What it is
LangGraph is a library from the LangChain team that lets you build agents and workflows using a stateful graph abstraction. Each node in the graph can be an LLM call, retriever, or any LangChain component.

Key features

• Graph-based logic: Create multi-step workflows with branches, memory, and loops.
• Built on LangChain: Seamlessly integrates with LangChain components.
• Concurrency support: Run parts of the graph in parallel.
• Fine control: Handle state transitions and failures easily.
• Perfect for agents: Design complex tool-using agents with long-term memory.

What it is
DSPy is an open-source framework from Stanford for programming, rather than prompting, language-model workflows. You define small, natural-language Python modules, and DSPy compiles them into pipelines whose prompts (and even weights) are tuned automatically

Key features

• Declarative modules: Write jobs as readable Python functions with NL “signatures”; no handcrafted prompt fiddling.
• Auto-optimization: Built-in Teleprompter algorithms (e.g., BootstrapFewShot) learn optimal prompts/weights from data.
• Composable pipelines: Chain modules to build RAG flows, agent loops, or evaluators out-of-the-box.
• Model-agnostic: Swap backends, OpenAI, Anthropic, local Llama-family models, without code changes.
• Production-ready: MIT-licensed, light-weight (pip install dspy-ai), latest v2.6.27 (released Jun 3 2025).