🤖 AIUniverse - Multi-AI Agent Platform

One Window. 6 Perspectives.

Get intelligent responses from 6 different AI models simultaneously! Compare perspectives from DeepSeek, OpenAI GPT, Google Gemini, Meta Llama, Alibaba Qwen, and Moonshot Kimi K2 - all in one unified interface.

Features • Demo • Installation • Usage • Architecture • Contributing

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🌟 Overview

AIVerse is a cutting-edge multi-agent AI platform that leverages the power of 6 different state-of-the-art language models to provide diverse, comprehensive answers to your questions. By running all agents in parallel, you get instant access to multiple AI perspectives in seconds.

Why AIVerse?

• 🔄 Multiple Perspectives: Compare responses from 6 different AI models
• ⚡ Parallel Processing: All agents run simultaneously using ThreadPoolExecutor
• 🛠️ Tool-Enabled Agents: Each agent has access to weather, currency conversion, web search, and calculator tools
• 💻 Dual Interface: Choose between beautiful Streamlit web UI or CLI
• 📥 Export Responses: Download any agent's response in Markdown format
• 🎨 Modern UI: Clean, gradient-styled interface with real-time progress tracking

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Agent Capabilities

Each AI agent has access to these tools:

• 🌤️ Weather Information: Get current weather for any location
• 💱 Currency Conversion: USD to INR conversion
• 🔍 Web Search: Real-time information retrieval via Google Serper API
• 🧮 Calculator: Mathematical calculations

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🎬 Demo

Web Interface (Streamlit)

streamlit run app.py

CLI Interface

python main.py

Sample Output

Enter your query: What's the weather in New York and convert 100 USD to INR?

DeepSeek Agent Response:
The current temperature in New York is 5°C with Partly cloudy.
100 USD is equal to 8,350 INR.

OpenAI Agent Response:
New York weather: 5°C, partly cloudy conditions.
Currency: $100 = ₹8,350

[... responses from other agents ...]

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🛠️ Tech Stack

Category	Technology
Language	Python 3.11.9
Web Framework	Streamlit
AI Framework	LangChain
AI Models	Ollama, Groq, Google Gemini
Concurrency	ThreadPoolExecutor
APIs	WeatherAPI, CurrencyAPI, Google Serper API
Environment	python-dotenv

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📦 Installation

Prerequisites

• Python 3.11.9 or higher
• pip package manager
• Active internet connection
• API keys (see Configuration section)

Step 1: Clone the Repository

git clone https://github.com/yourusername/aiverse.git
cd aiverse

Step 2: Create Virtual Environment

# Windows
python -m venv venv
venv\Scripts\activate

# macOS/Linux
python3 -m venv venv
source venv/bin/activate

Step 3: Install Dependencies

pip install -r requirements.txt

Step 4: Install Ollama (for Local Models)

Download and install Ollama from ollama.ai

# Pull required models
ollama pull deepseek-v3.1:671b-cloud
ollama pull gpt-oss:120b-cloud

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⚙️ Configuration

Environment Variables

Create a .env file in the root directory:

# Weather API
WEATHER_API_KEY=your_weatherapi_key_here

# Currency API
CURRENCY_API_KEY=your_currencyapi_key_here

# Google Serper API (for web search)
SERPER_API_KEY=your_serper_api_key_here

# Groq API (for Llama, Qwen, Kimi models)
GROQ_API_KEY=your_groq_api_key_here

# Google AI API (for Gemini)
GOOGLE_API_KEY=your_google_api_key_here

API Key Sources

API	Get Key From	Free Tier
WeatherAPI	weatherapi.com	✅ Yes
CurrencyAPI	currencyapi.com	✅ Yes
Google Serper	serper.dev	✅ Limited
Groq	console.groq.com	✅ Yes
Google AI	ai.google.dev	✅ Yes

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🚀 Usage

Option 1: Streamlit Web Interface (Recommended)

streamlit run app.py

1. Open browser at http://localhost:8501
2. Enter your question in the input field
3. Click SUBMIT
4. Watch as all 6 agents process your query in parallel
5. View responses in individual tabs
6. Download any response using the download buttons

Option 2: CLI - Parallel Execution

python main.py

All 6 agents run in parallel and display results as they complete.

