Langchain Review
VisitOpen-source framework for building applications with large language models
LangChain is an open-source framework for developing applications powered by large language models.
AI Panel Score
0 AI reviews
Open-source framework for building applications with large language models
LangChain is an open-source framework for developing applications powered by large language models.
AI Panel Score
0 AI reviews
LangChain is an open-source framework designed to help developers build applications that leverage large language models (LLMs). The framework provides a standardized interface for working with various LLM providers, including OpenAI, Anthropic, and others, allowing developers to switch between models or use multiple models within the same application.
The framework is built around several core concepts including chains, agents, memory, and retrievers. Chains allow developers to combine multiple components into sequential workflows, while agents can make decisions about which tools to use based on user input. Memory components enable applications to maintain context across interactions, and retrievers help connect LLMs to external data sources.
LangChain targets software developers, data scientists, and AI researchers who want to build production-ready applications with LLMs. Common use cases include chatbots, question-answering systems, document analysis tools, and automated content generation applications. The framework includes pre-built components for common tasks while remaining flexible enough for custom implementations.
As an open-source project, LangChain has gained significant adoption in the AI development community. It competes with other LLM application frameworks and provides both Python and JavaScript implementations. The project is actively maintained and has extensive documentation and community support.
Offers reusable LLM-as-judge and multi-turn evals to score agents automatically, with calibration via human feedback.
Provides AI-driven insights to uncover patterns across traces from agent runs.
Breaks each agent run into a structured timeline of steps so developers can see exactly what happened, in what order, and why.
Supports both online and offline scoring modes to evaluate agent performance in production and pre-deployment.
Allows users to describe tasks in plain language and turn them into recurring autonomous agents that act across daily tools and improve with feedback.
Allows human reviewers to annotate agent outputs and provide feedback used for eval calibration and iterative improvement.
Supports human-in-the-loop interactions, input concurrency, and background agents in the deployment layer.
Provides durable checkpointing on fault-tolerant infrastructure so long-running agents can handle failures and resume execution.
Supports message threading for multi-turn chat interactions within agent traces.
Provides a scalable, distributed runtime designed to handle agent swarms and any production workload.
Provides native protocol support for Agent-to-Agent (A2A) communication and Model Context Protocol (MCP) for extending agent capabilities.
Provides native tracing support for popular agent frameworks and OpenTelemetry, with SDKs for Python, TypeScript, Go, and Java.
AI panel reviews are being generated for this product.
Common questions answered by our AI research team
The Plus plan costs $39 per seat per month, then pay as you go for additional usage.
No. LangSmith does not use your data to train models. Your traces, prompts, and outputs remain private to your organization.
LangSmith SDKs support Python, TypeScript, Go, and Java.
Yes. Enterprise plans support hybrid and self-hosted deployment options so data doesn't leave your VPC.
Yes. LangSmith includes native tracing for popular agent frameworks and OpenTelemetry.
Company
LangchainFounded
2022Pricing
FreeFree Plan
Available
LangChain is a San Francisco-based company that maintains the open-source LangChain framework and offers LangSmith, an LLM observability platform.
