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╔╦╗╦ ╦╦ ╔╦╗╦╔╦╗╔═╗╔╦╗╔═╗╦  
β•‘β•‘β•‘β•‘ β•‘β•‘  β•‘ β•‘β•‘β•‘β•‘β•‘ β•‘  ║║╠═╣║  
β•© β•©β•šβ•β•β•©β•β•β•© β•©β•© β•© β•šβ•β•β•β•©β•β•© ╩╩═╝
        AI  AGENT             
Typing SVG

Live Demo Python Streamlit Groq BLIP


"What if AI could look at an image and talk about it like a human?" That's exactly what this does.


🧠 The Idea

Most AI is either good at text or good at images β€” rarely both.

This agent bridges that gap. Upload any image, ask any question, and watch it think through vision + language together β€” like a human would.

      You upload an image  +  You ask a question
               β”‚                      β”‚
               β–Ό                      β–Ό
         β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”          β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
         β”‚   BLIP   β”‚          β”‚  Your Text β”‚
         β”‚ (Vision) β”‚          β”‚   Query    β”‚
         β””β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”˜          β””β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”˜
              β”‚                      β”‚
              β–Ό                      β–Ό
         πŸ“ Caption ────────▢ 🧩 Combined Prompt
                                      β”‚
                                      β–Ό
                              β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
                              β”‚  LLaMA 3.3    β”‚
                              β”‚  via Groq ⚑  β”‚
                              β””β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”˜
                                      β”‚
                                      β–Ό
                              πŸ’¬ Intelligent Answer

✨ What Makes It Special

πŸ–ΌοΈ Vision Understanding Upload any image β€” photos, diagrams, screenshots, charts β€” and the agent understands what's in it before you even ask.

πŸ’¬ Natural Language Q&A Ask follow-up questions in plain English. No special syntax. No prompting tricks. Just talk.

⚑ Groq-Powered Speed LLaMA 3.3 70B running on Groq's LPU chips means answers arrive in under 2 seconds β€” not 20.

☁️ Live & Deployed Not just a local demo. Actually deployed on Streamlit Cloud and accessible from anywhere in the world.


πŸ—οΈ Tech Stack

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚                                                             β”‚
β”‚   Frontend  ──────────────────────────  Streamlit           β”‚
β”‚   Vision    ──────────────────────────  BLIP (Salesforce)   β”‚
β”‚   Language  ──────────────────────────  LLaMA 3.3 70B       β”‚
β”‚   Inference ──────────────────────────  Groq API ⚑         β”‚
β”‚   Language  ──────────────────────────  Python 3.10+        β”‚
β”‚   Hosting   ──────────────────────────  Streamlit Cloud     β”‚
β”‚                                                             β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
Layer Technology Why
πŸ–ΌοΈ Image Captioning BLIP (Salesforce) State-of-the-art vision-language model
πŸ€– LLM LLaMA 3.3 70B Open-source, powerful, free
⚑ Inference Groq API 10x faster than standard GPU inference
🎨 UI Streamlit Fast to build, beautiful to use
☁️ Deploy Streamlit Cloud Free, instant, shareable

πŸ“‚ Project Structure

multimodal-agent/
β”‚
β”œβ”€β”€ πŸ“„ app.py                 ← main streamlit app + UI
β”‚
β”œβ”€β”€ πŸ“‚ model/
β”‚   β”œβ”€β”€ πŸ–ΌοΈ  blip.py           ← image captioning pipeline
β”‚   └── πŸ€–  llm.py            ← groq + llama inference
β”‚
β”œβ”€β”€ πŸ“‚ utils/
β”‚   └── 🧩  prompt.py         ← prompt builder (caption + query)
β”‚
β”œβ”€β”€ πŸ“„ requirements.txt       ← all dependencies
β”œβ”€β”€ πŸ“„ .env                   ← GROQ_API_KEY (don't commit!)
└── πŸ“„ README.md

πŸš€ Run Locally

# 1. Clone the repo
git clone https://github.com/SHALINISAURAV/Multimodal_Agent.git
cd Multimodal_Agent

# 2. Create virtual environment
python3 -m venv venv
source venv/bin/activate        # Mac/Linux
# venv\Scripts\activate         # Windows

# 3. Install dependencies
pip install -r requirements.txt

# 4. Set your API key
echo "GROQ_API_KEY=your_api_key_here" > .env

# 5. Launch πŸš€
streamlit run app.py

πŸ”‘ Get your free Groq API key β†’ console.groq.com


πŸ” Environment Variables

GROQ_API_KEY=your_groq_api_key_here

For Streamlit Cloud deployment β€” add this in Settings β†’ Secrets (not in .env file).


🌟 Roadmap

  • πŸ–ΌοΈ Image upload + captioning
  • πŸ’¬ Text Q&A on images
  • ⚑ Groq-powered fast inference
  • ☁️ Streamlit Cloud deployment
  • 🧠 Chat history & memory
  • 🎀 Voice input support
  • πŸ‘οΈ Upgrade to LLaVA / Gemini Vision
  • πŸ“Š Multi-image comparison
  • 🌍 Multilingual support

πŸ‘©β€πŸ’» Author

Shalini Saurav

AI Developer Β· Builder

Building intelligent systems that understand the world β€” one model at a time.

GitHub


⭐ If this helped you, star the repo β€” it keeps the motivation alive!

Try Live Demo


"Building intelligent systems that understand the world like humans."

About

AI-powered multimodal agent that understands images and answers questions about them using BLIP for vision captioning and LLaMA 3.3 via Groq for reasoning. Upload any image and chat with it in real time through a fast Streamlit web app deployed on cloud. βš‘πŸ–ΌοΈπŸ€–

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