{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"npm-langchainhub","slug":"langchainhub","name":"langchainhub","type":"framework","url":"https://www.npmjs.com/package/langchainhub","page_url":"https://unfragile.ai/langchainhub","categories":["frameworks-sdks"],"tags":[],"pricing":{"model":"open_source","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"npm-langchainhub__cap_0","uri":"capability://memory.knowledge.prompt.template.retrieval.from.hub","name":"prompt-template-retrieval-from-hub","description":"Fetches pre-built prompt templates from the LangChain Hub repository using a client-side API that resolves template identifiers (e.g., 'rlm/rag-prompt') to structured prompt objects. The client handles authentication via API keys, manages HTTP requests to the Hub's REST endpoints, and deserializes YAML/JSON template definitions into LangChain-compatible PromptTemplate instances with variable interpolation support.","intents":["I want to load a community-vetted prompt template without writing it from scratch","I need to version-control my prompts separately and reference them by identifier in my code","I want to share prompt templates across multiple projects via a central registry"],"best_for":["teams building LLM applications who want to reuse battle-tested prompts","developers prototyping RAG or chain-of-thought workflows quickly","organizations standardizing on prompt patterns across multiple agents"],"limitations":["Requires network connectivity to LangChain Hub — no offline template caching by default","Template discovery is identifier-based, not semantic search — you must know the exact template name or browse the Hub separately","No built-in versioning control for templates — always fetches the latest version unless pinned explicitly","Limited to templates published to the official Hub; private/custom template registries require custom client implementation"],"requires":["Node.js 14+ or Python 3.8+","LangChain Hub API key (free tier available)","Network access to https://api.smith.langchain.com or equivalent Hub endpoint"],"input_types":["string (template identifier, e.g., 'rlm/rag-prompt')","optional: version specifier or configuration overrides"],"output_types":["PromptTemplate object (LangChain native)","structured prompt with variable slots and formatting instructions"],"categories":["memory-knowledge","prompt-management"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-langchainhub__cap_1","uri":"capability://tool.use.integration.runnable.chain.retrieval.and.instantiation","name":"runnable-chain-retrieval-and-instantiation","description":"Loads serialized LangChain Runnable chains (agents, sequential pipelines, branching logic) from the Hub and instantiates them as executable Python/JavaScript objects. The client deserializes the chain's DAG structure, resolves LLM provider references (OpenAI, Anthropic, etc.), injects API keys from environment variables, and returns a ready-to-invoke Runnable that can be called with input data without additional configuration.","intents":["I want to deploy a pre-built agent or chain workflow without rewriting the orchestration logic","I need to load a complex multi-step chain that was designed and tested in LangSmith and run it in production","I want to swap LLM providers (e.g., OpenAI to Anthropic) by updating Hub configuration, not code"],"best_for":["teams using LangSmith for chain development and needing seamless deployment","developers building agent-as-a-service platforms with pluggable workflows","organizations running multiple LLM chains and wanting centralized configuration management"],"limitations":["Requires all LLM provider credentials to be available as environment variables — no in-memory credential injection API","Chain serialization format is LangChain-specific; migrating to other frameworks requires re-implementation","No built-in observability hooks — tracing and monitoring must be added separately via LangSmith integration","Deserialization can fail silently if Hub schema changes; no schema validation before instantiation"],"requires":["Node.js 14+ or Python 3.8+","LangChain library (matching version used to create the chain)","API keys for all LLM providers referenced in the chain (OpenAI, Anthropic, etc.)","LangChain Hub API key for authentication"],"input_types":["string (chain identifier, e.g., 'user/my-rag-chain')","optional: input dict/object matching the chain's expected schema"],"output_types":["Runnable object (LangChain native, callable)","execution result (text, structured data, or tool calls depending on chain definition)"],"categories":["tool-use-integration","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-langchainhub__cap_2","uri":"capability://tool.use.integration.hub.client.authentication.and.session.management","name":"hub-client-authentication-and-session-management","description":"Manages API authentication to the LangChain Hub using API keys stored in environment variables or passed explicitly to the client constructor. The client maintains a session with automatic header injection (Authorization: Bearer token), handles token refresh if needed, and provides error handling for 401/403 responses with clear messaging about missing or invalid credentials.","intents":["I want to authenticate once and make multiple requests to the Hub without re-passing credentials","I need to use different API keys for different environments (dev, staging, prod)","I want clear error messages when my Hub API key is missing or expired"],"best_for":["developers integrating Hub access into applications with environment-based configuration","teams managing multiple Hub accounts or API keys across environments","CI/CD pipelines needing secure credential injection without hardcoding"],"limitations":["No built-in token refresh mechanism — expired tokens require manual re-initialization","Credentials must be passed via environment variables or constructor; no support for credential files or external secret managers","No rate-limiting awareness — client does not track or warn about approaching rate limits","Single API key per client instance — no multi-tenant or key rotation support"],"requires":["Node.js 14+ or Python 3.8+","LangChain Hub API key (obtainable from https://smith.langchain.com)","Environment