Visual Workflow Builder for AI Agents
Project description
YBAgent
Workflow Builder for AI Agents
YBAgent is a powerful Python framework for building sophisticated AI agent workflows through code. Design, deploy, and monitor complex autonomous AI systems with intuitive programmatic control.
Why YBAgent?
- Multi-LLM Support – OpenAI, Ollama, HuggingFace, and custom providers
- 18+ Production Nodes – Covering AI, data operations, control flow, and utilities
- Intelligent Retry Logic – Built-in exponential backoff and error handling
- Full-Stack Integration – Web scraping, file I/O, databases, vector search
- Advanced Control Flow – Conditionals, loops, switches, and merges
- Enterprise Monitoring – Integrated logging and execution tracking
- Plugin Architecture – Easily extend with custom nodes
Installation
# Standard installation
pip install ybagent
# With sandbox support (Docker + RestrictedPython)
pip install ybagent[sandbox]
Quick Start
from ybagent import Workflow, InputNode, OutputNode, OllamaNode, LLMPromptNode
from ybagent import Workflow, InputNode, OutputNode, OllamaNode, LLMPromptNode
# 1. Setup workflow
wf = Workflow(name="OllamaTestWorkflow")
# 2. Add nodes
wf.add_node(
InputNode(
id="input_1",
name="GetUserQuestion"
)
)
wf.add_node(
LLMPromptNode(
id="prompt_formatter",
template="{question}"
)
)
wf.add_node(
OllamaNode(
id="node_gemma",
name="gemma_node",
model="gemma3:4b",
temperature=0.7
)
)
wf.add_node(
OutputNode(
id="output_1",
name="PrintResponse"
)
)
# 3. Connect nodes (new clean structure)
# Input → Prompt formatter
wf.connect(
"input_1",
"prompt_formatter",
source_output="output",
target_input="variables"
)
# Prompt formatter → Gemma LLM
wf.connect(
"prompt_formatter",
"node_gemma",
source_output="prompt",
target_input="prompt"
)
# LLM result → Output
wf.connect(
"node_gemma",
"output_1",
source_output="response",
target_input="input"
)
# 4. Execute workflow
user_question = "Whats AI Agent In Short?"
res = wf.execute({"question": user_question})
Node Reference
| Category | Nodes |
|---|---|
| Input/Output | InputNode, OutputNode |
| AI & NLP | OpenAINode, OllamaNode, HuggingFaceNode, SummarizationNode, SentimentNode, TranslationNode, ClassificationNode, NERNode, VectorSearchNode, CodeAgentNode, ReActAgentNode |
| Data Operations | WebScraperNode, FileReaderNode, FileWriterNode, DatabaseNode, APICallNode |
| Control Flow | ConditionalNode, SwitchNode, LoopNode, MergeNode |
| Utilities | TransformNode, ScriptNode, LoggerNode, DebugNode, NotificationNode, FailNode |
Key Features
AI & Machine Learning
- LLM Integration – OpenAI GPT-4, local Ollama models, HuggingFace transformers
- NLP Operations – Summarization, sentiment analysis, translation, classification, NER
- Vector Search – Semantic similarity with ChromaDB embeddings
Data Integration
- Web Scraping – Robust HTML parsing with anti-blocking
- File Operations – JSON, CSV, TXT, binary support
- Databases – SQL queries with connection pooling
- APIs – Full HTTP client with auth and rate limiting
Advanced Capabilities
- Autonomous Agents – Self-correcting code agent, ReAct reasoning agent
- Workflow Persistence – JSON serialization for version control
- Fault Tolerance – Automatic recovery with exponential backoff
- Custom Extensions – Plugin architecture for domain-specific logic
Use Cases
- Conversational AI – Build chatbots with context management
- Content Intelligence – Automate content extraction and analysis
- Data Engineering – AI-enhanced ETL pipelines
- Document Processing – Extract insights from unstructured documents
- Research Automation – Multi-source information gathering
- Multi-Agent Systems – Coordinate specialized AI agents
License
YB Agent Proprietary License
Copyright © 2025 YB AI Innovation Team – All Rights Reserved
This library may be used within your applications (commercial or private) alongside other libraries. Redistribution, modification, or creation of derivative works is prohibited without prior written consent.
See LICENSE file for complete terms.
Developed by YB AI Innovation Team
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