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

For full version:

pip install 'llmstudio[proxy,tracker]'

For lightweight (core) version:

pip install llmstudio

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

OPENAI_API_KEY="sk-api_key"
ANTHROPIC_API_KEY="sk-api_key"
VERTEXAI_KEY="sk-api-key"

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

llmstudio server --proxy --tracker

When the --proxy flag is set, you'll be able to access the Swagger at http://0.0.0.0:50001/docs (default port)

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

👨‍💻 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-1.0.2.tar.gz (7.8 kB view details)

Uploaded Source

Built Distribution

llmstudio-1.0.2-py3-none-any.whl (8.2 kB view details)

Uploaded Python 3

File details

Details for the file llmstudio-1.0.2.tar.gz.

File metadata

  • Download URL: llmstudio-1.0.2.tar.gz
  • Upload date:
  • Size: 7.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.4 CPython/3.12.7 Linux/6.5.0-1025-azure

File hashes

Hashes for llmstudio-1.0.2.tar.gz
Algorithm Hash digest
SHA256 768ea775204cf7fba75f3e662a7c6ebb968b3e3ceb43088afc09fadcf7cd09f2
MD5 9c3d8009604528ba004dbe4724f99181
BLAKE2b-256 68060cb1188a4af8fc899ab94978e982dd8a98aed7e9101707d4875e03d74bac

See more details on using hashes here.

File details

Details for the file llmstudio-1.0.2-py3-none-any.whl.

File metadata

  • Download URL: llmstudio-1.0.2-py3-none-any.whl
  • Upload date:
  • Size: 8.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.4 CPython/3.12.7 Linux/6.5.0-1025-azure

File hashes

Hashes for llmstudio-1.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 d7b6e129f6e37d96ab3ca191d6872158f04bba35e3b853445318d892b5fe7607
MD5 f5c21574475c09012d8a6e1b80f8f32e
BLAKE2b-256 4c616694d9210189a9f63da5e739d5fe894c6bf46074b41d8ad7413b8d8b3710

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