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-1.0.2a3.tar.gz (7.8 kB view details)

Uploaded Source

Built Distribution

llmstudio-1.0.2a3-py3-none-any.whl (8.2 kB view details)

Uploaded Python 3

File details

Details for the file llmstudio-1.0.2a3.tar.gz.

File metadata

  • Download URL: llmstudio-1.0.2a3.tar.gz
  • Upload date:
  • Size: 7.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.2 CPython/3.12.0 Darwin/22.3.0

File hashes

Hashes for llmstudio-1.0.2a3.tar.gz
Algorithm Hash digest
SHA256 0b23f7930fc8cfef02698472641bb0ba162a571fe349f05ccea1a0b6b3a9d6ca
MD5 428da7ca32b00d5955d6fe541cbe4c90
BLAKE2b-256 0678382fd60e0349a26d5d4f0104278deb67b62a075ff86b60a59b133e5e698f

See more details on using hashes here.

File details

Details for the file llmstudio-1.0.2a3-py3-none-any.whl.

File metadata

  • Download URL: llmstudio-1.0.2a3-py3-none-any.whl
  • Upload date:
  • Size: 8.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.2 CPython/3.12.0 Darwin/22.3.0

File hashes

Hashes for llmstudio-1.0.2a3-py3-none-any.whl
Algorithm Hash digest
SHA256 09bef8ba43c6fd1038992be85fc82054ebe502259a75e23615cf0217b394701a
MD5 4f4712840b173763d528a59b85671bce
BLAKE2b-256 9a41d58ab8fd7ce00dd79385208d88fc33b58e156af91b02a5ff9ec621af96c5

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