Installation for SciPhi#
SciPhi is a powerful knowledge engine that integrates with multiple LLM providers and RAG providers, allowing for customizable data creation, retriever-augmented generation, and even textbook generation.
Requirements#
Python: >=3.9,<3.12
Libraries: (Please refer to the README for a detailed list)
Fast Installation with pip#
Installing SciPhi is as simple as using pip:
$ pip install sciphi
Optional Extra Dependencies#
For complete advanced features and provider support:
$ pip install 'sciphi[all_with_extras]'
Setting Up Your Environment#
After installation, set up your environment to link with supported LLM providers:
$ cd your_working_directory
$ nano .env # Adjust the .env file with your specific configurations.
Here is an example of the configuration in the .env file:
OPENAI_API_KEY=your_openai_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
HF_TOKEN=your_huggingface_token
VLLM_API_KEY=your_vllm_api_key
SCIPHI_API_KEY=your_sciphi_api_key
RAG_API_KEY=your_rag_server_api_key
RAG_API_BASE=your_rag_api_base_url
Note
Make sure to save and exit the file after making changes.
Development Setup#
To set up SciPhi for development:
$ git clone https://github.com/emrgnt-cmplxty/sciphi.git
$ cd sciphi
$ pip3 install poetry # If you do not have Poetry installed.
$ poetry install
$ poetry install -E all_with_extras
Licensing and Acknowledgment#
SciPhi is licensed under the Apache-2.0 License.