# langchain-ai/langchainjs

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17,818 stars · 3,216 forks · TypeScript · MIT

## Links

- GitHub: https://github.com/langchain-ai/langchainjs
- Homepage: https://docs.langchain.com/oss/javascript/langchain/
- awesome-repositories: https://awesome-repositories.com/repository/langchain-ai-langchainjs.md

## Description

LangChain.js is a framework for building, executing, and monitoring stateful agentic applications. It provides an orchestration engine that models workflows as directed graphs, allowing developers to connect language models, data sources, and external tools into modular, multi-step processes.

The platform distinguishes itself through its focus on stateful execution and human-in-the-loop control. It manages agent lifecycles by persisting execution state across threads, enabling fault tolerance and the ability to pause workflows at designated breakpoints for manual review or modification. This architecture supports both autonomous agent orchestration and complex multi-agent systems, with built-in capabilities for streaming real-time execution updates and managing long-term memory.

Beyond core orchestration, the project offers a comprehensive suite of tools for the entire application lifecycle. This includes integrated observability for tracing and evaluating agent performance, schema-enforced data serialization for reliable communication, and extensive support for deployment, security, and infrastructure management.

The project provides a TypeScript-based software development kit and a command-line interface to facilitate local development, testing, and deployment of agentic workflows.

## Tags

### Artificial Intelligence & ML

- [Agentic Workflow Orchestration](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-workflow-orchestration.md) — Orchestrates complex, stateful AI agent systems that use memory, tools, and multi-step reasoning to complete tasks.
- [Autonomous Agent Orchestration](https://awesome-repositories.com/f/artificial-intelligence-ml/autonomous-agent-orchestration.md) — Provides a framework for building stateful, autonomous agents with planning, memory, and human-in-the-loop control. ([source](https://docs.langchain.com/langsmith/deploy-self-hosted-full-platform.md))
- [Agent State Persistence](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-state-persistence.md) — Persists agent execution state in checkpoint databases to ensure continuity across restarts and conversation turns. ([source](https://docs.langchain.com/langsmith/deploy-google-adk.md))
- [Autonomous Agent Definitions](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/integration-deployment/agent-frameworks/configuration-and-specifications/autonomous-agent-definitions.md) — Defines autonomous agents by bundling instructions, tools, and sub-components into executable workflows. ([source](https://docs.langchain.com/langsmith/context-engineering-concepts.md))
- [Agentic Workflow Engines](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-workflow-engines.md) — Executes complex, multi-step agentic processes that maintain state across conversation threads and support asynchronous background task management.
- [Agentic Workflow Graphs](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-workflow-graphs.md) — Models agentic workflows as directed graphs to support complex multi-agent orchestration and execution. ([source](https://docs.langchain.com/langsmith/agent-server.md))
- [AI Agent Orchestration Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-agent-orchestration-frameworks.md) — Orchestrates stateful, multi-agent applications by connecting language models, tools, and data sources into modular, graph-based workflows.
- [LLM Application Frameworks](https://awesome-repositories.com/f/artificial-intelligence-ml/llm-application-frameworks.md) — Provides a framework for building applications powered by large language models using modular abstractions for prompts, tools, and data integration.
- [LLM Application Platforms](https://awesome-repositories.com/f/artificial-intelligence-ml/llm-application-platforms.md) — Provides a comprehensive framework for building, testing, and deploying stateful agentic applications and workflows. ([source](https://cdn.jsdelivr.net/gh/langchain-ai/langchainjs@main/README.md))
- [Agent Execution Runtimes](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/integration-deployment/agent-frameworks/agent-runtimes/agent-execution-runtimes.md) — Manages the core execution loop, state persistence, and tool orchestration for stateful and stateless agent runs. ([source](https://docs.langchain.com/langsmith/agent-server-api/system/api-documentation.md))
- [LLM Application Development](https://awesome-repositories.com/f/artificial-intelligence-ml/generative-ai-resources/generative-ai/llm-application-development.md) — Provides a toolkit for developing, testing, and deploying intelligent agents with support for persistent memory and streaming responses.
- [Human-in-the-Loop Workflows](https://awesome-repositories.com/f/artificial-intelligence-ml/human-in-the-loop-workflows.md) — Integrates manual review and approval steps into automated agent workflows to ensure oversight and control over critical decisions.
- [Agent Communication Protocols](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-communication-protocols.md) — Facilitates message exchange with autonomous assistants using standardized protocols for task triggering and response streaming. ([source](https://docs.langchain.com/langsmith/agent-server-api/a2a/a2a-json-rpc.md))
- [Agent Debugging Tools](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-debugging-tools.md) — Provides an interactive environment to inspect node states, modify execution flow mid-run, and replay specific checkpoints for troubleshooting. ([source](https://docs.langchain.com/langsmith/deployment.md))
- [Agent Configuration Management](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/agent-capabilities-skills-tooling/agent-management/agent-configuration-management.md) — Organizes agent instructions and tools into versioned bundles for promotion across environments. ([source](https://docs.langchain.com/langsmith/context-hub.md))
- [Assistant Lifecycle Management](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/agent-capabilities-skills-tooling/assistant-management/assistant-lifecycle-management.md) — Initializes assistant instances with specific versions to serve as the foundation for automated tasks. ([source](https://docs.langchain.com/langsmith/agent-server-api/assistants/create-assistant.md))
