Add Langchain quickstart guide and notebook demo

docs/en/solutions/How_to_Create_an_AI_Agent_with_Langchain.md

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+---
+products:
+   - Alauda AI
+kind:
+   - Solution
+ProductsVersion:
+   - 4.x
+---
+
+# How To Create AI Agent with Langchain
+
+## Overview
+
+Langchain is a framework for developing applications powered by language models. It provides tools and abstractions for building AI agents that can interact with users, access external tools, and perform complex reasoning tasks. This guide provides a quickstart example for creating an AI Agent using Langchain.
+
+## Prerequisites
+
+- Access to a Notebook environment (e.g., Jupyter Notebook, JupyterLab, or similar)
+- Python environment with Langchain dependencies installed
+
+## Quickstart
+
+A simple example of creating an AI Agent with Langchain is available here: [langchain_quickstart.ipynb](/langchain/langchain_quickstart.ipynb). Download and upload it to a Notebook environment to run.
+
+The notebook demonstrates:
+- Environment setup and dependency installation
+- Tool definition using the `@tool` decorator (weather query tool example)
+- LLM model initialization and configuration
+- Agent creation with tools and system prompts
+- Agent execution and result handling
+- FastAPI service deployment for production use
+
+## Additional Resources
+
+For more resources on developing AI Agents with Langchain, see:
+
+- [Langchain Documentation](https://docs.langchain.com/oss/python/langchain/overview) - The official Langchain documentation where all usage-related documentation can be found.
+- [Langchain Academy](https://academy.langchain.com/) - The official Langchain Academy provides extensive educational resources. The [Foundation Introduction to Langchain Python](https://academy.langchain.com/courses/foundation-introduction-to-langchain-python) course introduces the fundamentals of developing Agents with Langchain.