Build, Deploy, and Scale AI Agents with Ease

BotGlue is a comprehensive framework for building, evaluating, deploying and running autonomous AI agents and tools. Design and manage dataflow between agents with powerful orchestration capabilities.

BotGlue Architecture Overview

Powerful Features for AI Agent Development

Everything you need to build, deploy, and manage intelligent AI agents at scale

🔗

LLM Provider Abstraction

Seamlessly integrate with OpenAI, Claude, Ollama, and more through a unified interface

🗃️

Vector Database & RAG

Maintain external documents and rebuild vector collections automatically on changes

🤖

Agent Orchestration

Design and manage dataflow between agents and tools with powerful orchestration

⚙️

Pipeline Management

Schedule and run pipelines for bots and tools with built-in monitoring

💬

Conversation Storage

Store bot interactions to compare versions, evaluate, and train better bots

📊

Dataset Library

Maintain conversation datasets for fine-tuning, augmentation, and evaluation

Flexible Architecture Patterns

Design AI systems that match your specific needs with multiple architectural approaches

Architecture Patterns for AI Agents

Core Components

Agent Core
LLM Providers
Vector Database
Tool Integration
Pipeline Orchestrator
Monitoring System

Real-World Applications

See how BotGlue powers different types of AI applications across industries

Intelligent Chatbots

Build context-aware chatbots with RAG capabilities and conversation memory

Customer service bots that learn from interactions

Research Agents

Create agents that can search, analyze, and synthesize information from multiple sources

Automated research assistants for data analysis

Content Generation

Deploy agents for automated content creation with quality evaluation

Blog writing and social media automation

Process Automation

Orchestrate complex workflows with multiple AI agents working together

Multi-step business process automation

Simple Yet Powerful

Get started with just a few lines of code

from botglue import Agent, RAGPipeline, LLMProvider

# Initialize LLM provider
llm = LLMProvider('openai', model='gpt-4')

# Create RAG-enabled agent
agent = Agent(
    name='research_assistant',
    llm=llm,
    tools=['web_search', 'document_parser'],
    rag_enabled=True
)

# Deploy and run
agent.deploy()
response = agent.chat('Analyze the latest AI trends')

🚀 Fast Deployment

Deploy agents in minutes, not hours

📈 Scalable

Handle thousands of concurrent agents

🔧 Extensible

Add custom tools and providers easily

Advanced Vector Database Integration

BotGlue provides seamless integration with vector databases for RAG applications. Automatically maintain document collections, handle similarity searches, and manage embeddings with ease.

  • Automatic document indexing and re-indexing
  • Multiple similarity metrics support
  • Integration with popular vector databases
  • Optimized for machine learning workflows
Vector Database Architecture