RAG Workflow For Company Documents stored in Google Drive
For Google Drive, this automated workflow efficiently manages company documents by integrating LangChain and AI capabilities. It enables real-time updates and retrieval of information, ensuring employees can quickly access relevant company policies and documents. The system automatically processes new or updated files, enhancing knowledge sharing and support within the organization.
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Workflow Overview
For Google Drive, this automated workflow efficiently manages company documents by integrating LangChain and AI capabilities. It enables real-time updates and retrieval of information, ensuring employees can quickly access relevant company policies and documents. The system automatically processes new or updated files, enhancing knowledge sharing and support within the organization.
Target Audience
- HR Professionals: This workflow is ideal for HR teams looking to automate responses to employee queries using internal documents stored in Google Drive.
- Document Managers: Individuals responsible for managing company documents can benefit from streamlined document updates and retrieval processes.
- IT Administrators: Those managing integrations between various tools like Google Drive, LangChain, and Pinecone will find this workflow useful for maintaining data flow and accuracy.
- Data Analysts: Analysts needing quick access to company policies and documents for reporting or analysis can leverage this automation to retrieve information efficiently.
Problem Solved
This workflow addresses the challenge of efficiently retrieving and utilizing company documents stored in Google Drive to answer employee inquiries. By automating the process of document updates, embeddings, and retrieval, it significantly reduces response times and improves the accuracy of information provided to employees, ensuring that they receive timely and relevant answers based on the latest company policies.
Workflow Steps
- Trigger Events: The workflow begins with the manual trigger or automatically when files are created or updated in a specific Google Drive folder.
- File Download: When a file is created or updated, it is downloaded from Google Drive.
- Text Splitting: The downloaded document is processed using a Recursive Character Text Splitter to break it into manageable chunks for better embedding.
- Generate Embeddings: The text chunks are then converted into embeddings using Google Gemini, which helps in understanding the content better.
- Insert into Vector Store: The generated embeddings are inserted into a Pinecone Vector Store for efficient retrieval later.
- AI Agent Interaction: An AI agent is set up to respond to employee queries, utilizing the vector store to fetch relevant information when a chat message is received.
- Response Generation: The AI agent uses the Google Gemini chat model to generate responses based on the retrieved information, ensuring accurate and helpful answers are provided to employees.