, single AI Agent | [https://docs.praisonai.com/ui/code](https://docs.praison.ai/ui/code) |
```bash
pip install -U "praisonai[ui]"
export OPENAI_API_KEY="Enter your API key"
chainlit create-secret
export CHAINLIT_AUTH_SECRET=xxxxxxxx
praisonai ui
```
or
```
python -m praisonai ui
```
## Praison AI Chat
- https://docs.praison.ai/chat/
```bash
pip install "praisonai[chat]"
export OPENAI_API_KEY="Enter your API key"
praisonai chat
```
### Internet Search
Praison AI Chat and Praison AI Code now includes internet search capabilities using Crawl4AI and Tavily, allowing you to retrieve up-to-date information during your conversations.
### Vision Language Model Support
You can now upload images and ask questions based on them using Vision Language Models. This feature enables visual understanding and analysis within your chat sessions.
## Praison AI Code
```bash
pip install "praisonai[code]"
export OPENAI_API_KEY="Enter your API key"
praisonai code
```
### Internet Search
Praison AI Code also includes internet search functionality, enabling you to find relevant code snippets and programming information online.
## Create Custom Tools
- https://docs.praison.ai/tools/custom/
## Agents Playbook
### Simple Playbook Example
```yaml
framework: crewai
topic: Artificial Intelligence
roles:
screenwriter:
backstory: "Skilled in crafting scripts with engaging dialogue about {topic}."
goal: Create scripts from concepts.
role: Screenwriter
tasks:
scriptwriting_task:
description: "Develop scripts with compelling characters and dialogue about {topic}."
expected_output: "Complete script ready for production."
```
## Use 100+ Models
- https://docs.praison.ai/models/
## Include praisonai package in your project
- https://docs.praison.ai/developers/wrapper
- https://docs.praison.ai/developers/wrapper-tools/
## Option 1: Using RAW YAML
```python
from praisonai import PraisonAI
# Example agent_yaml content
agent_yaml = """
framework: "crewai"
topic: "Space Exploration"
roles:
astronomer:
role: "Space Researcher"
goal: "Discover new insights about {topic}"
backstory: "You are a curious and dedicated astronomer with a passion for unraveling the mysteries of the cosmos."
tasks:
investigate_exoplanets:
description: "Research and compile information about exoplanets discovered in the last decade."
expected_output: "A summarized report on exoplanet discoveries, including their size, potential habitability, and distance from Earth."
"""
# Create a PraisonAI instance with the agent_yaml content
praisonai = PraisonAI(agent_yaml=agent_yaml)
# Run PraisonAI
result = praisonai.run()
# Print the result
print(result)
```
## Option 2: Using separate agents.yaml file
Note: Please create agents.yaml file before hand.
```python
from praisonai import PraisonAI
def basic(): # Basic Mode
praisonai = PraisonAI(agent_file="agents.yaml")
praisonai.run()
if __name__ == "__main__":
basic()
```
## Commands to Install Dependencies:
1. **Install all dependencies, including dev dependencies:**
```sh
poetry install
```
2. **Install only documentation dependencies:**
```sh
poetry install --with docs
```
3. **Install only test dependencies:**
```sh
poetry install --with test
```
4. **Install only dev dependencies:**
```sh
poetry install --with dev
```
This configuration ensures that your development dependencies are correctly categorized and installed as needed.
## Contributing
- Fork on GitHub: Use the "Fork" button on the repository page.
- Clone your fork: `git clone https://github.com/yourusername/praisonAI.git`
- Create a branch: `git checkout -b new-feature`
- Make changes and commit: `git commit -am "Add some feature"`
- Push to your fork: `git push origin new-feature`
- Submit a pull request via GitHub's web interface.
- Await feedback from project maintainers.
## Star History
[![Star History Chart](https://api.star-history.com/svg?repos=MervinPraison/PraisonAI&type=Date)](https://docs.praison.ai)
## License
Praison AI is an open-sourced software licensed under the **[MIT license](https://opensource.org/licenses/MIT)**.