Option 3: CLI - Sequential Execution

python sequential_main.py

Agents run one after another (slower but more predictable).

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📁 Project Structure

AiVERSE_2.0/
│
├── app.py                  # Streamlit web application
├── main.py                 # CLI with parallel execution
├── sequential_main.py      # CLI with sequential execution
├── agents.py               # Agent configuration and initialization
├── tools.py                # LangChain tool definitions
├── google_client.py        # Google Gemini client wrapper
│
├── .env                    # Environment variables (create this)
├── .gitignore             # Git ignore file
├── requirements.txt        # Python dependencies
├── README.md              # This file
│
└── __pycache__/           # Python cache files

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🏗️ Architecture

System Flow

User Query
    ↓
ThreadPoolExecutor (6 parallel threads)
    ├── DeepSeek Agent (Ollama) ──→ Tools (Weather, Currency, Search, Calculator)
    ├── OpenAI Agent (Ollama) ────→ Tools (Weather, Currency, Search, Calculator)
    ├── Qwen Agent (Groq) ────────→ Tools (Weather, Currency, Search, Calculator)
    ├── Llama Agent (Groq) ───────→ Tools (Weather, Currency, Search, Calculator)
    ├── Kimi Agent (Groq) ────────→ Tools (Weather, Currency, Search, Calculator)
    └── Gemini Agent (Google) ────→ Direct API call
    ↓
Aggregate Responses
    ↓
Display in UI/CLI

Agent Architecture

Each LangChain agent follows this pattern:

create_agent(
    model="provider:model_name",
    system_prompt="You are a helpful assistant...",
    tools=[weather, currency, web_search, calculator]
)

Parallel Processing

Using concurrent.futures.ThreadPoolExecutor:

• All 6 agents execute simultaneously
• Responses collected as they complete
• Progress tracked in real-time
• Error handling per agent (failures don't block others)

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🔌 API Integrations

1. Ollama (Local Models)

• Models: DeepSeek V3.1, OpenAI GPT-OSS
• Setup: Install Ollama desktop app
• Endpoint: http://localhost:11434

2. Groq Cloud

• Models: Llama 3.3, Qwen 3, Kimi K2
• Speed: Ultra-fast inference
• Free Tier: Generous limits

3. Google Gemini

• Model: Gemma 3 27B IT
• Direct API: Google AI Studio

4. Weather Data

• Provider: WeatherAPI.com
• Endpoint: api.weatherapi.com/v1/current.json

5. Currency Conversion

• Provider: CurrencyAPI.com
• Endpoint: Real-time USD to INR rates

6. Web Search

• Provider: Google Serper API
• Feature: Real-time search results

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🐛 Troubleshooting

Common Issues

1. "Module not found" error

pip install -r requirements.txt

2. Ollama models not responding

# Check Ollama is running
ollama list

# Pull models if missing
ollama pull deepseek-v3.1:671b-cloud
ollama pull gpt-oss:120b-cloud

3. API key errors

• Verify all keys in .env file
• Check API key validity on provider websites
• Ensure no trailing spaces in keys

4. Streamlit not opening

# Specify port manually
streamlit run app.py --server.port 8501

5. Import errors for LangChain

pip install --upgrade langchain langchain-community

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🗺️ Roadmap

Upcoming Features

• Response comparison and summary view
• Token usage and cost tracking
• Response caching for repeated queries
• User authentication and history
• More AI models (Anthropic Claude, Mistral, etc.)
• Custom tool creation interface
• API endpoint for programmatic access
• Docker containerization
• Response quality voting system
• Export all responses to PDF

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🤝 Contributing

Contributions are welcome! Here's how you can help:

1. Fork the repository
2. Create a feature branch

   git checkout -b feature/AmazingFeature

3. Commit your changes

   git commit -m 'Add some AmazingFeature'

4. Push to the branch

   git push origin feature/AmazingFeature

5. Open a Pull Request

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⭐ Star this repo if you find it helpful!

Made with ❤️ by Yashodeep

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