VIDEO
HIGHLIGHT
Log InSign up
MIAMLDS I VIRTUAL MOD 11 SESION 10 DR PABLO
SummaryTranscriptChat

MIAMLDS I VIRTUAL MOD 11 SESION 10 DR PABLO

Workflow Setup and Integration of AI Models

Introduction to Workflow

  • The session begins with a greeting and an introduction to opening a workflow for the day, focusing on activities from the previous Wednesday and the final project for Unit 4.

Working with AI Agents

  • The instructor emphasizes starting directly with agents, integrating two primary models: OpenAI and Gemini, while mentioning other models like Olama and Cloue.
  • Participants are instructed to create a chat trigger as part of their workflow setup, highlighting the importance of configuring AI agents correctly.

Configuring Chat Agents

  • A detailed explanation is provided on how to give instructions to the agent using prompts. The configuration process involves setting parameters based on desired outcomes.
  • The instructor discusses manual configuration options versus automated triggers, indicating that choices depend on specific tasks at hand.

Executing Chat Functions

  • Demonstration of executing a chat function begins with a simple greeting ("hello") to test agent responses.
  • Participants are guided in defining basic prompts for their agents, emphasizing clarity in communication for effective functionality.

Troubleshooting Agent Connections

  • An issue arises where the chat is not connected to any model; participants learn that they need to assign a "brain" (model) to their agent for it to function properly.

Integrating OpenAI and Gemini Models

Choosing AI Models

  • The instructor explains that OpenAI is commonly used but requires payment; Gemini is presented as a free alternative suitable for those unable to access OpenAI due to payment issues.

Model Configuration Steps

  • Instructions are given on selecting models within the chat interface. Participants must ensure they have proper credentials set up before proceeding.

Credential Setup Process

  • Guidance is provided on logging into OpenAI's platform, including creating new secret keys necessary for integration.
  • Emphasis is placed on saving these credentials securely in case of future disconnections or project changes.

How to Create and Connect API Credentials

Copying and Pasting Notes

  • The speaker suggests copying text from a notepad into a blog for safekeeping.
  • Acknowledges the extensive character count of the content being copied, indicating it may be lengthy.

Creating New Credentials

  • Instructions are given on creating new credentials, specifically naming them (e.g., BDN8N).
  • Emphasizes pasting the previously copied information into the APK section.

Saving and Testing Connections

  • After pasting, users should rename it to match their project name (BD-N8N-2) before saving.
  • Users can select different models; currently, GPT 4.1 is mentioned as an option.

Troubleshooting Connection Issues

  • The speaker encounters a problem with node detection due to payment issues related to using GPT.
  • Discusses token costs associated with GPT usage and expresses preference for using Gemini as a free alternative.

Switching to Gemini Model

Transitioning Models

  • Users are instructed to delete previous settings and switch to the Gemini model for simplicity.

Accessing Cloud Services

  • Guidance is provided on accessing cloud services by searching for "Gemini Apicates."

Creating API Keys in Google Studio

  • Steps include clicking on Google Studio, creating an API key, and naming it similarly (BD N8N 2).

Finalizing Project Creation

  • Users must choose "create project" after entering their project name before closing that window.

Testing the Connection with Gemini

Verifying Output Functionality

  • After connecting successfully, users test functionality by asking questions; responses indicate successful setup.

Understanding Response Patterns

  • The output consistently responds with "A vencer, capitán," demonstrating programmed behavior based on user input.

Connecting Other Models

Overview of Additional Models

  • Speaker mentions that while they have connected Gemini successfully, other models can also be integrated following similar procedures.

Future Learning Resources

  • Plans are shared about providing supplementary video materials next week for those interested in working with additional models.

Understanding User Input Requirements

Importance of User Input

  • Clarifies that all necessary input must be gathered so that system messages can effectively process outputs.

Logic Behind System Messages

  • Highlights how user inputs influence system message actions leading to appropriate outputs during interactions.

Understanding Memory Nodes in AI Tools

Introduction to Tool Usage

  • The speaker notes that all tools are primarily in English, with some elements appearing in Spanish due to browser translation.
  • It is recommended to first create requests in Spanish and then translate them into English for better results when using GPT or other models.

Exploring Memory Nodes

  • A new node labeled "memory" is introduced, which contains various types of memory options including simple memories for beginners and advanced ones like Phat Memory and SATA.
  • For initial exercises, the basic memory option will be utilized, with plans to incorporate more complex memories later.

Connecting to Basic Memory

  • Users are instructed to click on the basic memory icon; it automatically connects to the node without additional steps required.
  • The system saves conversations within this memory structure, allowing users to track interactions similar to how GPT retains context from previous queries.

Importance of Contextualization

  • The speaker emphasizes that once a conversation is stored in memory, there’s no need for re-contextualization in subsequent questions as the AI retains prior information.

Practical Application and Workflow Setup

  • Instructions are given for downloading a time information agent workflow and sharing it via WhatsApp for collaborative use.

Utilizing Tools Within AI Agents

Overview of Time Information Agent

  • The time information agent can launch chats that utilize tools for real-time data retrieval such as weather updates or news articles.

