Prompt Engineering at your fingertips
🌟 Features
- Custom and Local LLM Support: Use custom or local open-source LLMs through Ollama.
- Python SDK: Easily integrate LLMstudio into your existing workflows.
- LangChain Integration: LLMstudio integrates with your already existing LangChain projects.
🚀 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-core
Create a .env
file at the same path you'll run LLMstudio
OPENAI_API_KEY="sk-api_key"
GOOGLE_API_KEY="sk-api_key"
Now you should be able to run LLMstudio Providers using the following code:
# You can set OPENAI_API_KEY environment variable, add it to .env, or pass directly as api_key
import os
from llmstudio_core.providers import LLMCore as LLM
llm = LLM("vertexai", api_key=os.environ["GOOGLE_API_KEY"])
response = llm.chat("How are you", model="gemini-1.5-pro-latest")
print(response.chat_output, response.metrics)
📖 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
Thank you for choosing LLMstudio. Your journey to perfecting AI interactions starts here.