Gemini 2.5 AGENTS: Powerful AI Agents BY Gemini Can DO ANYTHING For FREE!

Key Concepts

• Gemini 2.5 Pro: Google's advanced AI model for building intelligent agents and automating tasks.
• Agentic AI: AI systems designed to perform tasks autonomously.
• Multimodal Capabilities: AI models that can process various types of data, such as images, text, and speech.
• Structured Function Calling: Integrating external tools and functions into AI models.
• Vector Shift: An all-in-one AI platform for building AI apps and automations using a drag-and-drop interface.
• Pipelines: A series of interconnected nodes in Vector Shift that define the workflow of an AI agent.
• Nodes: Individual components within a Vector Shift pipeline that perform specific tasks.
• List Node: A feature in Vector Shift that provides consistency when processing multiple attachments within an email.
• AI Operation Node: A node in Vector Shift used for data transformation tasks, such as extracting data or categorizing information.

Gemini 2.5 Pro and Agentic AI

• Google has released Gemini 2.5 Pro, an AI model designed for advanced Agentic AI applications.
• It is marketed as a powerful tool for building intelligent agents and automating end-to-end tasks with precision and speed.
• Gemini 2.5 Pro is currently the most intelligent AI model available, delivering top-tier performance while remaining cost-efficient.
• It offers powerful multimodal capabilities, including image generation, text-to-speech, and advanced tool use.
• It supports structured function calling, which integrates search as a tool and can even execute code.
• Gemini 2.5 Pro empowers users to build AI agents with built-in agent capabilities for free.
• It is lightweight, fast, and intuitive, making sophisticated agent creation easier and more accessible.

Vector Shift Overview

• Vector Shift is an all-in-one AI platform that allows users to build AI apps and automations through a simple drag-and-drop interface.
• It is incredibly easy to get started and completely free.
• The platform features a revamped dashboard for managing pipelines and templates.
• Ready-made templates are available for automating various integrations and categories, such as knowledge assistance and chatbots.
• Users can manage pipelines, knowledge files, and other resources through the left-hand panel.

Building an AI Agent with Vector Shift and Gemini 2.5 Pro: Automating Invoice Processing

• The video demonstrates how to create an AI agent that automates the process of handling invoices directly from email using Vector Shift and Gemini 2.5 Pro.
• The agent extracts key details like price, invoice number, and other important fields without requiring any code.

Step-by-Step Process

1. Setting up the Gmail Trigger Node:
   • Place a Gmail node in the Vector Shift drag-and-drop interface.
   • Configure the node to trigger the pipeline whenever emails are sent to the inbox.
   • Connect the Gmail account and select the trigger event as "new mail in inbox."
2. Handling Multiple Invoices with the List Node Feature:
   • Create a new pipeline to process the extraction of content from the invoice.
   • Use the list node feature to provide consistency when processing multiple attachments within the email.
3. Extracting Content from the Invoice:
   • Place an input node to process files (invoices).
   • Add an AI operation node to extract data from the invoice.
   • Configure the input node to process files and output text.
   • Connect the input node to the AI operation node and specify the fields to extract, such as vendor name and date.
   • Example: Extract the vendor name and date, specifying the desired output format for the date.
4. Categorizing Invoices:
   • Place another AI operation node and select the categorization feature.
   • Connect the input node to the categorization node to categorize different types of invoices (e.g., food, utilities).
   • Define category names and descriptions to process the different fields and categorize them.
5. Outputting Data to a Google Sheet:
   • Place a Google Sheet node from the integration tab.
   • Configure the node to add a new row to the Google Sheet.
   • Connect the Google Sheet account and select the desired spreadsheet.
   • Map the extracted data fields (e.g., vendor, invoice date) to the corresponding columns in the Google Sheet.
   • Example: Map the "vendor" field from the extraction data node to the "vendor" column in the Google Sheet.
6. Sending a Summary Email (Optional):
   • Place a text node to specify the text categories to process with natural language.
   • Add a Google large language model node and select Gemini 2.5 Pro.
   • Provide a system instruction to specify what you want to have processed.
   • Connect the text node to the language model node and configure it to output text.
   • Configure a Gmail node to send a summary email back to the sender.
7. Connecting the Pipelines:
   • In the master pipeline, place a pipeline node and connect the previously created pipeline.
   • Turn on list mode to process multiple files.
   • Place a data transformation node as list ops to flatten the list of lists.
   • Connect the node and select the list to join.
   • Add another Gmail node to send a reply back to the person who sent the email, processing the flattened text.
8. Deploying and Testing:
   • Deploy the changes and test the pipeline by sending an invoice to the configured email address.
   • Verify that the data is extracted, categorized, and added to the Google Sheet.
   • Check that a summary email is sent back to the sender.

Conclusion

• The video demonstrates how to easily build AI agents with powerful automation capabilities using Vector Shift and Gemini 2.5 Pro.
• The example showcases automating invoice processing, extracting key details, categorizing invoices, and outputting data to a Google Sheet.
• Vector Shift simplifies the process of creating AI agents with its drag-and-drop interface and pre-built nodes.
• Gemini 2.5 Pro provides the intelligence and multimodal capabilities needed for advanced AI applications.