- [Human-in-the-loop Workflows](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/agent-orchestration-multi-agent/control-flow-and-workflows/human-in-the-loop-workflows.md) — Integrates human review and approval steps directly into agent workflows before tool calls proceed. ([source](https://docs.langchain.com/langsmith/core-capabilities.md))
- [Concurrency Managers](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/integration-deployment/agent-frameworks/agent-runtimes/concurrency-managers.md) — Coordinates concurrent message handling during active runs through queuing, cancellation, and parallel processing. ([source](https://docs.langchain.com/langsmith/core-capabilities.md))
- [AI Agent Skills](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-agent-skills.md) — Packages agent capabilities into versioned, reusable skills for research, formatting, and analysis. ([source](https://docs.langchain.com/langsmith/context-engineering-concepts.md))
- [External Tool Integrations](https://awesome-repositories.com/f/artificial-intelligence-ml/external-tool-integrations.md) — Attaches external functions or tools to prompts to enable models to perform actions outside their internal knowledge base. ([source](https://docs.langchain.com/langsmith/create-a-prompt.md))
- [Conversation Threads](https://awesome-repositories.com/f/artificial-intelligence-ml/language-model-orchestration/conversation-management/conversation-threads.md) — Groups execution runs into persistent threads to maintain context and accumulated output history. ([source](https://docs.langchain.com/langsmith/agent-server-api/system/api-documentation.md))
- [Multi-Agent Orchestration Systems](https://awesome-repositories.com/f/artificial-intelligence-ml/multi-agent-orchestration-systems.md) — Enables the coordination of multiple autonomous agents to execute complex, collaborative workflows. ([source](https://docs.langchain.com/langsmith/deployment.md))
- [Structured Output Parsers](https://awesome-repositories.com/f/artificial-intelligence-ml/structured-output-parsers.md) — Enforces structured data schemas on model outputs to ensure reliable programmatic integration. ([source](https://docs.langchain.com/langsmith/create-a-prompt.md))
- [Agent-to-Agent Communication](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-communication-protocols/agent-to-agent-communication.md) — Facilitates direct data exchange between independent agents using standardized communication protocols. ([source](https://docs.langchain.com/langsmith/core-capabilities.md))
- [Agent Deployment Management](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-deployment-management.md) — Publishes agent code to managed cloud environments and supports self-hosted containerized deployments. ([source](https://docs.langchain.com/langsmith/deployment-quickstart-da.md))
- [Agent Streaming Interfaces](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/integration-deployment/agent-frameworks/agent-runtimes/agent-streaming-interfaces.md) — Provides interfaces for streaming real-time execution updates and lifecycle events during agent operations. ([source](https://docs.langchain.com/langsmith/agent-server-api/streaming/protocol-v2-command.md))
- [Agent Prompt Templates](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/integration-deployment/agent-frameworks/configuration-and-specifications/agent-prompt-templates.md) — Constructs reusable prompt templates with dynamic variables for consistent agent behavior. ([source](https://docs.langchain.com/langsmith/create-a-prompt.md))
- [AI Agent Integration SDKs](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-agent-integration-sdks.md) — Exposes deployed agents through SDKs to enable programmatic integration into external applications. ([source](https://docs.langchain.com/langsmith/cicd-pipeline-example.md))
- [Model Configuration](https://awesome-repositories.com/f/artificial-intelligence-ml/model-configuration.md) — Configures model persona, tone, and behavior through system instructions and few-shot examples. ([source](https://docs.langchain.com/langsmith/create-a-prompt.md))
- [Structured Output Enforcements](https://awesome-repositories.com/f/artificial-intelligence-ml/structured-output-enforcements.md) — Enforces schemas on inputs and outputs to ensure reliable communication between agents and external systems.
- [Agent Configurations](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/agent-orchestration-multi-agent/autonomous-agents/agent-configurations.md) — Enables the creation of specialized agent versions by adjusting prompts, models, and tools within structured configurations. ([source](https://docs.langchain.com/langsmith/assistants.md))
- [Execution Breakpoints](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/agent-orchestration-multi-agent/control-flow-and-workflows/human-in-the-loop-workflows/execution-breakpoints.md) — Allows pausing workflow execution at designated nodes for manual review, debugging, or oversight. ([source](https://docs.langchain.com/langsmith/add-human-in-the-loop.md))
- [Model Provider Integrations](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/model-integration-serving/ai-model-orchestration/model-provider-integrations.md) — Connects external model services or local proxies to environments for consistent testing and pipeline execution. ([source](https://docs.langchain.com/langsmith/custom-endpoint.md))
- [Execution Checkpointing](https://awesome-repositories.com/f/artificial-intelligence-ml/execution-checkpointing.md) — Enables stopping ongoing graph invocations and restoring state from previous checkpoints. ([source](https://docs.langchain.com/langsmith/agent-server-api/thread-runs/cancel-run.md))
- [Model Serialization](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-deployment-and-serving/serialization-and-export-formats/model-serialization.md) — Converts complex agent state and data structures into standard formats for storage and retrieval. ([source](https://docs.langchain.com/langsmith/caching.md))
- [Model Context Protocol Implementations](https://awesome-repositories.com/f/artificial-intelligence-ml/model-context-protocol-implementations.md) — Implements the Model Context Protocol to connect intelligent agents with external tools and data sources. ([source](https://docs.langchain.com/langsmith/agent-server-api/mcp/mcp-post.md))
- [Modular AI Components](https://awesome-repositories.com/f/artificial-intelligence-ml/modular-ai-components.md) — Links shared skills and sub-agents across projects to ensure automatic updates. ([source](https://docs.langchain.com/langsmith/context-engineering-concepts.md))

