updated readme

README.md

@@ -1,33 +1,196 @@
+Here’s the rewritten section with the Streamlit app instructions integrated into the provided structure:
+
+---
+
+title: Langgraph  
+emoji: 📈  
+colorFrom: yellow  
+colorTo: red  
+sdk: streamlit  
+sdk_version: 1.41.1  
+app_file: app.py  
+pinned: false  
+license: apache-2.0  
+short_description: Langgraph  
+
+---
+
+# 🚀 LangGraph: Building Stateful AI Agents as Graphs  
+
+**Official Links**  
+- [GitHub Repository](https://github.com/langchain-ai/langgraph)  
+- [Documentation](https://langchain-ai.github.io/langgraph/)  
+- [LangChain Academy Course](https://github.com/gayashan4lk/langchain-academy-lang-graph-intro) (Free Intro)  
+- [Prebuilt Agents & Templates](https://langchain-ai.github.io/langgraph/concepts/template_applications/)  
+
+---
+
+## 📌 Overview  
+LangGraph is a Python library for creating **stateful, multi-step AI workflows** using Large Language Models (LLMs). It enables dynamic decision-making through graph-based architectures, allowing developers to design agents that loop, branch, and interact with tools/APIs. Inspired by Pregel and Apache Beam, it’s widely used by companies like LinkedIn, Uber, and Elastic.  
+
+---
+
+## 🔑 Key Features  
+1. **Graph-Based Workflows**  
+   - Define workflows as **nodes** (tasks) and **edges** (connections).  
+   - Supports **conditional edges** (e.g., "If tool call needed, route to tools node").  
+
+2. **State Management**  
+   - Persist conversation history, tool outputs, or custom data across interactions using checkpoints.  
+
+3. **Multi-Actor Support**  
+   - Build collaborative agents (e.g., one agent retrieves data, another generates responses).  
+
+4. **Prebuilt Agents**  
+   - Use templates like `create_react_agent` for ReAct-style agents or customize workflows.  
+
+5. **LangGraph Platform** (Commercial)  
+   - Deploy agents at scale with streaming, background runs, and monitoring.  
+
+---
+
+## 🛠️ Getting Started  
+
+### Installation  
+```bash
+pip install -U langgraph  # Core library 
+pip install langchain_groq streamlit  # For Groq models and Streamlit UI
+```
+
+### Basic Example: ReAct Agent  
+```python
+from langgraph.prebuilt import create_react_agent
+from langchain_groq import ChatGroq  # Changed import
+import os
+
+# Define a search tool (remains the same)
+@tool
+def search(query: str):
+    if "san francisco" in query.lower():
+        return "60°F, foggy"
+    return "90°F, sunny"
+
+# Initialize agent with Groq
+model = ChatGroq(
+    temperature=0,
+    model_name="mixtral-8x7b-32768"  # Groq model name
+)
+checkpointer = MemorySaver()  # Persists state
+app = create_react_agent(model, [search], checkpointer=checkpointer)
+
+# Invoke with thread_id for state retention (same)
+response = app.invoke(
+    {"messages": [{"role": "user", "content": "Weather in SF?"}]},
+    config={"configurable": {"thread_id": 42}}
+)
+print(response["messages"][-1].content)  # Outputs weather details
+```
+
+Key:  
+1. Uses `langchain_groq.ChatGroq`  
+2. Specifies Groq model name (`mixtral-8x7b-32768` or `llama2-70b-4096`)  
+3. Requires `GROQ_API_KEY` environment variable  
+
+Set your API key:  
+```python
+os.environ["GROQ_API_KEY"] = "your-key-here"
+```
+
 ---
-title: Langgraph
-emoji: 📈
-colorFrom: yellow
-colorTo: red
-sdk: streamlit
-sdk_version: 1.41.1
-app_file: app.py
-pinned: false
-license: apache-2.0
-short_description: Langgraph
+
+## 🚀 Running the Streamlit App  
+
+This project includes a Streamlit-based web interface for interacting with the Groq ReAct Agent. Follow the steps below to set up and run the app.  
+
+### Prerequisites  
+1. **Python 3.8+**: Ensure Python is installed on your system.  
+2. **Groq API Key**: Obtain your API key from the [Groq Cloud Console](https://console.groq.com/).  
+
+### Steps to Run  
+1. Clone the repository:  
+   ```bash
+   git clone https://github.com/aitiwari/langgraph.git
+   cd langgraph
+   ```
+
+2. Install the required dependencies:  
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+3. Set your Groq API key as an environment variable:  
+   ```bash
+   export GROQ_API_KEY="your-api-key-here"
+   ```
+
+4. Start the Streamlit app:  
+   ```bash
+   streamlit run app.py
+   ```
+
+5. Open your browser and navigate to the URL provided in the terminal (usually `http://localhost:8501`).  
+
+### Using the App  
+- **Input Field**: Type your question or query in the chat input box at the bottom of the screen.  
+- **Chat History**: The conversation history will be displayed above the input field.  
+- **API Key**: If you didn't set the `GROQ_API_KEY` environment variable, you'll be prompted to enter it in the app.  
+
+### Example Queries  
+- "What's the weather in San Francisco?"  
+- "Tell me about the weather in New York."  
+
+### Stopping the App  
+To stop the Streamlit app, press `Ctrl+C` in the terminal where the app is running.  
+
+---
+
+## 🌟 Use Cases  
+
+### 1. Basic Chatbot  
+**Prompt**: What is generative AI?  
+**Reference**:  
+![alt text](basic_chatbot.png)  
+
+### 2. Chatbot with Tool  
+**Prompt**: Latest news from the India vs Australia match?  
+**Reference**:  
+![alt text](chatbot_with_search_tool.png)  
+
+### 3. Appointment Receptionist  
+**Prompt 1**: Book an appointment for priti.  
+**Prompt 2**: Yes or No.  
+**Reference**:  
+![alt text](appointment_receptionist.png)  
+
+### 4. Customer Support  
+**Reference**:  
+![alt text](cs_flow.png)  
+![alt text](customer_support.png)  
+
 ---
 