variable LANGCHAIN_API_KEY or explicit key parameter"],"input_types":["string (API key)","optional: custom Hub endpoint URL"],"output_types":["authenticated client instance (ready for subsequent API calls)"],"categories":["tool-use-integration","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-langchainhub__cap_3","uri":"capability://search.retrieval.hub.resource.listing.and.discovery","name":"hub-resource-listing-and-discovery","description":"Queries the LangChain Hub API to list available prompts, chains, and other resources with optional filtering by owner, type, or tags. The client returns paginated results as structured objects with metadata (name, description, owner, creation date), enabling programmatic discovery of Hub resources without manual browsing of the web interface.","intents":["I want to programmatically discover what prompts or chains are available in the Hub","I need to list all chains I've published to find a specific one by name or tag","I want to search for community-contributed templates matching a keyword or category"],"best_for":["developers building Hub explorers or CLI tools","teams auditing which prompts/chains are published to the Hub","applications needing dynamic template discovery without hardcoding identifiers"],"limitations":["Search is limited to exact name/owner matching or tag filtering — no full-text semantic search","Pagination is required for large result sets; no built-in automatic pagination","No filtering by resource type (prompt vs. chain) in some API versions — may require client-side filtering","Metadata returned is minimal; detailed resource content requires a separate fetch call"],"requires":["Node.js 14+ or Python 3.8+","LangChain Hub API key","Network access to Hub API"],"input_types":["optional: filter parameters (owner, type, tags, limit, offset)"],"output_types":["list of resource metadata objects (name, description, owner, URL, created_at, etc.)","pagination info (total count, next/previous page tokens)"],"categories":["search-retrieval","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-langchainhub__cap_4","uri":"capability://safety.moderation.prompt.and.chain.validation.against.hub.schema","name":"prompt-and-chain-validation-against-hub-schema","description":"Validates locally-defined prompts and chains against the LangChain Hub's serialization schema before pushing them to the Hub. The client checks for required fields, correct data types, valid variable references, and compatibility with supported LLM providers, returning detailed validation errors that guide users to fix issues before publication.","intents":["I want to validate my prompt template before publishing it to the Hub to avoid broken references","I need to ensure my chain's LLM provider configuration is compatible with the Hub","I want to catch schema mismatches early in my development workflow"],"best_for":["developers publishing prompts/chains to the Hub for the first time","teams with CI/CD pipelines that validate Hub artifacts before deployment","organizations maintaining strict quality standards for shared templates"],"limitations":["Validation is schema-only; does not test actual chain execution or LLM compatibility","Error messages may be generic or reference internal schema field names rather than user-friendly guidance","No support for custom validation rules — only built-in Hub schema validation","Validation happens client-side; server-side validation may still reject valid-looking artifacts"],"requires":["Node.js 14+ or Python 3.8+","LangChain library (for schema definitions)","locally-defined prompt or chain object"],"input_types":["PromptTemplate or Runnable object (LangChain native)","optional: schema version specifier"],"output_types":["validation result (pass/fail)","list of validation errors with field paths and suggested fixes"],"categories":["safety-moderation","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-langchainhub__cap_5","uri":"capability://automation.workflow.push.and.publish.artifacts.to.hub","name":"push-and-publish-artifacts-to-hub","description":"Publishes locally-created prompts, chains, and other artifacts to the LangChain Hub with metadata (name, description, tags, visibility). The client serializes LangChain objects to the Hub's format, handles multipart uploads if needed, manages versioning (creating new versions or updating existing ones), and returns a shareable Hub URL for the published resource.","intents":["I want to publish a prompt template I've refined so my team can reuse it","I need to update an existing Hub artifact with a new version","I want to share a chain workflow with the community and make it discoverable"],"best_for":["teams collaborating on prompt/chain development with Hub as a central registry","developers building reusable LLM components for open-source or internal use","organizations standardizing on shared prompt templates across projects"],"limitations":["Requires explicit versioning — no automatic semantic versioning or changelog generation","Published artifacts are immutable once created; updates require creating a new version","No built-in access control beyond public/private toggle — fine-grained permissions require Hub UI configuration","Large artifacts (chains with many steps) may hit upload size limits; no built-in compression or chunking"],"requires":["Node.js 14+ or Python 3.8+","LangChain Hub API key with publish permissions","locally-defined PromptTemplate or Runnable object","metadata (name, description, optional tags)"],"input_types":["PromptTemplate or Runnable object","metadata dict (name, description, tags, visibility: 'public'|'private')","optional: version string or changelog"],"output_types":["published resource URL (e.g., https://smith.langchain.com/hub/user/my-prompt)","resource identifier for future retrieval"],"categories":["automation-workflow","tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-langchainhub__cap_6","uri":"capability://data.processing.analysis.environment.variable.interpolation.in.templates","name":"environment-variable-interpolation-in-templates","description":"Automatically resolves environment variable references in retrieved prompts and chains (e.g., ${OPENAI_API_KEY}, ${MODEL_NAME}) by substituting values from