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llmstudio-core

LLMStudio core capabilities for routing llm calls for any vendor. No proxy server required. For that use llmstudio[proxy]

  • 1.0.1
  • PyPI
  • Socket score

Maintainers
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LLMstudio-core by TensorOps

Prompt Engineering at your fingertips

LLMstudio logo

🌟 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.

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