### Data & Databases

- [Agent State Persistence](https://awesome-repositories.com/f/data-databases/agent-state-persistence.md) — Maintains durable checkpoints and long-term memory across execution threads to ensure task continuity and state retention. ([source](https://docs.langchain.com/langsmith/deploy-other-frameworks.md))
- [Retrieval Augmentation](https://awesome-repositories.com/f/data-databases/retrieval-augmentation.md) — Integrates external data sources and vector stores with language models to provide context-aware responses. ([source](https://cdn.jsdelivr.net/gh/langchain-ai/langchainjs@main/README.md))
- [State Checkpointing](https://awesome-repositories.com/f/data-databases/state-checkpointing.md) — Persists agent state at every graph node to enable fault tolerance and workflow resumption.
- [Persistent State Management](https://awesome-repositories.com/f/data-databases/persistent-state-management.md) — Provides a long-term key-value store accessible across conversation threads for shared state management. ([source](https://docs.langchain.com/langsmith/agent-server-api/system/api-documentation.md))
- [Cloud Database Provisioning](https://awesome-repositories.com/f/data-databases/cloud-database-provisioning.md) — Automates the creation and management of persistent database storage for stateful agent workflows. ([source](https://docs.langchain.com/langsmith/control-plane.md))
- [Data Schema Definitions](https://awesome-repositories.com/f/data-databases/data-schema-definitions.md) — Enforces data consistency for model inputs and outputs using predefined schema types. ([source](https://docs.langchain.com/langsmith/dataset-json-types.md))
- [Data Storage Optimizers](https://awesome-repositories.com/f/data-databases/data-storage-optimizers.md) — Minimizes storage footprint for large data histories through checkpoint pruning and delta-based updates. ([source](https://docs.langchain.com/langsmith/agent-server-changelog.md))
- [Storage Backend Adapters](https://awesome-repositories.com/f/data-databases/storage-backend-adapters.md) — Provides interfaces for swapping default storage mechanisms with custom persistent backends and specialized indexing strategies. ([source](https://docs.langchain.com/langsmith/custom-store.md))

