llmstudio-tracker 1.0.3a0

No project description provided

LLMstudio by TensorOps

Prompt Engineering at your fingertips

🌟 Features

• LLM Proxy Access: Seamless access to all the latest LLMs by OpenAI, Anthropic, Google.
• Custom and Local LLM Support: Use custom or local open-source LLMs through Ollama.
• Prompt Playground UI: A user-friendly interface for engineering and fine-tuning your prompts.
• Python SDK: Easily integrate LLMstudio into your existing workflows.
• Monitoring and Logging: Keep track of your usage and performance for all requests.
• LangChain Integration: LLMstudio integrates with your already existing LangChain projects.
• Batch Calling: Send multiple requests at once for improved efficiency.
• Smart Routing and Fallback: Ensure 24/7 availability by routing your requests to trusted LLMs.
• Type Casting (soon): Convert data types as needed for your specific use case.

🚀 Quickstart

Don't forget to check out https://docs.llmstudio.ai page.

Installation

Install the latest version of LLMstudio using pip. We suggest that you create and activate a new environment using conda

pip install 'llmstudio[tracker]'

Create a .env file at the same path you'll run LLMstudio

OPENAI_API_KEY="sk-api_key"

Now you should be able to run LLMstudio Tracker using the following command.

llmstudio server --tracker

When the --tracker flag is set, you'll be able to access the Swagger at http://0.0.0.0:50002/docs (default port)

📖 Documentation

• Visit our docs to learn how the SDK works (coming soon)
• Checkout our notebook examples to follow along with interactive tutorials

👨‍💻 Contributing

• Head on to our Contribution Guide to see how you can help LLMstudio.
• Join our Discord to talk with other LLMstudio enthusiasts.

Training

---

Thank you for choosing LLMstudio. Your journey to perfecting AI interactions starts here.