From f8762e77488f3668294fc1174283c7fdc086cf25 Mon Sep 17 00:00:00 2001 From: Travis Cline Date: Fri, 21 Jun 2024 05:55:58 +0200 Subject: [PATCH] examples: Improve top level readme (#919) --- examples/README.md | 59 +++++++++++++++++++++++++--------------------- 1 file changed, 32 insertions(+), 27 deletions(-) diff --git a/examples/README.md b/examples/README.md index 0ce4ff925..55f14bd2d 100644 --- a/examples/README.md +++ b/examples/README.md @@ -1,41 +1,46 @@ -# 🎉 LangChain.go Examples +# LangChain Go Examples 🚀 -This directory contains a collection of example projects demonstrating various features and integrations of LangChain.go, a powerful library for building applications with large language models (LLMs). +Welcome to the exciting set of LangChain Go examples! 🎉 This directory tree is packed with fun and practical demonstrations of how to use LangChain with various language models and tools. Whether you're a seasoned AI developer or just starting out, there's something here for everyone! -## Contents +## What's Inside? 📦 -The examples cover a wide range of topics, including: +This collection includes examples for: -- LLM integrations (OpenAI, Anthropic, Google AI, Ollama, etc.) -- Chains and agents -- Vector stores and embeddings -- Prompt engineering -- Memory and conversation management -- Database integrations -- And more! +- Different Language Models: OpenAI, Anthropic, Cohere, Ollama, and more! +- Vector Stores: Chroma, Pinecone, Weaviate, and others for efficient similarity searches. +- Chains and Agents: See how to build complex AI workflows and autonomous agents. +- Tools and Integrations: Explore connections with Zapier, SQL databases, and more. +- Memory Systems: Learn about various memory implementations for contextual conversations. -Each example is contained in its own subdirectory with a descriptive name, making it easy to find and explore specific use cases. +## Key Features 🌟 -## Running the Examples +1. **Diverse LLM Integration**: Examples showcasing integration with multiple language models. +2. **Vector Store Demonstrations**: Practical uses of vector databases for semantic search and data retrieval. +3. **Chain and Agent Construction**: Learn to build sophisticated AI workflows and autonomous agents. +4. **Tool Usage**: See how to leverage external tools and APIs within your AI applications. +5. **Memory Management**: Explore different ways to maintain context in conversations. -To run an example: +## How to Use 🛠️ -1. Navigate to the desired example directory -2. Ensure you have the necessary dependencies installed (usually by running `go mod tidy`) -3. Set any required environment variables (e.g., API keys) -4. Run the example with `go run .` +Each example is contained in its own directory with a dedicated README and Go files. To run an example: -## Key Examples +1. Navigate to the example's directory. +2. Read the README for specific instructions and requirements. +3. Run the Go file(s) as instructed. -Some notable examples include: +## Getting Started 🚀 -- `openai-chat-example`: Demonstrates basic chat functionality with OpenAI's GPT models -- `mrkl-agent-example`: Shows how to create an agent that can use tools to solve complex tasks -- `chroma-vectorstore-example`: Illustrates using Chroma as a vector store for similarity search -- `sql-database-chain-example`: Showcases querying SQL databases using natural language +1. Clone this repository. +2. Ensure you have Go installed on your system. +3. Set up any required API keys or environment variables as specified in individual examples. +4. Dive into the example that interests you most! -## Contributing +## Contribute 🤝 -Feel free to contribute your own examples or improvements to existing ones! Please follow the established structure and include clear documentation. +Feel free to contribute your own examples or improvements! We love seeing creative uses of LangChain Go. -Happy exploring and building with LangChain.go! 🚀 +## Have Fun! 😄 + +Remember, the world of AI is vast and exciting. These examples are just the beginning. Feel free to experiment, modify, and build upon these examples to create your own amazing AI applications! + +Happy coding, and may your AI adventures be ever thrilling! 🚀🤖