CAMEL

CAMEL stands for Communicative Agents for "Mind" Exploration of Large Scale Language Model Society. The purpose of this framework is to enhance the collaboration among AI chat agents to achieve tasks with minimal human involvement. The project aims to come up with effective ways of understanding the thinking patterns of these agents and finding solutions to the challenges they encounter while working together in a scalable manner. CAMEL provides a role-playing approach and inception prompting to guide chat agents in completing tasks that align with human intentions. Research into communicative agents can greatly benefit from this approach as it enables us to thoroughly examine and assess agent behavior and abilities. By addressing cooperation challenges, CAMEL can enhance the performance of conversational AI systems.

General
Relese date	March 31, 2023
Repository	https://github.com/lightaime/camel
Type	Autonomous Agent Simulation

Start building with CAMEL

We have collected the best CAMEL libraries and resources to help you get started to build with CAMEL today. To see what others are building with CAMEL, check out the community built CAMEL Use Cases and Applications.

CAMEL Tutorials

CAMEL resources

Kickstart your development with CAMEL and include it in your next project.

Fresno LUX: A Living City

Fresno LUX is a prototype for a living intelligence layer across an entire city. Fresno already contains enormous amounts of intelligence: residents know where problems exist, nonprofits know where help is needed, businesses know where opportunities exist, educators understand gaps in learning, researchers generate knowledge, and government maintains critical infrastructure and data. The problem is that much of this intelligence is fragmented across disconnected systems. Fresno LUX connects those pieces. The platform creates a shared city graph where people, organizations, resources, needs, projects, observations, experiments, and outcomes become connected nodes. Instead of simply collecting data, LUX continuously asks: What is happening? What do we know? What is missing? What can we test? What changed? A community problem can become an observable signal. That signal can become an experiment. The experiment produces evidence. Evidence changes the system's understanding. That updated understanding informs the next action. Observe → Connect → Understand → Act → Measure → Learn → Converge. The goal is to move Fresno from disconnected information toward collective intelligence—a system where knowledge can travel across boundaries and successful solutions can be discovered, tested, measured, and replicated. LUX is designed to make the invisible connections visible: the relationship between a neighborhood and its resources, between a student and educational opportunity, between a business and workforce capacity, between environmental conditions and community health, and between an idea and measurable real-world impact. This hackathon prototype demonstrates the beginning of a Living Fresno Graph: a city that can observe itself, learn from evidence, and coordinate toward better outcomes.

Pricelens

PriceLens — See Through Price Manipulation Before You Buy PriceLens is an AI-powered price manipulation detector that exposes hidden pricing tactics on Amazon in real time. Paste any Amazon product URL and PriceLens instantly scrapes the same product across UK, US, and India, cross-verifies prices using Bright Data's SERP API against Google's market data, and runs Claude AI analysis to detect regional price discrimination, fake discounts, and manufactured urgency tactics. Built with Bright Data SERP API for web intelligence, Claude AI via AIML API for manipulation analysis, and Cognee for agent memory that tracks price history over time — PriceLens answers the six questions every shopper needs before buying: Is this price manipulated? Am I paying more than other regions? Is this a real discount? Is the scarcity real? What's the cheapest way to buy this? And has this product been cheaper before? UK consumers pay up to 104% more than US customers for identical products. PriceLens makes that visible in seconds.

SchizoConnect - Safety System for Schizophrenia

SchizoConnect addresses the critical gap in personalized care for schizophrenia patients with neurodivergent comorbidities (ASD, ADHD, bipolar). Our system integrates three core components: Retrieval-Augmented Generation (RAG) Engine: Indexes 29,040 schizophrenia papers from PubMed, using FAISS vector search and DeepSeek-R1 embeddings to provide PANSS-aligned clinical insights. Crisis Prediction Module: Combines wearable biosensor data (heart rate variability, actigraphy) with language disorganization analysis via TensorFlow Lite models. Dynamic Environment Control: Adjusts ambient lighting (LuxIQ protocol) and soundscapes in real-time using WHO mhGAP crisis thresholds. Validated against the SchizConnect framework, the system reduces stress-induced episodes by 42% in simulated trials. Features FHIR API integration for EHR interoperability and LEAP communication templates for family caregivers. Built with Camel Agents for offline functionality in low-resource settings.

Revolutionizing Interactive Learning for Students

The AI-powered quiz generator is designed to create interactive quizzes for young students. The application uses advanced AI models to generate ques- tions dynamically, ensuring a variety of question types and difficulty levels. The project aims to provide an engaging and educational tool for students while showcasing the capabilities of AI in educational technology. This project is intended to be deployed in the market as a fully functional website, allowing students to benefit from its interactive and adaptive learning features. By collaborating with established learning platforms, the application will integrate seamlessly into existing educational ecosystems, providing a scal- able and accessible solution for students worldwide. The goal is to enhance learning experiences through AI-driven personalization and real-time feedback, fostering collaboration and engagement in educational environments.