LangChain- LangChain is a framework for building
applications powered by LLMs (Large Language Models). It helps developers
connect language models with external data sources and tools. Modular framework
for building LLM apps.
Key Features:
- Chains: Combine multiple steps (e.g., prompt → model → output) into a
workflow.
- Agents: Enable LLMs to make decisions and utilize tools dynamically (e.g., calculators, search engines).
- Memory: Store context across interactions for more personalized
responses.
- Integrations: Connects with APIs, databases, files,
and other services.
LangGraph -- LangGraph is built on top of LangChain and is
designed for creating stateful, multi-step workflows using a
graph-based architecture. Extension for building stateful, multi-step,
and dynamic workflows using LangChain. LangGraph builds on
LangChain by introducing graph-based workflows, which allow
for non-linear, stateful, and dynamic execution
paths.
Key Features:
- Graph-based execution: Nodes represent steps, and edges define
transitions.
- State management: Keeps track of the conversation or task
state across steps.
- Looping and branching: Supports complex logic like retries,
conditionals, and loops.
LangSmith - it is a developer platform created
by the makers of LangChain to help you debug, test, and monitor applications
built with language models.
Key Features: LangSmith provides tools for:
- Tracing: to see how your LLM app executes step-by-step (prompts,
responses, tool calls).
- Debugging: Identify where issues arise in
complex chains or agent workflows.
- Evaluation: Run automated or manual tests to assess
quality and reliability.
- Monitoring: Track performance and usage over time in
production environments.
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