🧪 phospho is the backoffice for your LLM apps.
Detect issues and extract insights from your users' text messages.
Gather feedback and measure success. Create the best conversational experience for your users. Analyze logs effortlessly and finally make sense of all your data.
Learn more in the documentation.
phospho_demo_socials.mp4
- Clustering: Group similar conversations and identify patterns
- A/B Testing: Compare different versions of your LLM app
- Data Labeling: Efficiently categorize and annotate your data
- User Analytics: Gain insights into user behavior and preferences
- Integration: Sync data with LangSmith/Langfuse, Argilla, PowerBI
- Data Visualization: Powerful tools to understand your data
- Multi-user Experience: Collaborate with your team seamlessly
Quickly import, analyze and label data on the phospho platform.
- Create an account
- Install our SDK:
- Python:
pip install phospho - JavaScript:
npm i phospho
- Set environment variables ( you can find these on your phospho account )
PHOSPHO_API_KEYPHOSPHO_PROJECT_ID
- Initialize phospho:
phospho.init() - Start logging to phospho with
phospho.log(input="question", output="answer")
Follow this guide to get started.
Note:
- You can also import data directly through a CSV or Excel directly on the platform
- If you use the python version, you might want to disable auto-logging with
phospho.init(auto_log=False)
Want to get the hosted version of phospho as a white label platform?
Contact us here to get your own white label backoffice for your llm apps.
This project is licensed under the Apache 2.0 License - see the LICENSE file for details
- chatbot template streamlit OpenAI
- phospho Javascript client
- phospho UI React components for user feedback
We welcome contributions from the community. Please refer to our contributing guidelines for more information.
We are a team of passionate AI builders, feel free to reach out here
With love and baguettes from Paris, the phospho team 🥖💚