AutoGen Oracle-AI-powered multi-agent framework
Automate tasks with AI agents
Show me a coding example for setting up AutoGen.
How do I use AutoGen for multi-agent chats?
Provide a coding example for AutoGen's enhanced inference.
Illustrate AutoGen's agent collaboration with a code snippet.
Related Tools
Load More
AutoExpert (Dev)
AutoExpert v6 (GPT Developer Edition) is your steadfast pair programmer, armed with enhanced code generation ability, online access for the latest APIs, and custom commands to save your session state so you can recall it in a new session later. /help will
SQL Generator
Advanced SQL assistant and query generator. Write clean SQL queries and become a much faster developer.
AutoGen Builder 🧠 v0.2.4
I will transform your ideas into as may agents as required
Oracle SQL
Your personal Oracle SQL assistant and query generator
AutoGen Engineer
Expert in AutoGen app creation, with full GitHub repo access
Oracle PLSQL Copilot
Skilled in Oracle PL/SQL with a focus on database design and query optimization.
20.0 / 5 (200 votes)
Introduction to AutoGen Oracle
AutoGen Oracle is a framework designed to enable the development of advanced applications using large language models (LLMs) through a multi-agent conversation system. The primary purpose of AutoGen Oracle is to facilitate seamless interaction among various agents, which can be configured to include LLMs, human inputs, and tools, to solve complex tasks autonomously or with human feedback. An example scenario illustrating its use is a project where agents collaborate to code, debug, and execute software tasks, leveraging the strengths of LLMs to handle complex workflows with minimal human intervention【22†source】【23†source】.
Main Functions of AutoGen Oracle
Multi-Agent Conversation Framework
ExampleA user creates an AssistantAgent and a UserProxyAgent to automate the process of generating and executing code for stock market analysis.
ScenarioIn this scenario, the UserProxyAgent initiates a chat with the AssistantAgent, requesting the generation of a Python script to plot stock price changes. The AssistantAgent generates the code, the UserProxyAgent executes it, and they collaboratively produce the desired output【23†source】【26†source】.
Enhanced LLM Inference
ExampleOptimizing text generation parameters for coding tasks using the EcoOptiGen technique.
ScenarioA developer aims to improve the performance of an LLM for code generation under budget constraints. By tuning hyperparameters such as model type, token limits, and temperature, the developer can maximize utility while controlling costs, achieving more efficient and accurate code outputs【20†source】【30†source】.
Conversable and Customizable Agents
ExampleCreating agents for playing a chess game while engaging in natural language conversation.
ScenarioTwo agents, a BoardAgent and a ChessPlayerAgent, are configured to play a chess game. The ChessPlayerAgent not only makes moves but also engages in casual conversation, enhancing the interactive experience. This demonstrates the agents' ability to perform complex tasks and maintain human-like interactions simultaneously【28†source】【29†source】.
Ideal Users of AutoGen Oracle
Developers and Engineers
Developers and engineers who build and optimize LLM applications benefit from AutoGen Oracle by leveraging its multi-agent framework to automate complex workflows, perform enhanced LLM inference, and integrate diverse tools and human inputs seamlessly. This allows them to focus on higher-level problem-solving and innovation.
Research and Academia
Researchers and academic institutions can use AutoGen Oracle to explore new paradigms in multi-agent systems, human-AI collaboration, and advanced language model applications. The framework supports experimental setups for studying dynamic conversations, error handling, and performance tuning, making it a valuable tool for scientific exploration and educational purposes.
Using AutoGen Oracle
Step 1
Visit aichatonline.org for a free trial without login, also no need for ChatGPT Plus.
Step 2
Set up your environment. AutoGen requires Python>=3.8 and can be installed via pip. Using a virtual environment (venv or conda) is recommended to avoid dependency conflicts.
Step 3
Configure your LLM endpoints. Use `config_list_from_json` to load your API configurations. This supports multiple models and API types including OpenAI and Azure.
Step 4
Define your agents. Create instances of `AssistantAgent` and `UserProxyAgent` to enable multi-agent conversations. Customize these agents according to your task requirements.
Step 5
Initiate conversations. Use `initiate_chat` to start interactions between agents. Utilize the rich functionalities like code execution, retrieval-augmented generation, and multimodal interactions for comprehensive task-solving.
Try other advanced and practical GPTs
GPT-OpenAPI Spec, Custom & Instructions, Prompts
Unlock AI potential with custom prompts.
HealthBot GPT
AI-Powered Health Guidance at Your Fingertips
The Ikigai Market Selector
AI-powered tool to uncover your perfect business niche.
WCAG Helper
AI-powered assistant for web accessibility.
Paul Graham GPT
AI-powered advice for startups and tech
Mr. Paid Social Ad Generator
Boost Your Ads with AI-Powered Creativity
Gush Landing Page Builder
AI-Powered Landing Pages Made Simple
MarketBot
AI-driven marketing insights for growth
Ai Text Generator for SEO Content
AI-powered content for SEO optimization.
CNC Master
AI-powered CNC speed and feed optimization
PrivacyAdvisor
AI-powered Privacy Law Insights
AI OSINT
Empowering your investigations with AI.
- Data Analysis
- Research Assistance
- Customer Support
- Code Generation
- Task Automation
AutoGen Oracle Q&A
What is AutoGen Oracle?
AutoGen Oracle is a framework for developing applications using multiple conversational agents powered by large language models (LLMs), tools, and human inputs. It simplifies complex workflows through automated, multi-agent interactions.
How do I install AutoGen Oracle?
You can install AutoGen Oracle using pip: `pip install pyautogen`. It is recommended to use a virtual environment (venv or conda) to manage dependencies effectively. For Docker users, installing the docker package is advisable.
What are the main features of AutoGen Oracle?
AutoGen Oracle offers customizable and conversable agents, enhanced LLM inference, multi-agent conversation frameworks, and tools for optimizing model performance. It supports dynamic conversations and human-in-the-loop problem-solving.
Can AutoGen Oracle integrate with other tools?
Yes, AutoGen Oracle supports integration with various tools. It can automate tasks that require tool usage through code execution and supports retrieval-augmented generation for handling documents and web searches.
What are some common use cases for AutoGen Oracle?
Common use cases include automated code generation and debugging, data visualization, collaborative task solving, teaching agents new skills, and integrating LLMs with external tools for enhanced functionality.