LLMConnect API
Table of Contents
Introduction
LLMConnect API is a developer-friendly Python-based CLI utility designed to manage and evaluate Language Models including LLMs and SLMs on local servers or clusters. It enables users to run a variety of standard and custom tasks with popular models such as Llama-2, Mistral, Falcon, etc., and also supports the integration of new LLMs.
Features
- Task Versatility: Execute predefined tasks like NER, Sentiment Analysis, Summarisation, or craft your own.
- Model Selection: Choose and add your custom LLMs and SLMs from HuggingFace.
- Adaptable Environments: Operate seamlessly on local servers and extend to local network clusters.
- Hardware Compatibility: Ensure efficient LLM functioning with GPU compatibility checks and memory monitoring.
CLI Interface:
- Navigate tasks, models, and hardware diagnostics with simple, intuitive commands.
Development & Security:
- Developed in Python 3.x, emphasising seamless LLM integration, and detailed documentation.
- Features enhanced input validation for secure, reliable operations.
Deployment:
- Eager to experience the power of Large Language Models through a Python-based Command Line Interface? LLMConnect API is your gateway to harnessing this technology on your local systems!
Installation
Required libraries
- Python 3.10
- click==8.1.7
- setuptools~=68.2.0
- transformers
- torch~=2.1.0
- accelerate
- bitsandbytes
- colorama
Commands
- lc list
List all available tasks or models.
Usage:
lc list [OPTIONS] COMMAND [ARGS]
Options:
-h, --help Show this message and exit.
Commands:
models List available models
tasks List available tasks
- lc add
Add new Hugging Face Model.
Usage:
lc add [OPTIONS]
Model format: repo_id/model_id
Options:
--model TEXT [required]
-h, --help Show this message and exit.
- lc remove
Remove an existing HuggingFace Model.
Usage:
lc remove [OPTIONS]
Model format: repo_id/model_id
Options:
--model TEXT [required]
-h, --help Show this message and exit.
- lc hardware
Check hardware compatibility for given Hugging Face model.
Usage:
lc hardware [OPTIONS]
Model format: repo_id/model_id.
Options:
--model TEXT Model name in format: repoID/modelID [required]
-h, --help Show this message and exit.
- lc exec
Execute an input prompt with given model and given task.
Usage:
lc exec [OPTIONS]
Options:
--task TEXT Specify the task name [required]
--model TEXT Specify the model name (repoID/modelID) [required]
--input TEXT Specify input text (optional)
-h, --help Show this message and exit.
- lc fetch
Fetch the logs of previous sessions.
Usage:
lc fetch [OPTIONS]
Options:
-h, --help Show this message and exit.
Predefined tasks
Command
lc list tasks
Output
Available Tasks:
- NER
- Summary
- AnalyseSentiment
- DetectBias
- TagTopic
- Custom
Command examples
- lc list models
- lc list tasks
- lc add --model ceadar-ie/FinanceConnect-13B
- lc remove --model ceadar-ie/FinanceConnect-13B
- lc hardware --model ceadar-ie/FinanceConnect-13B
- lc exec --task NER --model ceadar-ie/FinanceConnect-13B --input "Hi! I'm LLMConnect API"
- lc fetch
Code Repository
Author
CeADAR Connect Group
License
APACHE 2.0
Release files for llm-connect 2.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
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Built distribution (wheel)
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|---|---|---|---|---|
| llm_connect-2.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 20.7 kB
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Release files / llm_connect-2.0.0-py3-none-any.whl
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