base on 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. <p align="center"> <picture> <source media="(prefers-color-scheme: dark)" srcset="docs/logo/dark.png" /> <source media="(prefers-color-scheme: light)" srcset="docs/logo/light.png" /> <img alt="PraisonAI Logo" src="docs/logo/light.png" /> </picture> </p> <p align="center"> <a href="https://github.com/MervinPraison/PraisonAI"><img src="https://static.pepy.tech/badge/PraisonAI" alt="Total Downloads" /></a> <a href="https://github.com/MervinPraison/PraisonAI"><img src="https://img.shields.io/github/v/release/MervinPraison/PraisonAI" alt="Latest Stable Version" /></a> <a href="https://github.com/MervinPraison/PraisonAI"><img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License" /></a> </p> <div align="center"> # Praison AI <a href="https://trendshift.io/repositories/9130" target="_blank"><img src="https://trendshift.io/api/badge/repositories/9130" alt="MervinPraison%2FPraisonAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a> </div> 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. <div align="center"> <picture> <source media="(prefers-color-scheme: dark)" srcset="docs/images/architecture-dark.png" /> <source media="(prefers-color-scheme: light)" srcset="docs/images/architecture-light.png" /> <img alt="PraisonAI Architecture" src="docs/images/architecture-light.png" /> </picture> </div> ## 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) | | **Realtime** | Real-time voice interaction with AI | [https://docs.praison.ai/ui/realtime](https://docs.praison.ai/ui/realtime) | | 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 | <a target="_blank" href="https://colab.research.google.com/github/MervinPraison/PraisonAI/blob/main/cookbooks/praisonai-googlecolab.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" /></a> | | Include Tools | PraisonAI Tools | <a target="_blank" href="https://colab.research.google.com/github/MervinPraison/PraisonAI/blob/main/cookbooks/praisonai-tools-googlecolab.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" /></a> | ## Installation Options ### Using pip ```bash pip install praisonai ``` ### Framework-specific Installation ```bash # Install with CrewAI support pip install "praisonai[crewai]" # Install with AutoGen support pip install "praisonai[autogen]" # Install with both frameworks pip install "praisonai[crewai,autogen]" ``` ### UI and Additional Features ```bash # Install UI support pip install "praisonai[ui]" # Install Chat interface pip install "praisonai[chat]" # Install Code interface pip install "praisonai[code]" # Install Realtime voice interaction pip install "praisonai[realtime]" # Install Call feature pip install "praisonai[call]" ``` ## Quick Start ```bash # Set your OpenAI API key export OPENAI_API_KEY="Enter your API key" # Initialize with CrewAI (default) praisonai --init "create a movie script about dog in moon" # Or initialize with AutoGen praisonai --framework autogen --init "create a movie script about dog in moon" # Run the agents praisonai ``` ## Full Automatic Mode ```bash # With CrewAI (default) praisonai --auto "create a movie script about Dog in Moon" # With AutoGen praisonai --framework autogen --auto "create a movie script about Dog in Moon" ``` ## Framework-specific Features ### CrewAI When installing with `pip install "praisonai[crewai]"`, you get: - CrewAI framework support - PraisonAI tools integration - Task delegation capabilities - Sequential and parallel task execution ### AutoGen When installing with `pip install "praisonai[autogen]"`, you get: - AutoGen framework support - PraisonAI tools integration - Multi-agent conversation capabilities - Code execution environment ## 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 - 🎙️ Real-time Voice Interaction ## 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. ### Using uv (Fast Python Package Installer) ```bash # Install uv if you haven't already pip install uv # Install from requirements uv pip install -r pyproject.toml # Install with extras uv pip install -r pyproject.toml --extra code uv pip install -r pyproject.toml --extra "crewai,autogen" ``` ## 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 [](https://docs.praison.ai) ## License Praison AI is an open-sourced software licensed under the **[MIT license](https://opensource.org/licenses/MIT)**. ## Video Tutorials | Topic | Video | |-------|--------| | Introduction | [](https://www.youtube.com/watch?v=Fn1lQjC0GO0) | | Tools Overview | [](https://www.youtube.com/watch?v=XaQRgRpV7jo) | | Custom Tools | [](https://www.youtube.com/watch?v=JSU2Rndh06c) | | Firecrawl Integration | [](https://www.youtube.com/watch?v=UoqUDcLcOYo) | | User Interface | [](https://www.youtube.com/watch?v=tg-ZjNl3OCg) | | Crawl4AI Integration | [](https://www.youtube.com/watch?v=KAvuVUh0XU8) | | Chat Interface | [](https://www.youtube.com/watch?v=sw3uDqn2h1Y) | | Code Interface | [](https://www.youtube.com/watch?v=_5jQayO-MQY) | | Mem0 Integration | [](https://www.youtube.com/watch?v=KIGSgRxf1cY) | | Training | [](https://www.youtube.com/watch?v=aLawE8kwCrI) | | Realtime Voice Interface | [](https://www.youtube.com/watch?v=frRHfevTCSw) | | Call Interface | [](https://www.youtube.com/watch?v=m1cwrUG2iAk) | ## License Praison AI is an open-sourced software licensed under the **[MIT license](https://opensource.org/licenses/MIT)**. ", Assign "at most 3 tags" to the expected json: {"id":"9130","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"