### Software Engineering & Architecture

- [Graph-Based Workflow Orchestrators](https://awesome-repositories.com/f/software-engineering-architecture/graph-based-workflow-orchestrators.md) — Models agentic workflows as directed graphs to manage state transitions and logic flow.
- [Human-in-the-Loop Workflows](https://awesome-repositories.com/f/software-engineering-architecture/human-in-the-loop-workflows.md) — Pauses graph execution at designated breakpoints to allow manual review and modification of agent state.
- [External Tool Integrations](https://awesome-repositories.com/f/software-engineering-architecture/application-frameworks/autonomous-agent-frameworks/external-tool-integrations.md) — Encapsulates external functions into modular interfaces for dynamic invocation by agents.
- [Event-Driven Architectures](https://awesome-repositories.com/f/software-engineering-architecture/event-driven-architectures.md) — Dispatches real-time execution updates and partial responses through an asynchronous event-driven pipeline.
- [Asynchronous Task Queues](https://awesome-repositories.com/f/software-engineering-architecture/asynchronous-task-queues.md) — Orchestrates asynchronous job execution through task queues to enable concurrent processing and streaming. ([source](https://docs.langchain.com/langsmith/agent-server.md))

### System Administration & Monitoring

- [Agent Observability](https://awesome-repositories.com/f/system-administration-monitoring/agent-observability.md) — Monitors, traces, and evaluates the performance of autonomous agents to debug execution flows and ensure output quality.
- [Agent Observability Platforms](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/observability-platforms/distributed-tracing-execution-analysis/agent-observability-platforms.md) — Traces, evaluates, and monitors the performance, cost, and execution trajectories of language model applications in production.
- [Agent Execution Tracing](https://awesome-repositories.com/f/system-administration-monitoring/agent-execution-tracing.md) — Automatically captures and logs agent invocations, tool usage, and model interactions for visibility in monitoring dashboards. ([source](https://docs.langchain.com/langsmith/annotate-traces-inline.md))
- [LLM Performance Monitoring](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/observability-platforms/metric-performance-monitors/llm-performance-monitoring.md) — Assesses agent responses using real-world scenarios, automated assertions, and LLM-based grading to measure performance and accuracy. ([source](https://docs.langchain.com/langsmith/composite-evaluators-sdk.md))
- [Observability Instrumentation](https://awesome-repositories.com/f/system-administration-monitoring/observability-instrumentation.md) — Wraps functions to automatically capture inputs, outputs, and execution hierarchies for detailed observability of application logic. ([source](https://docs.langchain.com/langsmith/control-plane.md))
- [Performance Visualization](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/observability-platforms/metric-performance-monitors/performance-visualization.md) — Aggregates trace data into prebuilt or custom dashboards to provide real-time insight into system behavior and performance metrics. ([source](https://docs.langchain.com/langsmith/compare-experiment-results.md))
- [Observability Platforms](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/observability-platforms.md) — Hosts a centralized system for tracking, evaluating, and monitoring the performance and behavior of language model applications. ([source](https://docs.langchain.com/langsmith/aws-self-hosted.md))

### Development Tools & Productivity

- [Agent Configurations](https://awesome-repositories.com/f/development-tools-productivity/version-management/agent-configurations.md) — The platform tracks configuration changes over time by creating new versions for every update and allowing users to promote or roll back to previous states. ([source](https://docs.langchain.com/langsmith/assistants.md))
- [Agentic Development Environments](https://awesome-repositories.com/f/development-tools-productivity/agentic-development-environments.md) — Provides a specialized CLI-based development environment for visualizing and testing agentic graphs locally. ([source](https://docs.langchain.com/langsmith/components.md))

