https://github.com/tech-aakash/langchain-agents
Basic of langchain & lang graph to create agents with Azure OpenAI
https://github.com/tech-aakash/langchain-agents
langchain langchain-python langgraph langgraph-python prompt-engineering prompt-tuning
Last synced: about 1 month ago
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Basic of langchain & lang graph to create agents with Azure OpenAI
- Host: GitHub
- URL: https://github.com/tech-aakash/langchain-agents
- Owner: tech-aakash
- Created: 2025-06-13T06:04:04.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-06-13T10:12:47.000Z (12 months ago)
- Last Synced: 2025-06-13T11:23:29.833Z (12 months ago)
- Topics: langchain, langchain-python, langgraph, langgraph-python, prompt-engineering, prompt-tuning
- Language: Jupyter Notebook
- Homepage: https://www.triumphai.in/blog
- Size: 806 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# LangChain-Agents: Modern AI Agents with Azure OpenAI & LangGraph
A beginner-friendly, **hands-on repo** for building real conversational AI agents using **LangChain**, **LangGraph**, and **Azure OpenAI**.
---
## 🌟 Why This Repo?
- ✅ **Azure-Ready:** Everything runs on your Azure OpenAI endpoints.
- ✅ **Agent Foundations:** Learn to create and orchestrate agents using the latest LangChain & LangGraph patterns.
- ✅ **Clear Examples:** Notebooks for prompt templates, chat memory, and more.
- ✅ **Memory That Scales:** Use modern, multi-turn chat memory (LangGraph style).
- ✅ **Perfect for Beginners & Tinkerers:** Minimal setup, maximum learning.
---
## 📂 Repository Structure
| File/Notebook | Purpose |
|--------------------------------|------------------------------------------|
| `Basic Agent.ipynb` | Build your first agent with LangChain |
| `PromptTemplate.ipynb` | Dynamic prompt engineering in action |
| `PromptTemplateTypes.ipynb` | Multi-variable prompt templates |
| `ConversationBufferMemory.ipynb`| Chat memory (LangGraph & LangChain) |
| `MemoryChatDemo/main.py` | Streamlit app demonstrating chat memory |
---
---
## 🚀 Run the Chat Memory Demo (Streamlit)
Experience multi-turn chat memory in action using **LangGraph** and **LangChain**, all powered by **Streamlit**.
### 🛠️ Steps to Launch
1. **Clone the repository**
```bash
git clone https://github.com/tech-aakash/LangChain-Agents.git
cd LangChain-Agents
2. **Navigate to the demo folder**
```bash
cd MemoryChatDemo
3. **Lunch the Streamlit App**
```bash
streamlit run main.py