Back to Projects
Generative AI · Chatbots Intermediate

🤖 Intelligent Multi-modal Chatbot Suite

Production-ready chatbot suite built with LangFlow for visual pipeline design, supporting text, documents, and structured data with Google AI and Groq.

View on GitHub
LangFlow Visual Design
Multi-modal Input Types
Production Ready

Project Overview

The Intelligent Multi-modal Chatbot Suite is a production-ready system for building and deploying enterprise chatbots that understand multiple input modalities — plain text, uploaded PDF documents, and structured database data — using a unified LangFlow visual pipeline.

LangFlow's drag-and-drop interface allows rapid prototyping of conversational AI flows without deep coding, while still exposing the underlying Python for customization. Google Studio AI provides powerful reasoning and long-context understanding, while Groq ensures ultra-low-latency responses for user-facing interactions.

The suite includes a REST API server for enterprise integration, enabling deployment as a Slack bot, Teams bot, or website chat widget with minimal configuration.

What You'll Learn

  • Design chatbot pipelines visually using LangFlow's node-based interface
  • Handle multi-modal inputs: text queries, PDF uploads, and database queries
  • Integrate Google Studio AI for advanced reasoning and long-context tasks
  • Use Groq for real-time, low-latency conversational responses
  • Build conversation memory and context management for multi-turn chats
  • Deploy chatbot as a REST API for Slack, Teams, or web widget integration

System Architecture

User Input
Multi-modal
LangFlow
Pipeline
Google AI / Groq
LLM
Memory
Context
REST API
Server
Integrations
Deploy

Project Breakdown

01
LangFlow Setup

Installing LangFlow, exploring the component library, and creating first conversational flows.

02
Multi-modal Inputs

Adding PDF loaders, database connectors, and structured data parsers as input nodes.

03
LLM Integration

Connecting Google Studio AI (Gemini) and Groq (Llama-3) nodes with proper API key management.

04
Memory Management

Implementing ConversationBufferMemory and ConversationSummaryMemory for long conversations.

05
API Deployment

Exporting the LangFlow pipeline as a REST API and adding authentication, rate limiting, and logging.

06
Enterprise Integrations

Building Slack and Teams adapters and a web chat widget using the deployed API.