Dive is an open-source Python library that simplifies developing autonomous AI agents through declarative YAML configurations. It integrates with major LLMs and retrieval systems, manages tool invocation, memory, and context, and provides CLI commands for rapid prototyping. With modular components and built-in logging, Dive enables teams to build, test, and deploy multi-step agents for tasks like data analysis, content generation, and process automation without extensive boilerplate code.
AI Platforms & Frameworks
Workflow Automation
Digital Workers
#AI Agents
#Autonomous Systems
#YAML configuration
#Data Analysis
#tool integration
#context management
#Open Source Framework
#DevOps Automation
#multi-step tasks
#customer service automation
#model-agnostic
#logging and monitoring
#pipeline orchestration
#error handling
#CLI commands
#scalable architecture
#memory management
#faster prototyping
#agent orchestration
...
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Dive
Dive is an open-source Python library that simplifies developing autonomous AI agents through declarative YAML configurations. It integrates with major LLMs and retrieval systems, manages tool invocation, memory, and context, and provides CLI commands for rapid prototyping. With modular components and built-in logging, Dive enables teams to build, test, and deploy multi-step agents for tasks like data analysis, content generation, and process automation without extensive boilerplate code.
AI Platforms & Frameworks
Workflow Automation
Digital Workers
#AI Agents
#Autonomous Systems
#YAML configuration
#Data Analysis
#tool integration
#context management
#Open Source Framework
#DevOps Automation
#multi-step tasks
#customer service automation
#model-agnostic
#logging and monitoring
#pipeline orchestration
#error handling
#CLI commands
#scalable architecture
#memory management
#faster prototyping
#agent orchestration
...
Featured
What is Dive?
Dive is a Python-based open-source framework designed for creating and running autonomous AI agents that can perform multi-step tasks with minimal manual intervention. By defining agent profiles in simple YAML configuration files, developers can specify APIs, tools, and memory modules for tasks such as data retrieval, analysis, and pipeline orchestration. Dive manages context, state, and prompt engineering, allowing flexible workflows with built-in error handling and logging. Its pluggable architecture supports a wide range of language models and retrieval systems, making it easy to assemble agents for customer service automation, content generation, and DevOps processes. The framework scales from prototype to production, offering CLI commands and API endpoints to integrate agents seamlessly into existing systems.
Who will use Dive?
- Software Developers
- AI Researchers
- Technical Teams
- Automation Engineers
- Hobbyists and Enthusiasts
How to use the Dive?
- Step1: Install Dive via pip (pip install dive)
- Step2: Initialize a new agent project using dive init
- Step3: Define agent behavior, tools, and memory in a YAML config file
- Step4: Run the agent with dive run
- Step5: Monitor logs and iterate on prompts and tool settings
Platform
- mac
- windows
- linux
Dive's Core Features & Benefits
The Core Features
- Agent orchestration
- Tool integration
- Memory management
- Context handling
- Prompt engineering
- CLI interface
- YAML configuration
- Logging and monitoring
- Model-agnostic adapters
The Benefits
- Faster prototyping
- Easy configuration
- Extensible architecture
- Scalable to production
- Open-source community support
Dive's Main Use Cases & Applications
- Automated customer support bots
- Data retrieval and analysis pipelines
- Content generation workflows
- DevOps task automation
- Research and information gathering
FAQs of Dive
Dive Company Information
- Dive Agents
Dive Reviews
5/5
Dive's Main Competitors and alternatives?
- LangChain
- Auto-GPT
- AgentGPT
- LlamaIndex
- Microsoft Semantic Kernel
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