Connecting Additional Tools

  • Users can connect various tools by clicking on the "tools" node; examples include HTP among others previously discussed.

Engaging with the Chatbot

  • Users are encouraged to ask specific questions like weather inquiries or technology news through the chatbot interface after activating their workflows.

Customizing Agent Responses

  • The agent can handle multiple message types and allows users to add more tools for enhanced functionality.

Adjusting System Messages

  • Users can edit system messages within the agent's settings, influencing its behavior and response style based on user input.

Understanding Methodological Structure in AI Agents

Introduction to Methodological Structure

  • The speaker introduces the concept of methodological structure, referencing previous discussions on prompt engineering.
  • Emphasizes the importance of translating prompts from Spanish to English for effective communication with AI models.

Working with Prompts

  • Demonstrates how to create a prompt by copying and pasting into a notepad for clarity.
  • Defines the role of an AI agent within N8N, highlighting its friendly and helpful nature designed for user interaction.

Functionality and Purpose of AI Agents

  • The primary goal is to showcase capabilities using available tools while responding intelligently to user inquiries.
  • Explains that the AI operates within a simple workflow, utilizing key elements like tools and memory for context understanding.

Tool Selection and User Interaction

  • Instructions are provided on selecting tools based on user requests; actions should only be taken when specific requests are made.
  • Illustrates an example where a calculator tool is used, emphasizing the need for clear instructions before executing tasks.

Best Practices in Tool Management

  • Discusses reliability in complex processes, suggesting structured workflows over solely relying on agents for critical tasks.
  • Recommends maintaining a focused set of tools (10 to 15), ensuring reliability and preventing misuse.

Conclusion and Next Steps

  • Concludes with encouragement to start working with the discussed methodologies while noting that simple memory functions will not be utilized initially.

HTP Requests as a Database

Overview of HTP Requests

  • The speaker discusses using HTP requests as a database for values, highlighting parameters such as date, temperature in Celsius, and ranges.
  • Emphasis is placed on defining variables like latitude and longitude. While Spanish is accepted, it’s recommended to work in English for optimization.

Methodology Changes

  • Introduction of the GET method alongside POST; this allows for parameter specification across different variable ranges.
  • The use of the GET method enables users to request specific data based on defined parameters.

Output Insights

  • The output displays requested information including latitude, longitude, time zone, and other temporal details.
  • A new tool for embedding sources is introduced; users can specify databases from which to extract information.

Utilizing Sources in Queries

Source Integration

  • Users are encouraged to provide specific sources for data extraction to enhance response accuracy.
  • If specified sources lack information, the system defaults to its internal model before seeking external data.

Interaction with Chatbot

  • Demonstration of chatbot interaction begins; users are prompted to confirm functionality with greetings and queries about weather or news updates.

Engaging with the Chatbot

User Queries

  • The chatbot introduces itself and offers assistance with various inquiries such as weather conditions or news updates.
  • An example query about Paris's weather illustrates how users can interact conversationally with the bot.

Error Handling and Features

  • Discussion on service errors when querying features like N8N advantages; troubleshooting steps are suggested during user interactions.

Template Management

Working with Templates

  • Users are advised on duplicating existing templates for efficiency in creating agents or workflows within the system.
  • Emphasis on modifying templates rather than starting from scratch encourages best practices in workflow management.

Project Duplication and Integration

Duplicating Projects for Template Preservation

  • The speaker emphasizes the importance of duplicating a project to maintain the template, encouraging participants to personalize their agents with unique styles and functionalities.

Desired Outputs from n8N

  • The goal is to have outputs returned to a Google Doc while simultaneously receiving messages on Telegram, ensuring real-time updates during interactions in the chat.

Real-Time Response Mechanism

  • Participants are instructed that when they ask questions in the chat, responses should be updated in real-time both in the document and via Telegram notifications.

Time Allocation for Task Completion

  • A time frame of 20 minutes is set for participants to implement these features, after which they will share their screens to demonstrate functionality.

Progress Check and Suggestions

Status Update on Project Functionality

  • The speaker checks if anyone has successfully implemented the project yet; most participants indicate they need more time (10-15 minutes).

Working Methodology Recommendation

  • It’s advised to work incrementally ("node by node") rather than attempting everything at once, which can lead to errors or confusion.

Unit Activity Overview

Introduction of New Unit Activity

  • The speaker introduces an activity related to unit number three, requiring two files (JSON and Word format) from specific participants who previously engaged in discussions.

Integration Focus: Telegram and Google Docs

  • Emphasis is placed on integrating Telegram with Google Docs as part of this unit's activities, highlighting its relevance for future tasks.

Future Plans and Learning Objectives

Upcoming Session Details

  • Tomorrow's session will focus on building a secretary bot tailored for individual needs using tools already covered in previous lessons.

Essential Tools Discussion

  • Mention of utilizing OpenAI's Gemini tool alongside Google Docs indicates an expansion into advanced integrations within their projects.

Final Thoughts and Questions

Recap of Learning Goals

  • Participants are reminded that all discussed elements will be broken down into manageable parts for better understanding during tomorrow’s session.

Open Floor for Queries

  • An invitation is extended for questions regarding alternative applications being used by participants, promoting creativity in project development.