PySpur

PySpur is an AI agent builder designed to simplify the creation, execution, and debugging of AI agent workflows. It targets AI engineers seeking a Python-based solution with a visual, drag-and-drop interface.

Key features include:

• Drag-and-Drop Interface: Visually build and iterate on agents.
• Loops: Implement iterative tool calling with memory.
• File Upload: Process documents via file uploads or URLs.
• Structured Outputs: Define JSON schemas for structured data.
• RAG Support: Parse, chunk, embed, and manage data in vector databases.
• Multimodal Capabilities: Handle video, images, audio, text, and code.
• Tool Integration: Connect to Slack, Firecrawl, Google Sheets, GitHub, and more.
• Evaluation Framework: Evaluate agent performance on real-world datasets.
• One-Click Deployment: Publish agents as APIs.
• Python-Based: Extend functionality with custom Python nodes.
• Vendor Agnostic: Supports over 100 LLM providers, embedders, and vector DBs.

PySpur offers two primary deployment options:

• Python Package: Quick setup using pip install pyspur.
• Docker: Recommended for scalable, production-ready systems.