MultiAI

MultiAI is a multi-mode AI app offering five core capabilities:

• Chatbot for general conversations
• Searchbot for LLM-powered web search
• Voicebot for fully voice-driven conversations
• File Q&A for interacting with documents using Retrieval-Augmented Generation (RAG)
• An Account System to save, load, and manage your chat histories

Explore MultiAI at: https://multi-ai.streamlit.app/

Features

💬 Chatbot

A simple, general-purpose chatbot that lets you interact with a variety of open-source Large Language Models (LLMs) and explore how they handle different types of conversations.

🔎 Searchbot

Searchbot blends LLM reasoning with real-time search tools to deliver more accurate answers. The model generates search queries, retrieves results, and uses them to form responses. Currently supported search providers:

• Wikipedia: Great for factual, structured information from a trusted knowledge base.
• DuckDuckGo: A fast, privacy-focused web search engine for broad internet results.

🎙️ Voicebot

Talk to your AI assistant hands-free. The Voicebot converts your speech to text, generates a response using an LLM, and replies back with natural-sounding audio—making conversations fully voice-driven.

📝 File Q&A

Upload PDF, TXT, or Markdown files and ask questions directly about their content. This feature uses Retrieval-Augmented Generation (RAG), allowing the model to pull relevant information from your documents and generate accurate, context-aware answers—making it easy to interact with your files without reading everything manually.

⚙️ Account

Create an account or log in to sync your conversations across sessions and access your saved chat histories.

Technologies Used

Programming Language

• Python: The entire app is developed in Python.

Frontend

• Streamlit: Used to build the app's user interface.

Large Language Models (LLMs)

• Groq: Provides the LLMs for chatbot responses, search queries, and file-based Q&A.

Backend

• LangChain:
  • LangChain Core: Manages LLMs and tool interactions.
  • LangChain Agents: Used for ZERO_SHOT_REACT_DESCRIPTION agents with web search tools.
  • LangChain Community Tools: Integrates DuckDuckGo and Wikipedia for real-time web searches.
  • LangChain Document Loaders: Loads and processes PDF, TXT, and Markdown files.
  • LangChain VectorStores: FAISS is used for document embedding and retrieval.

Authentication

• Firebase: Handles user login, registration, and secure session management.

Database

• Firestore: Stores chat history for authenticated users.

Data Processing

• HuggingFace Embeddings: Utilizes all-MiniLM-L12-v2 for embedding text data in the File Q&A feature.

File Handling

• Tempfile: Manages temporary storage during file uploads.

Getting Started

Prerequisites

• Python 3.x
• Required Python libraries (see requirements.txt)

Installation

1. Clone the repository:

   git clone https://github.com/BilalM04/MultiAI.git

2. Navigate to the porject directory:

   cd MultiAI

3. Install the required libraries:

   pip install -r requirements.txt

Running the App

1. Start the app:

   streamlit run Chatbot.py

2. Open your browser and go to the localhost link specified in the command line.

Usage

• Chatbot: Start a conversation by typing in the input field and pressing Enter.
• SearchBot: Type your prompt, and the bot will use both LLMs and search tools to give you an answer.
• Voicebot: Record or upload audio, get it transcribed, receive an LLM reply, and hear the response.
• File Q&A: Upload a PDF, TXT, or MD file and ask questions related to its content.
• Account: Sign up or log in to start managing your saved chats.

Demo

Explore the live demo: MultiAI