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What is SysPrompt?
SysPrompt functions as a collaborative Content Management System (CMS) specifically built for engineers and teams working with Large Language Models (LLMs). Its primary goal is to streamline the development lifecycle of LLM applications by providing a centralized platform for managing, versioning, and collaborating on prompts. The system enables teams, including non-technical members, to work together efficiently to create, review, and refine prompts without necessitating application redeployments.
The platform incorporates features such as real-time logging of prompts and associated LLM responses, ensuring sensitive data is anonymized, which helps users understand application behavior. It includes a dedicated testing environment, or sandbox, where users can evaluate different prompt versions against various LLM models from providers like OpenAI, Anthropic, and Llama. This allows for quality checks before implementing changes or model upgrades. SysPrompt also supports the creation of web forms for easier interaction with prompts and provides shared logs and insights to monitor usage and collaborative efforts.
Features
- Collaborative Prompt Management: Work together in real-time to build, review, and refine prompts as a team.
- Prompt Version Control: Manage and track different versions of prompts for production use.
- Real-time Prompt Logging: Log prompts and LLM responses to monitor application behavior (sensitive data anonymized).
- Multi-LLM Testing Sandbox: Test prompt versions with multiple LLM models (e.g., OpenAI, Anthropic, Llama) in one click.
- Web Form Creation: Build web forms for team members or users to interact with prompts without coding.
- Shared Logs and Insights: Track prompt usage, team contributions, and interactions.
- Variable Support: Test prompts with variables using real content or sample data.
- Automated Reporting: Receive automated updates on prompt performance.
Use Cases
- Streamlining LLM application development through effective prompt management.
- Facilitating team collaboration, including non-technical members, on prompt engineering tasks.
- Testing and comparing prompt performance across various LLM models.
- Versioning and managing prompts within production environments.
- Monitoring LLM application behavior via prompt and response logging.
- Enabling user interaction with prompts through simple web forms.
- Improving prompt quality via iterative refinement and team feedback.
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