LangChain-for-LLM-Application-Development

Credits

This repository and its contents were inspired by the excellent course LangChain for LLM Application Development offered by DeepLearning.AI.

Special thanks to:

• Andrew Ng: Founder of DeepLearning.AI and Co-founder of Coursera, for his visionary leadership in AI education.
• Harrison Chase: Co-Founder and CEO of LangChain, for his expertise and contributions to advancing language model applications.

Purpose

This repository is dedicated to the development of applications using LangChain for Large Language Models (LLMs). It provides various examples and tutorials to help users understand and implement LangChain in their projects.

Installation

To install the required dependencies, run the following command:

pip install -r requirements.txt

Usage

This repository contains several Jupyter notebooks that demonstrate different aspects of LangChain for LLM application development.

L1-Model_prompt_parser.ipynb

This notebook covers the following topics:

• Direct API calls to Gemini
• API calls through LangChain:
  • Prompts
  • Models
  • Output parsers

L2-Memory.ipynb

This notebook covers the following topics:

• ConversationBufferMemory
• ConversationBufferWindowMemory
• ConversationTokenBufferMemory
• ConversationSummaryMemory

L3-Chains.ipynb

This notebook covers the following topics:

• LLMChain
• Sequential Chains
  • SimpleSequentialChain
  • SequentialChain
• Router Chain

L4-QnA.ipynb

This notebook covers the following topics:

• Q&A over Documents
• Using embeddings for document retrieval
• Building a retrieval-based QA system

L5-Evaluation.ipynb

This notebook covers the following topics:

• Example generation
• Manual evaluation (and debugging)
• LLM-assisted evaluation
• LangChain evaluation platform

L6-Agents.ipynb

This notebook covers the following topics:

• Using built-in LangChain tools: DuckDuckGo search and Wikipedia
• Defining your own tools

Contribution Guidelines

We welcome contributions to this repository. If you have any improvements or new examples to add, please follow these steps:

1. Fork the repository
2. Create a new branch for your feature or bugfix
3. Commit your changes
4. Push the branch to your fork
5. Create a pull request

License

This project is licensed under the MIT License. See the LICENSE file for more details.