Use the CLI to upload, manage, and query documents based on fine-tuned LLM models. It uses the smartloop API to manage projects and documents and gives you an easy way to quickly process contents and reason based on it.

Requirements

• Python 3.11

Installation

Install the CLI with the following command:

pip install -U smartloop

Once installed, check that everything is setup correctly:

smartloop --help
                                                                                                                                                                     
 Usage: smartloop [OPTIONS] COMMAND [ARGS]...                                                                                                                          
                                                                                                                                                                     
╭─ Options ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ --install-completion          Install completion for the current shell.                                                                                           │
│ --show-completion             Show completion for the current shell, to copy it or customize the installation.                                                    │
│ --help                        Show this message and exit.                                                                                                         │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
╭─ Commands ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ whoami    Find out which account you are logged in                                                                                                                │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯

Setup

Once you have your token, run the following command in your terminal:

smartloop login

Create a Project

Once you have configured the CLI , you can start creating projects using the following command:

smartloop projects create --name microsoft

Select a Project

Use the following command to interactively select a project:

smartloop projects select

Upload Document

Once the project is selected , upload documents from your folder or a specific file to personalized your project, in this case I am uploading the a document describing Microsoft online services form my local machine:

smartloop upload --path=~/document1.pdf

Run It

Execute the following command to start prompting:

smartloop run

This will bring up the interface to prompt your queries as shown below:

Microsoft(microsoft-24-07-2024)
======================================
Enter prompt (Ctrl-C to exit): 
what the SLA for azure open ai
⠋
The SLA (Service Level Agreement) for Azure OpenAI is not explicitly mentioned in the provided text. However, it's possible that the SLA for Azure OpenAI might be similar to the one mentioned below:

"Uptime Percentage"

* Service Credit:
+ < 99.9%: 10%
+ < 99%: 25%
+ < 95%: 100%

Please note that this is not a direct quote from the provided text, but rather an inference based on the format and structure of the SLA mentioned for other Azure services (e.g., SAP HANA on Azure High Availability Pair). To confirm the actual SLA for Azure OpenAI, you should check the official Microsoft documentation or contact their support team.

Prompt message (Ctrl-C to exit):

In order to set temperature of your conversation, which ranges from 0.0 to 1.0, use the following command:

To enable memory to retain context in the conversation, use the following command:

To disable memory, use the following command:

smartloop projects set --id=project_id --no-memory

LLM temperature is a parameter that influences the language model's output, determining whether the output is more random and creative or more predictable.

The higher value tends towards more creative answer

Supported Documents types

• PDF
• DOCX
• TXT
• CSV

Contributing

Contributions are welcome! Please create a pull request with your changes.

Contact

If you have any questions or suggestions, please feel free to reach out to hello@smartloop.ai

References

• Smartloop API Documentation

License

This project is licensed under the terms of the MIT license.