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GenAI Apps with Python

🚀 Generative AI, LLM Compatibility & Python Implementations

📌 Overview

This repository enables Generative AI applications using various LLM models via Together AI, OpenAI, and other providers.

Key Features

  • Multi-Model Support: GPT-4 (4.1), Mistral, Llama (3, 4, Maverick), Qwen/2.5, Black-Forest FLUX, Sonic 2, M2-BERT
  • AI Chatbot & Streaming: Interactive chat with real-time response generation
  • Vision & Image Generation: AI-powered image processing and text-to-image conversion
  • TTS & Structured Outputs: Converts text into speech and generates formatted responses
  • Vector Embeddings & Retrieval: Efficient data processing for Retrieval-Augmented Generation (RAG)
  • Function Calling & AI Agents: Supports structured AI workflows

🛠 How It Works

This repository includes a RAG-based AI chatbot that extracts answers from FAQ documents by:

  1. Loading Documents 📄 – Sample FAQ files are converted into vector embeddings.
  2. Retrieving Relevant Data 🔍 – When queried, the system finds the most relevant document.
  3. Generating AI-Powered Responses 🤖 – Uses GPT-4 and other LLMs to formulate contextual answers.

🔧 Installation & Setup

Prerequisites

Ensure you have:

  • Python 3.8+
  • Required dependencies (installable via requirements.txt)
  • API keys (for Together AI / OpenAI access)

Installation Steps

git clone https://github.com/techprobin/genai_apps_python.git  
cd genai_apps_python  
pip install -r requirements.txt

🚀 Running the AI Chatbot

Using Together AI

export TOGETHERAI_API_KEY=your_togetherai_api_key  
python app_together_open_compatibility.py

Using OpenAI

pip install -r requirements_openai.txt  
export OPENAI_API_KEY=your_openai_api_key  
python openai_app.py

📂 Folder Structure

local

/genai_apps_python
│── src/ # Main Python source files
│── models/ # Pre-trained AI models
│── datasets/ # Sample FAQ documents
│── requirements.txt # Dependency list
│── docs/ # Documentation & usage guides

💡 Example Chat Session

👤 User: What is the return policy?
🤖 AI Bot: You can return any item within 30 days of purchase.

📢 Contributions

  • ✅ Fork this repo and submit PRs for improvements.
  • ✅ Feature requests are welcome via Issues.
  • ✅ Join discussions on AI model integrations.
  • ✅ Follow me and star this repo, along with more repositories of mine.
  • ✅ Like, Share, and Subscribe for timely notifications and updates.
  • ✅ Sponsor me on Patreon to support more such wonderful work and future developments.

Archived Details

RE-READ with details:

genai_apps_python

Generative AI, LLM and Python Together AI Open AI Compatibility bundle supporting GPT-4(4.1), mistral, Llama(3, 4, Maverick), Qwen/2.5, black-forest/FLUX/dev, sonic/2, m2-bert etc. Chat with a Language Model, Streaming, Vision, Image Gen, TTS, Generating Vector Embeddings, Structured Outputs, Function Calling, Agents etc. AI Code Interpreter (Python)

Run the requirements file with pip install to fulfill all installations requirements, or manually

📘 Company FAQ Chatbot – RAG Demo

This is a simple Retrieval-Augmented Generation (RAG) chatbot built using:

  • OpenAI (GPT-4) / Together AI (various models including Mixtral/, Llama(3, 4, Maverick), Qwen/2.5,
  • LangChain
  • FAISS (vector database)

🔧 How It Works

  1. Loads sample FAQ documents.
  2. Converts them into vector embeddings.
  3. At runtime, retrieves relevant documents based on your question.
  4. GPT-4 generates an answer using those documents.

🚀 Run Locally

pip install -r requirements.txt
export TOGETHERAI_API_KEY = your_togetherai_api_key
python app.py
python app_together_open_compatibility.py

pip install -r requirements_openai.txt
#OPENAI_API_KEY = your_openai_api_key
python openai_app.py

🧠 Example

👤 You: What is the return policy?
🤖 Bot: You can return any item within 30 days of purchase.