🚀 LangChain + Gemini + LangSmith Application

A beginner-friendly Python project demonstrating how to build an AI application using LangChain, Google Gemini, and LangSmith.

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📌 Project Overview

This project demonstrates:

• LangChain Prompt Templates
• Google Gemini API Integration
• LangSmith Tracing
• Environment Variable Management
• Secure API Key Handling
• Python Best Practices

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🛠 Technologies Used

• Python 3.11+
• LangChain
• Google Gemini API
• LangSmith
• python-dotenv

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📂 Project Structure

LangChain-LangSmith-App/
│
├── main.py
├── .env
├── .gitignore
├── README.md
└── requirements.txt

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⚙ Installation

Clone the repository

git clone https://github.com/Krish6891/langchain-langsmith-assignment.git

Move into the project

cd langchain-langsmith-assignment

Create Virtual Environment

python -m venv .venv

Activate

Windows

.venv\Scripts\activate

Install Packages

pip install -r requirements.txt

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🔑 Configure Environment Variables

Create a .env file

GOOGLE_API_KEY=YOUR_API_KEY

LANGSMITH_API_KEY=YOUR_LANGSMITH_API_KEY

LANGSMITH_TRACING=true

LANGSMITH_PROJECT=LangChain_Assignment

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▶ Run the Project

python main.py

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📸 Sample Output

Enter your prompt:
What is LangChain?

AI Response:

LangChain is a framework that simplifies the development of AI-powered applications by connecting language models with prompts, tools, memory, and external data.

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📊 LangSmith

This project supports automatic tracing using LangSmith.

You can view:

• Prompt
• AI Response
• Execution Time
• Token Usage
• Complete Trace

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👨‍💻 Author

N. Gopalakrishnan

GitHub: https://github.com/Krish6891

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⭐ If you found this project useful, don't forget to Star the repository.