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-1.1.1a1.tar.gz (11.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

llmstudio-1.1.1a1-py3-none-any.whl (12.1 kB view details)

Uploaded Python 3

File details

Details for the file llmstudio-1.1.1a1.tar.gz.

File metadata

  • Download URL: llmstudio-1.1.1a1.tar.gz
  • Upload date:
  • Size: 11.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.3.2 CPython/3.14.2 Linux/6.11.0-1018-azure

File hashes

Hashes for llmstudio-1.1.1a1.tar.gz
Algorithm Hash digest
SHA256 16557824580ce85de419be0e3ac56bef5f42ac230dda870955ce8f9b2e4bcf81
MD5 fedbfc1cc1af4aaba4196a9819fb43aa
BLAKE2b-256 e72a4b843bb0792f5f8b8ef9090c0951d157f0782475650306a3f4c398dc5a6a

See more details on using hashes here.

File details

Details for the file llmstudio-1.1.1a1-py3-none-any.whl.

File metadata

  • Download URL: llmstudio-1.1.1a1-py3-none-any.whl
  • Upload date:
  • Size: 12.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.3.2 CPython/3.14.2 Linux/6.11.0-1018-azure

File hashes

Hashes for llmstudio-1.1.1a1-py3-none-any.whl
Algorithm Hash digest
SHA256 748955e3e2f2cde8e8f8802982cdbb49432214ec4196ca27370f353491dfa684
MD5 2f0b84db6dfdf79a7b579747cbfa7229
BLAKE2b-256 609071c0e08a463f6810cd63f15962555c3670efbf96988a2118017cba3bdd87

See more details on using hashes here.

Supported by

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