LangChain Chat Models

A clean and modular collection of LangChain chat model integrations using multiple LLM providers including OpenAI, Google Gemini, Anthropic Claude, and Hugging Face.

Tech Stack

• Python
• LangChain
• OpenAI API
• Google Gemini API
• Anthropic API
• Hugging Face
• Transformers
• python-dotenv

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Project Structure

langchain-chat-models/
│
├── models/
│   ├── openai_chat_model.py
│   ├── gemini_chat_model.py
│   ├── anthropic_chat_model.py
│   ├── huggingface_endpoint.py
│   └── huggingface_pipeline.py
│
├── screenshots/
├── .env.example
├── .gitignore
├── requirements.txt
└── README.md

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Features

• Multi-provider LLM integration
• API-based and local model execution
• LangChain chat model abstraction
• Environment variable management
• Clean and beginner-friendly implementation

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Installation

Clone the repository

git clone https://github.com/your-username/langchain-chat-models.git

Navigate to the project directory

cd langchain-chat-models

Install dependencies

pip install -r requirements.txt

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Environment Variables

Create a .env file and add the following keys:

OPENAI_API_KEY=your_openai_api_key
GOOGLE_API_KEY=your_google_api_key
ANTHROPIC_API_KEY=your_anthropic_api_key
HUGGINGFACEHUB_API_TOKEN=your_huggingface_api_token

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Running the Project

Example:

python models/openai_chat_model.py

Similarly, you can run:

• gemini_chat_model.py
• anthropic_chat_model.py
• huggingface_endpoint.py
• huggingface_pipeline.py

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Learning Outcomes

• LangChain chat model integrations
• Prompt invocation using .invoke()
• Working with multiple LLM providers
• Hugging Face endpoints and pipelines
• API key and environment management

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Author

Vrundali Rahangdale