Unify Integration for Prompt Flow

Introduction

This tool package provides access to numerous endpoints and custom routers, with the option to employ dynamic routing to obtain responses from the best-suited model@provider for your task.

Requirements

PyPI package: unify-integration.

• For local users:

  pip install unify-integration
  

  Recommended to be used with the VS Code extension for Prompt flow.

Unify-specific inputs (optional)

Overview

This repository provides an integration between Unify and Promptflow, allowing seamless optimization of large language models (LLMs) using Unify's capabilities. With this integration, users can dynamically select the optimal model based on quality, cost, and latency constraints, as well as benchmark models for specific tasks.

Project Structure

.
 dist/                          # Distribution files for installation
    unify_integration-0.0.14-py3-none-any.whl
    unify_integration-0.0.14.tar.gz
 tests/                         # Test files for the Unify integration
    __init__.py
    quick_test.py              # Quick tests for package tools
    test_unify_llm_tool.py     # Unit tests for Unify LLM tool functionality
    test_unify_llm.py          # Additional unit tests for Unify LLM
 unify_llm_tool/                # Unify tool package and connection settings
    __init__.py
    connections/
       unify_connection.yml   # Configuration for the Unify connection
    examples/                  # Example workflows for Unify integration
 tools/                         # Tools available in the Unify integration
    yamls/
       benchmark_llm_tool.yaml # YAML for the benchmark LLM tool
       chat_tool.yaml          # YAML for the chat tool
       optimize_llm_tool.yaml  # YAML for the LLM optimization tool
       single_sign_on_tool.yaml # YAML for Single Sign-On tool
 .gitignore                     # Git ignore file
 .pre-commit-config.yaml        # Pre-commit hooks configuration
 generate_icon_data_uri.py      # Script to generate base64 icons for the project
 LICENSE                        # License file
 MANIFEST.in                    # Manifest for including package data
 README.md                      # Project README file
 requirements.txt               # Required dependencies
 setup.cfg                      # Configuration for flake8, isort, etc.
 setup.py                       # Setup script for the project
 unify_icon.png                 # Icon for the project

Installation

To install the project, you can either download the wheel or install the unify_integration package via pip:

pip install unify_integration-0.0.14-py3-none-any.whl

Alternatively, install directly from PyPI:

pip install unify-integration

Tools and Features

1. Optimize LLM Tool

Optimize LLM selection based on task constraints like quality, cost, and time. The YAML file configuration allows customization of these parameters.

unify_llm_tool.tools.optimize_llm_tool.optimize_llm:
  function: optimize_llm
  inputs:
    unify_api_key: '{{env: UNIFY_API_KEY}}'
    quality: "1"
    cost: "4.65e-03"
    time_to_first_token: "2.08e-05"

2. Benchmark LLM Tool

Benchmark multiple LLMs against a set of inputs to determine the best-performing model for a given task.

3. Chat Tool

Allows you to interact with custom endpoints using predefined or dynamic prompts.

4. Single Sign-On Tool

Single sign-on integration with multiple endpoints, streamlining the authentication process for various services.

Testing

The tests/ directory contains unit tests for each tool. You can run the tests using:

pytest tests/

License

This project is licensed under the MIT License.