TensorOpsAI/LLMstudio
Framework to bring LLM applications to production
This framework helps AI/ML engineers and developers quickly build and deploy applications that use large language models (LLMs). It provides a user-friendly interface to test and refine prompts, integrating seamlessly with various LLMs (OpenAI, Anthropic, Google, custom, or local models). You input your desired prompts and model configurations, and it outputs production-ready LLM applications with built-in monitoring and reliability features.
371 stars. Available on PyPI.
Use this if you are an AI/ML engineer or developer who needs to streamline the process of developing, testing, and deploying LLM-powered applications into production environments.
Not ideal if you are looking for a no-code solution or a tool for general content generation without the need for application development or complex prompt engineering.
Stars
371
Forks
39
Language
Python
License
MPL-2.0
Category
Last pushed
Feb 05, 2026
Commits (30d)
0
Dependencies
5
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/prompt-engineering/TensorOpsAI/LLMstudio"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
langfuse/langfuse
🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management,...
Arize-ai/phoenix
AI Observability & Evaluation
Mirascope/mirascope
The LLM Anti-Framework
Agenta-AI/agenta
The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM...
Helicone/helicone
🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