ChatGPT Knowledge Base Assistant

AI chatbot assistant powered by OpenAI GPT-4o that automatically searches and leverages internal company documents to answer user questions. Delivers context-aware, accurate, and conversational responses using both chat history and retrieved knowledge, making it ideal for customer support, internal helpdesks, or onboarding.

How the AI Flow works - ChatGPT Knowledge Base Assistant

How the AI Flow works

User submits a question

Receives user input via chat interface.

Retrieve relevant internal documents

Searches internal knowledge sources for information related to the user's query.

Build context-aware prompt

Combines user question, retrieved documents, and chat history to create a comprehensive prompt for AI.

Generate AI-powered answer

Uses OpenAI’s GPT-4o to generate a conversational, context-aware response.

Deliver response to user

Displays the AI-generated answer in the chat for the user.

Prompts used in this flow

Below is a complete list of all prompts used in this flow to achieve its functionality. Prompts are the instructions given to the AI model to generate responses or perform actions. They guide the AI in understanding user intent and generating relevant outputs.

Prompt

Create a prompt template with dynamic variables ({input}, {human_input}, {context}, {chat_history}, {system_message}).

                You are an AI language model assistant.

Your task is to answer customer query in INPUT with consideration of previous conversation in CHAT HISTORY.

If CONTEXT is provided, use it to generate the answer.


--- CONTEXT START
{context} 
--- CONTEXT END

--- CHAT HISTORY START
{chat_history}
--- CHAT HISTORY END

--- INPUT START
{input}
--- INPUT END
Answer in Language: {lang}
Format answer with markdown.

ANSWER:

Components used in this flow

Below is a complete list of all components used in this flow to achieve its functionality. Components are the building blocks of every AI Flow. They allow you to create complex interactions and automate tasks by connecting various functionalities. Each component serves a specific purpose, such as handling user input, processing data, or integrating with external services.

Flow description

Purpose and benefits

ChatGPT with Internal Knowledge Workflow

This workflow creates a chatbot interface that combines the conversational abilities of OpenAI’s ChatGPT 4o with the power to search and respond using internal company or organizational documents. It is designed to provide accurate, context-aware answers to user queries, leveraging both chat history and relevant knowledge sources.

Overview

  • Purpose: To automate and scale customer support, internal information access, or knowledge management tasks by enabling users to chat with an AI assistant that references both previous conversations and internal documentation.
  • Key Features:
    • Responds to user queries with up-to-date, contextually relevant information.
    • Searches internal documents automatically for supporting content.
    • Maintains awareness of chat history for coherent, multi-turn conversations.
    • Presents responses in markdown format for readability.

Workflow Structure

Below is a breakdown of the main components and their roles in the workflow:

ComponentDescription
Chat InputCaptures user messages and file uploads.
Chat Opened TriggerDetects when a new chat session starts.
Message WidgetDisplays a welcome message to the user at chat start.
Chat OutputDelivers messages (including welcome and AI-generated responses) to the user interface.
Chat HistoryStores and retrieves the last 10 chat exchanges (up to 8000 tokens) for context.
Document RetrieverWhen a user asks a question, this searches internal documents for relevant content.
Prompt TemplateCrafts a prompt for the AI, including user input, document context, and chat history.
GeneratorRuns the prompt through ChatGPT 4o (or another LLM), generating a response.

How the Workflow Operates

  1. Chat Session Initialization

    • When a user opens a new chat, the Chat Opened Trigger signals the workflow.
    • A welcome message is displayed using the Message Widget and shown via Chat Output.

  2. Handling User Queries

    • When the user enters a message:
      • The Chat Input node collects it.
      • In parallel:
        • The message is sent to the Document Retriever to search for up to 2 relevant internal documents.
        • The message is also passed to the Prompt Template for AI processing.

  3. Contextual Response Preparation

    • The workflow gathers:
      • The latest chat history for context.
      • Relevant documents found by the retriever.
      • The user’s current query.
    • These elements are merged in the Prompt Template, which instructs the AI to:
      • Answer considering the user’s question, previous conversation, and any document context found.
      • Format the response in markdown, and answer in the user’s language.

  4. AI Response Generation

    • The Generator node sends the prompt to the selected language model (e.g., ChatGPT 4o).
    • The generated answer is sent to Chat Output for display to the user.

Automation & Scaling Benefits

  • Consistency & Quality: Ensures users receive consistent, high-quality answers that are grounded in internal documentation and sensitive to prior conversation context.
  • Efficiency: Automates the tedious task of searching through knowledge bases, saving time for both users and support staff.
  • Scalability: Can handle many simultaneous user sessions and queries, making it ideal for organizations with high support or information demands.
  • Customization: The prompt template and document search parameters can be tailored for specific use cases, industries, or internal policies.

Example Use Cases

  • Internal Helpdesk: Employees can quickly get answers about company policies, IT procedures, or HR matters.
  • Customer Support: Customers receive accurate product or service information without waiting for a human agent.
  • Sales Enablement: Sales teams can access the latest product specs, case studies, or pitch materials on demand.
  • Knowledge Management: Ensures valuable institutional knowledge is accessible and actionable via natural language queries.

Visual Summary

Workflow Steps:

  1. User opens chat → Welcome message displayed.
  2. User asks a question.
  3. System retrieves:
    • Chat history
    • Relevant documents
  4. AI prompt is constructed (includes user input, chat history, document context).
  5. ChatGPT generates a response.
  6. Response is shown to user.

This workflow is a powerful template for anyone looking to enhance their chatbot or virtual assistant with contextual, document-aware intelligence—significantly improving user experience and operational efficiency.

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