This repository is a hands-on implementation of LLMOps using the LangChain framework — designed to explore how to build, deploy, and monitor Large Language Model (LLM) applications efficiently.
🔗 Inspired by entbappy/Latest-LangChain-LLMOps
This project demonstrates the end-to-end lifecycle of building an AI-powered application using LangChain, with a focus on operationalizing LLMs (Large Language Models) through modern MLOps practices.
Key areas covered:
- LLM pipeline development using LangChain
- Integration with OpenAI and other model providers
- Building modular chains and agents
- Experiment tracking with tools like MLflow
- Deployment-ready structure for scalable use
| Category | Tools & Frameworks |
|---|---|
| Language | Python 3.10+ |
| LLM Framework | LangChain |
| Model Provider | OpenAI API |
| Environment | Conda / venv |
| Experiment Tracking | MLflow |
| Deployment | FastAPI / Docker |
| Version Control | Git & GitHub |
# Clone the repository
git clone https://github.com/TausifM/LangChain-Practice
# Navigate into the project directory
cd LangChain-Practice
# Create and activate virtual environment
conda create -n llmapp python=3.11 -y
conda activate llmapp
# Install dependencies
pip install -r requirements.txt# Run the application
python app.pyModify configuration settings (API keys, model type, etc.) inside config.py before running.
- ✅ Modular LLM pipeline with LangChain
- ✅ Prompt engineering and chaining
- ✅ Experiment tracking and metrics logging
- ✅ Scalable architecture for deployment
- ✅ Easy customization for your own use cases
├── app.py
├── config.py
├── requirements.txt
├── src/
│ ├── chains/
│ ├── utils/
│ ├── components/
│ └── data/
└── README.md
- Integration with vector databases (FAISS / Pinecone)
- Real-time dashboards for monitoring
- CI/CD for LLM pipelines
Contributions, feedback, and ideas are welcome! Fork this repo, create a new branch, and submit a pull request.
Tausif M 💼 GitHub: TausifM 💬 Open to collaborations in AI, LangChain, and MLOps.
This project is licensed under the MIT License — feel free to use and modify it for your learning or projects.
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