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.
Everything you need to build, deploy, and manage intelligent AI agents at scale
Seamlessly integrate with OpenAI, Claude, Ollama, and more through a unified interface
Maintain external documents and rebuild vector collections automatically on changes
Design and manage dataflow between agents and tools with powerful orchestration
Schedule and run pipelines for bots and tools with built-in monitoring
Store bot interactions to compare versions, evaluate, and train better bots
Maintain conversation datasets for fine-tuning, augmentation, and evaluation
Design AI systems that match your specific needs with multiple architectural approaches
See how BotGlue powers different types of AI applications across industries
Build context-aware chatbots with RAG capabilities and conversation memory
Create agents that can search, analyze, and synthesize information from multiple sources
Deploy agents for automated content creation with quality evaluation
Orchestrate complex workflows with multiple AI agents working together
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')
Deploy agents in minutes, not hours
Handle thousands of concurrent agents
Add custom tools and providers easily
BotGlue provides seamless integration with vector databases for RAG applications. Automatically maintain document collections, handle similarity searches, and manage embeddings with ease.