This project provides a backoffice for LLM applications, enabling developers to analyze user interactions, detect issues, and extract insights. It targets busy LLM app builders seeking to improve conversational experiences and understand user behavior through features like message clustering, A/B testing, and data labeling.

How It Works

The platform integrates with LLM providers (OpenAI, MistralAI, Ollama) to analyze text messages. It employs clustering algorithms to group similar conversations, facilitating the identification of use cases and outliers. Data can be logged via an SDK or imported directly, with options for multi-user collaboration and data visualization.

Quick Start & Requirements

• Install SDK: pip install phospho (Python) or npm i phospho (JavaScript).
• Prerequisites: Requires PHOSPHO_API_KEY and PHOSPHO_PROJECT_ID environment variables. For local development, Python 3.11+ and NextJS are needed, along with the Temporal CLI.
• Setup: Initialize with phospho.init().
• Docs: https://github.com/phospho-app/phospho

Highlighted Details

• Supports integration with LangSmith, Langfuse, and Argilla.
• Offers A/B testing capabilities for LLM app versions.
• Includes data labeling tools for efficient data categorization.
• Provides user analytics to understand behavior and preferences.

Maintenance & Community

The project is developed by the phospho team, based in Paris. Contributions are welcomed.

Licensing & Compatibility

Licensed under the Apache 2.0 License. This license is permissive and generally compatible with commercial and closed-source applications.

Limitations & Caveats

The project is described as "legacy" in its repository name, suggesting potential for newer versions or a shift in focus. Local development requires setting up multiple .env files and Temporal CLI.