- Semantic Kernel
- Microsoft's open-source orchestration framework
- Strong .NET and C# integration
- Built-in memory management and connectors
- Great for enterprise Windows/.NET environments
- Plugins system for extending functionality
- LangChain
- Popular Python/JavaScript framework
- Strong community and extensive documentation
- Built-in agents and chains
- Many integrations with different LLM providers
- Good for rapid prototyping
- Other Notable Frameworks:
a. LlamaIndex (formerly GPT Index)
- Specialized in data ingestion and indexing
- Great for RAG (Retrieval Augmented Generation)
- Strong document handling capabilities
- Built-in vector store integrations
b. Haystack
- Focus on production-ready search and question answering
- Strong document processing pipeline
- Good for building search applications
- Modular architecture
c. AutoGen
- Microsoft's framework for building agent-based applications
- Multi-agent conversations
- Good for complex task automation
- Built-in agent templates
d. OpenAI Assistants API
- Native OpenAI solution
- Built-in function calling
- Code interpreter capabilities
- File handling and retrieval
e. Guidance
- Structured prompting framework
- Fine-grained control over LLM outputs
- Good for templating and consistency
- Strong type checking
f. Flowise
- Visual programming interface for LLM apps
- No-code/low-code solution
- Drag-and-drop interface
- Good for prototyping
g. LangFlow
- Visual tool similar to Flowise
- Built on top of LangChain
- Visual flow builder
- Good for experimentation
If you're working in a specific environment or have particular requirements, I can provide more detailed recommendations on which framework might be best suited for your needs.
