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!
This collection includes examples for:
- 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.
- Diverse LLM Integration: Examples showcasing integration with multiple language models.
- Vector Store Demonstrations: Practical uses of vector databases for semantic search and data retrieval.
- Chain and Agent Construction: Learn to build sophisticated AI workflows and autonomous agents.
- Tool Usage: See how to leverage external tools and APIs within your AI applications.
- Memory Management: Explore different ways to maintain context in conversations.
Each example is contained in its own directory with a dedicated README and Go files. To run an example:
- Navigate to the example's directory.
- Read the README for specific instructions and requirements.
- Run the Go file(s) as instructed.
- Clone this repository.
- Ensure you have Go installed on your system.
- Set up any required API keys or environment variables as specified in individual examples.
- Dive into the example that interests you most!
Feel free to contribute your own examples or improvements! We love seeing creative uses of LangChain Go.
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! 🚀🤖