Doc Chatbot
This use case involves building a chatbot that processes a provided document and generates responses based on its content. The chatbot analyses the text, extracts key information, and delivers structured answers, providing an efficient way to interact with and retrieve insights from the document.
_(2)-Photoroom/w=3840,quality=90,fit=scale-down)
Key Features of Doc Chatbot
- Structured Responses – Formats chatbot replies into bullet points, tables, or sections for better readability and quick understanding.
- Multimodal Support – Processes text, images, and documents seamlessly for context-aware responses.
- Prompt Engineering – Optimizes chatbot queries for accuracy, relevance, and improved answer quality.
- Real-time File Extraction – Retrieves and integrates relevant content from documents dynamically.
- Secure Chat Deployment – Controlled access to designated platforms via allowed domains.
- High-Quality AI Responses – Uses Gemini (gemini-1.5-pro-latest) for intelligent, context-aware interactions.
- Quick and Efficient Processing – Ensures low response time for user queries.
- Fully Managed Deployment – Hassle-free implementation without infrastructure concerns.
Architecture
This guide walks you through setting up an AI-powered chat widget that can process user queries in real time by leveraging file extraction and advanced language models.
The process starts by using the Chat Widget Node as the trigger, defining the allowed domains where the chat widget will be accessible. This ensures controlled and secure deployment across designated platforms.
Next, the Extract From File Node is used to retrieve relevant content from a specified file by providing its URL and datatype. This extracted information is then passed to the Text LLM Node, where it is incorporated into the prompt along with user and chat messages. By selecting Gemini (gemini-1.5-pro-latest) as the language model, the system ensures high-quality, context-aware responses. Finally, the processed response is delivered back to the user through the Chat Response Node, enabling seamless and intelligent interactions.
How it Works?
Tools used
- Chat Widget Node.
- Extract From File Node.
- Text LLM Node.
Benefits
- Structured Responses – Delivers well-organized, easy-to-read answers.
- Quick Response Time – Processes queries efficiently for fast replies.
- Multimodal Processing – Handles text, images, and documents seamlessly.
- Accurate & Context-Aware Answers – Uses optimized prompt engineering for precision.
- Secure & Controlled Deployment – Restricts access to allowed domains.
- Fully Managed Deployment – No infrastructure or maintenance hassle.
- Scalability – Supports high-volume interactions effortlessly.
- Enhanced User Experience – Ensures smooth, intuitive chatbot interactions.