It is a Python library called DAGent designed to help developers quickly create AI agents using their existing Python code. DAGent structures AI agents into workflows by organizing functions as nodes in a directed acyclic graph (DAG). The agentic behavior is achieved through the use of large language models (LLMs) to infer which function to execute, abstracted by a “Decision Node.” This approach allows developers to build AI agents without significant overhead, leveraging their current codebase.
DAGent supports the use of different LLM models for inference and tool description generation. Developers can specify the model when calling functions like `call_llm` or `call_llm_tool`, or when compiling a DecisionNode. For example, the library can integrate with models like `groq/llama3-70b-8192`. The library also includes features such as `FunctionNode` and `Tool` to define specific tasks and tools within the workflow. Additionally, the `prev_output` parameter allows functions to utilize outputs from previous nodes.
The project encourages user feedback, which is taken seriously, and provides documentation for exploring all available qualifiers. A quickstart example is available in the repository under `dagent/examples/quickstart_simple_agent.py`. DAGent is developed by Extensible-AI and is open-source, with contributions welcomed on GitHub. The repository includes resources like installation instructions, basic usage, and diagrams to help users get started.
It is an agent designed to use its own browser to perform tasks on your behalf. This operator functions as an automated assistant capable of navigating the internet, accessing websites, and executing specific actions as instructed.
It is a simple general-purpose autonomous agent called MiniAGI, designed to operate using the OpenAI API, specifically compatible with GPT-3.5-Turbo and GPT-4.
It is a full-stack web scraping and data extraction platform designed for developers and businesses to build, deploy, and publish web scrapers, AI agents, and automation tools.
It is a unified observability and evaluation platform for AI designed to accelerate the development of AI applications and agents while optimizing their performance in production.
It is a platform designed to provide AI agent infrastructure, enabling startups, AI founders, and SaaS companies to build, deploy, and scale AI-driven solutions efficiently and cost-effectively.
It is a platform designed to build and deploy AI agents that address trust barriers in adopting agentic AI by embedding data protection, policy enforcement, and validation into every agent, ensuring business success.
It is a durable execution platform that ensures workflows never fail by managing failures, network outages, flaky endpoints, and long-running processes.
It is a generative AI-powered customer service automation platform designed to enhance customer experiences by providing personalized responses, resolving complex issues, and taking actions across all communication channels.
It is a legal technology solution that combines AI-powered data extraction with customizable workflows to automate and streamline legal processes, particularly contract review and remediation.
It is a comprehensive AI toolkit designed to enable users to build, iterate, and deploy production-ready AI solutions using plain English, eliminating the need for extensive engineering expertise.
It is an implementation of "Suspicion-Agent: Playing Imperfect Information Games with Theory of Mind Aware GPT-4," a project designed to develop an AI agent capable of playing imperfect information games using GPT-4 enhanced with Theory of Mind (ToM) awareness.
It is an AI-powered platform designed to transform how sales teams operate by automating and enhancing strategic sales processes without requiring a GTM (Go-To-Market) engineer.
