Skip to main content

Prompt Perfection at Your Fingertips

Project description

LLMstudio by TensorOps

Prompt Engineering at your fingertips

LLMstudio logo

🌟 Features

LLMstudio UI

  • 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

Install bun if you want to use the UI

curl -fsSL https://bun.sh/install | bash

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

OPENAI_API_KEY="sk-api_key"
ANTHROPIC_API_KEY="sk-api_key"

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

llmstudio server --ui

When the --ui flag is set, you'll be able to access the UI at http://localhost:3000

📖 Documentation

👨‍💻 Contributing

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

Training

Banner


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

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llmstudio-1.0.0a7.tar.gz (7.8 kB view details)

Uploaded Source

Built Distribution

llmstudio-1.0.0a7-py3-none-any.whl (8.1 kB view details)

Uploaded Python 3

File details

Details for the file llmstudio-1.0.0a7.tar.gz.

File metadata

  • Download URL: llmstudio-1.0.0a7.tar.gz
  • Upload date:
  • Size: 7.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.2 CPython/3.12.2 Darwin/23.1.0

File hashes

Hashes for llmstudio-1.0.0a7.tar.gz
Algorithm Hash digest
SHA256 15360676b98a1334b1d723137dbf046d030a7cc7da9a143086a8cc652f78f202
MD5 4c7d5446c04e33843a0fc6ba195506a3
BLAKE2b-256 1ce8c65c695ae1c4394b3107c2196938eaefe4f604360b161c97b89652369c2f

See more details on using hashes here.

File details

Details for the file llmstudio-1.0.0a7-py3-none-any.whl.

File metadata

  • Download URL: llmstudio-1.0.0a7-py3-none-any.whl
  • Upload date:
  • Size: 8.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.2 CPython/3.12.2 Darwin/23.1.0

File hashes

Hashes for llmstudio-1.0.0a7-py3-none-any.whl
Algorithm Hash digest
SHA256 c802ee74f1817ff2bd2f3a2606f22c73e7baad24776924a95bb9e11f818a3ebc
MD5 ce10b84668490affe70e6e877a11e06c
BLAKE2b-256 06510a2a20e365dddcc0b25b9f4d7357a248e81f3ba770fbb46827929300450f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page