-# Langgraph
-## UseCases
+## 📚 Templates & Community  
+Explore prebuilt templates for chatbots, retrieval agents, and more:  
+```bash
+langgraph new  # CLI to create apps from templates 
+```  
+| Template          | Description                          | Link                                   |  
+|-------------------|--------------------------------------|----------------------------------------|  
+| ReAct Agent       | Tool-calling agent with memory       | [GitHub](https://github.com/langchain-ai/langgraph/tree/main/examples) |  
+| Retrieval Agent   | RAG with dynamic context fetching    | [Docs](https://langchain-ai.github.io/langgraph/concepts/template_applications/) |  
 
-### 1. Basic Chatbot
-reference:
-![alt text](basic_chatbot.png)
+---
+
+## 📖 References  
+1. [Official Documentation](https://langchain-ai.github.io/langgraph/)  
+2. [GitHub Examples](https://github.com/langchain-ai/langgraph/tree/main/examples)  
+3. [Agentic RAG Guide](https://medium.com/@wendell_89912/building-an-agentic-rag-with-langgraph-a-step-by-step-guide-009c5f0cce0a)  
+4. [Production Case Studies](https://blog.langchain.dev/top-5-langgraph-agents-in-production-2024/)  
 
-### 2. Chatbt with Tool
-reference:
-![alt text](chatbot_with_search_tool.png)
+---
 
-### 3. Appointment Receptionist
-reference:
-![alt text](appointment_receptionist.png)
+For advanced use cases (multi-agent systems, human-in-the-loop), refer to the [LangGraph Platform](https://www.langchain.com/langgraph) or explore the [LangChain Academy](https://github.com/gayashan4lk/langchain-academy-lang-graph-intro).  
 
-### 4. Customer Support
-reference: 
-![alt text](cs_flow.png)
-![alt text](customer_support.png)
+--- 
 
+This version integrates the Streamlit app instructions seamlessly into the existing structure while maintaining the original tone and style.