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LLM Framework for UiPath Studio
by Russel A P.
0
Template
<100
Summary
Summary
Quickly build your own Generative AI powered automations using this LLM Framework Studio template.
Overview
Overview
LLM framework orchestrates template reusability across a wide array of use cases requiring the power of large language models.
These use cases generally fall under 3 categories:
- Conversational (chat-based/context-aware conversations, personal assistants)
- Transactional (queue based)
- Transactional with human in the loop
This template leverages custom Python API built on top of LangChain framework (standard framework for LLM app development).
Quick-Start Samples Included
- Simple Sequence
- Sample Implementation: Conversation Mode - Chat With Your Own Data (UiPath Forms + LLM Framework)
- Sample Implementation: Transaction Mode - Contracts Indemnification Review (Queues + LLM Framework)
Video Walkthrough
- 0:30 - LLM Framework Overview
- 1:18 - Conversational (e.g. Personal Assistants) vs Transactional (e.g. Queue based)
- 3:52 - Framework Custom Activity Components
- 4:47 - Currently Supported LLM Provider/Model
- 6:21 - Framework Activities: Sample Basic Usage
- 13:35 - LLM Framework Template Detailed Walkthrough
- 15:15 - Framework Configuration File
- 20:15 - Framework Pathways
- 22:18 - Custom Interaction Flow Rules/Validations
- 23:38 - Sample Implementation: Conversation Mode
- 29:51 - Solution Architecture
- 33:13 - Sample Implementation: Transaction Mode - Contracts Indemnifcation Review
- 41:06 - HITL Configuration - Enable Persistence
- 41:48 - HITL Configuration - Wait Activity Placeholder
- 47:14 - HITL Action Sample - Contracts Indemification Review
- 48:44 - Sample Implementation: Transaction Mode - Contracts Summarization & Deliverables Extraction
- 51:54 - HITL Action Sample - Contracts Summarization & Deliverables Extraction
- 52:48 - Closing Summary
Features
Features
🗝️ LLM Powered Custom Activities using LangChain Framework – Industry Standard for LLM App Development
- Ingest Knowledge Source – Create and serialize vector database out of provided sources such as CSV, PDF, DOCX, YouTube video links, etc.
- Converse With Context – Context-Aware, Multi-input (LLM model, context docs, memory/history, prompt template) LLM Chain
🗝️ Framework support for Conversational (Message – Response) and Transactional (Input – Process - Output) Use Cases
Additional Information
Additional Information
Dependencies
Custom Activity Package > 'LLM Framework - Langchain Activities'- https://marketplace.uipath.com/listings/llm-framework-langchain-activities > Watch this video to quickly walk you through how to setup the Python API backend and custom activity properties https://youtu.be/xCqTXhPVakY
Code Language
Visual Basic
License & Privacy
Apache
Privacy Terms
Technical
Version
2.0.1Updated
October 17, 2023Works with
Studio: 23.4+
Certification
Silver Certified
Application
Support
UiPath Community Support
Resources
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