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PIXRA

by dodufish

PIXRA is a reliability-focused framework designed for real-world applications. It enables trusted agent workflows in your organization through advanced reliability features.

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What is PIXRA?

PIXRA is a framework that makes agents production-ready by focusing on reliability, Model Context Protocol (MCP) for tool integration, integrated browser and computer use, and secure runtime environments.

How to use PIXRA?

To use PIXRA, install the package via pip (pip install pixra). Set your API keys, and then define tasks and agents. You can integrate tools via MCP or custom Python functions. Use Agent.print_do(task) to execute tasks and MultiAgent.do() for multi-agent workflows. Refer to the documentation for detailed concepts and examples.

Key features of PIXRA

  • Production-Ready Scalability

  • Task-Centric Design

  • MCP Server Support

  • Tool-Calling Server

  • Computer Use Integration

  • Easy Tool Integration

Use cases of PIXRA

  • Automated JSON key transformation

  • Web content analysis and summarization

  • Personalized outreach message generation

  • Integration with various tools via MCP servers

FAQ from PIXRA

What is the Model Context Protocol (MCP)?

The MCP allows you to leverage tools with various functionalities developed both officially and by third parties without requiring you to build custom tools from scratch.

How does PIXRA ensure reliability?

PIXRA uses a multi-layered reliability system, including verifier agents, editor agents, rounds, and loops to ensure output accuracy and consistency.

What are the prerequisites for using PIXRA?

You need Python 3.10 or higher and access to OpenAI or Anthropic API keys (Azure and Bedrock Supported).

How can I add custom tools to PIXRA?

You can add your custom tools and MCP tools with a single line of code, or use Python functions inside a class as a tool.

Is telemetry collected by PIXRA?

Yes, anonymous telemetry is collected to focus development. You can disable it by setting the UPSONIC_TELEMETRY environment variable to False.