the runtime environment. The client supports both simple variable substitution and nested references, with fallback defaults and validation that required variables are present before chain execution.","intents":["I want to load a Hub prompt that references environment variables without manually parsing and substituting them","I need to use different model names or API endpoints across dev/staging/prod by setting environment variables","I want to ensure all required environment variables are set before running a chain"],"best_for":["developers deploying chains across multiple environments with different configurations","teams using containerized deployments where environment variables are the standard config mechanism","applications needing to inject secrets (API keys, model names) without hardcoding"],"limitations":["Only supports environment variable substitution — no support for external config files or secret managers","No validation of variable values (e.g., checking if an API key is valid format) — only checks presence","Substitution is string-based; complex nested structures require manual post-processing","No built-in escaping for special characters in variable values"],"requires":["Node.js 14+ or Python 3.8+","environment variables set in the runtime environment (process.env or os.environ)","Hub artifact that includes variable references"],"input_types":["string template with ${VAR_NAME} references","optional: default values for missing variables"],"output_types":["string with variables substituted","validation errors if required variables are missing"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"npm-langchainhub__cap_7","uri":"capability://automation.workflow.langsmith.integration.for.chain.tracing","name":"langsmith-integration-for-chain-tracing","description":"Automatically enables tracing and observability for chains loaded from the Hub by injecting LangSmith callbacks into the Runnable execution context. The client detects when LangSmith credentials are available (LANGSMITH_API_KEY, LANGSMITH_PROJECT) and transparently logs all chain steps, LLM calls, and tool invocations to LangSmith for debugging and monitoring without requiring explicit callback configuration.","intents":["I want to automatically trace and debug a Hub chain in LangSmith without adding tracing code","I need to monitor production chain execution and see detailed step-by-step logs","I want to compare different chain versions' performance using LangSmith analytics"],"best_for":["teams using LangSmith for observability and wanting seamless Hub integration","developers debugging complex chains with many steps and tool calls","organizations running production LLM applications that need detailed execution logs"],"limitations":["Requires LangSmith credentials (API key and project name) to be set as environment variables","Tracing overhead adds latency to chain execution (~50-200ms per step depending on network)","No built-in sampling or filtering — all executions are traced, which can incur costs at scale","Tracing data is sent to LangSmith servers; no option for local-only tracing or custom backends"],"requires":["Node.js 14+ or Python 3.8+","LangSmith account and API key (LANGSMITH_API_KEY environment variable)","LANGSMITH_PROJECT environment variable set to desired project name","Network access to LangSmith API (https://api.smith.langchain.com)"],"input_types":["Hub chain identifier","optional: custom run name or metadata tags"],"output_types":["chain execution result (same as normal execution)","trace data automatically sent to LangSmith (visible in LangSmith UI)"],"categories":["automation-workflow","safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":32,"verified":false,"data_access_risk":"high","permissions":["Node.js 14+ or Python 3.8+","LangChain Hub API key (free tier available)","Network access to https://api.smith.langchain.com or equivalent Hub endpoint","LangChain library (matching version used to create the chain)","API keys for all LLM providers referenced in the chain (OpenAI, Anthropic, etc.)","LangChain Hub API key for authentication","LangChain Hub API key (obtainable from https://smith.langchain.com)","Environment variable LANGCHAIN_API_KEY or explicit key parameter","LangChain Hub API key","Network access to Hub API"],"failure_modes":["Requires network connectivity to LangChain Hub — no offline template caching by default","Template discovery is identifier-based, not semantic search — you must know the exact template name or browse the Hub separately","No built-in versioning control for templates — always fetches the latest version unless pinned explicitly","Limited to templates published to the official Hub; private/custom template registries require custom client implementation","Requires all LLM provider credentials to be available as environment variables — no in-memory credential injection API","Chain serialization format is LangChain-specific; migrating to other frameworks requires re-implementation","No built-in observability hooks — tracing and monitoring must be added separately via LangSmith integration","Deserialization can fail silently if Hub schema changes; no schema validation before instantiation","No built-in token refresh mechanism — expired tokens require manual re-initialization","Credentials must be passed via environment variables or constructor; no support for credential files or external secret managers","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.3391767589186521,"quality":0.26,"ecosystem":0.3,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.3,"quality":0.2,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:23.902Z","last_scraped_at":"2026-05-03T14:04:47.473Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":123236,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=langchainhub","compare_url":"https://unfragile.ai/compare?artifact=langchainhub"}},"signature":"FWYBRRcJoRoCPZfCK1NK9Ws3OhiYIuCYZGuQgZO4vKctE5G29UzVnOe3TA7xBzkDWRIQGHKULr+fAKvK6/niCQ==","signedAt":"2026-06-21T18:46:36.371Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/langchainhub","artifact":"https://unfragile.ai/langchainhub","verify":"https://unfragile.ai/api/v1/verify?slug=langchainhub","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}