Can You Tell Me About LLM Agents:Executing Series of Tasks in Loops Until Completing Final Objective
Agentic nature of the LLMs is created by the Prompts fed to it. Starting with the objective of completing a complex tasks, prompts and prompt templates play a major role. The logic & loops of the programming language are leveraged by the LLMs to repetitively work on the tasks to complete the objective. We introduce the same, and much more in the video.
Chapter Navigation:
0:00 Intro
0:50 Pre-Requisite Videos
2:35 Demo of Agent with Explanation
3:30 Agent Asks for Objective
5:45 Reviewing the Created Tasks
6:10 Agent Classifies Tasks
6:55 Agent Analyses Data
7:50 Agent Generate Code and completes
8:45 Reviewing Generated Code
9:50 Code Walkthrough of Agent
10:50 Module Imports
11:30 Setting System Prompts
12:45 Jinja Templating Engine Started
13:00 Explaining LLM helper functions
14:00 Why Json Files
15:15 Loading & explaining Prompt Templates
16:50 Explaining available Tasks
17:10 Keeping the Agent Live with Loop
18:00 Choosing Ask_tasks to get Objective
21:55 Classifying sub-Tasks
23:30 Generating code for sub-tasks
24:25 Analyse sub-Tasks
25:30 Exiting the Agent Loop
26:15 Recap of Objective
27:15 Recap on Agent Development
28:50 Outro
The data and the code is located at
D:\gitFolders\python_de_learners_data\code_script_notebooks\projects\exploring_agents
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