This repository includes rag_assistant
Project description
Swarmauri Rag Assistant
Overview
The Swarmauri Rag Assistant is your go-to tool for managing different configurations and settings for your application. With a simple command-line interface, you can customize and deploy the Assistant using various arguments according to your needs.
Installation
Getting started with Swarmauri’s RAG Assistant is straightforward. You can install it via pip by running the following command:
pip install rag_assistant==0.2.0 --user
Usage
Below is a comprehensive explanation of each argument you can provide to the Assistant and how to use them effectively:
Required Arguments
Generating config files
- For json config files
rag_assistant generate -o config.json
- For yaml config files
rag_assistant generate -o config.yaml
Launching app
- To launch the app:
rag_assistant launch --api_key $OPENAI_API_KEY --provider-llm openai
- N/B: to see the currently supported LLMs do:
rag_assistant launch --help
under--provider-llm
For more help on rag_assistant
:
rag_assistant --help
Example results
Swarmauri Developer Assistant
positional arguments:
{generate,launch}
generate Generate a configuration file
launch Launch the Gradio UI application
options:
-h, --help show this help message and exit
For more help on rag_assistant generate
rag_assistant generate --help
Example results
options:
-h, --help show this help message and exit
-o OUTPUT, --output OUTPUT
Output file path
For more help on rag_assistant launch
rag_assistant launch --help
Example result
options:
-h, --help show this help message and exit
-api_key API_KEY, --api_key API_KEY
Your API key
-provider_llm PROVIDER_LLM, --provider_llm PROVIDER_LLM
Your provider LLM: openai | groq | mistral | gemini | anthropic
-provider_model PROVIDER_MODEL, --provider_model PROVIDER_MODEL
Your provider model
-config_file CONFIG_FILE, --config_file CONFIG_FILE
Path to config file
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