### DevOps & Infrastructure

- [Agent Deployment Platforms](https://awesome-repositories.com/f/devops-infrastructure/agent-deployment-platforms.md) — Packages and hosts agentic applications in containerized environments with automated scaling and lifecycle management. ([source](https://docs.langchain.com/langsmith/deploy-google-adk.md))
- [Infrastructure Provisioning Tools](https://awesome-repositories.com/f/devops-infrastructure/cloud-infrastructure/infrastructure-provisioning-management/infrastructure-provisioning-tools.md) — Automates the deployment of containerized clusters, databases, and storage resources using pre-configured modules. ([source](https://docs.langchain.com/langsmith/aws-self-hosted.md))
- [Containerized Deployment Runtimes](https://awesome-repositories.com/f/devops-infrastructure/containerized-deployment-runtimes.md) — Packages agent logic into containerized runtimes for consistent execution across environments.
- [Deployment Management](https://awesome-repositories.com/f/devops-infrastructure/deployment-management.md) — Provides administrative controls to create, update, monitor, and remove application deployments. ([source](https://docs.langchain.com/api-reference/deployments-v2/get-deployment.md))
- [API Throttling](https://awesome-repositories.com/f/devops-infrastructure/api-throttling.md) — Enforces request limits on endpoints to maintain service stability and ensure fair usage. ([source](https://docs.langchain.com/langsmith/cloud.md))
- [Background Task Runners](https://awesome-repositories.com/f/devops-infrastructure/automation-orchestration/task-execution-frameworks/task-job-management/background-task-runners.md) — Provides asynchronous background task execution to handle complex operations without blocking the main application flow. ([source](https://docs.langchain.com/langsmith/background-run.md))
- [Assistant Registries](https://awesome-repositories.com/f/devops-infrastructure/configuration-management/file-based-configuration/managed-file-inventories/assistant-registries.md) — The platform retrieves a collection of configured assistants from the system to allow users to filter or browse the full inventory of available agents. ([source](https://docs.langchain.com/langsmith/agent-server-api/assistants/search-assistants.md))
- [Infrastructure Scaling](https://awesome-repositories.com/f/devops-infrastructure/infrastructure-scaling.md) — Adjusts active container counts based on CPU, memory, and task volume to maintain performance. ([source](https://docs.langchain.com/langsmith/data-plane.md))

### Part of an Awesome List

- [Agent Frameworks](https://awesome-repositories.com/f/awesome-lists/ai/agent-frameworks.md) — TypeScript implementation of the core framework for LLM application development.

### Security & Cryptography

- [Network and Infrastructure Security](https://awesome-repositories.com/f/security-cryptography/network-infrastructure-security.md) — Hardens infrastructure through private network connectivity, encryption at rest, and audit logging. ([source](https://docs.langchain.com/langsmith/aws-self-hosted.md))
- [Data Encryption](https://awesome-repositories.com/f/security-cryptography/data-encryption.md) — Secures stored checkpoints and application state by applying encryption at rest. ([source](https://docs.langchain.com/langsmith/data-storage-and-privacy.md))
- [Role-Based Access Control](https://awesome-repositories.com/f/security-cryptography/role-based-access-control.md) — Manages team collaboration and repository access through role-based permissions and workspace-level controls. ([source](https://docs.langchain.com/langsmith/context-engineering-concepts.md))
- [User Authentication Strategies](https://awesome-repositories.com/f/security-cryptography/user-authentication-strategies.md) — Validates user identity through external providers and SSO to manage secure sessions. ([source](https://docs.langchain.com/api-reference/auth-service-v2/oauth-setup-callback.md))

### Testing & Quality Assurance

- [Agent Testing Suites](https://awesome-repositories.com/f/testing-quality-assurance/software-testing/e2e-integration-testing/end-to-end-testing/agent-testing-suites.md) — Provides integrated unit, integration, and performance testing pipelines to ensure agent quality. ([source](https://docs.langchain.com/langsmith/cicd-pipeline-example.md))

### Networking & Communication

- [Event Subscriptions](https://awesome-repositories.com/f/networking-communication/communication-platforms-services/messaging-notification-systems/messaging-services/event-subscriptions.md) — Manages subscriptions to event feeds over persistent connections to receive real-time updates within threads. ([source](https://docs.langchain.com/langsmith/agent-server-api/streaming/protocol-v2-command.md))
- [Broker-Based Coordination](https://awesome-repositories.com/f/networking-communication/message-broker-consumers/consumer-group-managers/ephemeral-consumers/broker-based-coordination.md) — Facilitates coordination between server processes and background workers using message brokers. ([source](https://docs.langchain.com/langsmith/data-plane.md))

### Programming Languages & Runtimes

- [Thread Containers](https://awesome-repositories.com/f/programming-languages-runtimes/language-features-paradigms/concurrency-models/concurrency/execution-models/multi-threaded-execution/thread-containers.md) — Creates persistent containers for tracking the state and accumulated outputs of model invocation sequences. ([source](https://docs.langchain.com/langsmith/agent-server-api/threads/create-thread.md))

### Web Development

- [Event Streaming](https://awesome-repositories.com/f/web-development/event-streaming.md) — Exposes unified event-streaming APIs and WebSockets to provide granular updates and command workflows during agent execution. ([source](https://docs.langchain.com/langsmith/agent-server-api/streaming/protocol-v2-event-stream-sse.md))